Eating breakfast effects of the school breakfast program

              EATING BREAKFAST:
EFFECTS OF THE SCHOOL
BREAKFAST PROGRAM
August 1998
Authors:
Barbara Devaney
Elizabeth Stuart
Submitted to:
Office of Analysis and Evaluation
USDA Food and Nutrition Service
3101 Park Center Dr.
Alexandria, VA 22302
Project Officer:
Patricia McKinney
Submitted by:
Mathematica Policy Research, Inc.
P.O. Box 2393
Princeton, NJ 08543-2393
(609) 799-3535
Project Director:
John Czajka
This study was conducted under Contract No. 53-3198-7-006 with the Food and Nutrition Service,
United States Department of Agriculture. Points of view or opinions stated in this report do not
necessarily represent the official position of the Food and Nutrition Service.
- ■•"- £
ir.
CONTENTS
Chapter Page
EXECUTIVE SUMMARY vi
I INTRODUCTION 1
A. OVERVIEW OF THE SCHOOL BREAKFAST PROGRAM 2
B. THE SCHOOL NUTRITION DIETARY ASSESSMENT
(SNDA-1) STUDY 3
C. REANALYSIS OF THE SNDA-1 DATA 4
II REVIEW OF THE LITERATURE ON BREAKFAST CONSUMPTION 6
A. PREVIOUS RESEARCH ON BREAKFAST CONSUMPTION 6
B. DESCRIPTIVE ANALYSIS OF SNDA-1 DATA 9
C. ALTERNATE DEFINITIONS OF EATING
BREAKFAST: RECOMMENDATION 14
III EFFECTS OF THE SCHOOL BREAKFAST PROGRAM ON
THE LIKELIHOOD OF EATING BREAKFAST 14
A. DATA AND METHODOLOGY 14
B. EMPIRICAL RESULTS 15
C. SUMMARY AND DISCUSSION 18
REFERENCES 22
APPENDIX A: STUDY METHODOLOGY AND DETAILED
PROBIT ANALYSIS RESULTS 24
Hi
TABLES
Table Page
II. 1 REVIEW OF STUDIES USING ALTERNATE DEFINITIONS
OF BREAKFAST 7
II.2 PERCENTAGE OF STUDENTS EASING BREAKFAST:
ALTERNATE DEFINITIONS 10
III.l STUDENT AND FAMILY CHARACTERISTICS: MEAN VALUES 16
iv
FIGURES
Figure Page
III. 1 PREDICTED PERCENTAGE OF STUDENTS EATING
BREAKFAST: TOTAL SAMPLE AND LOW-INCOME SAMPLE 17
111.2 PREDICTED PERCENTAGE OF STUDENTS EATING
BREAKFAST: ELEMENTARY SCHOOL STUDENTS 19
111.3 PREDICTED PERCENTAGE OF STUDENTS EATING
BREAKFAST: MIDDLE AND HIGH SCHOOL STUDENTS 20
EXECUTIVE SUMMARY
Started as a pilot in 1966, the School Breakfast Program (SBP) was designed to provide funding
for meals served to children in poor areas and areas where children had to travel a great distance to
school. On small farms in rural communities, many young children ate an early breakfast, performed
their chores, and, after a lengthy school bus trip, arrived at school hungry. In 1975, Congress made
the SBP permanent, with the stated objective that the program be made "available in all schools
where it is needed to provide adequate nutrition for children in attendance."
In recent years, researchers have become interested in the question of whether the availability
of SBP at school increased the likelihood of a child eating breakfast.
The answer to that question depends on how breakfast is defined and also upon family income.
The 1992 School Nutrition Dietary Assessment Study (SNDA-1) defined breakfast as eating any
food containing at least 50 calories. Using this very broad definition of breakfast, the SNDA-1 study
found that the availability of a SBP at school did not increase the likelihood of a child eating
breakfast. Commentors on this finding have expressed an interest in whether the finding would be
the same if breakfast was defined more substantively, for example, as providing more than a
minimum level of food energy. This study is a reanalysis of data from SNDA-1 and examines this
and related questions.
A review ofthe literature on breakfast consumption shows that breakfast is defined in a variety
of ways. Studies that examine the prevalence of eating (or skipping) breakfast typically use a
simplistic definition of breakfast, based either on reports of whether breakfast was eaten or on dietary
recall data on whether any food or beverage was consumed. In contrast, studies that assess the
effects of eating breakfast on various performance measures usually define breakfast more
substantively, (for example, providing some minimum level of food energy). The analysis conducted
in this study builds on these two strands of the literature and uses three alternate definitions of
breakfast:
1. Consumption of any food or beverage
2. Breakfast intake of food energy greater than 10 percent of the Recommended Dietary
Allowance (RDA)
3. Consumption of foods from at least two of five main food groups and intake of food
energy greater than 10 percent of the RDA
As the definition of breakfast becomes more robust, the percentage of students who eat breakfast
declines. Almost 9 of 10 students consumed any food or beverage, but only 6 of 10 students
consumed food from at least two of the main food groups and had breakfast intake of food energy
greater than 10 percent ofthe RDA.
vi
Three important findings from the analysis of the effects of the SBP are the following:
1. If breakfast is defined as any food or beverage consumed, the SBP is not associated with
an increased likelihood of eating breakfast. These results are consistent with previous
studies that found that the SPB had no effect on the likelihood of eating any food or food
with a minimum number ofcalories.
2. For low-income students, as the definition of breakfast becomes more robust, the SBP
is associated with an increased likelihood of eating breakfast.
- When breakfast is defined as intake of food energy greater than 10 percent of the
RDA, the likelihood of eating breakfast is significantly higher for low-income
students attending schools with the SBP than for similar students attending
schools without it (74 percent versus 63 percent).
- When breakfast is defined as consumption of food from two or more food groups
and intake of food energy greater than 10 percent of the RDA, the likelihood of
earing breakfast is significantly higher for low-income students attending schools
with the SBP than for similar students attending schools without it (67 percent
versus 55 percent).
3. The estimated effects ofSBP availability on the likelihood of eating breakfast are largest
for low-income elementary students.
- When breakfast is defined as intake of food energy greater than 10 percent of the
RDA, the likelihood of eating breakfast is significantly higher for low-income
elementary students attending schools with the SBP than for similar elementary
students attending schools without it (82 percent versus 66 percent).
- When breakfast is defined as consumption of food from two or more food
and intake of food energy greater than 10 percent ofthe RDA, the likelihood of
eating breakfast is significantly higher for low-income elementary students
attending schools with the SBP than for similar elementary students attending
schools without it (77 percent versus 62 percent).
vu
I. INTRODUCTION
Authorized by the Child Nutrition Act of 1966, the School Breakfast Program (SBP) started as
a pilot program to provide funding for breakfast in poor areas and areas where children had to travel
a great distance to school. The intent was to provide a nutritious breakfast to children who might
otherwise not receive one. The importance of breakfast is supported by several studies that have
linked it to improved diet and enhanced school performance. To the extent that the SBP increases
the percentage ofchildren who eat breakfast, the program can be expected to improve their diet and
school performance.
Previous studies of the impact of the SBP on the likelihood of eating breakfast, however, do not
provide strong evidence that children attending schools with the SBP are more likely than other
children to eat breakfast. Older studies 01 data from the first National Evaluation of School Nutrition
Programs (NESNP-1) had mixed results. One study reported that children attending schools with
the SBP were more likely to eat breakfast, although the statistical basis for this conclusion is not
presented (Wellisch et al. 1983). In addition, a reanalysis ofthose data indicated that the availability
of the SBP was not associated with the likelihood ofeating breakfast on a given school day (Devaney
and Fraker 1986 and 1989). Data from the 1992 School Nutrition Dietary Assessment study (SNDA-
1) also suggest mat the availability ofthe SBP does not affect whether a student eats breakfast: the
percentage of students eating breakfast was the same in schools that participated in the SBP as in
those that did not, even after controlling for other demographic and socioeconomic characteristics
(Burghardt et al. 1993; and Gleason 1995).
An important issue to consider in these analyses is the definition ofbreakfast. Both NESNP-1
and SNDA-1 use 24-hour dietary recall data to define breakfast consumption. The reanalysis of the
NESNP-1 data defined breakfast as any breakfast and prebreakfast foods, based on self-reported
meals consumed. Thus, the consumption of any calories at either prebreakfast or breakfast meals
constituted having had breakfast. The analysis of data from SNDA-1 defined breakfast as the
consumption of at least SO calories between the time of waking and 45 minutes after the start of
school.
Recently, what constitutes an adequate or substantive breakfast has been debated. Specifically,
questions have arisen about the 50-calorie cutoff and whether "eating breakfast" ought to encompass
a higher calorie cutoff or be based on foods or food groups. This report presents findings from a
reanalysis ofthe SNDA-1 data that used alternate definitions of breakfast. For each of the alternate
definitions of breakfast selected the report presents findings from descriptive and multivariate
analyses of the percentage of students eating breakfast and the effect of the availability of the SBP
on the likelihood of eating breakfast
The rest of this chapter provides brief background material on the SBP, presents an overview
ofSNDA-1, and describes the objective ofthe research. Chapter II examines previous research on
breakfast consumption patterns and, based on this literature review, provides three alternate
definitions of breakfast. Chapter III describes the SNDA-1 data and study methodology and presents
findings from the analysis of die likelihood ofeating breakfast.
A. OVERVIEW OF THE SCHOOL BREAKFAST PROGRAM
The SBP was originally a pilot program that targeted children from low-inconv* school districts
and was intended to provide a nutritious breakfast to children who might not otherwise rece' wt ,ne.
With the 1975 amendments to the Chfld Nutrition Act of 1966, tne SBP becanie permanent, with the
objective of making the program "available in all schools where it is needed to provide adequate
nutrition fix- children in attendance." To expand the availability ofdie program, the Child Nutrition
Act of 1989 required that the Secretary of Agriculture provide funds to states to support the costs of
starting breakfast programs in schools in low-income areas.
All public and private elementary and secondary schools in the United States are eligible to
participate in the SBP. To participate, schools must make breakfast available to all :f'dents. The
U.S. Department of Agriculture (USDA) reimburses schools for each breakfast served that meets
nutritional standards. The cash reimbursements vary according to whether students qualify for free,
reduced-price, or full-price meals. To be eligible for free meals, students must have family income
less than or equal to 130 percent of the poverty level. To be eligible for reduced-price meals,
students must have family income between 130 and 185 percent of the poverty level. For the 1997-98
school year, die reimbursement was $ 1.045 tor free breakfasts, $0,745 for reduced-price breakfasts,
and $020 for full-price breakfasts. For schools with a large proportion of needy individuals ("severe
needs" schools), reimbursements were $0.20 higher for free and reduced-price breakfasts.
SBP breakfarts are required to provide approximately one-fourth of the Recommended Dietary
Allowance (RDA) for important nutrients over a period oftime. At the time of SNDA-1, program
regulations specified that each reimbursable breakfast include a serving of fluid milk, a serving of
fruit or vegetable ora full-strength fruit or vegetable juice, and two servings of either bread or meat
or their equivalent In addition, recent legislation requires that schools offer meals that limit fat and
saturated fats as recommended in die Dietary Guidelinesfor Americans. To achieve bom the RDA
and Dietary Guidelines standards, schools may use several methods for planning menus.
B. THE SCHOOL NUTRITION DIETARY ASSESSMENT (SNDA-1) STUDY
Conducted from 1990 through 1993, SNDA-! addressed three key sets of questions: (1) What
is the nutrient content of school meals as offered to children in schools? (2) What are the nutrient
intakes ofprogram participants? and (3) What .re the dietary effects of the NSLP and SBP? The
detailed findings of SNDA-1 are presented in three major reports, as well as in several subsequent
reports and publications.' The SNDA-1 data set consists of a nationally representative sample of
3,350 student' in grades I through 12 from 329 schools. During a one-week period between
February and May 1992, experienced interviewers administered a student survey, a student 24-hour
recall of foods eaten, a parent survey, surveys of key school and food service officials, and an
instrument & obtain information on foods offered for school breakfasts and lunches.
The data used in this analysis are the student characteristics data from the parent and student
surveys and the dietary intake data from the student 24-hour recall. The data set contains
information on the characteristics of students and their families; foods eaten at breakfast, at lunch,
and ove< a 24-hour period; and information on the schools attended and meal service characteristics
at the schools.
C. REANALYSIS OF THE SNDA-1 DATA
This study, a reanalysis of SNDA-1 data on the likelihood of eating breakfast, includes two main
components:
1. Review of the literature on breakfast consumption patterns to identify alternate
definitions of eating breakfast and, based on this review, recommend alternate
definitions
2. Reanalysis of the data from SNDA-1 using the alternate definitions of breakfast
The literature review is a critical first component of the analysis. The objective is to identify
studies ofbreakfast consumption, especially those using 24-hour dietary recall data, and summarize
'The three main project reports include one on school food service, meals offered, and dietary
(Burghardt et al. 1993); one on dietary intakes ofprogram participants and nonparticipants
(Devaney et al. 1993); and one on sampling and data collection operations for SNDA-1 (Burghardt,
Ensor.etal. 1993).
the different ways in which breakfast has been defined and examined. For example, the definition
of "eating breakfast" may range on a continuum from a loose definition, such as whether any food
item is consumed in the morning, to a strict definition, such as whether foods with some specified
amount of calories and/or from specific food groups are consumed.
The reanalysisof the SNDA-1 data includes the following:
• Descriptive Analysis. Descriptive tabulations are presented on the percentage of
students eating breakfast, under alternate definitions, by school level and SBP
availability. These tabulations are presented for all students and for students from low-income
households.
• Multivariate Analysis. To investigate further the decision to eat breakfast, probit
analysis is used to estimate the relationship between the availability of the SBP and the
likelihood of eating breakfast for each alternate definition of breakfast
Comparing the results for the alternate definitions of breakfast will indicate whether the findings
regarding the availability ofthe SBP are sensitive to the definition of what constitutes breakfast and,
if so, how.
II. REVIEW OF THE LITERATURE ON BREAKFAST CONSUMPTION
p~"ious studies of the effects of the SBP provide little evidence that it increases the likelihood
that schoolchildren will eat breakfast. None of the previous studies, however, includes a careful and
thorough discussion of what constitutes "eating breakfast." Both NESNP-1 and SNDA-1 define
breakfast consumption simplistically: as either eating any breakfast food in the morning, or eating
any prebreakfast or breakfast food, or eating any food or foods with more than 50 calories from the
time of waking until 45 minutes after the start of school.
As discussed previously, questions have arisen about what constitutes an adequate breakfast.
Should breakfast be defined as consuming any food item in the morning? Does a breakfast that
includes only 50 calories meet the nutritional requirements of breakfast? In addition, do the findings
on the lack of a relationship between the availability of the SBP and the likelihood of eating
breakfast change under alternate definitions of breakfast?
This chapter summarizes findings from a review of the literature on breakfast consumption to
identify alternate definitions of breakfast. In addition, descriptive tabulations from the SNDA-1 data
provide important information on the percentage of children eating breakfast, using a wide range of
alternate definitions. Based on the literature review and on the descriptive tabulations, the final
section of the chapter provides three aJter.iate definitions for the reanalysis of the decision to eat
breakfast
A. PREVIOUS RESEARCH ON BREAKFAST CONSUMPTION
The large body of literature on breakfast consumption encompasses a broad range ofdefinitions.
As Table II. 1 shows, the studies examining breakfast consumption fall into two primary groups: (1)
those that focu? on whether or not breakfast is eaten; and (2) those that examine the effects of eating
TABLE H.I
REVIEW OF STUDIES USING ALTERNATE DEFINITIONS OF BREAKFAST
Authors Study Design Definitions of Breakfast Comments/Findings
^iw^taMutClWfUu MMllMlMMI l|Hp*t
Siega-Riz, Popkin, and Carson (1998) Secondary data analysis to examine breakfast Any food or beverage consumed between 5A.M. and 10 A.M. Breakfast consumption declined over time.
consumption patterns between 1965 and 1991 for for children and between 5A.M. and 9 A.M. for adults especially among older adolescents and
Haines. Guilkey, and Popkin (1996) children and adults in the United States
Used 1965 NFCS, 1977-78 NFCS, and 1989-91
CSFII
adults.
Mclntyre and Horbul (1995) Breakfast survey of 4,079 children in grades 1 to 3 No breakfast: answered no to a question about whether they About 6 percent of children in grades 1 to
in 50 public and separate schools in northeastern had anything to eat or drink before coming to school 3 came to school without eating or
Mclntyre(1993) Ontario during the fall of 1993
Adequate breakfast: consumption of foods from at least 2 food
drinking anything.
groups, one of which contains protein of high biologic value 84 percent consumed an adequate
breakfast, consuming foods from at least 2
Vigorous breakfast: consumption of foods from at least 3 food food groups.
groups, one of which contains protein of high biologic value
Morgan, Zabik, and Leveille (1981) 7-day food diaries from 657 American children ages Breakfast eaters: consumed at least 3 breakfasts during the 7- There is no explanation of how eating at
5 to 12 in 1977 day period. Nonbrcakfast eaters: consumed fewer than 3
breakfasts during 7-day period
least 3 breakfasts per week is defined.
Few children skipped breakfast; non-
5 groups: (1) 3 or more breakfasts containing presweetened breakfast eaters consisted ofonly 10
ready-to-eat (RTE) cereal; (2) 3 or more breakfasts containing children, or 1.5 percent of the sample.
nonsweetened RTE cereal; (3) three or more breakfasts
containing any RTE cereal; (4) consuming breakfasts with
ready-to-eat cereal less than 3 times; and (5) no RTE cereal
consumed
Nicklas. Weihang, Webber, aid 24-hour recall for 6 cohorts of children 10 years of 3 groups: (1) breakfast at home, (2) breakfast at school, and After the School Breakfast Program was
Berenson(1993) age (1973-1974 through I987-198S) from the (3) no breakfast eaten. Breakfast skipping refers to no foods introduced, the percentage ofstudents who
Bogalusa Heart Study, n=464 or liquids consumed. skipped breakfast declined.
Sampson, Dixit, Meyers, and Houso* 4-day eating behavior survey and 24-hour recall of Eating behavior survey: Did you have anything to eat before On any given day, 12 to 26 percent of
(1995) 1,151 children in grades 2 though 5 in East Orange, coming to school? Did you eat a snack on the way to school? children attended school without having
New Jersey
24-hour recall: reported all foods eaten from the time of
waking up to the time of the interview.
4 groups: (1) breakfast eaters, (2) breakfast and snack eaters,
(3) snack-only eaters, and (4) neither breakfast nor snack
enters.
eaten anything.
TABLE IU (continued)
1 Authors Study Design Definitions of Breakfast I Comments/Findings
Lopez, de Andraca, Perales, Heresj
Castillo, and Colombo (1993)
Study of 279 children in Chile who were 8 to 11
years of age to determine the effects of breakfast
skipping on cognitive performance
Students were randomly assigned to 1 of 2 study
conditions: breakfast or fasting
Breakfast included 2 cakes and 200 ml flavored milk; total
calories were 394 Kcal
No coi.sisteni association appears between
eating breakfast and cognitive performance
for children with a low socioeconomic
background from Santiago, Chile
Wyon, Abrahamsson, Jartelius, aid
Fletcher < 1997)
Experimental design to determine the effects of
energy intake at breakfast on test performance of 10-
year-old children in school
Standard breakfast with low energy content
• 147 Kcal for girls
- 197 Kcal for boys
Standard breakfast with high energy content
- S67 Kcal for girls
- 832 Kcal for boys
For boys, average energy intake was 25
percent and 8 percent of the RDA for the
high and low energy breakfasts
For girls, average energy intake was 22
percent and 6 percent of the RDA for the
high and low energy breakfasts,
respectively
Dickie and Bender (1982a) Literature review on the effects of breakfast on
performance: summarizes studies with different
definitions of breakfast
Skipping breakfast defined as eating nothing more than a cup
of tea or coffee
Four breakfast classifications for adults: (1) heavy (800 Kcal),
(2) light (400 Kcal), (3) no breakfast ( no food between 18.3
and 12.00 the next day) and (4) coffee with 28 g of cream and
no sugar (60 Kcal)
Literature review suggests mixed evidence
on whether skipping breakfast is
detrimental for school performance
Dickie and Bender (1982b) 2 studies of the effects on mental performance of
omitting breakfast among schoolchildren in London,
average age 12.5 years
Four breakfast classifications: (1) breakfast and midmoming
snack; (2) breakfast, no midmoming snack; (3) no breakfast
but midmoming snack; and (4) no breakfast and no
midmoming snack
Breakfast: any solid food taken on the morning before arriving
at school
Midmoming snack: any food or drink taken at break time
Breakfast typically eaten was substantial,
usually providing more than 2.1 MJ.
Neither study found differences in mental
performance associated with eating or
skipping breakfast
Michaudetal. (1991) Clinical study to examine the effects of breakfast
size on short-term memory, mood, and blood glucose
319 adolescents 13 to 20 years of age in 4 counties
of Lorraine, France
Normal breakfast were supplemented by varying amounts: (1)
0-99 Kcal, (2) 100-199 Kcal, (3) 200-299 Kcal, (4) 300-399
Kcal, and (5) more than 400 Kcal
High energy intake had a beneficial effect
on short-term memory. However,
concentration was impaired by a high
calorie breakfast.
breakfast on various performance measures. In general, studies that examine whether or not
breakfast is eaten define breakfast through either self-reports of breakfast consumption or whether
any food or beverage was consumed after waking in the morning. These studies typically do not use
a definition that reflects any minimum calorie content or attempts to define an adequate breakfast.
The exception is the analysis of SNDA-1 data, in which breakfast had to include at least SO calories,
but even this cutoff value still allows someone to be classified as a breakfast eater with only a
minimal intake of food energy.
In contrast, studies that focus on the effects of eating breakfast on cognitive tests and
performance measures typically define breakfast with some minimum calorie content. As Table II. 1
shows, these caloric contents exceed the 50 Kcal cutoff value used in SNDA-1. For example, in the
experimental study Wyon et al. (1997) conducted to determine the effects of energy intake at
breakfast on test performance, a breakfast with low energy content was defined as 147 Kcal for girls
10 years of age and 197 Kcal for boys 10 years of age, and a breakfast with high energy content was
defined as 567 Kcal for girls and 832 Kcal for boys.
B. DESCRIPTIVE ANALYSIS OF SNDA-1 DATA
Table II.2 provides tabulations on the percentage of students eating breakfast under several
alternative definitions of breakfast, which include the following general categories:
Whether any food or beverage is consumed between waking up and 45 minutes after the
start of school
Breakfast intake of food energy greater than various cutoffs
- 50 Kcal, 100 Kcal, 150 Kcal, and 200 Kcal
- 10 percent and 15 percent of the RDA
TABLE 11.2
PERCENTAGE OF STUDENTS EATING BREAKFAST:
ALTERNATE DEFINITIONS
Alternate Definition
Percentage Eating Breakfast
Total Sample
Elementary
School
Students
Middle and
High School
Students
Any Food Item Consumed 88 93 84
Breakfast Intake of Food Energy > SO Kcal 87 92 13
Breakfast Intake of Food Energy > 100 Kcal 84 90 79
Breakfast Intake of Food Energy > ISO Kcal 78 83 74
Breakfast Intake of Food Energy > 200 Kcal 72 77 68
Breakfast Intake of Food Energy > 10 Percent of the
RDA
Breakfast Intake of Food Energy > 15 Percent of the
RDA
Consuming Food from at Least 2 of the Main Food
Groups'
Consuming Food from at Least 2 of the Main Food
Groups and Breakfast Intake > 10 Percent of the RDA
Consuming Food from at Least 2 of the Main Food
Groups and Breakfast Intake > IS Percent of the RDA
Consuming Food from at Least 3 of the 4 SBP Food
Groups and Breakfast Intake > 20 Percent of the RDAb
Consuming Food from at Least 3 of the 4 SBP Food
Groups and Breakfast Intake > 25 Percent of the RDAb
69 76 62
50 54 45
71 tl 62
61 71 53
45 51 40
17 20 14
11 12 9
Sample Size (Unweighted) 3381 1,611 1,770
SOURCE: School Nutrition Dietary Assessment (SNDA-1) data, weighted.
'The main food groups are (1) milk and milk products, (2) meat and meat alternate, (3) grain products, (4) fruits and
fruit juices, and (5) vegetable and vegetable juice.
"The SBP food groups are (1) milk and milk products, (2) meat and meat alternate, (3) grain products, and (4) fruits and
vegetables or full-strength r~uit or vegetable juices.
10
• Consuming food items from different food groups
- At least two ofthe main food groups
- At least two food groups and breakfast intake of food energy greater than either
10 percent or 15 percent of the RDA
- Consuming food from at least three of the four SBP food groups and breakfast
intake of food energy greater than either 20 percent or 25 percent ofthe RDA
As the definition of eating breakfast becomes more stringent, the percentage of students who
eat breakfast declines. To illustrate, 88 percent of students consumed some food or beverage, buc
only 45 percent of students ate a breakfast that included food from at least two of the main food
groups and had breakfast intake of food energy greater than 15 percent of the RDA (see Table 11.2).
About 11 percent of students had a breakfast that was equal to or exceeded what SBP breakfasts are
designed to offer at breakfast: food from at least three ofthe four SBP food groups and breakfast
intake of food energy greater than 25 percent of the RDA.
The likelihood of eating any breakfast, regardless of how defined, declines with age. Overall,
about 88 percent of students consume some foo i or beverage in the morning, and 12 percent do not
For elementary school students, about 93 percent consume some food or beverage in the morning,
compared with 84 percent of middle and high school students (Table II.2). As the definition of
breakfast becomes more robust, the percentage ofstudents eating it declines, but elementary students
are more likely than middle and high school students to eat each iype ofbreakfast.
The percentage of students eating the most robust breakfast-greater than or equal to the SBP
meal pattern-is quite low. Only about one in 10 students consumed a breakfast with foods from at
least three ofthe SBP food groups and had breakfast intake of food energy greater than 25 percent
ofthe RDA. This result is not surprising nor does it imply that the SBP is not achieving its goal of
providing one-fourth ofthe RDA, on average, for important nutrients. Using a cutoff of consuming
11
at least 20 or 25 percent of the RDA for food energy as a definition of breakfast does not have any
support in die nutrition literature. In fact, there is a major problem with using this strict a definition
of breakfast. If breakfast is defined such mat an individual must have at least 25 percent of the RDA
for food energy, men the average intake ofbreakfast eaters will far exceed the goal of 25 percent of
the RDA. Put another way, the breakfast eaters will be a group of students who are, on average,
consuming much more than either 25 percent of the RDA for food energy at breakfast and, most
likely, more than 100 percent of the RDA for food energy over 24 hours.
Tabulations from the SNDA-1 data show that, amor < students who consumed three of four S3P
food groups and had breakfast intake of food energy greater than 25 percent of the RDA, the mean
breakfast intake of food energy is 39 percent ofthe RDA and the mean daily intake of food energy
is 150 percent ofthe RDA. These intakes of food energy are significantly higher than recommended
levels. Adopting such a strict rule for defining breakfast would implicitly be recommending food
consumption levels mat would contribute to the growing problem of obesity. For these reasons, the
two most robust definitions of breakfast are not recommended as alternate definitions of breakfast
C. ALTERNATE DEFINITIONS OF EATING BREAKFAST: RECOMMENDATION
As discussed above, the existing literature on breakfast consumption uses two very different
approaches to defining breakfast: (1) a simple yes/no approach; and (2) more robust definitions that
specify substantial calorie content For the reanalysis ofthe SNDA-1 data on the likelihood of eating
bi akfast it is useful to consider incorporating both approaches and including a series ofalternate
definitions in the multivariate analysis.
Based on the alternate definitions provided in Table II.2, three alternative definitions of
breakfast are:
12
1. Consumption of any food or beverage
2. Breakfast intake of food energy greater than 10 percent of the RDA
3. Consumption of foods from at least two of the main food groups and breakfast intake
of food energy greater than 10 percent ofthe RDA
There are two main advantages to using all three alternate definitions (or some other similar
combination). First, using definitions that range from minimal to robust allows us to assess the
effects of the program on the likelihood of eating any breakfast versus the effects on eating a
substantial breakfast. Second, using the three alternate definitions allows us to synthesize and even
reconcile the different approaches used in the existing literature. To date, the literature on breakfast
consumption has generally not even recognized that studies of whether breakfast is eaten have taken
approaches vastly different from those of studies of the effects of breakfast consumption.
Presumably, however, these studies should be interrelated: studies of whether breakfast is eaten are
likely to be motivated by evidence that breakfast is important, while sti «> *s that focus on the effects
ofeating breakfast are likely to be informed by evidence on breakfast consumption patten ».
The second and third alternate definitions discussed above use 10 percent of the RDA rather
than IS percent The primary reason for this suggestion is that the intake data collected in SNDA-1
are based on 24-hour recall data, and it is widely known that single-day intake distributions are more
dispersed than usual intake distributions (Nusser et al. 19%). Thus, the percentage of students with
breakfast intakes of food energy less than a given percentage ofthe RDA on a certain day is higher
than the percentage of students with usual breakfast intake of food energy less than the given
percentages. To account for mis, the recommendation includes the lower cutoffof 10 percent ofthe
RDA.
13
III. EFFECTS OF THE SCHOOL BREAKFAST PROGRAM ON
THE LIKELIHOOD OF EATING BREAKFAST
This chapter provides estimates ofthe effects of the availability of the SBP on the likelihood of
eating breakfast, using data from the SNDA-1 study. It begins with a brief description of the data
and methodology and continues with a presentation and discussion ofthe analysis results.
A. DATA AND METHODOLOGY
The SNDA-1 data set is a nationally representative sample of 3,350 students in grades 1 through
12 in 1991 The analysis reported here is based on student characteristics data from the parent and
student surveys and di-r* iry intake data ofstudents from the 24-hour food recall. The main outcome
measure is whether or not the student ate breakfast, based on students' dietary recall data on foods
and beverages consumed.
To review, the analysis uses three alternate definitions of breakfast, ranging from a simple
yes/no approach for whether any food or beverage is consumed to more robust definitions based on
foods and food energy consumed at breakfast. The three alternate definitions are:
1. Consumption ofany food or beverage from die time ofwaking until 45 minutes after the
start of school
2. Breakfast intake of food energy greater than 10 percent of the RDA
3. Consumption of foods from at least two offive main food groups and breakfast intake
of food energy greater C&n 10 percent of the RDA. The five food groups used are (1)
milk and milk prrV-icts, (2) meat and meat equivalents, (3) grain products, (4) fruits and
fruit jukes, and (5) vegetables and vegetablejuices.1
'These five food groups are derived from the SBP food groups but separate fruits and fruit juices
tarn vegetables and vegetable jtrices.
14
The explanatory variables used in the analysis include the availability of the SBP (or another
breakfast program) in school and a variety of student and family characteristics. Student and family
characteristics assumed to influence the likelihood of eating breakfast include the following: age,
gender, race and ethnicity, whether the child is income-eligible for free or reduced-price school
meals, family size and composition, mother's employment status, and residential location.
Table HI. 1 presents descriptive data on the explanatory variables used in the analysis. Of particular
importance is the fact that the SBP is available to slightly more than half of all students and to a*- jut
two-thirds of all low-income students.
Because the decision to eat breakfast is a binary variable, probit analysis is used to examine the
effect ofthe SBP on the likelihood of eating breakfast, while controlling for the student and family
characteristics just discussed. To facilitate the interpretation of the empirical results, the analysis
presents regression-adjusted or predicted values of the likelihood of eating breakfast under two
conditions: (1) students attend schools with the SBP, and (2) students attend schools without the
SBP. These predicted values are based upon the estimated coefficients from the probit analysis.2
B. EMPIRICAL RESULTS
The principal finding from the analysis of the likelihood of eating breakfast is mat the
availability of the SBP in schools is associated with a higher likelihood of eating a more robust
breakfast for students from low-income households. As the definition ofbreakfast becomes more
stringent, the difference in the predicted values ofeating that breakfast between low-income students
with and without die SBP available becomes larger and statistically significant (Figure III. 1). Using
the definition of breakfast as any food or beverage consumed, the difference in the predicted
2An appendix to this report includes a rigorous description ofthe methodology and presents die
detailed analysis results from the probit analysis.
15
TABLE HI. 1
STUDENT AND FAMILY CHARACTERISTICS: MEAN VALUES
Characteristic Total Sample Low-Income Sample
School Has SBP 0.51 0.66
School Has Other Breakfast Program 0.05 0.03
Aft 11.61 11.13
Female 0.50 0.50
Black 0.16 0.29
Hispanic 0.13 0.20
Other Race 003 0.03
Income-Eligible for Free or Reduced-Price
Meal
0.42 1.00
Eligibility Data Missing 0.12 0.00
Mother in Household 0.92 0.90
Mother Employed 0.62 0.52
Family Size 3 or 4 0.53 0.43
Family Size 5 to 7 0JI 0.43
Family Size Larger than 7 0.03 0.06
Urban 0.39 0.46
Suburban 0J7 0.24
Mid-Atlantic 0.12 0 11
Southeast 0.21 02;
Midwest 0.19 0.16
Southwest 0.15 0 IS
Mountain Plains 0.09 0.11
West 0.15 0.12
Sample Size Vii 1,44!
SOWCE School Nutrition Dietary Assesrnent (SNDA-1 )Jata.
NOTE: Means are based upon weighted data
16
Figure 111.1
Predicted Percentage of Students Eating Breakfast:
Total Sample and Low-Income Sample
Total Sample
Any Food or Beverage
Consumed
Breakfast Intake of Consumed Food From 2 Food
Food Energy > 10% of Groups and Breakfast Intake of
RDA Food Energy > 10% of ROA
100
80
60
40
20
0
Low-Income Sample
87.5 86.2
Any Food or Beverage
Consumed
Breakfast Intake of Consumed Food From 2 Food
Food Energy > 10% of Groups and Breakfast Intake of
ROA Food Energy > 10% of ROA
•(*•): p< 0.06 (0.01)
Source: SNDA-1 database ISBP Available D SBP Not Available
17
percentage of students eating breakfast with and without the SBP available is small and not
statistically significant either for the total sample or for students from low-income households.
These results are consistent with previous studies that found no effect of the SBP on the likelihood
of eating any food or food containing a minium number of calories. However, when breakfast is
defined as intake of food energy greater than 10 percent of the RDA, the likelihood of eating
breakfast is significantly higher for low-income students attending schools with the SBP available
than for comparable students attending schools without it (74 percent versus OJ percent). Similarly,
when breakfast is defined as consumption of food from two or more food groups and intake of food
energy greater than 10 percent of the RDA, the predicted percentage of students is significantly
higher for low-income students attending schools with the SBP available than for comparable
students attending schools without it (67 percent versus 55 percent).
The estimated effects of SBP availability on the likelihood of eating breakfast are largest for
low-income elementary students (Figure I1I.2). For the two more robust definitions of breakfast, the
predicted percentages of low-income elementary students with the SBP available are significantly
higher for -students than for students without it. In fact, for both of the more robust breakfast
definitions, low-income elementary students with the SBP available are 23 percent more likely than
similar students without the SBP to consume breakfast. Even for low-income middle and high
school students, a group that is less likely than younger students to eat any kind of breakfast, the SBP
b associated with a higher likelihood of eating the breakfast meeting the most robust definition
(Figure III 3).
C. SUMMARY AND DISCUSSION
A primary goal ofthe SBP is to provide a nutritious breakfast to students who might otherwise
not eat one. Previous studies of the SBF, however, provide little evidence that this goal is achieved
18
Figure 111.2
Predicted Percentage of Students Eating Breakfast:
Elementary School Students
Elementary School Students
100 r 94.1 93.1
Any Food or Beverage
Consumed
Breakfast Intake of Consumed Food From 2 Food
Food Energy > 10% of Groups and Breakfast Intake of
RDA Food Energy > 10% of RDA
100
80
Low-Income Elementary Students
934 90.3
81.7
Any Food or Beverage
Consumed
Breakfast Intake of Consumed Food From 2 Food
Food Energy > 10% of Groups and Breakfast Intake of
RDA Food Energy > 10% of RDA
*(**): p< 0.05 (0.01)
Source: SNDA-1 database ISBP Available D SBP Not Available
19
Figure 111.3
Predicted Percentage of Students Eating Breakfast:
Middle and High School Students
100
80
60
40
20
0
Middle and High School Students
82.3 84.5
Any Food or Beverage
Consumed
53.8 51.9
Breakfast Intake of Consumed Food From 2 Food
Food Energy > 10% of Groups and Breakfast Intake of
RDA Food Energy > 10% of RDA
100
80
60
40
20
0
Low-Income Middle and High School Students
80.3 80.4
63
Any Food or Beverage
Consumed
Breakfast Intake of Consumed Food From 2 Food
Food Energy > 10% of Groups and Breakfast Intake of
RDA Food Energy > 10% of RDA
T):p< 0.05 (0.01)
Source: SNDA-1 database ISBP Available D SBP Not Available
20
for any subgroup of students (Devaney and Fraker 1986 and 1989; Burghardt et al. 1993; and
Gleason 1995). The reanalysis of data from SNDA-1 undertaken for this study suggests that the
effect ofthe SBP on the likelihood of eating breakfast depends both on how breakfast is defined and
on family income.
If breakfast is defined as any food or beverage consumed, the SBP is not associated with an
increased likelihood of eating breakfast. About 12 percent of students do not consume any food or
beverage for breakfast This percentage is the same for students in schools with the SBP as without
it, even after controlling for student and family characteristics. This percentage is roughly the same
for the low-income sample as well. These results are consistent with previous studies that found that
the SBP had no effect on the likelihood ofeating any food or foods containing at least SO calories.
When the definition of breakfast is more robust, the SBP is associated with an increased
likelihood of eating breakfast among low-income students, especially ♦hose in elementary school.
Low-income elementary students attending schools with the SBP available are significantly more
likely man similar students attending schools without the SBP to consume a more robust breakfast
For the total sample, there are no significant differences associated with the SBP in the likelihood
ofeating any breakfast, suggesting that program effects vary by family income.
Expansion of the SBP is a policy issue currently being debated. The findings from mis study
suggest that expanding the program to low-income students would be associated with an increased
likelihood of consuming a breakfast that included at least 10 percent of the RDA for food energy.
At the time ofSNDA-1, approximately two-thirds of low-income students attended schools with the
SBP, suggesting that a significant proportion of low-income students would be affected by an
expansion ofthe SBP.
21
REFERENCES
Burghardt, John, Anne Gordon, Nancy Chapman, Philip Gleason, and Thomas Fraker. The School
Nutrition Dietary Assessment Study: School Food Service, Meals Offered, and Dietary Intakes.
Alexandria, VA: U.S. Department of Agriculture, Food and Nutrition Service, Office of
Analysis and Evaluation, October 1993.
Burghardt, John, Todd Ensor, Gayle Hutchinson, Charlene Weiss, and Bruce Spencer. The School
Nutrition Dietary Assessment Study: Data Collection and Sampling. Alexandria, VA: U.S.
Department of Agriculture, Food and Nutrition Service, Office of Analysis and Evaluation,
October 1993.
Devaney, Barbara, Anne Gordon, and John Burghardt. The School Nutrition Dietary Assessment
Study: Dietary Intakes ofProgram Participants and Nonparticipants. Alexandria, VA: U.S.
Department of Agriculture, Food and Nutrition Service, Office of Analysis and Evaluation,
October 1993.
Devaney, Barbara, and Thomas Fraker. "The Dietary Impacts of the School Breakfast Program."
American Journal ofAgricultural Economics, Vol. 71, no. 4, November 1989, pp. 932-948.
Devaney, Barbara, and Thomas Fraker. "The Dietary Impacts of the School Breakfast Program."
Report submitted to the U.S. Department of Agriculture, Food and Nutrition Service. Princeton,
NJ: Mathematica Policy Research, Inc., October 1986.
Gleason, Philip M. "Participation in the National School Lunch Program and the School Breakfast
Program." The American Journal ofClinical Nutrition, vol. 61, no. l(s), January 1995, pp.
2135-2205.
Dickie, N.H., and A.E. Bender. "Breakfast and Performance." Human Nutrition: Applied Nutrition,
1982a, vol. 36A, pp. 46-56.
Dickie, N.H., and A.E. Bender. "Breakfast and Performance in Schoolchildren." British Journal
ofNutrition, 1982b, vol. 48, pp. 483-496.
Haines, Pamela S., David K. Guilkey, and Barry M. Popkin. "Trends in Breakfast Consumption of
U.S. Adults Between 1965 and 1991." Journal of the American Dietetic Association, May
1996, vol. 96, no. 5. pp. 464-470.
Lopez, I., I. de Andraca, C.G. Perales, E. Heresi, M. Castillo, and M. Colombo. "Breakfast Omission
and Cognitive Performance of Normal, Wasted, and Stunted School Children." European
Journal ofClinical Nutrition, 1993, vol. 47, pp. 533-542.
22
Mclntyre, Lynn, and Betty Ann Horbul. "A Survey of Breakfast-Eating Among Young
Schoolchildren in Northeastern Ontario." Canadian Journal of Public Health, vol. 86,
September-October 1995, no. 5, pp. 305-308.
Mclntyre, Lynn. "A Survey of Breakfast-Skipping and Inadequate Breakfast-Eating Among Young
Schoolchildren in Nova Scotia." Canadian Journal of Public Health, November-December
1993, vol. 84, no. 6, pp. 410-414.
Michaud, Claude, Nadine Musee, Jean P. Nicholas, and Luc Mejean. "Effects of Breakfast-Size on
Short-Term Memory, Concentration, Mood and Blood Glucose." Journal ofAdolescent Health,
vol. 12, 1991, pp. 53-57.
Morgan, Karen J., Mary E. Zabik, and Gilbert A. Leveille. "The Role of Breakfast in Nutrient Intake
of 5- to 12-Year-Old Children." The American Journal ofClinical Nutrition, July 1981, vol.
34, pp. 1418-1427.
Nicklas, Theresa, Weihang Bao, Larry S. Webber, and Gerald S. Berenson. "Breakfast Consumption
Affects Adequacy of Total Daily Intake in Children." Journal of the American Dietetic
Association, August 1993, vol. 93, no. 8, pp. 886-891.
Nusser, S.M., A.L. Carriquiry, K.W. Dodd, and W.A. Fuller. "A Semiparametric Transformation
Approach to Estimating Usual Daily Intake Distributions." Journal ofthe American Statistical
Association, vol. 91, 1996, pp. 1440-1449.
Sampson, Am> E., Sujata Dixit, Alan F. Meyers, and Robert Houser, Jr. "The Nutritional Impact
of Breakfast Consumption on the Diets of Inner-City African-American Elementary School
Children." Journal ofthe National Medical Association, vol. 87, no. 3, pp. 195-202.
Siega-Riz, Anna Maria, Barry Popkin, and Terri Carson. "Trends in Breakfast Consumption for
Children in the United States from 1965 to 1991." The American Journal of Clinical Nutrition,
vol. 67 (supplement), April 1998, pp. 7485-7565.
Wellisch, Jean B., Sally D. Hanes, Lawrence A. Jordan, Kenneth M. Mauer, and Joyce A.
Vermeerch. "The National Evaluation of School Nutrition Programs: Final Report, Volume 1—
Overview and Presentation of Findings." Santa Monica, CA: System Development Corporation,
1983.
Wyon, David P., Lillemor Abrahamsson, Marja Jartelius, and Rej J. Fletcher. "An Experimental
Study of the Effects of Energy Intake at Breakfast on the Test Performance of 10-year-old
Children in School." International Journal ofFood Sciences and Nutrition, 1997, vol. 48, pp.
5-12.
23
APPENDIX A
STUDY METHODOLOGY AND DETAILED
PROBIT ANALYSIS RESULTS
M
The analysis presented in this report uses data from SNDA-1 to estimate the effects ofthe SBP
and other student and family characteristics on the likelihood ofeating breakfast, as defined in three
different ways. The model underlying the statistical analysis assumes that the decision to eat
breakfast is a nonlinear function of both SBP availability and student and family characteristics.
Specifically, the model is depicted by the following:
B*=Xfi+e
B =lifB*>0
= 0ifB*<0
where B* is the student's propensity to eat breakfast and B is the student's actual breakfast
consumption-equal to one if the student ate breakfast on the day interviewed and equal to zero if
die student did not. It is not possible to estimate B* directly; however, ifa student eats breakfast,
then B* is greater than zero, while ifa student does not eat breakfast, then B* is less man or equal
to zero. The vector AT contains a set of variables hypothesized to influence the propensity to eat
breakfast, fi is a vector ofcoefficients relating the explanatory variables to the propensity ofeating
breakfast, and e is a random error term that represents random factors that affect the decision to eat
breakfast. Because the observed dependent variable—the decision to eat breakfast (/?)-is binary,
probit analysis is used to estimate the model.
The probit equation for the likelihood of earing breakfast is estimated for the following
subgroups: total sample, total low-income sample, elementary sample, low-income elementary
sample, middle and high school sample, and low-income middle and high school sample. The probit
models use unweighted data.
25
Tables A.l through A.6 present the detailed results from the probit analyses. The coefficient
estimates presented in these tables underlie the analysis findings presented in the report
Specifically, for each student, the predicted probability of eating breakfast is calculated given the
values of the student's characteristics under two conditions: (1) the student attends a school with
the SBP, and (2) the student does not attend a school with the SBP. These predicted probabilities
are averaged across students. The difference between the average predicted probabilities ofeating
breakfast with and without the SBP is the estimated effect of SBP availability on the probability of
eating breakfast
26
TABLE A. 1
PROBIT EQUATION FOR WHETHER A STUDENTCONSUMED ANY FOOD OR MM .CFOR
BREAKFAST
(Sbudard Errors in Parentheses)
Estimated Coefficients
Explanatory Variables Total Sample
E'anentijy School
Students
Middle and High
School Students
Intercept 2.744 ••
(0.250)
1.336"
(0.490)
3275 ••
(0291)
School Has SBP -0.042
(MW)
•.082
(••123)
-0.094
(•MS)
School Has Other Breakfast
Piogram
0.169
(0144)
-0.013
(0.395)
0.177
(0.159)
Age -0.100 ••
(0.009)
-0.013
(0.034)
-0.123 "
(0.019)
Female -0.184"
(0.059)
•0.044
(0.102)
-0274"
(0.075)
Black -0.010
(0.088)
0.138
(0-157)
-0.056
(0.110)
Hispanic -0.071
(0.096)
0.187
(0171)
-0.183
(0.121)
Oner Race 0.126
(0.180)
-0233
(0282)
0235
(0233)
raceme Eligible for Free or
Reduced Price Meal
-0.196 ••
(0.072)
-0238*
(0.120)
-0.171
(0.091)
Eligibility Data Missing 0.114
(0.106)
0.108
(0229)
0.120
(0.122)
Mother in Household 0.101
(0.128)
-0.038
(0230)
0.185
(0.159)
Mother Employed •0.106
(0.069)
-0.015
(0111)
-0.169
(0.089)
Family Size 3 or 4 -0204
(0.143)
0228
(0238)
-0257 •
(0.179)
Family Size 5 to 7 -0229
(0.146)
0294
(0242)
-0206"
(0184)
Family Size Larger than 7 0.061
(0228)
0288
(0263)
•0.045
(0294)
Urban -0.005
(0.078)
0.136
(0.132)
-0.083
(0.100)
27
TABLE AAfcoMomed)
Estimated Coefficients
Eiementary School Middle and High
Explanatory Variables Total Sample Students School Students
Suburban 0.02' 0.193 -0.041
(0.0r (0134) (0.105)
Mk--Atlantic 0.112 0.071 0.120
(0136) (0351) (0.167)
Southeast 0.030 -0.046 0.077
(0.1 It) (0222) (0.143)
Midwest -0.004 -0.011 -0.034
(0117) (0323) (0-141)
Southwest 0.013 0.021 0.005
(0.124) (033<> (0.150)
Mountain Plains 0.088 -0.073 0.160
(0.136) (0342) (0.169)
West 0.050 0.037 0.061
(0.126) (0338) (0.154)
Sa.pkSfae 3,3*1 Mil l,77t
SOURCE: School Nutrition Dietary Assessment (SNDA-1) dsta.
NOTE: The coefficient and standard error rnthnatrs are from an unweighted probit equation of whether a
student ale breakfast.
'Significantly different from zero at the .05 level, two-tailed test
••Significantly different from zero at the .01 level, two-tailed test
TABLE AJ
PROBIT EQUATION FOR WHETHER A STUDENT HAD BREAKFAST INTAKE OF FOOD ENERGY
GREATER THAN 10 PERCENT OF THE RDA
(Standard Errors in Parentheses)
Estimated Coefficients
Explanatory Variables Total Sample
Elementary School
Students
Middle and High
School Students
Intercept 1.294 ••
(0.191)
0.352
(0.353)
1.788 ••
(0J13)
School Has SBP 0.067
(0.054)
0.116
(0J07)
•.027
(0*72)
School Has Other Breakfast
Program
-0.033
(0.109)
-0.478
(0.259)
0.044
(0.124)
Age -0.071 ••
(0.007)
0.006
(0.024)
-0.094 ••
(0.016)
Female -0.160"
(0.046)
-0.096
(0.071)
4226"
(0.062)
Black 0.031
(0.071)
-0.011
(0.111)
0.082
(0.094)
Hispanic -0.043
(0.076)
0.104
(0.115)
-0.137
(0.105)
Other Race 0.180
(0.139)
-0.086
(0.219)
0J57*
(0.179)
Income Eligible for Free or
Reduced Price Meal
-0.026
(0.057)
•0.049
(0086)
-0.007
(0.076)
Eligibility Data Missing 0.100
(0.081)
-0204
(0.139)
0.233 •
(0.100)
Mother in Household 0.099
(0.103)
•0.046
(0.169)
0.174
(0134)
Mother Employed -0.072
(0.053)
-0.093
(0.079)
-0.066
(0.073)
Family Size 3 or 4 -0.032
(0.110)
0.239
(0182)
-0.156
(0.139)
Family Size 5 to 7 -0.056
(0.112)
0.282
(0.183)
-0251
(0143)
Family Size Larger than 7 0.006
(0.169)
0JO0
(0.261)
•0.180
(0.224)
Urban 0.005
(0.062)
0.120
(0.095)
-0.088
(0084)
TABLE A.2 (continued)
Estimated Coefficients
Explanatory Variables
Middle and High
Total Sample Students School Students
0.054
(0.064)
0.179
(0.096)
-0.034
(0087)
0.080
(0.106)
0.033
(0.169)
0.157
(0.138)
0.065
(0.093)
0.085
(0.153)
0.069
(0.119)
0.044
(0.092)
0.149
(0.154)
-0.035
(0H7)
0.132
(0.099)
0.149
(0.162)
0.157
(0128)
0.069
(0.105)
0.123
(0.171)
0.031
(0.137)
0.063
(0.098)
0.042
(0.161)
0.115
(0.127)
Suburban
Mid-Atlantic
Southeast
Midwest
Southwest
Mountain Plains
West
Sa-pkSoe 3381 1,6n 1,778
SOURCE: School Nutrition Dietary Assessment (SNDA-1) data.
NOTE: The coefficient and standard error estimates arc from an unweighted probit equation of whether a
student ate breakfast
•Significantly different from zero at the .05 level two-tailed test
*'Significantly different from zero at the .01 level, two-tailed test
TABLE A.3
PROBIT EQUATION FOR WHETHER A STUDENT CONSUMED FOOD FROM AT LEAST TWO FOOD
GROUPS AND BREAKFAST INTAKE OF FOOD ENERGY GREATER THAN 10 PERCENT OF THE RDA
(Standard Errors in Parentheses)
Estimated Coefficients
Explanatory Variables Total Sample
Elementary School
Students
Middle and High
School Students
Intercept 1.214**
(0.187)
0.3%
(0.340)
1.487**
(0.306)
School Has SBP M73
(0.053)
0.078
(0.083)
0.050
(0.071)
School Has Other Breakfast
Program
0.093
(0.108)
-0.451
(0.255)
0.180
(0.122)
Age -0.078 **
(0.007)
-0.007
(0.023)
-0.088 **
(0.015)
Female -0.220 ••
(0.045)
-0.139*
(0.068)
-0.299 •*
(0.061)
Black 0.033
(0.069)
0.045
(0.107)
0.065
(0.092)
Hispanic -0.032
(0.074)
0.048
(0.109)
-0.077
(0.104)
Other Race 0.150
(0.133)
-0.026
(0.213)
0.279
(0.170)
Income Eligible for Free or
Reduced Price Meal
-0.008
(0.055)
0.015
(0.082)
-0.039
(0.075)
Eligibility Data Missing 0.082
(0.078)
-0.232
(0.133)
0.212 *
(0.097)
Mother in Household 0.065
(0.100)
0.071
(0.158)
0.058
(0.133)
Mother Employed -0.049
(0.052)
-0.038
(0.075)
-0.060
(0.072)
Family Size 3 or 4 -0.004
(0.107)
0.099
(0.179)
-0.030
(0.135)
Family Size 5 to 7 0.010
(0.110)
0.141
(0.181)
-0.059
(0.140)
Family Size Larger than 7 0.148
(0.165)
0.222
(0.255)
0.132
(0.221)
Urban 0.060
(0.061)
0.155
(0.091)
-0.026
(0.082)
31
TTAABBLE A.3 (continued)
Estimated Coefficients
Explanatory Variables Total Sample
Elementary School
Students
Middle and High
School Students
Suburban 0.025
(0.062)
0.113
(0.091)
-0.045
(0.086)
Mid-Atlantic 0.029
(0.103)
-0.058
(0.164)
0.119
(0.136)
Southeast -0.038
(0.091)
0.008
(0.150)
-0.066
(0.118)
Midwest -0.038
(0.091)
0.004
(0.150)
-0.077
(0.116)
Southwest 0.035
(0.097)
0.030
(0.157)
0.065
(0.125)
Mountain Plains 0.0O2
(0.103)
-0.026
(0.165)
0.022
(0.135)
West -0.016
(0.096)
-0.071
(0.157)
0.057
(0.125)
Sample Size 3,381 Mil 1,770
SOURCE: School Nutrition Dietary Assessment (SNDA-1) data.
NOTE: The coefficient and standard error estimates are from an unweighted probit equation of whether a
student ate breakfast
•Significantly different from zero at the .05 level, two-tailed test
"Significantly different from zero at the .01 level, two-tailed test
TABLE A.4
PROBIT EQUATION FOR WHETHER A STUDENT CONSUMED ANY FOOD OR DRINK FOR
BREAKFAST: LOW-INCOME SAMPLE
(Standard Errors in Parentheses)
Estimated Coefficients
Explanatory Variables
Low-Income
Students
Low-Income
Elementary
School Students
Middle and High
School Low-Income
Students
Intercept 2.458**
(0.348)
0.887
(0.640)
3.440**
(0.604)
School Has SBF 0.069
(0.107)
0.212
(0.179)
-0.004
(0.140)
School Has Other Breakfast
Program
0.049
(0.264)
-0.569
(0.501)
0.270
(0.322)
Age -0.097**
(0.014)
0.014
(0.046)
-0.138**
(0.030)
Female -0.242**
(0.089)
•0.143
(0.142)
-0.342**
(0.119)
Black 0.013
(0.112)
0.285
(0.185)
-0.101
(0.151)
Hispanic -0.030
(0.130)
0.251
(0.212)
-0.152
(0.178)
Othc Race 0.018
(0.246)
-0.307
(0.355)
0249
(0.348)
Mother in Household 0.013
(0.169)
-0.129
(0.265)
0.151
(0.226)
Mother Employed -0.018
(0.095)
0.244
(0.149)
•0.185
(0.130)
Family Size 3 or 4 -0.205
(0.194)
0.422
(0289)
-0.523
(0.271)
Family Size 5 to 7 -0.137
(0.198)
0.614*
(0.293)
-0.572*
(0277)
Family Size Larger than 7 0.083
(0.269)
0.487
(0.395)
-0.121
(0.373)
Urban •0.142
(0.116)
-0.091
(0.181)
-0.179
(0.160)
Suburban -0.023
(0.127)
0.050
(0.189)
-0.024
(0.178)
33
TABLE A.4 (continued)
Explanatory Variables
Estimated Coefficients
Low-Income Middle and High
Low-Income Elementary School Low-Income
Students School Students Students
0.318 0.049 0.410
(0.224) (0.396) (0.293)
0.IS1 •0.260 0.302
(0.189) (0.347) (0.244)
0.060 -0.319 0.174
(0.195) (0.352) (0.248)
-0.002 -0.290 0.073
(0.202) (0.355) (0.268)
0.199 -0.175 0.283
(0.220) (0.381) (0.287)
0.193 0.113 0.205
(0.207) (0.384) (0.263)
Mid-Atlantic
Southeast
Midwest
Southwest
Mountain Plains
West
Sample Size 1,441 777 664
SOURCE: School Nutrition Dietary Assessment (SNDA-1) data.
NOTE: The coefficient and standard error estimates are from an unweighted probit equation of whether a
student ate breakfast.
'Significantly different from zero at the .05 level, two-tailed test.
**Significantly different from zero at the .01 level, two-tailed test.
34
TABLE A.5
PR0B1T EQUATION FOR WHETHER A STUDENT HAD BREAKFAST INTAKE OF FOOD ENERGY
GREATER THAN 10 PERCENT OF THE RDA: LOW-INCOME STUDENTS
(Standard Errors in Parentheses)
Estimated Coefficients
Explanatory Variables
Low-Income
Students
Low- Income
Elementary School
Students
Middle and High
School Low- Income
Students
Intercept 1.525**
(0.284)
0.649
(0.483)
2.465**
(0.510)
School Has SBP 0.295**
(0.087)
0.503**
(0.133)
0.153
(0.121)
School Has Other Breakfast
Program
0.070
(0.216)
-0.372
(0.426)
0.322
(0.261)
Age -0.079**
(0.011)
-0.046
(0.034)
-0.118**
(0.026)
Female -0.108
(0.072)
0.016
(0.104)
-0.260*
(0.103)
Black 0.041
(0.091)
0.014
(0.132)
0.148
(0.132)
Hispanic 0.010
(0.106)
0.161
(0.154)
-0.075
(0.156)
Other Race -0.027
(0.200)
-0.177
(0.292)
0.175
(0.280)
Mother in Household -0.028
(0.138)
-0.069
(0.204)
0.046
(0.194)
Mother Employed -0.019
(0.077)
0.073
(0.110)
-0.109
(0.112)
Family Size 3 or 4 -0.162
(0.158)
0.230
(0.236)
-0.402
(0.217)
Family Size 5 to 7 -0.057
(0.161)
0.422
(0.237)
-0.390
(0.223)
Family Size Larger than 7 -0.1 II
(0.207)
0.352
(0.302)
-0.447
(0.289)
Urban -0.126
(0.095)
-0.079
(0.136)
-0.197
(0.138)
Suburban -0.091
(0.101)
0.068
(0.142)
-0.256
(0.150)
35
TABLE A.5 (continued)
Explanatory Variables
Estimated Coefficients
Low-Income
Students
Low- Income
Elementary School
Students
Middle and High
School Low- Income
Students
0.019
(0.183)
-0.263
(0.271)
0.301
(0.260)
-0.034
(0.162)
-0.193
(0.250)
0.094
(0.221)
0.001
(0.168)
0.065
(0.263)
-0.080
(0.225)
-0.021
(0.174)
-0.171
(0.261)
0.096
(0.245)
-0.073
(0.183)
-0.160
(0.276)
-0.064
(0.252)
-0.085
(0.174)
-0.164
(0.267)
0.015
(0.236)
Mid-Atlantic
Southeast
Midwest
Southwest
Mountain Plains
West
Sample Size 1,441 777 664
SOURCE: School Nutrition Dietary Assessment (SNDA-1) data.
NOTE: The coefficient and standard error estimates are from an unweighted probit equation of whether a
student ate breakfast.
•Significantly different from zero at the .05 level, two-tailed test.
**Significantly different from zero at the .01 level, two-tailed test.
36
TABLE A.6
PROBIT EQUATION FOR WHETHER A STUDENT CONSUMED FOOD FROM AT LEAST TWO FOOD
GROUPS AND BREAKFAST INTAKE OF FOOD ENERGY GREATER THAN 10 PERCENT OF THE RDA:
LOW-INCOME SAMPLE
(Standard Errors in Parentheses)
Estimated Coefficients
Explanatory Variables
Low-Income
Students
Low-Income
Elementary School
Students
Middle and High
School Low-Income
Students
Intercept 1.489**
(0.278)
0.716
(0.469)
2.147**
(0.500)
School Has SBP 0.348**
(0.086)
0.425**
(0.128)
0.307**
(0.120)
School Has Other Breakfast
Program
0.124
(0.215)
-0.565
(0.429)
0.467
(0.258)
Age -0.093**
(0.011)
-0.058
(0.033)
-0.118**
(0.026)
Female -0.160*
(0.071)
-0.055
(0.100)
-0.293 ••
(0.102)
Black 0.083
(0.089)
0.122
(0.127)
0.142
(0.130)
Hispanic 0.052
(0.104)
0.152
(0.147)
0.018
(0.155)
Other Race 0.111
(0.199)
0.033
(0.294)
0.269
(0J76)
Mother in Household 0.051
(0.135)
0.095
(0.193)
0.041
(0.191)
Mother Employed -0.065
(0.076)
0.017
(0.106)
-0.150
(0.110)
Family Size 3 or 4 -0.224
(0.155)
0.055
(0.234)
-0.336
(0.210)
Family Size 5 to 7 -0.093
(0.157)
0.250
(0.235)
-0.286
(0.216)
Family Size Larger than 7 -0.077
(0.204)
0.172
(0.297)
-0.190
(0.283)
Urban •0.116
(0.093)
-0.021
(0.130)
-0.250
(0.135)
Suburban -0.135
(0.099)
0.029
(0.136)
-0.331*
(0.149)
37
TABLE A.6 (continued)
Explanatory Variables
Estimated Coefficients
Low-Income
Students
Low-Income
Elementary School
Students
Middle and High
School Low-Income
Students
-0.070
(0.180)
•0.313
(0.264)
0.167
(0.255)
-0.080
(0.159)
-0.195
(0.244)
-0.012
(0.219)
0.002
(0.165)
0.031
(0.256)
-0.075
(0.224)
-0.052
(0.171)
-0.196
(0.254)
0.043
(0.243)
-0.165
(0.179)
-0.358
(0.267)
-0.049
(0.251)
-0.069
(0.171)
•0.150
(0.261)
-0.013
(0.235)
Mid-Atlantic
Southeast
Midwest
Southwest
Mountain Plains
West
Sample Size 1,441 777 664
SOURCE: School Nutrition Dietary Assessment (SNDA-1) data.
NOTE: The coefficient and standard error estimates are from an unweighted probit equation of whether a
student ate breakfast.
'Significantly different from zero at the .05 level, two-tailed test
••Significantly different from zero at the .01 level, two-tailed test.
38