Understanding Risk Gradients from Environment on Native American Child Health Trajectories: Toxicants, Immunomodulation, Metabolic syndromes, & Metals Exposure

了解环境对美国原住民儿童健康轨迹的风险梯度：毒物、免疫调节、代谢综合征、

• 批准号: 10205869
• 负责人: Johnnye L Lewis
• 金额: $ 32.09万
• 依托单位: UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-21 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10205869
• 关键词: Address; Affect; African American; Birth; COVID-19; COVID-19 pandemic; Caregiver Burden; Caregivers; Child; Child Health; Child Rearing; Cities; Cohort Studies; Collection; Communities; Consent; Data; Data Collection; Data Set; Development; Disasters; Discrimination; Ensure; Environment; Family; Frequencies; Future; Government; Home environment; Indigenous; Infrastructure; Internet; Intervention; Knowledge; Life; Measures; Metabolic syndrome; Metal exposure; Methods; Minority; Native Americans; Native-Born; Natural experiment; Navajo; Needs Assessment; Outcome; Participant; Population; Preparation; Prevalence; Protocols documentation; Reproducibility; Research; Risk; Schools; Services; Site; South Dakota; Stress; System; Testing; Time; Training; Trauma; Visit; Vulnerable Populations; cohort; coronavirus disease; data exchange; data portal; experience; immunoregulation; infection rate; insight; member; mortality; neurodevelopment; non-Native; pandemic disease; racism; response; screening; social exclusion; stressor; success; toxicant

Project Summary Available knowledge about how stress in the home environment influences child neurodevelopment points to the importance of capturing time-sensitive data on major stressors, such as the COVID-19 pandemic, across the many populations represented in ECHO. The collective ECHO data offers insight into an unfortunate natural experiment on how such a major stress affects ECHO children and families. Understanding this will allow for better preparation to meet the needs of affected children as they re-enter school and community life, while helping to mitigate the impacts of similar stressors in future disasters affecting children. Minority and marginalized populations are representative of US population prevalence in ECHO, but the total number of any group within the 55,000 ECHO children may still be relatively small. For example, most Native American ECHO participants are in 2 cohorts, and represent fewer than 1500 of the 55,000 children in ECHO. It is conceivable that time-sensitive measures such as responses to ECHO will be captured in very few, or none, of the ECHO participants within marginalized populations most affected. This ECHO NOSI application examines the relative pandemic-induced stress across multiple cohorts differing with respect to marginalization, COVID-19 population prevalence, and experience with historical trauma/systemic racism. At present, this comparison includes the Navajo Birth Cohort Study/ECHO (NBCS/ECHO) cohort, the PASS ECHO cohorts (Indigenous and non-Indigenous populations in South Dakota), and the Atlanta ECHO cohort of urban Black participants. We propose three aims to address our overall hypothesis that pandemic-induced stress will be greatest in populations experiencing the greatest rates of infection and mortality, but exacerbated by historical trauma in Indigenous and Black populations. Aim 1 will ensure availability of time-sensitive data to test this hypothesis in the future; Aim 2 will expand the opportunities for remote and lay staff collection of neurodevelopmental data to ensure availability for testing the hypothesis, and Aim 3 will test and develop a reliable system for transfer of NBCS data to the DAC NBCS portal at greater frequency than is currently possible with infrastructure limits. This is the first study exploring the impact of increased stress across communities already affected by historical trauma and facing a disaster like COVID-19 to address whether collective stress affects long-term child neurodevelopment through changes in parenting and the home environment, and will ensure minority cohorts are represented in the time-sensitive datasets in sufficient numbers to evaluate and compare impacts to develop mitigation interventions, rather than simply by population proportional representation.

项目总结