The Effect of Socioeconomic and Environmental Factors on Obesity: A Spatial Regression Analysis

The Effect of Socioeconomic and Environmental Factors on Obesity: A Spatial Regression Analysis

Ortis Yankey (Kent State University, USA), Prince M. Amegbor (Aarhus University, Denmark) and Marcellinus Essah (University of Toronto, Canada)
Copyright: © 2021 |Pages: 17
DOI: 10.4018/IJAGR.2021100104
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Abstract

This paper examined the effect of socio-economic and environmental factors on obesity in Cleveland (Ohio) using an OLS model and three spatial regression models: spatial error model, spatial lag model, and a spatial error model with a spatially lagged response (SEMSLR). Comparative assessment of the models showed that the SEMSLR and the spatial error models were the best models. The spatial effect from the various spatial regression models was statistically significant, indicating an essential spatial interaction among neighboring geographic units and the need to account for spatial dependency in obesity research. The authors also found a statistically significant positive association between the percentage of families below poverty, Black population, and SNAP recipient with obesity rate. The percentage of college-educated had a statistically significant negative association with the obesity rate. The study shows that health outcomes such as obesity are not randomly distributed but are more clustered in deprived and marginalized neighborhoods.
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Introduction

Globally, obesity continues to generate debates in both public health and food discourses, especially in western countries where prevalence is on the rise. Indeed, the World Health Organization (WHO) in 2015 indicated that there is a global obesity epidemic taking place in Western countries (WHO, 2015). Understanding the pathway towards the development of obesity is complex, given the causes of obesity are multifaceted and multidimensional. Many social, environmental, and individual factors negatively contribute to the susceptibility of individuals to obesity (Schroeder et al. 2021, Gerlach et al. 2014, Dinsa et al. 2012, Joshua et al., 2008, McLaren, 2007). Nonetheless, these factors are not independent of each other. Instead, they are often intertwined in influence genetic predisposition, physical activity, and eating behaviours that contribute to the risk of obesity.

Some researchers argue that understanding and targeting effort to combat obesity has to do with understanding environmental factors that promote a high energy intake and sedentary behaviour in what they termed “obesogenic environment” (Swinburn et al. 1999; Swinburn et al. 2011; Ball et al. 2012; Ewing et al. 2014; Rey-López et al. 2014). Two distinct yet complementary factors (social factors and environmental factors) combine towards the development of obesity. Social factors pertain to the socio-economic disposition of individuals such as age, gender, education, income, and race; while environmental factors have to do with the natural and built environments and how they influence physical activity, food access, and consumption (Cutts et al. 2009; Jones, 2015; Pouliou and Elliott, 2010).

In the US, increasing consumption of fast-food rich in calories and a “car culture” environment provides little incentives for people to walk (Frank et al. 2004; Inagami et al. 2009; Lopez-Zetina et al. 2006; Swinburn et al. 2009). Lifestyle choices that encourage less physical activity, such as television watching (Brocklebank et al. 2015; Ewing et al., 2014; Pouliou & Elliott, 2010; Rey-López et al., 2008) has heightened the issue. Between 2015- 2016 the prevalence of obesity in the US was 39.8% in adults and 18.5% among the youth (Hales et al. 2017). Disaggregation of obesity prevalence rates shows a contrasting difference among various socio-economic groups (Frank et al., 2008; Jones, 2015; Wen & Maloney, 2011). The overall prevalence rate of obesity has been consistently higher among people of African American and Hispanic origin (Hales et al. 2017; Wen & Maloney, 2011). Hales et al. (2017) estimate that the obesity rate among Asian-Americans is 12.7%, 37.9% among Whites, 46.8% among Blacks, and 47.0% among Hispanics.

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