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.

研究者的职业目标是成为学术机构的独立流行病学家 机构并利用多学科框架来研究和设计改善生活的干预措施 拟议研究的目标是了解地理空间因素和资源匮乏地区的儿童。 与儿童更好的成长和健康相关的社区卫生工作者的特征。 将分析在孟加拉国农村地区进行的整群随机对照试验中有关儿童的现有数据 (n = 4,708)。研究者将使用儿童生长数据、环境生物标志物实验室数据。 每个地点、家庭约 1500 名儿童的子集出现肠功能障碍（生长不良的拟议原因） 信息（包括地理位置和报告的到达村庄资源的步行时间）以及特征数据 我们建议提供水、环境卫生和个人卫生干预措施的社区卫生工作者。 实现以下目标： 目标 1：估计不同资源的距离对 将进行儿童生长和 EED 多元回归来测试步行时间对医疗保健的影响。 目标 2：创建一个关于儿童生长和 EED 生物标志物的中心、市场、水源和主要道路。 家庭可达性得分并确定其与儿童成长和 EED 的关系。 将使用对村庄内资源的旅行时间的主成分分析来创建可达性分数 我们将使用地理空间分析来确定家庭可达性和 目标 3：确定可改善的社区卫生工作者的特征。 WaSH 干预背景下的儿童成长将进行机器学习和变量重要性分析。 通过了解异质性来了解独立预测儿童生长的特征。 通过研究空间风险因素及其与儿童生长和健康的关系，我们或许可以针对家庭 关注发展不良风险增加的儿童，并为有效实施干预措施提供信息 农村、资源匮乏地区的儿童成长和健康 由研究者、资助者制定的培训计划。 Lia Fernald 博士以及共同发起人 Alan Hubbard 博士和 Justin Remais 博士将支持研究者的目标 获得流行病学、生物统计学和数据科学方面的高级培训，更好地理解高级主题 全球儿童健康，并提高口头和书面科学沟通技巧培训和研究。 将在加州大学伯克利分校举行，该大学在指导和支持科学方面享有盛誉 对多学科感兴趣的多元化教师群体采用严格的方法进行研究 总体而言，机构环境、赞助团队、培训计划和 拟议的研究项目将有助于研究者过渡到独立研究职业 学术机构实施积极的干预措施，以改善人们的健康和发展 农村、资源匮乏地区的儿童。