Geospatial analysis of food environment demonstrates associations with gestational diabetes

Maike K. Kahr, Melissa A. Suter, Jerasimos Ballas, Susan M. Ramin, Manju Monga, Wesley Lee, Min Hu, Cindy D. Shope, Arina Chesnokova, Laura Krannich, Emily N. Griffin, Joan Mastrobattista, Gary A. Dildy, Stacy L. Strehlow, Ryan Ramphul, Winifred J. Hamilton, Kjersti M. Aagaard

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

Background Gestational diabetes mellitus (GDM) is one of most common complications of pregnancy, with incidence rates varying by maternal age, race/ethnicity, obesity, parity, and family history. Given its increasing prevalence in recent decades, covariant environmental and sociodemographic factors may be additional determinants of GDM occurrence. Objective We hypothesized that environmental risk factors, in particular measures of the food environment, may be a diabetes contributor. We employed geospatial modeling in a populous US county to characterize the association of the relative availability of fast food restaurants and supermarkets to GDM. Study Design Utilizing a perinatal database with >4900 encoded antenatal and outcome variables inclusive of ZIP code data, 8912 consecutive pregnancies were analyzed for correlations between GDM and food environment based on countywide food permit registration data. Linkage between pregnancies and food environment was achieved on the basis of validated 5-digit ZIP code data. The prevalence of supermarkets and fast food restaurants per 100,000 inhabitants for each ZIP code were gathered from publicly available food permit sources. To independently authenticate our findings with objective data, we measured hemoglobin A1c levels as a function of geospatial distribution of food environment in a matched subset (n = 80). Results Residence in neighborhoods with a high prevalence of fast food restaurants (fourth quartile) was significantly associated with an increased risk of developing GDM (relative to first quartile: adjusted odds ratio, 1.63; 95% confidence interval, 1.21-2.19). In multivariate analysis, this association held true after controlling for potential confounders (P =.002). Measurement of hemoglobin A1c levels in a matched subset were significantly increased in association with residence in a ZIP code with a higher fast food/supermarket ratio (n = 80, r = 0.251 P <.05). Conclusion As demonstrated by geospatial analysis, a relationship of food environment and risk for gestational diabetes was identified.

Original languageEnglish (US)
Pages (from-to)110.e1-110.e9
JournalAmerican journal of obstetrics and gynecology
Volume214
Issue number1
DOIs
StatePublished - Jan 1 2016
Externally publishedYes

Keywords

  • food environment
  • geospatial analysis
  • gestational diabetes
  • neighborhood
  • pregnancy outcome

ASJC Scopus subject areas

  • Obstetrics and Gynecology

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