Estimating Childhood Obesity Prevalence in Communities Through Multi-institutional Data Sharing. Issue 4 (July 2020)

• Record Type: Journal Article
• Authors: Daley, Matthew F.; Barrow, Jennifer C.; Tabano, David C.; Reifler, Liza M.; Kraus, Emily M.; Davies, Sara Deakyne; Williford, Devon L.; White, Benjamin; Shupe, Alyson; Davidson, Arthur J.
• Is Part Of: Journal of public health management and practice. Volume 26:Issue 4(2020)
• Publication Date: 2020-07
• Subjects: data sharing -- electronic health records -- obesity -- population health -- surveillance; Public health administration -- United States -- Periodicals; 253.6
• DOI: 10.1097/PHH.0000000000000942
• Languages: English
• ISSNs: 1078-4659

Abstract

Abstract : Context: Although local childhood obesity prevalence estimates would be valuable for planning and evaluating obesity prevention efforts in communities, these data are often unavailable. Objective: The primary objective was to create a multi-institutional system for sharing electronic health record (EHR) data to produce childhood obesity prevalence estimates at the census tract level. A secondary objective was to adjust obesity prevalence estimates to population demographic characteristics. Design/Setting/Participants: The study was set in Denver County, Colorado. Six regional health care organizations shared EHR-derived data from 2014 to 2016 with the state health department for children and adolescents 2 to 17 years of age. The most recent height and weight measured during routine care were used to calculate body mass index (BMI); obesity was defined as BMI of 95th percentile or more for age and sex. Census tract location was determined using residence address. Race/ethnicity was imputed when missing, and obesity prevalence estimates were adjusted by sex, age group, and race/ethnicity. Main Outcome Measure(s): Adjusted obesity prevalence estimates, overall, by demographic characteristics and by census tract. Results: BMI measurements were available for 89 264 children and adolescents in Denver County, representing 73.9% of the population estimate from census data. Race/ethnicity was missing for 4.6%. The county-level adjusted childhood obesity prevalence estimate was 13.9% (95% confidence interval, 13.6-14.1). Adjusted obesity prevalence was higher among males, those 12 to 17 years of age, and those of Hispanic race/ethnicity. Adjusted obesity prevalence varied by census tract (range, 0.4%-24.7%). Twelve census tracts had an adjusted obesity prevalence of 20% or more, with several contiguous census tracts with higher childhood obesity occurring in western areas of the city. Conclusions: It was feasible to use a system of multi-institutional sharing of EHR data to produce local childhood obesity prevalence estimates. Such a system may provide useful information for communities when implementing obesity prevention programs.