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',[R!AL'"; OEPf\RTMF. Special Issue Promoting Family Economic and Nutrition Security Feature Articles 4 Maintaining Food and Nutrition Security: The Role of the Food Stamp Program and WIC P. Peter Basiotis, CarolS. Kramer-LeBlanc, and Eileen T Kennedy 17 Household Food Security in the United States in 1995: Results From the Food Security Measurement Project Margaret Andrews, Gary Bickel, and Steven Carlson 29 Do Child Support Awards Cover the Cost of Raising Children? MarkLino 41 Child Care and Welfare Reform MarkLino 49 Discussion Paper on Domestic Food Security CarolS. Kramer-LeBlanc and Kathryn McMurry, Editors Research Summaries 79 Regional Differences in Family Poverty 84 Work Schedules of Low-Educated American Women and Welfare Reform 86 Family Finances in the U.S.: Recent Evidence From the Survey of Consumer Finances Regular Items 90 Charts From Federal Data Sources 92 Research and Evaluation Activities in USDA 95 Cost of Food at Home UNITED STATES DEPARTMENT OF AGRICULTURE Volume 11, Numbers 1&2 1998 Dan Glickman, Secretary U.S. Department of Agriculture Shirley R. Watkins, Under Secretary Food, Nutrition, and Consumer Services Rajen Anand, Executive Director Center for Nutrition Policy and Promotion Carol S. Kramer-LeBlanc, Deputy Executive Director Center for Nutrition Policy and Promotion P. Peter Basiotis, Director Nutrition Policy and Analysis Staff TRIBUTE To Joan Courtless, Edit.or Family Economics and Nutrition Review 1986-1997 This issue is dedicated to Joan Courtless, who recently retired as editor of Family Economics and Nutrition Review. Joan was the editor of the journal from 1986 to 1997. As editor, she made many significant and positive contributions to the journal. She oversaw the transition from Family Economic.s Review to Family Economics and Nutrition Review, with its greater emphasis on matters of nutrition and nutrition policy. She gqided the journal in the direction of soliciting and reviewing externally authored articles. She herself authored numerous articles, many dealing with clothing issues, and she edited the 50th anniversary issue of the journal. Colleagues and readers associated with the journal will miss Joan and wish her the best. Editor-in-Chief Carol S. Kramer-LeBlanc Editor Julia M. Dinkins Special Features Editor Mark Uno Managing Editor Jane W. Fleming Family Economics and Nutrition Review is written and publis'hed each quarter by the Center for Nutrition Policy and Promotion, U.S. Department of Agriculture, Washington, DC. The Secretary of Agriculture has determined that publication of this periodical is necessary in the transaction of the public busiless required by law of the Department. This publication is not copyrighted. Contents may be reprinted without permission, but credit to Family Economics and Nutrition Review would be appreciated. Use of commercial or trade names does not imply approval or constitute endorsement by USDA. Family Economics and Nutrition Review is indexed in the following databases: AGRICOlA, Ageline, Economic Literature Index, ERIC, Family Studies, PAIS, and Sociological Abstracts. Family Economics and Nutrition Review is for sale by the Superintendent of Documents. Subscription price is $12.00 per year ($15.00 for foreign addresses). Send subscription orders and change of address to Superintendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250·7954. (See subscription form on p. 96.) Original manuscripts are accepted for publication. (See "guidelines for authors" on back inside cover). Suggestions or comments concerning this publication should be addressed to: Julia M. Dinkins, Ed~or, Family Economics and Nutrition Review, Center for Nutrition Policy and Promotion, USDA, 112020th St. NW, Suite 200 North Lobby, Washington, DC 20036. Phone (202) 606-4876. USDA prohibits discrimination in all its programs and activities on the basis of race, color, national origin, gender, religion, age, disability, political beliefs, sexual orientation, or marital or family status. (Not all prohibited bases apply to all programs.) Persons with disabilities who require ~lternative means for communication of program Information (Braille, large print, audiotape, etc.) should contact USDA's TARGET Center at (202) 720·2600 (voice and TDD). To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room 326-W, Whitten Building, 14th and Independence Avenue, SW, Washington, DC 20250·941 0 or call (202) 720-5964 (voice and TDD). USDA is an equal Opportunity provider and employer. Center for Nutrition Policy and Promotion PRop~n.'l"l .. ~ rrc~r Of LIBR4Rv ot.~c 4 ... 1998 UrullcrsJt, } 01 Nurn at Green h J Caratina Speciirq~ue Promoting Family Economic and Nutrition Security Feature Articles 4 Maintaining Food and Nutrition Security: The Role of the Food Stamp Program and WIC P. Peter Basiotis, CarolS. Kramer-LeBlanc, and Eileen T. Kennedy 17 Household Food Security in the United States in 1995: Results From the Food Security Measurement Project Margaret Andrews, Gary Bickel, and Steven Carlson 29 Do Child Support Awards Cover the Cost of Raising Children? Mark Lino 41 Child Care and Welfare Reform MarkLino 49 Discussion Paper on Domestic Food Security CarolS. Kramer-LeBlanc and Kathryn McMurry, Editors Research Summaries 79 84 86 Regional Differences in Family Poverty Work Schedules of Low-Educated American Women and Welfare Reform Family Finances in the U.S.: Recent Evidence From the Survey of Consumer Finances Regular Items 90 Charts From Federal Data Sources 92 Research and Evaluation Activities in USDA 95 Cost of Food at Home Volume 11, Numbers 1&2 1998 PROMOTING FAMILY ECONOMIC AND NUTRITION SECURITY Family Economics and Nutrition Review: Special Issue (Volume 11, Numbers 1&2) Introduction-Opportunities During an Era of Change CarolS. Kramer-LeBlanc In August 1996, the 1 04th Congress enacted and the President signed into law the Personal Responsibility and Work Opportunity Reconciliation Act. The legislation replaced Federal welfare payments under the Aid to Families With Dependent Children Program with a block grant program known as the Temporary Assistance for Needy Families Program (TANF). This program gives greater flexibility to States to set benefit levels, establish eligibility criteria, and determine the benefit blend. Welfare reform has altered more than 40 years of social welfare policy to move people from welfare to work and reduce the Federal budget deficit. New welfareto- work policies can influence significantly the wellbeing of over 30 million people in the United States. The challenge for all is to ensure that welfare reform works, and that both family economic security and food and nutrition security are maintained and enhanced as the United States approaches the year 2000. This special, double issue considers family economic and nutrition security. We are pleased to include some important articles that address significant aspects of this topic. Included are the following: 2 "Maintaining Food and Nutrition Security: The Role of the Food Stamp Program and WIC," by P. Peter Basiotis, CarolS. Kramer-LeBlanc, and Eileen T. Kennedy of the Center for Nutrition Policy and Promotion (Basiotis and Kramer-LeBlanc) and Research, Education, and Economics (Kennedy), respectively, USDA. This article examines the contribution of the Food Stamp Program (FSP) and The Special Supplemental Food Program for Women, Infants, and Children (WIC) to maintaining the nutrition security/diet quality of low-income participant households. This issue is important to examine in the context of recent welfare policy reforms that have emphasized moving people from welfare to work and have replaced the Federal Aid to Families With Dependent Children Program with the more limited State-administered Temporary Assistance to Needy Families Program. Federal food assistance programs were retained as a nutritional safety net, but in some cases, access and benefits have been restricted. The paper examines the hypothesis that participation in the FSP and/or WIC is an important factor in maintaining and improving the dietary quality of low-income households. Family Economics and Nutrition Review "Household Food Security in the United States in 1995: Results From the Food Security Measurement Project," by Margaret Andrews, Gary Bickel, and Steven Carlson, economists at the Office of Analysis and Evaluation of the Food and Nutrition Service, U.S. Department of Agriculture. This article reports important results from the landmark effort to measure food insecurity in the United States. Results have not been reported previously in a peer-reviewed journal and are of broad interest to the policy community. These results will contribute to the baseline against which progress in achieving food security in the United States will be measured. "Do Child Support Awards Cover the Cost of Raising Children?" by Mark Lino of the Center for Nutrition Policy and Promotion, USDA. Lino examines the adequacy of child support awards to single parents. Whereas welfare reform legislation has focused on child support payment enforcement to improve the well-being of children, Lino points out that awards need to assist single parents in meeting the costs of raising children. Comparing USDA estimates of expenditures on children with average full child support payments indicates that full payments only cover a small proportion of the total cost of raising children. 1998 Vol. 11 Nos. 1 &2 "Child Care and Welfare Reform," by Mark Lino of the Center for Nutrition Policy and Promotion, USDA. Lino reviews provisions of the Personal Responsibility and Work Opportunity Act affecting child care. Because the Welfare Reform Act establishes mandatory work requirements, sufficient quantity and quality of child care is crucial for the welfare of children and society and the success of welfare reform policy measures. In addition to the legislation, Lino reviews selected State child care initiatives. "Discussion Paper on Domestic Food Security," edited by CarolS. Kramer-LeBlanc and Kathryn McMuny for the Domestic Subgroup of the U.S. Interagency Working Group on Food Security. The Domestic Secretariat that developed this broadly reviewed discussion paper consists of the Center for Nutrition Policy and Promotion, USDA, and the Office of Disease Prevention and Health Promotion, HHS. We are including the discussion paper to make it available to as broad a readership as possible, and we believe it may be of particular interest to the readership ofFENR. The paper was developed in 1997-98 in response to the World Food Summit held in November 1996 in Rome that focused the world's attention on chronic problems of hunger and undernutrition internationally and in the United States. We at the Center for Nutrition Policy and Promotion and at the Family Economics and Nutrition Review are pleased to bring you this special issue. We welcome your comments, and we hope that you will send us your articles. I would like to thank our retired editor Joan C. Courtless for her years of service and welcome the new editor Julia M. Dinkins. 3 4 Maintaining Nutrition Security and Diet Quality: The Role of the Food Stamp Program and WIC P. Peter Basi otis USDA, Center for Nutrition Policy and Promotion Carol S. Kramer-LeBlanc USDA, Center for Nutrition Policy and Promotion Eileen T. Kennedy USDA, Research, Education, and Economics We examine the contribution of the Food Stamp Program (FSP) and the Special Supplemental Program for Women, Infants, and Children (WIC) to the nutrition security and diet quality of low-income participating households. This information can improve future monitoring of the effects of welfare policy reforms. Welfare reform has emphasized moving people from welfare to work and modifying or eliminating many former entitlement programs. However, after debate, Federal food assistance programs were retained as a nutritional safety net, although in some cases access and benefits were restricted. Using historical consumption data (CSFII 1989-91 ), we examine the hypothesis that participation in the FSP and/or WIC is an important factor in maintaining and improving the diet quality of low-income households. Using USDA's Healthy Eating Index (HEI), as an indicator of overall diet quality, and its 10 component indices, we estimate for the first time overall diet quality effects of changes in FSP and WIC participation and benefit levels. (The HEI permits us to examine diet quality as nutritionists see it-with some foods consumed too little and others too much.) Results suggest that both programs contribute significantly to maintaining and improving the nutritional well-being of lowincome households, considering both quantity and quality of diet oomponents. We believe the implication is that these food assistance programs help low-income households achieve nutrition security-including improved diet quality-and that their support provides a critical safety net to accompany welfare reform. Family Economics and Nutrition Review ITJ o examine relationships between diet quality and food program participation, we use USDA's 1989-91 Continuing Survey of Food Intakes by Individuals (CSFII) to analyze how the diet quality of low-income households is affected by participation in the Food Stamp Program (FSP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). The measure of diet quality used is the USDA Healthy Eating Index (HEI), developed to assess the overall quality of individuals' diets, defined as the de gree of adherence to Federal nutritional guidance ( 12,22). The Index consists of 10 equally weighted components that reflect how well individual diets conform to both the 1995 Dietary Guidelines for Americans (26) and the USDA Food Guide Pyramid (25) recommendations. Use of this index permits us to ex amine changes in diet quality associated with program benefits that may involve consuming less of particular dietary components and more of others. For the first time, this article reports how responsive the HEI and its individual components are to participation in the FSP and WIC. To provide a context for the analysis that follows, we briefly describe the FSP and WIC within the framework of Federal food assistance. We then mention pertinent elements of welfare reform and food assistance program changes to indicate how legislative provisions may affect food assistance program participants. We present methods and results and discuss implications. 1998 Vol. 11 Nos. 1 &2 Overview and Background on Food Programs and Welfare Reform Context The United States has a longstanding commitment to supporting food and nutrition security. Fourteen domestic food assistance programs comprise the formal Federal food and nutrition safety net and provide low-income consumers with foods, or with expanded means to purchase food products, along with nutrition information and education (table 1, p. 6). Among the "modern" Federal programs that began in 1945 with the National School Lunch Program and, 53 years later, have grown to provide about $37 billion annually (23 ), FSP and WIC are arguably the most significant in terms of benefits transferred and nutritional vulnerability of recipients, respectively. Advocates of the food assistance programs contend that they improve participants' diet quality and ameliorate public health. Despite welfare reform in late 1996, the structure of the Federal food programs was essentially preserved. However, FSP eligibility criteria and benefit levels were severely curtailed for some key groups-including legal immigrants and able-bodied adults without dependents-and results of this analysis raise concerns about the potential, negative effects on diet quality of affected groups when, or if, access to these two important food and nutrition programs is reduced. The FSP, an entitlement program, is the main food security program for lowincome households and provides coupons or electronic benefit cards to enhance recipients' food purchasing power and nutritional status. By FY 1996, the FSP provided $24.3 billion in benefits to an average of 10 million households and 25.5 million individuals. In FY 1996, the average monthly benefit received was more than $73 per person and more than $172 per household (24). Over 80 percent of Food Stamp households contain either a child, elder, or disabled person, and 42 percent are single-parent households (24). WIC is targeted to pregnant and postpartum (including breast-feeding) mothers, infants, and children up to 5 years of age at nutritional risk and serves more than 7 million people each month at an annual program cost of about $3.7 billion. WIC provides a combination of services including nutrient-dense food packages, nutrition counseling, and access to health services. Approximately 45 percent of all infants and 25 percent of all pregnant women in the United States participate in the WIC Program ( 11 ). The value of the average 1995 WIC food package was $43.12 per month, and the average monthly infant food package was $73.74 (24). The most common foods included in the WIC packages are milk, cheese, infant formula, cereal for adults and infants, juice, peanut butter, dried beans, and eggs. In 1992, a WIC Farmers' Market Nutrition Program was created to provide additional coupons to WIC participants, which can be used to purchase fresh fruits and vegetables in farmers' markets. This is a relatively minor share of the WIC Program, constituting only about $7 million of the $3.7 billion total WIC benefits. 5 Table 1. Federal food assistance programs Year FY 1996 budget FY 1996 Program name begun (in millions) Participation National School Lunch Program 1945 $4,313 24,050,000 bunches per day Special Milk Program 1955 $16.8 144,246,000 total served Food Stamp Program 1961 pilot $24,330 25,540,000 recipients 1974 permanent per month Nutrition Program for the Elderly 1965 $150 245,979,000 total meals School Breakfast Program 1966 pilot $1,118 6,103,000 daily average 1975 permanent breakfasts served Summer Food Service Program 1968 $258 2,216,000 daily average attendance (July) Commodity Supplemental Food Program 1968 $100.2 357,000 average participation Special Supplemental Program for Women, Infants, 1972 pilot $3,730 Average participation and Children (WIC) 1974 permanent 1,648,000 (women) 1,827,000 (infants) 3,712,000 (children) Child and Adult Care Food Program 1975 pilot $1,553 2,343,000 August average 1978 permanent 1,546,171,000 total 1989 adults meals served Food Distribution Program on Indian Reservations 1977 $70 120,000 average The Emergency Food Assistance Program 1981 $44 40,899,000 total pounds distributed Nutrition Assistance Program for Puerto Rico 1981 $1,153 Not available Homeless Children Program 1989 $3 Not available WIC Farmers Market Nutrition Program 1992 $7 742,000 Federal (of WIC total) 364,000 Non-Federal Source: U.S. Department of Agriculture, Food and Nutrition SeTllice. 1998. Administrative data. 6 Family Economics and Nutrition Review The FSP and the WIC Program share some commonalities. Each transfers benefits to low-income individuals to enhance food consumption and diet quality. As an entitlement program, the FSP conveys food purchasing power to any low-income individual who meets eligibility criteria (based on means testing). Food purchases are relatively unrestricted. Nutrition education is a much smaller component of the FSP than of the WIC Program. By contrast, the WIC Program is not an entitlement program but targets specific priority subgroups ofthe low-income population as funds are appropriated. WIC provides vouchers for purchase of one of seven food baskets selected to be nutrientdense and to supply specific nutrients deficient in the diets of the target participants. Unlike the FSP, WIC includes individual nutrition counseling along with a referral to other subsidized health services. Evaluations of the effects of the two programs suggest generally that they have been successful. Food consumption surveys show that diets of the poor improved markedly between 1965-66 and 1977-78, a period marked by nationwide expansion of the FSP (5). Numerous studies have shown that the FSP has succeeded in transferring purchasing power to low-income consumers and has increased food expenditures and nutrient availability relative to the transfer of cash benefits ( 3, 7, 14,15 ). 1998 Vol. 11 Nos. 1&2 Seventeen studies summarized by Fraker and cited by Rossi yielded estimates that out of each food stamp dollar, between $0.17 and $0.49 was spent on home-consumed food ("best estimate, $0.30") compared with only $0.05 to $0.10 of each dollar of cash benefits transferred. Fraker found that food stamp participation significantly increased the household availability of calcium, vitamin C, and iron. Far fewer studies have demonstrated the link between program participation, individual intake data, and improved nutritional status. WIC Program evaluations from the inception have demonstrated WIC effectiveness in increasing birth weight, decreasing incidence of low birth weight and prematurity, improving hematological status, and/or improving nutrient intake (11,18,19). Recent welfare reform includes replacement of Federal welfare payments with block grants to States (Temporary Assistance for Needy Families Program, or T ANF), welfare time limits and caps, and State discretion among benefit types, levels, and eligibility standards. States are encouraged to promote work and move recipients from welfare to work. Legal immigrants were made ineligible for Federal T ANF benefits. Major food assistance program changes passed in 1996 included reductions in food stamp benefits for able-bodied adults without dependents and elimination of Federal food stamps for most legal immigrants. (The President's 1998 Budget restores some immigrant FSP benefits.) In the welfare reform context, if lost food assistance and welfare benefits are replaced by increased earnings or other income, then net effects on dietary status may be more modest. If, however, food and welfare assistance losses are not offset, effects found here are likely to be illustrative. Methodology We use the Healthy Eating Index developed by the USDA Center for Nutrition Policy and Promotion as the indicator of individual and household overall diet quality. Based on the 1995 Dietary Guidelines for Americans and the Food Guide Pyramid (FGP), this index almost alone focuses on the consumption of foods rather than nutrients. Few indices focusing on the total diet exist ( 1 ,2, 17,21) and most of these-with the exception of Patterson et al.-focus exclusively on consumption of nutrients. The Healthy Eating Index has 10 equally weighted components, each based on different aspects of a healthful diet. The score of each component ranges between zero and 10 and the overall index, from zero to 100. The components can be grouped in terms of those that relate to adequacy or sufficiency, to moderation, and to variety in the diet. Specifically, Components 1 through 5 measure the degree to which a person's diet contains adequate servings of the 5 major food groups depicted in the FGP: Grains, vegetables, fruits, milk, and meats. Components 6 through 9 measure how well recommendations to moderate fat, saturated fat, sodium, and cholesterol are met. Component 6 is based on total fat consumption as a percentage of total food energy intake; component 7 is based on saturated fat consumption as a percentage of total food energy intake; component 8 is based on cholesterol intake; and component 9 is based on sodium intake. Finally, component 10 reflects the amount of variety in a person's diet. The HEI does not set overall limits on food energy consumed. 7 An individual's score in any of the food group components is based on the proportion of the recommended number of servings consumed for a given energy intake level. For instance, the average energy allowance for a 40-year-old female is 2,200 kilocalories, and the FGP indicates that at this energy level, 4 servings of vegetables per day are recommended. If a 40-year-old female consumes the recommended number of servings, she receives the maximum score of 10 in the vegetable category. A person who consumes the recommended number of servings from any food group receives a maximum component score of 10. A person consuming no servings from a food group receives the minimum score of zero. Between zero and 10, the component score is calculated proportionately; for example, a person needing 6 servings from the grain category who consumed only half that many would achieve a score of 5. Food serving amounts were computed from food consumption data using factors derived from the serving size assumptions given in the FGP. Calculation of scores for all food group (adequacy) components followed this procedure with actual servings compared with recommended servings based on the FGP. In each food group, once the maximum recommended number of servings is achieved, neither further credit nor penalties are awarded for additional servings consumed. Components 6 to 9 measure moderation in the diet and are scored differently. Component 6 reflects how well total fat is limited in the diet: A score of 10 8 means total fat intake as a proportion of energy intake is 30 percent or Jess. The score declines to zero when this proportion reaches 45 percent. Between these two points, the scores decline proportionately. The score for saturated fat (component 7) is computed analogously to that for total fat, with a maximum score achieved at a ratio of less than 10 percent of energy from saturated fat and zero when the ratio is 15 percent or greater. The component scores for cholesterol and sodium are each based on milligrams consumed. Cutoff points for a perfect score of I 0 are set at 300 mg for cholesterol and 2,400 mg for sodium. The corresponding zero points are 450 mg and 4,800 mg for cholesterol and sodium, respectively. Finally, the Dietary Guidelines, as well as the National Academy of Sciences' Diet and Health Report ( 16), stress the importance of variety in the diet to help ensure that people get the nutrients they need. To assess variety, counting the total number of different foods eaten by an individual that contribute substantially to meeting one or more of the 5 food group requirements is necessary. Foods consumed were counted only if they amounted to at least one-half serving in any one food group. Identical food items eaten on separate occasions are summed before imposing the onehalf serving cut-off. Similar foods such as two different forms of potatoes or two different forms of white bread count only once in the variety category. Mixtures are decomposed into constituent parts, meaning that a single food mixture (such as lasagna) could contribute 2 or more points to the variety index (contributing to both grain and meat, for example). In the variety category, a person attains a score of 10 if 16 or more different foods are eaten over a 3-day period. If 6 or fewer distinct foods are eaten over a 3-day period, the individual earns zero. Here again, little guidance was available to suggest upper or lower limits in scoring variety; similar to categories 6 to 9, the limits for variety were derived by exploration of the consumption data and consultation with researchers. For a more detailed description of the construction of the HEI, see Kennedy et al. or U.S. Department of Agriculture ( 12,22). Data Data used in this study were collected in USDA's Continuing Survey of Food Intakes by Individuals (CSFII) 1989-91. The CSFII provides ongoing data on food and nutrient consumption with a yearly sample of about 2,000 households containing about 5,000 individuals. In CSFII 1989-91, 3 days offood and nutrient intake data (a 1-day recall followed by a 2-day diary) were obtained along with relevant demographic, economic, and Federal food program participation data. Food and nutrient consumption data from a separate lowincome sample were also collected at the same time. The survey design was such that each year's data are nationally representative and can be used independently; however, the combined years provide a larger sample size. The lowincome sample can be combined with the all-income sample through the use of survey weights. These survey weights Family Economics and Nutrition Review also adjust the survey sample to be representative of the U.S. population living in households. This analysis uses lowincome households with complete data records in the combined 1989-90 sample (N=1,438); the HEI was not available for 1991. Low-income households were those with annual income of 130 percent or less of the poverty threshold. There were 418 households participating in the FSP at the time of the survey. Of those, 359 had every household member authorized to receive food stamps. The remaining 59 FSP households with one or more members not authorized to receive food stamps were excluded from the analysis so as not to confound the relationships because of possible lea~ge of benefits (i.e, use of food purchased with food stamps by nonauthorized household members). This resulted in a final sample size of 1,379 households. Statistical Model A set of 11 reduced form equations was estimated including one HEI equation and one equation each for the 10 component dietary scores. This Ad Hoc reduced form specification was guided by household production theory (6) and previous studies of food and nutrient consumption in order to estimate net effects of the independent variables on the HEI and its components (2,10,13). Because the household is the unit of analysis in this study, each household member's HEI and component scores are totaled. These aggregated scores are the dependent variables. Independent variables are annual household income as a percentage of the poverty threshold; participation in the FSP; the weekly dollar value of food stamps received; participation by one or more household 1998 Vol. 11 Nos. 1 &2 members in the WIC Program; household size in Thrifty Food Plan Male Adult Equivalents (TFP MAEs);1 headship status; the higher grade of formal schooling completed by either head of household; race; ethnic origin; geographic region and urbanization; and tenancy status. The number of household members who did not provide 3 days of dietary intake data, and thus lacked an HEI and component scores, was entered in the regression equation as an additional control. Because the HEI is, by construction, equal to the sum of its components, the 10 component equations' estimated coefficients were restricted to sum to the corresponding estimated coefficient of the HEI equation. This specification results in a potential gain in statistical efficiency. Restricted Ordinary Least Squares was used to estimate the models (9) and the SYSLIN procedure of the Statistical Analysis System (20) performed the estimation. Results Results include the means for the dependent and independent variables and the estimated regression coefficients as shown in table 2. The means are further subdivided by Food Stamp Program participation status. All means are weighted to represent population means of low-income households, and within those, of food stamp and nonfood stamp participating households. Means of the dependent variables are per person and are shown directly under the dependent variable name row. 1To account for the households' varying age/sex compositions, a "Thrifty Food Plan Male Adult Equivalent Scale" was constructed by dividing each household member's maximum allotment given by the Thrifty Food Plan by that of a male 20 to 50 years of age. Then, the household size in TFP MAEs was constructed by summing over all household members. ... the value of food stamps received exerts a positive and statistically significant effect on vegetables, dairy, meat, and sodium component scores .... [and] participation in the WIC program ... has a very strong positive effect on aggregate household diet quality .... 9 Table 2. Weighted means and regression coefficients estimating relationships between household-level Healthy Eating Index and its components by food stamp receiving households and value of food stamps received and WIC participation controlling for other relevant variables, CSFII1989-90 Mean All FSP NFSP N=l,379 N=359 N=l,020 HEI Grains Vegetables Mean for All 62.18* 5.95 5.66 Mean forFSP 60.70 5.86 5.29 Mean for NFSP 62.74 5.99 5.79 Intercept -12.69 -1.85 -0.06 0.00** 0.05 0.95 Income as percent of poverty threshold 81.89 65.71 87.93 -0.01 0.00 O.Ql 0.63 0.74 0.18 Food stamp participating household 0.27 1.00 -3.86 -0.28 -0.49 0.03 0.59 0.42 Weekly value of food stamps received 9.30 34.22 0.22 0.00 O.Q3 0.00 0.95 0.02 Household member participates in WIC 0.08 0.19 0.05 23.45 4.20 1.19 0.00 0.00 0.06 Household size in TFP MAEs 2.13 2.29 2.07 73.00 8.27 6.08 0.00 0.00 0.00 Dual-headed household 0.34 0.20 0.39 1.12 -1.30 1.66 0.54 0.01 0.01 Female-headed household 0.53 0.71 0.46 10.67 -0.19 0.92 0.00 0.67 0.07 Highest grade completed 10.59 10.16 10.76 0.81 0.04 0.00 0.00 0.39 0.97 African American 0.23 0.33 0.19 -5.16 -0.54 -0.65 0.00 0.15 0.12 Other race 0.06 0.08 0.06 -4.16 -0.29 0.25 0.05 0.64 0.73 Hispanic ethnic origin 0.11 0.11 0.11 4.11 -0.34 -0.81 0.01 0.47 0.13 Midwest 0.26 0.24 0.27 -2.50 0.11 -0.64 0.13 0.82 0.24 South 0.42 0.39 0.44 -5.20 -0.21 -0.56 0.00 0.63 0.28 West 0.18 0.13 0.20 -0.69 -0.24 -1.31 0.69 0.63 0.02 Suburbs 0.31 0.26 0.33 -0.64 -0.11 0.02 0.59 0.76 0.95 Nonmetro 0.28 0.25 0.30 -4.46 0.30 0.01 0.00 0.39 0.99 Household rents dwelling 0.55 0.77 0.47 -0.07 0.23 0.02 0.95 0.48 0.96 Occupies dwelling without payment 0.04 0.02 0.05 1.52 0.78 -0.04 0.54 0.28 0.96 Number with no HEI 0.43 0.55 0.39 -59.70 -6.54 -5.22 Adjusted R2 0.00 0.00 0.00 0.90 0.81 0.66 *Dependent variable means are per person with 3-day dietary intake data. **Numbers below estimated regression coefficients are prob values. 10 Family Economics and Nutrition Review Total Saturated Fruit Dairy Meat fat fat Cholesterol Sodium Variety 3.60 6.21 7.19 6.31 5.15 8.33 7.86 5.92 3.23 6.47 7.21 6.33 4.67 8.21 7.86 5.56 3.74 6.12 7.18 6.31 5.33 8.38 7.86 6.05 -3.18 -1.48 -1.62 0.12 2.70 -2.92 0.60 -5.00 0.02 0.24 0.09 0.93 0.06 0.02 0.60 0.00 0.01 0.00 0.00 -0.01 -0.01 0.00 -0.01 0.01 0.30 0.76 0.70 0.16 0.19 0.57 0.35 0.28 -0.06 0.32 -0.42 -0.38 -0.95 -0.65 -0.72 -0.23 0.94 0.65 0.43 0.58 0.24 0.37 0.26 0.74 -0.01 0.04 0.05 0.02 0.02 0.02 O.D3 0.02 0.73 0.03 0.00 0.35 0.45 0.23 0.03 0.30 2.79 3.35 2.25 2.33 -0.33 2.49 3.09 2.09 0.00 0.00 0.00 0.00 0.70 0.00 0.00 0.01 4.18 8.01 8.53 7.53 5.18 9.41 8.23 7.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.39 -1.10 0.41 -0.07 0.87 0.49 0.56 -0.02 0.61 0.12 0.45 0.92 0.29 0.50 0.38 0.98 1.63 -0.63 -0.40 1.11 0.96 3.04 3.39 0.84 0.01 0.29 0.38 0.06 0.16 0.00 0.00 0.16 0.19 0.22 0.05 0.04 -0.02 0.18 -0.18 0.30 0.00 0.00 0.34 0.48 0.78 0.00 0.00 0.00 -0.40 -2.70 1.06 -0.28 0.61 -0.96 -0.72 -0.57 0.45 0.00 0.01 0.56 0.28 0.06 0.11 0.26 -0.81 -3.26 -0.23 0.39 1.25 -0.91 0.64 -1.19 0.36 0.00 0.72 0.63 0.19 0.29 0.39 0.16 -0.59 -1.78 2.55 2.18 2.72 -0.08 0.18 0.08 0.38 0.01 0.00 0.00 0.00 0.90 0.75 0.90 -0.13 0.41 -0.45 -1.76 -1.79 0.84 0.81 0.12 0.85 0.52 0.35 0.01 0.01 0.20 0.16 0.86 -1.86 -1.43 0.37 -0.93 -0.41 0.23 0.59 -0.98 0.00 0.02 0.42 0.12 0.55 0.71 0.28 0.10 1.10 -0.37 -0.98 -0.74 -0.86 0.05 2.25 0.40 0.13 0.58 0.06 0.26 0.27 0.94 0.00 0.56 1.09 -0.15 -0.32 0.05 -0.84 -0.03 -0.18 -0.18 O.D3 0.75 0.36 0.92 0.12 0.95 0.67 0.71 0.03 -1.27 0.16 -0.15 -0.15 -2.08 -1.26 -0.05 0.96 0.01 0.66 0.75 0.78 0.00 0.00 0.92 -0.30 0.16 0.78 -0.08 -0.68 -0.16 -0.04 0.00 0.52 0.71 0.02 0.85 0.17 0.72 0.91 1.00 0.37 -0.08 0.22 1.01 0.61 -0.60 -1.17 0.44 0.72 0.93 0.77 0.29 0.58 0.54 0.18 0.65 -3.65 -6.65 -7.15 -6.25 -4.46 -7.17 -6.27 -6.35 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.35 0.70 0.83 0.68 0.43 0.74 0.74 0.67 1998 Vol. 11 Nos. 1&2 11 The average low-income household in the United States had a household-level HEI of 62.18. Food stamp households have slightly lower means at 60.70, whereas nonparticipant households are slightly higher at 62.74. With regard to components, the lowest overall component score is for fruits (3.60 of 10), and the best component score is for cholesterol (8.33). Food stamp households have lower mean component scores than do low-income nonfood stamp households for all components except dairy, meat, and fat. Food stamp households have lower mean component scores for fruit (they eat too few servings) and for saturated fats (they receive an excessive percentage of calories from saturated fats). These correspond to the highest and lowest values for the general population ( 12). Sample means for the independent variables help characterize the groups. The means of the dummy (zero-1) variables reflect the proportion of the population with a particular characteristic, for example, the proportion of female-headed food stamp households is 71 percent, compared with 53 percent of all lowincome households and 46 percent of nonfood stamp households. The mean income of food stamp households expressed as percent of the poverty threshold was substantially less than nonfood stamp low-income households (65.71 percent versus 87.93 percent). The average household size in TFP MAEs was 2.13, with food stamp participating households slightly larger at 2.29 than nonfood stamp households, at 2.07. The proportion of food stamp households with at least one member participating in the WIC program is 19 percent. Food stamp households receive food stamps valued at $34.22 per week, on average. 12 Regression results for the 11 equations are also shown in table 2. Unlike the means, these regression results are not weighted, since many of the variables used to construct survey weights are included in the equations ( 8). Estimated regression coefficients are shown for each independent variable for each of the 11 diet quality measures. The level of statistical significance (prob-value) of each estimated regression coefficient is shown directly underneath the coefficient. Interestingly, regression results indicate that the estimated effect of household income on the diet quality of the sample households was not significant at conventional levels of statistical significance. Recall that average household income as a percent of the poverty threshold for food stamp receiving households was 65 .71, substantially lower than that of the nonfood stamp households (87.93). The estimated coefficient on the food stamp participation variable is interpreted as the effect on the level of the dependent variable (HEI or HEI component) that a food stamp participating household (27 percent of households) with value of food stamp benefits equal to zero would have, other things equal. The estimated coefficient on the food stamp participation variable is negative for the HEI and all components but dairy. However, it is only significant for the HEI at the 0.03 level of statistical significance. By contrast, the value of food stamps received has a substantial and statistically significant effect on overall diet quality, controlling for other relevant factors. For each additional dollar of food stamps received, the aggregate household HEI score increases by an estimated 0.22 points. At the average weekly food stamp value of $34.22, the aggregate household HEI increases 7.5 points, on average. However, since food stamp households "start" at an HEI about 3.86 points lower than similarly situated nonfood stamp households, the net effect of food stamp participation on aggregate household HEI is about 3.7 points,2 on average. Not surprisingly, the positive nutritional effect of food stamp participation is larger for higher levels of food stamps, but lower for lesser food stamp benefit values. A break-even point is estimated at $17.54 per week. That is to say, when weekly household food stamp benefits are at least $17.54, food stamp participants demonstrate superior diet quality to similarly situated nonprogram participants. At a food stamp value of ($3.86/.22) $17.54 per week or lower, food stamp participants have diet quality inferior to nonparticipants. Thirty-two percent of Food Stamp Program participating households received food stamps valued at less than $17.54 per week. With regard to the HEI components, the value of food stamps received exerts a positive and statistically significant effect on vegetables, dairy, meat, and sodium component scores. Turning to WIC, results suggest that participation in the WIC program by one or more household members has a very strong positive effect on aggregate household diet quality measures, controlling for other factors. WIC participation alone contributes 23.45 points to the aggregate household HEI score 2The estimated coefficient of 3.86 is significant at the 0.03 level of statistical significance. However, given that no adjustments for survey design effects were made in estimating standard errors of the coefficients, it could be statistically insignificant. In fact, when the HEI equation is estimated independently from those of its components, the estimated coefficient on the food stamp value remains at 0.22 points and is significant, but the food stamp participation dummy variable coefficient is not significant. Family Economics and Nutrition Review (controlling for household size among other variables). This overall effect is distributed about evenly in all diet quality components except for vegetables and saturated fat, where the estimated coefficients are not statistically significant. The possibility that WIC participation may improve household scores for some diet components not included in the WIC food package, for example, fruits3 and possibly vegetables, is interesting and may be explained in several ways. One is that consumption of the WIC food package (by those for whom it was intended, and possibly their families) improves diet quality scores for the types of foods that it includes, for example, dairy products and grains, as well as frees up food stamps and money income to purchase more of all foods for the household. Another, more general, explanation is that households that participate in the WIC Program are more health and nutrition oriented than are other households, including households receiving only food stamps. Finally, the nutrition education received as part of participation in the WIC Program is likely to improve diet quality through better diet-related behaviors. Only a minority (34 percent) of lowincome households was dual-headed, with food stamp participating households less likely to have both male and female heads (20 percent) than were nonparticipating low-income households (39 percent). Seventy-one percent of food stamp households were headed by a female head only, compared with 46 percent for nonfood stamp households and 53 percent for all low-income households. Compared with female- 3 The exception is fruit juice, which is included in WIC packages. 1998 Vol. 11 Nos. 1 &2 headed households, dual-headed households have lower grains scores and higher vegetable scores, on average. Female-headed households have much higher HEI, cholesterol and sodium scores, and somewhat higher fruit and total fat scores than comparable maleheaded households. The mean highest grade of formal schooling completed by the household head was 10.59 years. Food stamp and nonfood stamp households differed little in average years of education. Regression results show that years of education has a positive and statistically significant effect on overall diet quality. Every additional grade completed increases the household HEI score by 0.81 points. Years of education has a small positive effect on fruit, dairy, and cholesterol scores, and a small negative impact on the sodium score. Thirty-three percent of the food stampreceiving households were African American, 8 percent were of other race, and the remaining 59 percent were White. The corresponding figures for nonfood stamp households were 19 percent African American, 6 percent other, and 75 percent White. African American households have, on average, a lower household HEI by 5.16 points than comparable White households. They also have lower dairy and higher meat scores than White households. Race does not appear to have significant effects on most of the diet quality component measures. Hispanic households, at 11 percent of households, have substantially higher HEI scores than non-Hispanic households (4.11 points). They have higher total fat and saturated fat scores, but lower dairy scores than non-Hispanic households. Geographic location and urbanization status have few statistically significant effects on the HEI and its components. Households in the Midwest (24 percent of food stamp and 27 percent of nonfood stamp households) have poorer total fat and saturated fat scores than those in the East. Households in the South (39 percent of food stamp and 44 percent of nonfood stamp households) have lower fruit and dairy scores than those in the East. Households in the Western United States (13 percent of food stamp and 20 percent of nonfood stamp households) have lower vegetable and higher sodium scores than similar households in the Eastern region of the United States. Households in the suburbs (26 percent of food stamp and 33 percent of nonfood stamp households) have better fruit scores, while households in nonrnetro areas (25 percent of food stamp and 30 percent of nonfood stamp households) have lower HEI, dairy, cholesterol, and sodium scores than similar households in the central city. Tenancy status has no significant effects on HEI or its components scores. The only exception is for households that rent their dwelling (77 percent of food stamp and 47 percent of nonfood stamp households), which have a better meat score, compared with those households that own their dwelling. As expected, the control variable for the number of household members with no computable HEI score has an extremely strong and statistically significant negative association with the total HEI score and its components. This control variable is also responsible for the relatively high R-squared values. 13 Limitations Severallintitations are relevant when interpreting the results. First, our study is exploratory; however, household production theory and past analyses of the demand for foods or nutrients guided model specification and the selection of variables (8). Thus, the possibility of comntitting gross errors is reduced. Several problems remain, however. A major limitation is that the Restricted Ordinary Least Squares reduced form specification is used as opposed to a system of simultaneous equations reflecting the usual derived demands for inputs in the household production function, the household production function itself, and the final demand for health and healthy eating. The range of the dependent variables is constructed between zero and 100 for the HEI and zero and 10 for its components, which may imply the usual estimation problems with linear probability models (9). Because an HEI is not computed for children below the age of 2 years and for infants, they are necessarily excluded from the household aggregates of the dependent variables. This could distort results, to some extent. We did not explicitly account for the survey's clustered design effects on statistical hypothesis testing. Thus, estimated "prob" values between 0.05 and around 0.01 could result in either acceptance or rejection of the null hypothesis, if tested to account for design effects. As several variables of potential importance in influencing "healthy eating" are not available (for example, taste of particular foods, the present value of future health outcomes, etc.) and, as there may be self-selection relative to 14 the FSP or WIC participation, the results may well suffer from specification biases. 4 Despite these limitations, this study provides valuable new insights into the relationship between food assistance program participation and diet quality. Summary and Conclusions In this study, we estimated a statistical model using the USDA Healthy Eating Index and its 10 components at the household level as dependent variables to better understand the effects of food assistance program (FSP and WIC) participation and food stamp benefit levels on the diet quality of low-income households (controlling for intervening factors). Independent variables included relevant socioeconomic variables available in the CSFII. As is typical of such studies, selection of independent variables was heavily influenced by their availability. The interpretation of their estimated coefficients can vary substantially depending on the theoretical model the researcher believes is most appropriate for the task at hand. Here, we were broadly guided by well-known household production theory and past research in selection of variables. A novel contribution to the literature is that the HEI and its components aggregated to the household level were the dependent variables. Thus, effects of FSP and WIC participation on a household level measure of the overall diet and, at the same time, its components, could be estimated. "Typically, in situations such as this, a statistical correction for self-selection bias is performed. However, the procedure requires identification of variables that are highly correlated with the decision to participate in the program but not with diet quality. In practice, such variables are not readily available (see reference 4). Results tend to be in general agreement with previous studies of diets that were based on components of the total diet, mostly nutrient intakes. These results reaffirm the effectiveness of two of the main food assistance programs, the FSP and the WIC in meeting nutritional needs of low-income households, needs that may continue after welfare reform. On average, the estimated effect of Food Stamp Program participation on the overall diet of participating households is positive. The effect increases with increased value of food stamps received, as intended. In terms of its effect on HEI components, the Food Stamp Program had statistically significant and positive effects on the consumption of vegetables, dairy, and meat products, as well as on sodium component scores. Assuming that ablebodied adults without dependents or immigrants have sintilar HEI and component consumption responses to food stamp income, removal from the Food Stamp Program would result in a reduction in these scores, unless food stamp income is replaced by earned or other income. Participation in the WIC Program by household members improved household level HEI scores dramatically. In addition, WIC participation resulted in improved scores for all HEI components except for saturated fat. Positive effects reflect the value and increased availability of in-kind foods found in the WIC food package coupled with beneficial effects of the nutrition education component of the WIC Program. Family Economics and Nutrition Review References 1. Abdel-Ghany, M. 1978. Evaluation of household diets by index of nutritional quality. Journal of Nutrition Education 10(2):79-81. 2. Basiotis, P.P., Guthrie, J.F., Bowman, S.A., and Welsh, S.O. 1995. Construction and evaluation of a Diet Status Index. Family Economics and Nutrition Review 8(2):2-13. 3. Basiotis, P.P., Johnson, S.R., Morgan, K.J., and Chen, J.-S.A. 1987. Food stamps, food costs, nutrient availability, and nutrient intake. Journal of Policy Modeling 9:383-404. 4. Burtless, G. 1995. The case for randomized field trials in economic and policy research. Journal of Economic Perspectives 9(2):63-84. 5. Cronin, F.J. 1980 (Spring). Nutrient levels and food used by households, 1977 and 1965. Family Economics Review, pp. 10-15. 6. Deaton, A. and Muellbauer, J. 1980. Economics and Consumer Behavior. Cambridge University Press, New York. 7. Devaney, B., Haines, P., and Moffitt, R. 1989. Assessing the Dietary Effects of the Food Stamp Program-Volumes I and II. U.S. Department of Agriculture, Food and Nutrition Service, Alexandria, VA. 8. DuMouchel, W.H. And Duncan, G.J. 1983. Using sample survey weights in multiple regression analyses of stratified samples. Journal of the American Statistical Association 78( 383 ):535-543. 9. Fomby, T.B., Hill, C.R., and Johnson, S.R. 1984. Advanced Econometric Methods. Springer-Verlag, New York. 10. Fraker, T.M. 1990. The Effects of Food Stamps on Food Consumption: A Review of the Literature. U.S. Department of Agriculture, Food and Nutrition Service, Alexandria, VA. 11. Kennedy, E. T. 1997. Intervention strategies for undernutrition. In F. Bronner (Ed.), Strategies for Improving Undernutrition (Chapter 6). Spring Press, Hartford. 12. Kennedy, E.T., Ohls, J., Carlson, S., and Fleming, K. 1995. The Healthy Eating Index: Design and applications. Journal of the American Dietetic Association 95(10). 13. Kramer-LeBlanc, C.S., Kennedy, E.T., and Basiotis, P.P. 1997. Food expenditure and nutritional implications of the Personal Responsibility and Work Opportunity and Reconciliation Act of 1996. American Journal of Agricultural Economics 79(4):105-112. 1998 Vol. 11 Nos. 1 &2 15 16 14. Levedahl, J.W. 1995 (November). A theoretical and empirical evaluation of the functional forms used to estimate the food expenditure equation of food stamp recipients. American Journal of Agricultural Economics, Vol. 77. 15. Morgan, K.J. 1986. Socioeconomic factors affecting dietary status: An appraisal. American Journal of Agricultural Economics 68(5): 1240-1246. 16. National Academy of Sciences, National Research Council, Food and Nutrition Board. 1989. Diet and Health: Implications for Reducing Chronic Disease Risk. National Academy Press, Washington, DC. 17. Patterson, R.E., Haines, P.S., and Popkin, B.M. 1994. Diet quality index: Capturing a multidimensional behavior. Journal of the American Dietetic Association 94(1):57-64. 18. Rose, D., Habicht, J-P., and Devaney, B. 1998. Household participation in the Food Stamp and WIC Programs increases the nutrient intakes of preschool children. Journal of Nutrition 128:548-555. 19. Rossi, P.H. 1996. Feeding the poor: Five Federal nutrition programs; food stamps, WIC, school lunch, school breakfast, and child care. Report submitted to The American Enterprise Institute. Social and Demographic Research Institute, University of Massachusetts, Amherst, MA. 20. SAS User's Manual, Version 6. SAS Institute, Research Triangle Park, NC. 21. Sorenson, A.W., Wyse, B.W., Wittwer, A.J., and Hansen, R.G. 1976. An index of nutritional quality for a balanced diet. Journal of the American Dietetic Association 68:236-242. 22. U.S. Department of Agriculture, Center for Nutrition Policy and Promotion. 1995. The Healthy Eating Index. Report No. CNPP-1. 23. U.S. Department of Agriculture, Food and Nutrition Service. 1998. Administrative data. 24. U.S. Department of Agriculture, Food and Nutrition Service, Office of Analysis and Evaluation. 1996, July. Administrative data, "FY 1995 WIC Food Package Cost Analysis Estimated Average Monthly Food Package Cost for Participants in Dollars." 25. U.S. Department of Agriculture, Human Nutrition Information Service. 1992. The Food Guide Pyramid. Home and Garden Bulletin No. 252. 26. U.S. Department of Agriculture and U.S. Department of Health and Human Services. 1995. Nutrition and Your Health: Dietary Guidelines for Americans. Home and Garden Bulletin No. 232. Family Economics and Nutrition Review 1998 Vol. 11 Nos. 1&2· Household Food Security in the United States in 1995: Results From the Food Security Measurement Project Margaret Andrews Gary Bickel Steven Carlson Office of Analysis and Evaluation Food and Nutrition Service U.S. Department of Agriculture The need for a reliable measure of U.S. hunger and food insecurity has been recognized since the early 1980's. This paper describes the development of such a measure and presents initial findings from data collected for USDA by the Census Bureau. A unidimensional scale of severity, based on survey responses, was used to identify food security status; household weights were then applied to estimate the prevalence of food insecurity and hunger in three designated severity ranges. The large majority of American households (88 percent) were food secure in the year ending April 1995. Hunger was evident in 4.1 percent of all households. The paper concludes with a discussion of future nutrition monitoring and research directions for food security measurement. espite the recent economic recovery that has lowered unemployment and poverty rates in the United States, many American families still struggle to meet basic needs. This was the context for Vice President Gore's announcement in September 1997 at the National Summit on Food Recovery and Gleaning of new U.S. Department of Agriculture (USDA) estimates of the extent of food insecurity and hunger in U.S. households. Based on a state-of-the-art measurement method developed through a broad collaborative effort, the new estimates indicate that nearly 12 million households experienced food insecurity in the 12 months prior to April1995, while one or more persons i~ about 4 million of these food-insecure households experienced hunger due to resource constraints during the period. Although efforts to estimate the level of hunger in the United States have been made previously (7,10,28,31,33), the new USDA estimates are the first based 17 upon specially designed data collected from a large, nationally representative sample and subsequently validated to show strong statistical properties of internal validity and reliability. The new estimates thus represent the first reliable, standard national measure of food insecurity and hunger for the United States. The availability of a standard national measure of hunger and food insecurity provides a powerful tool for monitoring changes in the food situation of U.S. households. It may be particularly useful in tracking the effectiveness of the Federal Government's efforts through food assistance and food recovery programs to help ensure that all Americans are able to obtain adequate food. In a time of tight Federal budgets and with welfare reform shifting increased responsibility for social welfare to the States, this monitoring function is especially important. This paper provides a brief introduction to the genesis of the new measure, including its conceptual basis and methodology, presents brief summary findings from the baseline estimates for 1995, and discusses implications of the measure for future research on family nutritional and general well-being. Background Federal interest in developing a hunger measure can be traced from at least 1984 when the President's Task Force on Food Assistance recognized the distinction between the concept of hunger in the traditional medical usage and a more socially oriented, common-sense meaning. The report noted: "To many people hunger means not just symptoms that can be diagnosed by a physician, it 18 bespeaks the existence of a social, not a medical, problem: a situation in which someone cannot obtain an adequate amount of food, even if the shortage is not prolonged enough to cause health problems" (23 ). The Task Force also noted the absence of any reliable measure of hunger in this latter commonly understood meaning and the resulting inability of policymakers to verify or negate claims of increasing hunger. This lack of an accepted standard measure of hunger prevalence was cited by the Task Force as posing a continuing policy conundrum. After the 1984 Task Force report, State and local researchers increased efforts to develop soundly based survey measures (22). The Food Research and Action Center sponsored and obtained major funding for the Community Childhood Hunger Identification Project (CCHIP) ( 12,30-32) and researchers at the Cornell University Division of Nutritional Sciences sought to develop independent hunger scales (8,25,26). At the Federal level, USDA began the process, in the mid 1980's, of analyzing the significance of the single survey question on the adequacy of household food supplies that had been added to its regular national food consumption surveys beginning in 1977 but had not been analyzed in depth ( 4,11 ). A similar household food sufficiency question and several others adapted from the CCHIP instrument were included in the Third National Health and Nutrition Examination Survey sponsored by the National Center for Health Statistics (NCHS) ( 1,6). Finally, the Federal Government's commitment to develop a standardized measure of food insecurity or food insufficiency for the United States took definitive shape in 1990-92 when USDA's Food and Nutrition Service (FNS)1 and NCHS were assigned joint responsibility to carry out this task under the Ten-Year Comprehensive Plan for the National Nutrition Monitoring and Related Research Program (NNMRRP) Act of 1990. FNS took lead responsibility for developing the measures; it established an Interagency Working Group for Food Security Measurement to maintain a collaborative process for the project. As a key part of its conceptual basis, the project adopted the authoritative definitions of food insecurity and hunger developed by a special expert panel convened by the American Institute of Nutrition (AIN) and reported by the Life Sciences Research Office of the Federation of American Societies for Experimental Biology ( 3 ). According to these definitions, food insecurity occurs when a household does not have access to enough food, at all times, for an active, healthy life. Hunger, defined as "the painful or uneasy sensation that results from not having enough food" is a potential but not necessary consequence of food insecurity. 2 1 FNS was renamed Food and Consumer Service (FCS) in 1994 in the context of broader USDA agency reorganizations. The original name was restored in December 1997. 2For a description of the conceptual basis of the Government's measure, including its debt to the body of prior research and an extensive bibliography of the literature to that point, see reference 5. For further discussion of this conceptual basis and its operationalized form and testing in the Government's new measure, see references 14, 15, and 24. For recent validation studies and related work within the same general approach, see references 2, 13, 16-18, and 21. Family Economics and Nutrition Review Methods The subsequent operational development of the hunger and food security measure was also a broad-based, cooperative venture. At an early stage, FNS enlisted the expertise of the Census Bureau for developing and administering a national food security questionnaire. In January 1994, FNS and NCHS jointly sponsored a Conference on Food Security Measurement and Research, bringing together a wide range of experts in the field. Participants discussed their previous experiences with measuring hunger and food insecurity and then organized into working groups to provide continuing advice and critique to FNS in developing a baseline draft questionnaire (29 ). In the next stage, the Census Bureau worked closely with FNS and its collaborators to analyze, field test, and refine the food security questionnaire. The draft version from the research conference was revised after review by an expert panel convened by the Census Bureau's Center for Survey Methods Research. The questionnaire was field tested and analyzed in the autumn of 1994 (27) and, with some further revision, was administered for the first time as a Supplement to the Current Population Survey (CPS) in April1995. With minor revisions, the food security supplement was administered with the CPS again in September 1996 and April 1997. The data collection in April 1995 produced some 45,000 usable interviews. In September 1995, FNS contracted with Abt Associates, Inc. (Abt) to analyze these data in a cooperative venture with FNS staff and other researchers involved in developing the questionnaire. From the beginning, 1998 Vol. 11 Nos. 1&2 FNS expected the analysis to produce a scaled measure of food insecurity and hunger that would allow the government to identify households experiencing problems providing adequate food for all members.3The Abt team was selected because it had developed an innovative analysis design that applied state-of-theart scaling methods that were used most widely in the educational testing industry. (See reference 15 for technical details of the scale estimation.) The initial Abt procedure used standard factor analysis techniques to perform a systematic set of exploratory analyses of the 1995 survey results. The preliminary work found that, with one important area of exception, most of the food security indicators in the questionnaire fit a single-dimensional measurement scale. A few items failed to meet the rigorous fit criteria for inclusion and were dropped from the scale. However, one general type of indicator also did not fit the single-dimensional measure of severity of food insecurity: those items dealing with the coping strategies that a food-insecure or at-risk household might engage in to improve its food supply from emergency sources (e.g., getting food from a food bank or borrowing money for food). This is understandable given that all households do not face the same set of choices for coping with an inadequate food supply. 3The choice of household-level as opposed to family-level unit of analysis was due in part to the sampling frame of the Current Population Survey; it also reflects the objective of developing a comprehensive measure encompassing the entire U.S. residential population. In the March 1995 CPS sample, 70 percent of households were family households including two or more persons residing together and related by birth, marriage, or adoption; 20 percent were single-person households; and 5 percent consisted of two or more unrelated persons residing together. ... food insecurity occurs when a household does not have access to enough food, at all times, for an active, healthy life. Hunger, defined as "the painful or uneasy sensation that results from not having enough food" is a potential but not necessary consequence of food insecurity. 19 Once it was established that a core set of food security and hunger items could be scaled along a single dimension, subsequent analyses used the Rasch model, conceptually the most basic form within the general class of item-response-theory (IRT) statistical scaling models. Initially the Rasch model was applied to a subset of the sample including only households with children. The resulting scale was subjected to further analyses that showed it to be robust for other household types as well. Various reliability indicators were calculated and found to be within accepted ranges.4 Item response stability measures for individual items on the scale and for the overall scale were judged to be acceptable by the Census Bureau using data from some 1,100 quality control re-interviews that were performed in the week following the regular Apri11995 CPS interviews (20).5 4 A general discussion of potential sources of error in the food security measure is presented in the Summary Report volume ( 14). More extensive tteatment is provided in the Technical Report ( 15). Based on three traditional measures of reliability (Speannan-Brown's and Rulon's split-half reliability estimates and Cronbach's alpha), the estimated reliability values ranged from .86 to .93 for the 12- month measurement scale. Since the distribution of household scale scores is highly skewed (56.5 percent of sample households passing the income and food security screener had zero score), a further dichotomized split-halftest was conducted, collapsing the split-half scales into the dichotomous variable "answered all questions negatively" and "answered one or more questions affirmatively." On this test, the level of agreement between paired subscales was 84.8 percent for households with children and 85.8 percent for households without children, while the corresponding kappa statistic (showing the extent of agreement beyond mere chance) was .70 and .69 for the respective household types. 20 Table 1. Sequenced items and food security status categories for food security measurement scale Sequenced questions in scale Q53 Worried food would run out Q55 Unable to afford balanced meals Q58 Child fed few low-cost foods Q24 Adult cut size or skipped meals Q56 Couldn't feed child balanced meals eat less than felt Food security status Food secure Food insecure Adult cut size or skipped meals, 3+ months Child not eating enough Food insecure with moderate hunger Adult hungry but didn't eat The 18 items included in the scale are shown in abbreviated form in table 1 with their original question numbering. The scale items are ordered according to increasing levels of severity. The least severe items (Q53 and Q54) ask whether the household respondent has 5Jn this analysis of response variance, 17 percent of the continuous variables and 9 percent of the categorical questions with enough cases to be analyzed exhibited "low" variance, 75 percent and 68 percent respectively showed "moderate" variance, and 8 percent and 24 percent showed "high" variance. Thus, 76 to 92 percent of the two question types exhibited "low to moderate" response variance while the food insecurity scale overall showed "moderate" response variance. The authors noted, "(t]his distribution is typical of response variance results for households surveys" (20 ). worried about or experienced a situation within the past 12 months where food was running out, and there was no money to buy more. Subsequent items indicating experiences or perceptions of inadequate food intake in terms of both quality and quantity (Q32, Q55, Q56, Q57, Q58) fall in the low to intermediate ranges of severity measured by the scale. Items dealing with reduced food intakes and hunger for adults (Q24, Q25, Q35, Q38) fall in the intermediate range of severity measured, and those indicating reduced food intakes and hunger for children in the household (Q40, Q43, Q44, Q47, Q50) or more severe hunger for adults (Q28, Q29) fall at the severe end of the scale. All items refer to the 12-month Family Economics and Nutrition RevieW period preceding April1995, and all ask respondents to report only experiences, perceptions, or behaviors that result from a lack of financial resources. Thus, instances of hunger or meals skipped due to dieting, illness, or busy schedules are excluded by design. Each household in the sample received a scale score between zero and 10 under the Rasch measurement model, based on its particular pattern of responses to all 18 items. These detailed household scores indicate the distinct levels of severity of food insecurity experienced by U.S. households across the full range of severity captured by the measure. The scaled measure provides much greater detail about the nature and extent of this poverty-linked phenomenon than ever before available. However, the very detail of the nearly continuous severity measure makes it inappropriate to serve, in itself, as a useful measure of the prevalence of food insecurity and hunger. For this purpose, several well-defined, broad subranges of severity level need to be designated and a simpler, categorical measure created based on these specified severity ranges. To provide this second type of measure, FNS worked with Abt and other collaborators to develop a categorical measure that would classify the food security status of households in terms of several broad subranges of the measured severity levels indicated by their scale scores ( 15 ). The four designated status categories are illustrated in table 1. Households with complete responses to all 18 items were classified as food secure if the respondent answered affirmatively to fewer than 3 of the 18 questions on the 1998 Vol. JJ Nos. 1 &2 scale,6 while those with 3 or more positive responses were assigned to one of the food-insecure groups. Those with 3 to 7 positive answers were classified as food insecure without evident hunger, those with 8 to 12 as food insecure with moderate hunger, and those with 13 or more as food insecure with severe hunger. Locating the initial threshold (scale cutpoint) of each designated severity-range category was done by identifying the second or third item in sequence indicative of the salient conditions characterizing the category.7 It should be noted that the main role of the categorical measure is to provide an established, consistent basis for comparison of food insecurity and hunger prevalence over time and across population subgroups. In this sense, the exact placement of the category boundaries (scale-score cutpoints, in operational terms) is a matter primarily of identifying severity-range categories that have relevance to ongoing program objectives and policy discussion. In a deeper sense, locating the category boundaries or thresholds is a matter of identifying the 6.Two groups of households were classified as food secure on the basis of zero scale scores: higher income households (~185 percent poverty) that were screened from the food security portion of the interview on the basis of consistent negative responses to three broad food security screening questions, and both high- and low-income households that passed the screener but then gave no affirmliive response to any food security scale item. 7.ln contrast to the underlying scale estimation, which is fully detennined by the measurement model and the data, locating the designated category thresholds involved judgment as to how many indications of a given severity subrange should be present and across how broad a range of measured severity they should be observed. ... food insecurity is more prevalent among Black and Hispanic households (almost twice the levels for Whites), households with children, households under the poverty level, and households in central city metropolitan areas. 21 important distinctions (conceptual and in reality) between the several subranges of severity level encompassed within the full range of food insecurity observed for contemporary U.S. households.8 The sequenced pattern of items on the scale reflects the underlying commonality among otherwise diverse households of the conditions and experience of food insufficiency in relation to basic need and the available set of potential household responses to such conditionswhat Radimer termed "hunger as a managed process." In measurement terms, this predominant sequential response pattern means that the typical household answering positively to any given scale item will also have answered affirmatively to all less severe items. For the entire CPS sample, 76 percent of households exhibited this common ordering of responses and were termed the "modal group" of households. While not all the April 1995 respondents followed this common ordering pattern perfectly, most of the non-modal households did not diverge very far from the common pattern. 9 8The names applied to the designated severity level subranges, or food insecurity status categories, are nominal only and intended to reflect U.S. social reality as articulated; for example, in the 1984 President's Task Force Report on Food Assistance. Clearly, the names chosen for relevance to the U.S. context are not intended to suggest, and do not reflect, the much deeper severity ranges of food insecurity and hunger that are relevant to underdeveloped countries subject to famine conditions. In principle, the form of measurement scale developed from contemporary U.S. data could be extended, with a similar data set collected in poorer countries, to encompass the deeper levels of food insecurity and hunger severity experienced in those circumstances within the same unidimensional measurement construct. For a similar food-security scale developed for urban subsistence dwellers in Kampala, Uganda, see reference 19. 22 Figure 1. Item response patterns for food security status groups 053 055 054 058 024 032 057 038 028 029 044 056 025 035 040 047 043 050 Fl* - Food Insecure The response patterns for the four food security status groups are illustrated in figure 1 where the questions in the scale are ordered sequentially and the proportion of affirmative responses to each item within each status group is projected onto the vertical axis. Overall, the response pattern shows the expected contrast among the food security status groups. 90f those households with at least one positive response to a scale item, the proportion following the modal pattern was only 32 percent for households with children and 48 percent for households without children. Nonetheless, the fit statistics produced in estimating the Rasch model indicate an acceptable degree of conformance of their responses to the modal pattern. Detailed analysis of the non-modal response patterns is one of the areas of research now opened up and expected to be fruitful in helping identify constellations of conditions and behaviors occurring in highly stressed household settings. Findings By classifying survey responses according to food security status and applying household weights provided by the Census Bureau, Abt used the supplement data to estimate the prevalence of food insecurity and hunger within the specified severity range categories in the United States for the 12 months preceding the April 1995 survey. As can be seen in figure 2, the large majority of American households (88 percent) were found to be food secure in the year ending April 1995. About 11 .9 million (of approximately 100 million) households experienced food insecurity as a consequence of limited resources during that period. Family Economics and Nutrition Review Figure 2. Distribution of U.S. Households, by food security status level, 1995 Table 2 shows that household food insecurity is more prevalent among Black andHispanic households (almost twice the levels for Whites), households with children, households under the poverty level, and households in central city metropolitan areas. D Food secure II Food insecure - No hunger evident • Food insecure - Moderate hunger • Food insecure - Severe hunger The number of households where hunger due to inadequate resources 88.1 o/o was experienced during the period can Most of the food-insecure households were food insecure without hunger (7.78 million households), meaning that they reported experiencing concerns about the adequacy of their food supply, substituted cheaper food items, and reduced the quality and variety of their diets, but without significantly reducing food intakes. There were 3.34 million households classified as food insecure with moderate hunger, where some reduction in food intake due to inadequate household resources was evident for one or more household members, Primarily adults. 1998 Vol. 11 Nos. 1&2 be estimated by combining the number of households assigned to the two most severe levels of food insecurity. This yields an overall estimate of 4.16 million households where one or more members 0.8o/o experienced some level of hunger in the 12-month period preceding the April1995 3.3% survey. An additional 817,000 households were identified as food insecure with severe hunger. In these households, reductions in food intake were observed for both children and adults, and one or more of the adults was likely to have experienced an extensive reduction in food intake (i.e., going whole days without food) du e to m. ad e quate resources. 10 10-For the modal household group, children's hunger indicators appear only within the severe hunger range of household level food insecurity measured by the scale. Among the non-modal households, however, children's hunger may appear within other food insecure categories as well. Analysis of the CPS data is continuing to identify the extent of such cases. The number of individuals affected by hunger is not easily extrapolated from these estimates. Because the data were collected in a household survey, homeless individuals are not included. Furthermore, for many households (i.e., those with more than one adult or with more than one child), the structure of the questionnaire does not allow accurate determination of the food security status of each adult or each child in the household. An upper bound for the number of individuals affected by hunger is given by the total population of persons living in those households that were classified into either of the two hunger categories. From the Apri11995 survey, this number is 11.2 million individuals, most of them adults. For most of the food insecure households with children (and for all such households fitting the modal response pattern), the children are not likely to be seriously affected unless the household has reached the overall severity level required to classify it as experiencing food insecurity 23 Table 2. Prevalence of household food security status, by selected characteristics, 1995 Food insecure- Food insecure- Food insecure- Characteristics Food secure without hunger moderate hunger severe hunger Number Percent Number Percent Number Percent Number Percent All households 88,266 88.1 7,783.4 7.8 3,343.3 3.3 816.8 0.8 Household composition Household with children under age 18 31,434 82.5 4,676.2 12.3 1,670.6 4.4 331.9 0.9 Household with elderly but no children 26,155 94.1 1,124.1 4.0 436.2 1.6 89.9 0.3 Household with no children or elderly 30,677 89.5 1,983.1 5.8 1,236.4 3.6 394.9 1.2 Race/ethnicity White 76,129 90.0 5,653.7 6.7 2,298.1 2.7 534.0 0.6 Black 9,104 75.8 1,779.4 14.8 895.4 7.5 233.8 1.9 Other 3,032 84.6 350.6 9.8 150.1 4.2 49.4 1.4 Hispanic1 5,725 74.3 1,360.2 17.7 501.0 6.5 115.6 1.5 I ncome-to-poverty rati.O 2 Under 0.50 3,240 58.4 1,365.0 24.6 688.4 12.1 270.9 4.9 Under 1.00 10,230 64.7 3,500.7 22.1 1,587.6 10.0 489.5 3.1 Under 1.30 14,841 68.1 4,367.9 20.0 2,032.7 9.3 567.7 2.6 Under 1.85 25,914 73.8 5,952.6 17.0 2,568.0 7.3 680.4 1.9 Over 1.85 62,352 95.8 1,830.8 2.8 775.3 1.2 136.3 0.2 Area of residence Central city metropolitan area 20,172 83.9 2,494.4 10.4 1,102.5 4.6 286.5 1.2 Other metropolitan area 33,115 90.5 2,244.3 6.1 976.4 2.7 265.8 0.7 Nonrnetropolitan area 20,007 88.0 1,906.2 8.0 802.8 3.4 161.2 0.7 Census geographic region Northeast 17,443 89.7 1,335.6 6.9 524.6 2.7 142.6 0.7 Midwest 21,113 89.4 1,614.6 6.8 743.9 3.2 150.9 0.6 South 31,311 87.5 2,959.2 8.3 1,244.6 3.5 285.5 0.8 West 18,399 86.2 1,874.0 8.8 830.3 3.9 237.7 1.1 1 Persons of Hispanic ethnicity can be of any race. 2Income and poverty status refer to household income in a recent 12-month period, varying among rotation groups in the CPS sample. 24 Family Economics and Nutrition RevieW with severe hunger. Thus, a preliminary estimate for the number of children who experienced hunger during the period is given by the number of children living in households classified into the severe hunger category .11 This preliminary approximation indicates that 692,000 children were living in households where severe hunger was experienced in the 12 months prior to the April 1995 survey. (Further information on household and individual estimates can be found in reference 14.) Discussion The development of the food security and hunger measures as described here provides the baseline from which the Government can improve its capacity to monitor the food adequacy of U.S. households. As such, the true importance of the estimates can only be known in the future, when consistent comparisons can be made over time against the baseline numbers. To the extent possible, the new measures are being implemented at the national level by all Federal agencies cooperating in the National Nutrition Monitoring and Related Research Program. USDA plans to continue annual collection of the basic household data needed to replicate the baseline hunger and food security measures through regular supplements to the Current Population Survey. The core set of survey questions needed to liThe estimate is approximate and preliminary for two reasons. First, as noted, the number of children living in households classified to the severe hunger category provides only an upper bound to the number of children experiencing hunger within that category of households. Second, an undetennined number of children living in some of the (non-modal) households classified to the moderate hunger category also experience hunger, but are excluded from the Preliminary approximation. 1998 Vol. 11 Nos. 1 &2 estimate the scaled measures are planned for inclusion in the Fourth National Health and Nutrition Examination Survey (NHANES-IV) and the next round of USDA's Continuing Survey of Food Intakes by Individuals (CSFII), scheduled to be merged with NHANES-IV beginning in the year 2000. The Centers for Disease Control and Prevention, Division of Nutrition (CDC), NCHS, and FNS are working together to test subscales of the 18-item scale that can be used to measure food insecurity and hunger in State surveillance systems such as NCHS's State and Local Area Integrated Telephone Survey and CDC's Pediatric Nutrition Surveillance System. Food security modules are also planned for the Census Bureau's Survey of Program Dynamics to be fielded for 5 consecutive years beginning in 1998 and the Early Childhood Longitudinal Study being conducted by the U.S. Department of Education, National Center for Educational Statistics. The University of Michigan Panel Survey of Income Dynamics included the food security module in a special supplement on women and children in 1997, and this module is being considered for implementation. FNS has collected food security and household food-use data in a national sample of low-income households. As these data emerge, researchers will begin to expand beyond the basic monitoring function to explore the causation and consequences of household food insecurity and hunger across the various levels of severity at which they are experienced and measured. Aside from their incorporation in various research settings and the Government's use in nutrition monitoring, the new measures will provide a baseline for assessing food assistance program performance under the requirements of the Government Performance and Results Act. Specifically, USDA has proposed using the number of households experiencing poverty-linked hunger as a performance measure for assessing the extent to which the agency is succeeding in its goal to enhance food and nutrition security for low-income Americans. Finally, ongoing food security and hunger measures will provide a direct measure of unmet need, which may prove useful for researchers interested in exploring alternative measures of material deprivation. While the Census Bureau's annual estimate of the number of households living below the poverty line has been the standard measure of the extent of material deprivation, the poverty measure has been criticized as increasingly inadequate for this task (9). Future explorations of the relationship of food security and hunger measures to other social and economic indicators of basic needs and resources may be fruitful in this area. Acknowledgments Andrews and Bickel were members of the Office of Analysis and Evaluation's food-security measurement team under the direction of Carlson at the time this work was performed. Other members included Sharron Cristofar and Bruce Klein. Andrews is currently employed by the Economic Research Service, USDA. 25 26 References 1. Alaimo, K. and Briefel, R.R. 1994, July. National estimates of food insufficiency, NHANES III, 1988-91. Presented at the 27th Annual Meeting of the Society of Nutrition Education, Portland, OR. 2. Alaimo, K., Briefel, R.R. , Frongillo, Jr., E.A., and Olson, C.M. 1998. Food insufficiency exists in the United States: Results from the Third National Health and Nutrition Examination Survey (NHANES III). American Journal of Public Health 88:419-426. 3. Anderson, S.A. (Ed.). 1990. Core Indicators of nutritional state for difficult-tosample populations. Journal of Nutrition 120 (11 S): 1557-1600. 4. Basiotis, P.P. 1992. Validity of self-reported food sufficiency status item in the U.S. Department of Agriculture's food consumption surveys. In V.A. Haldeman (Ed.), American Council on Consumer Interests 381h Annual Conference: The Proceedings. Columbia, MO. 5. Bickel, G.W., Andrews, M.S., and Klein, B.W. 1996, January. Measuring food security in the United States: A supplement to the CPS. In D. Hall and M. Stavrianos (Eds.), Nutrition and Food Security in the Food Stamp Program. U.S. Department of Agriculture, Food and Consumer Service, Alexandria, VA. 6. Briefel, R.R. and Woteki, C. E. 1992. Development of food sufficiency questions for the Third National Health and Nutrition Examination Survey. Journal of Nutrition Education 24 (Suppl.):24S-28S. 7. Brown, J.L. 1987. Hunger in the United States. Scientific American 256:36-41. 8. Campbell, C.C. 1991. Food insecurity: A nutritional outcome or a predictor variable? Journal of Nutrition 121:408-415. 9. Citro, C.F. and Michael, R. (Eds.). 1995. Measuring Poverty: A New Approach. Summary and Recommendations. National Academy Press, Washington, DC. 10. Cook, J.T. and Brown, J.L. 1992. Estimating the number of hungry Americans. Working paper, Tufts University Center on Hunger, Poverty, and Nutrition Policy. Tufts School of Nutrition Science and Policy, Medford, MA. 11. Cristofar, S. and Basiotis, P.P. 1992. Dietary intakes and selected characteristics of women 19-50 years and their children ages 1-5 years by reported perception of food sufficiency. Journal of Nutrition Education 24:53-58. Family Economics and Nutrition RevieW 12. Food Research and Action Center (FRAC). 1983. How to Document Hunger in Your Community. Washington, DC. 13. Frongillo, Jr., E.A., Rauschenbach, B.S., Olson, C.M., Kendall, A., and Colmenares, A. G. 1997. Questionnaire-based measures are valid for the identification of rural households with hunger and food insecurity. Journal of Nutrition 127:699-705. 14. Hamilton, W.L., Cook, J.T., Thompson, W.W., Buron, L.F., Frongillo, Jr., E.A., Olson, C.M., and Wehler, C.A. 1997, September. Household Food Security in the United States in 1995: Summary Report of the Food Security Measurement Project. Report prepared for the U.S. Department of Agriculture, Food and Consumer Service. 15. Hamilton, W.L., Cook, J.T., Thompson, W.W., Buron, L.F., Frongillo, Jr., E.A., Olson, C.M., and Wehler, C.A. 1997, September. Household Food Security in the United States in 1995: Technical Report. Report prepared for the U.S. Department of Agriculture, Food and Consumer Service. 16. Kendall, A., Olson, C.M., and Frongillo, Jr., E.A. 1995. Validation of the Radimer/ Cornell measures of hunger and food insecurity. Journal of Nutrition 125:2793-2801. 17. Kendall, A., Olson, C.M., and Frongillo, Jr., E.A. 1996. Relationship of hunger and food insecurity to food availability and consumption. Journal of the American Dietetic Association 96:1019-1024. 18. Kleinman, R.E., Murphy, J.M., Little, M., Pagano, M., Wehler, C.A., Regal, K., and Jellinek, M.S. 1998. Hunger in children in the United States: Potential behavioral and emotional correlates. Pediatrics 101:E3-E9. 19. Maxwell, D.G. 1995, December. Measuring Food Insecurity: The Frequency and Severity of "Coping Strategies." FCND Discussion Paper No. 8. International Food Policy Research Institute, Food Consumption and Nutrition Division, Washington, DC. 20. McGuiness, R. 1997, January. Response Variance in the 1995 Food Security Supplement. Quality Assurance and Evaluation Branch, Demographic Statistical Methods Division, Bureau of the Census. 21. Murphy, J.M., Wehler, C.A., Pagano, M.E., Little, M., Kleinman, R.E., and Jellinek, M.S. 1998. The relationship between hunger and psychosocial functioning in low-income American children. Journal of the American Academy of Child and Adolescent Psychiatry 37: 163-170. 22. Nestle, M. and Guttmacher, S. 1992. Hunger in the United States: Rationale, methods and policy implications of state hunger surveys. Journal of Nutrition Education 24 (Suppl.): 18S-22S. 1998 Vol. 1J Nos. 1&2 27 28 23. President's Task Force on Food Assistance. 1984. Report of the President's Task Force on Food Assistance. U.S. Government Printing Office, Washington, DC. 24. Price, C., Hamilton, W.C., and Cook, J.T. 1997, September. Household Food Security in the United States in 1995: Guide to Implementing the Core Food Security Module. Report prepared for the U.S. Department of Agriculture, Food and Consumer Service. 25. Radimer, K.L., Olson, C.M., and Campbell, C. C. 1990. Development of indicators to assess hunger. The Journal of Nutrition 120 (Suppl.):1544-1548. 26. Radimer, K.L., Olson, C.M., Green, J.C., Campbell, C.C., and Habicht, J.P. 1992. Understanding hunger and developing indicators to assess it in women and children. Journal of Nutrition Education 24 (Suppl.):36S-44S. 27. Singer, E. and Hess, J. 1994, October. Evaluation of the Pretest Results for the Food Security Supplement to April1995 CPS. U.S. Bureau of the Census, Center for Survey Methods Research. 28. Tufts University, Center on Hunger, Poverty and Nutrition Policy. 1993. Policy Report: Thirty Million Hungry Americans. Testimony prepared for the House Select Committee on Hunger, Washington, DC. Tufts School of Nutrition Science and Policy, Medford, MA. 29. U.S. Department of Agriculture, Food and Consumer Service, Office of Analysis and Evaluation. 1995. Food Security Measurement and Research Conference: Papers and Proceedings. Alexandria, VA. 30. Wehler, C.A. 1989. Identification of Childhood Hunger: The FRAC Model. Paper presented at the AIN Conference on Nutrition Monitoring and Nutrition Status Assessment, December 8-10, Charleston, SC. 31. Wehler, C.A., Scott, R.I., Anderson, J.J., and Parker, L. 1991. Community Childhood Hunger Identification Project: A Survey of Childhood Hunger in the United States. Food Research and Action Center, Washington, DC. 32. Wehler, C.A., Scott, R.I., and Anderson, J.J. 1992. The Community Childhood Hunger Identification Project: A model of domestic hunger-Demonstration project in Seattle, Washington. Journal of Nutrition Education 24 (Suppl.):29S-35S. 33. Wehler, C.A., Scott, R.I. , Anderson, J.J., and Parker, L. 1995. Community Childhood Hunger Identification Project: A Survey of Childhood Hunger in the United States. Food Research and Action Center, Washington, DC. Family Economics and Nutrition RevieW 1998 Vol. 11 Nos. 1 &2 Do Child Support Awards Cover the Cost of Raising Children? Mark Lino Center for Nutrition Policy and Promotion A large proportion of the poor in the United States is composed of single mothers and their children. Many of these women receive partial child support payment or none at all. Welfare reform legislation has, therefore, focused on child support payment enforcement. However, the economic well-being of single-parent families can be improved only if child support payments are paid on a regular basis and reflect the cost of raising children. Comparing USDA estimates of expenditures on children with average full child support payments, which represent average child support awards, shows that these full payments cover a small proportion of the total cost of raising children. Therefore, to improve the economic well-being of single-mother families, child support enforcement plus child support awards that reflect the cost of raising children are needed. dra.-natic change in American family life during the past 30 years has been the growth in the number of single-parent families. In 1970, 13 percent of all families with children were headed by a single parent. By 1996, this proportion had climbed to 32 percent ( 14,17). It is estimated that half of the children in the United States will spend part of their childhood in families headed by a single parent (4)-typically, the mother. Since 1970, single parenthood has become synonymous with poverty. In 1994, the median income of single-parent families headed by a female was less than onethird that of married-couple families with children ( 17); 53 percent of these female-headed families had income below the poverty threshold ( 17). Child support-legally mandated payments from a noncustodial parent to a custodial parent 1--can improve the economic well-being of single-parent families if these payments are paid on a regular basis and reflect the cost of raising children. Given that the recent Welfare Reform Act limits the time single parents are eligible for public assistance, child support is an important way to improve the economic well-being of single-parent families. 1The custodial parent has primary physical care of a child. It does not necessarily mean the parent has sole legal or sole physical custody. The noncustodial parent does not have primary physical care of a child; although, a child can reside with this parent some portion of the time. 29 Much of the focus on child support has been on payment enforcement because noncustodial parents often do not make payments. In 1991, of custodial mothers who were due child support, 48 percent received partial payment or none at all (15 ). The adequacy of child support awards has received much less attention. Beller and Graham compared 1985 child support awards with the cost of raising children (based on 1972-73 data inflated to 1985 dollars) and found these awards only covered a fraction of the cost of raising children (2). A U.S. Department of Health and Human Services study reviewed a variety of estimates of the cost of raising children and compared them with 1990 State child support guidelines ( 18). Most State guidelines were within the range of cost estimates; however, these guidelines were at or near the lower bound of these estimates. Pirog-Good compared 1991 State child support awards determined by the guidelines in each State with estimates of the cost of raising children and concluded most State guidelines fell short of this cost (9). The Women's Legal Defense Fund compared 1989-90 State child support guidelines with a standardof- living measure for children (5). It was found that, in most States, support awards based on the guidelines left children with less than a decent standard of living. Since 1960, the U.S. Department of Agriculture (USDA) has provided annual estimates of family expenditures on children (often referred to as the cost of raising a child) by family income level. This study examines the adequacy of child support awards by comparing average full child support payments with 30 USDA's estimates of the cost of raising children. Average full child support payments should reflect total child support awards. This study differs from previous research-it focuses on USDA's estimates of the cost of raising children as a basis for comparison; whereas, other studies use a range of estimates, some of which are outdated. Also, it uses actual child support payments to make this comparison. The article begins with a brief overview of child support guidelines in the United States, a description of the USDA childrearing expense estimates, and a comparison of the USDA estimates with other estimates of expenditures on children. The article concludes with a discussion of the policy implications for child support guidelines. Overview of the U.S. Child Support Guideline System Before 1984, the use of child support guidelines was limited in many States (21 ). Child support awards, typically set on a case-by-case basis, varied tremendously among judges (5). This system often resulted in awards that had little rationale (2). The emphasis during this time was on the enforcement of child support payments since a large percentage of single mothers received no paymentsa problem that still exists. In 1978, about half of custodial mothers due child support received partial payment or none at all (2). By 1991, this proportion remained almost unchanged at 48 percent ( 15 ). Title N-D of the 1975 Social Security Act made the Federal Government an overseer of child support collection; although, the daily work of collecting child support remained a State responsibility. The Child Support Enforcement Amendments of 1984 were primarily aimed to improve the collection of child support. These amendments required States to (1) use automatic wage withholding to collect overdue child support, (2) use expedited legal processes to establish and enforce support orders, (3) collect overdue support by intercepting State income tax refunds, and (4) initiate a process for imposing liens against real and personal property for nonpayment of child support. The amendments also required States to set numeric child support guidelines and to make these guidelines available to officials in charge of setting the level of child support. The amendments, however, did not require that these guidelines be binding. The Family Support Act of 1988 required States to implement presumptive rather than advisory child support guidelines. It stipulates that these guidelines are to be followed unless their application would be unjust or inappropriate. In addition, States are required to review their guidelines every 4 years to ensure that their application results in appropriate child support award amounts and to consider economic data on the cost of raising children in this review. This act, for the first time, requires States to establish child support guidelines and to use them as the basis of child support awards. Family Economics and Nutrition RevieW The welfare reform bill (Personal Responsibility and Work Opportunity Reconciliation Act of 1996) also contained major child support enforcement provisions as receipt of child support and dependency on public assistance are typically inversely related. Overall, child support legislation has primarily dealt with better enforcement of such support. This emphasis is not swprising given the large percentage of custodial parents who receive no child support. However, the enforcement of child support will significantly improve the economic situation of single-parent families only if the awards reflect child-rearing expenses or the cost of raising children. USDA Estimates of Expenditures on Children by Families Methodology Since 1960, USDA has provided annual estimates of expenditures on children from birth through age 17 by marriedcouple and single-parent families. 2 These expenditures on children are estimated for the major budgetary components: Housing, food, transportation, clothing, health care, child care/education, and miscellaneous goods and services (personal care items, entertainment, etc.). The latest child-rearing expense estimates are based on the 1990-92 Consumer Expenditure Survey (CE) updated to 1996 dollars using the Consumer Price Index (CPI). The CE is the only Federal 2 The administrative report has a detailed description of the USDA methodology used to estimate child-rearing expenses and a discussion of the expenses (6). 1998 Vol. 11 Nos. 1 &2 Milestones in Federal Legislation Regarding Child Support Guidelines 1975: Title IV-D of the Social Security Act: The U.S. Department of Health and Human Services (then named the U.S. Department of Health, Education, and Welfare) is given primary responsibility for" ... establishing standards for State (child support) program organization, staffing, and operation to assure an effective program." However, primary responsibility for operating the child support enforcement program " ... is placed on the States pursuant to the State plan." 1984: Child Support Enforcement Amendments: States were required to " ... formulate guidelines for determining appropriate child support obligation amounts and distribute the guidelines to judges and other individuals who possess authority to establish obligation amounts." The amendments, however, did not require judges and other officials to follow these child support guidelines. 1988: Family Support Act of 1988: Judges and other officials are required to" ... use State guidelines for child support unless they are rebutted by a written finding that applying the guidelines would be unjust or inappropriate in a particular case." States are also required to " ... review guidelines for awards every four years" and to consider economic data on the cost of raising children in this review. 1996: Personal Responsibility and Work Opportunity Reconciliation Act: This act strengthened child support enforcement provisions given the link between receipt of child support and welfare dependency. Source: U.S. Department of Health and Human Services. Administration for Children and Families, Office of Child Support Enforcement. 1994. Child Support Enforcement Nineteenth Allllual Report to Congress. survey of household expenditures collected nationwide. It collects information on sociodemographic characteristics, income, and expenditures of a nationally representative sample of households. The methodology employed by USDA to estimate child-rearing expenses specifically examines the intrahousehold distribution of expenditures using data for each budgetary component. The CE contains child-specific expenditure data for some budgetary components (clothing and child care/education) and household level data for other budgetary components. 31 32 Multivariate analysis is used to estimate household and child-specific expenditures. Income level, family size, and age of the younger child are controlled for so estimates can be made for families with these varying characteristics (regional estimates are also derived by controlling for region). Estimated household and child-specific expenditures are allocated among family members (e.g., in a married-couple, two-child family: the husband, wife, older child, and younger child). Since the estimated expenditures for clothing and child care/education only apply to children, these expenses are allocated by dividing them equally among the children. Because the CE does not collect expenditures on food and health care by family member, data from other Federal studies are used to apportion these budgetary components to a child by age. The USDA food plans are used to allocate food expenses among family members. These plans, derived from a national food consumption survey, show the share of food expenses attributable to individual family members by age and household income level. These members' food budget shares are applied to estimated household food expenditures to determine food expenses on a child. Health care expenses are allocated to each family member based on data from the National Medical Expenditure Survey. This survey contains data on the proportion of health care expenses attributable to individual family members. These members' budget shares for health care are applied to estimated household health care expenditures to determine expenses on a child. Unlike food and health care, no authoritative base exists for allocating estimated household expenditures on housing, transportation, and other miscellaneous goods and services among family members. Two common approaches used to allocate these expenses are the per capita and the marginal cost methods. The marginal cost method measures expenditures on children as the difference in expenses between couples with children and equivalent childless couples. This method depends on development of an equivalency measure; however, there is no standard measure. Various measures have been proposed, each yielding different estimates of expenditures on children. Also, the marginal cost approach assumes-without much basis-that the difference in total expenditures between couples with and without children can be attributed solely to the children in a family. In addition, couples without children often buy homes larger than they need in anticipation of children. Underestimates of expenditures on children can result when these couples are compared with similar couples with children. For these reasons, USDA uses the per capita method to allocate housing, transportation, and miscellaneous goods and services among household members. This method allocates expenses among household members in equal proportions. Although the per capita method has limitations, they are considered Jess severe than those of the marginal cost approach. In implementing the per capita method, it should be noted that for homeowners, housing expenses do not include mortgage principal payments; in the CE, such payments are considered to be part of savings. Also, because workrelated transportation expenses are not directly child specific, these costs are excluded when estimating children's transportation expenses. Family Economics and Nutrition Review Estimated Child-Rearing Expenditures Estimates of 1996 family expenditures on the younger child in husband-wife households with two children for the overall United States are shown in table 1. Expenses on children vary considerably by household income level. Depending on the age of the child, the annual expenses range from $5,670 to $6,740 for families in the lowest income group (1996 before-tax income less than $34,700), from $7,860 to $8,960 for families in the middle-income group (1996 before-tax income between $34,700 and $58,300), and from $11,680 to $12,930 for families in the highest income group ( 1996 before-tax income more than $58,300).3 On average, households in the lowest income group spend 28 percent of their before-tax income per year on a child, those in the middleincome group, 18 percent, and those in the highest income group, 14 percent. Housing accounts for the largest share of total child-rearing expenses. Based on the average for the six age groups, housing accounts for 33 to 37 percent of child-rearing expenses, depending on income. Food is the second largest average expense on a child for families regardless of income level, accounting for 15 to 20 percent of child-rearing expenses. Transportation is the third largest childrearing expense, making up 14 to 15 percent of child-rearing expenses across income levels. Expenditures on a child are lower in the younger age categories and higher in the older age categories. 3 The estimates are based on all households, including those with and without specific expenses. So, for some families their expenditures may be htgher or lower than the mean estimates, dependtng on whether they incur the expense or not. This Particularly applies to child care/education for which about 50 percent of families in the study had no expenditure. 1998 Vol. 11 Nos. 1 &2 This held across income groups. Expenses for the various budgetary components varied by each age group. Food expenses were highest for teenagers, whereas child care expenses were one of the largest expenses for preschoolers. Additional analysis found that, on average, the expenses depicted in table 1 also reflect those on the older child in a given age category in a two-child family. However, compared with expenditures for each child in a two-child family, husband-wife households with one child spend an average of 24 percent more on the single child, and those with three or more children spend an average of 23 percent less on each child. This is due to family income being spread over fewer or more children and diseconomies or economies of scale. For example, a middle-income family with one child age 6-8 spends $10,080 on the child, a middle-income family with two children ages 6-8 and 15-17 spends $17,090 on the children, and a middle-income family with three children ages 6-8, 12-14, and 15-17 spends $19,960 on the children. For child-rearing expense estimates by region and for single-parent households, see Lino (6). USDA Child-Rearing Expense Estimates Compared With Other Estimators Among other estimators used to determine child-rearing expenses, the Engel and Rothbarth estimators are two of the most commonly used. Both of these estimators are marginal cost approachesexpenses on children are gauged as the difference between expenses of couples with children and equivalent childless couples. This difference is thought to represent additional or marginal expenditures that couples make on a child. The two estimators use different equivalency scales, however, to compare the expenditures of couples with and without children. The Engel estimator (based on the work of Engel in the 19th century, see DHHS ( 18) for a description of Engel's work) assumes that if two families spend an equal percentage of their total expenditures on food, they are equally well-off. The Rothbarth estimator (based on the work of Roth barth in the 1940's, see Roth barth ( 10 )) uses the level of excess income available to people after necessary expenditures on family members are made as the equivalency measure. Roth barth's definition of excess income includes luxuries (alcohol, tobacco, entertainment, and sweets) and savings. Both estimators have limitations, as previously explained. Each assumes a "true" equivalency measure. However, in the economics literature, neither of the equivalency measures has been validated as the "true" measure. Also, the marginal cost estimators do not provide direct estimates of how much is spent on a child. They estimate how much money families with children must be compensated to bring the parents to the same utility level (as gauged by an equivalence scale) of couples without children-this is a different question from "how much do parents spend on children?" According to Bamow, an economist who studied the issue of estimating expenditures on children, " ... while they [the Engel and Rothbarth estimators] undoubtedly yield biased estimates of the true level of expenditures made on behalf of children, the direction of the bias is believed to be known" ( 1 ). He makes the argument that " ... the Rothbarth estimator is likely to provide 33 Table 1. Estimated annual expenditures* on a child by husband-wife families, overall United States, 1996 Child care Transpor- Health and Miscel- Age of child Total Housing Food tation Clothing care education laneoust Before-tax income: Less than $34,700 (A verage=$21,600) 0-2 $5,670 $2,160 $810 $720 $370 $390 $660 $560 3-5 5,780 2,140 900 700 360 370 740 570 6-8 5,900 2,060 1,160 810 400 420 440 610 9-11 5,940 1,860 1,380 880 450 460 270 640 12-14 6,740 2,080 1,450 1,000 750 470 190 800 15-17 6,650 1,680 1,570 1,340 670 500 310 580 Total $110,040 $35,940 $21 ,810 $16,350 $9,000 $7,830 $7,830 $11 ,280 Before-tax income: $34,700 to $58,300 (Average=$46,100) 0-2 $7,860 $2,930 $960 $1 ,080 $440 $510 $1,080 $860 3-5 8,060 2,900 1,110 1,050 430 490 1,200 880 6-8 8,130 2,830 1,420 1,170 470 560 770 910 9-11 8,100 2,630 1,670 1,240 520 600 500 940 12-14 8,830 2,840 1,680 1,350 880 610 370 1,100 15-17 8,960 2,440 1,870 1,710 780 640 630 890 Total $149,820 $49,710 $26,130 $22,800 $10,560 $10,230 $13,650 $16,740 Before-tax income: More than $58,300 (Average=$87,300) 0-2 $11,680 $4,650 $1 ,280 $1,510 $580 $580 $1,630 $1,450 3-5 11 ,910 4,620 1,450 1,480 560 560 1,780 1,460 6-8 11 ,870 4,550 1,740 1,600 620 640 1,220 1,500 9-11 11 ,790 4,350 2,030 1,670 670 690 850 1,530 12-14 12,620 4,570 2,130 1,780 1,110 690 650 1,690 15-17 12,930 4,160 2,240 2,160 1,010 730 1,150 1,480 Total $218,400 $80,700 $32,610 $30,600 $13,650 $11,670 $21,840 $27,330 • Estimates are based on 1990-92 Consumer Expenditure Survey data updated to 1996 dollars using the Consumer Price Index. The figures represent estimated expenses on the younger child in a two-child family . Estimates are about the same for the older child, so to calculate expenses for two children, figures should be summed for the appropriate age categories. To estimate expenses for an only child, multiply the total expense for the appropriate age category by 1.24. To estimate expenses for each child in a family with three or more children, multiply the total expense for each appropriate age category by 0.77. For expenses on all children in a fam ily, these totals should be summed. t Miscellaneous expenses include personal care items, entertainment, and reading materials. 34 Family Economics and Nutrition Review a lower bound estimate of actual expenditures on children, while the Engel estimator is likely to provide an upper bound." The precise magnitude of the overestimate of the Engel estimator or the underestimate of the Roth barth estimator is unknown. Barnow states the Engel estimator yields results too high to be believed so recommends the Rothbarth estimator be slightly increased to determine child-rearing expenditures (1 ). How do child-rearing expense estimates derived from the Engel and Rothbarth estimators compare with the USDA estimates? Table 2 shows this comparison by number of children and total household expenditures. The results for the Engel and Rothbarth estimators are from a U.S. Department of Health and Human Services study (18) that estimated child-rearing expenses by married couples based on the 1980-87 CE; this study contains the most recent child-rearing expense estimates using the Engel and Rothbarth approaches. The USDA estimates are based on the 1995 study. The comparison is based on child-rearing expense estimates as a percentage of total family expenditures; hence, the estimates did not have to be converted into real dollars. For the USDA estimates, average expenditures of families in each income group (as derived from the CE data) were used to make the percentages comparable to those from the DHHS study. The Engel and Rothbarth methods yield varying child-rearing expense estimates that differ as much as 20 percentage points for a family with three children. So when using the marginal cost method in estimating expenditures on children, the choice of an equivalency measure 1998 Vol. 11 Nos. 1&2 Table 2. Average percent of household expenditures attributable to children in husband-wife families Number of children One Two Three Household expenditure level3 Low Average High Engel1 33 49 59 49 49 49 Estimator Rothbarth1 Percent 25 35 39 36 36 35 USDA2 26 42 48 45 42 39 1 Percentages for these estimators are taken from the U.S. Department of Health and Human Services 1~0. , 2Percentages are from the 1995 USDA study. Average expenditures of families in each income level were used to make comparisons. Percentages by number of children are based on average expenditures of middle-income families. 3Percentages by household expenditure level are for a family with two children. is obviously critical since different measures yield different results. If the Rothbarth technique is a lower bound estimator of child-rearing expenses and the Engel technique is an upper bound estimator as Barnow believes, this gives credence to the USDA estimates of childrearing expenses-they are between those produced by the Engel and Rothbarth techniques. For families with one child and for families with a high expenditure level, the USDA estimates are closer to the Rothbarth estimates, whereas for families with a low expenditure level, the USDA estimates are closer to the Engel estimates. For families with two or more children and for families with an average household expenditure level, the USDA estimates are about in the middle of the Roth barth and Engel estimates. It is sometimes argued that the USDA method overestimates child-rearing expenses since the per capita method is used to allocate housing, transportation, and miscellaneous expenses among household members. These three budgetary components account for about 60 percent of the child-rearing costs calculated by USDA. One study argues that childrelated housing expenses should be measured as the difference in rent between one- and two-bedroom apartments (3). This argument assumes all children will reside in rental property. Housing expenses on an only child in a lower income and middle-income family for the overall United States are estimated by USDA to be about $205 and $285 per month, respectively, in 1996. This includes the cost of shelter, utilities, 35 furnishings, home insurance, and appliances. According to the Census Bureau, the difference in median rental price between an efficiency/one-bedroom housing unit and a two-bedroom housing unit in the overall United States was about $100 per month in 1996 dollars (16). This does not include utility costs for many units, furnishings, insurance, or appliances. Also, the USDA childrearing housing expense includes home owners' and renters' expenses; housing costs for homeowners are typically higher than the costs for renters because owned housing usually has more space than does rental housing. The USDA child-rearing expenses do not include work-related transportation expenses. These expenses were calculated to be 40 percent of total transportation expenses. Miscellaneous expenses include expenditures on personal care (e.g., toothpaste and haircuts), entertainment (e.g., video cassettes and toys), and reading material (e.g., newspapers and books). Many of the miscellaneous goods and services are child-oriented so a per capita approach is reasonable in allocating these expenses. Based on some of the goods and services that are included in this category, it could be argued that children use more than a per capita share of these expenses. Therefore, it is unlikely that the USDA child-rearing estimates grossly overestimate expenditures on children for housing, transportation, and miscellaneous goods and services. 36 Table 3. Average full child support payments, household expenditures on children, and percentage of child-rearing expenditures covered by full payments, by income group and number of children, 1991 Household expenditures on children 1 Number of Full child Low Middle High children support payments income income income $2,776 $6,022 $8,395 $11,789 (46%) (33%) (24%) 2 $4,220 $10,103 $14,085 $19,779 (42%) (30%) (21%) 3 $4,277 $11,878 $16,560 $23,255 (36%) (26%) (18%) 4 or more $4,901 $15,877 $22,135 $31,083 (31%) (22%) (16%) 1Child-rearing expenses are for husband-wife households. Note: Numbers in parentheses are the percentage of child-rearing expenditures ·covered by full child support payments. Sources: Scoon-Rogers, L. and Lester, G.H., 1995, Child Support for Custodial Mothers and Fathers: 1991, Current Population Reports, Consumer Income, Series P60-187, U.S. Department of Commerce, Bureau ~fthe Census ( 11) and U.S. Department of Agriculture, Agricultural Research Service, Family Economzcs Research Group, 1992, Expenditures on a Child by Families, 1991 (13). USDA Child-Rearing Expense Estimates Compared With Child Support A wards How do the USDA child-rearing expense estimates compare with average child support awards? Are these awards adequate in terms of the cost of raising children? The U.S. Bureau of the Census periodically publishes a child support report. The most recent report contains information on mean child support income in 1991 for custodial parents receiving full payment from noncustodial parents by number of children ( 11 ). Full child support payments should reflect the total child support award. The Census estimates are for all families of which middle-income families are likely the norm. Table 3 compares 1991 full child support payments from noncustodial parents with the 1991 USDA childrearing expense estimates for low-, middle-, and high-income households by number of children ( 13 ). If each parent equally shares child-rearing expenses, average full payment of child support should cover half the cost of raising children. Full child support payments should not reflect total expenditures on children as this expense is divided between the custodial and noncustodial parent. As seen in table 3, these payments cover less than 50 percent of the cost of raising children regardless of income group. Family Economics and Nutrition RevieW Table 4. Average full child support payments, household expenditures on children (excluding health care and child care/education expenses), and percentage of child-rearing expenditures covered by full payments, by income group and number of children, 1991 Household expenditures on children1 Number of Full child Low Middle High children support payments income income income $2,776 $5,177 $7,176 $9,967 (54%) (39%) (28%) 2 $4,220 $8,685 $12,039 $16,721 (49%) (35%) (25%) 3 $4,277 $10,211 $14,155 $19,660 (42%)
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Title | Family Economics and Nutrition Review [Volume 11, Number 1-2] |
Date | 1998 |
Contributors (group) | Center for Nutrition Policy and Promotion (U.S.) |
Subject headings |
Home economics--United States--Periodicals Nutrition policy--United State--Periodicals |
Type | Text |
Format | Pamphlets |
Physical description | v. : $b ill. ; $c 28 cm. |
Publisher | Washington, D.C. : U.S. Dept. of Agriculture |
Language | en |
Contributing institution | Martha Blakeney Hodges Special Collections and University Archives, UNCG University Libraries |
Source collection | Government Documents Collection (UNCG University Libraries) |
Rights statement | http://rightsstatements.org/vocab/NoC-US/1.0/ |
Additional rights information | NO COPYRIGHT - UNITED STATES. This item has been determined to be free of copyright restrictions in the United States. The user is responsible for determining actual copyright status for any reuse of the material. |
SUDOC number | A 77.245:11/1-2 |
Digital publisher | The University of North Carolina at Greensboro, University Libraries, PO Box 26170, Greensboro NC 27402-6170, 336.334.5482 |
Full-text | ',[R!AL'"; OEPf\RTMF. Special Issue Promoting Family Economic and Nutrition Security Feature Articles 4 Maintaining Food and Nutrition Security: The Role of the Food Stamp Program and WIC P. Peter Basiotis, CarolS. Kramer-LeBlanc, and Eileen T Kennedy 17 Household Food Security in the United States in 1995: Results From the Food Security Measurement Project Margaret Andrews, Gary Bickel, and Steven Carlson 29 Do Child Support Awards Cover the Cost of Raising Children? MarkLino 41 Child Care and Welfare Reform MarkLino 49 Discussion Paper on Domestic Food Security CarolS. Kramer-LeBlanc and Kathryn McMurry, Editors Research Summaries 79 Regional Differences in Family Poverty 84 Work Schedules of Low-Educated American Women and Welfare Reform 86 Family Finances in the U.S.: Recent Evidence From the Survey of Consumer Finances Regular Items 90 Charts From Federal Data Sources 92 Research and Evaluation Activities in USDA 95 Cost of Food at Home UNITED STATES DEPARTMENT OF AGRICULTURE Volume 11, Numbers 1&2 1998 Dan Glickman, Secretary U.S. Department of Agriculture Shirley R. Watkins, Under Secretary Food, Nutrition, and Consumer Services Rajen Anand, Executive Director Center for Nutrition Policy and Promotion Carol S. Kramer-LeBlanc, Deputy Executive Director Center for Nutrition Policy and Promotion P. Peter Basiotis, Director Nutrition Policy and Analysis Staff TRIBUTE To Joan Courtless, Edit.or Family Economics and Nutrition Review 1986-1997 This issue is dedicated to Joan Courtless, who recently retired as editor of Family Economics and Nutrition Review. Joan was the editor of the journal from 1986 to 1997. As editor, she made many significant and positive contributions to the journal. She oversaw the transition from Family Economic.s Review to Family Economics and Nutrition Review, with its greater emphasis on matters of nutrition and nutrition policy. She gqided the journal in the direction of soliciting and reviewing externally authored articles. She herself authored numerous articles, many dealing with clothing issues, and she edited the 50th anniversary issue of the journal. Colleagues and readers associated with the journal will miss Joan and wish her the best. Editor-in-Chief Carol S. Kramer-LeBlanc Editor Julia M. Dinkins Special Features Editor Mark Uno Managing Editor Jane W. Fleming Family Economics and Nutrition Review is written and publis'hed each quarter by the Center for Nutrition Policy and Promotion, U.S. Department of Agriculture, Washington, DC. The Secretary of Agriculture has determined that publication of this periodical is necessary in the transaction of the public busiless required by law of the Department. This publication is not copyrighted. Contents may be reprinted without permission, but credit to Family Economics and Nutrition Review would be appreciated. Use of commercial or trade names does not imply approval or constitute endorsement by USDA. Family Economics and Nutrition Review is indexed in the following databases: AGRICOlA, Ageline, Economic Literature Index, ERIC, Family Studies, PAIS, and Sociological Abstracts. Family Economics and Nutrition Review is for sale by the Superintendent of Documents. Subscription price is $12.00 per year ($15.00 for foreign addresses). Send subscription orders and change of address to Superintendent of Documents, P.O. Box 371954, Pittsburgh, PA 15250·7954. (See subscription form on p. 96.) Original manuscripts are accepted for publication. (See "guidelines for authors" on back inside cover). Suggestions or comments concerning this publication should be addressed to: Julia M. Dinkins, Ed~or, Family Economics and Nutrition Review, Center for Nutrition Policy and Promotion, USDA, 112020th St. NW, Suite 200 North Lobby, Washington, DC 20036. Phone (202) 606-4876. USDA prohibits discrimination in all its programs and activities on the basis of race, color, national origin, gender, religion, age, disability, political beliefs, sexual orientation, or marital or family status. (Not all prohibited bases apply to all programs.) Persons with disabilities who require ~lternative means for communication of program Information (Braille, large print, audiotape, etc.) should contact USDA's TARGET Center at (202) 720·2600 (voice and TDD). To file a complaint of discrimination, write USDA, Director, Office of Civil Rights, Room 326-W, Whitten Building, 14th and Independence Avenue, SW, Washington, DC 20250·941 0 or call (202) 720-5964 (voice and TDD). USDA is an equal Opportunity provider and employer. Center for Nutrition Policy and Promotion PRop~n.'l"l .. ~ rrc~r Of LIBR4Rv ot.~c 4 ... 1998 UrullcrsJt, } 01 Nurn at Green h J Caratina Speciirq~ue Promoting Family Economic and Nutrition Security Feature Articles 4 Maintaining Food and Nutrition Security: The Role of the Food Stamp Program and WIC P. Peter Basiotis, CarolS. Kramer-LeBlanc, and Eileen T. Kennedy 17 Household Food Security in the United States in 1995: Results From the Food Security Measurement Project Margaret Andrews, Gary Bickel, and Steven Carlson 29 Do Child Support Awards Cover the Cost of Raising Children? Mark Lino 41 Child Care and Welfare Reform MarkLino 49 Discussion Paper on Domestic Food Security CarolS. Kramer-LeBlanc and Kathryn McMurry, Editors Research Summaries 79 84 86 Regional Differences in Family Poverty Work Schedules of Low-Educated American Women and Welfare Reform Family Finances in the U.S.: Recent Evidence From the Survey of Consumer Finances Regular Items 90 Charts From Federal Data Sources 92 Research and Evaluation Activities in USDA 95 Cost of Food at Home Volume 11, Numbers 1&2 1998 PROMOTING FAMILY ECONOMIC AND NUTRITION SECURITY Family Economics and Nutrition Review: Special Issue (Volume 11, Numbers 1&2) Introduction-Opportunities During an Era of Change CarolS. Kramer-LeBlanc In August 1996, the 1 04th Congress enacted and the President signed into law the Personal Responsibility and Work Opportunity Reconciliation Act. The legislation replaced Federal welfare payments under the Aid to Families With Dependent Children Program with a block grant program known as the Temporary Assistance for Needy Families Program (TANF). This program gives greater flexibility to States to set benefit levels, establish eligibility criteria, and determine the benefit blend. Welfare reform has altered more than 40 years of social welfare policy to move people from welfare to work and reduce the Federal budget deficit. New welfareto- work policies can influence significantly the wellbeing of over 30 million people in the United States. The challenge for all is to ensure that welfare reform works, and that both family economic security and food and nutrition security are maintained and enhanced as the United States approaches the year 2000. This special, double issue considers family economic and nutrition security. We are pleased to include some important articles that address significant aspects of this topic. Included are the following: 2 "Maintaining Food and Nutrition Security: The Role of the Food Stamp Program and WIC," by P. Peter Basiotis, CarolS. Kramer-LeBlanc, and Eileen T. Kennedy of the Center for Nutrition Policy and Promotion (Basiotis and Kramer-LeBlanc) and Research, Education, and Economics (Kennedy), respectively, USDA. This article examines the contribution of the Food Stamp Program (FSP) and The Special Supplemental Food Program for Women, Infants, and Children (WIC) to maintaining the nutrition security/diet quality of low-income participant households. This issue is important to examine in the context of recent welfare policy reforms that have emphasized moving people from welfare to work and have replaced the Federal Aid to Families With Dependent Children Program with the more limited State-administered Temporary Assistance to Needy Families Program. Federal food assistance programs were retained as a nutritional safety net, but in some cases, access and benefits have been restricted. The paper examines the hypothesis that participation in the FSP and/or WIC is an important factor in maintaining and improving the dietary quality of low-income households. Family Economics and Nutrition Review "Household Food Security in the United States in 1995: Results From the Food Security Measurement Project," by Margaret Andrews, Gary Bickel, and Steven Carlson, economists at the Office of Analysis and Evaluation of the Food and Nutrition Service, U.S. Department of Agriculture. This article reports important results from the landmark effort to measure food insecurity in the United States. Results have not been reported previously in a peer-reviewed journal and are of broad interest to the policy community. These results will contribute to the baseline against which progress in achieving food security in the United States will be measured. "Do Child Support Awards Cover the Cost of Raising Children?" by Mark Lino of the Center for Nutrition Policy and Promotion, USDA. Lino examines the adequacy of child support awards to single parents. Whereas welfare reform legislation has focused on child support payment enforcement to improve the well-being of children, Lino points out that awards need to assist single parents in meeting the costs of raising children. Comparing USDA estimates of expenditures on children with average full child support payments indicates that full payments only cover a small proportion of the total cost of raising children. 1998 Vol. 11 Nos. 1 &2 "Child Care and Welfare Reform," by Mark Lino of the Center for Nutrition Policy and Promotion, USDA. Lino reviews provisions of the Personal Responsibility and Work Opportunity Act affecting child care. Because the Welfare Reform Act establishes mandatory work requirements, sufficient quantity and quality of child care is crucial for the welfare of children and society and the success of welfare reform policy measures. In addition to the legislation, Lino reviews selected State child care initiatives. "Discussion Paper on Domestic Food Security," edited by CarolS. Kramer-LeBlanc and Kathryn McMuny for the Domestic Subgroup of the U.S. Interagency Working Group on Food Security. The Domestic Secretariat that developed this broadly reviewed discussion paper consists of the Center for Nutrition Policy and Promotion, USDA, and the Office of Disease Prevention and Health Promotion, HHS. We are including the discussion paper to make it available to as broad a readership as possible, and we believe it may be of particular interest to the readership ofFENR. The paper was developed in 1997-98 in response to the World Food Summit held in November 1996 in Rome that focused the world's attention on chronic problems of hunger and undernutrition internationally and in the United States. We at the Center for Nutrition Policy and Promotion and at the Family Economics and Nutrition Review are pleased to bring you this special issue. We welcome your comments, and we hope that you will send us your articles. I would like to thank our retired editor Joan C. Courtless for her years of service and welcome the new editor Julia M. Dinkins. 3 4 Maintaining Nutrition Security and Diet Quality: The Role of the Food Stamp Program and WIC P. Peter Basi otis USDA, Center for Nutrition Policy and Promotion Carol S. Kramer-LeBlanc USDA, Center for Nutrition Policy and Promotion Eileen T. Kennedy USDA, Research, Education, and Economics We examine the contribution of the Food Stamp Program (FSP) and the Special Supplemental Program for Women, Infants, and Children (WIC) to the nutrition security and diet quality of low-income participating households. This information can improve future monitoring of the effects of welfare policy reforms. Welfare reform has emphasized moving people from welfare to work and modifying or eliminating many former entitlement programs. However, after debate, Federal food assistance programs were retained as a nutritional safety net, although in some cases access and benefits were restricted. Using historical consumption data (CSFII 1989-91 ), we examine the hypothesis that participation in the FSP and/or WIC is an important factor in maintaining and improving the diet quality of low-income households. Using USDA's Healthy Eating Index (HEI), as an indicator of overall diet quality, and its 10 component indices, we estimate for the first time overall diet quality effects of changes in FSP and WIC participation and benefit levels. (The HEI permits us to examine diet quality as nutritionists see it-with some foods consumed too little and others too much.) Results suggest that both programs contribute significantly to maintaining and improving the nutritional well-being of lowincome households, considering both quantity and quality of diet oomponents. We believe the implication is that these food assistance programs help low-income households achieve nutrition security-including improved diet quality-and that their support provides a critical safety net to accompany welfare reform. Family Economics and Nutrition Review ITJ o examine relationships between diet quality and food program participation, we use USDA's 1989-91 Continuing Survey of Food Intakes by Individuals (CSFII) to analyze how the diet quality of low-income households is affected by participation in the Food Stamp Program (FSP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). The measure of diet quality used is the USDA Healthy Eating Index (HEI), developed to assess the overall quality of individuals' diets, defined as the de gree of adherence to Federal nutritional guidance ( 12,22). The Index consists of 10 equally weighted components that reflect how well individual diets conform to both the 1995 Dietary Guidelines for Americans (26) and the USDA Food Guide Pyramid (25) recommendations. Use of this index permits us to ex amine changes in diet quality associated with program benefits that may involve consuming less of particular dietary components and more of others. For the first time, this article reports how responsive the HEI and its individual components are to participation in the FSP and WIC. To provide a context for the analysis that follows, we briefly describe the FSP and WIC within the framework of Federal food assistance. We then mention pertinent elements of welfare reform and food assistance program changes to indicate how legislative provisions may affect food assistance program participants. We present methods and results and discuss implications. 1998 Vol. 11 Nos. 1 &2 Overview and Background on Food Programs and Welfare Reform Context The United States has a longstanding commitment to supporting food and nutrition security. Fourteen domestic food assistance programs comprise the formal Federal food and nutrition safety net and provide low-income consumers with foods, or with expanded means to purchase food products, along with nutrition information and education (table 1, p. 6). Among the "modern" Federal programs that began in 1945 with the National School Lunch Program and, 53 years later, have grown to provide about $37 billion annually (23 ), FSP and WIC are arguably the most significant in terms of benefits transferred and nutritional vulnerability of recipients, respectively. Advocates of the food assistance programs contend that they improve participants' diet quality and ameliorate public health. Despite welfare reform in late 1996, the structure of the Federal food programs was essentially preserved. However, FSP eligibility criteria and benefit levels were severely curtailed for some key groups-including legal immigrants and able-bodied adults without dependents-and results of this analysis raise concerns about the potential, negative effects on diet quality of affected groups when, or if, access to these two important food and nutrition programs is reduced. The FSP, an entitlement program, is the main food security program for lowincome households and provides coupons or electronic benefit cards to enhance recipients' food purchasing power and nutritional status. By FY 1996, the FSP provided $24.3 billion in benefits to an average of 10 million households and 25.5 million individuals. In FY 1996, the average monthly benefit received was more than $73 per person and more than $172 per household (24). Over 80 percent of Food Stamp households contain either a child, elder, or disabled person, and 42 percent are single-parent households (24). WIC is targeted to pregnant and postpartum (including breast-feeding) mothers, infants, and children up to 5 years of age at nutritional risk and serves more than 7 million people each month at an annual program cost of about $3.7 billion. WIC provides a combination of services including nutrient-dense food packages, nutrition counseling, and access to health services. Approximately 45 percent of all infants and 25 percent of all pregnant women in the United States participate in the WIC Program ( 11 ). The value of the average 1995 WIC food package was $43.12 per month, and the average monthly infant food package was $73.74 (24). The most common foods included in the WIC packages are milk, cheese, infant formula, cereal for adults and infants, juice, peanut butter, dried beans, and eggs. In 1992, a WIC Farmers' Market Nutrition Program was created to provide additional coupons to WIC participants, which can be used to purchase fresh fruits and vegetables in farmers' markets. This is a relatively minor share of the WIC Program, constituting only about $7 million of the $3.7 billion total WIC benefits. 5 Table 1. Federal food assistance programs Year FY 1996 budget FY 1996 Program name begun (in millions) Participation National School Lunch Program 1945 $4,313 24,050,000 bunches per day Special Milk Program 1955 $16.8 144,246,000 total served Food Stamp Program 1961 pilot $24,330 25,540,000 recipients 1974 permanent per month Nutrition Program for the Elderly 1965 $150 245,979,000 total meals School Breakfast Program 1966 pilot $1,118 6,103,000 daily average 1975 permanent breakfasts served Summer Food Service Program 1968 $258 2,216,000 daily average attendance (July) Commodity Supplemental Food Program 1968 $100.2 357,000 average participation Special Supplemental Program for Women, Infants, 1972 pilot $3,730 Average participation and Children (WIC) 1974 permanent 1,648,000 (women) 1,827,000 (infants) 3,712,000 (children) Child and Adult Care Food Program 1975 pilot $1,553 2,343,000 August average 1978 permanent 1,546,171,000 total 1989 adults meals served Food Distribution Program on Indian Reservations 1977 $70 120,000 average The Emergency Food Assistance Program 1981 $44 40,899,000 total pounds distributed Nutrition Assistance Program for Puerto Rico 1981 $1,153 Not available Homeless Children Program 1989 $3 Not available WIC Farmers Market Nutrition Program 1992 $7 742,000 Federal (of WIC total) 364,000 Non-Federal Source: U.S. Department of Agriculture, Food and Nutrition SeTllice. 1998. Administrative data. 6 Family Economics and Nutrition Review The FSP and the WIC Program share some commonalities. Each transfers benefits to low-income individuals to enhance food consumption and diet quality. As an entitlement program, the FSP conveys food purchasing power to any low-income individual who meets eligibility criteria (based on means testing). Food purchases are relatively unrestricted. Nutrition education is a much smaller component of the FSP than of the WIC Program. By contrast, the WIC Program is not an entitlement program but targets specific priority subgroups ofthe low-income population as funds are appropriated. WIC provides vouchers for purchase of one of seven food baskets selected to be nutrientdense and to supply specific nutrients deficient in the diets of the target participants. Unlike the FSP, WIC includes individual nutrition counseling along with a referral to other subsidized health services. Evaluations of the effects of the two programs suggest generally that they have been successful. Food consumption surveys show that diets of the poor improved markedly between 1965-66 and 1977-78, a period marked by nationwide expansion of the FSP (5). Numerous studies have shown that the FSP has succeeded in transferring purchasing power to low-income consumers and has increased food expenditures and nutrient availability relative to the transfer of cash benefits ( 3, 7, 14,15 ). 1998 Vol. 11 Nos. 1&2 Seventeen studies summarized by Fraker and cited by Rossi yielded estimates that out of each food stamp dollar, between $0.17 and $0.49 was spent on home-consumed food ("best estimate, $0.30") compared with only $0.05 to $0.10 of each dollar of cash benefits transferred. Fraker found that food stamp participation significantly increased the household availability of calcium, vitamin C, and iron. Far fewer studies have demonstrated the link between program participation, individual intake data, and improved nutritional status. WIC Program evaluations from the inception have demonstrated WIC effectiveness in increasing birth weight, decreasing incidence of low birth weight and prematurity, improving hematological status, and/or improving nutrient intake (11,18,19). Recent welfare reform includes replacement of Federal welfare payments with block grants to States (Temporary Assistance for Needy Families Program, or T ANF), welfare time limits and caps, and State discretion among benefit types, levels, and eligibility standards. States are encouraged to promote work and move recipients from welfare to work. Legal immigrants were made ineligible for Federal T ANF benefits. Major food assistance program changes passed in 1996 included reductions in food stamp benefits for able-bodied adults without dependents and elimination of Federal food stamps for most legal immigrants. (The President's 1998 Budget restores some immigrant FSP benefits.) In the welfare reform context, if lost food assistance and welfare benefits are replaced by increased earnings or other income, then net effects on dietary status may be more modest. If, however, food and welfare assistance losses are not offset, effects found here are likely to be illustrative. Methodology We use the Healthy Eating Index developed by the USDA Center for Nutrition Policy and Promotion as the indicator of individual and household overall diet quality. Based on the 1995 Dietary Guidelines for Americans and the Food Guide Pyramid (FGP), this index almost alone focuses on the consumption of foods rather than nutrients. Few indices focusing on the total diet exist ( 1 ,2, 17,21) and most of these-with the exception of Patterson et al.-focus exclusively on consumption of nutrients. The Healthy Eating Index has 10 equally weighted components, each based on different aspects of a healthful diet. The score of each component ranges between zero and 10 and the overall index, from zero to 100. The components can be grouped in terms of those that relate to adequacy or sufficiency, to moderation, and to variety in the diet. Specifically, Components 1 through 5 measure the degree to which a person's diet contains adequate servings of the 5 major food groups depicted in the FGP: Grains, vegetables, fruits, milk, and meats. Components 6 through 9 measure how well recommendations to moderate fat, saturated fat, sodium, and cholesterol are met. Component 6 is based on total fat consumption as a percentage of total food energy intake; component 7 is based on saturated fat consumption as a percentage of total food energy intake; component 8 is based on cholesterol intake; and component 9 is based on sodium intake. Finally, component 10 reflects the amount of variety in a person's diet. The HEI does not set overall limits on food energy consumed. 7 An individual's score in any of the food group components is based on the proportion of the recommended number of servings consumed for a given energy intake level. For instance, the average energy allowance for a 40-year-old female is 2,200 kilocalories, and the FGP indicates that at this energy level, 4 servings of vegetables per day are recommended. If a 40-year-old female consumes the recommended number of servings, she receives the maximum score of 10 in the vegetable category. A person who consumes the recommended number of servings from any food group receives a maximum component score of 10. A person consuming no servings from a food group receives the minimum score of zero. Between zero and 10, the component score is calculated proportionately; for example, a person needing 6 servings from the grain category who consumed only half that many would achieve a score of 5. Food serving amounts were computed from food consumption data using factors derived from the serving size assumptions given in the FGP. Calculation of scores for all food group (adequacy) components followed this procedure with actual servings compared with recommended servings based on the FGP. In each food group, once the maximum recommended number of servings is achieved, neither further credit nor penalties are awarded for additional servings consumed. Components 6 to 9 measure moderation in the diet and are scored differently. Component 6 reflects how well total fat is limited in the diet: A score of 10 8 means total fat intake as a proportion of energy intake is 30 percent or Jess. The score declines to zero when this proportion reaches 45 percent. Between these two points, the scores decline proportionately. The score for saturated fat (component 7) is computed analogously to that for total fat, with a maximum score achieved at a ratio of less than 10 percent of energy from saturated fat and zero when the ratio is 15 percent or greater. The component scores for cholesterol and sodium are each based on milligrams consumed. Cutoff points for a perfect score of I 0 are set at 300 mg for cholesterol and 2,400 mg for sodium. The corresponding zero points are 450 mg and 4,800 mg for cholesterol and sodium, respectively. Finally, the Dietary Guidelines, as well as the National Academy of Sciences' Diet and Health Report ( 16), stress the importance of variety in the diet to help ensure that people get the nutrients they need. To assess variety, counting the total number of different foods eaten by an individual that contribute substantially to meeting one or more of the 5 food group requirements is necessary. Foods consumed were counted only if they amounted to at least one-half serving in any one food group. Identical food items eaten on separate occasions are summed before imposing the onehalf serving cut-off. Similar foods such as two different forms of potatoes or two different forms of white bread count only once in the variety category. Mixtures are decomposed into constituent parts, meaning that a single food mixture (such as lasagna) could contribute 2 or more points to the variety index (contributing to both grain and meat, for example). In the variety category, a person attains a score of 10 if 16 or more different foods are eaten over a 3-day period. If 6 or fewer distinct foods are eaten over a 3-day period, the individual earns zero. Here again, little guidance was available to suggest upper or lower limits in scoring variety; similar to categories 6 to 9, the limits for variety were derived by exploration of the consumption data and consultation with researchers. For a more detailed description of the construction of the HEI, see Kennedy et al. or U.S. Department of Agriculture ( 12,22). Data Data used in this study were collected in USDA's Continuing Survey of Food Intakes by Individuals (CSFII) 1989-91. The CSFII provides ongoing data on food and nutrient consumption with a yearly sample of about 2,000 households containing about 5,000 individuals. In CSFII 1989-91, 3 days offood and nutrient intake data (a 1-day recall followed by a 2-day diary) were obtained along with relevant demographic, economic, and Federal food program participation data. Food and nutrient consumption data from a separate lowincome sample were also collected at the same time. The survey design was such that each year's data are nationally representative and can be used independently; however, the combined years provide a larger sample size. The lowincome sample can be combined with the all-income sample through the use of survey weights. These survey weights Family Economics and Nutrition Review also adjust the survey sample to be representative of the U.S. population living in households. This analysis uses lowincome households with complete data records in the combined 1989-90 sample (N=1,438); the HEI was not available for 1991. Low-income households were those with annual income of 130 percent or less of the poverty threshold. There were 418 households participating in the FSP at the time of the survey. Of those, 359 had every household member authorized to receive food stamps. The remaining 59 FSP households with one or more members not authorized to receive food stamps were excluded from the analysis so as not to confound the relationships because of possible lea~ge of benefits (i.e, use of food purchased with food stamps by nonauthorized household members). This resulted in a final sample size of 1,379 households. Statistical Model A set of 11 reduced form equations was estimated including one HEI equation and one equation each for the 10 component dietary scores. This Ad Hoc reduced form specification was guided by household production theory (6) and previous studies of food and nutrient consumption in order to estimate net effects of the independent variables on the HEI and its components (2,10,13). Because the household is the unit of analysis in this study, each household member's HEI and component scores are totaled. These aggregated scores are the dependent variables. Independent variables are annual household income as a percentage of the poverty threshold; participation in the FSP; the weekly dollar value of food stamps received; participation by one or more household 1998 Vol. 11 Nos. 1 &2 members in the WIC Program; household size in Thrifty Food Plan Male Adult Equivalents (TFP MAEs);1 headship status; the higher grade of formal schooling completed by either head of household; race; ethnic origin; geographic region and urbanization; and tenancy status. The number of household members who did not provide 3 days of dietary intake data, and thus lacked an HEI and component scores, was entered in the regression equation as an additional control. Because the HEI is, by construction, equal to the sum of its components, the 10 component equations' estimated coefficients were restricted to sum to the corresponding estimated coefficient of the HEI equation. This specification results in a potential gain in statistical efficiency. Restricted Ordinary Least Squares was used to estimate the models (9) and the SYSLIN procedure of the Statistical Analysis System (20) performed the estimation. Results Results include the means for the dependent and independent variables and the estimated regression coefficients as shown in table 2. The means are further subdivided by Food Stamp Program participation status. All means are weighted to represent population means of low-income households, and within those, of food stamp and nonfood stamp participating households. Means of the dependent variables are per person and are shown directly under the dependent variable name row. 1To account for the households' varying age/sex compositions, a "Thrifty Food Plan Male Adult Equivalent Scale" was constructed by dividing each household member's maximum allotment given by the Thrifty Food Plan by that of a male 20 to 50 years of age. Then, the household size in TFP MAEs was constructed by summing over all household members. ... the value of food stamps received exerts a positive and statistically significant effect on vegetables, dairy, meat, and sodium component scores .... [and] participation in the WIC program ... has a very strong positive effect on aggregate household diet quality .... 9 Table 2. Weighted means and regression coefficients estimating relationships between household-level Healthy Eating Index and its components by food stamp receiving households and value of food stamps received and WIC participation controlling for other relevant variables, CSFII1989-90 Mean All FSP NFSP N=l,379 N=359 N=l,020 HEI Grains Vegetables Mean for All 62.18* 5.95 5.66 Mean forFSP 60.70 5.86 5.29 Mean for NFSP 62.74 5.99 5.79 Intercept -12.69 -1.85 -0.06 0.00** 0.05 0.95 Income as percent of poverty threshold 81.89 65.71 87.93 -0.01 0.00 O.Ql 0.63 0.74 0.18 Food stamp participating household 0.27 1.00 -3.86 -0.28 -0.49 0.03 0.59 0.42 Weekly value of food stamps received 9.30 34.22 0.22 0.00 O.Q3 0.00 0.95 0.02 Household member participates in WIC 0.08 0.19 0.05 23.45 4.20 1.19 0.00 0.00 0.06 Household size in TFP MAEs 2.13 2.29 2.07 73.00 8.27 6.08 0.00 0.00 0.00 Dual-headed household 0.34 0.20 0.39 1.12 -1.30 1.66 0.54 0.01 0.01 Female-headed household 0.53 0.71 0.46 10.67 -0.19 0.92 0.00 0.67 0.07 Highest grade completed 10.59 10.16 10.76 0.81 0.04 0.00 0.00 0.39 0.97 African American 0.23 0.33 0.19 -5.16 -0.54 -0.65 0.00 0.15 0.12 Other race 0.06 0.08 0.06 -4.16 -0.29 0.25 0.05 0.64 0.73 Hispanic ethnic origin 0.11 0.11 0.11 4.11 -0.34 -0.81 0.01 0.47 0.13 Midwest 0.26 0.24 0.27 -2.50 0.11 -0.64 0.13 0.82 0.24 South 0.42 0.39 0.44 -5.20 -0.21 -0.56 0.00 0.63 0.28 West 0.18 0.13 0.20 -0.69 -0.24 -1.31 0.69 0.63 0.02 Suburbs 0.31 0.26 0.33 -0.64 -0.11 0.02 0.59 0.76 0.95 Nonmetro 0.28 0.25 0.30 -4.46 0.30 0.01 0.00 0.39 0.99 Household rents dwelling 0.55 0.77 0.47 -0.07 0.23 0.02 0.95 0.48 0.96 Occupies dwelling without payment 0.04 0.02 0.05 1.52 0.78 -0.04 0.54 0.28 0.96 Number with no HEI 0.43 0.55 0.39 -59.70 -6.54 -5.22 Adjusted R2 0.00 0.00 0.00 0.90 0.81 0.66 *Dependent variable means are per person with 3-day dietary intake data. **Numbers below estimated regression coefficients are prob values. 10 Family Economics and Nutrition Review Total Saturated Fruit Dairy Meat fat fat Cholesterol Sodium Variety 3.60 6.21 7.19 6.31 5.15 8.33 7.86 5.92 3.23 6.47 7.21 6.33 4.67 8.21 7.86 5.56 3.74 6.12 7.18 6.31 5.33 8.38 7.86 6.05 -3.18 -1.48 -1.62 0.12 2.70 -2.92 0.60 -5.00 0.02 0.24 0.09 0.93 0.06 0.02 0.60 0.00 0.01 0.00 0.00 -0.01 -0.01 0.00 -0.01 0.01 0.30 0.76 0.70 0.16 0.19 0.57 0.35 0.28 -0.06 0.32 -0.42 -0.38 -0.95 -0.65 -0.72 -0.23 0.94 0.65 0.43 0.58 0.24 0.37 0.26 0.74 -0.01 0.04 0.05 0.02 0.02 0.02 O.D3 0.02 0.73 0.03 0.00 0.35 0.45 0.23 0.03 0.30 2.79 3.35 2.25 2.33 -0.33 2.49 3.09 2.09 0.00 0.00 0.00 0.00 0.70 0.00 0.00 0.01 4.18 8.01 8.53 7.53 5.18 9.41 8.23 7.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.39 -1.10 0.41 -0.07 0.87 0.49 0.56 -0.02 0.61 0.12 0.45 0.92 0.29 0.50 0.38 0.98 1.63 -0.63 -0.40 1.11 0.96 3.04 3.39 0.84 0.01 0.29 0.38 0.06 0.16 0.00 0.00 0.16 0.19 0.22 0.05 0.04 -0.02 0.18 -0.18 0.30 0.00 0.00 0.34 0.48 0.78 0.00 0.00 0.00 -0.40 -2.70 1.06 -0.28 0.61 -0.96 -0.72 -0.57 0.45 0.00 0.01 0.56 0.28 0.06 0.11 0.26 -0.81 -3.26 -0.23 0.39 1.25 -0.91 0.64 -1.19 0.36 0.00 0.72 0.63 0.19 0.29 0.39 0.16 -0.59 -1.78 2.55 2.18 2.72 -0.08 0.18 0.08 0.38 0.01 0.00 0.00 0.00 0.90 0.75 0.90 -0.13 0.41 -0.45 -1.76 -1.79 0.84 0.81 0.12 0.85 0.52 0.35 0.01 0.01 0.20 0.16 0.86 -1.86 -1.43 0.37 -0.93 -0.41 0.23 0.59 -0.98 0.00 0.02 0.42 0.12 0.55 0.71 0.28 0.10 1.10 -0.37 -0.98 -0.74 -0.86 0.05 2.25 0.40 0.13 0.58 0.06 0.26 0.27 0.94 0.00 0.56 1.09 -0.15 -0.32 0.05 -0.84 -0.03 -0.18 -0.18 O.D3 0.75 0.36 0.92 0.12 0.95 0.67 0.71 0.03 -1.27 0.16 -0.15 -0.15 -2.08 -1.26 -0.05 0.96 0.01 0.66 0.75 0.78 0.00 0.00 0.92 -0.30 0.16 0.78 -0.08 -0.68 -0.16 -0.04 0.00 0.52 0.71 0.02 0.85 0.17 0.72 0.91 1.00 0.37 -0.08 0.22 1.01 0.61 -0.60 -1.17 0.44 0.72 0.93 0.77 0.29 0.58 0.54 0.18 0.65 -3.65 -6.65 -7.15 -6.25 -4.46 -7.17 -6.27 -6.35 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.35 0.70 0.83 0.68 0.43 0.74 0.74 0.67 1998 Vol. 11 Nos. 1&2 11 The average low-income household in the United States had a household-level HEI of 62.18. Food stamp households have slightly lower means at 60.70, whereas nonparticipant households are slightly higher at 62.74. With regard to components, the lowest overall component score is for fruits (3.60 of 10), and the best component score is for cholesterol (8.33). Food stamp households have lower mean component scores than do low-income nonfood stamp households for all components except dairy, meat, and fat. Food stamp households have lower mean component scores for fruit (they eat too few servings) and for saturated fats (they receive an excessive percentage of calories from saturated fats). These correspond to the highest and lowest values for the general population ( 12). Sample means for the independent variables help characterize the groups. The means of the dummy (zero-1) variables reflect the proportion of the population with a particular characteristic, for example, the proportion of female-headed food stamp households is 71 percent, compared with 53 percent of all lowincome households and 46 percent of nonfood stamp households. The mean income of food stamp households expressed as percent of the poverty threshold was substantially less than nonfood stamp low-income households (65.71 percent versus 87.93 percent). The average household size in TFP MAEs was 2.13, with food stamp participating households slightly larger at 2.29 than nonfood stamp households, at 2.07. The proportion of food stamp households with at least one member participating in the WIC program is 19 percent. Food stamp households receive food stamps valued at $34.22 per week, on average. 12 Regression results for the 11 equations are also shown in table 2. Unlike the means, these regression results are not weighted, since many of the variables used to construct survey weights are included in the equations ( 8). Estimated regression coefficients are shown for each independent variable for each of the 11 diet quality measures. The level of statistical significance (prob-value) of each estimated regression coefficient is shown directly underneath the coefficient. Interestingly, regression results indicate that the estimated effect of household income on the diet quality of the sample households was not significant at conventional levels of statistical significance. Recall that average household income as a percent of the poverty threshold for food stamp receiving households was 65 .71, substantially lower than that of the nonfood stamp households (87.93). The estimated coefficient on the food stamp participation variable is interpreted as the effect on the level of the dependent variable (HEI or HEI component) that a food stamp participating household (27 percent of households) with value of food stamp benefits equal to zero would have, other things equal. The estimated coefficient on the food stamp participation variable is negative for the HEI and all components but dairy. However, it is only significant for the HEI at the 0.03 level of statistical significance. By contrast, the value of food stamps received has a substantial and statistically significant effect on overall diet quality, controlling for other relevant factors. For each additional dollar of food stamps received, the aggregate household HEI score increases by an estimated 0.22 points. At the average weekly food stamp value of $34.22, the aggregate household HEI increases 7.5 points, on average. However, since food stamp households "start" at an HEI about 3.86 points lower than similarly situated nonfood stamp households, the net effect of food stamp participation on aggregate household HEI is about 3.7 points,2 on average. Not surprisingly, the positive nutritional effect of food stamp participation is larger for higher levels of food stamps, but lower for lesser food stamp benefit values. A break-even point is estimated at $17.54 per week. That is to say, when weekly household food stamp benefits are at least $17.54, food stamp participants demonstrate superior diet quality to similarly situated nonprogram participants. At a food stamp value of ($3.86/.22) $17.54 per week or lower, food stamp participants have diet quality inferior to nonparticipants. Thirty-two percent of Food Stamp Program participating households received food stamps valued at less than $17.54 per week. With regard to the HEI components, the value of food stamps received exerts a positive and statistically significant effect on vegetables, dairy, meat, and sodium component scores. Turning to WIC, results suggest that participation in the WIC program by one or more household members has a very strong positive effect on aggregate household diet quality measures, controlling for other factors. WIC participation alone contributes 23.45 points to the aggregate household HEI score 2The estimated coefficient of 3.86 is significant at the 0.03 level of statistical significance. However, given that no adjustments for survey design effects were made in estimating standard errors of the coefficients, it could be statistically insignificant. In fact, when the HEI equation is estimated independently from those of its components, the estimated coefficient on the food stamp value remains at 0.22 points and is significant, but the food stamp participation dummy variable coefficient is not significant. Family Economics and Nutrition Review (controlling for household size among other variables). This overall effect is distributed about evenly in all diet quality components except for vegetables and saturated fat, where the estimated coefficients are not statistically significant. The possibility that WIC participation may improve household scores for some diet components not included in the WIC food package, for example, fruits3 and possibly vegetables, is interesting and may be explained in several ways. One is that consumption of the WIC food package (by those for whom it was intended, and possibly their families) improves diet quality scores for the types of foods that it includes, for example, dairy products and grains, as well as frees up food stamps and money income to purchase more of all foods for the household. Another, more general, explanation is that households that participate in the WIC Program are more health and nutrition oriented than are other households, including households receiving only food stamps. Finally, the nutrition education received as part of participation in the WIC Program is likely to improve diet quality through better diet-related behaviors. Only a minority (34 percent) of lowincome households was dual-headed, with food stamp participating households less likely to have both male and female heads (20 percent) than were nonparticipating low-income households (39 percent). Seventy-one percent of food stamp households were headed by a female head only, compared with 46 percent for nonfood stamp households and 53 percent for all low-income households. Compared with female- 3 The exception is fruit juice, which is included in WIC packages. 1998 Vol. 11 Nos. 1 &2 headed households, dual-headed households have lower grains scores and higher vegetable scores, on average. Female-headed households have much higher HEI, cholesterol and sodium scores, and somewhat higher fruit and total fat scores than comparable maleheaded households. The mean highest grade of formal schooling completed by the household head was 10.59 years. Food stamp and nonfood stamp households differed little in average years of education. Regression results show that years of education has a positive and statistically significant effect on overall diet quality. Every additional grade completed increases the household HEI score by 0.81 points. Years of education has a small positive effect on fruit, dairy, and cholesterol scores, and a small negative impact on the sodium score. Thirty-three percent of the food stampreceiving households were African American, 8 percent were of other race, and the remaining 59 percent were White. The corresponding figures for nonfood stamp households were 19 percent African American, 6 percent other, and 75 percent White. African American households have, on average, a lower household HEI by 5.16 points than comparable White households. They also have lower dairy and higher meat scores than White households. Race does not appear to have significant effects on most of the diet quality component measures. Hispanic households, at 11 percent of households, have substantially higher HEI scores than non-Hispanic households (4.11 points). They have higher total fat and saturated fat scores, but lower dairy scores than non-Hispanic households. Geographic location and urbanization status have few statistically significant effects on the HEI and its components. Households in the Midwest (24 percent of food stamp and 27 percent of nonfood stamp households) have poorer total fat and saturated fat scores than those in the East. Households in the South (39 percent of food stamp and 44 percent of nonfood stamp households) have lower fruit and dairy scores than those in the East. Households in the Western United States (13 percent of food stamp and 20 percent of nonfood stamp households) have lower vegetable and higher sodium scores than similar households in the Eastern region of the United States. Households in the suburbs (26 percent of food stamp and 33 percent of nonfood stamp households) have better fruit scores, while households in nonrnetro areas (25 percent of food stamp and 30 percent of nonfood stamp households) have lower HEI, dairy, cholesterol, and sodium scores than similar households in the central city. Tenancy status has no significant effects on HEI or its components scores. The only exception is for households that rent their dwelling (77 percent of food stamp and 47 percent of nonfood stamp households), which have a better meat score, compared with those households that own their dwelling. As expected, the control variable for the number of household members with no computable HEI score has an extremely strong and statistically significant negative association with the total HEI score and its components. This control variable is also responsible for the relatively high R-squared values. 13 Limitations Severallintitations are relevant when interpreting the results. First, our study is exploratory; however, household production theory and past analyses of the demand for foods or nutrients guided model specification and the selection of variables (8). Thus, the possibility of comntitting gross errors is reduced. Several problems remain, however. A major limitation is that the Restricted Ordinary Least Squares reduced form specification is used as opposed to a system of simultaneous equations reflecting the usual derived demands for inputs in the household production function, the household production function itself, and the final demand for health and healthy eating. The range of the dependent variables is constructed between zero and 100 for the HEI and zero and 10 for its components, which may imply the usual estimation problems with linear probability models (9). Because an HEI is not computed for children below the age of 2 years and for infants, they are necessarily excluded from the household aggregates of the dependent variables. This could distort results, to some extent. We did not explicitly account for the survey's clustered design effects on statistical hypothesis testing. Thus, estimated "prob" values between 0.05 and around 0.01 could result in either acceptance or rejection of the null hypothesis, if tested to account for design effects. As several variables of potential importance in influencing "healthy eating" are not available (for example, taste of particular foods, the present value of future health outcomes, etc.) and, as there may be self-selection relative to 14 the FSP or WIC participation, the results may well suffer from specification biases. 4 Despite these limitations, this study provides valuable new insights into the relationship between food assistance program participation and diet quality. Summary and Conclusions In this study, we estimated a statistical model using the USDA Healthy Eating Index and its 10 components at the household level as dependent variables to better understand the effects of food assistance program (FSP and WIC) participation and food stamp benefit levels on the diet quality of low-income households (controlling for intervening factors). Independent variables included relevant socioeconomic variables available in the CSFII. As is typical of such studies, selection of independent variables was heavily influenced by their availability. The interpretation of their estimated coefficients can vary substantially depending on the theoretical model the researcher believes is most appropriate for the task at hand. Here, we were broadly guided by well-known household production theory and past research in selection of variables. A novel contribution to the literature is that the HEI and its components aggregated to the household level were the dependent variables. Thus, effects of FSP and WIC participation on a household level measure of the overall diet and, at the same time, its components, could be estimated. "Typically, in situations such as this, a statistical correction for self-selection bias is performed. However, the procedure requires identification of variables that are highly correlated with the decision to participate in the program but not with diet quality. In practice, such variables are not readily available (see reference 4). Results tend to be in general agreement with previous studies of diets that were based on components of the total diet, mostly nutrient intakes. These results reaffirm the effectiveness of two of the main food assistance programs, the FSP and the WIC in meeting nutritional needs of low-income households, needs that may continue after welfare reform. On average, the estimated effect of Food Stamp Program participation on the overall diet of participating households is positive. The effect increases with increased value of food stamps received, as intended. In terms of its effect on HEI components, the Food Stamp Program had statistically significant and positive effects on the consumption of vegetables, dairy, and meat products, as well as on sodium component scores. Assuming that ablebodied adults without dependents or immigrants have sintilar HEI and component consumption responses to food stamp income, removal from the Food Stamp Program would result in a reduction in these scores, unless food stamp income is replaced by earned or other income. Participation in the WIC Program by household members improved household level HEI scores dramatically. In addition, WIC participation resulted in improved scores for all HEI components except for saturated fat. Positive effects reflect the value and increased availability of in-kind foods found in the WIC food package coupled with beneficial effects of the nutrition education component of the WIC Program. Family Economics and Nutrition Review References 1. Abdel-Ghany, M. 1978. Evaluation of household diets by index of nutritional quality. Journal of Nutrition Education 10(2):79-81. 2. Basiotis, P.P., Guthrie, J.F., Bowman, S.A., and Welsh, S.O. 1995. Construction and evaluation of a Diet Status Index. Family Economics and Nutrition Review 8(2):2-13. 3. Basiotis, P.P., Johnson, S.R., Morgan, K.J., and Chen, J.-S.A. 1987. Food stamps, food costs, nutrient availability, and nutrient intake. Journal of Policy Modeling 9:383-404. 4. Burtless, G. 1995. The case for randomized field trials in economic and policy research. Journal of Economic Perspectives 9(2):63-84. 5. Cronin, F.J. 1980 (Spring). Nutrient levels and food used by households, 1977 and 1965. Family Economics Review, pp. 10-15. 6. Deaton, A. and Muellbauer, J. 1980. Economics and Consumer Behavior. Cambridge University Press, New York. 7. Devaney, B., Haines, P., and Moffitt, R. 1989. Assessing the Dietary Effects of the Food Stamp Program-Volumes I and II. U.S. Department of Agriculture, Food and Nutrition Service, Alexandria, VA. 8. DuMouchel, W.H. And Duncan, G.J. 1983. Using sample survey weights in multiple regression analyses of stratified samples. Journal of the American Statistical Association 78( 383 ):535-543. 9. Fomby, T.B., Hill, C.R., and Johnson, S.R. 1984. Advanced Econometric Methods. Springer-Verlag, New York. 10. Fraker, T.M. 1990. The Effects of Food Stamps on Food Consumption: A Review of the Literature. U.S. Department of Agriculture, Food and Nutrition Service, Alexandria, VA. 11. Kennedy, E. T. 1997. Intervention strategies for undernutrition. In F. Bronner (Ed.), Strategies for Improving Undernutrition (Chapter 6). Spring Press, Hartford. 12. Kennedy, E.T., Ohls, J., Carlson, S., and Fleming, K. 1995. The Healthy Eating Index: Design and applications. Journal of the American Dietetic Association 95(10). 13. Kramer-LeBlanc, C.S., Kennedy, E.T., and Basiotis, P.P. 1997. Food expenditure and nutritional implications of the Personal Responsibility and Work Opportunity and Reconciliation Act of 1996. American Journal of Agricultural Economics 79(4):105-112. 1998 Vol. 11 Nos. 1 &2 15 16 14. Levedahl, J.W. 1995 (November). A theoretical and empirical evaluation of the functional forms used to estimate the food expenditure equation of food stamp recipients. American Journal of Agricultural Economics, Vol. 77. 15. Morgan, K.J. 1986. Socioeconomic factors affecting dietary status: An appraisal. American Journal of Agricultural Economics 68(5): 1240-1246. 16. National Academy of Sciences, National Research Council, Food and Nutrition Board. 1989. Diet and Health: Implications for Reducing Chronic Disease Risk. National Academy Press, Washington, DC. 17. Patterson, R.E., Haines, P.S., and Popkin, B.M. 1994. Diet quality index: Capturing a multidimensional behavior. Journal of the American Dietetic Association 94(1):57-64. 18. Rose, D., Habicht, J-P., and Devaney, B. 1998. Household participation in the Food Stamp and WIC Programs increases the nutrient intakes of preschool children. Journal of Nutrition 128:548-555. 19. Rossi, P.H. 1996. Feeding the poor: Five Federal nutrition programs; food stamps, WIC, school lunch, school breakfast, and child care. Report submitted to The American Enterprise Institute. Social and Demographic Research Institute, University of Massachusetts, Amherst, MA. 20. SAS User's Manual, Version 6. SAS Institute, Research Triangle Park, NC. 21. Sorenson, A.W., Wyse, B.W., Wittwer, A.J., and Hansen, R.G. 1976. An index of nutritional quality for a balanced diet. Journal of the American Dietetic Association 68:236-242. 22. U.S. Department of Agriculture, Center for Nutrition Policy and Promotion. 1995. The Healthy Eating Index. Report No. CNPP-1. 23. U.S. Department of Agriculture, Food and Nutrition Service. 1998. Administrative data. 24. U.S. Department of Agriculture, Food and Nutrition Service, Office of Analysis and Evaluation. 1996, July. Administrative data, "FY 1995 WIC Food Package Cost Analysis Estimated Average Monthly Food Package Cost for Participants in Dollars." 25. U.S. Department of Agriculture, Human Nutrition Information Service. 1992. The Food Guide Pyramid. Home and Garden Bulletin No. 252. 26. U.S. Department of Agriculture and U.S. Department of Health and Human Services. 1995. Nutrition and Your Health: Dietary Guidelines for Americans. Home and Garden Bulletin No. 232. Family Economics and Nutrition Review 1998 Vol. 11 Nos. 1&2· Household Food Security in the United States in 1995: Results From the Food Security Measurement Project Margaret Andrews Gary Bickel Steven Carlson Office of Analysis and Evaluation Food and Nutrition Service U.S. Department of Agriculture The need for a reliable measure of U.S. hunger and food insecurity has been recognized since the early 1980's. This paper describes the development of such a measure and presents initial findings from data collected for USDA by the Census Bureau. A unidimensional scale of severity, based on survey responses, was used to identify food security status; household weights were then applied to estimate the prevalence of food insecurity and hunger in three designated severity ranges. The large majority of American households (88 percent) were food secure in the year ending April 1995. Hunger was evident in 4.1 percent of all households. The paper concludes with a discussion of future nutrition monitoring and research directions for food security measurement. espite the recent economic recovery that has lowered unemployment and poverty rates in the United States, many American families still struggle to meet basic needs. This was the context for Vice President Gore's announcement in September 1997 at the National Summit on Food Recovery and Gleaning of new U.S. Department of Agriculture (USDA) estimates of the extent of food insecurity and hunger in U.S. households. Based on a state-of-the-art measurement method developed through a broad collaborative effort, the new estimates indicate that nearly 12 million households experienced food insecurity in the 12 months prior to April1995, while one or more persons i~ about 4 million of these food-insecure households experienced hunger due to resource constraints during the period. Although efforts to estimate the level of hunger in the United States have been made previously (7,10,28,31,33), the new USDA estimates are the first based 17 upon specially designed data collected from a large, nationally representative sample and subsequently validated to show strong statistical properties of internal validity and reliability. The new estimates thus represent the first reliable, standard national measure of food insecurity and hunger for the United States. The availability of a standard national measure of hunger and food insecurity provides a powerful tool for monitoring changes in the food situation of U.S. households. It may be particularly useful in tracking the effectiveness of the Federal Government's efforts through food assistance and food recovery programs to help ensure that all Americans are able to obtain adequate food. In a time of tight Federal budgets and with welfare reform shifting increased responsibility for social welfare to the States, this monitoring function is especially important. This paper provides a brief introduction to the genesis of the new measure, including its conceptual basis and methodology, presents brief summary findings from the baseline estimates for 1995, and discusses implications of the measure for future research on family nutritional and general well-being. Background Federal interest in developing a hunger measure can be traced from at least 1984 when the President's Task Force on Food Assistance recognized the distinction between the concept of hunger in the traditional medical usage and a more socially oriented, common-sense meaning. The report noted: "To many people hunger means not just symptoms that can be diagnosed by a physician, it 18 bespeaks the existence of a social, not a medical, problem: a situation in which someone cannot obtain an adequate amount of food, even if the shortage is not prolonged enough to cause health problems" (23 ). The Task Force also noted the absence of any reliable measure of hunger in this latter commonly understood meaning and the resulting inability of policymakers to verify or negate claims of increasing hunger. This lack of an accepted standard measure of hunger prevalence was cited by the Task Force as posing a continuing policy conundrum. After the 1984 Task Force report, State and local researchers increased efforts to develop soundly based survey measures (22). The Food Research and Action Center sponsored and obtained major funding for the Community Childhood Hunger Identification Project (CCHIP) ( 12,30-32) and researchers at the Cornell University Division of Nutritional Sciences sought to develop independent hunger scales (8,25,26). At the Federal level, USDA began the process, in the mid 1980's, of analyzing the significance of the single survey question on the adequacy of household food supplies that had been added to its regular national food consumption surveys beginning in 1977 but had not been analyzed in depth ( 4,11 ). A similar household food sufficiency question and several others adapted from the CCHIP instrument were included in the Third National Health and Nutrition Examination Survey sponsored by the National Center for Health Statistics (NCHS) ( 1,6). Finally, the Federal Government's commitment to develop a standardized measure of food insecurity or food insufficiency for the United States took definitive shape in 1990-92 when USDA's Food and Nutrition Service (FNS)1 and NCHS were assigned joint responsibility to carry out this task under the Ten-Year Comprehensive Plan for the National Nutrition Monitoring and Related Research Program (NNMRRP) Act of 1990. FNS took lead responsibility for developing the measures; it established an Interagency Working Group for Food Security Measurement to maintain a collaborative process for the project. As a key part of its conceptual basis, the project adopted the authoritative definitions of food insecurity and hunger developed by a special expert panel convened by the American Institute of Nutrition (AIN) and reported by the Life Sciences Research Office of the Federation of American Societies for Experimental Biology ( 3 ). According to these definitions, food insecurity occurs when a household does not have access to enough food, at all times, for an active, healthy life. Hunger, defined as "the painful or uneasy sensation that results from not having enough food" is a potential but not necessary consequence of food insecurity. 2 1 FNS was renamed Food and Consumer Service (FCS) in 1994 in the context of broader USDA agency reorganizations. The original name was restored in December 1997. 2For a description of the conceptual basis of the Government's measure, including its debt to the body of prior research and an extensive bibliography of the literature to that point, see reference 5. For further discussion of this conceptual basis and its operationalized form and testing in the Government's new measure, see references 14, 15, and 24. For recent validation studies and related work within the same general approach, see references 2, 13, 16-18, and 21. Family Economics and Nutrition Review Methods The subsequent operational development of the hunger and food security measure was also a broad-based, cooperative venture. At an early stage, FNS enlisted the expertise of the Census Bureau for developing and administering a national food security questionnaire. In January 1994, FNS and NCHS jointly sponsored a Conference on Food Security Measurement and Research, bringing together a wide range of experts in the field. Participants discussed their previous experiences with measuring hunger and food insecurity and then organized into working groups to provide continuing advice and critique to FNS in developing a baseline draft questionnaire (29 ). In the next stage, the Census Bureau worked closely with FNS and its collaborators to analyze, field test, and refine the food security questionnaire. The draft version from the research conference was revised after review by an expert panel convened by the Census Bureau's Center for Survey Methods Research. The questionnaire was field tested and analyzed in the autumn of 1994 (27) and, with some further revision, was administered for the first time as a Supplement to the Current Population Survey (CPS) in April1995. With minor revisions, the food security supplement was administered with the CPS again in September 1996 and April 1997. The data collection in April 1995 produced some 45,000 usable interviews. In September 1995, FNS contracted with Abt Associates, Inc. (Abt) to analyze these data in a cooperative venture with FNS staff and other researchers involved in developing the questionnaire. From the beginning, 1998 Vol. 11 Nos. 1&2 FNS expected the analysis to produce a scaled measure of food insecurity and hunger that would allow the government to identify households experiencing problems providing adequate food for all members.3The Abt team was selected because it had developed an innovative analysis design that applied state-of-theart scaling methods that were used most widely in the educational testing industry. (See reference 15 for technical details of the scale estimation.) The initial Abt procedure used standard factor analysis techniques to perform a systematic set of exploratory analyses of the 1995 survey results. The preliminary work found that, with one important area of exception, most of the food security indicators in the questionnaire fit a single-dimensional measurement scale. A few items failed to meet the rigorous fit criteria for inclusion and were dropped from the scale. However, one general type of indicator also did not fit the single-dimensional measure of severity of food insecurity: those items dealing with the coping strategies that a food-insecure or at-risk household might engage in to improve its food supply from emergency sources (e.g., getting food from a food bank or borrowing money for food). This is understandable given that all households do not face the same set of choices for coping with an inadequate food supply. 3The choice of household-level as opposed to family-level unit of analysis was due in part to the sampling frame of the Current Population Survey; it also reflects the objective of developing a comprehensive measure encompassing the entire U.S. residential population. In the March 1995 CPS sample, 70 percent of households were family households including two or more persons residing together and related by birth, marriage, or adoption; 20 percent were single-person households; and 5 percent consisted of two or more unrelated persons residing together. ... food insecurity occurs when a household does not have access to enough food, at all times, for an active, healthy life. Hunger, defined as "the painful or uneasy sensation that results from not having enough food" is a potential but not necessary consequence of food insecurity. 19 Once it was established that a core set of food security and hunger items could be scaled along a single dimension, subsequent analyses used the Rasch model, conceptually the most basic form within the general class of item-response-theory (IRT) statistical scaling models. Initially the Rasch model was applied to a subset of the sample including only households with children. The resulting scale was subjected to further analyses that showed it to be robust for other household types as well. Various reliability indicators were calculated and found to be within accepted ranges.4 Item response stability measures for individual items on the scale and for the overall scale were judged to be acceptable by the Census Bureau using data from some 1,100 quality control re-interviews that were performed in the week following the regular Apri11995 CPS interviews (20).5 4 A general discussion of potential sources of error in the food security measure is presented in the Summary Report volume ( 14). More extensive tteatment is provided in the Technical Report ( 15). Based on three traditional measures of reliability (Speannan-Brown's and Rulon's split-half reliability estimates and Cronbach's alpha), the estimated reliability values ranged from .86 to .93 for the 12- month measurement scale. Since the distribution of household scale scores is highly skewed (56.5 percent of sample households passing the income and food security screener had zero score), a further dichotomized split-halftest was conducted, collapsing the split-half scales into the dichotomous variable "answered all questions negatively" and "answered one or more questions affirmatively." On this test, the level of agreement between paired subscales was 84.8 percent for households with children and 85.8 percent for households without children, while the corresponding kappa statistic (showing the extent of agreement beyond mere chance) was .70 and .69 for the respective household types. 20 Table 1. Sequenced items and food security status categories for food security measurement scale Sequenced questions in scale Q53 Worried food would run out Q55 Unable to afford balanced meals Q58 Child fed few low-cost foods Q24 Adult cut size or skipped meals Q56 Couldn't feed child balanced meals eat less than felt Food security status Food secure Food insecure Adult cut size or skipped meals, 3+ months Child not eating enough Food insecure with moderate hunger Adult hungry but didn't eat The 18 items included in the scale are shown in abbreviated form in table 1 with their original question numbering. The scale items are ordered according to increasing levels of severity. The least severe items (Q53 and Q54) ask whether the household respondent has 5Jn this analysis of response variance, 17 percent of the continuous variables and 9 percent of the categorical questions with enough cases to be analyzed exhibited "low" variance, 75 percent and 68 percent respectively showed "moderate" variance, and 8 percent and 24 percent showed "high" variance. Thus, 76 to 92 percent of the two question types exhibited "low to moderate" response variance while the food insecurity scale overall showed "moderate" response variance. The authors noted, "(t]his distribution is typical of response variance results for households surveys" (20 ). worried about or experienced a situation within the past 12 months where food was running out, and there was no money to buy more. Subsequent items indicating experiences or perceptions of inadequate food intake in terms of both quality and quantity (Q32, Q55, Q56, Q57, Q58) fall in the low to intermediate ranges of severity measured by the scale. Items dealing with reduced food intakes and hunger for adults (Q24, Q25, Q35, Q38) fall in the intermediate range of severity measured, and those indicating reduced food intakes and hunger for children in the household (Q40, Q43, Q44, Q47, Q50) or more severe hunger for adults (Q28, Q29) fall at the severe end of the scale. All items refer to the 12-month Family Economics and Nutrition RevieW period preceding April1995, and all ask respondents to report only experiences, perceptions, or behaviors that result from a lack of financial resources. Thus, instances of hunger or meals skipped due to dieting, illness, or busy schedules are excluded by design. Each household in the sample received a scale score between zero and 10 under the Rasch measurement model, based on its particular pattern of responses to all 18 items. These detailed household scores indicate the distinct levels of severity of food insecurity experienced by U.S. households across the full range of severity captured by the measure. The scaled measure provides much greater detail about the nature and extent of this poverty-linked phenomenon than ever before available. However, the very detail of the nearly continuous severity measure makes it inappropriate to serve, in itself, as a useful measure of the prevalence of food insecurity and hunger. For this purpose, several well-defined, broad subranges of severity level need to be designated and a simpler, categorical measure created based on these specified severity ranges. To provide this second type of measure, FNS worked with Abt and other collaborators to develop a categorical measure that would classify the food security status of households in terms of several broad subranges of the measured severity levels indicated by their scale scores ( 15 ). The four designated status categories are illustrated in table 1. Households with complete responses to all 18 items were classified as food secure if the respondent answered affirmatively to fewer than 3 of the 18 questions on the 1998 Vol. JJ Nos. 1 &2 scale,6 while those with 3 or more positive responses were assigned to one of the food-insecure groups. Those with 3 to 7 positive answers were classified as food insecure without evident hunger, those with 8 to 12 as food insecure with moderate hunger, and those with 13 or more as food insecure with severe hunger. Locating the initial threshold (scale cutpoint) of each designated severity-range category was done by identifying the second or third item in sequence indicative of the salient conditions characterizing the category.7 It should be noted that the main role of the categorical measure is to provide an established, consistent basis for comparison of food insecurity and hunger prevalence over time and across population subgroups. In this sense, the exact placement of the category boundaries (scale-score cutpoints, in operational terms) is a matter primarily of identifying severity-range categories that have relevance to ongoing program objectives and policy discussion. In a deeper sense, locating the category boundaries or thresholds is a matter of identifying the 6.Two groups of households were classified as food secure on the basis of zero scale scores: higher income households (~185 percent poverty) that were screened from the food security portion of the interview on the basis of consistent negative responses to three broad food security screening questions, and both high- and low-income households that passed the screener but then gave no affirmliive response to any food security scale item. 7.ln contrast to the underlying scale estimation, which is fully detennined by the measurement model and the data, locating the designated category thresholds involved judgment as to how many indications of a given severity subrange should be present and across how broad a range of measured severity they should be observed. ... food insecurity is more prevalent among Black and Hispanic households (almost twice the levels for Whites), households with children, households under the poverty level, and households in central city metropolitan areas. 21 important distinctions (conceptual and in reality) between the several subranges of severity level encompassed within the full range of food insecurity observed for contemporary U.S. households.8 The sequenced pattern of items on the scale reflects the underlying commonality among otherwise diverse households of the conditions and experience of food insufficiency in relation to basic need and the available set of potential household responses to such conditionswhat Radimer termed "hunger as a managed process." In measurement terms, this predominant sequential response pattern means that the typical household answering positively to any given scale item will also have answered affirmatively to all less severe items. For the entire CPS sample, 76 percent of households exhibited this common ordering of responses and were termed the "modal group" of households. While not all the April 1995 respondents followed this common ordering pattern perfectly, most of the non-modal households did not diverge very far from the common pattern. 9 8The names applied to the designated severity level subranges, or food insecurity status categories, are nominal only and intended to reflect U.S. social reality as articulated; for example, in the 1984 President's Task Force Report on Food Assistance. Clearly, the names chosen for relevance to the U.S. context are not intended to suggest, and do not reflect, the much deeper severity ranges of food insecurity and hunger that are relevant to underdeveloped countries subject to famine conditions. In principle, the form of measurement scale developed from contemporary U.S. data could be extended, with a similar data set collected in poorer countries, to encompass the deeper levels of food insecurity and hunger severity experienced in those circumstances within the same unidimensional measurement construct. For a similar food-security scale developed for urban subsistence dwellers in Kampala, Uganda, see reference 19. 22 Figure 1. Item response patterns for food security status groups 053 055 054 058 024 032 057 038 028 029 044 056 025 035 040 047 043 050 Fl* - Food Insecure The response patterns for the four food security status groups are illustrated in figure 1 where the questions in the scale are ordered sequentially and the proportion of affirmative responses to each item within each status group is projected onto the vertical axis. Overall, the response pattern shows the expected contrast among the food security status groups. 90f those households with at least one positive response to a scale item, the proportion following the modal pattern was only 32 percent for households with children and 48 percent for households without children. Nonetheless, the fit statistics produced in estimating the Rasch model indicate an acceptable degree of conformance of their responses to the modal pattern. Detailed analysis of the non-modal response patterns is one of the areas of research now opened up and expected to be fruitful in helping identify constellations of conditions and behaviors occurring in highly stressed household settings. Findings By classifying survey responses according to food security status and applying household weights provided by the Census Bureau, Abt used the supplement data to estimate the prevalence of food insecurity and hunger within the specified severity range categories in the United States for the 12 months preceding the April 1995 survey. As can be seen in figure 2, the large majority of American households (88 percent) were found to be food secure in the year ending April 1995. About 11 .9 million (of approximately 100 million) households experienced food insecurity as a consequence of limited resources during that period. Family Economics and Nutrition Review Figure 2. Distribution of U.S. Households, by food security status level, 1995 Table 2 shows that household food insecurity is more prevalent among Black andHispanic households (almost twice the levels for Whites), households with children, households under the poverty level, and households in central city metropolitan areas. D Food secure II Food insecure - No hunger evident • Food insecure - Moderate hunger • Food insecure - Severe hunger The number of households where hunger due to inadequate resources 88.1 o/o was experienced during the period can Most of the food-insecure households were food insecure without hunger (7.78 million households), meaning that they reported experiencing concerns about the adequacy of their food supply, substituted cheaper food items, and reduced the quality and variety of their diets, but without significantly reducing food intakes. There were 3.34 million households classified as food insecure with moderate hunger, where some reduction in food intake due to inadequate household resources was evident for one or more household members, Primarily adults. 1998 Vol. 11 Nos. 1&2 be estimated by combining the number of households assigned to the two most severe levels of food insecurity. This yields an overall estimate of 4.16 million households where one or more members 0.8o/o experienced some level of hunger in the 12-month period preceding the April1995 3.3% survey. An additional 817,000 households were identified as food insecure with severe hunger. In these households, reductions in food intake were observed for both children and adults, and one or more of the adults was likely to have experienced an extensive reduction in food intake (i.e., going whole days without food) du e to m. ad e quate resources. 10 10-For the modal household group, children's hunger indicators appear only within the severe hunger range of household level food insecurity measured by the scale. Among the non-modal households, however, children's hunger may appear within other food insecure categories as well. Analysis of the CPS data is continuing to identify the extent of such cases. The number of individuals affected by hunger is not easily extrapolated from these estimates. Because the data were collected in a household survey, homeless individuals are not included. Furthermore, for many households (i.e., those with more than one adult or with more than one child), the structure of the questionnaire does not allow accurate determination of the food security status of each adult or each child in the household. An upper bound for the number of individuals affected by hunger is given by the total population of persons living in those households that were classified into either of the two hunger categories. From the Apri11995 survey, this number is 11.2 million individuals, most of them adults. For most of the food insecure households with children (and for all such households fitting the modal response pattern), the children are not likely to be seriously affected unless the household has reached the overall severity level required to classify it as experiencing food insecurity 23 Table 2. Prevalence of household food security status, by selected characteristics, 1995 Food insecure- Food insecure- Food insecure- Characteristics Food secure without hunger moderate hunger severe hunger Number Percent Number Percent Number Percent Number Percent All households 88,266 88.1 7,783.4 7.8 3,343.3 3.3 816.8 0.8 Household composition Household with children under age 18 31,434 82.5 4,676.2 12.3 1,670.6 4.4 331.9 0.9 Household with elderly but no children 26,155 94.1 1,124.1 4.0 436.2 1.6 89.9 0.3 Household with no children or elderly 30,677 89.5 1,983.1 5.8 1,236.4 3.6 394.9 1.2 Race/ethnicity White 76,129 90.0 5,653.7 6.7 2,298.1 2.7 534.0 0.6 Black 9,104 75.8 1,779.4 14.8 895.4 7.5 233.8 1.9 Other 3,032 84.6 350.6 9.8 150.1 4.2 49.4 1.4 Hispanic1 5,725 74.3 1,360.2 17.7 501.0 6.5 115.6 1.5 I ncome-to-poverty rati.O 2 Under 0.50 3,240 58.4 1,365.0 24.6 688.4 12.1 270.9 4.9 Under 1.00 10,230 64.7 3,500.7 22.1 1,587.6 10.0 489.5 3.1 Under 1.30 14,841 68.1 4,367.9 20.0 2,032.7 9.3 567.7 2.6 Under 1.85 25,914 73.8 5,952.6 17.0 2,568.0 7.3 680.4 1.9 Over 1.85 62,352 95.8 1,830.8 2.8 775.3 1.2 136.3 0.2 Area of residence Central city metropolitan area 20,172 83.9 2,494.4 10.4 1,102.5 4.6 286.5 1.2 Other metropolitan area 33,115 90.5 2,244.3 6.1 976.4 2.7 265.8 0.7 Nonrnetropolitan area 20,007 88.0 1,906.2 8.0 802.8 3.4 161.2 0.7 Census geographic region Northeast 17,443 89.7 1,335.6 6.9 524.6 2.7 142.6 0.7 Midwest 21,113 89.4 1,614.6 6.8 743.9 3.2 150.9 0.6 South 31,311 87.5 2,959.2 8.3 1,244.6 3.5 285.5 0.8 West 18,399 86.2 1,874.0 8.8 830.3 3.9 237.7 1.1 1 Persons of Hispanic ethnicity can be of any race. 2Income and poverty status refer to household income in a recent 12-month period, varying among rotation groups in the CPS sample. 24 Family Economics and Nutrition RevieW with severe hunger. Thus, a preliminary estimate for the number of children who experienced hunger during the period is given by the number of children living in households classified into the severe hunger category .11 This preliminary approximation indicates that 692,000 children were living in households where severe hunger was experienced in the 12 months prior to the April 1995 survey. (Further information on household and individual estimates can be found in reference 14.) Discussion The development of the food security and hunger measures as described here provides the baseline from which the Government can improve its capacity to monitor the food adequacy of U.S. households. As such, the true importance of the estimates can only be known in the future, when consistent comparisons can be made over time against the baseline numbers. To the extent possible, the new measures are being implemented at the national level by all Federal agencies cooperating in the National Nutrition Monitoring and Related Research Program. USDA plans to continue annual collection of the basic household data needed to replicate the baseline hunger and food security measures through regular supplements to the Current Population Survey. The core set of survey questions needed to liThe estimate is approximate and preliminary for two reasons. First, as noted, the number of children living in households classified to the severe hunger category provides only an upper bound to the number of children experiencing hunger within that category of households. Second, an undetennined number of children living in some of the (non-modal) households classified to the moderate hunger category also experience hunger, but are excluded from the Preliminary approximation. 1998 Vol. 11 Nos. 1 &2 estimate the scaled measures are planned for inclusion in the Fourth National Health and Nutrition Examination Survey (NHANES-IV) and the next round of USDA's Continuing Survey of Food Intakes by Individuals (CSFII), scheduled to be merged with NHANES-IV beginning in the year 2000. The Centers for Disease Control and Prevention, Division of Nutrition (CDC), NCHS, and FNS are working together to test subscales of the 18-item scale that can be used to measure food insecurity and hunger in State surveillance systems such as NCHS's State and Local Area Integrated Telephone Survey and CDC's Pediatric Nutrition Surveillance System. Food security modules are also planned for the Census Bureau's Survey of Program Dynamics to be fielded for 5 consecutive years beginning in 1998 and the Early Childhood Longitudinal Study being conducted by the U.S. Department of Education, National Center for Educational Statistics. The University of Michigan Panel Survey of Income Dynamics included the food security module in a special supplement on women and children in 1997, and this module is being considered for implementation. FNS has collected food security and household food-use data in a national sample of low-income households. As these data emerge, researchers will begin to expand beyond the basic monitoring function to explore the causation and consequences of household food insecurity and hunger across the various levels of severity at which they are experienced and measured. Aside from their incorporation in various research settings and the Government's use in nutrition monitoring, the new measures will provide a baseline for assessing food assistance program performance under the requirements of the Government Performance and Results Act. Specifically, USDA has proposed using the number of households experiencing poverty-linked hunger as a performance measure for assessing the extent to which the agency is succeeding in its goal to enhance food and nutrition security for low-income Americans. Finally, ongoing food security and hunger measures will provide a direct measure of unmet need, which may prove useful for researchers interested in exploring alternative measures of material deprivation. While the Census Bureau's annual estimate of the number of households living below the poverty line has been the standard measure of the extent of material deprivation, the poverty measure has been criticized as increasingly inadequate for this task (9). Future explorations of the relationship of food security and hunger measures to other social and economic indicators of basic needs and resources may be fruitful in this area. Acknowledgments Andrews and Bickel were members of the Office of Analysis and Evaluation's food-security measurement team under the direction of Carlson at the time this work was performed. Other members included Sharron Cristofar and Bruce Klein. Andrews is currently employed by the Economic Research Service, USDA. 25 26 References 1. Alaimo, K. and Briefel, R.R. 1994, July. National estimates of food insufficiency, NHANES III, 1988-91. Presented at the 27th Annual Meeting of the Society of Nutrition Education, Portland, OR. 2. Alaimo, K., Briefel, R.R. , Frongillo, Jr., E.A., and Olson, C.M. 1998. Food insufficiency exists in the United States: Results from the Third National Health and Nutrition Examination Survey (NHANES III). American Journal of Public Health 88:419-426. 3. Anderson, S.A. (Ed.). 1990. Core Indicators of nutritional state for difficult-tosample populations. Journal of Nutrition 120 (11 S): 1557-1600. 4. Basiotis, P.P. 1992. Validity of self-reported food sufficiency status item in the U.S. Department of Agriculture's food consumption surveys. In V.A. Haldeman (Ed.), American Council on Consumer Interests 381h Annual Conference: The Proceedings. Columbia, MO. 5. Bickel, G.W., Andrews, M.S., and Klein, B.W. 1996, January. Measuring food security in the United States: A supplement to the CPS. In D. Hall and M. Stavrianos (Eds.), Nutrition and Food Security in the Food Stamp Program. U.S. Department of Agriculture, Food and Consumer Service, Alexandria, VA. 6. Briefel, R.R. and Woteki, C. E. 1992. Development of food sufficiency questions for the Third National Health and Nutrition Examination Survey. Journal of Nutrition Education 24 (Suppl.):24S-28S. 7. Brown, J.L. 1987. Hunger in the United States. Scientific American 256:36-41. 8. Campbell, C.C. 1991. Food insecurity: A nutritional outcome or a predictor variable? Journal of Nutrition 121:408-415. 9. Citro, C.F. and Michael, R. (Eds.). 1995. Measuring Poverty: A New Approach. Summary and Recommendations. National Academy Press, Washington, DC. 10. Cook, J.T. and Brown, J.L. 1992. Estimating the number of hungry Americans. Working paper, Tufts University Center on Hunger, Poverty, and Nutrition Policy. Tufts School of Nutrition Science and Policy, Medford, MA. 11. Cristofar, S. and Basiotis, P.P. 1992. Dietary intakes and selected characteristics of women 19-50 years and their children ages 1-5 years by reported perception of food sufficiency. Journal of Nutrition Education 24:53-58. Family Economics and Nutrition RevieW 12. Food Research and Action Center (FRAC). 1983. How to Document Hunger in Your Community. Washington, DC. 13. Frongillo, Jr., E.A., Rauschenbach, B.S., Olson, C.M., Kendall, A., and Colmenares, A. G. 1997. Questionnaire-based measures are valid for the identification of rural households with hunger and food insecurity. Journal of Nutrition 127:699-705. 14. Hamilton, W.L., Cook, J.T., Thompson, W.W., Buron, L.F., Frongillo, Jr., E.A., Olson, C.M., and Wehler, C.A. 1997, September. Household Food Security in the United States in 1995: Summary Report of the Food Security Measurement Project. Report prepared for the U.S. Department of Agriculture, Food and Consumer Service. 15. Hamilton, W.L., Cook, J.T., Thompson, W.W., Buron, L.F., Frongillo, Jr., E.A., Olson, C.M., and Wehler, C.A. 1997, September. Household Food Security in the United States in 1995: Technical Report. Report prepared for the U.S. Department of Agriculture, Food and Consumer Service. 16. Kendall, A., Olson, C.M., and Frongillo, Jr., E.A. 1995. Validation of the Radimer/ Cornell measures of hunger and food insecurity. Journal of Nutrition 125:2793-2801. 17. Kendall, A., Olson, C.M., and Frongillo, Jr., E.A. 1996. Relationship of hunger and food insecurity to food availability and consumption. Journal of the American Dietetic Association 96:1019-1024. 18. Kleinman, R.E., Murphy, J.M., Little, M., Pagano, M., Wehler, C.A., Regal, K., and Jellinek, M.S. 1998. Hunger in children in the United States: Potential behavioral and emotional correlates. Pediatrics 101:E3-E9. 19. Maxwell, D.G. 1995, December. Measuring Food Insecurity: The Frequency and Severity of "Coping Strategies." FCND Discussion Paper No. 8. International Food Policy Research Institute, Food Consumption and Nutrition Division, Washington, DC. 20. McGuiness, R. 1997, January. Response Variance in the 1995 Food Security Supplement. Quality Assurance and Evaluation Branch, Demographic Statistical Methods Division, Bureau of the Census. 21. Murphy, J.M., Wehler, C.A., Pagano, M.E., Little, M., Kleinman, R.E., and Jellinek, M.S. 1998. The relationship between hunger and psychosocial functioning in low-income American children. Journal of the American Academy of Child and Adolescent Psychiatry 37: 163-170. 22. Nestle, M. and Guttmacher, S. 1992. Hunger in the United States: Rationale, methods and policy implications of state hunger surveys. Journal of Nutrition Education 24 (Suppl.): 18S-22S. 1998 Vol. 1J Nos. 1&2 27 28 23. President's Task Force on Food Assistance. 1984. Report of the President's Task Force on Food Assistance. U.S. Government Printing Office, Washington, DC. 24. Price, C., Hamilton, W.C., and Cook, J.T. 1997, September. Household Food Security in the United States in 1995: Guide to Implementing the Core Food Security Module. Report prepared for the U.S. Department of Agriculture, Food and Consumer Service. 25. Radimer, K.L., Olson, C.M., and Campbell, C. C. 1990. Development of indicators to assess hunger. The Journal of Nutrition 120 (Suppl.):1544-1548. 26. Radimer, K.L., Olson, C.M., Green, J.C., Campbell, C.C., and Habicht, J.P. 1992. Understanding hunger and developing indicators to assess it in women and children. Journal of Nutrition Education 24 (Suppl.):36S-44S. 27. Singer, E. and Hess, J. 1994, October. Evaluation of the Pretest Results for the Food Security Supplement to April1995 CPS. U.S. Bureau of the Census, Center for Survey Methods Research. 28. Tufts University, Center on Hunger, Poverty and Nutrition Policy. 1993. Policy Report: Thirty Million Hungry Americans. Testimony prepared for the House Select Committee on Hunger, Washington, DC. Tufts School of Nutrition Science and Policy, Medford, MA. 29. U.S. Department of Agriculture, Food and Consumer Service, Office of Analysis and Evaluation. 1995. Food Security Measurement and Research Conference: Papers and Proceedings. Alexandria, VA. 30. Wehler, C.A. 1989. Identification of Childhood Hunger: The FRAC Model. Paper presented at the AIN Conference on Nutrition Monitoring and Nutrition Status Assessment, December 8-10, Charleston, SC. 31. Wehler, C.A., Scott, R.I., Anderson, J.J., and Parker, L. 1991. Community Childhood Hunger Identification Project: A Survey of Childhood Hunger in the United States. Food Research and Action Center, Washington, DC. 32. Wehler, C.A., Scott, R.I., and Anderson, J.J. 1992. The Community Childhood Hunger Identification Project: A model of domestic hunger-Demonstration project in Seattle, Washington. Journal of Nutrition Education 24 (Suppl.):29S-35S. 33. Wehler, C.A., Scott, R.I. , Anderson, J.J., and Parker, L. 1995. Community Childhood Hunger Identification Project: A Survey of Childhood Hunger in the United States. Food Research and Action Center, Washington, DC. Family Economics and Nutrition RevieW 1998 Vol. 11 Nos. 1 &2 Do Child Support Awards Cover the Cost of Raising Children? Mark Lino Center for Nutrition Policy and Promotion A large proportion of the poor in the United States is composed of single mothers and their children. Many of these women receive partial child support payment or none at all. Welfare reform legislation has, therefore, focused on child support payment enforcement. However, the economic well-being of single-parent families can be improved only if child support payments are paid on a regular basis and reflect the cost of raising children. Comparing USDA estimates of expenditures on children with average full child support payments, which represent average child support awards, shows that these full payments cover a small proportion of the total cost of raising children. Therefore, to improve the economic well-being of single-mother families, child support enforcement plus child support awards that reflect the cost of raising children are needed. dra.-natic change in American family life during the past 30 years has been the growth in the number of single-parent families. In 1970, 13 percent of all families with children were headed by a single parent. By 1996, this proportion had climbed to 32 percent ( 14,17). It is estimated that half of the children in the United States will spend part of their childhood in families headed by a single parent (4)-typically, the mother. Since 1970, single parenthood has become synonymous with poverty. In 1994, the median income of single-parent families headed by a female was less than onethird that of married-couple families with children ( 17); 53 percent of these female-headed families had income below the poverty threshold ( 17). Child support-legally mandated payments from a noncustodial parent to a custodial parent 1--can improve the economic well-being of single-parent families if these payments are paid on a regular basis and reflect the cost of raising children. Given that the recent Welfare Reform Act limits the time single parents are eligible for public assistance, child support is an important way to improve the economic well-being of single-parent families. 1The custodial parent has primary physical care of a child. It does not necessarily mean the parent has sole legal or sole physical custody. The noncustodial parent does not have primary physical care of a child; although, a child can reside with this parent some portion of the time. 29 Much of the focus on child support has been on payment enforcement because noncustodial parents often do not make payments. In 1991, of custodial mothers who were due child support, 48 percent received partial payment or none at all (15 ). The adequacy of child support awards has received much less attention. Beller and Graham compared 1985 child support awards with the cost of raising children (based on 1972-73 data inflated to 1985 dollars) and found these awards only covered a fraction of the cost of raising children (2). A U.S. Department of Health and Human Services study reviewed a variety of estimates of the cost of raising children and compared them with 1990 State child support guidelines ( 18). Most State guidelines were within the range of cost estimates; however, these guidelines were at or near the lower bound of these estimates. Pirog-Good compared 1991 State child support awards determined by the guidelines in each State with estimates of the cost of raising children and concluded most State guidelines fell short of this cost (9). The Women's Legal Defense Fund compared 1989-90 State child support guidelines with a standardof- living measure for children (5). It was found that, in most States, support awards based on the guidelines left children with less than a decent standard of living. Since 1960, the U.S. Department of Agriculture (USDA) has provided annual estimates of family expenditures on children (often referred to as the cost of raising a child) by family income level. This study examines the adequacy of child support awards by comparing average full child support payments with 30 USDA's estimates of the cost of raising children. Average full child support payments should reflect total child support awards. This study differs from previous research-it focuses on USDA's estimates of the cost of raising children as a basis for comparison; whereas, other studies use a range of estimates, some of which are outdated. Also, it uses actual child support payments to make this comparison. The article begins with a brief overview of child support guidelines in the United States, a description of the USDA childrearing expense estimates, and a comparison of the USDA estimates with other estimates of expenditures on children. The article concludes with a discussion of the policy implications for child support guidelines. Overview of the U.S. Child Support Guideline System Before 1984, the use of child support guidelines was limited in many States (21 ). Child support awards, typically set on a case-by-case basis, varied tremendously among judges (5). This system often resulted in awards that had little rationale (2). The emphasis during this time was on the enforcement of child support payments since a large percentage of single mothers received no paymentsa problem that still exists. In 1978, about half of custodial mothers due child support received partial payment or none at all (2). By 1991, this proportion remained almost unchanged at 48 percent ( 15 ). Title N-D of the 1975 Social Security Act made the Federal Government an overseer of child support collection; although, the daily work of collecting child support remained a State responsibility. The Child Support Enforcement Amendments of 1984 were primarily aimed to improve the collection of child support. These amendments required States to (1) use automatic wage withholding to collect overdue child support, (2) use expedited legal processes to establish and enforce support orders, (3) collect overdue support by intercepting State income tax refunds, and (4) initiate a process for imposing liens against real and personal property for nonpayment of child support. The amendments also required States to set numeric child support guidelines and to make these guidelines available to officials in charge of setting the level of child support. The amendments, however, did not require that these guidelines be binding. The Family Support Act of 1988 required States to implement presumptive rather than advisory child support guidelines. It stipulates that these guidelines are to be followed unless their application would be unjust or inappropriate. In addition, States are required to review their guidelines every 4 years to ensure that their application results in appropriate child support award amounts and to consider economic data on the cost of raising children in this review. This act, for the first time, requires States to establish child support guidelines and to use them as the basis of child support awards. Family Economics and Nutrition RevieW The welfare reform bill (Personal Responsibility and Work Opportunity Reconciliation Act of 1996) also contained major child support enforcement provisions as receipt of child support and dependency on public assistance are typically inversely related. Overall, child support legislation has primarily dealt with better enforcement of such support. This emphasis is not swprising given the large percentage of custodial parents who receive no child support. However, the enforcement of child support will significantly improve the economic situation of single-parent families only if the awards reflect child-rearing expenses or the cost of raising children. USDA Estimates of Expenditures on Children by Families Methodology Since 1960, USDA has provided annual estimates of expenditures on children from birth through age 17 by marriedcouple and single-parent families. 2 These expenditures on children are estimated for the major budgetary components: Housing, food, transportation, clothing, health care, child care/education, and miscellaneous goods and services (personal care items, entertainment, etc.). The latest child-rearing expense estimates are based on the 1990-92 Consumer Expenditure Survey (CE) updated to 1996 dollars using the Consumer Price Index (CPI). The CE is the only Federal 2 The administrative report has a detailed description of the USDA methodology used to estimate child-rearing expenses and a discussion of the expenses (6). 1998 Vol. 11 Nos. 1 &2 Milestones in Federal Legislation Regarding Child Support Guidelines 1975: Title IV-D of the Social Security Act: The U.S. Department of Health and Human Services (then named the U.S. Department of Health, Education, and Welfare) is given primary responsibility for" ... establishing standards for State (child support) program organization, staffing, and operation to assure an effective program." However, primary responsibility for operating the child support enforcement program " ... is placed on the States pursuant to the State plan." 1984: Child Support Enforcement Amendments: States were required to " ... formulate guidelines for determining appropriate child support obligation amounts and distribute the guidelines to judges and other individuals who possess authority to establish obligation amounts." The amendments, however, did not require judges and other officials to follow these child support guidelines. 1988: Family Support Act of 1988: Judges and other officials are required to" ... use State guidelines for child support unless they are rebutted by a written finding that applying the guidelines would be unjust or inappropriate in a particular case." States are also required to " ... review guidelines for awards every four years" and to consider economic data on the cost of raising children in this review. 1996: Personal Responsibility and Work Opportunity Reconciliation Act: This act strengthened child support enforcement provisions given the link between receipt of child support and welfare dependency. Source: U.S. Department of Health and Human Services. Administration for Children and Families, Office of Child Support Enforcement. 1994. Child Support Enforcement Nineteenth Allllual Report to Congress. survey of household expenditures collected nationwide. It collects information on sociodemographic characteristics, income, and expenditures of a nationally representative sample of households. The methodology employed by USDA to estimate child-rearing expenses specifically examines the intrahousehold distribution of expenditures using data for each budgetary component. The CE contains child-specific expenditure data for some budgetary components (clothing and child care/education) and household level data for other budgetary components. 31 32 Multivariate analysis is used to estimate household and child-specific expenditures. Income level, family size, and age of the younger child are controlled for so estimates can be made for families with these varying characteristics (regional estimates are also derived by controlling for region). Estimated household and child-specific expenditures are allocated among family members (e.g., in a married-couple, two-child family: the husband, wife, older child, and younger child). Since the estimated expenditures for clothing and child care/education only apply to children, these expenses are allocated by dividing them equally among the children. Because the CE does not collect expenditures on food and health care by family member, data from other Federal studies are used to apportion these budgetary components to a child by age. The USDA food plans are used to allocate food expenses among family members. These plans, derived from a national food consumption survey, show the share of food expenses attributable to individual family members by age and household income level. These members' food budget shares are applied to estimated household food expenditures to determine food expenses on a child. Health care expenses are allocated to each family member based on data from the National Medical Expenditure Survey. This survey contains data on the proportion of health care expenses attributable to individual family members. These members' budget shares for health care are applied to estimated household health care expenditures to determine expenses on a child. Unlike food and health care, no authoritative base exists for allocating estimated household expenditures on housing, transportation, and other miscellaneous goods and services among family members. Two common approaches used to allocate these expenses are the per capita and the marginal cost methods. The marginal cost method measures expenditures on children as the difference in expenses between couples with children and equivalent childless couples. This method depends on development of an equivalency measure; however, there is no standard measure. Various measures have been proposed, each yielding different estimates of expenditures on children. Also, the marginal cost approach assumes-without much basis-that the difference in total expenditures between couples with and without children can be attributed solely to the children in a family. In addition, couples without children often buy homes larger than they need in anticipation of children. Underestimates of expenditures on children can result when these couples are compared with similar couples with children. For these reasons, USDA uses the per capita method to allocate housing, transportation, and miscellaneous goods and services among household members. This method allocates expenses among household members in equal proportions. Although the per capita method has limitations, they are considered Jess severe than those of the marginal cost approach. In implementing the per capita method, it should be noted that for homeowners, housing expenses do not include mortgage principal payments; in the CE, such payments are considered to be part of savings. Also, because workrelated transportation expenses are not directly child specific, these costs are excluded when estimating children's transportation expenses. Family Economics and Nutrition Review Estimated Child-Rearing Expenditures Estimates of 1996 family expenditures on the younger child in husband-wife households with two children for the overall United States are shown in table 1. Expenses on children vary considerably by household income level. Depending on the age of the child, the annual expenses range from $5,670 to $6,740 for families in the lowest income group (1996 before-tax income less than $34,700), from $7,860 to $8,960 for families in the middle-income group (1996 before-tax income between $34,700 and $58,300), and from $11,680 to $12,930 for families in the highest income group ( 1996 before-tax income more than $58,300).3 On average, households in the lowest income group spend 28 percent of their before-tax income per year on a child, those in the middleincome group, 18 percent, and those in the highest income group, 14 percent. Housing accounts for the largest share of total child-rearing expenses. Based on the average for the six age groups, housing accounts for 33 to 37 percent of child-rearing expenses, depending on income. Food is the second largest average expense on a child for families regardless of income level, accounting for 15 to 20 percent of child-rearing expenses. Transportation is the third largest childrearing expense, making up 14 to 15 percent of child-rearing expenses across income levels. Expenditures on a child are lower in the younger age categories and higher in the older age categories. 3 The estimates are based on all households, including those with and without specific expenses. So, for some families their expenditures may be htgher or lower than the mean estimates, dependtng on whether they incur the expense or not. This Particularly applies to child care/education for which about 50 percent of families in the study had no expenditure. 1998 Vol. 11 Nos. 1 &2 This held across income groups. Expenses for the various budgetary components varied by each age group. Food expenses were highest for teenagers, whereas child care expenses were one of the largest expenses for preschoolers. Additional analysis found that, on average, the expenses depicted in table 1 also reflect those on the older child in a given age category in a two-child family. However, compared with expenditures for each child in a two-child family, husband-wife households with one child spend an average of 24 percent more on the single child, and those with three or more children spend an average of 23 percent less on each child. This is due to family income being spread over fewer or more children and diseconomies or economies of scale. For example, a middle-income family with one child age 6-8 spends $10,080 on the child, a middle-income family with two children ages 6-8 and 15-17 spends $17,090 on the children, and a middle-income family with three children ages 6-8, 12-14, and 15-17 spends $19,960 on the children. For child-rearing expense estimates by region and for single-parent households, see Lino (6). USDA Child-Rearing Expense Estimates Compared With Other Estimators Among other estimators used to determine child-rearing expenses, the Engel and Rothbarth estimators are two of the most commonly used. Both of these estimators are marginal cost approachesexpenses on children are gauged as the difference between expenses of couples with children and equivalent childless couples. This difference is thought to represent additional or marginal expenditures that couples make on a child. The two estimators use different equivalency scales, however, to compare the expenditures of couples with and without children. The Engel estimator (based on the work of Engel in the 19th century, see DHHS ( 18) for a description of Engel's work) assumes that if two families spend an equal percentage of their total expenditures on food, they are equally well-off. The Rothbarth estimator (based on the work of Roth barth in the 1940's, see Roth barth ( 10 )) uses the level of excess income available to people after necessary expenditures on family members are made as the equivalency measure. Roth barth's definition of excess income includes luxuries (alcohol, tobacco, entertainment, and sweets) and savings. Both estimators have limitations, as previously explained. Each assumes a "true" equivalency measure. However, in the economics literature, neither of the equivalency measures has been validated as the "true" measure. Also, the marginal cost estimators do not provide direct estimates of how much is spent on a child. They estimate how much money families with children must be compensated to bring the parents to the same utility level (as gauged by an equivalence scale) of couples without children-this is a different question from "how much do parents spend on children?" According to Bamow, an economist who studied the issue of estimating expenditures on children, " ... while they [the Engel and Rothbarth estimators] undoubtedly yield biased estimates of the true level of expenditures made on behalf of children, the direction of the bias is believed to be known" ( 1 ). He makes the argument that " ... the Rothbarth estimator is likely to provide 33 Table 1. Estimated annual expenditures* on a child by husband-wife families, overall United States, 1996 Child care Transpor- Health and Miscel- Age of child Total Housing Food tation Clothing care education laneoust Before-tax income: Less than $34,700 (A verage=$21,600) 0-2 $5,670 $2,160 $810 $720 $370 $390 $660 $560 3-5 5,780 2,140 900 700 360 370 740 570 6-8 5,900 2,060 1,160 810 400 420 440 610 9-11 5,940 1,860 1,380 880 450 460 270 640 12-14 6,740 2,080 1,450 1,000 750 470 190 800 15-17 6,650 1,680 1,570 1,340 670 500 310 580 Total $110,040 $35,940 $21 ,810 $16,350 $9,000 $7,830 $7,830 $11 ,280 Before-tax income: $34,700 to $58,300 (Average=$46,100) 0-2 $7,860 $2,930 $960 $1 ,080 $440 $510 $1,080 $860 3-5 8,060 2,900 1,110 1,050 430 490 1,200 880 6-8 8,130 2,830 1,420 1,170 470 560 770 910 9-11 8,100 2,630 1,670 1,240 520 600 500 940 12-14 8,830 2,840 1,680 1,350 880 610 370 1,100 15-17 8,960 2,440 1,870 1,710 780 640 630 890 Total $149,820 $49,710 $26,130 $22,800 $10,560 $10,230 $13,650 $16,740 Before-tax income: More than $58,300 (Average=$87,300) 0-2 $11,680 $4,650 $1 ,280 $1,510 $580 $580 $1,630 $1,450 3-5 11 ,910 4,620 1,450 1,480 560 560 1,780 1,460 6-8 11 ,870 4,550 1,740 1,600 620 640 1,220 1,500 9-11 11 ,790 4,350 2,030 1,670 670 690 850 1,530 12-14 12,620 4,570 2,130 1,780 1,110 690 650 1,690 15-17 12,930 4,160 2,240 2,160 1,010 730 1,150 1,480 Total $218,400 $80,700 $32,610 $30,600 $13,650 $11,670 $21,840 $27,330 • Estimates are based on 1990-92 Consumer Expenditure Survey data updated to 1996 dollars using the Consumer Price Index. The figures represent estimated expenses on the younger child in a two-child family . Estimates are about the same for the older child, so to calculate expenses for two children, figures should be summed for the appropriate age categories. To estimate expenses for an only child, multiply the total expense for the appropriate age category by 1.24. To estimate expenses for each child in a family with three or more children, multiply the total expense for each appropriate age category by 0.77. For expenses on all children in a fam ily, these totals should be summed. t Miscellaneous expenses include personal care items, entertainment, and reading materials. 34 Family Economics and Nutrition Review a lower bound estimate of actual expenditures on children, while the Engel estimator is likely to provide an upper bound." The precise magnitude of the overestimate of the Engel estimator or the underestimate of the Roth barth estimator is unknown. Barnow states the Engel estimator yields results too high to be believed so recommends the Rothbarth estimator be slightly increased to determine child-rearing expenditures (1 ). How do child-rearing expense estimates derived from the Engel and Rothbarth estimators compare with the USDA estimates? Table 2 shows this comparison by number of children and total household expenditures. The results for the Engel and Rothbarth estimators are from a U.S. Department of Health and Human Services study (18) that estimated child-rearing expenses by married couples based on the 1980-87 CE; this study contains the most recent child-rearing expense estimates using the Engel and Rothbarth approaches. The USDA estimates are based on the 1995 study. The comparison is based on child-rearing expense estimates as a percentage of total family expenditures; hence, the estimates did not have to be converted into real dollars. For the USDA estimates, average expenditures of families in each income group (as derived from the CE data) were used to make the percentages comparable to those from the DHHS study. The Engel and Rothbarth methods yield varying child-rearing expense estimates that differ as much as 20 percentage points for a family with three children. So when using the marginal cost method in estimating expenditures on children, the choice of an equivalency measure 1998 Vol. 11 Nos. 1&2 Table 2. Average percent of household expenditures attributable to children in husband-wife families Number of children One Two Three Household expenditure level3 Low Average High Engel1 33 49 59 49 49 49 Estimator Rothbarth1 Percent 25 35 39 36 36 35 USDA2 26 42 48 45 42 39 1 Percentages for these estimators are taken from the U.S. Department of Health and Human Services 1~0. , 2Percentages are from the 1995 USDA study. Average expenditures of families in each income level were used to make comparisons. Percentages by number of children are based on average expenditures of middle-income families. 3Percentages by household expenditure level are for a family with two children. is obviously critical since different measures yield different results. If the Rothbarth technique is a lower bound estimator of child-rearing expenses and the Engel technique is an upper bound estimator as Barnow believes, this gives credence to the USDA estimates of childrearing expenses-they are between those produced by the Engel and Rothbarth techniques. For families with one child and for families with a high expenditure level, the USDA estimates are closer to the Rothbarth estimates, whereas for families with a low expenditure level, the USDA estimates are closer to the Engel estimates. For families with two or more children and for families with an average household expenditure level, the USDA estimates are about in the middle of the Roth barth and Engel estimates. It is sometimes argued that the USDA method overestimates child-rearing expenses since the per capita method is used to allocate housing, transportation, and miscellaneous expenses among household members. These three budgetary components account for about 60 percent of the child-rearing costs calculated by USDA. One study argues that childrelated housing expenses should be measured as the difference in rent between one- and two-bedroom apartments (3). This argument assumes all children will reside in rental property. Housing expenses on an only child in a lower income and middle-income family for the overall United States are estimated by USDA to be about $205 and $285 per month, respectively, in 1996. This includes the cost of shelter, utilities, 35 furnishings, home insurance, and appliances. According to the Census Bureau, the difference in median rental price between an efficiency/one-bedroom housing unit and a two-bedroom housing unit in the overall United States was about $100 per month in 1996 dollars (16). This does not include utility costs for many units, furnishings, insurance, or appliances. Also, the USDA childrearing housing expense includes home owners' and renters' expenses; housing costs for homeowners are typically higher than the costs for renters because owned housing usually has more space than does rental housing. The USDA child-rearing expenses do not include work-related transportation expenses. These expenses were calculated to be 40 percent of total transportation expenses. Miscellaneous expenses include expenditures on personal care (e.g., toothpaste and haircuts), entertainment (e.g., video cassettes and toys), and reading material (e.g., newspapers and books). Many of the miscellaneous goods and services are child-oriented so a per capita approach is reasonable in allocating these expenses. Based on some of the goods and services that are included in this category, it could be argued that children use more than a per capita share of these expenses. Therefore, it is unlikely that the USDA child-rearing estimates grossly overestimate expenditures on children for housing, transportation, and miscellaneous goods and services. 36 Table 3. Average full child support payments, household expenditures on children, and percentage of child-rearing expenditures covered by full payments, by income group and number of children, 1991 Household expenditures on children 1 Number of Full child Low Middle High children support payments income income income $2,776 $6,022 $8,395 $11,789 (46%) (33%) (24%) 2 $4,220 $10,103 $14,085 $19,779 (42%) (30%) (21%) 3 $4,277 $11,878 $16,560 $23,255 (36%) (26%) (18%) 4 or more $4,901 $15,877 $22,135 $31,083 (31%) (22%) (16%) 1Child-rearing expenses are for husband-wife households. Note: Numbers in parentheses are the percentage of child-rearing expenditures ·covered by full child support payments. Sources: Scoon-Rogers, L. and Lester, G.H., 1995, Child Support for Custodial Mothers and Fathers: 1991, Current Population Reports, Consumer Income, Series P60-187, U.S. Department of Commerce, Bureau ~fthe Census ( 11) and U.S. Department of Agriculture, Agricultural Research Service, Family Economzcs Research Group, 1992, Expenditures on a Child by Families, 1991 (13). USDA Child-Rearing Expense Estimates Compared With Child Support A wards How do the USDA child-rearing expense estimates compare with average child support awards? Are these awards adequate in terms of the cost of raising children? The U.S. Bureau of the Census periodically publishes a child support report. The most recent report contains information on mean child support income in 1991 for custodial parents receiving full payment from noncustodial parents by number of children ( 11 ). Full child support payments should reflect the total child support award. The Census estimates are for all families of which middle-income families are likely the norm. Table 3 compares 1991 full child support payments from noncustodial parents with the 1991 USDA childrearing expense estimates for low-, middle-, and high-income households by number of children ( 13 ). If each parent equally shares child-rearing expenses, average full payment of child support should cover half the cost of raising children. Full child support payments should not reflect total expenditures on children as this expense is divided between the custodial and noncustodial parent. As seen in table 3, these payments cover less than 50 percent of the cost of raising children regardless of income group. Family Economics and Nutrition RevieW Table 4. Average full child support payments, household expenditures on children (excluding health care and child care/education expenses), and percentage of child-rearing expenditures covered by full payments, by income group and number of children, 1991 Household expenditures on children1 Number of Full child Low Middle High children support payments income income income $2,776 $5,177 $7,176 $9,967 (54%) (39%) (28%) 2 $4,220 $8,685 $12,039 $16,721 (49%) (35%) (25%) 3 $4,277 $10,211 $14,155 $19,660 (42%) |
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