Modeling potential health gains of prevention measures in the elderly population of North Rhine-Westphalia

M Mensing, OCL Mekel, C Terschuren NRW Centre for Health, Bielefeld, Germany Contact: odile.mekel@lzg.gc.nrw.de Background Health Impact Assessment aims at estimating potential health effects in populations, due to plans, proposals, projects or policies. The software DYNAMO-HIA (www.dynamo-hia.eu), developed within the framework of an EC-funded research project, allows prospective mathematical modeling of healthrelated outcomes by considering alternative scenarios of risk and exposure distributions. Methods DYNAMO-HIA is gradually being transferred for the use in North Rhine-Westphalia (NRW). For body mass index (BMI), we evaluated the quality of different data sources and opted for the KIGGS (German Health Interview and Examination Survey for Children and Adolescents) and GEDA NRW (telephone health survey for adults), both conducted by the Robert KochInstitute, Berlin. Linear interpolation and proportional calculation generated BMI data for every age year 0-95. Simulated changes between risk factor levels (normal weight, overweight, obesity) over the life course are defined by varying transition rates. BMI related health outcomes of particular interest are: ischaemic heart diseases, diabetes, selected cancers, overall mortality and life expectancy. Results Based on national and international epidemiological studies addressing the exposure-response functions (ERF) for BMI and specific health outcomes, it is possible to estimate health outcomes for the NRW population taking different risk exposure rates in defined scenarios into account. Results from the EPIC study (European Prospective Investigation into Cancer and Nutrition) are used to estimate selected cancers in the elderly population in NRW. Sensitivity analyses are performed, testing for model robustness. We present the effects of sustainable BMI reduction on the outcomes of interest, like disease prevalence, mortality and years of life lost. Conclusions Modeling health outcomes using DYNAMO-HIA requires data of high quality as well as implementation of complex epidemiological interrelations. The modeled estimations depend on the specifications integrated in the model. DYNAMO-HIA presents a manageable software tool supporting the estimation of health effects of different intervention measures on the population in North Rhine-Westphalia. Key messages The software DYNAMO-HIA models health impacts in populations due to intervention policies and allows comparative analysis of reference vs. intervention scenarios. By adapting the data input, potential health effects on disease prevalence and mortality can be assessed for the population in North Rhine-Westphalia.