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A multivariate "time based" analysis of SIDS risk factors.
T Matthews1, M McDonnell, C McGarvey
1University College Dublin, Dept of Paediatrics, The Children's University Hospital, Temple St, Dublin, Republic of Ireland. tommatt@iol.ie
Archives of Disease in Childhood
|February 24, 2004
Summary
Sudden infant death syndrome (SIDS) risk factors identified in studies vary based on the analytical model used. Including variables like prone sleeping position can alter the significance of previously identified risk factors.
Area of Science:
- Epidemiology
- Biostatistics
- Pediatrics
Background:
- Sudden infant death syndrome (SIDS) remains a significant concern in infant mortality.
- Published research on SIDS risk factors exhibits considerable variability.
- The analytical approach in studies may influence the identification and significance of risk factors.
Purpose of the Study:
- To examine how different analytical designs impact the observed variability in SIDS research findings.
- To understand the influence of multivariate model construction on the identification of SIDS risk factors.
Main Methods:
- A prospective case-control study involving 203 SIDS cases and 622 control infants.
- Multivariate analysis was conducted in nine sequential stages, progressively adding variable categories.
- Variables included sociodemographic factors, pregnancy and birth details, infant's health, and sleep practices.
Main Results:
- Initially identified risk factors like social deprivation and young maternal age became non-significant as more variables were added.
- Factors such as co-sleeping and lack of soother use emerged as significant in later stages.
- Adding 'prone sleep position' in the final stage re-established the significance of 'previous live births' and 'reduced birth weight'.
Conclusions:
- The selection of variables within a multivariate model critically influences which factors are deemed significant in SIDS case-control studies.
- Analytical design choices directly contribute to the heterogeneity of findings in SIDS research.
- Researchers must carefully consider model composition to accurately interpret SIDS risk factors.