Obesity among U.S. rural adults: Assessing selection and causation with prospective cohort data

Highlights

• Rural residents were more likely to have obesity than urban residents in a cross-sectional analysis.

• People with obesity were less likely to move to a new county than people without obesity.

• Moving to a rural county predicted a within-person increase in body weight.

Abstract

Rural adults in the U.S. have disproportionately high rates of obesity, but it is unclear whether this association exists because of selective migration or a contextual effect of the rural environment. Using nationally representative longitudinal data, this study investigates: (1) whether people with obesity select into rural counties, and (2) whether living in a rural area increases body weight after accounting for selection bias. Results indicate that people with obesity are less likely to move to a different county than people without obesity even after controlling for individual and household differences. Next, individual fixed effects regression models, which implicitly control for all time-constant variables, are used to produce a more robust estimate of the effect of rural residence on body weight. Rural residence predicts a significant increase in probability of obesity and body mass index. These results suggest that the association between rural residence and obesity in the United States is likely bidirectional.

Introduction

There is a disproportionate prevalence of obesity among U.S. rural adults (Hales et al., 2018; Lundeen et al., 2018). This trend increases the overall health burden in rural areas, which is exacerbated by relatively fewer resources and higher barriers to health care access compared to urban areas (Douthit et al., 2015). Identifying the reasons for this pattern is essential to crafting effective policy interventions. However, the factors that explain the relationship between rural residence and obesity are not well understood.

Compositional differences between rural and urban populations partially explain the link between rural residence and obesity. For example, rural residents are more likely to be older, less educated, and live in poverty (U.S. Department of Agriculture, 2017, 2018). These factors are also linked to excess body weight. However, several studies have shown that living in a rural area continues to predict obesity after accounting for a host of demographic characteristics, including age, sex, race, education, income, employment, marital status, household structure, nativity, and language (Befort et al., 2012; Bennett et al., 2011; Hales et al., 2018; Jackson et al., 2005; Patterson et al., 2004; Sobal et al., 1996; Voss et al., 2013; Wen et al., 2018). The authors of these studies implicitly assume that the residual association between rural residence and obesity that is not explained by these individual-level control variables represents an unbiased estimate of the effect of the rural context on body weight.

However, it is dubious to infer a causal relationship between rural residence and obesity from previous studies. The county people live in is not randomly assigned; adjusting for demographic covariates in a multiple regression equation does not make it so. Distinguishing between selection and contextual effects on health is difficult in observational studies, especially when the researcher is limited by cross-sectional data (Oakes, 2004).

Obese-selective migration could also explain disproportionate obesity prevalence in rural counties. Under the human capital view of migration, people move to seek greater economic returns to their labor. People with obesity tend to face greater discrimination in the work force (Morris, 2007; Tunceli et al., 2006). Reduced job opportunities may subsequently reduce an obese person's odds of migrating relative to a similarly qualified person without obesity. This would represent a passive selection process in which people with obesity do not choose to move to rural areas, but they remain there because they lack opportunities for better employment elsewhere. Combined with a net migration flow of people without obesity from rural to urban counties (Johnson and Lichter, 2019), this process would create a residual increase in obesity prevalence in rural areas over time even if no true contextual effect were operative.

People without obesity might also be actively selected into urban areas due to lifestyle preferences and local amenities. For example, rural counties are less likely to have accessible walking and biking paths, and a smaller proportion of commuters who use these physically-active modes of transportation (Hansen et al., 2015). A person who highly values these activities may choose to move to an area where the built environment better accommodates active commuting. This process may sort people without obesity into urban counties.

The relationship between rural residence and obesity could be bidirectional: people with obesity selecting into rural counties and the rural environment causing people's weight to increase (see Jokela et al., 2009). The current study used longitudinal data from a nationally representative cohort to improve on existing evidence in the United States. Longitudinal data make it possible to observe the temporal order of events—whether people with obesity are sorted into rural areas, or rural residents become obese. To investigate the possible bidirectional relationship between rural residence and obesity, this study aimed: (1) to demonstrate that individual socio-demographic characteristics do not entirely explain why rural residents have greater odds of obesity, (2) to test whether obesity predicts future inter-county migration, and (3) to test whether moving to a rural county predicts increased probability of obesity and increased BMI in an individual fixed effects analysis.