The career goal of the investigator is to become an independent epidemiologist at an academic
institution and utilize a multidisciplinary framework to research and design interventions that improve the lives
of children in low-resource settings. The goal of the proposed study is to understand geospatial factors and
characteristics of community health workers that are associated with better child growth and health. The study
will analyze existing data on children from a cluster-randomized controlled trial conducted in rural Bangladesh
(n = 4,708). The investigator will use data on child growth, laboratory data on biomarkers of environmental
enteric dysfunction (a proposed cause of poor growth) in a subset of ~1500 children per site, household
information (including geolocation and reported walking time to village resources), and data on characteristics
of community health workers that delivered the water, sanitation, and hygiene interventions. We propose to
accomplish the following aims: Aim 1: Estimate the independent effects of distance to different resources on
child growth and EED. Multiple regression will be performed to test the impact of walking time to healthcare
center, markets, water source, and major roads on child growth and EED biomarkers. Aim 2: Create a
household accessibility score and determine its association with child growth and EED. A household
accessibility score will be created using principal components analysis on travel time to resources in the village
and we will use geospatial analyses to determine the spatial association between household accessibility and
child growth and EED biomarkers. Aim 3: Determine characteristics of community health workers that improve
child growth in the context of WaSH interventions. Machine learning and a variable importance analysis will be
used to understand characteristics that independently predict child growth. By understanding the heterogeneity
of spatial risk factors and their associations with child growth and health, we may be able to target households
with children at increased risk for poor development and inform the effective implementation of interventions for
child growth and health in rural, low-resource settings. The training plan developed by the investigator, sponsor
Dr. Lia Fernald, and co-sponsors Dr. Alan Hubbard and Dr. Justin Remais will support the investigator’s goals
to gain advanced training in epidemiology, biostatistics, and data science, better understand advanced topics
in global child health, and improve on oral and written scientific communication skills. Training and research
will occur at University of California, Berkeley, which has a reputation for mentorship and supporting scientific
research with rigorous methodology among a diverse pool of faculty members interested in multidisciplinary
causes of health outcomes. Overall, the institutional environment, sponsorship team, training plan, and
proposed research project will facilitate the investigator’s transition to an independent research career at an
academic institution implementing rigorous interventions that will improve the health and development of
children in rural, low-resource settings.
