Mortality atlas of the main causes of death in Switzerland, 2008-2012
- PMID: 26901250
- DOI: 10.4414/smw.2016.14280
Mortality atlas of the main causes of death in Switzerland, 2008-2012
Abstract
Principles: Analysis of the spatial distribution of mortality data is important for identification of high-risk areas, which in turn might guide prevention, and modify behaviour and health resources allocation. This study aimed to update the Swiss mortality atlas by analysing recent data using Bayesian statistical methods. We present average pattern for the major causes of death in Switzerland.
Methods: We analysed Swiss mortality data from death certificates for the period 2008-2012. Bayesian conditional autoregressive models were employed to smooth the standardised mortality rates and assess average patterns. Additionally, we developed models for age- and gender-specific sub-groups that account for urbanisation and linguistic areas in order to assess their effects on the different sub-groups.
Results: We describe the spatial pattern of the major causes of death that occurred in Switzerland between 2008 and 2012, namely 4 cardiovascular diseases, 10 different kinds of cancer, 2 external causes of death, as well as chronic respiratory diseases, Alzheimer's disease, diabetes, influenza and pneumonia, and liver diseases. In-depth analysis of age- and gender-specific mortality rates revealed significant disparities between urbanisation and linguistic areas.
Conclusions: We provide a contemporary overview of the spatial distribution of the main causes of death in Switzerland. Our estimates and maps can help future research to deepen our understanding of the spatial variation of major causes of death in Switzerland, which in turn is crucial for targeting preventive measures, changing behaviours and a more cost-effective allocation of health resources.
Comment in
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Navigating the geography of mortality--towards a GPS for Public Health Policy.Swiss Med Wkly. 2016 Mar 21;146:w14308. doi: 10.4414/smw.2016.14308. eCollection 2016. Swiss Med Wkly. 2016. PMID: 26999775 No abstract available.
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