SIDS/SUID (henceforth referred to as SIDS) is a leading cause of neonate death, taking the lives of ~10 infants every day in the US alone. SIDS is defined as the death of an infant for which no cause of death can be determined after a complete autopsy, death scene investigation, and medical history review, all of which makes SIDS a very diffcult disease to study. Death scene investigations have identified several contributing environmental factors. However, etiological investigation has been complicated by inconsistencies in classification of death by medical examiners or coroners and unreliable resources for law enforcement to complete death scene investigations, which leads to epidemiological studies often lacking rigor or suffcient data. Using data from Child Fatality Review Team (CFRT) of Harris County, the Medical Examiner’s Offce, and the Texas Department of State Health Services, we performed a retrospective analysis of 17-years of SIDS cases in Harris County, Texas. We applied a novel birth rate correction for SIDS rates over the first year of life. Associations were tested using a Tukey HSD and linear regression models with co-linear factors considered. To focus on biologically unexplained SIDS cases, we subsetted our dataset to only include SIDS and Undetermined causes of death. Our preliminary data includes 1,094 cases comprised of ~43% black, ~32% Hispanic, ~20% white, ~3% Asian, and ~0.4% unknown and 57% male infants. Distribution of death across the first 12 months of life shows a peak of death around 2 months of age. We do not see an association with month or season in the raw SIDS data nor when using our novel correction for birth rates. When we apply the standard per 1,000 live births normalization, we see a significant increase in Spring and Winter. We also report race-dependent significant differences in yearly and monthly case numbers, male-to-female ratios, and age at death and additional significant race-dependent associations between SIDS cases and adults diagnosed with asthma, income level, and overcrowding based on Zip Code. This dataset represents one of the most racially and socio-economically diverse in the United States. Our data suggests that standard trends may be driven by majority white datasets and that response to socioeconomic stress varies by race/ ethnicity, which leads to differences in risk between classically described minority groups. NIH: 1F32HL160073-01A1, R01HL130249 44617-S4. BCM McNair Scholar Program, March of Dimes Basil O'Connor Research Award, Parker B. Francis Fellowship, CJ Foundation for SIDS. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
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