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

地理空间因素和卫生工作者特征对儿童健康的影响：对资源匮乏环境中干预措施的影响

• 批准号: 10515645
• 负责人: Caitlin Hemlock
• 金额: $ 3.82万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-15 至 2023-08-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10515645
• 关键词: Adherence; Affect; Area; Attitude; Bangladesh; Biological Markers; Biometry; California; Cessation of life; Characteristics; Child; Child Development; Child Health; Chronic Disease; Cognitive; Communicable Diseases; Communication; Communities; Community Health Aides; Country; Data; Data Science; Development; Dietary Intervention; Education; Enrollment; Enteral; Environment; Epidemiologist; Epidemiology; Faculty; Feces; Frontline worker; Functional disorder; Geographic Distribution; Goals; Growth; Health; Health Promotion; Health care facility; Healthcare; Height; Heterogeneity; Household; Hygiene; Immunology; Income; Individual; Infection; Inflammation; Inflammatory; Institution; International; Intervention; Intervention Trial; Laboratories; Length; Link; Literature; Machine Learning; Malnutrition; Marketing; Measures; Medical; Mentorship; Methodology; Methods; Microbe; Motivation; Oral; Outcome; Outcome Assessment; Performance; Permeability; Play; Population; Positioning Attribute; Poverty; Primary Health Care; Principal Component Analysis; Randomized, Controlled Trials; Reporting; Research; Research Design; Research Personnel; Research Project Grants; Resource-limited setting; Resources; Risk; Risk Factors; Rural; Sanitation; Site; Small Intestines; Social support; Source; Supervision; Sustainable Development; Testing; Time; Training; Travel; Universities; Urine; Wages; Walking; Water; Work; Writing; behavior change; care seeking; career; chronic infection; community involvement; demographics; design; dietary; effective intervention; experience; food insecurity; gut inflammation; health management; high risk; implementation intervention; improved; innovation; interest; machine learning algorithm; member; multidisciplinary; novel; nutrient absorption; nutrition; programs; rural area; skills; therapy design; urban area

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.

调查员的职业目标是成为一名学术机构的独立流行病学家。 建立并利用多学科框架来研究和设计改善生活的干预措施 在资源匮乏的环境中的儿童。拟议研究的目标是了解地理空间因素和 社区卫生工作者的特征与儿童更好的成长和健康有关。这项研究 将分析孟加拉国农村地区进行的整群随机对照试验中关于儿童的现有数据 (n=4,708)。研究人员将使用有关儿童生长发育的数据、环境生物标志物的实验室数据 每个站点、家庭约1500名儿童的肠道功能障碍(被认为是生长不良的原因) 信息(包括地理位置和报告的到村庄资源的步行时间)，以及关于特征的数据 提供水、卫生设施和个人卫生干预的社区卫生工作者。我们建议 实现以下目标：目标1：估计距离对不同资源的独立影响 儿童成长和EED。将进行多元回归以测试步行时间对医疗保健的影响 儿童生长和EED生物标志物的中心、市场、水源和主要道路。目标2：创建 家庭可获得性评分，并确定其与儿童生长和EED的关联。一户人家 将使用主成分分析对村里的资源进行旅行时间的可达性评分 我们将使用地理空间分析来确定家庭可访问性和 儿童生长发育和EED生物标志物。目标3：确定改进的社区卫生工作者的特征 在环卫运动干预背景下的儿童成长。机器学习和变量重要性分析将 用于理解独立预测儿童成长的特征。通过了解异质性 空间风险因素及其与儿童成长和健康的关联，我们或许能够针对家庭 使儿童面临更高的发展不良风险，并为有效实施干预措施提供信息 在农村、低资源环境中的儿童成长和健康。由调查人员、赞助商制定的培训计划 Lia Fernald博士和共同赞助人Alan Hubbard博士和Justin Remais博士将支持研究人员的目标 要获得流行病学、生物统计学和数据科学方面的高级培训，请更好地了解高级主题 在全球儿童健康方面，并提高口头和书面的科学交流技能。培训和研究 将在加州大学伯克利分校举行，该校以指导和支持科学研究而闻名 在对多学科感兴趣的不同教职员工中以严谨的方法进行研究 健康后果的原因。总体来说，机构环境、赞助团队、培训计划和 拟议的研究项目将促进调查员向独立研究职业生涯的过渡 实施严格干预的学术机构，将改善儿童的健康和发展 农村、低资源环境中的儿童。