Additional file 1 of The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach

Supplementary Material 1

Additional file 1 of Impact of short-term exposure to air pollution on natural mortality and vulnerable populations: a multi-city case-crossover analysis in Belgium

Additional file 1: Table S1. Summary statistics for population and mortality by agglomeration. Table S2. Algorithms defining the pseudopathologies. Table S3. Pollutants averaged (2010-2015) daily concentrations (µg/m3) by agglomeration. Table S4. Summary statistics for air pollutants by subgroups, 2010-2015. Table S5. I-square statistic and p-values for Cochran Q-test for heterogeneity. Table S6. Pearson correlations between pollutants. Table S7. Percentage changes and 95% confidence intervals associated with 10 μg/m3 increase in PM2.5, PM10, O3, NO2 and black carbon, 2010-2015 in sensitivity analyses. Figure S1. Agglomeration-specific and pooled PM2.5-mortality relationships. Figure S2. Agglomeration-specific and pooled PM10-mortality relationships. Figure S3. Agglomeration-specific and pooled O3-mortality relationships. Figure S4. Agglomeration-specific and pooled NO2 -mortality relationships. Figure S5. Agglomeration-specific and pooled black carbon-mortality relationships

Additional file 1 of A healthy lifestyle is positively associated with mental health and well-being and core markers in ageing

Additional file 1: Text S1. TL, mtDNAc and single copy-gene reaction mixture and PCR cycling conditions. Table S1. The mental health indicators with their scores and uses. Table S2. Comparison of the characteristics of the 6,054 eligible BHIS participants that were included in the BHIS subset compared to the 1,838 eligible participants that were excluded from the BHIS subset. Table S3. Comparison of the characteristics of the 739 participants from the BHIS subset that were included in the BELHES subset compared to the 5,315 participants that were excluded from the BELHES subset. Table S4. Bivariate associations between the characteristics and telomere length (TL), mitochondrial DNA content (mtDNAc), the lifestyle score or psychological distress. Table S5. Results of the sensitivity analysis of the association between lifestyle and mental health. Table S6. Results of the sensitivity analysis of the association between lifestyle and the biomarkers of ageing. Table S7. Results of the sensitivity analysis of the association between mental health and the biomarkers of ageing. Fig. S1. Exclusion criteria. The BHIS subset consisted of 6,055 BHIS participants and the BELHES subset consisted of 739 BELHES participants. Fig. S2. Histogram of the lifestyle score. Fig. S3. Validation of the lifestyle score. ROC curve for the lifestyle score as a predictor for good to very good self-perceived health. The model was adjusted for age, sex, region, highest educational level in the household, household composition and country of birth