The geographic distribution of obesity by census tract among 59 767 insured adults in King County, WA

Int J Obes (Lond). 2014 Jun;38(6):833-9. doi: 10.1038/ijo.2013.179. Epub 2013 Sep 16.

Abstract

Objective: To evaluate the geographic concentration of adult obesity prevalence by census tract (CT) in King County, WA, in relation to social and economic factors.

Methods and design: Measured heights and weights from 59 767 adult men and women enrolled in the Group Health (GH) healthcare system were used to estimate obesity prevalence at the CT level. CT-level measures of socioeconomic status (SES) were median home values of owner-occupied housing units, percent of residents with a college degree and median household incomes, all drawn from the 2000 Census. Spatial regression models were used to assess the relation between CT-level obesity prevalence and socioeconomic variables.

Results: Smoothed CT obesity prevalence, obtained using an Empirical Bayes tool, ranged from 16.2-43.7% (a 2.7-fold difference). The spatial pattern of obesity was non-random, showing a concentration in south and southeast King County. In spatial regression models, CT-level home values and college education were more strongly associated with obesity than household incomes. For each additional $100 000 in median home values, CT obesity prevalence was 2.3% lower. The three SES factors together explained 70% of the variance in CT obesity prevalence after accounting for population density, race/ethnicity, age and spatial dependence.

Conclusions: To our knowledge, this is the first report to show major social disparities in adult obesity prevalence at the CT scale that is based, moreover, on measured heights and weights. Analyses of data at sufficiently fine geographic scale are needed to guide targeted local interventions to stem the obesity epidemic.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Bayes Theorem
  • Body Mass Index
  • Censuses
  • Environment
  • Female
  • Geography
  • Health Behavior*
  • Health Status Disparities*
  • Humans
  • Income
  • Insurance, Health / statistics & numerical data*
  • Male
  • Obesity / epidemiology*
  • Prevalence
  • Socioeconomic Factors
  • United States / epidemiology
  • Washington / epidemiology