Impact of waist circumference difference on health-care cost among overweight and obese subjects: the PROCEED cohort.

OBJECTIVE To estimate the incremental effect of waist circumference (WC) on health-care costs among overweight and obese subjects after adjusting for body mass index (BMI). METHODS A prospective study. The subjects were members of Internet panels in the United States (US) and Germany. 10,816 individuals (United States: n = 5410; Germany: n = 5406) aged 30-70 years with BMI scores between 20 and 35 kg/m(2) were recruited and grouped by category: healthy weight (BMI 20-24.9 kg/m(2)), overweight (BMI 25-29.9 kg/m(2)), and obese (BMI 30-35 kg/m(2)). Within the overweight and obese categories, the individuals were stratified by sex and within those subgroups, characterized as above or below the median WC. The subjects self-reported weight, WC, and health-care resource use at baseline, 3 months, and 6 months using online questionnaires. Over 65% of the recruited subjects completed all surveys. Resource utilization was translated into health-care costs by multiplying unit costs from national sources in each country. Annualized health costs were summarized for subjects with low and high WC within the overweight and obese categories. A two-part model generated predicted annual costs because of the WC difference controlling for BMI, demographic, and lifestyle variables among the overweight and obese subjects. RESULTS When BMI and other characteristics are constant, annual health-care costs are 16% to 18% higher in Germany and 20% to 30% higher in the United States for the subjects with a high WC compared with subjects with a low WC. CONCLUSIONS Targeting people with a high waist circumference for weight management whether they are overweight or obese may maximize cost-efficacy.

[1]  D. Abbey,et al.  Medicare Physician Fee Schedule. , 2023, JAMA.

[2]  E. Finkelstein,et al.  Annual medical spending attributable to obesity: payer-and service-specific estimates. , 2009, Health affairs.

[3]  N. Wong,et al.  Abdominal obesity and the spectrum of global cardiometabolic risks in US adults , 2009, International Journal of Obesity.

[4]  L. Aronne,et al.  PROCEED: Prospective Obesity Cohort of Economic Evaluation and Determinants: baseline health and healthcare utilization of the US sample * , 2008, Diabetes, obesity & metabolism.

[5]  T. Sørensen,et al.  Waist Circumference and Body Mass Index as Predictors of Health Care Costs , 2008, PloS one.

[6]  T. Sørensen,et al.  Economic Costs of Abdominal Obesity , 2008, Obesity Facts.

[7]  C. Block,et al.  Mechanisms linking obesity with cardiovascular disease , 2006, Nature.

[8]  J. Nonnemaker,et al.  Erratum: The ATTEMPT cohort: A multi-national longitudinal study of predictors, patterns and consequences of smoking cessation; introduction and evaluation of internet recruitment and data collection methods (Addiction (2006) 101, (1352-1361)) , 2006 .

[9]  J. Nonnemaker,et al.  The ATTEMPT cohort: a multi-national longitudinal study of predictors, patterns and consequences of smoking cessation; introduction and evaluation of internet recruitment and data collection methods. , 2006, Addiction.

[10]  T. Lengerke,et al.  Direkte medizinische Kosten der (starken) Adipositas: ein Bottom-up-Vergleich über- vs. normalgewichtiger Erwachsener in der KORA-Studienregion , 2006 .

[11]  M. Feinleib National Center for Health Statistics (NCHS) , 2005 .

[12]  Walter C Willett,et al.  Comparison of abdominal adiposity and overall obesity in predicting risk of type 2 diabetes among men. , 2005, The American journal of clinical nutrition.

[13]  Melinda Beeuwkes Buntin,et al.  Too much ado about two-part models and transformation? Comparing methods of modeling Medicare expenditures. , 2004, Journal of health economics.

[14]  S. Teutsch,et al.  NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. , 2003, Diabetes.

[15]  G. Grunwald,et al.  Relationship between waist circumference, body mass index, and medical care costs. , 2002, Obesity research.

[16]  S. Heymsfield,et al.  Waist circumference and obesity-associated risk factors among whites in the third National Health and Nutrition Examination Survey: clinical action thresholds. , 2002, The American journal of clinical nutrition.

[17]  L. Groop,et al.  Cardiovascular morbidity and mortality associated with the metabolic syndrome. , 2001, Diabetes care.

[18]  A. Bauman,et al.  The relationship between body mass index and waist circumference: implications for estimates of the population prevalence of overweight , 2000, International Journal of Obesity.

[19]  T. Sellers,et al.  Associations of general and abdominal obesity with multiple health outcomes in older women: the Iowa Women's Health Study. , 2000, Archives of internal medicine.

[20]  G A Colditz,et al.  Abdominal adiposity and coronary heart disease in women. , 1998, JAMA.

[21]  W. Thefeld,et al.  [The German Health Survey. 1997/98]. , 1998, Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)).

[22]  G. Oster,et al.  Estimated Economic Costs of Obesity to U.S. Business , 1998, American journal of health promotion : AJHP.

[23]  A. Wolf,et al.  What is the economic case for treating obesity? , 1998, Obesity research.

[24]  J. Mullahy Much Ado About Two: Reconsidering Retransformation and the Two-Part Model in Health Economics , 1998, Journal of health economics.

[25]  L. Tucker,et al.  Obesity and Absenteeism: An Epidemiologic Study of 10,825 Employed Adults , 1998, American journal of health promotion : AJHP.

[26]  K. Fontaine,et al.  Health-related quality of life in obese persons seeking treatment. , 1996, The Journal of family practice.

[27]  N. Hearst,et al.  Costs of visits to emergency departments. , 1996, The New England journal of medicine.

[28]  C. Swanson,et al.  Body weight: estimation of risk for breast and endometrial cancers. , 1996, The American journal of clinical nutrition.

[29]  J. Manson,et al.  Weight, weight change, and coronary heart disease in women. Risk within the 'normal' weight range. , 1995, JAMA.

[30]  G A Colditz,et al.  Weight as a risk factor for clinical diabetes in women. , 1990, American journal of epidemiology.

[31]  E. Rimm,et al.  A Prospective Study of Nutritional Factors and Hypertension Among US Men , 1989, Circulation.

[32]  B. Efron,et al.  The Jackknife: The Bootstrap and Other Resampling Plans. , 1983 .

[33]  N. Unwin,et al.  Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Detection, Evaluation, and Treatment of High Blood Cholesterol Education Program (NCEP) Expert Panel on Executive Summary of the Third Report of the National , 2009 .

[34]  G. Nahler direct medical costs , 2009 .

[35]  H. Hauner,et al.  Association of waist circumference, cardiometabolic risk factors and health care utilization in a German internet-based cohort study , 2008 .

[36]  W A Rowe,et al.  Limits of body mass index to detect obesity and predict body composition. , 2001, Nutrition.

[37]  M. Laakso,et al.  Hyperinsulinemia cluster predicts the development of type 2 diabetes independently of family history of diabetes. , 1999, Diabetes care.

[38]  Bellach Bm,et al.  Der Bundes-Gesundheitssurvey 1997/98 , 1998 .

[39]  K Clark,et al.  The effect of age on the association between body-mass index and mortality. , 1998, Journal of insurance medicine.

[40]  I. Sartori Weight, Weight Change, and Coronary Heart Disease in Women: Risk Within the 'Normal' Weight Range , 1996 .

[41]  B. Efron The jackknife, the bootstrap, and other resampling plans , 1987 .