Neighborhood socioeconomic differences in BMI: The role of fast‐food outlets and physical activity facilities

Abstract

Objective: The goal of this study was to investigate the association between neighborhood socioeconomic status (NSES) and BMI and to what extent this association is moderated by availability of fast-food (FF) outlets and pay-for-use physical activity (PA) facilities.Methods: Baseline data of adults in Lifelines (N = 146,629) were linked to Statistics Netherlands and a register using geocoding to compute, respectively, NSES (i.e., low, middle, high) and the number of FF outlets and PA facilities within 1 km of the residential address. Multivariable multilevel linear regression analyses were performed to examine the association between NSES and BMI. Two-way and three-way interaction terms were tested to examine moderation by FF outlets and PA facilities. Results: Participants living in low NSES areas had a higher BMI than participants living in high (B [95% CI]: 0.76 [0.65 to 0.87]) or middle NSES areas (B [95% CI]: 0.40 [0.28 to 0.51]), independent of individual socioeconomic status. Although two-and three-way interactions between NSES, FF outlets, and PA facilities were significant, stratified analyses did not show consistent moderation patterns.Conclusions: People living in lower NSES areas had a higher BMI, independent of their individual socioeconomic status. The study found no clear moderation of FF outlets and PA facilities. Environmental factors that may mitigate NSES differences in BMI should be the subject of future research.

Obesity and COVID-19 Pandemics: Epidemiology, Mechanisms, and Management

“…Diabetes, Metabolic Syndrome and Obesity 2023:16 4148 choose cheap and unhealthy foods, 26,27 leading to unhealthy dietary choices and lifestyles. The impact was particularly severe for both disproportionately affecting marginalized/disadvantaged populations.…”

“…Studies had found that people living in areas with low socioeconomic indices had high rates of overweight or obesity, and that existing negative sociodemographic factors (unemployment, income insecurity, and education) seemed to have a cumulative effect. 25 They may face more economic pressures and restrictions and choose cheap and unhealthy foods, 26 , 27 leading to unhealthy dietary choices and lifestyles. The impact was particularly severe for both disproportionately affecting marginalized/disadvantaged populations.…”