Alyssa Cadez-Martin
Pronouns: she/her
Research Mentor(s): Sarah Fox, Research Manager
Research Mentor School/College/Department: Pediatric Surgery, Michigan Medicine
Presentation Date: Thursday, April 22, 2021
Session: Session 4 (2pm-2:50pm)
Breakout Room: Room 2
Presenter: 1
Abstract
Infant mortality is the death of an infant within the first year of life, and this is a very useful indicator of population health. The United States has one of the highest infant mortality rates among developed countries, and while the reason for this remains unclear, it is hypothesized that social determinants of health play a large role. Social determinants of health are conditions in the lives of people that affect health risks and outcomes. It is still unclear how these determinants influence infant mortality, and which determinants have the most influence. In Michigan, the infant mortality rate as of 2018 was 6.8 deaths per 1,000 live births (Centers for Disease Control and Prevention (CDC), 2018). This puts Michigan high on the spectrum within the United States, and just as these rates differ by country, they also differ by state and even county. It was hypothesized that by studying two counties with different infant mortality rates, the difference could be attributed to the social determinants of health that vary among these populations. Therefore, if it can be determined that particular determinants have a more significant influence on infant mortality rates, then vulnerable populations can be more easily identified, and implementation efforts can be better catered to these populations and their disadvantages. Infant mortality data were collected from the Michigan Department of Health and Human Services from 2010-2018 for both Washtenaw and Wayne County, Michigan. Additional data were collected from the United States Census Bureau from 2010-2018 regarding social determinants such as poverty rate, unemployment rate, uninsured rate, race, and education level for both counties. After performing a series of calculations including linear regressions and logistic regression curves to find odds ratios, no correlation was found between the infant mortality rates and any of the determinants. Therefore, it can be concluded that one social determinant of health is unlikely to be a good predictor of infant outcomes. Instead, high infant mortality rates are likely a result of interactions between several determinants that, together, increase an infant’s risk. Therefore, simultaneous targeting of multiple determinants is necessary to implement meaningful interventions.
Authors: Samir Gadepalli, Barbara Tan
Research Method: Survey Research
