Spatio-temporal patterns of under-five mortality in Matlab HDSS in rural Bangladesh

Abstract

Background: Knowledge of spatial and temporal distributions of mortality and morbidity is important to prioritise areas for adjusting the public health system where people need services most. A Health and Demographic Surveillance System (HDSS) plays an important role where accurate national vital events are not available in identifying areas and periods with excess mortality risks. Methods: The HDSS in Matlab, a rural area of Bangladesh, provided data on yearly number of deaths and children aged below 5 years for each of 90 villages during 1998–2007, along with village location points, longitudes and latitudes. Kulldorff's space–time scan statistic was used to identify villages and periods that experienced high mortality risks in the HDSS area with a statistical significance of p<0.001. Logistic regression was conducted to examine if village-level education and economic status explained village-level mortality risks. Results: There were 3,434 deaths among children aged below 5 years in the HDSS area during 1998–2007 with an average yearly rate of 13 deaths per 1,000 under-five child-years. The mortality rate showed a declining trend with high concentration in 1998–2002, but not in 2003–2007. Two clusters of villages had significantly higher mortality risks in 1998–2002, but not later, and the mortality risks in the high-risk clusters reduced little, but remained significant after controlling for adult education and economic status at village level. Conclusions: Spatial clustering of childhood mortality observed during 1998–2002 had disappeared in subsequent years with a decline in mortality rates. Space–time scanning helps identify high-risk areas and periods to enhance public health actions.

Keywords

• clustering
• children
• mortality
• Matlab
• Bangladesh