RESUMO
Diarrhoeal mortality rates in Mexican children dramatically declined during the 1980s and 1990s, concomitant with a temporal shift in peak deaths from summer to autumn-winter. The spatial dynamics of these patterns have not previously been studied. We first describe the seasonal features of paediatric diarrhoeal mortality in Mexico as a whole, then across individual states. While no geographical gradients in the magnitude of diarrhoeal mortality rates have been detected in recent years, we identified a distinct spatial pattern in the timing of peak mortality rate. In the 1980s the summer peak mortality was earliest around Mexico's capital and later in states to the southeast and northwest. Our results suggest that the direction and timing of those annual waves are related to the mean monthly precipitation and mean daily temperature. This pattern has disintegrated in recent years as the summer peak has diminished.
Assuntos
Clima , Diarreia/mortalidade , Criança , Pré-Escolar , Diarreia/epidemiologia , Análise de Fourier , Humanos , Lactente , Recém-Nascido , México/epidemiologia , Chuva , Estudos Retrospectivos , Estações do Ano , Estatísticas não Paramétricas , TemperaturaRESUMO
Public health data is often highly aggregated in time and space. The consequences of temporal aggregation for modeling in support of policy decisions have largely been overlooked. We examine the effects of changing temporal scale on spatial regression models of pediatric diarrhea mortality patterns, mortality rates and mortality peak timing, in Mexico. We compare annual and decadal level univariate models that incorporate known risk factors. Based on normalized sums of squared differences we compare between annual and decadal coefficients for variables that were significant in decadal models. We observed that spurious relationships might be created through aggregating time scales; obscuring interannual variation and resulting in inflated model diagnostics. In fact, variable selection and coefficient values can vary with changing temporal aggregation. Some variables that were significant at the decadal level were not significant at the annual level. Implications of such aggregation should be part of risk communication to policy makers.