Street Connectivity and Obesity Risk: Evidence From Electronic Health Records.

Abstract

This study aimed to determine the feasibility of using electronic health record (EHR) data from a federally qualified health center (FQHC) to assess the association between street connectivity, a measure of walkability for the local environment, and BMI obtained from EHRs. The study included patients who visited Daughters of Charity clinics in 2012-2013. A total of 31,297 patients were eligible, of which 28,307 were geocoded. BMI and sociodemographic information were compiled into a de-identified database. The street connectivity measure was intersection density, calculated as the number of three-way or greater intersections per unit area. Multilevel analyses of BMI, measured on 17,946 patients who were aged ≥20 years, not pregnant, had complete sociodemographic information, and a BMI value that was not considered an outlier, were conducted using random intercept models. Overall, on average, patients were aged 44.1 years, had a BMI of 30.2, and were mainly non-Hispanic black (59.4%). An inverse association between BMI and intersection density was observed in multilevel models controlling for age, gender, race, and marital status. Tests for multiple interactions were conducted and a significant interaction between race and intersection density indicated the decrease in BMI was strongest for non-Hispanic whites (decreased by 2) compared with blacks or Hispanics (decreased by 0.6) (p=0.0121). EHRs were successfully used to assess the relationship between street connectivity and BMI in a multilevel framework. Increasing street connectivity levels measured as intersection density were inversely associated with directly measured BMI obtained from EHRs, demonstrating the feasibility of the approach.