title: Intracluster correlation coefficients from the 2005 WHO Global Survey on Maternal and Perinatal Health: implications for implementation research.
abstract: Cluster-based studies involving aggregate units such as hospitals or medical practices are increasingly being used in healthcare evaluation. An important characteristic of such studies is the presence of intracluster correlation, typically quantified by the intracluster correlation coefficient (ICC). Sample size calculations for cluster-based studies need to account for the ICC, or risk underestimating the sample size required to yield the desired levels of power and significance. In this article, we present values for ICCs that were obtained from data on 97,095 pregnancies and 98,072 births taking place in a representative sample of 120 hospitals in eight Latin American countries. We present ICCs for 86 variables measured on mothers and newborns from pregnancy to the time of hospital discharge, including 'process variables' representing actual medical care received for each mother and newborn. Process variables are of primary interest in the field of implementation research. We found that overall, ICCs ranged from a minimum of 0.0003 to a maximum of 0.563 (median 0.067). For maternal and newborn outcome variables, the median ICCs were 0.011 (interquartile range 0.007-0.037) and 0.054 (interquartile range 0.013-0.075) respectively; however, for process variables, the median was 0.161 (interquartile range 0.072-0.328). Thus, we confirm previous findings that process variables tend to have higher ICCs than outcome variables. We demonstrate that ICCs generally tend to increase with higher prevalences (close to 0.5). These results can help researchers calculate the required sample size for future research studies in maternal and perinatal health.
authors.affiliation: Ottawa Health Research Institute and University of Ottawa, Ottawa, Ontario, Canada. mtaljaard@ohri.ca
authors.forename: Monica
authors.initials: M
authors.lastname: Taljaard
authors.forename: Allan
authors.initials: A
authors.lastname: Donner
authors.forename: José
authors.initials: J
authors.lastname: Villar
authors.forename: Daniel
authors.initials: D
authors.lastname: Wojdyla
authors.forename: Alejandro
authors.initials: A
authors.lastname: Velazco
authors.forename: Vicente
authors.initials: V
authors.lastname: Bataglia
authors.forename: Anibal
authors.initials: A
authors.lastname: Faundes
authors.forename: Ana
authors.initials: A
authors.lastname: Langer
authors.forename: Alberto
authors.initials: A
authors.lastname: Narváez
authors.forename: Eliette
authors.initials: E
authors.lastname: Valladares
authors.forename: Guillermo
authors.initials: G
authors.lastname: Carroli
authors.forename: Nelly
authors.initials: N
authors.lastname: Zavaleta
authors.forename: Archana
authors.initials: A
authors.lastname: Shah
authors.forename: Liana
authors.initials: L
authors.lastname: Campodónico
authors.forename: Mariana
authors.initials: M
authors.lastname: Romero
authors.forename: Sofia
authors.initials: S
authors.lastname: Reynoso
authors.forename: Karla Simônia
authors.initials: KS
authors.lastname: de Pádua
authors.forename: Daniel
authors.initials: D
authors.lastname: Giordano
authors.forename: Marius
authors.initials: M
authors.lastname: Kublickas
authors.forename: Arnaldo
authors.initials: A
authors.lastname: Acosta
mesh_terms: D016000:Cluster Analysis; D005260:Female; D006302:Health Services Research / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D007231:Infant, Newborn; D008429:Maternal Welfare; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data*; D018743:Perinatal Care; D011247:Pregnancy; D014944:World Health Organization