Additional file 1: of Decomposing health inequality with population-based surveys: a case study in Rwanda

2018-05-10T05:00:00Z (GMT) by Kai Liu Chunling Lu
Box S1. Sampling and implementation process of the Integrated Living Conditions Survey (EICV). Box S2. Measurement of covariates used in the models on analyzing medical care utilization and catastrophic health spending. Box S3. Measurement of household catastrophic health spending (HCHS). Box S4. Multivariate logistic regression models in the analysis of adjusted mean of medical care utilization and HCHS. Table S1. Summary statistics for variables used in regression models on medical care utilization. Table S2. Summary statistics for variables used in regression models on HCHS. Table S3. T-tests about the mean differences of covariates by poverty status. Table S4. Odds ratios for covariates from the logistic model: Medical care utilization. Table S5. Odds ratios for covariates from the logistic model: HCHS. Table S6. Estimated absolute contribution of covariates to inequalities in medical care utilization by poverty status using BO decomposition method (EICV 2005, 2010). Table S7. Estimated contribution of covariates to inequalities in HCHS with different thresholds by poverty status using BO decomposition method (EICV 2005, 2010). Figure S1. Absolute inequalities in HCHS using different thresholds in 2005 and 2010. Figure S2. Decomposing absolute inequality in HCHS using different thresholds by poverty status in 2005 and 2010. (DOCX 89 kb)