Mapping the cause-specific premature mortality reveals large between-districts disparity in Belgium, 2003–2009

Reducing premature mortality is a crucial public health objective. The goal of this paper, beside updating previous mortality atlases with recent data, is to explore the relative between-districts disparity using a relative-scale map design.

Causes of deaths and population data were provided by Statistics Belgium. All deaths occurring in the periods 1993–1999 and 2003–2009, in people aged 1–74 residing in Belgium were included. Age-adjusted rates by cause of death were computed for both periods; the 2003-2009 rates were classified using a relative scale with a 10% change between each level and represented on chloropleths maps with a green-to-red divergent colour scheme centred on the national mean. This particular design allows the comparability across all the maps since a same meaning is given to a specific colour. The variation coefficient and the decile ratio were calculated and compared between the 2 periods.

A clear-cut regional divide at the disadvantage of Wallonia, and to some extent, of Brussels, was seen for all-cause, cardiovascular, cerebrovascular, diabetes, alcohol-related, mental and neurological diseases and non-transport accidents premature mortality. A NE-SW pattern parallel to the French border was observed for Lip, Oral Cavity, Pharynx, Larynx and oesophageal cancers, while various patterns are observed for the other cancers. The highest rates of road accident mortality are observed in the Southern districts. Many of those patterns are in continuity with earlier observations. However, the pattern of diabetes and mental and neurological diseases are new features. The variation coefficient and the decile ratios increased by 10% between the 1993-1997 and 2003-2009 periods.

The use of a relative scale in the maps highlights the importance of the between-districts disparity in premature mortality, with for most causes, a clear-cut regional divide at the disadvantage of Wallonia; this health gap results of complex interactions between various factors, including the socioeconomic context, cultural habits and environmental influences, as well as public health policies. It should be considered as a warning signal, warranting the attention of the policy makers. Meanwhile, these results also highlight the potential for improvement in the more disadvantaged regions.