An index of geospatial disadvantage predicts both obesity and unmeasured body weight

Abstract

Neighborhood context impacts health. Using an index of geospatial disadvantage measures to predict neighborhood socioeconomic disparities would support area-based allocation of preventative resources, as well as the use of location as a clinical risk factor in care of individual patients. This study tested the association of the Area Deprivation Index (ADI), a neighborhood-based index of socioeconomic contextual disadvantage, with elderly obesity risk. We sampled 5066 Medicare beneficiaries at the University of Missouri between September 1, 2013 and September 1, 2014. We excluded patients with unknown street addresses, excluded body mass index (BMI) lower than 18 or higher than 62 as probable errors, and excluded patients with missing BMI data. We used a plot of simple proportions to examine the association between ADI and prevalence of obesity, defined as BMI of 30 and over. We found that obesity was significantly less prevalent in the least-disadvantaged ADI decile (decile 1) than in all other deciles (p < 0.05) except decile 7. Obesity prevalence within the other deciles (2–6 and 8–10) was not significantly distinguishable except that decile 2 was significantly lower than decile 4. Patients with missing BMI data were more likely to reside in the most disadvantaged areas. There was a positive association between neighborhood disadvantage and obesity in this Midwestern United States Medicare population. The association of missing BMI information with neighborhood disadvantage may reflect unmeasured gaps in care delivery to the most disadvantaged patients. These preliminary results support the continued study of neighborhood socioeconomic measures to identify health disparities in populations.

Keywords

• Risk prediction
• Obesity risk
• Elderly
• Social determinants
• Geospatial analysis
• Data quality