In 2007-2008, approximately 36% of US children aged 6 to 11 years were classified as overweight and approximately 20% were considered obese.1 The prevalence of obesity among US children and adolescents aged 10 to 17 years increased by 10% between 2003 and 2007. During the same time period, the prevalence of obesity among girls increased approximately 18%.2 Pediatric obesity has been associated with type 2 diabetes, cardiovascular disease, several types of cancer, and hypertension, especially when tracked into adulthood.3 Obesity among young girls has been associated with early puberty,4- 6 and early puberty among young girls has been linked to unfavorable body image,7,8 eating problems,9 depression,10 earlier onset of sexual intercourse,11 and breast cancer in womanhood.12- 15
Policy makers and researchers are focusing on school settings and the food that these settings provide as a possible mechanism to reduce childhood obesity. The National School Lunch Program (NSLP) was established in 1946 as an intervention and prevention program intended to mitigate malnutrition and promote the healthy development of schoolchildren by providing a nutritional safety net for children from low-income families. The NSLP increases the availability of food and protein and is associated with lower intake of added sugars and an increased intake of vitamins and minerals.16,17 Although the NSLP was not originally designed as an obesity prevention program, it has undergone criticism for contributing to an increase in dietary fat and calories among children who participate in the program.17- 19
Whether the NSLP is contributing to the obesity epidemic is largely inconclusive, and it is unknown whether NSLP participation affects the relative weight status of girls and boys differently. Using cross-sectional data on students from grades 1 through 12, Gleason and Dodd20 found that participation in the NSLP was not related to a student's body mass index (BMI; calculated as weight in kilograms divided by height in meters squared). However, findings based on longitudinal data differ. Using data from the Early Childhood Longitudinal Study–Kindergarten (ECLS-K), Schanzenbach19 found that by the end of first grade, children eligible for free or reduced-price lunches weighed more than children right above or below the income-eligible cutoff and were more likely obese, despite the fact that both groups of children entered kindergarten with similar BMIs and obesity rates. Millimet et al21 also used data from the ECLS-K and found a positive association between participation in the NSLP at kindergarten and a child's weight at third grade. Yet, these longitudinal studies do not make a distinction as to whether the sex of the child moderates the positive association between NSLP participation and BMI.
Furthermore, to our knowledge, there are no known published studies on the patterns of NSLP participation among low-income children and their association with sex differences in BMI trajectories. Limited research has been conducted on the patterns of participation in the food stamp program among adults. Baum22 found that among both women and men, a positive association existed between persistent participation in the food stamp program and overweight or obesity, whereas Gibson23 found this association only in women. In a study of preadolescents and adolescents aged 12 to 14 years, Gibson24 reported that long-term participation had a positive influence on young girls' weight gain but a negative influence on young boys' weight gain. By examining participation patterns in the NSLP, we aim to determine whether long-term participation in the NSLP has a cumulative positive effect on the weight status of children and early adolescents, in the same way that participation in the food stamp program has had a cumulative positive effect on the weight status of women22 and adolescent girls.24 The positive association could further inform research on the precursors to obesity.
Building on recent NSLP studies19,21 and studies that have focused on longitudinal participation patterns,22- 24 our study focuses on children from low-income families to examine (1) participation patterns (ie, persistent, transient, or no participation) in the NSLP from kindergarten to fifth grade; (2) how NSLP participation relates to BMI trajectories through eighth grade; and (3) whether NSLP participation influences sex differences in BMI trajectories. It is hypothesized that among low-income children, those who persistently participate in the NSLP will display more socioeconomically disadvantaged characteristics than children who temporarily or never participate. In addition, it is hypothesized that the pattern in which individuals participate in the NSLP may influence their BMI, with the NSLP having a positive cumulative effect on relative weight status among individuals who persistently participate. Based on work by Gibson,24 it is hypothesized that participation in the NSLP will positively influence the BMI trajectories of girls and will negatively influence the BMI trajectories of boys.
Data were obtained from the ECLS-K, a nationally representative, longitudinal study of children's school experiences and development conducted by the National Center for Education Statistics. A total of 21 260 children from 1280 public and private schools were first assessed in kindergarten. The ECLS-K collected data on children in the fall and spring of kindergarten (1998-1999), in the fall and spring of first grade (1999-2000), and in the spring of third grade (2002), fifth grade (2004), and eighth grade (2007). For consistency, we focus on data collected in the spring term of each grade listed. Further information on sampling, recruitment, and attrition can be found at http://nces.ed.gov/ecls/kindergarten.asp. The institutional review board at The Pennsylvania State University approved our study.
The analysis sample consists of 1140 students from low-income families. The analysis sample was selected on the basis of those students who were interviewed through eighth grade (n = 9725). The sample was further restricted to students who attended schools that participated in the NSLP (3916 students were excluded) and students who were eligible to participate in the program at kindergarten based on their families' income (≤185% of the federal poverty level) (3407 students were excluded). Students who never responded to questions about school lunch program participation were not included in the analysis sample (4 students were excluded). Finally, students who had missing information on the covariates were dropped from the final analysis sample (800 students were excluded).
Mean differences were assessed between the students included in the analysis sample and the students excluded because of missing data on the covariates (eTable 1). The students included in the final analyses were less likely to have persistently participated in the NSLP and were more likely to have temporarily participated or to have never participated in the NSLP compared with students in the excluded sample. Students included in the analysis were less likely to be non-Hispanic black or other race and were more likely to be non-Hispanic white compared with students in the excluded sample. The analysis sample also included students who were less likely to attend Head Start and who watched fewer hours of television per day compared with students who were excluded from the analysis sample. Students in the included sample lived with mothers who were more likely to be married, more likely to have a high school education, and less likely to be employed full time compared with students who were excluded from the analysis sample. Students included in the analysis lived in households that earned $20 000 or more and in households where families ate more breakfast meals together. Students included in the analysis also had significantly lower BMIs at eighth grade compared with students who were excluded from the sample.
Students' BMIs were calculated from direct measurement of height and weight collected at each time point. Height was measured in duplicate using a standing height board, and weight was also measured in duplicate using a digital bathroom scale (Shorr Products, Olney, Maryland). The mean of the 2 measures was used to calculate age-specific and sex-specific BMIs on the basis of national reference criteria outlined by the Centers for Disease Control and Prevention.25
At each data collection point, parents were asked to indicate whether their child receives free or reduced-price lunches at school. Using this information, we created 4 dichotomous variables indicating that the child participated in the school lunch program during kindergarten, first grade, third grade, and fifth grade. We decided to focus on NSLP participation during the elementary school years because the available school lunch options are qualitatively different in elementary school compared with middle school and high school.
Three mutually exclusive variables that capture the consistency of participation in the NSLP were also created: no participation, persistent participation, and transient participation. Students who never participated in the NSLP at any of the 4 points were in the no-participation group. Students who participated in the NSLP at all 4 points were in the persistent-participation group. Students who participated at some grade levels but not in others were in the transient-participation group.
Factors capturing the characteristics of the student, mother, and household that are related to program participation and relative weight status were included in our models as control variables (eTable 2). A sedentary lifestyle and higher levels of television viewing have been associated with overweight and obesity,26,27 whereas full-day Head Start attendance has been associated with a reduction in the proportion of children who are classified as obese.28 Thus, measures of physical activity, television viewing habits, and Head Start attendance were included in the analyses. Physical activity was measured as the mean number of days per week that a child received 20 minutes of exercise; television viewing was captured as the mean number of hours per day that a child watched television. Family meals, captured in 2 separate variables as the number of times a family eats (1) breakfast and (2) dinner, are included because research on children and adolescents has found that eating breakfast29- 31 and dinner32,33 regularly has a protective effect against overweight and obesity. Given that income can be volatile over time and that this income volatility may influence eligibility in the NSLP, we included 3 variables indicating income eligibility in the NSLP (≤185% of the federal poverty level) at first, third, and fifth grade. State-level contextual variables are included because they are related to program participation and may be related to relative weight status.
Descriptive analysis was conducted and Poisson regression models were constructed using STATA version 10.1 statistical software (StataCorp LP, College Station, Texas). To answer the first research question of what characteristics predict children experiencing persistent and transient participation, incidence risk ratios were estimated using Poisson regression models. The Huber-White sandwich variance estimator was included in the regression models to account for the fact that the outcome is binary. The regression models resulted in 2 comparisons being made: (1) a comparison of children who persistently participated in the NSLP with children who did not persistently participate (ie, persistent participants vs transient participants and nonparticipants) and (2) a comparison of children who persistently participated in the NSLP with children who temporarily participated in the NSLP (ie, persistent participants vs transient participants). The control variables outlined in eTable 2 were included in all of these models. Although we include a rich set of covariates in our models, we acknowledge that the children who participate in the NSLP are different from those who do not participate and that the results from this model may be capturing some unobservable differences between these 2 groups (differences that are not mitigated by the software program).
Nonlinear mixed models (PROC MIXED in SAS version 9.2 statistical software [SAS Institute, Inc, Cary, North Carolina]) were used to examine the association between NSLP participation and the trajectories of BMI in children for the full sample and separately by sex. The main effects of time (ie, slope), NSLP participation, and NSLP participation × time interaction were tested in this model. A significant main effect of NSLP participation suggests that the level of BMI differs at that particular time for children participating in the NSLP compared with children not participating in the NSLP; a significant interaction effect provides evidence for a differential rate of change in relative weight over time for children participating in the NSLP compared with children not participating in the NSLP. For all mixed models, nonlinearity was further tested by including age-squared, age-cubed, and sex × age interactions terms. However, these terms were nonsignificant and worsened the overall model fit; thus, they were excluded from the final models. All models included quadratic and cubic terms for the slope to create the best-fitting model for the data; the terms do not add theoretical meaning to the results.
Eighty-two percent of the children from low-income families (35% persistent and 47% transient) participated in the NSLP at some point during kindergarten to fifth grade (Table 1), with children in the transient group participating, on average, 3 of the possible 4 times (results not shown). There are few statistically significant differences in BMI percentiles at each grade level between children who participated in the NSLP and children who did not. Descriptive statistics of participation patterns demonstrate that low-income children who persistently and temporarily participate in the NSLP were more socioeconomically disadvantaged than those who were from low-income families but never participated. In addition, bivariate statistics demonstrated that children who persistently participated in the NSLP were more socioeconomically disadvantaged than children who temporarily participated; however, both groups shared similar disadvantaged characteristics.
Poisson regression models further confirm the association between disadvantaged characteristics and persistent and transient participation in the NSLP. In Table 2, we compare children who persistently participate in the NSLP with those who do not persistently participate. We found that low-income non-Hispanic black children were 39% more likely than low-income non-Hispanic white children to persistently participate in the NSLP; low-income Hispanic children were 79% more likely than low-income non-Hispanic white children to persistently participate in the NSLP. Children who participated in Head Start were 19% more likely than children who did not participate in Head Start to persistently participate in the NSLP. Children who, on average, spent more hours per day watching television were 9% more likely than children who spent fewer hours per day watching television to persistently participate in the NSLP. Children whose mothers did not complete high school were 29% more likely than children whose mothers completed high school to persistently participate in the program. Children whose mothers were employed full time were 16% more likely than children whose mothers were not employed full time to persistently participate in the NSLP. Children who lived in households with a family income less than 185% of the federal poverty level at first, third, and fifth grade were approximately 1.5 to 2 times more likely than other children to persistently participate in the program. Children whose families ate breakfast together more frequently were 3% less likely than other children to persistently participate in the NSLP. Children who lived in states with a greater percentage of NSLP participants were 12% more likely than children who lived in other states to persistently participate in the NSLP.
In Table 2, we also compare children who persistently participated in the NSLP with children who transitioned in and out of the program. The results are similar to those comparing persistent participants with nonparticipants; however, the size of the coefficients is smaller and/or less significant for some characteristics. This is expected because the sample size for these 2 groups (ie, persistent participants and transient participants) is smaller and more homogeneous. Thus, similar disadvantaged characteristics were associated with persistently and temporarily participating in the NSLP.
Nonlinear mixed models with the 3 program participation groups (never, persistent, and transient) were first conducted for the full sample. Persistent and transient participation groups were collapsed into 1 group representing the participants for all the analyses that follow given that (1) the mixed model (including the 3 types of program participation categories) suggested that the rate of change in BMI (ie, an increase) and the mean BMIs for those who persistently participated compared with those who transitioned in and out of the program did not statistically differ (results not shown) and (2) the Poisson regression models in Table 2 indicated that similar socioeconomic and demographic characteristics are associated with persistent and temporary participation. Results for the full sample indicated that low-income children who participated in the NSLP do not have statistically significantly higher mean BMIs at each grade level compared with low-income children who never participate (Table 3 and eTable 3). Furthermore, low-income children who participated in the program did not have statistically significant larger rates of change in BMI (ie, increases) compared with low-income children who did not participate in the NSLP.
Nonlinear mixed models conducted separately (according to sex) revealed differences between girls and boys. Results indicated that low-income girls who participated in the NSLP had larger rates of change in BMI compared with low-income nonparticipating girls (Table 3 and Figure 1). However, mean BMIs at each school grade did not statistically differ between participating and nonparticipating low-income girls. Mixed models also suggested that low-income boys who participate in the program do not statistically differ in either their rate of change in BMI or in their mean BMIs compared with low-income boys who do not participate in the program (Table 3 and Figure 2).
Trajectories of body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) among girls aged 5 to 13 years from low-income families, stratified by participation in the National School Lunch Program. Trajectories include covariates. Trajectories are plotted on the Centers for Disease Control and Prevention growth chart, for girls.34
Trajectories of body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) among boys aged 5 to 13 years from low-income families, stratified by participation in the National School Lunch Program. Trajectories include covariates. Trajectories are plotted on the Centers for Disease Control and Prevention growth chart, for boys.34
Focusing on low-income children, our study explored the patterns of participation in the NSLP and how participation influences the trajectories of BMI during childhood and investigated whether NSLP participation influences BMI trajectories differently between girls and boys. Given that the end goal of the NSLP is to improve the well-being of children from low-income families, a longitudinal examination focused solely on the target population of the NSLP facilitates a greater understanding of who among the target population the program is serving over time and how participation is influencing health. Contrary to the hypothesis, results suggest that similar socioeconomically disadvantaged characteristics are associated with persistently and temporarily participating in the NSLP. Thus, the longitudinal examination provides policy makers and social service providers with the knowledge base that families with comparable background characteristics are participating in the program, although their patterns of participation differ. There is still a limited understanding of why income-eligible families do not participate in the NSLP, and qualitative interviews with these families may clarify this.
Unlike the studies by Schanzenbach19 and Millimet et al,21 our study found no statistically significant association between participation and mean relative weight level. This is likely due to the fact that our study focused on a sample of children from low-income families, the target population of the NSLP, whereas the other studies focused on all school-aged children regardless of their income status. Our study does add new information on the extent to which relationships between NSLP participation and BMI trajectory are moderated by sex. The results indicate that low-income girls who participate in the NSLP display a faster rate of change in BMI over time compared with low-income girls who do not participate in the program. The results also indicate that the BMIs of low-income boys who participate in the program do not statistically differ from the BMIs of low-income boys who do not participate; this finding differs from the predicted hypothesis and previous food-assistance research.24
Although most low-income children enter kindergarten at a healthy weight, as they develop, the combination of biological and contextual factors may contribute to the differences between girls and boys in the rate at which weight is gained. Our study suggests that low-income children who participate in the NSLP display more characteristics of living in a socioeconomically disadvantaged environment compared with children who are income eligible but do not participate. Poor living conditions have also been associated with more fast-food restaurants in the area35,36 and with fewer opportunities for physical activity,37,38 both of which are correlates of obesity. Furthermore, living in a stressful environment has been associated with early puberty,39,40 with the onset of pubertal characteristics observed as early as age 8 years for girls.41 Although early puberty has not been observed in overweight boys, early breast development and menstruation have been observed in obese girls.4- 6 This is because as girls transition to puberty, they tend to lay down more adipose tissue (or body fat), whereas boys lay down more lean muscle. Thus, the poor living conditions experienced by the girls who participate in the NSLP may interact with biological changes, resulting in their rate of change in BMI differing from that of girls who do not participate in the program.
Overall, low-income children participating in the NSLP display similar socioeconomically disadvantaged characteristics, despite different patterns of participation. Participation in the NSLP appears to be associated with the rate at which low-income girls gain weight compared with low-income girls who do not participate in the program. Although our study includes a measure of physical activity and television viewing, the results should be interpreted carefully because the measures are based on recall methods that are subject to social desirability bias.42- 44 Although physical activity recall methods are feasible and an inexpensive approach compared with objective measures (eg, accelerometers), previous research has indicated that females tend to overreport their physical activity.42,43,45 Our study also lacks information on dietary intake and consumption patterns during the school lunch period and outside the school environment, precluding us from examining the mechanisms by which these differences exist. Thus, it is unclear whether low-income children who are participating in the NSLP are actually consuming their lunch and/or consuming à la carte items. Future studies focusing on participation in food-assistance programs and children’s BMIs should include detailed information on the built environment, along with dietary intake, consumption patterns, and physical activity of income-eligible girls and boys, using both dietary recall techniques and objective measures (such as physiological monitoring). Efforts to gain a better understanding of what children are consuming and how often children are consuming particular foods in relation to environmental stressors may provide important new best practices on creating healthier lunch options for all children.
Correspondence: Daphne C. Hernandez, PhD, MSEd, Department of Human Development Family Studies, The Pennsylvania State University, 110 S Henderson Bldg, University Park, PA 16802 (email@example.com).
Accepted for Publication: October 4, 2010.
Published Online: December 6, 2010. doi:10.1001/archpediatrics.2010.253
Author Contributions:Study concept and design: Hernandez and Francis. Acquisition of data: Hernandez and Doyle. Analysis and interpretation of data: Hernandez, Francis, and Doyle. Drafting of the manuscript: Hernandez. Critical revision of the manuscript for important intellectual content: Hernandez, Francis, and Doyle. Statistical analysis: Francis and Doyle. Obtained funding: Hernandez and Francis. Study supervision: Hernandez.
Financial Disclosure: None reported.
Funding/Support: Drs Hernandez and Francis received funding for this project from the US Department of Agriculture Research Innovation and Development Grants in Economics (RIDGE) program with the Department of Nutrition at the University of California–Davis. In addition, the project described was supported by award K12HD055882 from the Eunice Kennedy Shriver National Institute of Child and Human Development (Dr Hernandez).
Disclaimer: The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child and Human Development or the National Institutes of Health.
Hernandez DC, Francis LA, Doyle EA. National School Lunch Program Participation and Sex Differences in Body Mass Index Trajectories of Children From Low-Income Families. Arch Pediatr Adolesc Med. 2011;165(4):346–353. doi:10.1001/archpediatrics.2010.253