Demographic Research (Aug 2012)

The contribution of smoking to regional mortality differences in the Netherlands

  • Fanny Janssen,
  • Alette Spriensma

Journal volume & issue
Vol. 27
p. 9

Abstract

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BACKGROUND Smoking is an important preventable determinant of morbidity and mortality. Knowledge about its role in regional mortality differences can help us to identify relevant policy areas, and to explain national mortality differences. OBJECTIVE We explored the extent to which the regional differences in all-cause mortality in the Netherlands could be due to smoking, by examining its link with regional differences in smoking-attributable mortality. METHODS All-cause mortality, lung cancer mortality, and population numbers were obtained from Statistics Netherlands for the period 2004-2008, by 40 NUTS-3 regions, age, and sex. Smoking-attributable mortality was estimated using an adapted indirect Peto-Lopez method. We mapped regional differences in age-standardised all-cause mortality, smoking-attributable mortality fractions, and smoking- and non-smoking-related mortality rates. We assessed spatial clustering, calculated correlations, and compared and decomposed regional variance. RESULTS Significant regional differences in all-cause mortality, exhibiting a random pattern, were found. Smoking-attributable mortality fractions, which ranged from 22Š to 30Š among males and 7Š to 14Š among females, correlated significantly with all-cause mortality, especially among males. Smoking-attributable mortality varied far more than all-cause mortality, while non-smoking-attributable mortality varied less than all-cause mortality. The variance in smoking-attributable mortality contributed 39Š to the regional variance in all-cause mortality among males, and 30Š among females. CONCLUSIONS Smoking-attributable mortality thus clearly contributed to the regional differences in all-cause mortality, especially among males. This finding can be linked to past regional differences in smoking behaviour and underlying regional differences in socio-economic variables.