The effect of socioeconomic and environmental factors on obesity: A spatial regression analysis

Ortis Yankey, Prince M. Amegbor, Marcellinus Essah

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)58-74
Number of pages17
JournalInternational Journal of Applied Geospatial Research
Issue number4
StatePublished - Oct 1 2021


  • Cleveland
  • Obesity
  • Spatial Analysis
  • Spatial Dependency
  • Spatial Error Model
  • Spatial Lag Model

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth and Planetary Sciences (miscellaneous)


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