Cardiovascular Diseases Mortality in Mexican Municipalities: A Spatio-Temporal Approach

Noncommunicable diseases (NCDs) accounted for approximately 74% of all deaths globally in 2022. Among the deaths from NCDs, the leading causes is cardiovascular disease (CVD), which represents approximately 32% of all global deaths. Furthermore, estimates indicate that over three-quarters of CVD deaths occur in low- and middle-income countries such as Mexico. Therefore, the goal of this study is to analyze the spatio-temporal patterns of mortality from cardiovascular diseases across Mexican municipalities from 2010 to 2019. We used a spatial Bayesian hierarchical regression model based on the Integrated Nested Laplace Approximation (INLA) and implemented in the R-INLA package to study the spatial pattern of mortality from cardiovascular diseases in Mexican municipalities. The modeling process revealed that the best model for both populations under and over 60 years old was the spatio-temporal model with space-time interaction. Overall, the purely spatial results suggest that the relative risks for both age groups (under and over 60 years old) do not have a consistent spatial pattern in 2019. On the other hand, the spatio-temporal results show that the interactions are stronger for the population over 60 years of age. This paper demonstrates the importance of assessing not only the spatial pattern of deaths, but also simultaneously incorporating temporal trends. With the understanding that this relationship (space-time) cannot be neglected, first the results of a purely spatial model are presented and, soon after, this model is expanded and the spatio-temporal results of mortality from cardiovascular diseases across Mexican municipalities from 2010 to 2019 are shown.