Neighborhoods and obesity in later life

Objectives. We examined the influence of neighborhood environment on the weight status of adults 55 years and older.Methods. We conducted a 2-level logistic regression analysis of data from the 2002 wave of the Health and Retirement Study. We included 8 neighborhood scales: economic advantage, economic disadvantage, air pollution, crime and segregation, street connectivity, density, immigrant concentration, and residential stability.Results. When we controlled for individual- and family-level confounders, living in a neighborhood with a high level of economic advantage was associated with a lower likelihood of being obese for both men (odds ratio OR] = 0.86; 95% confidence interval CI] = 0.80, 0.94) and women (OR = 0.83; 95% CI = 0.77, 0.89). Men living in areas with a high concentration of immigrants and women living in areas of high residential stability were more likely to be obese. Women living in areas of high street connectivity were less likely to be overweight or obese.Conclusions. The mechanisms by which neighborhood environment and weight status are linked in later life differ by gender, with economic and social environment aspects being important for men and built environment aspects being salient for women.Over the past few decades the prevalence of obesity has been rising for men and women across all age groups, including the elderly.¹ For example, in 2001 to 2002 in the United States, about 1 in 3 adults 60 years or older was obese.² This trend raises concerns because excess weight is associated with a number of chronic health conditions, including diabetes, high blood pressure, asthma, and arthritis.³ Moreover, obesity can have very important implications for publicly financed health care.⁴ Recent research suggests that a number of demographic, socioeconomic, and family factors⁵ influence obesity, but the role of the neighborhood context has not been fully explored.Excess weight results from an energy imbalance in which caloric intake exceeds energy expenditures, the latter closely related to physical activity. The neighborhood environment may influence energy intake (through its influence on food availability⁶) and energy expenditure (by facilitating or impeding physical activity). For example, the presence of supermarkets in the neighborhood is associated with higher fruit and vegetable intake,⁷ whereas eating at fast-food restaurants is associated with a high-fat diet and higher body mass index (BMI; weight in kilograms divided by height in meters squared).⁸ In terms of physical activity, individuals living in neighborhoods with less crime,^9–13 higher land-use mix,¹⁴ higher street connectivity,^11,14,15 higher residential density,^11,14 a greater number of destinations,^9,16 better aesthetics,^9,10,17 and sidewalks^10,12,17,18 tend to walk more often.^19,20Only a handful of studies linking neighborhood features to late-life obesity have focused on older adults.^{11,13,16,21–23} National studies are particularly lacking for the elderly. Yet evidence from national studies of adults of all ages suggests plausible connections between obesity and neighborhood factors. Using the 1990 to 1994 waves of the National Health Interview Survey, for example, Boardman et al.²⁴ found that adults residing in neighborhoods with a high concentration of poverty and in neighborhoods with a high percentage of Blacks were more likely to be obese. In another study, Robert and Reither²⁵ found that higher community socioeconomic disadvantage was related to higher BMI among women but not among men. Because these studies had very limited characterizations of the neighborhoods, the mechanism through which poor neighborhoods result in obesity remains unclear. It could be, for instance, that poor neighborhoods tend to have fewer supermarkets^26–28 and more-limited access to places for physical activity.^29,30Using a large, nationally representative survey, we examined the relationship between the economic, built, and social environments and weight status among men and women 55 years and older. We included 8 previously validated neighborhood scales reflecting neighborhood safety and segregation, concentration of immigrants, air pollution, residential stability, connectivity, density or access, and high and low neighborhood socioeconomic status.³¹ We modeled both obesity and overweight status by using multilevel modeling techniques in which we controlled for detailed individual- and family-level confounders.