Development of a Risk Score to Predict Sudden Infant Death Syndrome

Mounika Polavarapu (), Hillary Klonoff-Cohen, Divya Joshi, Praveen Kumar, Ruopeng An and Karin Rosenblatt
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Mounika Polavarapu: School of Population Health, The University of Toledo, HH 1010, Mail Stop 119, 2801 W. Bancroft St., Toledo, OH 43606, USA
Hillary Klonoff-Cohen: Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Divya Joshi: Department of Pediatrics, Johns Hopkins All Children’s Hospital, St. Petersburg, FL 33701, USA
Praveen Kumar: Department of Pediatrics, Children’s Hospital of Illinois, Peoria, IL 61603, USA
Ruopeng An: Brown School, Washington University in St. Louis, St. Louis, MO 63130, USA
Karin Rosenblatt: Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA

IJERPH, 2022, vol. 19, issue 16, 1-16

Abstract: Sudden Infant Death Syndrome (SIDS) is the third leading cause of death among infants younger than one year of age. Effective SIDS prediction models have yet to be developed. Hence, we developed a risk score for SIDS, testing contemporary factors including infant exposure to passive smoke, circumcision, and sleep position along with known risk factors based on 291 SIDS and 242 healthy control infants. The data were retrieved from death certificates, parent interviews, and medical records collected between 1989–1992, prior to the Back to Sleep Campaign. Multivariable logistic regression models were performed to develop a risk score model. Our finalized risk score model included: (i) breastfeeding duration (OR = 13.85, p < 0.001); (ii) family history of SIDS (OR = 4.31, p < 0.001); (iii) low birth weight (OR = 2.74, p = 0.003); (iv) exposure to passive smoking (OR = 2.64, p < 0.001); (v) maternal anemia during pregnancy (OR = 2.07, p = 0.03); and (vi) maternal age <25 years (OR = 1.77, p = 0.01). The area under the curve for the overall model was 0.79, and the sensitivity and specificity were 79% and 63%, respectively. Once this risk score is further validated it could ultimately help physicians identify the high risk infants and counsel parents about modifiable risk factors that are most predictive of SIDS.

Keywords: SIDS; prediction model; risk score; risk factors; prevention (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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