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Obesity Linked to Income?

by | Apr 12, 2018

Obesity has become a major issue around the world. It has been labeled as an epidemic and many efforts have been made to help reduce the number of people that are overweight/obese. Worldwide, the prevalence of obesity has increased 3 times from what it was in 1975. The World Health Organization (WHO) defines being overweight as having a body mass index of 25 or greater. It defines obesity as having a body mass index of 30 or greater. This outcome variable, body mass index (BMI), has been directly linked to living a healthy, longer life.

Much research has been done to find causal factors, going beyond exercise and diet, that are linked to obesity. In previous studies, one factor that has been found to be associated with obesity is household income. This predictor variable has been thought to be negatively correlated with BMI. Body mass index is likely to be higher among those with a lower household income. This is because families do not have enough money to buy healthy foods. Additionally, gender is a covariate that was tested in this study. Differences in gender could be related to differences in household income and BMI. Females are more likely to be single mothers supporting their children and are also paid lower wages than men. Furthermore, gender may be connected to differences in BMI because men and women are biologically different.

The hypothesis that was tested was whether or not family income is negatively associated with obesity when controlling for physical exercise. The data was taken from the National Health and Nutrition Examination Survey (NHANES) from 2013- 2015. It is a survey given to children and adults in the United States. Participants are recruited by mailed surveys and home visits. The data is then collected through home interviews and in Medical Exam Centers (MEC).

We analyzed the relationship between annual household income and body mass index in a large nationally representative sample of people in the United Stated. It was hypothesized that a lower household income would be associated with a higher BMI. These results were significant (p < 0.05, see figure 16) and the effect of the association was what was hypothesized. It was also predicted that gender may be a covariate that would confound the results. After controlling for gender, the effect of the predictor on the outcome variable was still significant and remained unchanged, determined by the p value and confidence interval (p < 0.05, see figure 17).

Overall, the study shows that there is a significant effect of annual household income on body mass index. This could be due to the lack of resources and money to put towards healthy foods and exercise tools to help individuals maintain a healthy weight. Even after controlling for gender, something that could affect both income and BMI, the effect was still significant.

References (5 points)

  1. “Obesity and Overweight.” World Health Organization, World Health Organization, Feb. 2018, www.who.int/mediacentre/factsheets/fs311/en/.
  2. Stenholm, S, et al. “Body Mass Index as a Predictor of Healthy and Disease-Free Life Expectancy between Ages 50 and 75: a Multicohort Study.” International Journal of Obesity (2005), Nature Publishing Group, May 2017, www.ncbi.nlm.nih.gov/pmc/articles/PMC5418561/.
  3. McLeod, G F, et al. “Childhood Predictors of Adult Adiposity: Findings from a Longitudinal Study.” The New Zealand Medical Journal., U.S. National Library of Medicine, 23 Mar. 2018, ncbi.nlm.nih.gov/pubmed/29565932.
  4. Silva, K, et al. “Stability in the Feeding Practices and Styles of Low-Income Mothers: Questionnaire and Observational Analyses.”The International Journal of Behavioral Nutrition and Physical Activity., U.S. National Library of Medicine, 23 Mar. 2018, ncbi.nlm.nih.gov/pubmed/29566714.
  5. “NHANES 2011-2012: Demographic Variables & Sample Weights Data Documentation, Codebook, and Frequencies.”Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, Jan. 2015, wwwn.cdc.gov/Nchs/Nhanes/2011-2012/DEMO_G.htm.
  6. “NHANES 2011-2012: Body Measures Data Documentation, Codebook, and Frequencies.”Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, Jan. 2015, wwwn.cdc.gov/Nchs/Nhanes/2011-2012/BMX_G.htm#BMXBMI.
  7. Schmeiser, Maximilian D. “Expanding Wallets and Waistlines: The Impact of Family Income on the BMI of Women and Men Eligible for the Earned Income Tax Credit.”Institute for Research on Poverty, July 2008, irp.wisc.edu/publications/dps/pdfs/dp133908.pdf.