Additional file 1 of Estimating physical activity from self-reported behaviours in large-scale population studies using network harmonisation: findings from UK Biobank and associations with disease outcomes

Additional file 1: Table S1. Questions used to generate domain-specific and composite behavioural variables. Table S2. Calculation of comparison summary scores using METs. Table S3. International Classification of Diseases 10th edition (ICD-10) codes for outcome definition. Table S4. Mutually adjusted sex-specific coefficients (standard errors) for prediction of average daily wrist acceleration (m-g) from 14 self-reported behaviours. Table S5. Hazard ratio and 95% confidence interval for fatal and non-fatal outcomes by quartile of PAEESR in UK Biobank. Table S6 Baseline characteristics of participants with prevalent chronic disease in UK Biobank. Figure S1. Exclusions and sample sizes for analyses. Figure S2. Differences between physical activity energy expenditure predicted from self-report (PAEESR) and doubly labelled water based PAEE (PAEEDLW), plotted against their mean. Figure S3. Hazard ratio and 95% confidence intervals for association between physical activity energy expenditure predicted from self-report (PAEESR) and disease outcomes in UK Biobank. Figure S4. Hazard ratio (HR) and 95% confidence interval (CI) for linear associations of physical activity energy expenditure predicted from self-report (PAEESR, per 5 kJ/day/kg increments) with fatal and non-fatal outcomes in UK Biobank. Figure S5. Hazard ratio (HR) and 95% confidence interval (CI) for linear associations of physical activity energy expenditure predicted from self-report (PAEESR, per 5 kJ/day/kg increments) with fatal and non-fatal outcomes in UK Biobank.