How Income Inequality and Race/Ethnicity Drive Obesity in U.S. Adults: 1999–2016

Abstract

Obesity is a major public health problem both globally and within the U.S. It varies by multiple factors, including but not limited to income and sex. After controlling for potential covariates, there is little evidence to determine the association between income and obesity and how obesity may be moderated by sex and family income. We examined the association between income and obesity in U.S. adults aged 20 years and older, and tested whether this relationship differs by race or ethnicity groups. For this analysis, we used data from the 1999–2016 National Health and Nutrition Examination Surveys (NHANES). Obesity was determined using Body Mass Index ≥ 30 kg/m2; the Gini coefficient (GC) was calculated to measure income inequality using the Poverty Income Ratio (PIR). We categorized the PIR into five quintiles to examine the relationship between income inequality and obesity. For the first set of analyses, we used a modified Poisson regression in a sample of 36,665 adults, with an almost equal number of men and women (women’s ratio was 50.6%), including 17,303 white non-Hispanics (WNH), 7475 black non-Hispanics (BNHs), and 6281 Mexican Americans. The models included age, racial/ethnic groups, marital status, education, health behaviors (smoking and drinking status and physical activities), health insurance coverage, self-reported health, and household structure (live alone and size of household). Adjusting for potential confounders, our findings showed that the association between PIR and obesity was positive and significant more frequently among WNH and BNH in middle and top PIR quintiles than among lower-PIR quintiles; this association was not significant in Mexican Americans (MAs). Results of GC in obese women showed that in comparison with WNHs (GC: 0.34, S.E.: 0.002), BNHs (GC: 0.38, S.E.: 0.004) and MAs (GC: 0.41, S.E.: 0.006) experienced higher income inequality, and that BNH obese men experienced the highest income inequality (GC: 0.45, S.E.: 0.011). The association between PIR and obesity was significant among WNHs and BNHs men in the 3rd, 4th and 5th PIR quintiles. The same association was not found for women. In treating obesity, policymakers should consider not only race/ethnicity and sex, but also strategies to reduce inequality in income.

Income Disparities in Obesity Trends among U.S. Adults: An Analysis of the 2011–2014 California Health Interview Survey

“…Using the same data set, Zare et al investigated whether the relationship between obesity and income differed by sex and race. They found that the poverty income ratio and obesity were significant and positive more often among white non-Hispanics and black non-Hispanics with middle and high income than those in the lower income category; this association was not found among Mexican Americans [ 20 ]. When considering obese women, compared to white women, Mexican American and black women faced higher income inequality [ 20 ].…”

“…They found that the poverty income ratio and obesity were significant and positive more often among white non-Hispanics and black non-Hispanics with middle and high income than those in the lower income category; this association was not found among Mexican Americans [ 20 ]. When considering obese women, compared to white women, Mexican American and black women faced higher income inequality [ 20 ]. In looking at men, black non-Hispanic males were found to have the highest income inequality [ 20 ].…”

“…When considering obese women, compared to white women, Mexican American and black women faced higher income inequality [ 20 ]. In looking at men, black non-Hispanic males were found to have the highest income inequality [ 20 ]. So, besides looking at addressing the systematic failures of income distribution, it is also imperative to take note of sex, race/ethnicity, and economically homogeneous/heterogeneous locations.…”

Associations between socioeconomic status and stroke in American adults: A population-based study

“…Multiple studies have shown that populations in low- and middle-income countries have a higher risk of stroke ( Saini et al, 2021 , Akinyemi et al, 2021 , Krishnamurthi et al, 2020 , Marshall et al, 2015 ). Furthermore, in addition to income disparities, racial differences also play a role in influencing disease incidence ( Zare et al, 2021 ). Some studies have shown that the risk of stroke varies by race ( Howard et al, 2019 , Finnegan et al, 2022 ).…”

“…Socioeconomic status (SES) measures a person's or family's economic and social status relative to other people or families in society. Some studies have shown that SES is associated with non-communicable diseases such as ischemic heart disease, heart failure, diabetes and obesity ( Zare et al, 2021 , Mustapha et al, 2022 , Hawkins Carranza et al, 2022 , Zare et al, 2021 ). Generally speaking, SES from higher socioeconomic status may provide direct or indirect defense against these diseases.…”