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. 2020 May:220:49-55.e2.
doi: 10.1016/j.jpeds.2020.01.006. Epub 2020 Feb 12.

Geographic Variation in Sudden Unexpected Infant Death in the United States

Edwin A Mitchell  1 , Xiaohan Yan  2 , Shirley You Ren  2 , Tatiana M Anderson  3 , Jan-Marino Ramirez  4 , Juan M Lavista Ferres  2 , Richard Johnston  2
Affiliations

Geographic Variation in Sudden Unexpected Infant Death in the United States

Edwin A Mitchell et al. J Pediatr. 2020 May.

Abstract

Objectives: To assess the geographic variation of sudden unexpected infant death (SUID) and test if variation in geographic factors, such as state, latitude, and longitude, play a role in SUID risk across the US.

Study design: We analyzed the Centers for Disease Control and Prevention's Cohort Linked Birth/Infant Death dataset (2005-2010; 22 882 SUID cases, 25 305 837 live births, rate 0.90/1000). SUID was defined as infant deaths (ages 7-364 days) that included sudden infant death syndrome, ill-defined and unknown cause of mortality, and accidental suffocation and strangulation in bed. SUID geographic variation was analyzed using 2 statistical models, logistic regression and generalized additive model (GAM).

Results: Both models produced similar results. Without adjustment, there was marked geographic variation in SUID rates, but the variation decreased after adjusting for covariates including known risk factors for SUID. After adjustment, nine states demonstrated significantly higher or lower SUID mortality than the national average. Geographic contribution to SUID risk in terms of latitude and longitude were also attenuated after adjustment for covariates.

Conclusion: Understanding why some states have lower SUID rates may enhance SUID prevention strategies.

Keywords: SIDS; SUID; climate; poverty; socioeconomic disadvantage; sudden infant death.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1.
Figure 1.
Geographic variation of SUID mortality odds ratio by state, 2005–2010. The left panel (A) shows all states, whereas the right panel (B) only shows states with statistically significant variation from the national average. After adjustment for individual covariates and county-level urbanization rate (C) shows all states, whereas the (D) only shows states with statistically significant variation from the national average. Statistically insignificant states are shown in grey in the right panels. Blue colors are below average and red above average.
Figure 2.
Figure 2.
Heatmap of estimated smoothing surface from GAM model for SUID mortality on 2005–2010 data. The 2-dimensional smoothing surface on longitude and latitude gives the amount of contribution of a spatial location to the SUID mortality rate. Live births from blue areas have lower chance to die from SUID, where as those from red areas have higher chance to die from SUID. The spatial locations on the same contour share the same value on the smoothing surface. The left panel (A) include all locations uniformly drawn from the US. In the right panel (B), grey areas represent regions with estimated smoothing surface values that are not statistically different from zero.
Figure 3.
Figure 3.
Heatmap of estimated smoothing surface from GAM model for SUID mortality on 2005–2010 data, after adjustment for individual covariates and county-level urbanization rate. The left panel (A) include all locations uniformly drawn from the US. In the right panel (B), grey areas represent regions with estimated smoothing surface values that are not statistically different from zero. The same color scale is used for visualizing the smoothing surface as was used in Figure 2.
See this image and copyright information in PMC

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