George L Wehby1,2,3, Benjamin W Domingue4, Fred Ullrich1, Fredric D Wolinsky1,5. 1. Department of Health Management and Policy, University of Iowa, Iowa City. 2. Department of Economics, Department of Preventive & Community Dentistry, and Public Policy Center, University of Iowa, Iowa City. 3. National Bureau of Economic Research, Cambridge, Massachusetts. 4. Graduate School of Education, Stanford University, California. 5. Department of Internal Medicine, Department of Gerontological Nursing, University of Iowa, Iowa City.
Abstract
BACKGROUND: The relationship between obesity and health expenditures is not well understood. We examined the relationship between genetic predisposition to obesity measured by a polygenic risk score for body mass index (BMI) and Medicare expenditures. METHODS: Biennial interview data from the Health and Retirement Survey for a nationally representative sample of older adults enrolled in fee-for-service Medicare were obtained from 1991 through 2010 and linked to Medicare claims for the same period and to Genome-Wide Association Study (GWAS) data. The study included 6,628 Medicare beneficiaries who provided 68,627 complete person-year observations during the study period. Outcomes were total and service-specific Medicare expenditures and indicators for expenditures exceeding the 75th and 90th percentiles. The BMI polygenic risk score was derived from GWAS data. Regression models were used to examine how the BMI polygenic risk score was related to health expenditures adjusting for demographic factors and GWAS-derived ancestry. RESULTS: Greater genetic predisposition to obesity was associated with higher Medicare expenditures. Specifically, a 1 SD increase in the BMI polygenic risk score was associated with a $805 (p < .001) increase in annual Medicare expenditures per person in 2010 dollars (~15% increase), a $370 (p < .001) increase in inpatient expenses, and a $246 (p < .001) increase in outpatient services. A 1 SD increase in the polygenic risk score was also related to increased likelihood of expenditures exceeding the 75th percentile by 18% (95% CI: 10%-28%) and the 90th percentile by 27% (95% CI: 15%-40%). CONCLUSION: Greater genetic predisposition to obesity is associated with higher Medicare expenditures.
BACKGROUND: The relationship between obesity and health expenditures is not well understood. We examined the relationship between genetic predisposition to obesity measured by a polygenic risk score for body mass index (BMI) and Medicare expenditures. METHODS: Biennial interview data from the Health and Retirement Survey for a nationally representative sample of older adults enrolled in fee-for-service Medicare were obtained from 1991 through 2010 and linked to Medicare claims for the same period and to Genome-Wide Association Study (GWAS) data. The study included 6,628 Medicare beneficiaries who provided 68,627 complete person-year observations during the study period. Outcomes were total and service-specific Medicare expenditures and indicators for expenditures exceeding the 75th and 90th percentiles. The BMI polygenic risk score was derived from GWAS data. Regression models were used to examine how the BMI polygenic risk score was related to health expenditures adjusting for demographic factors and GWAS-derived ancestry. RESULTS: Greater genetic predisposition to obesity was associated with higher Medicare expenditures. Specifically, a 1 SD increase in the BMI polygenic risk score was associated with a $805 (p < .001) increase in annual Medicare expenditures per person in 2010 dollars (~15% increase), a $370 (p < .001) increase in inpatient expenses, and a $246 (p < .001) increase in outpatient services. A 1 SD increase in the polygenic risk score was also related to increased likelihood of expenditures exceeding the 75th percentile by 18% (95% CI: 10%-28%) and the 90th percentile by 27% (95% CI: 15%-40%). CONCLUSION: Greater genetic predisposition to obesity is associated with higher Medicare expenditures.
Authors: Kirsty Bowman; João Delgado; William E Henley; Jane A Masoli; Katarina Kos; Carol Brayne; Praveen Thokala; Louise Lafortune; George A Kuchel; Alessandro Ble; David Melzer Journal: J Gerontol A Biol Sci Med Sci Date: 2016-08-04 Impact factor: 6.053