title: Health care costs attributable to overweight calculated in a standardized way for three European countries.
abstract: This article presents a tool to calculate health care costs attributable to overweight in a comparable and standardized way. The purpose is to describe the methodological principles of the tool and to put it into use by calculating and comparing the costs attributable to overweight for The Netherlands, Germany and Czech Republic. The tool uses a top-down and prevalence-based approach, consisting of five steps. Step one identifies overweight-related diseases and age- and gender-specific relative risks. Included diseases are ischemic heart disease, stroke, hypertension, type 2 diabetes mellitus, colorectal cancer, postmenopausal breast cancer, endometrial cancer, kidney cancer and osteoarthritis. Step two consists of collecting data on the age- and gender-specific prevalence of these diseases. Step three uses the population-attributable prevalence to determine the part of the prevalence of these diseases that is attributable to overweight. Step four calculates the health care costs associated with these diseases. Step five calculates the costs of these diseases that are attributable to overweight. Overweight is responsible for 20-26% of the direct costs of included diseases, with sensitivity analyses varying this percentage between 15-31%. Percentage of costs attributable to obesity and preobesity is about the same. Diseases with the highest percentage of costs due to overweight are diabetes, endometrial cancer and osteoarthritis. Disease costs attributable to overweight as a percentage of total health care expenditures range from 2 to 4%. Data are consistent for all three countries, resulting in roughly a quarter of costs of included diseases being attributable to overweight.
authors.affiliation: National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, P.O. Box 1, 3720, BA, Bilthoven, The Netherlands. manon.lette@rivm.nl.
authors.forename: M
authors.initials: M
authors.lastname: Lette
authors.affiliation: National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, P.O. Box 1, 3720, BA, Bilthoven, The Netherlands. wanda.bemelmans@rivm.nl.
authors.forename: W J E
authors.initials: WJ
authors.lastname: Bemelmans
authors.affiliation: WHO Regional Office for Europe, Nutrition, Physical Activity and Obesity, Marmorvej 51, 2100, Copenhagen, Denmark. jbr@euro.who.int.
authors.forename: J
authors.initials: J
authors.lastname: Breda
authors.affiliation: National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, P.O. Box 1, 3720, BA, Bilthoven, The Netherlands. lany.slobbe@rivm.nl.
authors.forename: L C J
authors.initials: LC
authors.lastname: Slobbe
authors.affiliation: Department of Clinical Sciences in Malmö, Lund University, Clinical Research Center 60:13:36, Jan Waldenströms Gata 35, 20502, Malmö, Sweden. joana.alves_dias@med.le.se.
authors.forename: J
authors.initials: J
authors.lastname: Dias
authors.affiliation: National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, P.O. Box 1, 3720, BA, Bilthoven, The Netherlands. hendriek.boshuizen@rivm.nl.
authors.forename: H C
authors.initials: HC
authors.lastname: Boshuizen
mesh_terms: D000367:Age Factors; D000368:Aged; D002318:Cardiovascular Diseases / Q000191:economics / Q000209:etiology; D017281:Cost of Illness; D003924:Diabetes Mellitus, Type 2 / Q000191:economics / Q000209:etiology; D005060:Europe / Q000453:epidemiology; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D009369:Neoplasms / Q000191:economics / Q000209:etiology; D009765:Obesity / Q000150:complications / Q000191:economics; D010003:Osteoarthritis / Q000191:economics / Q000209:etiology; D050177:Overweight / Q000150:complications* / Q000191:economics*; D012306:Risk; D012737:Sex Factors
keywords: Cost calculation; Health care costs; Macrolevel data; Overweight