Abstract
BackgroundThe purpose of the study was to evaluate intraclass correlation coefficients (ICC) of variables concerning personal characteristics, structure, outcome and process in the Brazilian Network for Surveillance of Severe Maternal Morbidity study conducted to identify severe maternal morbidity/near miss cases using the World Health Organization criteria.MethodIt was a cross-sectional, multicenter study involving 27 hospitals providing care for pregnant women in Brazil. Cluster size and the mean size of the primary sampling unit were described. Estimated prevalence rates, ICC, their respective 95% confidence intervals, the design effect and the mean cluster size were presented for each variable.ResultsOverall, 9,555 cases of severe maternal morbidity (woman admitted with potentially life-threatening conditions, near miss events or death) were included in the study. ICC ranged from < 0.001 to 0.508, with a median of 0.035. ICC was < 0.1 for approximately 75% of the variables. For process-related variables, median ICC was 0.09, with 0.021 for those related to outcome. These findings confirm data from previous studies. Homogeneity may be considered minor, thus increasing reliability of these findings.ConclusionsThese results may be used to design new cluster trials in maternal and perinatal health and to help calculate sample sizes.
Highlights
The purpose of the study was to evaluate intraclass correlation coefficients (ICC) of variables concerning personal characteristics, structure, outcome and process in the Brazilian Network for Surveillance of Severe Maternal Morbidity study conducted to identify severe maternal morbidity/near miss cases using the World Health Organization criteria
The ICCs for the variables related to the process are shown in Table 2, with values ranging from 0.001 to 0.508, while design effect (DEFF) values varied from 1.5 to 292.63
P: Prevalence of each category; ICC: Intraclass Correlation Coefficient; 95% confidence intervals (95% CI): 95% confidence interval; DEFF: Design effect; na: Mean cluster size; PLTC: Potentially life-threatening condition; NM: Near miss
Summary
The purpose of the study was to evaluate intraclass correlation coefficients (ICC) of variables concerning personal characteristics, structure, outcome and process in the Brazilian Network for Surveillance of Severe Maternal Morbidity study conducted to identify severe maternal morbidity/near miss cases using the World Health Organization criteria. Cluster studies are widely used in epidemiological research to evaluate health interventions and implement public policies In these cases, selection units or randomization units consist of population groups (specific geographical areas) or healthcare units (hospitals) or healthcare sectors rather than individuals [1,2]. Unlike simple random sampling (SRS) in which each individual has an equal likelihood of being selected within the general population, data obtained from clusters may not be sufficiently representative to allow for generalization. This is due to a greater degree of homogeneity in characteristics of the population under observation, as opposed to heterogeneity found in the general population [2]. Another way to perform measurements is to calculate the design effect (DEFF)
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