Background: Climate change is projected to induce extreme and irregular rainfall patterns in the West African Sahel region, affecting household food security and income. Children are among the worst affected population groups. Previous studies focusing on rainfall irregularities in specified periods have revealed how child health and nutritional status are impacted, especially in rural settings. However, the aggregated effect of rainfall over a lifetime on chronic child undernutrition remains poorly understood. Methodology: We conducted a multilevel regression using a 2017 household survey from rural Burkina Faso containing 12919 under-five-year-old children and their corresponding household rainfall data. The rainfall data originated from the Climate Hazards Infrared Precipitation with Stations monthly dataset with a native resolution of 4.8km (0.05°). Results: We show that an increase in rainfall below 75mm monthly average tends to produce poor nutritional outcomes (regression coefficient= -0.11***; 95% CI= -0.13, -0.10; p<0.001) in rural Burkina Faso children. We found a consistent negative relationship between different sex and household wealth groups, but not age groups. Vulnerable younger children were more affected by the adverse effects of increased rainfall, while older children seemed to handle it better. Conclusion: Our methodological approach tracing the impact of rainfall over children's lifetimes makes a meaningful contribution to the portfolio of tools for studying the complex relationship between climate change and health outcomes. Our work confirms that rainfall is a risk factor for chronic child undernutrition, highlighting the need for adaptation strategies that boost household and community resilience to counteract the harmful impacts of climate change on child nutritional status.
In September 2018, India launched Pradhan Mantri Jan Arogya Yojana (PM-JAY), a nationally implemented government-funded health insurance scheme to improve access to quality inpatient care, increase financial protection, and reduce unmet need for the most vulnerable population groups. This protocol describes the methodology adopted to evaluate implementation processes and early effects of PM-JAY in seven Indian states. The study adopts a mixed and multi-methods concurrent triangulation design including three components: 1. demand-side household study, including a structured survey and qualitative elements, to quantify and understand PM-JAY reach and its effect on insurance awareness, health service utilization, and financial protection; 2. supply-side hospital-based survey encompassing both quantitative and qualitative elements to assess the effect of PM-JAY on quality of service delivery and to explore healthcare providers’ experiences with scheme implementation; and 3. process documentation to examine implementation processes in selected states transitioning from either no or prior health insurance to PM-JAY. Descriptive statistics and quasi-experimental methods will be used to analyze quantitative data, while thematic analysis will be used to analyze qualitative data. The study design presented represents the first effort to jointly evaluate implementation processes and early effects of the largest government-funded health insurance scheme ever launched in India.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.