203769 Identifying Communities at Risk for Sudden and Unexpected Infant Deaths

Monday, November 9, 2009

Sabrina Walsh, DrPH , Department of Epidemiology, University of Kentucky, Lexington, KY
Daniel Carey, PhD , Kentucky Geological Survey, University of Kentucky, Lexington, KY
Background: In 2004, approximately 4,500 cases of sudden, unexpected infant death (SUID) occurred in the United States. A diagnosis of sudden infant death syndrome (SIDS) was made in the majority and it remains the leading cause of postneonatal SUID.

Methods: In 2006 the Centers for Disease Control and Prevention funded seven states to record and collect statewide data to clarify certification practices, and identify if state performances fall short of national expectations. Statewide 2004 and 2005 SUID data were retrospectively collected in Kentucky. There were 160 evaluable SUID cases during the study period. SUID cases were separated into two groups: SIDS cases and Other SUIDs. For visual analysis of the data, cases were geocoded then spatially joined to the county GIS data layer in a combined data set in order to create maps. Indirect standardization and probability maps were generated and areas with unexpectedly high or low SUIDs identified.

Results: Of Kentucky's 120 counties, 21 were found to have SUIDs higher than expected and 11 lower than expected. The remaining 88 counties were considered average with an expected number of SUID cases.

Conclusions: By identifying regions with higher than expected SUID rates communities may be targeted, risk factors (whether geographical or behavioral) identified and possibly prevented. Regions with lower than expected rates offer possible understanding of protective factors. Similar analyses could be undertaken in other states to direct limited resources to appropriate targets, implementing optimal and safe risk reduction strategies, and future pregnancy planning.

Learning Objectives:
1) Understand the problem of sudden and unexpected infant death in one state and, considering limited resources, explain why itís important to determine which geographical areas are most risk. 2) Describe how probability mapping can identify at risk communities 3) Describe how communities with lower than expected mortality can offer as much as those with higher than expected mortality.

Keywords: Child Health Promotion, Community-Based Health Promotion

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: The area of research I am submitting was a part of my dissertation research on sudden, unexpected infant death
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.