Author ORCID Identifier

Date of Award

Spring 5-5-2022

Degree Type

Capstone Project

Degree Name

Master of Public Health (MPH)


Public Health

First Advisor

Ruiyan Luo, Ph.D.

Second Advisor

Harry J Heiman, MD, MPH



INTRODUCTION: The prevalence of childhood overweight and obesity in the United States has increased dramatically in recent decades, contributing to poor health outcomes and larger societal impacts. Overweight in children is defined as having a BMI at the 85th to 95th percentiles, and obesity is defined as being at or above the 95th percentile. Children who are overweight or obese are significantly more likely to experience comorbidities like diabetes and hypertension, as well as profound psychosocial effects. The prevalence of overweight and obesity has been shown to differ based on certain factors like race, income, and nutrition. The purpose of this study is to explore the association between certain social and economic factors and childhood obesity and overweight. Analyzing this relationship could help to shape more effective and targeted interventions for at-risk children.

AIM: This study aims to assess:

• The prevalence of overweight/obesity among children based on social and economic status

• The odds of overweight/obesity among children based on specific predictors of youth overweight/obesity like race, income, fast-food exposure, and enrollment in free/reduced lunch programs

METHODS: This cross-sectional study will evaluate the associations between certain social (race, gender, age) and economic (income, lunch program enrollment, fast food exposure) factors and childhood obesity using the 2017-2020 NHANES datasets. Only those aged 4-19 years old with values for the following variables: age, race/ethnicity, BMI category, lunch price, fast food consumption, and family income were eligible for this study. 2,006 individuals met all the criteria and were included in the analysis.

ANALYSIS: Bivariate and multivariate logistic regression were conducted to determine the association between youth weight status and several risk factors. Multivariate logistic regression model includes race, family income to poverty ratio, gender, age, lunch price, fast-food consumption, the interaction between race and lunch price, and the interaction between race and fast-food consumption. Results are presented using both tables and figures. I considered p-values less than .05 as statistically significant.

RESULTS: The study sample consisted of 2,066 participants (822 overweight/obese children and 1,184 who were neither). The mean age of overweight/obese children was 11 (sd=3.6), the majority (81.2%) of whom were under the age of 15. The mean age of children who were not overweight/obese was 10.44 (sd=3.9), most (80.7%) of whom were under the age of 15. In studying the marginal association by logistic regression models, Mexican children had a significantly increased odds of overweight and obesity (OR=1.8) compared to White. Differences in odds for other races were not significant. There was no significant difference in odds of overweight/obesity between females vs males, or based on age to income. Lowest and middle income were associated with 25% and 39% increased odds of overweight/obesity compared to the highest income group, respectively. However, these associations were not statistically significant. Children in the free lunch price program and in the reduced program had 53% increased odds of overweight/obesity compared to the reference group, full price (OR = 1.53, OR=1.67, respectively) and this difference was significant. However, neither fast food association was statistically significant. The final multivariate model included the following predictors: age, sex, income, race, lunch status, fast-food exposure, race*lunch price, and race*fast-food exposure. Free and reduced lunch status was associated with a significant 68% and 140% increased odds of overweight or obesity for non-Hispanic white after controlling for all other predictors (OR=1.68, CI: 1.168-2.425; OR=2.4, CI: 1.199-4.823). No significant associations between weight and predictors race, age, sex, income, or fast food were found after controlling for other predictors. The two interaction variables were present in the final model (race*lunch price and race*fast-food exposure) reached significance, with both having a p-value of <.0001.

CONCLUSION: Overall, the findings of this study showed that low-income children are more likely to be overweight/obese, and certain neighborhood-level risk factors are also associated with overweight/obesity, though the associations were not significant. In the absence of a truly experimental study, which is unethical, it is difficult to make conclusions about causation, and when certain factors are highly associated with each other, even correlation can be muddled. Addressing risk factors disproportionately impacting families with lower socioeconomic status is crucial in the fight against childhood overweight and obesity. Current interventions mostly target individual behaviors, like increasing exercise for overweight children using step counters, or logging food to share with practitioners for weight loss. However, overweight and obesity in childhood are clearly contextual, associated with social and economic environments, and prevention is ideal, even as the intricacies are difficult to tease out. This study reinforces the need for childhood interventions aimed at obesity and overweight to target these contextual factors. Since the predictors of childhood overweight and obesity are tightly intertwined, and often not well understood, this capstone can help to inform further research into this field. This study proposes bigger programs targeting health disparities at the neighborhood level, not at the child or family level.


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