Improving the precision of maternal, newborn, and child health impact through geospatial analysis of the association of contextual and programmatic factors with health trends in Bihar, India.

Abstract

There is a scarcity of research that comprehensively examines programme impact from a context-specific perspective. We aimed to determine the conditions under which the Bihar Technical Support Programme led to more favourable outcomes for maternal and child health in Bihar. We obtained block-level data on maternal and child health indicators during the state-wide scale-up of the pilot Ananya programme and data on health facility readiness, along with geographical and sociodemographic variables. We examined the associations of these factors with increases in the levels of indicators using multilevel logistic regression, and the associations with rates of change in the indicators using Bayesian Hierarchical modelling. Frontline worker (FLW) visits between 2014-2017 were more likely to increase in blocks with better night lighting (odds ratio (OR) = 1.23, 95% confidence interval (CI) = 1.01-1.51). Birth preparedness increased in blocks with increasing FLW visits (OR = 3.43, 95% CI = 1.15-10.21), while dry cord care practice increased in blocks where satisfaction with FLW visits was increasing (OR = 1.52, 95% CI = 1.10-2.11). Age-appropriate frequency of complementary feeding increased in blocks with higher development index (OR = 1.55, 95% CI = 1.16-2.06) and a higher percentage of scheduled caste or tribe (OR = 3.21, 95% CI = 1.13-9.09). An increase in most outcomes was more likely in areas with lower baseline levels. Contextual factors (eg, night lighting and development) not targeted by the programme and FLW visits were associated with favourable programme outcomes. Intervention design, including intervention selection for a particular geography, should be modified to fit the local context in the short term. Expanding collaborations beyond the health sector to influence modifiable contextual factors in the long term can result in a higher magnitude and more sustainable impact. ClinicalTrials.gov: NCT02726230.