Loading…

Loading grant details…

Completed TRAINING, INDIVIDUAL NIH (US)

Effects of geospatial factors and health worker characteristics on child health: implications for interventions in low-resource settings

$382.2K USD

Funder EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT
Recipient Organization University of California Berkeley
Country United States
Start Date Dec 15, 2021
End Date Aug 14, 2023
Duration 607 days
Number of Grantees 1
Roles Principal Investigator
Data Source NIH (US)
Grant ID 10515645
Grant Description

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.

All Grantees

University of California Berkeley

Advertisement
Apply for grants with GrantFunds
Advertisement
Browse Grants on GrantFunds
Interested in applying for this grant?

Complete our application form to express your interest and we'll guide you through the process.

Apply for This Grant