ABSTRACT
In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.
Subject(s)
Analysis of Variance , Child , Cluster Analysis , Cohort Studies , Data Interpretation, Statistical , Epidemiologic Studies , Health Surveys , Humans , India/epidemiology , Linear Models , Nutrition Assessment , Risk Factors , Rural Population , Sex Distribution , Vitamin A/administration & dosage , Vitamin A Deficiency/diagnosisABSTRACT
The main strategy to prevent transfusion-associated Chagas disease is the identification of T. cruzi-infected blood donors by serological screening tests, however there is no perfect serological gold standard. We evaluated an enzyme immunoassay (EIA), an indirect hemaglutination (IHA), and an indirect immunofluorescence (IIF) test for detecting T. cruzi antibodies in Brazilian blood donors. The results were submitted to latent class analysis, and a radioimmunopreciptation (RIPA) test was performed on repeatedly positive samples. Among 1951 donors, 11 (0.56) were positive by EIA, 6 (0.31) by IHA and 16 (0.82) by IIF. Six samples were positive with all tests, while 4 reacted with EIA and IIF. The RIPA was positive in 6 (75.0), 7 (66.6), and 4 (54.0) samples reacting by the EIA, IHA and IIF tests, respectively. The latent class model detected a high sensitivity rate (100) for the EIA and IIF, and a specificity rate of 99.95 and 99.69 for the EIA and IIF tests, respectively. The probability of being case according to the model was 99.92 when both EIA and IIF were positive, and 100 for the association of EIA, IIF, and IHA.