Effects of health intervention programs and arsenic exposure on child mortality from acute lower respiratory infections in rural Bangladesh

Abstract

BackgroundRespiratory infections continue to be a public health threat, particularly to young children in developing countries. Understanding the geographic patterns of diseases and the role of potential risk factors can help improve future mitigation efforts. Toward this goal, this paper applies a spatial scan statistic combined with a zero-inflated negative-binomial regression to re-examine the impacts of a community-based treatment program on the geographic patterns of acute lower respiratory infection (ALRI) mortality in an area of rural Bangladesh. Exposure to arsenic-contaminated drinking water is also a serious threat to the health of children in this area, and the variation in exposure to arsenic must be considered when evaluating the health interventions.MethodsALRI mortality data were obtained for children under 2 years old from 1989 to 1996 in the Matlab Health and Demographic Surveillance System. This study period covers the years immediately following the implementation of an ALRI control program. A zero-inflated negative binomial (ZINB) regression model was first used to simultaneously estimate mortality rates and the likelihood of no deaths in groups of related households while controlling for socioeconomic status, potential arsenic exposure, and access to care. Next a spatial scan statistic was used to assess the location and magnitude of clusters of ALRI mortality. The ZINB model was used to adjust the scan statistic for multiple social and environmental risk factors.ResultsThe results of the ZINB models and spatial scan statistic suggest that the ALRI control program was successful in reducing child mortality in the study area. Exposure to arsenic-contaminated drinking water was not associated with increased mortality. Higher socioeconomic status also significantly reduced mortality rates, even among households who were in the treatment program area.ConclusionCommunity-based ALRI interventions can be effective at reducing child mortality, though socioeconomic factors may continue to influence mortality patterns. The combination of spatial and non-spatial methods used in this paper has not been applied previously in the literature, and this study demonstrates the importance of such approaches for evaluating and improving public health intervention programs.

Cumulative Risk and Impact Modeling on Environmental Chemical and Social Stressors

“…We found that some complex regression-based modeling approaches have been used to evaluate the joint effects of multiple stressors. For example, the combined effects of exposure to arsenic contamination in drinking water and health intervention programs on child mortality from acute lower respiratory infections were modeled by a zero-inflated negative binomial regression [54]. Both simple regression and Bayesian sparse spatial multilevel models were utilized to evaluate the relationship between lead exposure and both gonorrhea and chlamydia, accounting for other non-chemical stressors such as index of concentrated disadvantage [57].…”

Cumulative Risk and Impacts Modeling on Environmental/Chemical and Social Stressors

“…We found that some complex regression-based modeling approaches have been used to evaluate the joint effects of multiple stressors. For example, the combined effects of exposure to arsenic contamination in drinking water and health intervention programs on child mortality from acute lower respiratory infections were modeled by a zero-inflated negative binomial regression [56]. Both simple regression and Bayesian sparse spatial multilevel models were utilized to evaluate the relationship between lead exposure and both gonorrhea and chlamydia, accounting for other non-chemical stressors such as index of concentrated disadvantage [53].…”

On Becoming a Mathematical Demographer—And the Career in Problem-Focused Inquiry that Followed

“…Migrant location methods developed by Kuhn and Barham that took advantage of near-universal cell phone availability were extraordinarily successful: More than 92% of those alive in each targeted age/sex group responded to our survey. This is not the place for a full list of publications, but I mention a few studies of determinants of elder's survival (Kuhn et al 2006, Rahman et al 2004, childbearing and women's survival (Menken et al 2003), arsenic exposure and health ( Jochem et al 2016), and long-term effects of exposure to famine (Kagy 2015). Early evaluations of the MCH/FP intervention show it was associated with higher cognitive functioning (Barham 2012), less outmigration (Barham & Kuhn 2014 title their paper "Staying for Benefits"), lower family size and increased consumption and child education (Foster & Milusheva 2015), and better labor market outcomes (Barham et al 2016).…”