Claudia Leonardi1, Neal R Simonsen1, Qingzhao Yu1, Chi Park1, Richard A Scribner2. 1. School of Public Health, Louisiana Cancer Research Center, Louisiana State University, New Orleans, Louisiana. 2. School of Public Health, Louisiana Cancer Research Center, Louisiana State University, New Orleans, Louisiana. Electronic address: rscrib@lsuhsc.edu.
Abstract
INTRODUCTION: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
INTRODUCTION: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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.
Authors: Mona N Fouad; Gabriela R Oates; Isabel C Scarinci; Wendy Demark-Wahnefried; Bryant W Hamby; Lori B Bateman; John J Estrada; Marinelle Payton; Mario Sims; Lucio Miele; Edward E Partridge Journal: Am J Prev Med Date: 2017-01 Impact factor: 5.043
Authors: Elham Hatef; Zachary Predmore; Elyse C Lasser; Hadi Kharrazi; Karin Nelson; Idamay Curtis; Stephan Fihn; Jonathan P Weiner Journal: AIMS Public Health Date: 2019-07-03
Authors: Elham Hatef; Masoud Rouhizadeh; Claudia Nau; Fagen Xie; Christopher Rouillard; Mahmoud Abu-Nasser; Ariadna Padilla; Lindsay Joe Lyons; Hadi Kharrazi; Jonathan P Weiner; Douglas Roblin Journal: JAMIA Open Date: 2022-02-16
Authors: Anthony Barnett; Ester Cerin; Erika Martino; Luke D Knibbs; Jonathan E Shaw; David W Dunstan; Dianna J Magliano; David Donaire-Gonzalez Journal: Environ Health Date: 2022-09-03 Impact factor: 7.123