Quantitative Data were entered in EpiData (version 3.1) and analyzed using EpiData analysis software (v 2.2.2.183) and STATA 14 (StataCorp, College Station, Texas). Sociodemographics such as gender, birth details, parental factors, breastfeeding status, supplementary feeding started or not, and food items consumed by the child are summarized as frequencies and percentages. Of the several groups of foods, if the child had consumed at least four groups of foods on the previous day, it was considered as dietary diversity present. Prevalence of dietary diversity is presented as percentages with a 95% confidence interval (CI). To avoid overestimating the risk by odds ratio for highly prevalent conditions like dietary diversity, it was preferred to present an adjusted prevalence ratio (PR) using negative log-binomial regression with the Poisson family. Factors identified with P value of 0.2 or less were further subjected to Poisson model with log link.[ 34 ] Measures of association with dietary diversity were reported as adjusted PR with 95% CI.
Epidata analysis software
Manufactured by StataCorp
Sourced in Denmark, United States
EpiData analysis software is a data entry, data management, and statistical analysis tool designed for epidemiological research and data analysis. The software provides a user-friendly interface for data entry, validation, and basic statistical analyses.
Automatically generated - may contain errors
3 protocols using epidata analysis software
1
Dietary Diversity Factors in Children
2
Undernutrition Prevalence and Risk Factors
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Data entry was performed using EpiData software (v. 3.1 EpiData Association, Odense, Denmark) and analysis was done using EpiData Analysis software and Stata (StataCorp. 2009. Stata Statistical Software: Release 11, College Station, TX: StataCorp LP). Prevalence of undernutrition is reported as frequency and proportions. The continuous variables were summarized as mean and standard deviation or median and interquartile range as applicable. The categorical variables were reported as frequency and proportion. Children found to be undernourished by at least one of the following criteria, namely weight-for-age, height/length-for-age, or BMI-for-age were classified as undernutrition. Cross-tabulations were made to find the association between various known risk factors and undernutrition using Chi-square test and a P value of less than 0.05 was considered to be statistically significant. Unadjusted prevalence ratios with 95% CI were calculated. Multivariate analysis was done considering the independent variables which had a P value of less 0.25 into the model.
3
HBV Vaccination Predictors and Outcomes
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Data was exported into EpiData analysis software (version 2.2.2.183) and STATA (version 11, StataCorp, College Station, TX, USA) for data analysis. Continuous variables such as age were described as median and interquartile ranges (IQR). Categorical variables such as gender (male/female), vaccination completion (yes/no) and sero-protection (yes/no) were described as frequencies and proportions. Unadjusted risk ratios (RR) and adjusted risk ratios (aRR) were calculated for the association of select socio-demographic and clinical factors (age group, gender, project site, educational levels, occupation, risk group and HIV status) with outcome variables (HBV vaccination refusal, vaccination incompletion, those who did not return for HBV antibody testing and HBV sero-un-protection). Confidence intervals (CI) of 95% and a p-value < 0.05 were considered significant.
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