Survive and Thrive – A New Future for African American Babies

African American women in Ohio are three times as likely to lose an infant before their first birthday than white women. Ohio Department of Health has identified nine Ohio counties that account for more than 90% of all black infant deaths. Recent research suggests that toxic stress is the driver for poor birth outcomes in African American women and is a prevalent factor in premature birth, a leading cause of infant death in the United States (CDC, 2017). Toxic stress is caused by chronic overwhelming social and environmental conditions such as poor housing conditions, parental unemployment, lack of transportation, food deserts, as well as the lack of diverse, culturally sensitive health care providers adversely impacts the African American mother and the child in utero (Braveman et al., 2017; Dominguez, Dunkel-Schetter, Glynn, Hobel, & Sandman, 2008; Nuru-Jeter et al., 2009).

 

A multi-disciplinary team at Cleveland State University and our partners, Birthing Beautiful Communities (BBC) and the Cleveland Clinic propose an innovative, pathbreaking project, Survive & Thrive: A New Future for African American Babies that promises to significantly reduce the incidence of African American Infant mortality in Ohio. Central to the project is the use of a social determinants of health research and practice framework to scale and implement a two-county pilot in Cuyahoga and Summit Counties, which can be used as proof of concept for translation and replication statewide.

 

The grounding research for this project employs a social determinant “big” data set, ranging from macroeconomic factors (e.g., deindustrialization) to microeconomic factors (e.g., income, housing) to neighborhood and household conditions (e.g., trauma exposure, environmental toxins, neighborhood amenities). The resulting analysis will form the “upstream” pathways to the “downstream” effect of care access and birth outcomes and will be used to understand the etiology of infant mortality through the use of machine learning techniques. Specifically, this project will develop an explanatory algorithm identifying the causal links that lead to infant mortality thus further informing, illustrating and enhancing our core intervention.