The logistic
regression models were adjusted for all the covariates described above (with find more country-specific exclusions) to minimize confounding and ensure comparability of findings across countries. Age and number of household members were treated as continuous variables. In Brazil, the ‘education’ variable was not included in the model because the variable definition was not comparable with other GATS countries (Palipudi et al., 2012), however, we did conduct a sensitivity analysis by including education variable in the model and found that the results were consistent with those obtained without including it in the model. We tested for multicollinearity between the covariates adjusted for in the analysis for each country. The multicollinearity diagnostics variance inflation factor (VIF) values were all less than five, indicating reasonable independence between the predictor variables for each country-specific model (Glantz and Slinker, 2001). The only exception HIF inhibitor to this was the covariate ‘education’ in Poland where VIF values were less than 6.5. The variable ‘national region’ was removed from the model in Egypt due to collinearity. Country-specific
sampling weights were applied for all analyses to account for the complex study design. To estimate the overall association of being employed in a smoke-free workplace with living in a smoke-free home across the 15 LMICs, we calculated a pooled AOR and 95% CI using a random effects meta-analysis based on the AOR’s from the individual countries (The random effects meta-analysis accounts for heterogeneity between countries, p < 0.0005.). All the statistical analyses were conducted using STATA v.12.0. Of the participants employed indoors outside the home, the percentage reporting
a smoke-free workplace was 83% in Uruguay, 81% in Mexico, 76% in Brazil, 74% in Thailand, 70% in India, 68% in Ukraine and Philippines, 66% in Romania old and Poland, 64% in Russian Federation, 63% in Turkey, 44% in Viet Nam, 40% in Egypt and 35% in Bangladesh and China (data not shown). In all the 15 LMICs, the percentage of participants living in a smoke-free home was higher among those employed in a smoke-free workplace compared with those employed in a workplace where smoking occurred (Fig. 1, Table 1). Among participants employed in a smoke-free workplace, the percentage living in a smoke-free home varied from 21% in China to 75% in Mexico. Among participants employed in a workplace that was not smoke-free, the percentage living in a smoke-free home varied from 9% in China to 69% in Mexico. Table 1 describes the country-specific percentages of participants reporting living in smoke-free homes by their socio-demographic characteristics. There were significant positive associations between being employed in a smoke-free workplace and living in a smoke-free home in all the LMICs except Uruguay and Mexico (Fig. 2, Table 2). The AOR estimates ranged from 1.