Deepak Palakshappa1,2,3, Kristin Lenoir4, Callie L Brown2,3, Joseph A Skelton2,3, Jason P Block5, Elsie M Taveras6, Kristina H Lewis3. 1. Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 2. Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 3. Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 4. Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 5. Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts, USA. 6. Division of General Academic Pediatrics, Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts, USA.
Abstract
BACKGROUND: Identifying areas with higher sugar-sweetened beverage intake could help tailor policy and public health efforts intended to reduce sugary beverage consumption. OBJECTIVE: Demonstrate the feasibility of using health system data to examine the geographic distribution of sugar-sweetened beverage intake and evaluate neighbourhood characteristics associated with intake. METHODS: We extracted electronic health record data from a sugar-sweetened beverage and 100% fruit juice screener used for children ages 1 to 17 years in eight pediatric practices in North Carolina (March 2017-2018) and dichotomized intake to high (≥3 sugar-sweetened beverages/day) vs not. We geocoded address and mapped the proportion of consumers in each census tract. We combined electronic health record data with US census data and evaluated associations of census tract income and race/ethnicity with intake. We used multivariable models to evaluate the association between geographic concentrations of income and race/ethnicity and sugar-sweetened beverage intake, controlling for demographics extracted from the electronic health record and clustering by tract. RESULTS: Of 19 451 patients, 4579 (23.5%) reported consuming ≥3 sugar-sweetened beverages/day. In multivariable models, children living in tracts with high concentrations of low-income (OR: 1.45, 95% CI: 1.26, 1.68) and non-white residents (OR: 1.44, 95% CI: 1.21, 1.71) were more likely to consume ≥3 sugar-sweetened beverages/day than children in tracts with a high concentration of high-income and white residents. CONCLUSION: We demonstrate how health system data could be used to characterize geographic variation in sugar-sweetened beverage and 100% fruit juice consumption. This approach could help target public health efforts and monitor the effects of community-level interventions.
BACKGROUND: Identifying areas with higher sugar-sweetened beverage intake could help tailor policy and public health efforts intended to reduce sugary beverage consumption. OBJECTIVE: Demonstrate the feasibility of using health system data to examine the geographic distribution of sugar-sweetened beverage intake and evaluate neighbourhood characteristics associated with intake. METHODS: We extracted electronic health record data from a sugar-sweetened beverage and 100% fruit juice screener used for children ages 1 to 17 years in eight pediatric practices in North Carolina (March 2017-2018) and dichotomized intake to high (≥3 sugar-sweetened beverages/day) vs not. We geocoded address and mapped the proportion of consumers in each census tract. We combined electronic health record data with US census data and evaluated associations of census tract income and race/ethnicity with intake. We used multivariable models to evaluate the association between geographic concentrations of income and race/ethnicity and sugar-sweetened beverage intake, controlling for demographics extracted from the electronic health record and clustering by tract. RESULTS: Of 19 451 patients, 4579 (23.5%) reported consuming ≥3 sugar-sweetened beverages/day. In multivariable models, children living in tracts with high concentrations of low-income (OR: 1.45, 95% CI: 1.26, 1.68) and non-white residents (OR: 1.44, 95% CI: 1.21, 1.71) were more likely to consume ≥3 sugar-sweetened beverages/day than children in tracts with a high concentration of high-income and white residents. CONCLUSION: We demonstrate how health system data could be used to characterize geographic variation in sugar-sweetened beverage and 100% fruit juice consumption. This approach could help target public health efforts and monitor the effects of community-level interventions.