Abstract

Participation in the School Breakfast Program is much less common than participation in the National School Lunch 

Program, even among children with access to both programs. This report examines the determinants of participation 

in the School Breakfast Program among third grade public school students, as well as the impacts of the program on 

food insecurity and children‘s risk of skipping breakfast. Data are from the Early Childhood Longitudinal Survey—

Kindergarten Cohort and from the Wisconsin Schools Food Security Survey. The study found that students are 

more likely to participate when breakfast is served in the classroom, when time available for breakfast in school is 

longer, and when they come from lower income or time-constrained households. Children with access to the School 

Breakfast Program are more likely to eat breakfast in the morning and that program access may enhance food security among families at the margin of food insecurity. 

By Judi Bartfeld, Myoung Kim, Jeong Hee Ryu, and Hong-Min Ahn, 

University of Wisconsin – Madison

The School Breakfast Program

Participation and Impacts

Contractor and Cooperator Report No. 54

July 2009

This study was conducted by the University of Michigan under a cooperative 

research contract with USDA’s Economic Research Service (ERS) Food 

and Nutrition Assistance Research Program (FANRP): contract number 

58-5000-6-0111 (ERS project representative: Katerine Ralston). The views 

expressed are those of the authors and not necessarily those of ERS or USDA.

3

The School Breakfast Program: Participation and Impacts 

by 

Judi Bartfeld 

Consumer Science Department, Institute for Research on Poverty, and Cooperative Extension 

University of Wisconsin – Madison 

bartfeld@wisc.edu 

Myoung Kim 

Graduate Student, Department of Consumer Science 

University of Wisconsin – Madison 

mkim5@wisc.edu 

Jeong Hee Ryu 

Graduate Student, School of Social Work 

University of Wisconsin – Madison 

ryu2@wisc.edu 

and 

Hong-Min Ahn 

Graduate Student, School of Social Work 

University of Wisconsin – Madison 

ahn1@wisc.edu 

July 2009 

 

 

Work was funded in part by a Food Assistance and Nutrition Research Program (FANRP) grant 

from the Economic Research Service of the U.S. Department of Agriculture. We are grateful 

for research assistance from Kisun Nam, as well as valuable input from Katherine Ralston, Mark 

Nord, Joe Robare, Jane Mandell, Rebecca Orbeta, and two anonymous reviewers. 
4

Executive Summary 

The School Breakfast Program is an important component of the nutritional safety net, serving 

over 10 million children per day. Despite the scope of the program, it is less widely available 

and less consistently used than the National School Lunch Program. There remains substantial 

variability, both across and within states, in the extent to which it is available and the degree to 

which students participate, and the factors related to this variability are not well understood. 

And, while some benefits of the program have been well documented, the impact of the program 

on other outcomes, including food insecurity and breakfast-skipping, remains unclear. 

What is the issue? 

This report is intended to shed light both on the determinants of participation in the School 

Breakfast Program, and on some of the potential benefits of the program on children, using more 

recent data than has been available in most existing analyses. First, we focus on patterns and 

predictors of participation in the School Breakfast Program among third-grade students in public 

schools nationwide, contrasting participation patterns in school breakfast with those in school 

lunch, where the latter is much more widely available and utilized. Next, we explore the impact 

of the School Breakfast Program on food insecurity, focusing on differences between lowincome children who do and do not have access to the program at their school. Finally, we 

examine the impact of the School Breakfast Program on the likelihood that children skip 

breakfast. 

What Did the Study Find? 

Our analysis confirms that school breakfast is much less widely used than school lunch, even 

among children with access to both programs. Furthermore, breakfast participation is almost 

entirely limited to a subset of the students who regularly eat school lunch. The program appears 

to serve as an expanded way of utilizing school meals for a subset of the students already 

predisposed to such meals; it receives only extremely limited use among other students. And, 

more so than school lunch, school breakfast appears to be used primarily by the subset of 

students who are most vulnerable. At the same time, there remains a substantial share of at-risk 

children who have access to the program yet do not participate—including 38 percent of those 

who are food insecure. 

Multivariate analyses suggest that both economic vulnerability and time constraints are linked to 

participation, with low income and education, more children, and having two employed parents 

in the home emerging as significant predictors. We also find indirect evidence that local norms 

may be important in the participation decision, as evidenced by significantly higher participation 

in schools with a larger share of low-income students, as well as in neighborhoods with lower 

median incomes. Furthermore, it appears the normative nature of participation in low-income 

schools may have spillover effects on higher income children who might otherwise be less 

inclined to participate. Pronounced differences in participation according to race and ethnicity 

could also reflect differences in norms or preferences. On the other hand, and counter to our 

expectation, we found less likelihood of participation among children living in counties with 

more liberal political climates, suggesting that prevailing wisdom about political norms and 

attitudes towards public programs may not be reflected in school meal program decisions. 

Of particular interest, we found that programmatic and logistical aspects of how breakfast is 

structured at the school are significantly linked to the likelihood of participation. Results strongly 

support the hypothesis that increasing the convenience of the School Breakfast Program leads to 

greater participation, with evidence of the importance of where breakfast is offered (classroom 

versus cafeteria), the duration of the breakfast period, and the arrival time of buses relative to the 
5

start of classes. While smaller-scale local studies have found evidence that features such as inclass breakfast increase participation, this is the first evidence, to our knowledge, of its impact on 

a national scale. 

Our findings suggest that school breakfast availability is linked to a lower probability of 

marginal food security among low-income children, though not to food insecurity at the standard 

threshold. That is, the program appears beneficial in offsetting food-related concerns among atrisk families, though not necessarily in alleviating food insecurity once hardships have crossed 

the food insecurity threshold. While it is possible that unmeasured differences between schools 

that do and do not offer the program could bias our results, we find it more plausible that any 

bias would result in underestimates, rather than overestimates, of the true impact, given that 

school breakfast is disproportionately offered in schools with higher-need populations, at least 

based on observable characteristics. On the other hand, we were unable to substantiate our 

findings with an instrumental variable model, despite the existence of a strong state policy 

instrument. We note the relatively small number of low-income students in our sample who do 

not have access to school breakfast, thus hampering our ability to obtain more precise estimates 

of program impact. 

We also found that availability of the School Breakfast Program significantly reduces the 

probability of skipping at least one breakfast per week, and in particular, that offering breakfast 

at school serves to moderate the risk of breakfast-skipping associated with low income. 

Taken as a whole, our findings indicate that access to the School Breakfast Program yields 

significant benefits in terms of enhancing food security among families at the margin of food 

insecurity, and increasing the probability that children—particularly low-income children—eat 

breakfast in the morning. Our findings suggest that making school breakfast more broadly 

available would be beneficial in ensuring that more children start their school day with a meal, 

and that fewer families are confronted with uncertain access to sufficient food. Furthermore, our 

findings on participation patterns suggest that these benefits could also be enhanced with greater 

participation among children who already have access to the program. 

How Was the Study Conducted? 

We used the third-grade wave of the Early Childhood Longitudinal Survey Kindergarten Cohort 

(ECLS-K) to estimate probit models of students’ participation in SBP, as well as probit and 

instrumental variable models of food security of students’ households. The ECLS-K is a 

national survey providing data on, among other things, the availability of and participation in 

school meal programs as well as food security status and a range of other child outcomes. In 

addition, we used data from the Wisconsin Schools Food Security Survey to estimate probit and 

instrumental variable models of breakfast-skipping. 
6

The School Breakfast Program: Participation and Impacts 

 

The School Breakfast Program is an important component of the nutritional safety net, 

serving over 10 million children per day (Food Research and Action Center 2007). Despite the 

scope of the program, it is less widely available and less consistently used than the National 

School Lunch Program. There remains substantial variability, both across and within states, in 

the extent to which it is available and the degree to which students participate, and the factors 

related to this variability are not well understood. Furthermore, the impact of the program on 

various measures of child wellbeing remains uncertain, due in part to hard-to-measure 

differences between localities that do and don’t offer the program and between students who do 

and don’t choose to participate (see, e.g., Fox, Hamilton, and Lin 2004). 

 This report is intended to shed light both on the determinants of participation in the 

School Breakfast Program, and on some of the potential benefits of the program on children, 

using more recent data than has been available in most existing analyses. First, we focus on 

patterns and predictors of participation in the School Breakfast Program among third-grade 

students in public schools nationwide, contrasting participation patterns in school breakfast with 

those in school lunch, where the latter is much more widely available and utilized. We use data 

from the Early Childhood Longitudinal Survey – Kindergarten Cohort (ECLS-K), third grade 

wave, a national survey providing data on, among other things, the availability of and 

participation in school meal programs as well as food security status and a range of other child 

outcomes. Next, we use the ECLS-K data to explore the impact of the School Breakfast Program 

on food insecurity, focusing on differences between low income children who do and do not 

have access to the program at their school. Finally, we examine the impact of the School 

Breakfast Program on the likelihood that children skip breakfast, using data from a selfadministered survey of parents of elementary school children in Wisconsin, collected during 

2003-2005. 

BACKGROUND 

The School Breakfast Program is an important part of the nutritional safety net. Funded 

by the federal government and administered locally by schools and school districts around the 

country, the program offers all children in participating schools an opportunity to eat a low-cost, 

or sometimes free, breakfast either prior to or during the school day. The School Breakfast 

Program operates in more than 85,000 public and nonprofit private schools and residential child 

care institutions. School districts and independent schools that choose to take part in the 

program receive cash subsidies from the U.S. Department of Agriculture (USDA) for each meal 
7

they serve, and agree to serve breakfasts that meet federal program requirements. Children 

whose families have income below 130 percent of the federal poverty line receive free meals; 

children whose family incomes are between 130 percent and 185 percent of the poverty line 

receive reduced-price meals (costing no more than 30 cents); and children above this threshold 

pay full price. Schools are provided some federal reimbursement for all participating children, 

with higher reimbursement rates for children who are eligible for free or reduced price meals 

(U.S. Department of Agriculture 2008). 

Participation in School Breakfast Program

 Despite considerable evidence that eating breakfast has beneficial impacts on children 

(see Gleason and Suitor 2001, p18-19, for overview), availability of and participation in the 

School Breakfast Program continue to trail comparable indicators for the National School Lunch 

Program. Nationwide, approximately 85 percent of schools that offer school lunch also offer 

breakfast (Food Research and Action Center 2007), although this varies considerably among 

states – from a low of 52 percent to a high of 100 percent. When breakfast is available at school, 

past research suggests that only 18 percent of children participate on a given day, as compared to 

62 percent participating in school lunch (Gordon and Fox 2007). And, past research has shown 

that participation is heavily tilted towards students who receive subsidized meals: students 

approved for free meals have participation rates of 39 percent, as compared to 20 percent for 

students approved for reduced-price meals and 8 percent among students who pay full price (Fox 

et al 2001). In fiscal year 2008, 80.6 percent of school breakfasts served were to students who 

received free or reduced price meals (Food and Nutrition Service). 

The most recent information on characteristics of participants and nonparticipants, as 

well as determinants of participation, is from the School Nutrition and Dietary Assessment 

Survey-III (SNDA-III). Both descriptive and multivariate analyses suggest that, among 

students with access to the program, participation is more common among boys than girls, 

among elementary school children as compared to older children, and among nonwhite children 

as compared to white children. Students who are income eligible for free or reduced price meals 

are more likely to participate than are higher income students, and students in rural areas are 

more likely to participate than are their urban counterparts (Gordon et al 2007). Other research 

on School Breakfast Program participation examines perceived barriers rather than formal 

predictors of participation. Common themes from that body of research include stigma 

associated with the program, time conflicts associated with eating school breakfast prior to the 

start of the school day, and a belief that parents should be responsible for feeding their own 
8

children in the morning (see, e.g. Kennedy and Davis 1998; Lent and Emerson 2007; Reddan, 

Wahlstrom, and Reicks 2002; Rosales and Janowski 2002). This work suggests that both 

community norms as well as details of how the program is implemented that could reduce stigma 

and time conflicts should have beneficial impacts on participation. Initial research is consistent 

with this expectation: Making school breakfast available at no cost (i.e. universal free breakfast) 

is strongly linked to higher participation rates, based on comparisons of schools with and without 

a universal program (Bernstein et al 2004; Lent and Emerson 2006). There is also suggestive 

evidence that universal breakfast is particularly beneficial to participation when breakfast is 

offered during the classroom as part of the school day rather than before school (Bernstein et al 

2004; Wong and Emerson 2006), although this has not received careful research attention. 

Among students in the SNDA-III who did not usually eat school breakfast, more than half 

indicated they would be more likely to do so if it were served in the classroom (Gordon et al 

2007). 

 Almost entirely absent from the literature on School Breakfast Program participation is 

any formal attention to the role of the local programmatic, economic or social/political climate. 

This absence is striking, considering the well documented impact of such factors on caseloads in 

other assistance programs (see, e.g., Figlio, Gundersen, and Ziliak 2000; Ziliak, Gundersen, and 

Figlio 2003 for examples of studies linking macroeconomic and political indicators to food 

stamp caseloads). Certainly perceptions about the role of stigma and community norms are 

consistent with a role for contextual factors in influencing participation. With regard to 

programmatic characteristics, Gordon et al (2007) do find evidence that the cost of school 

breakfast is linked to the likelihood of participation, with higher costs associated with lower 

participation. On the other hand, they found no evidence of a role for several other program 

attributes including the form of delivery (offer versus serve); the type of menu planning system 

(food-based versus nutrient standard); the percent of calories from fat; or whether meals were 

prepared onsite. 

 This report explores School Breakfast Program participation among third-grade public 

school students in a national sample. We use recent data to examine participation patterns 

among a very specific age group, rather than looking collectively at multiple age groups that 

might have varying determinants of participation. We pay particular attention to the role of 

operational features of the program as well as contextual characteristics intended to proxy for 

local norms and economic conditions. 
9

Impacts of School Breakfast Program on Selected Outcomes

The School Breakfast Program could potentially have a range of impacts on children and 

families. By offering a source of breakfast—school-based meals—that would not otherwise be 

available, it could alter eating patterns, affecting the likelihood of eating breakfast, the location 

of breakfast (home versus school), and/or the kinds of food eaten. Likewise, by providing 

children with access to subsidized breakfasts—for some children free or at very low cost—it 

could reduce the risk of food-related hardships. By altering eating patterns, it could, ultimately, 

affect affect nutritional, health, cognitive, and other kinds of outcomes. We provide a brief 

overview of what is currently known about the impacts of the School Breakfast Program on two 

outcomes that are the focus of this report—food insecurity and breakfast skipping. For a detailed 

discussion of the impact of the School Breakfast Program on other outcomes, see Fox, Hamilton 

and Lin (2004). 

Impacts of School Breakfast Program on Food Insecurity 

 Efforts to identify the impact of food assistance programs on food insecurity are 

complicated by self-selection into programs on the basis of unobservable characteristics, with 

persons at greater risk of food insecurity more likely to participate. Indeed, bivariate statistics 

and many multivariate analyses typically reveal the counterintuitive finding that participants in 

food assistance programs have higher rates of food insecurity than do nonparticipants, even when 

limited to the low income, suggesting important underlying differences in risk of food insecurity 

between participants and nonparticipants (see, e.g., Wilde 2007, for discussion of the literature 

on food stamps and food insecurity). 

 Looking across food assistance programs, analyses that do not rely solely on individual 

measures of program participation have found some evidence of beneficial impacts on food 

security. For instance, Bartfeld and Dunifon (2006) found that near-poor households in states 

with higher food stamp participation rates have lower risk of food insecurity, and Bernell, Weber 

and Edwards (2004) found that higher county-level food stamp participation is linked to reduced 

risk of food insecurity among households in Oregon. Yen and colleagues (2007) documented a 

negative impact of food stamp participation on food insecurity, using an instrumental variable 

approach utilizing state policy differences including the length of the food stamp recertification 

period. Likewise, Bartfeld and Dunifon (2006) found that households in states with higher 

participation in summer food programs have lower risk of food insecurity, and Nord and Romig 

(2006) found that seasonal differences in food insecurity (higher in the summer than the spring) 

are smaller in states with more widespread participation in the Summer Food Service program, 
10

providing suggestive evidence that the program helps ameliorate food insecurity among 

households with school-aged children. 

 Research on the relationship between the School Breakfast Program and food security 

lags behind such research on other food assistance programs. To date, no research has 

documented a link between the School Breakfast Program and household food security. Bartfeld 

and Dunifon (2006) found no significant relationship between the state participation rate of lowincome children in the School Breakfast Program (benchmarked against participation of lowincome children in the School Lunch Program) and food security, and likewise, Bartfeld and 

Wang (2006) found no evidence that the estimated participation rate among eligible children is 

linked to food insecurity, using data from Wisconsin. Comparing students in schools with 

universal-free school breakfast to a control group without universal-free breakfast, McLaughlin 

et al (2002) found no difference in the likelihood of food insecurity. 

Because the School Breakfast Program is only available in a subset of schools, it is 

possible to look at program availability, and not merely program participation, to assess impacts 

on food insecurity. Research to date has not addressed this question. There are reasons, though, 

to hypothesize that access to the School Breakfast Program could reduce food insecurity. 

Participation is highly concentrated among the low income, where the greatest food insecurity 

risk is found, and among participating children, school breakfast is linked to clear changes in 

nutrition outcomes (see, e.g., Fox, Hamilton, and Lin 2004). Furthermore, Bhattacharya, Currie 

and Haider (2004) found some evidence that availability of the School Breakfast Program 

contributes to improved diet quality even among other family members, suggesting that 

participation affects broader patterns of food consumption in the household. In this report, we 

examine the relationship between the School Breakfast Program and food insecurity, using a 

national sample of third grade public school students. Our primary strategy is to compare 

household food insecurity among students with and without access to the program, controlling 

for observable attributes of students, households, and communities; we explore the use of 

instrumental variable models to further control for unmeasured differences in program 

availability. 

Impacts of School Breakfast Program on Breakfast-Skipping 

 An important stream of research has considered whether the School Breakfast Program 

increases the likelihood that students eat breakfast on school days (or equivalently, whether it 

decreases the likelihood of skipping breakfast). Despite the importance of this question to 

policymakers interested in gauging the impacts of the program, the evidence here is mixed. The 
11

continuing uncertainly appears to be due in part to variation in how breakfast is defined, and in 

part to difficulty in documenting program impacts in the absence of random assignment—a 

pervasive concern in the broader literature on impacts of nutrition assistance programs. 

 Initial research from the School Nutrition Dietary Assessment Study (SNDA) found no 

evidence that the availability of the School Breakfast Program is linked to greater likelihood of 

eating breakfast (Gleason 1995). However, a reanalysis of the SNDA using more rigorous 

definitions of breakfast and looking separately at impacts for children at different income levels 

found that, when a more stringent definition of breakfast is used, access to the School Breakfast 

Program does reduce the risk of skipping breakfast among low-income children, but not among 

higher income children (Devaney and Stuart 1998). On the other hand, Bhattacharya, Currie and 

Haider (2004) controlled for endogeneity by using a difference-in-differences approach based on 

changes in breakfast patterns during the school year and the summer, and found no evidence that 

children with access to the School Breakfast Program have a lower risk of skipping breakfast. 

Their approach, however, is potentially biased due to failure to account for the availability of 

summer food programs. 

 More recently, Waehrer (2007) used time use diary data from the Child Development 

Supplement of the Panel Study of Income Dynamics to estimate the impact of school breakfast 

participation on breakfast consumption, with the counter-intuitive finding that participation, as 

reported by parents, is linked to lower likelihood of children’s breakfast consumption. However, 

results hinge on the assumption that breakfast consumption at schools is as accurately reported in 

time use diaries as is breakfast consumption at home—a problematic assumption given that 

fewer than 20 percent of the sample reported any meal consumption during the whole school 

day. 

 In short, existing research is inconclusive about whether access to the School Breakfast 

Program affects the likelihood that children eat breakfast, and if so, which children are most 

affected. The best evidence of a beneficial impact is from Devaney and Stuart (1998) and relies 

on data from 1992; the program has evolved considerably in size and form since that time. In 

this report, we examine the relationship between availability of the School Breakfast Program 

and the likelihood of skipping breakfast, using recent data collected from parents of elementary 

school children in Wisconsin. Our primary approach is to compare breakfast skipping among 

children with and without access to the program, controlling for other observable characteristics; 

we also consider instrumental variable models to control for unmeasured factors that may be 

correlated with program availability and breakfast skipping. 

 
12

DATA

We use two primary sources of data in this report—the Early Childhood Longitudinal 

Survey—Kindergarten cohort (ECLS-K), and the Wisconsin Schools Food Security Survey. The 

former is used to examine School Breakfast Program participation patterns, as well as impacts on 

food insecurity; the latter is used to examine impacts on skipping breakfast, as the ECLS-K does 

not support that analysis.1

Early Childhood Longitudinal Survey-Kindergarten Cohort

 Data are from the ECLS-K, wave 5 (third grade), restricted file. The ECLS-K is a 

nationally representative longitudinal survey providing information about children who entered 

kindergarten in the fall of 1998. A multistage probability sample design was employed to select 

the ECLS-K sample. Data were collected in the fall and the spring of kindergarten (1998-99), 

the fall and spring of 1st grade (1999-2000), the spring of 3rd grade (2002), 5th grade (2004), 

and 8th grade (2007). A wide variety of information was collected from children, caregivers, 

and schools. Of particular relevance to this study, data collected from school administrators 

indicates whether the School Breakfast Program is offered, as well as key attributes of the 

program including where and at what time breakfast is served, as well as information on the 

share of children in the school eligible for free or reduced price meals. Relevant data collected 

from parents indicate, among other things, whether children usually eat school breakfast and/or 

school lunch, as well as the household’s food security status using the standard 18-item food 

security scale. We use the restricted access data, which includes geographical identifiers; 

selected contextual data at the county level have been appended to the data. The sample for 

these analyses is limited to public school students for whom parents and school administrators 

provided survey responses during wave 5. Because of regulations related to the use of the 

restricted access data, all sample sizes reported, including subsamples, are rounded to the nearest 

ten. 

Wisconsin Schools Food Security Survey

 The Wisconsin Schools Food Security Survey is a self-administered survey sent home 

with students to parents of elementary school children in Wisconsin. It is used in this report to 

explore the relationship between school breakfast availability and children’s breakfast patterns. 

 

1

 The ECLS-K does not directly ask about skipped meals. It does include information about the number of meals 

eaten at home and at school, but the information on meals at school is only asked of the subset of respondents who 

report that the child usually participates in the School Breakfast Program. As such, school breakfasts for occasional 

participants are not counted, and estimates of breakfast skipping are biased upward. 
13

The survey includes a range questions about sources of food, participation in nutrition assistance 

programs, details about breakfast behavior including frequency of participating in school 

breakfast and skipping breakfast, reasons for not participating in school breakfast, food security 

based on the standard six-item scale, and demographic information. A variety of contextual data 

at the school, zipcode, and county levels have been appended to the data, including information 

on School Breakfast Program availability obtained from state records. Data were collected 

between fall of 2003 and fall of 2005. 

 Surveys were administered through a collaborative effort with University of Wisconsin – 

Extension. County Extension educators contacted local elementary schools regarding 

participation, worked with participating schools to ensure that surveys were disseminated using 

standard protocols, and coordinated local logistics. A total of 66 schools serving children in 26 

counties participated during the primary survey period. For this report, we exclude 6 schools 

with ambiguous information about breakfast availability at school.2

 The sample size for this 

report consists of 7528 students. Note that the sample selection strategy was not designed to 

yield a fully representative sample of schools statewide, but rather, a sample of schools 

sufficiently diverse in terms of community attributes to allow identification of linkages between 

local attributes and outcomes of interest. Thus, overall prevalence rates of school meal 

participation should not be construed as representative of the state as a whole. 

 The mean response rate across schools was 69 percent, a high response rate for a selfadministered survey. To assess the representativeness of the sample, we compared the share of 

surveys indicating that the child had received free or reduced price school meals in the past year 

with the official free and reduced price certification rate for the school, as provided by the 

Department of Public Instruction (DPI).3

 The average difference between the share reporting 

free or reduced-price meals and the official certification rate is minus two percentage points, and 

three-quarters of schools have reported rates within five percentage points of official rates, with 

official rates ranging from 9 percent to 80 percent of students. 

DETERMINANTS OF PARTICIPATION IN THE SCHOOL BREAKFAST PROGRAM 

 In this section, we focus on participation in the School Breakfast Program, using the 

ECLS-K data. We introduce our analytic strategy, and present both descriptive and multivariate 

results. 

 

2

 These are schools for which a non-trivial number of parents reported that their child eats breakfast at school, but 

the School Breakfast Program is not offered, according to official information. These appear to be schools that offer 

breakfast or morning snack programs that are not connected to the School Breakfast Program. 3

 We compare self-reported participation rates to official certification rates, rather than official participation rates, as 

the latter are not available at the school level. 
14

Methods

Data are from the ECLS-K, as described above. For this analysis, the sample is limited to 

the subset of students who attend a school that participates in the School Breakfast Program, as 

our focus is on participation among students with access to the program. Information about 

whether the school participates in the program is available both from school administrators’ and 

from parents’ reports. Because there are some inconsistencies, we rely on administrators’ 

reports, under the assumption that their information is most accurate, and that parents whose 

children do not participate may not, necessarily, know that the program is available. We exclude 

children for whom data from school administrators are not available. 

It is possible that some of the schools in the sample offer universal free breakfast, 

whereby all children in the school are offered school breakfast at no cost regardless of income. 

We do not have an explicit indicator of this in the data; however, we identify 140 students who 

attend schools in which the free and reduced price eligibility rate for breakfast, as reported by 

school administrators, is 100 percent, and assume that this could be an indication of universal 

free breakfast, although we cannot be certain. Because availability of universal free breakfast 

would be expected to increase breakfast participation, and could potentially be correlated with 

other school-level variables of interest, we exclude these cases from the analysis, which does not 

significantly nor substantively affect the results. 

 We estimate probit models, where the dependent variable indicates whether the child 

usually eats a school breakfast, based on the parent’s report.4

 This is coded as 1 if the parent 

responds in the affirmative to the question, “Does {Child} usually eat a breakfast provided by 

the school?”. The conceptual model underlying this analysis reflects the expectation that 

participation in the School Breakfast Program is influenced by household characteristics that 

affect the perceived value of participating; programmatic and logistical factors that affect the 

ease of participating; and local norms regarding appropriate government roles and participation 

in assistance programs. As such, independent variables include household characteristics, 

programmatic characteristics, and contextual characteristics. 

 One set of independent variables includes household characteristics expected to reflect 

differences in need and/or preferences for participating. We include variables denoting 

household income, parental education, home ownership status, and number of children, as 

indicators of economic need; household structure cross-classified with employment, to capture 

the time constraints that may be present when parents work outside the home; estimated 

 

4

 For this as well as the subsequent models, we also experimented with logit models; results are not sensitive to 

functional form. 
15

eligibility for free or reduced price meals, as participation may be more attractive when costs are 

lower; race and ethnicity, as participation in food assistance programs often varies across racial 

and ethnic groups; and gender, as some past work has found gender differences in school 

breakfast participation patterns. 

 A second set of independent variables includes programmatic and logistical factors that 

affect the ease of participation. We include an indicator for having breakfast served in the 

classroom, as compared to the cafeteria or other central location, as this may facilitate 

participation; the duration of the breakfast period, as longer periods may make the program more 

convenient; and the length of time between arrival at school and the start of classes, interacted 

with a dummy variable denoting children who take the school bus to school. For students who 

ride the bus, and for whom arrival time is thus exogenous to desired breakfast participation, 

arriving with more time before class is expected to make participation more feasible. 

 A third set of indicators is intended to proxy for local norms regarding appropriate 

government roles and participation in assistance programs. We include two measures—one 

intended to proxy for school norms regarding breakfast participation, and one intended to capture 

general liberal versus conservative tendencies in the community, which may be correlated with 

attitudes towards participating in government-sponsored food programs. For the former, we 

include the share of students in the school who are officially certified for free or reduced price 

meals. Higher certification rates denote a higher prevalence of low-income families, which may 

reduce any stigma associated with school breakfast participation—even for children who are not 

themselves low income. For the latter, we include the share of voters in the county who voted 

for the Democratic candidate in the 2004 presidential election, where local preference for 

Democrats versus Republicans serves as a proxy for a more positive attitude towards public 

assistance programs and is hypothesized to coincide with more openness to schools (as opposed 

to exclusively families) being involved in feeding schoolchildren. Because of the correlation 

between political preferences and economic conditions (as evidenced in these data), we also 

include a variable for median income based on the 2000 Census, as well as unemployment rate in 

the 12 months prior to the survey, both measured at the county level. 

 Finally, we include two sets of geographic indicators. We differentiate among regions, to 

identify areas where participation is more or less common than expected based on household 

characteristics. And, we include a series of variables describing the urban, surburban or rural 

character of the community. The ECLS-K provide an 8-part categorization including large cities, 

mid-size cities, large suburban areas, mid-size suburban areas, large towns, small towns, rural 

areas located within metropolitan statistical areas (MSAs), and rural areas outside of MSA’s. 
16

Results

How common is participation in the School Breakfast Program? 

 Participation in the School Breakfast Program is much less common than participation in 

the School Lunch Program. This reflects both differences in availability, as well as differences in 

participation when offered. In our broadest sample—third grade public school students with 

nonmissing survey data (regardless of breakfast availability)—35 percent of students usually eat 

school breakfast, as compared to 84 percent of students who usually eat school lunch (Table 1). 

Limiting the sample to children in schools where breakfast is offered—83 percent of the third 

graders for whom breakfast information is available from school administrators—42 percent 

usually eat school breakfast, compared to 82 percent who usually eat school lunch.5

 Looking 

more closely at participation in the two programs reveals that, unless students eat school lunch 

regularly, they are extremely unlikely to have any involvement with the breakfast program; but 

even among regular lunch participants, fewer than half participate in school breakfast. 

 Not only is school breakfast less widely utilized than school lunch, its use appears more 

skewed towards families at greatest risk of food-related hardships. As shown in Table 2, the 

prevalence of breakfast participation is closely related to income, declining steadily from almost 

three-quarters of students in the lowest income group to fewer than 10 percent in the highestincome group. In contrast, participation in school lunch decreases much less dramatically with 

income, from 97 percent to 72 percent. Consistent with this pattern, 80 percent of all children 

who eat school breakfast have meals that are either free or reduced price; among children who 

eat school lunch, far fewer—55 percent—eat meals that are free or reduced-price (not shown). 

 Examining other potential indicators of economic need, participation in school breakfast 

declines from 70 percent of students whose parents have less than a high school education to 

fewer than one-fifth of those with college-educated parents. And, participation increases 

sharply as the number of children in the household increases, from 37 percent of third graders in 

one-child households to 58 percent of those in households with four or more children. Focusing 

on food security, 62 percent of children who are food insecure eat school breakfast when it is 

available, as do only 35 percent of those who are food secure. (Of course, to the extent that 

school breakfast reduces the risk of food insecurity, the true underlying association between food 

insecurity and breakfast participation would be even stronger). School lunch participation, on 

the other hand, shows much more modest differences according to any of the various measures 

examined. Unlike the School Lunch Program, then, the School Breakfast Program appears to 

 

5

 Note that, for our original sample of 10350 children, 2050 are missing information from school administrators 

regarding availability of school breakfast. These children are excluded from the participation analysis. 
17

serve mostly, although not entirely, as a means of providing free or very low-cost meals to low 

income or at-risk children, as opposed to serving more broadly as a nutrition program for a crosssection of families. 

 School meal participation also differs across geographic areas, with sizable regional 

differences as well as differences among urban, suburban and rural areas. Participation is most 

common in the South, where just under half (49 percent) of children who have access to the 

School Breakfast Program participate, as compared to 39 percent in the west, 34 percent in the 

Midwest, and 31 percent in the northeast. In terms of urban-rural patterns, participation is most 

common in rural areas located out of metropolitan statistical areas (57 percent), lower in cities 

and towns (41-47 percent), still lower in the suburbs (35 percent), and lowest in rural areas that 

are part of MSAs (31 percent). In the case of school lunch, in contrast, there is substantially less 

geographic variation. 

 

Multivariate Analysis of School Breakfast Program Participation 

 To assess factors predictive of participation in the School Breakfast Program, we estimate 

probit models with participation as the dependent variable, coded one to denote students who 

usually eat school breakfasts (based on parental report), and zero otherwise. Results are shown 

in Table 3. 

 The first panel focuses on household characteristics. Not surprisingly, participation 

declines as household income increases, and increases when there are more children in the 

household. There is no further impact of estimated eligibility for free or reduced price meals. In 

terms of household structure and employment, relative to two-parent households with one 

employed parent, participation is more likely among children with two employed parents in the 

household, perhaps reflecting the greater time constraints facing 2-parent households when both 

are employed. It also appears more likely among children with a single not-employed parent—a 

finding inconsistent with the time constraints hypothesis, and perhaps instead reflecting 

unmeasured hardship among the single unemployed households. Participation also becomes 

less common as parents’ education level increases; education could proxy for earnings capacity 

and/or could be associated with different attitudes towards participation. And, participation is 

much more common among renters as compared to homeowners. There are large differences by 

race and ethnicity, with the probability of participation much higher among blacks, and to a 

lesser extent other racial and ethnic minorities, relative to whites. There are no significant 

differences in participation by gender. 
18

 The second panel focuses on geographic variables. Consistent with bivariate results, we 

find geographic differences—by region and by urban versus rural status—that persist even after 

controlling for differences in household characteristics. In particular, participation is more 

common in the Midwest and South relative to the Northeast, and is less common in cities and 

suburbs than in rural areas, net of other factors controlled for in the model. 

 The third panel focuses on local characteristics intended to reflect local norms. Even 

after controlling for household income and other characteristics, participation is significantly 

more common among children in schools with a larger share of low-income children (based on 

certification rates for free and reduced price meals). As noted, previous and current research find 

greater participation among lower-income households; we speculate that this translates into 

differing norms that influence participation rates, with greater participation in schools and 

communities in which it is more normative. Results are consistent with this pattern. We also 

examine differences according to local political preferences, expecting, as discussed previously, 

that participation would be more common in areas with democratic versus republican voting 

preferences; the former may have greater acceptance of the legitimacy of a public role in 

providing meals for children. Counter to our expectations, we found that participation actually 

decreases as democratic voting preferences increase, and this pattern is robust across a variety of 

model specifications. Because political preferences are highly correlated with economic 

attributes of communities, the model includes controls for median income and unemployment 

rate. We find no link between unemployment rate and breakfast participation, but a significant 

negative relationship between county median income and participation. 

 The fourth panel focuses on logistical and programmatic features that affect the 

convenience of participating in the School Breakfast Program. Results suggest that, indeed, such 

features are significantly linked to participation. First, the probability of participation increases 

dramatically when breakfast is served in the classroom rather than in the cafeteria. Second, the 

probability of participation increases with the duration of the breakfast period. Third, among the 

subset of students who take the bus to school, participation is more common as the time between 

arrival and the start of classes increases, that is, students are more likely to participate the more 

time they have available at school. 

 In Model 2, we also include an interaction between the school-level free and reducedprice certification rate and the child’s free and reduced price eligibility status. The coefficient on 

child’s eligibility status is now positive and significant, as is the certification rate, while the 

interaction is negative and significant. Thus, in schools with a small share of low-income 

children, a child’s own eligibility status is a strong predictor of breakfast participation; in the 
19

context of a more sizable low-income student population, individual eligibility status becomes 

less important. To the extent that a higher certification rate proxies for reduced stigma, this 

suggests that, when participation is more normative due to a larger share of low-income children, 

children who themselves are not eligible for free or reduced price meals become increasingly 

likely to participate. 
20

SCHOOL BREAKFAST PROGRAM AND FOOD INSECURITY 

This section focuses on the relationship between the School Breakfast Program and food 

insecurity. As discussed earlier, the program could reduce food insecurity by providing children 

with a regular source of breakfast, in many cases free or at minimal cost, thereby both increasing 

the likelihood that children have food, and also freeing up family resources to feed others in the 

household. 

Methods

We use the ECLS-K data, and limit the sample to low-income students, those below 185 

percent of the poverty line. These are the students most at risk for food insecurity, and thus the 

group for which the program could potentially have a role in reducing food insecurity. 

To estimate the impact of school breakfast on household food insecurity, we estimate a 

series of probit models with food insecurity as the dependent variable. We consider two 

measures of food insecurity: the official food security measure, based on an 18-item scale that 

classifies households as food secure or insecure based on the number of affirmative responses 

(with three or more affirmative responses required to be considered as food insecure); and a less 

restrictive measure, marginal food security, which we define as at least one affirmative response. 

This alternative measure has also been used in other research with the ECLS-K, and has been 

found to be a predictor of a variety of child outcomes (Jyoti, Frongillo, & Jones 2005; Winicki & 

Jemison 2003). We consider this less restrictive measure, in addition to the official measure, in 

part because of the unexpectedly low rate of food insecurity found in the ECLS-K sample 

relative to other national surveys (described below in our results). We also explored a measure 

of ‘adult food insecurity’; results were quite similar to those for household food security and are 

not reported. 

The key independent variable is the availability of the School Breakfast Program at the 

child’s school. Other independent variables include a range of socioeconomic characteristics 

often predictive of food insecurity in past research, including income, parental education, race, 

household composition and employment, home ownership, and health status. We also include 

selected contextual characteristics including median rent (defined at the zipcode level), since 

higher housing costs have been linked to greater risk of food insecurity (Bartfeld and Dunifon 

2006); as well as geographic region and indictors of urban, suburban, or rural character of the 

child’s community, since past research reveals persistent geographic variation after controlling 

for household attributes. And, we control for the free and reduced price certification rate in the 

child’s school, as the School Breakfast Program is more common in schools with larger share of 
21

low income children, although we do not anticipate that the certification rate would be predictive 

of food security outcomes after controlling for household income. The primary purpose of our 

model is to adequately control for differences between students with and without access to the 

program, so as to obtain an unbiased estimate of the impact of the School Breakfast Program. 

By focusing on availability of school breakfast, rather than participation of a particular 

child, we address the policy question of whether making the program available—such that 

students may choose to participate based on their own needs and preferences—reduces the 

prevalence of food insecurity among students with access to the program. This avoids inherent 

selection problems stemming from the tendency of higher-need students to select into the 

program, a problem endemic to efforts to link voluntary participation in food assistance 

programs to measures of food-related hardship. The coefficient on breakfast availability 

indicates the average association between program availability and food insecurity, across all 

students with access to the program; to the extent that this association is causal, the impact of 

school breakfast on the subset of students who actually participate would, presumably, be 

greater. 

 Although focusing on availability rather than participation mitigates biases stemming 

from self-selection of students, there remain potential problems due to self-selection of schools 

into the program. While some states mandate participation for elementary schools, others only 

require participation when eligibility for free or reduced price meals (set at 185 percent of the 

poverty line) exceeds a given threshold, and still others leave the decision entirely up to schools 

or school districts. To the extent that schools with higher-risk students are more likely to offer 

breakfast, as suggested by the disproportionate availability of the program in schools with more 

low-income students, estimates of the impact of program availability on food security will be 

biased downward, unless underlying differences between students with and without access to the 

program are fully controlled for in the model. 

 To address this, we consider an instrumental variable approach. We use state-level 

mandates regarding the School Breakfast Program as instruments, and construct a dummy 

variable denoting whether each child’s school is covered by a state mandate requiring that the 

program be offered. Seven states required that all public elementary schools offer breakfast 

during 2001; 16 states required that breakfast be offered when the free and reduced price 

certification rate exceeded a threshold that varied from 15 percent to 80 percent; and the 

remaining states had no requirement (FRAC 2003). We compared the school-reported 

certification rate to the relevant state policy to determine whether each child attended a school 

mandated to offer breakfast. We use the ‘mandate’ variable as an identifying variable in a probit 
22

model to predict breakfast availability, and use the predicted availability in our food security 

model. Implicit in this identification strategy is the assumption that the ‘mandate’ variable is 

uncorrelated with the error in the food security equation, that is, that the mandate variable is not 

associated with food security other than through its association with breakfast availability. 

 Although our main interest is in the impact of program availability on food insecurity, we 

also consider an alternative model that focuses on participation in the School Breakfast Program, 

as distinct from the availability of the program. For this analysis, we limit our sample to students 

in schools in which breakfast is offered (N=2620). Unfortunately, we do not have credible 

instruments for program participation that would allow us to control for unmeasured factors that 

may influence the participation decision. 

Results

Descriptive results 

 Overall, 8.8 percent of children in our ECLS-K sample of third-graders who attend public 

schools live in households classified as food insecure, and 16.8 percent in households that are 

marginally food secure (Table 4). Note that the ‘marginally food security’ category also includes 

those classified as food insecure. The 8.8 percent food insecurity rate is considerably lower than 

expected, based on the official food security estimates generated by the Current Population 

Survey – Food Security Supplements. A Current Population Survey sample of children aged 7-9 

during 2001-3, used as a comparison for the ECLS-K third grade sample used here, showed a 

household food insecurity rate of 19.3 percent--more than twice that in the ECLS-K sample.6 

The reason for this discrepancy is not apparent.

 Food insecurity is strongly linked to income, in our sample and in other surveys. Here, 

we find that 16.6 percent of the low-income children (below 185 percent of the poverty line) in 

our sample are in households that are food insecure, as compared to 2.6 percent of higher income 

children. As a result, we limit our analysis to the low-income group; the extremely low rate of 

household food insecurity among higher income children makes it unlikely that the School 

Breakfast Program would have a meaningful or measurable impact. Note that a large majority of 

low-income children do have access to school breakfast; the relatively small number without 

access makes it more difficult to detect differences. Nonetheless, results show that the 

household food insecurity rate among low-income children with access to the School Breakfast 

Program is 16.1 percent, as compared to 24.5 percent among those without access; the analogous 

marginal food security rates are 29.2 percent and 42.2 percent. 

 

6

 CPS results are based on analyses conducted by Mark Nord, Economic Research Service, U.S.D.A., August 2008. 
23

 

Multivariate Analysis of School Breakfast Program and Food Insecurity 

To assess the impact of school breakfast on household food insecurity, we estimate a 

probit model with food insecurity as the dependent variable (Table 5). We estimate an 

equivalent model for marginal food security, which uses a lower threshold to define food-related 

hardships. The key independent variable is a dummy variable denoting that the School Breakfast 

Program is available at the child’s school. In the food insecurity model, the school breakfast 

coefficient is negative but not significant; in the marginal food security model, on the other 

hand, the coefficient is still negative, but larger in magnitude and highly significant (p<.01), 

suggesting reduced risk of marginal food security when the breakfast program is offered. Other 

variables in the model have coefficients largely in keeping with existing research on food 

security, with minor differences between the two models. The probability of household food 

insecurity declines as household income and education increase; is greater for renters as 

compared to homeowners; and increases with poorer health status and more children. In the 

standard food insecurity model we find no differences by race or ethnicity, net of other factors, 

other than a higher rate in the ‘other race’ category; however, blacks have significantly greater 

risk of marginal food security than do whites. We do not find significant differences according 

to household composition or employment status, with the exception of higher probability of 

marginal food security among children of single not-employed parents. Higher median rent is 

strongly associated with a heightened risk of food insecurity, though only weakly significant in 

the marginal food security model. Net of other factors we find little evidence of remaining 

regional differences in food insecurity, with the exception of a marginally significant higher 

probability of food insecurity in the West. Compared to rural areas, the risk of food insecurity is 

greater in small towns, mid-sized suburbs, and mid-sized cities, with only weak significance on 

any of these variables in the marginal food security model. 

 We use the coefficients from the marginal food security model to estimate the predicted 

probability of marginal household food security for a prototypical student, with and without 

access to the School Breakfast Program (Figure 1). Specifically, we consider a white student in 

the rural Midwest in a county with median rent of $600 per month, at a school with a 25 percent 

certification rate for free and reduced price meals; we assume the student is living with a single 

employed mother who is in good health, has a high school education, rents her home, has 2 

children, and annual income of $15,001-$20,000. In this case, the predicted probability of 

marginal food security is 47 percent if the school does not off breakfast, decreasing to 33 percent 

if breakfast is offered. 
24

To the extent that there are underlying differences between students with and without 

access to school breakfast, beyond those controlled for in our model, our estimates of program 

impact would be biased. To address this, we use an instrumental variable approach to estimate 

the impact of School Breakfast Program availability on food insecurity. As discussed earlier, we 

use state-level mandates regarding the program as instruments. Table 6 shows our first-stage 

model as well as the food insecurity models for both food security measures, including predicted 

probability of breakfast availability as the key independent variable. 

 Our first-stage model confirms that state policy mandates are indeed strong and 

significant predictors of School Breakfast Program availability. Not surprisingly, students whose 

school is covered by a state mandate to offer the program are significantly more likely to have 

the program available at school than are other students. Other predictors of breakfast availability 

include region (most common in the south, and least common in the Midwest); location (least 

common in surburban areas and large towns, and most common in rural areas that are located 

within metropolitan areas); share of low-income students in the school (with greater availability 

as share of low-income students increases, though at a decreasing rate); and median housing 

costs (less common in higher-rent areas). In the second-stage models, whether using the 

standard or marginal food security measures, the coefficients on predicted availability of the 

School Breakfast Program do not approach significance. We also considered an alternative 

operationalization of state mandates, by controlling for the level of the mandate rather than the 

applicability of the mandate to the particular child (that is, including separate variables to denote 

covering all elementary schools, elementary schools with at least a 75 percent free and reduced 

price meal certification rate, etc.). Results, not shown, are comparable to those reported. 

 Finally, we consider an alternative model in which student participation in the School 

Breakfast Program—as distinct from availability of the program at the school—is the key 

independent variable. As previously noted, our sample for this analysis is limited to the subset of 

students attending schools that offer breakfast. Results indicate that participation is associated 

with a significantly higher risk of food insecurity and marginal food security (Table 7), which we 

attribute to self-selection of higher risk children into the program. Unfortunately we do not have 

credible instruments that would allow us to control for unmeasured differences between 

participants and nonparticipants. The remaining variables in the model have similar associations 

with food insecurity and marginal security as found in our previous models. 
25

SCHOOL BREAKFAST PROGRAM AND BREAKFAST SKIPPING: EVIDENCE 

FROM WISCONSIN

Methods

 Our analysis relies on the Wisconsin Schools Food Security Survey, which asks parents, 

among other things, how many times their elementary school child skips breakfast in a typical 

school week. As with the food security analysis, we focus on availability of the School 

Breakfast Program, rather than on participation, thus examining how access to the program is 

linked to breakfast-skipping. We estimate a probit model with breakfast-skipping as the 

dependent variable, coded 1 if parents report that the child skips breakfast at least once in a 

typical week, otherwise coded 0. The key independent variable is the availability of the School 

Breakfast Program at the child’s school, as reported by the Wisconsin Department of Public 

Instruction. Other independent variables include income, parental education, household 

composition and employment, home ownership, number of children, and degree of urbanicity 

(based on census data for the child’s zipcode). 

 Breakfast-skipping differs from food insecurity in that it occurs at nontrivial levels in all 

income groups. As such, we do not limit our analysis to a low-income sample. We hypothesize 

that school breakfast may moderate the relationship between income and breakfast-skipping, 

however, and explore this by estimating a model with interactions between income and breakfast 

availability. 

 Finally, we consider an instrumental variable model. Unlike in our analysis of breakfast 

availability and food insecurity, we cannot rely on state policy variables as instruments, as our 

sample is limited to Wisconsin. Instead we use the free and reduced price meal certification rate 

(and rate squared), in the school, as well as median rent (from the 2000 Census, defined at the 

zipcode level), as identifying variables in a probit model of breakfast availability. Consistent 

with the ECLS-K analysis, we expect the availability of school breakfast to differ between lowincome and higher-income schools, and between wealthier and less wealthy communities (as 

captured by differences in housing costs), yet we do not expect these school and community 

indicators to directly impact breakfast-skipping patterns after controlling for household 

characteristics. 

Results 

Breakfast-skipping among children with and without access to the School Breakfast Program 

 Overall, 24 percent of parents report that their child skips breakfast at least once in a 

typical school week, with 9 percent reporting 3 or more times. Breakfast skipping patterns are 
26

similar in schools with and without the School Breakfast Program—23.7 vs 24.8 percent (Table 

7). Direct comparisons between breakfast patterns in schools with and without breakfast are 

complicated by substantial differences among the students in the two groups of schools. In the 

Wisconsin Schools sample used here, 44 of 59 schools offer breakfast. The School Breakfast 

Program schools serve, on average, a disproportionately low income population: the average 

free and reduced price meal eligibility rate among breakfast-providing schools in the sample is 

.47, as compared to .26 among the non-breakfast schools (not shown). As such, comparisons of 

meal patterns are more informative when they differentiate between meal-skipping among 

higher-risk versus lower-risk students. 

Figure 2 illustrates the prevalence of breakfast-skipping among various income groups, 

looking separately at students in schools that do and do not offer breakfast. The rate of skipping 

is much more strongly linked to income in the non-breakfast schools. In those schools, the 

prevalence of breakfast-skipping ranges from 38 to 41 percent in the three lowest income groups, 

from 26 to 33 percent in the three higher groups, and from 18 to 19 percent in the highest income 

groups. In the breakfast schools, on the other hand, breakfast skipping is much less variable 

across groups, and rates are sharply lower than in the non-breakfast schools at the lower income 

levels. Simple descriptive statistics, then, suggest that the availability of school breakfast may 

reduce the differential risk of skipping breakfast that is evident among lower income children. 

Table 8 compares the prevalence of breakfast-skipping in breakfast and non-breakfast 

schools, according to a variety of other household attributes suggestive of economic need. 

Specifically, we look at breakfast-skipping in families classified as food insecure versus secure; 

who use food pantries versus who do not; and who receive food stamps versus not. When school 

breakfast isn’t available, almost half of children in food insecure households skip breakfast at 

least once in a typical week (46.1 percent); this falls to 35.2 percent among children whose 

school participates in the program. Among children in food secure households, the rate of 

breakfast-skipping is approximately 20 percent regardless of school breakfast availability. A 

similar pattern holds when stratifying by use of food pantries: Among children without access to 

school breakfast, 45.7 percent of those who live in households that have received food from food 

pantries in the past year skip one or more breakfasts in a typical week, as compared to 30.2 

percent of pantry users in schools that offer breakfast. Among children whose families have not 

used food pantries, the rate of breakfast skipping is approximately 23 percent regardless of 

breakfast availability. Stratifying by food stamp use also tells a similar story. In sum, the 

descriptive data provide preliminary evidence that availability of school breakfast is associated 

with lower likelihood of skipping breakfast among vulnerable subsets of elementary school 
27

students, and thus reduces the gap in breakfast-skipping between more vulnerable and less 

vulnerable children. 

Multivariate Analysis of School Breakfast Program and Breakfast-Skipping 

 To more formally estimate the impact of the School Breakfast Program on the probability 

that a child skips breakfast, we turn to a multivariate approach, considering several different 

models. First, we estimate a probit model with a dichotomous measure of breakfast-skipping as 

the dependent variable, and the key independent variable an indicator of the availability of the 

breakfast program (Table 9). Other variables include a variety of household characteristics 

broadly reflective of economic wellbeing, which may also be linked to breakfast patterns. 

 Results suggest that the availability of school breakfast significantly reduces the 

probability of breakfast-skipping (p<.01). Skipping breakfast is also more common among 

children from lower income households and those living in households that rent versus own their 

home, and less common among children with a college-educated parent. Education may proxy 

here for economic resources, or may be associated with greater awareness of the importance of 

breakfast for children. And, skipping breakfast is more common among children living with a 

single employed mother, relative to those living with both an employed and an at-home parent, 

perhaps reflecting time constraints that may make it more difficult for single employed parents to 

consistently feed children breakfast before school. There are no significant differences 

according to the number of children, and some evidence of less breakfast-skipping in mixed 

urban-rural communities (specifically, communities that are predominantly but not fully urban) 

as compared to fully urban communities. 

 In our next model, we look more closely at the role of the School Breakfast Program, 

allowing for different impacts among children at greater versus lesser risk. Specifically, we 

include, in addition to a breakfast program indicator, a series of interaction terms between 

breakfast program availability and income group. We expect that, rather than a constant impact, 

access to the School Breakfast Program may moderate the risk associated with low income. 

Results are consistent with this hypothesis. The income coefficients are highest for the lowest 

income group, and decline as income increases, indicating the relationship between income and 

breakfast-skipping in the absence of the program. The interaction terms on the several lowest 

income categories are negative and highly significant, suggesting that availability of school 

breakfast offsets the higher risk of breakfast-skipping found among the lower income groups. 

When breakfast is offered at school, then, income appears to be much less important an influence 

on breakfast consumption 
28

 In our third and final model, we use an instrumental variable strategy to control for 

unmeasured differences between children with and without access to breakfast at school. As 

discussed earlier, the identifying variables are the share of children in the school who are 

certified for free or reduced price meals (and the rate squared), as well as the median rent. 

Schools with a larger share of low-income students are much more likely to offer school 

breakfast, while the share of low-income children is not expected to be linked to breakfast 

patterns at the individual level, net of household income and other characteristics. Likewise, we 

expect wealthier areas, proxied by higher housing costs, to be less likely to offer school 

breakfast, but we do not posit any direct link between housing costs and breakfast skipping. The 

first-stage model, shown in Table 10, confirms that the certification rate is indeed a strong 

predictor of breakfast availability (at a decreasing rate, as evidenced by the negative coefficient 

on the squared term). Other predictors of access to school breakfast include lower median rent in 

the area, and living in a more urban area. In the second-stage model, the predicted probability of 

breakfast availability is negatively and significantly linked to breakfast skipping. Results are 

consistent with our earlier model, which controls for actual rather than predicted availability. 

We also examined whether results were sensitive to our choice of identifying variables, by 

alternately including one or the other of the potential identifying variables in the breakfast 

skipping model as well as in the prediction model. While the impact is most precisely estimated 

when certification rate and median rent are both used to identify the model, as in the results 

shown, we find a significant impact of school breakfast with either one serving as an identifying 

restriction. In general, results of the instrumental variable model appear robust to a variety of 

specifications. 

 To illustrate the magnitude of the estimated impact of school breakfast, we use the 

coefficients from Model 2 in Table 9 to estimate the predicted probability of skipping breakfast 

for prototypical students at varying income levels, with and without access to the School 

Breakfast Program (Table 11). Specifically, we consider a student in a rural area, who is living 

with a two employed parents with a high school education, in a household with 2 children and a 

rented home, at each of eight different income levels. In the absence of the School Breakfast 

Program, the predicted probability of skipping breakfast at least once per week is strongly linked 

to income, declining from a high of .42 at the lowest income level to a low of .25 at the highest 

income level. In contrast, when the School Breakfast Program is available, the additional risk 

associated with low income declines dramatically, with the predicted probabilities ranging from 

a high of .30 at the lowest income to a low of .24 at the highest income. Consistent with the 

earlier descriptive results (Figure 2), predictions derived from the multivariate analysis indicate 
29

that access to the School Breakfast Program sharply reduces the negative relationship that 

otherwise exists between low income and breakfast-skipping. 

CONCLUSION 

 This report provides an updated look at patterns and determinants of School Breakfast 

Program participation, as well as impacts of the program on food insecurity and on breakfast 

skipping. Past research clearly shows that school breakfast is inconsistently available, and when 

available, inconsistently implemented, with widely ranging participation patterns. This matters 

more, to the extent that offering the program, and encouraging participation, is in fact beneficial 

to children. In this report, we confirm that participation is inconsistent, even among children 

who appear to have unmet food-related needs, and we identify a range of factors at the household 

and school levels that appear important in influencing the decision to participate. And, we 

provide evidence that access to the program is beneficial in at least two ways—enhancing food 

security and reducing the likelihood that children skip breakfast on school days, with more 

robust findings for the latter outcome. Many would consider these outcomes desirable in their 

own right; they are particularly important in light of growing evidence of their links to both 

cognitive and health-related outcomes including, for instance, academic performance and obesity 

(see, e.g., Joyoti, Frongillo, and Jones 2005; Haines et al 2007). 

 Our analysis confirms that school breakfast is much less widely used than school lunch, 

even among children with access to both programs. Furthermore, breakfast participation is 

almost entirely limited to a subset of the students who regularly eat school lunch. The program 

appears to serve as an expanded way of utilizing school meals for a subset of the students already 

predisposed to such meals; it receives only extremely limited use among other students. And, in 

contrast to school lunch, school breakfast appears to be used primarily by the subset of students 

who are most vulnerable. At the same time, there remains a substantial share of at-risk children 

who have access to the program yet do not participate—including 38 percent of those who are 

food insecure. 

 Multivariate analyses suggest that both economic vulnerability and time constraints are 

linked to participation, with low income and education, more children, and having two employed 

parents in the home emerging as significant predictors. We also find indirect evidence that local 

norms may be important in the participation decision, as evidenced by significantly higher 

participation in schools with a larger share of low-income students, as well as in neighborhoods 

with lower median incomes. Furthermore, it appears the normative nature of participation in 

low-income schools may have spillover effects on higher income children who might otherwise 
30

be less inclined to participate. Pronounced differences in participation according to race and 

ethnicity could also reflect differences in norms or preferences. On the other hand, and counter 

to our expectation, we found less likelihood of participation among children living in counties 

with more liberal political climates, suggesting that prevailing wisdom about political norms and 

attitudes towards public programs may not be reflected in school meal program decisions. 

 Of particular interest, we found that programmatic and logistical aspects of how breakfast 

is structured at the school are significantly linked to the likelihood of participation. Results 

strongly support the hypothesis that increasing the convenience of the School Breakfast Program 

leads to greater participation, with evidence of the importance of where breakfast is offered 

(classroom versus cafeteria), the duration of the breakfast period, and the arrival time of buses 

relative to the start of classes. While smaller-scale local studies have found evidence that 

features such as in-class breakfast increase participation (see, e.g., Lent and Emerson 2006; 

Wong and Emerson 2007), this is the first evidence, to our knowledge, of its impact on a national 

scale. 

 Understanding factors that facilitate or impede participation in the School Breakfast 

Program is particularly important to the extent that participation contributes to desirable 

outcomes for children. Our preferred analyses avoid an explicit focus on participation impacts, 

due to fairly intractable problems stemming from self-selection of more vulnerable children into 

the program, instead capitalizing on differences in program availability to assess program 

impacts. 

Our findings suggest that school breakfast availability is linked to a lower probability of 

marginal household food security among low-income children, though not to food insecurity at 

the standard threshold. That is, the program appears beneficial in offsetting food-related 

concerns among at-risk families, though not necessarily in alleviating food insecurity once 

hardships have crossed the food insecurity threshold. The magnitude of the estimated impact is 

substantial, with availability of school breakfast reducing the predicted probability of marginal 

food security from 47 percent to 33 percent in the hypothetical case considered here. It is 

notable that food insecurity at this marginal threshold has also been linked to poor developmental 

trajectories for children (Jyoti, Frongillo, and Jones 2005). While it is possible that unmeasured 

differences between schools that do and do not offer the program could bias our results, we find 

it more plausible that any bias would result in underestimates, rather than overestimates, of the 

true impact, given that school breakfast is disproportionately offered in schools with higher-need 

populations, at least based on observable characteristics. On the other hand, we were unable to 

substantiate our findings with an instrumental variable model, despite the existence of a strong 
31

state policy instrument. We note the relatively small number of low-income students in our 

sample who do not have access to school breakfast, thus hampering our ability to obtain more 

precise estimates of program impact. 

In contrast to a negative association between School Breakfast Program availability and 

marginal food security, we found a positive association between actual participation in the 

program and both of the food insecurity outcomes. We attribute this relationship to selfselection of higher risk children into the program; that is, we expect that children with more 

immediate food security concerns would be more likely to eat a school breakfast when available, 

making it difficult to obtain valid impact estimates. This problem is pervasive in the literature on 

food assistance program participation and food insecurity. Overall, we find the analyses that 

focus on availability of the program, rather than participation, to have both greater policy 

relevance and greater statistical merit. 

 Evidence that availability of the School Breakfast Program reduces the risk of breakfastskipping is robust. Results, which are based on Wisconsin data, suggest that offering breakfast 

significantly reduces the probability of skipping at least one breakfast per week, and that offering 

breakfast at school serves to moderate the risk of breakfast-skipping associated with low income. 

A beneficial impact is also evident when we use an instrumental variable approach, further 

strengthening our confidence in the findings. Our results are broadly consistent with those of 

Devaney & Stuart (1998), though we use much more recent data, look more formally at how 

impacts change across income levels, and use an instrumental variable approach as a robustness 

check. Note that these results are based on data for only one state; it is possible that the impact 

of the program on breakfast-skipping might differ elsewhere, particularly if patterns of program 

uptake vary across locations. 

Taken as a whole, our findings indicate that access to the School Breakfast Program 

yields significant benefits in terms of enhancing food security among families at the margin of 

food insecurity, and increasing the probability that children—particularly low-income children—

eat breakfast in the morning. Currently, the share of schools that offer the program ranges 

dramatically across states, from a low of 51.5 percent of schools offering lunch in Connecticut, 

to availability in more than 95 percent of schools in 13 states (FRAC 2007). Our findings 

suggest that making school breakfast more broadly available would be beneficial in ensuring that 

more children start their school day with a meal, and that fewer families are confronted with 

uncertain access to sufficient food. 

Furthermore, our findings on participation patterns suggest that these benefits could also 

be enhanced with greater participation among children who already have access to the program. 
32

On the one hand, the most vulnerable children are already the most likely to participate, 

suggesting that the program is generally well targeted. At the same time, there appears to be 

substantial unmet need, as evidenced by nontrivial amounts of nonparticipation among children 

who are food insecure and/or who don’t consistently eat breakfast. As such, it seems likely that 

strengthening participation could yield further benefits, though likely at decreasing rates. To the 

extent that stigma, negative impressions of school breakfast, or logistical barriers are dampening 

participation among children who would find it beneficial to participate, identifying and taking 

steps to counter such barriers seems warranted. 

Our results point to potential strategies to enhance participation through program design 

as well as outreach efforts. In particular, the relationship between program attributes and 

participation patterns suggest that there are policy levers that can be used to enhance 

participation by removing logistical barriers. For instance, Kansas mandates that all school 

buses arrive at school with adequate time for children to eat breakfast (FRAC 2007); in 

Milwaukee, all schools that participate in a Universal Free Breakfast program are required to 

make breakfast available in the classroom. 

In terms of program outreach, the concentration of participants among the subset of 

students who regularly eat lunch suggests that outreach efforts may be most effective if they 

market school breakfast as an expansion of the school lunch concept, building on students’ 

connection with that program. In addition, participation patterns suggest that expanding school 

breakfast to additional schools may be most effective as a means to increase participation in 

schools that already have relatively high rates of lunch participation, as students in those schools 

are most likely to be receptive to the breakfast program. Efforts to expand the reach of school 

breakfast to a broader cross-section of students may benefit by outreach/marketing strategies that 

focus on convenience or other potential benefits, in addition to the economic benefits of 

participating, to help broaden the appeal beyond the current primarily low-income clientele. To 

the extent that stigma associated with the program may discourage participation, successfully 

targeting a broader cross-section may also help to counter existing stereotypes. Social marketing 

efforts to present the program as normative would likely be effective. 

A variety of extensions to this work would be of value. First, it would be useful to 

examine how individual participation in the School Breakfast Program changes over time; the 

ECLS-K is well suited to this given the longitudinal structure of the data. Likewise, it could be 

beneficial to examine the relationship between the School Breakfast Program and food security 

in a longitudinal framework, although the relatively low rates of food insecurity in the ECLS-K 

could create some challenges for such an analysis. Although not directly related to the School 
33

Breakfast Program, the unexpectedly low rate of food insecurity found in these data is also a 

topic that warrants further attention, particularly given the potential value of the data to explore 

the relationship between food insecurity and a variety of child outcomes. In terms of the 

relationship between the School Breakfast Program and breakfast skipping, it would be useful to 

attempt to replicate these findings with data from a national sample; unfortunately, the ECLS-K 

are not well suited to this as breakfast skipping cannot be accurately identified. 

Finally, we note some inherent limitations in our data. With regard to school breakfast 

participation, we only have information on parents’ report of whether a child ‘usually eats a 

breakfast provided by the school’. We do not know anything about occasional (rather than 

usual) participation, nor do we know about the accuracy of the parents’ reports. Other research 

has found that parents report higher levels of school meal participation than do children (Gordon 

et all 2007), and parents’ reports do not clearly distinguish between breakfasts obtained from the 

School Breakfast Program versus other food that may be available at the school. Our reports of 

usual participation are higher than usual participation among all public elementary school 

students as reported in the SNDA-III (Gordon et al 2007) (40.8 percent versus 31.2 percent), 

which could reflect our use of parent-reported participation as compared to the SNDA-III use of 

child-reported participation. Differences could also reflect different sample frames: our sample 

is limited to 3rd graders, who may or may not participate at rates comparable to all elementary 

school students. With regard to our breakfast-skipping analysis, we are likewise limited to 

parents’ reports, which may or may not be an accurate reflection of children’s behavior. And, 

we know from past research that analyses of the determinants of breakfast-skipping are sensitive 

to the specific definition of breakfast that is used (see, e.g., Devaney & Stuart 1998). 
34

Table 1 

Participation in School Meal Programs, Among Third Grade Public School Students 

 Percent Participating2

 N1 School Breakfast School Lunch

All students3 10,350 35.3% 84.4% 

 Students in schools serving breakfast 6,680 41.8% 87.6% 

 Students who eat school lunch 5,610 43.0% 100% 

 Students who don’t eat school lunch 890 6.8% 0% 

 Students who eat school breakfast 2,470 100% 97.6% 

 Students who don’t eat school breakfast 4080 0% 79.5% 

 

Note: Data are from the Early Childhood Longitudinal Survey—Kindergarten Cohort (ECLS-K), wave 5, restricted 

access file. 

1

Due to licensing requirements for ECLS-K restricted data, all sample sizes are rounded to the nearest 10. 2

Percents are weighted. 

3

Full sample includes students with missing information on breakfast availability from school administrators. 

 
35

Table 2 

Participation in School Meal Programs, by Household Characteristics 

 Percent Participating2

N1 School Breakfast School Lunch

Total (limited to children in schools 

 serving school breakfast) 

Income 

6,680 41.8% 87.6% 

 $15,000 or less 750 73.3% 96.8% 

 $15,001 to $20,000 430 64.2% 94.9% 

 $20,001 to $25,000 480 54.5% 94.9% 

 $25,001 to $30,000 550 52.9% 92.9% 

 $30,001 to $35,000 390 42.6% 92.0% 

 $35,001 to $40,000 510 40.2% 87.2% 

 $40,001 to $50,000 700 30.0% 83.6% 

 $50,001 to $75,000 1,090 19.5% 81.0% 

 $75,001 or more 1,050 9.3% 72.2% 

Eligible for free or reduced price meals 

 Eligible 2,800 59.8% 94.3% 

 Not eligible 3,160 20.7% 79.8% 

Highest education in household 

 Less than high school 770 70.0% 96.0% 

 High school 1,720 52.2% 93.1% 

 Some college 2,430 38.8% 86.7% 

 College degree 1,040 20.0% 81.6% 

 Graduate degree 710 14.5% 70.7% 

Number of children 

 1 1,010 37.0% 88.0% 

 2 2,770 34.6% 84.4% 

 3 1,850 45.6% 89.5% 

 4 or more 1,060 58.4% 92.1% 

Food security status 

 Food secure 6,000 35.2% 85.4% 

 Food insecure 590 62.1% 95.7% 

Region 

 Northeast 980 30.5% 78.6% 

 Midwest 1,530 34.0% 89.6% 

 South 2,720 49.8% 89.4% 

 West 1,440 38.7% 87.6% 

Urban vs. Rural Status 

 Large city 1,030 43.2% 88.0% 

 Mid-size city 110 40.9% 87.3% 

 Large suburban area 1,400 35.3% 82.8% 

 Mid-size suburban area 440 35.0% 82.9% 

 Large town 250 46.6% 95.1% 

 Small town 530 45.1% 91.1% 

 Rural area in MSA 740 30.9% 84.0% 

 Rural area outside MSA 1,100 57.1% 94.7% 

 

Note: Data are from the Early Childhood Longitudinal Survey—Kindergarten Cohort (ECLS-K), wave 5, restricted 

access file. Sample is limited to children in schools participating in School Breakfast Program. 1

Due to licensing requirements for ECLS-K restricted data, all sample sizes are rounded to the nearest 10. 2

Percents are weighted. 
36

Table 3 

Probit Models of Participation in School Breakfast Program, 

Among Children Attending Schools that Offer Breakfast 

Model 1 Model 2 

Coefficient Standard Error Coefficient Standard Error 

Intercept 0.164 0.237 0.056 0.240 

Household Characteristics

 

Income 

 $15,000 or less (omitted) (omitted) 

 $15,001 to $20,000 -0.170** 0.087 -0.169* 0.086 

 $20,001 to $25,000 -0.312*** 0.085 -0.317*** 0.085 

 $25,001 to $30,000 -0.320*** 0.084 -0.333*** 0.084 

 $30,001 to $35,000 -0.525*** 0.094 -0.544*** 0.094 

 $35,001 to $40,000 -0.388*** 0.097 -0.409*** 0.097 

 $40,001 to $50,000 -0.634*** 0.104 -0.666*** 0.104 

 $50,001 to $75,000 -0.716*** 0.113 -0.731*** 0.113 

 $75,001 or more -0.957*** 0.122 -0.961*** 0.122 

Eligible for free or reduced price meals 

 Eligible 0.075 0.076 0.297*** 0.103 

 Not eligible (omitted) (omitted) 

Number of children 

 1 (omitted) (omitted) 

 2 0.032 0.057 0.037 0.057 

 3 0.192*** 0.061 0.201*** 0.062 

 4 or more 0.417*** 0.071 0.423*** 0.071 

Household structure 

 Single parent, not employed 0.198** 0.093 0.192** 0.093 

 Single parent, employed 0.062 0.063 0.058 0.063 

 2 parents, 1 employed (omitted) (omitted) 

 2 parents, both employed 0.121** 0.048 0.123** 0.048 

 2 parents, neither employed 0.139 0.132 0.140 0.132 

 Other 0.252** 0.117 0.251** 0.118 

Highest education in household 

 Less than high school (omitted) (omitted) 

 High school -0.198*** 0.066 -0.203*** 0.066 

 Some college -0.273*** 0.066 -0.275*** 0.066 

 College degree -0.445*** 0.082 -0.440*** 0.082 

 Graduate degree -0.639*** 0.096 -0.629*** 0.096 

Housing arrangements 

 Own home (omitted) (omitted) 

 Rent home 0.214*** 0.046 0.212*** 0.046 

Race 

 White (omitted) (omitted) 

 Black 0.639*** 0.063 0.637*** 0.063 

 Hispanic 0.350*** 0.060 0.354*** 0.060 

 Asian 0.192** 0.091 0.181* 0.092 

 Other 0.235*** 0.083 0.228*** 0.083 

Gender 

 Male (omitted) (omitted) 

 Female -0.056 0.037 -0.056 0.037 

Geographic Variables

 

Region 

 Northeast (omitted) (omitted) 

 Midwest 0.280*** 0.084 0.282*** 0.085 

 South 0.284*** 0.081 0.284*** 0.081 

 West 0.124 0.086 0.121 0.086 

Urban vs. Rural Status 

 
37

 Large city -0.406*** 0.080 -0.407*** 0.079 

 Mid-size city -0.318*** 0.070 -0.308*** 0.069 

 Large suburban area -0.220*** 0.070 -0.214*** 0.069 

 Mid-size suburban area -0.332*** 0.089 -0.327*** 0.089 

 Large town -0.162 0.110 -0.159 0.108 

 Small town -0.125 0.083 -0.134 0.082 

 Rural area in MSA -0.271*** 0.078 -0.282*** 0.077 

 Rural area outside MSA (omitted) (omitted) 

Local Characteristics

 

School free/reduced price meal 

certification rate 

0.007*** 0.001 0.010*** 0.001 

 

School certification rate*child eligibility -0.005*** 0.001 

Percent of county voting democratic -0.010*** 0.002 -0.010*** 0.002 

Median income in county($100’s) -0.0012*** 0.0003 -0.0012*** 0.0003 

Unemployment rate in county 0.006 0.014 0.005 0.014 

Logistical & Programmatic Features

 

Location of school breakfast served 

 Cafeteria (omitted) (omitted) 

 Classroom 0.504*** 0.102 0.504*** 0.102 

 Common areas 0.055 0.123 0.069 0.123 

 Other locations -0.278 0.234 -0.268 0.234 

Duration of school breakfast 

period(minutes) 

0.004** 0.002 0.004** 0.002 

Time between school arrival & start of class, 

for school bus riders

 

 Fewer than 10 minutes (omitted) (omitted) 

 10 to 20 minutes 0.331*** 0.072 0.325*** 0.074 

 More than 20 minutes 0.938*** 0.096 0.932*** 0.096 

Transportation to school 

 School bus (omitted) (omitted) 

 Parents drive 0.008 0.069 0.001 0.069 

 Carpool 0.051 0.149 0.044 0.149 

 Walk 0.138* 0.083 0.133 0.083 

 Someone else drives -0.054 0.124 -0.060 0.124 

 Other 0.396** 0.190 0.400** 0.191 

 

Log-likelihood -3208.309 -3202.969 

N 6410 6410 

Notes: *=p<.1, **=p<.05, ***=p<.01; 

Data are from the Early Childhood Longitudinal Survey—Kindergarten Cohort (ECLS-K), wave 5, restricted access 

file. 

Due to licensing requirements for ECLS-K restricted data, all sample sizes are rounded to the nearest 10. 

Dependent variable is school breakfast participation, coded 1 when the respondent indicates that the child usually 

eats a school breakfast. 

Model also includes dummy variables denoting missing information on independent variables, wherever relevant, as 

well as variables for other housing arrangements. 
38

Table 4 

Household Food Insecurity Among Third Grade Public School Students 

Percent2

Total N1

Standard 

Food Insecurity 

Measure 

Marginal 

Food Security

Measure 

All students3 8,120 8.8% 16.8% 

 Below 185% poverty line 3,010 16.6% 30.1% 

 Above 185% poverty line 4,340 2.6% 6.1% 

Limited to households below 185% of 

poverty line 

 

School offers breakfast 2,800 16.1% 29.2% 

School doesn’t offer breakfast 210 24.5% 42.2% 

 

Notes: Data are from the Early Childhood Longitudinal Survey—Kindergarten Cohort (ECLS-K), wave 5, restricted 

access file. 

Households are considered marginally food secure if the respondent answers at least one of the questions on the 

food security scale in the affirmative; the standard food security measure requires at least three affirmative responses 

to be considered food insecure. 

1

Due to licensing requirements for ECLS-K restricted data, all sample sizes are rounded to the nearest 10. 2

Percents are weighted. 

3

Students with missing information on School Breakfast Program availability from school administrators are 

excluded. 
39

Table 5. 

Probit Models of Household Food Insecurity, Among Low Income Third Grade Public 

School Students 

 Standard Food Insecurity Marginal Food Security 

Coeff. SE Coeff. SE 

Intercept -1.199*** 0.257 -0.394* 0.223 

School breakfast available -0.113 0.123 -0.369*** 0.107 

Income 

 $15,000 or less (omitted) (omitted) 

 $15,001 to $20,000 -0.037 0.090 0.039 0.081 

 $20,001 to $25,000 -0.117 0.093 -0.164** 0.084 

 $25,001 to $30,000 -0.467*** 0.107 -0.437*** 0.091 

 $30,001 to $35,000 -0.358*** 0.121 -0.411*** 0.103 

 $35,001 to $40,000 -0.436*** 0.139 -0.377*** 0.115 

 $40,001 to $50,000 -0.526*** 0.171 -0.531*** 0.142 

 $50,001 to $75,000 -0.713 0.596 -0.697 0.465 

 0 0 0 0 

Highest education in household 

 Less than high school (omitted) (omitted) 

 High school -0.156* 0.083 -0.127* 0.075 

 Some college -0.187** 0.086 -0.123 0.076 

 College degree -0.400*** 0.145 -0.192* 0.118 

 Graduate degree -0.675*** 0.244 -0.452*** 0.181 

Housing arrangements 

 Own (omitted) (omitted) 

 Rent 0.169*** 0.067 0.183*** 0.059 

 Temporary 0.859** 0.414 0.342 0.409 

Parent’s health status 

 Excellent -0.186*** 0.070 -0.153*** 0.060 

 Good (omitted) (omitted) 

 Poor 0.505*** 0.077 0.401*** 0.071 

Number of children 

 1 (omitted) (omitted) 

 2 0.045 0.112 0.064 0.098 

 3 0.155 0.112 0.164* 0.098 

 4 or more 0.247** 0.116 0.301*** 0.102 

Race of children 

 White (omitted) (omitted) 

 Black 0.073 0.094 0.234*** 0.082 

 Hispanic -0.076 0.091 0.024 0.080 

 Asian 0.015 0.139 0.021 0.122 

 Other 0.211* 0.120 0.234** 0.105 

Household structure & 

employment 

 

 Single parent, not employed 0.089 0.114 0.200** 0.103 

 Single parent, employed -0.001 0.088 -0.076 0.078 

 2 parents, 1 employed (omitted) (omitted) 

 2 parents, both employed -0.113 0.081 -0.061 0.070 

 2 parents, neither employed 0.124 0.156 0.110 0.142 

 Other -0.291 0.183 -0.225 0.158 

Median rent 0.001** 0.0002 0.0003* 0.0002 

Region 

 Northeast (omitted) (omitted) 

 Midwest 0.167 0.113 0.102 0.096 

 South 0.062 0.106 0.022 0.090 

 West 0.196* 0.108 0.139 0.094 

Urban vs. Rural Status 

 Large city 0.043 0.121 -0.103 0.102 

 Mid-size city 0.245** 0.113 0.164* 0.095 

 Large suburban 0.102 0.115 -0.029 0.097 
40

 Mid-size suburban 0.399*** 0.137 0.184 0.121 

 Large town 0.238 0.175 -0.019 0.155 

 Small town 0.433*** 0.126 0.183* 0.111 

 Rural area in MSA 0.159 0.137 0.086 0.115 

 Rural area outside MSA (omitted) (omitted) 

School free/reduced price meal 

certification rate 

-0.001 0.001 -0.002 0.001 

Log-likelihood -1179.211 -1628.923 

N 2,960 2,960 

Notes: *=p<.1, **=p<.05, ***=p<.01 

Data are from the Early Childhood Longitudinal Survey—Kindergarten Cohort (ECLS-K), wave 5, restricted access 

file. 

Due to licensing requirements for ECLS-K restricted data, all sample sizes are rounded to the nearest 10. 

Households are considered marginally food secure if the respondent answers at least one of the questions on the 

food security scale in the affirmative; the standard food security measure requires at least three affirmative responses 

to be considered food insecure. 

Model also includes dummy variables denoting missing information on independent variables, wherever relevant, as 

well as variables for other housing arrangements. 
41

Figure 1 

Predicted Probability of Marginal Household Food Security Among Low Income 

Third Grade Public School Students, Based on Probit Model 

Predicted probabilities are based on probit model of marginal food security among children below 185% of poverty 

line, using data from Early Childhood Longitudinal Survey—Kindergarten Cohort, wave 5, restricted access files 

(see Table 5). Predictions assume the following characteristics: household is in rural Midwest in county with 

median rent of $600/month; school has free and reduced price meal certification rate of 25%; student is white and 

lives with single employed mother who rents home and is in good health with high school education, two children, 

and annual income of $15,001-$20,000. 
42

Table 6. 

Instrumental Variable Models of Household Food Insecurity, Among Low Income Third 

Grade Public School Students 

 1st Stage 2nd Stage 

Prediction Model Standard Food Insecurity Marginal Food Security 

Coeff. SE Coeff. SE Coeff. SE 

Intercept 1.730 *** 0.310 -1.370*** 0.348 -0.669** 0.300 

 

Predicted probability of school 

breakfast availability 

 0.085 0.296 -0.133 0.254 

Covered by State Policy Mandate 1.149*** 0.159 

Region 

 Northeast (omitted) (omitted) (omitted) 

 Midwest -0.665*** 0.140 0.185(p=0.109) 0.115 0.121 0.098 

 South 1.108*** 0.221 0.055 0.106 0.002 0.090 

 West 0.594*** 0.159 0.193* 0.108 0.124 0.094 

Urban vs. Rural Status 

 Large city 0.135 0.217 0.043 0.121 -0.101 0.102 

 Mid-size city 0.088 0.206 0.244** 0.113 0.158* 0.095 

 Large suburban -0.346** 0.171 0.118 0.116 -0.003 0.098 

 Mid-size suburban -0.453** 0.203 0.406*** 0.137 0.193(p=0.109) 0.121 

 Large town -0.833*** 0.266 0.249 0.175 -0.006 0.154 

 Small town 0.101 0.223 0.433*** 0.126 0.180(p=0.106) 0.111 

 Rural area in MSA 0.396* 0.233 0.151 0.137 0.082 0.116 

 Rural area outside MSA (omitted) (omitted) (omitted) 

School free/reduced price meal 

certification rate 

0.038*** 0.004 -0.003 0.003 -0.0002 0.003 

Certification rate squared -0.0002*** 0.000 0.0000 0.0000 -0.0000 0.0000 

Median rent in county -0.003*** 0.0004 0.001** 0.0003 0.0004** 0.0002 

Highest education in household 

 Less than high school (omitted) (omitted) (omitted) 

 High school -0.193 0.182 -0.156* 0.083 -0.125* 0.075 

 Some college -0.438*** 0.174 -0.181** 0.086 -0.117 0.077 

 College degree -0.396* 0.211 -0.391*** 0.145 -0.182 0.118 

 Graduate degree -0.267 0.281 -0.673*** 0.244 -0.442*** 0.180 

Income 

 $15,000 or less (omitted) (omitted) 

 $15,001 to $20,000 -0.038 0.090 0.036 0.081 

 $20,001 to $25,000 -0.117 0.093 -0.163** 0.084 

 $25,001 to $30,000 -0.471*** 0.107 -0.443*** 0.091 

 $30,001 to $35,000 -0.363*** 0.121 -0.419*** 0.103 

 $35,001 to $40,000 -0.435*** 0.139 -0.370*** 0.115 

 $40,001 to $50,000 -0.525*** 0.171 -0.529*** 0.142 

 $50,001 to $75,000 -0.723 0.598 -0.735 0.465 

 $75,001 or more 0 0 0 0 

Housing ownership 

 Own (omitted) (omitted) 

 Rent 0.167*** 0.067 0.174*** 0.058 

 Temporary 0.870** 0.415 0.374 0.412 

Parent’s health status 

 Excellent -0.187*** 0.070 -0.154*** 0.060 

 Good (omitted) (omitted) 

 Poor 0.506*** 0.077 0.403*** 0.071 

Number of children 

 1 (omitted) (omitted) 
43

 2 0.047 0.112 0.068 0.097 

 3 0.157 0.112 0.167* 0.098 

 4 or more 0.247** 0.116 0.303*** 0.102 

Race of children 

 White (omitted) (omitted) 

 Black 0.073 0.094 0.232*** 0.082 

 Hispanic -0.079 0.091 0.021 0.080 

 Asian 0.014 0.139 0.015 0.122 

 Other 0.212* 0.120 0.227** 0.105 

Household structure & 

employment 

 

 Single parent, not employed 0.090 0.114 0.204** 0.103 

 Single parent, employed 0.002 0.088 -0.064 0.078 

 2 parents, 1 employed (omitted) (omitted) 

 2 parents, both employed -0.110 0.081 -0.050 0.069 

 2 parents, neither employed 0.128 0.156 0.117 0.142 

 Other -0.290 0.184 -0.211 0.158 

Log-likelihood -408.939 -1179.572 -1634.612 

N 2,960 2,960 2,960 

Notes: *=p<.1, **=p<.05, ***=p<.01 

Data are from the Early Childhood Longitudinal Survey—Kindergarten Cohort (ECLS-K), wave 5, restricted access 

file. 

Due to licensing requirements for ECLS-K restricted data, all sample sizes are rounded to the nearest 10. 

Households are considered marginally food secure if the respondent answers at least one of the questions on the 

food security scale in the affirmative; the standard food security measure requires at least three affirmative responses 

to be considered food insecure. 

Model also includes dummy variables denoting missing information on independent variables, wherever relevant, as 

well as variables for other housing arrangements. 
44

Table 7. 

Probit Models of Household Food Insecurity, Among Low Income Third Grade Public 

School Students With Access to School Breakfast Program 

Standard Food Insecurity Marginal Food Security 

Coeff. SE Coeff. SE 

Intercept -1.438*** 0.249 -0.935*** 0.215 

Participates in School Breakfast 0.144** 0.070 0.197*** 0.061 

Income 

 $15,000 or less (omitted) (omitted) 

 $15,001 to $20,000 -0.019 0.095 0.081 0.085 

 $20,001 to $25,000 -0.084 0.100 -0.099 0.089 

 $25,001 to $30,000 -0.484*** 0.116 -0.479*** 0.099 

 $30,001 to $35,000 -0.331*** 0.132 -0.406*** 0.114 

 $35,001 to $40,000 -0.461*** 0.155 -0.444*** 0.128 

 $40,001 to $50,000 -0.448** 0.200 -0.699*** 0.175 

 $50,001 to $75,000 -5.412 4830.308 -0.694 0.557 

 $75,001 or more 0 0 0 0 

Highest education in household 

 Less than high school (omitted) (omitted) 

 High school -0.156* 0.087 -0.110 0.078 

 Some college -0.189** 0.091 -0.116 0.081 

 College degree -0.477*** 0.169 -0.227* 0.135 

 Graduate -0.621** 0.273 -0.402** 0.207 

Housing ownership 

 Own (omitted) (omitted) 

 Rent 0.145** 0.072 0.120* 0.063 

 Temporary 1.035** 0.443 0.460 0.437 

Parent’s health status 

 Excellent -0.155** 0.076 -0.130** 0.065 

 Good (omitted) (omitted) 

 Poor 0.498*** 0.082 0.386*** 0.075 

Number of children 

 1 (omitted) (omitted) 

 2 -0.009 0.119 0.043 0.104 

 3 0.125 0.118 0.186* 0.104 

 4 or more 0.245** 0.124 0.330*** 0.109 

Race of children 

 White (omitted) (omitted) 

 Black 0.035 0.100 0.196** 0.087 

 Hispanic -0.059 0.098 0.047 0.086 

 Asian -0.119 0.169 -0.004 0.144 

 Other 0.025* 0.140 0.045 0.120 

Household structure & 

employment 

 

 Single parent, not employed 0.077 0.119 0.176* 0.108 

 Single parent, employed -0.006 0.095 -0.088 0.084 

 2 parents, 1 employed (omitted) (omitted) 

 2 parents, both employed -0.101 0.088 -0.092 0.075 

 2 parents, neither employed 0.175 0.165 0.099 0.152 

 Other -0.295 0.192 -0.194 0.165 

Median rent 0.001* 0.0003 0.0004 0.0002 

Region 

 Northeast (omitted) (omitted) 

 Midwest 0.201 (p=108) 0.125 0.131 0.107 

 South 0.072 0.114 -0.003 0.098 

 West 0.142 0.119 0.027 0.104 

Urban vs. Rural Status 

 Large city 0.158 0.132 -0.065 0.112 

 Mid-size city 0.319*** 0.123 0.207** 0.103 
45

 Large suburban 0.161 0.128 0.012 0.107 

 Mid-size suburban 0.485*** 0.151 0.269** 0.133 

 Large town 0.271 0.187 -0.048 0.166 

 Small town 0.530*** 0.136 0.259** 0.119 

 Rural area in MSA 0.211 0.147 0.128 0.124 

 Rural area outside MSA (omitted) (omitted) 

School free/reduced price meal 

certification rate 

-0.001 0.001 -0.001 0.001 

Log-likelihood -1016.068 -1392.186 

N 2,620 2,620 

Notes: *=p<.1, **=p<.05, ***=p<.01 

Data are from the Early Childhood Longitudinal Survey—Kindergarten Cohort (ECLS-K), wave 5, restricted access 

file. 

Due to licensing requirements for ECLS-K restricted data, all sample sizes are rounded to the nearest 10. 

Households are considered marginally food secure if the respondent answers at least one of the questions on the 

food security scale in the affirmative; the standard food security measure requires at least three affirmative responses 

to be considered food insecure. 

Model also includes dummy variables denoting missing information on independent variables, wherever relevant, as 

well as variables for other housing arrangements. 

 
46

Table 8 

Breakfast-Skipping Among Wisconsin Elementary School Students 

 Percent skipping breakfast 

 N Children with 

School Breakfast 

Available 

Children without 

School Breakfast 

Available 

Total 7,428 23.7% 24.8% 

Food security status 

 Food insecure 1,630 35.2% 46.1% 

 Food secure 5,898 20.3% 20.1% 

Food pantry use 

 Yes 905 30.2% 45.7% 

 No 6,524 22.6% 22.7% 

Food stamp participation 

 Yes 1,101 28.6% 37.2% 

 No 6,335 22.6% 23.4% 

 

Note: Data are from the Wisconsin Schools Food Security Survey. 

Students are considered to skip breakfast if the respondent indicates that the child skips breakfast at least once in a 

typical week. 
47

Figure 2 

Breakfast-Skipping among Elementary School Children in Wisconsin, by Income Level 

and School Breakfast Program Availability 

0

5

10

15

20

25

30

35

40

45

 

$15,000

or less

 

$15,001

to

$20,000

 

$20,001

to

$25,000

 

$25,001

to

$30,000

 

$30,001

to

$35,000

 

$35,001

to

$40,000

 

$40,001

to

$50,000

 

$50,001

or more

Income

Percentage Skipping Breakfast

Schools not offering breakfast

Schools offering breakfast
48

Table 9 

Probit Models of Breakfast-Skipping Among Elementary School Children in Wisconsin 

 Model 1 Model 2 Model 3 

 Coeff. SE Coeff. SE Coeff. SE 

Intercept -0.367** 0.186 -0.444** 0.188 -0.301 0.190 

School breakfast available -0.105*** 0.038 0.031 0.054 

Predicted probability of 

 school breakfast availability1

 

-0.153*** 0.057 

 

Income 

 

 $15,000 or less 0.242*** 0.066 0.509*** 0.119 0.249*** 0.067 

 $15,001 to $20,000 0.183*** 0.069 0.453*** 0.123 0.191*** 0.070 

 $20,001 to $25,000 0.190*** 0.074 0.517*** 0.142 0.182** 0.075 

 $25,001 to $30,000 0.164** 0.079 0.301* 0.167 0.195** 0.081 

 $30,001 to $35,000 0.103 0.065 0.167 0.114 0.101 0.066 

 $35,001 to $40,000 0.184*** 0.062 0.385*** 0.110 0.191*** 0.063 

 $40,001 to $50,000 0.112* 0.067 0.091 0.124 0.121* 0.068 

 $50,001 or more (omitted) (omitted) (omitted) 

Breakfast availability*Income 

 Available*$15,000 or less -0.349*** -0.349 

 Available*$15,001 to $20,000 -0.374*** -0.374 

 Available*$20,001 to $25,000 -0.443*** -0.443 

 Available*$25,001 to $30,000 -0.197 -0.197 

 Available*$30,001 to $35,000 -0.104 -0.104 

 Available*$35,001 to $40,000 -0.297** -0.297 

 Available*$40,001 to $50,000 0.015 0.015 

 Available*$50,001 or more (omitted) 

Housing arrangements 

 Own (omitted) (omitted) (omitted) 

 Rent 0.083* 0.043 0.083* 0.043 0.076* 0.044 

 Homeless -0.033 0.156 -0.023 0.156 -0.070 0.168 

Highest education in household 

 Less than high school (omitted) (omitted) (omitted) 

 High school -0.054 0.082 -0.052 0.082 -0.053 0.084 

 Some college -0.122 0.082 -0.119 0.082 -0.128 0.084 

 College degree -0.312*** 0.086 -0.312*** 0.086 -0.322*** 0.087 

Household structure 

 Single mother, not employed -0.045 0.106 -0.051 0.107 -0.028 0.108 

 Single mother, employed 0.149** 0.060 0.142** 0.060 0.144** 0.061 

 Single father 0.013 0.103 0.011 0.103 0.014 0.104 

 2 parents, 1 employed (omitted) (omitted) (omitted) 

 2 parents, both employed 0.038 0.047 0.038 0.047 0.025 0.047 

 2 parents, neither employed 0.008 0.131 0.010 0.131 0.010 0.133 

 Grandparents 0.006 0.151 0.000 0.151 0.042 0.156 

 Other 0.138* 0.077 0.141* 0.077 0.108 0.078 
49

Notes: *=p<.1, **=p<.05, ***=p<.01 

Data are from the Wisconsin Schools Food Security Survey. 

The dependent variable, breakfast-skipping, is coded as 1 if the respondent indicates that the child skips breakfast at 

least once in a typical week,Model also includes dummy variables denoting missing information on independent 

variables, wherever relevant. 

1

Predictions generated by probit model of School Breakfast Program availability; model shown in Table 10. 

Number of children 

 1 (omitted) (omitted) (omitted) 

 2 -0.032 0.045 -0.038 -0.038 -0.04 .045 

 3 -0.006 0.050 -0.005 -0.005 -0.011 .050 

 4 or more 0.034 0.061 0.031 0.031 0.027 .062 

Urban vs. Rural Status of zipcode 

 All urban (omitted) (omitted) (omitted) 

 Mostly urban -0.326** 0.155 -0.330** 0.155 -0.339** 0.156 

 Mostly rural -0.201 0.158 -0.208 0.158 -0.215 0.158 

 All rural -0.251 0.155 -0.260* 0.155 -0.252 0.155 

Log-likelihood -4059.274 -4048.727 -3938.127 

N 7528 7528 7299 
50

Table 10 

Probit Model of School Breakfast Availability Among Elementary School Children in 

Wisconsin1

Coeff. SE 

Intercept 0.931*** 0.062 

School free/reduced price certification 

rate 

3.101*** 0.132 

School certification rate squared -1.972*** 0.154 

Median rent($100’s) -0.179*** 0.006 

Urban vs. Rural Status 

 All urban (omitted) 

 Mostly urban -0.253*** 0.038 

 Mostly rural -0.260*** 0.039 

 All rural -0.259*** 0.039 

Log-likelihood -1992.428 

N 7553 

Notes: *=p<.1, **=p<.05, ***=p<.01 

Data are from the Wisconsin Schools Food Security Survey. 

Model also includes dummy variables denoting missing information on independent variables, wherever relevant. 

1

Model is used to estimate the predicted probability of school breakfast availability in Model 3, Table 9. 
51

Table 11 

Predicted Probability of Breakfast-Skipping Among Wisconsin Elementary School 

Students With and Without Access to School Breakfast Program 

 Predicted probability of skipping breakfast 

 N Children with 

School Breakfast 

Available 

Children without 

School Breakfast 

Available 

 

Income 

 $15,000 or less .30 .42 

 $15,001 to $20,000 .27 .40 

 $20,001 to $25,000 .27 .42 

 $25,001 to $30,000 .28 .34 

 $30,001 to $35,000 .27 .29 

 $35,001 to $40,000 .28 .37 

 $40,001 to $50,000 .28 .27 

 $50,000 or more .25 .24 

 

Note: Predicted probabilities are based on probit model of breakfast skipping, using data from the Wisconsin 

Schools Food Security Survey (see Table 9, Model 2). Predictions assume the student’s household has 2 children 

and 2 employed parents, with high school education, rents their home, and lives in rural area in Wisconsin. 

 
52

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