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. 2021 May 25;18(11):5664.
doi: 10.3390/ijerph18115664.

Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death

Miguel A Martinez-Beneito  1   2 , Carlos Vergara-Hernández  3 , Paloma Botella-Rocamora  4 , Francisca Corpas-Burgos  2   3 , Jordi Pérez-Panadés  4 , Óscar Zurriaga  2   3   4   5 , Elena Aldasoro  6 , Carme Borrell  2   7   8 , Elena Cabeza  9 , Lluís Cirera  2   10 , Josu Delfrade Osinaga  2   11 , Ana Fernández-Somoano  2   12   13 , Ana Gandarillas  14 , Pedro L Lorenzo Ruano  15 , Marc Marí-Dell'Olmo  2   7   8 , Andreu Nolasco  16 , M Dolores Prieto-Salceda  17 , Rebeca Ramis  2   18 , Maica Rodríguez-Sanz  2   7   8 , Pablo Sánchez-Villegas  19 , The Medea Project Group
Affiliations

Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death

Miguel A Martinez-Beneito et al. Int J Environ Res Public Health. .

Abstract

The geographical distribution of mortality has frequently been studied. Nevertheless, those studies often consider isolated causes of death. In this work, we aim to study the geographical distribution of mortality in urban areas, in particular, in 26 Spanish cities. We perform an overall study of 16 causes of death, considering that their geographical patterns could be dependent and estimating the dependence between the causes of death. We study the deaths in these 26 cities during the period 1996-2015 at the census tract level. A multivariate disease mapping model is used in order to solve the potential small area estimation problems that these data could show. We find that most of the geographical patterns found show positive correlations. This suggests the existence of a transversal geographical pattern, common to most causes of deaths, which determines those patterns to a higher/lower extent depending on each disease. The causes of death that exhibit that underlying pattern in a more prominent manner are chronic obstructive pulmonary disease (COPD), lung cancer, and cirrhosis for men and cardiovascular diseases and dementias for women. Such findings are quite consistent for most of the cities in the study. The high positive correlation found between geographical patterns reflects the existence of both high and low-risk areas in urban settings, in general terms for nearly all the causes of death. Moreover, the high-risk areas found often coincide with neighborhoods known for their high deprivation. Our results suggest that dependence among causes of death is a key aspect to be taken into account when mapping mortality, at least in urban contexts.

Keywords: geographical inequalities; mortality; multivariate disease mapping; urban areas.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Mean (log)-SMRs correlations between causes of death (upper triangle) and 95% interval for the observed correlation across cities (lower triangle) in men.
Figure 2
Figure 2
Mean (log-)SMRs correlations between causes of death (upper triangle) and 95% interval for the observed correlation across cities (lower triangle) in women.
Figure 3
Figure 3
Choropleth maps for COPD in men, stomach and prostate cancer mortality risk patterns in men for the cities of Madrid (left) and Barcelona (right).
See this image and copyright information in PMC

References

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