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Intracluster correlation coefficients for the Brazilian Multicenter Study on Preterm Birth (EMIP): methodological and
Giuliane J Lajos1, Samira M Haddad, Ricardo P Tedesco
1Department of Obstetrics and Gynecology, School of Medical Sciences, University of Campinas, Campinas, Brazil. giuliane@unicamp.br.
BMC Medical Research Methodology
|April 24, 2014
Summary
Intracluster correlation coefficients (ICC) in a Brazilian preterm birth study were mostly low, indicating significant variability within clusters. These findings are crucial for designing future maternal and perinatal health research sample sizes.
Area of Science:
- Maternal and Perinatal Health Research
- Biostatistics
- Epidemiology
Background:
- Cluster-based health studies are increasingly common.
- Intracluster correlation coefficient (ICC) quantifies variability due to clustering.
- Evaluating ICC is vital for accurate study design.
Purpose of the Study:
- To assess the intracluster correlation coefficient (ICC) for various variables in the Brazilian Multicenter Study on Preterm Birth.
- To understand the extent of data variability attributable to clustering in this cohort.
Main Methods:
- A multicenter cross-sectional study on preterm births across 20 Brazilian hospitals.
- Nested case-control study to identify spontaneous preterm birth factors.
- Calculated ICC, design effects, and mean cluster sizes for over 250 variables.
Main Results:
- Intracluster correlation coefficients (ICC) ranged from <0.001 to 0.965, with a median of 0.028.
- Median ICC for descriptive characteristics was 0.014, for newborn outcomes 0.041, and for process variables 0.102.
- Approximately 95% of variables had ICC <0.3, with higher ICCs (>0.3) noted in specific clinical management aspects like corticosteroid use.
Conclusions:
- Clusters in the Brazilian Multicenter Study on Preterm Birth exhibited predominantly heterogeneous findings.
- The calculated ICC values provide essential data for sample size estimations in future maternal and perinatal health research.
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