The Economic Burden of Obesity in Germany: Results from the Population-Based KORA Studies.

To estimate the excess costs of obese compared to normal-weight persons in Germany based on self-reported resource utilisation and work absence.Five cross sectional surveys of cohort studies in southern Germany were pooled resulting in 9,070 observations for 6,731 individuals (31-96 years). BMI was measured in the study centre. Self-reported health care utilisation and work absence was used to estimate direct and indirect costs for the year 2011 based on unit costs. Using regression analyses, adjusted costs for different BMI groups were calculated.Overweight and obese people showed significantly higher odds of health care utilisation and productivity losses compared with normal-weight people in most categories. Total direct/indirect costs were significantly higher with increasing severity of obesity (pre-obese (1.05 (0.90-1.23) / 1.38 (1.11-1.71)), obesity level I (1.18 (1.00-1.39) / 1.33 (1.02-1.73)), obesity level II (1.46 (1.14-1.87) / 1.77 (1.18-2.65)) or level III (2.04 (1.40-2.97) / 1.99 (1.20-3.30)) compared to normal-weight participants. In particular, higher obesity classes were significantly associated with increased costs for medication, general practitioner utilisation and work absence.Our results show that overweight and obesity are associated with enormous societal direct and indirect costs in Germany. This supports the evidence from previous top-down studies, but provides important new information based on a large pooled data set and measured BMI.     «

To estimate the excess costs of obese compared to normal-weight persons in Germany based on self-reported resource utilisation and work absence.Five cross sectional surveys of cohort studies in southern Germany were pooled resulting in 9,070 observations for 6,731 individuals (31-96 years). BMI was measured in the study centre. Self-reported health care utilisation and work absence was used to estimate direct and indirect costs for the year 2011 based on unit costs. Using regression analyses, ad...     »