Using big data to understand the influence of extreme weather events on child health and development in the United States - PROJECT SUMMARY/ABSTRACT Globally, extreme weather events pose widespread potential negative health effects. Children are a particularly vulnerable population because the first few years of life is a critical period of rapid physical and brain development that is sensitive to environmental insults and sets the foundation for lifelong health, learning, and well-being. Poor child health and development may be exacerbated by extreme weather events, which threaten to disproportionately affect children already at risk of suboptimal health, aggravating the health disparities we see today. Extreme weather negatively affects Gross Domestic Product, income-generating activities, and population health outcomes of mortality and morbidity. Little is known, however, about the potential effects of weather-related events on child physical health, mental health, and development. Further, extreme heat and drought have been the principal weather variables explored in prior research, while flooding and storms have rarely been examined; all four are types of extreme weather events that can have devastating impacts on child health and development. Improved understanding of how extreme weather events are consequential for pediatric outcomes is necessary to inform weather and public health policies in the USA and other countries. The proposed study will use a multi-level repeated cross-sectional design with big data methods to investigate the impact of extreme weather on childhood health and development over the past two decades using seven rigorous national datasets that incorporate data on extreme weather events, socio- demographic, psychosocial, mental health, nutritional, and built environment measures and indicators. We will combine individual-level data on health (i.e., physical and mental) and development (i.e., language, behavior, socio-emotional) of children 0-5 years of age from the U.S. National Survey of Children’s Health with temperature, drought, flooding, and storm data from the Parameter-elevation Regressions on Independent Slopes Model, Evaporative Demand Drought Index, and National Oceanic and Atmospheric Administration datasets. This combined dataset will then be merged with data from the U.S. Department of Health and Human Services, the Current Population Survey, and the National Center for Health Statistics. We will then employ big data methods, including geospatial analyses and machine learning methods, to 1) understand the relationships between key measures and indicators of extreme heat, drought, flooding, and storms and suboptimal child health and development across the USA, and 2) explore mediators along the indirect paths for effects of extreme weather events on child health and development (i.e., built environment, caregiver physical and mental health, caregiving practices, income, access to healthcare and social protection, community health and economy, and food insecurity). The results of this study will lay the foundation for future analyses of data from other parts of the world and provide critical evidence for national and global policies tackling extreme weather and health.
