Mona Sharifi1, Thomas D Sequist2, Sheryl L Rifas-Shiman3, Steven J Melly4, Dustin T Duncan5, Christine M Horan6, Renata L Smith3, Richard Marshall7, Elsie M Taveras8. 1. Division of General Academic Pediatrics, Department of Pediatrics, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, United States. Electronic address: mona.sharifi@yale.edu. 2. Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States; Department of Health Care Policy, Harvard Medical School, Boston, MA, United States; Partners HealthCare System, Inc., Boston, MA, United States. 3. Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States. 4. Department of Environmental Health, Harvard School of Public Health, Boston, MA, United States. 5. Department of Population Health, New York University School of Medicine, New York, NY, United States. 6. Division of General Academic Pediatrics, Department of Pediatrics, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, United States. 7. Harvard Vanguard Medical Associates, Boston, MA, United States. 8. Division of General Academic Pediatrics, Department of Pediatrics, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, United States; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Abstract
BACKGROUND: Childhood obesity prevalence remains high and racial/ethnic disparities may be widening. Studies have examined the role of health behavioral differences. Less is known regarding neighborhood and built environment mediators of disparities. The objective of this study was to examine the extent to which racial/ethnic disparities in elevated child body mass index (BMI) are explained by neighborhood socioeconomic status (SES) and built environment. METHODS: We collected and analyzed race/ethnicity, BMI, and geocoded address from electronic health records of 44,810 children 4 to 18years-old seen at 14 Massachusetts pediatric practices in 2011-2012. Main outcomes were BMI z-score and BMI z-score change over time. We used multivariable linear regression to examine associations between race/ethnicity and BMI z-score outcomes, sequentially adjusting for neighborhood SES and the food and physical activity environment. RESULTS: Among 44,810 children, 13.3% were black, 5.7% Hispanic, and 65.2% white. Compared to white children, BMI z-scores were higher among black (0.43units [95% CI: 0.40-0.45]) and Hispanic (0.38 [0.34-0.42]) children; black (0.06 [0.04-0.08]), but not Hispanic, children also had greater increases in BMI z-score over time. Adjusting for neighborhood SES substantially attenuated BMI z-score differences among black (0.30 [0.27-0.34]) and Hispanic children (0.28 [0.23-0.32]), while adjustment for food and physical activity environments attenuated the differences but to a lesser extent than neighborhood SES. CONCLUSIONS: Neighborhood SES and the built environment may be important drivers of childhood obesity disparities. To accelerate progress in reducing obesity disparities, interventions must be tailored to the neighborhood contexts in which families live.
BACKGROUND:Childhood obesity prevalence remains high and racial/ethnic disparities may be widening. Studies have examined the role of health behavioral differences. Less is known regarding neighborhood and built environment mediators of disparities. The objective of this study was to examine the extent to which racial/ethnic disparities in elevated child body mass index (BMI) are explained by neighborhood socioeconomic status (SES) and built environment. METHODS: We collected and analyzed race/ethnicity, BMI, and geocoded address from electronic health records of 44,810 children 4 to 18years-old seen at 14 Massachusetts pediatric practices in 2011-2012. Main outcomes were BMI z-score and BMI z-score change over time. We used multivariable linear regression to examine associations between race/ethnicity and BMI z-score outcomes, sequentially adjusting for neighborhood SES and the food and physical activity environment. RESULTS: Among 44,810 children, 13.3% were black, 5.7% Hispanic, and 65.2% white. Compared to white children, BMI z-scores were higher among black (0.43units [95% CI: 0.40-0.45]) and Hispanic (0.38 [0.34-0.42]) children; black (0.06 [0.04-0.08]), but not Hispanic, children also had greater increases in BMI z-score over time. Adjusting for neighborhood SES substantially attenuated BMI z-score differences among black (0.30 [0.27-0.34]) and Hispanic children (0.28 [0.23-0.32]), while adjustment for food and physical activity environments attenuated the differences but to a lesser extent than neighborhood SES. CONCLUSIONS: Neighborhood SES and the built environment may be important drivers of childhood obesity disparities. To accelerate progress in reducing obesity disparities, interventions must be tailored to the neighborhood contexts in which families live.
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