Associations between alcohol, tobacco and cannabis use and daily job exposure to the public, taking no daily exposure as reference category, in 16,566 men and 17,426 women.

<p>Associations between alcohol, tobacco and cannabis use and daily job exposure to the public, taking no daily exposure as reference category, in 16,566 men and 17,426 women.</p

Additional file 3 of Atypical working hours are associated with tobacco, cannabis and alcohol use: longitudinal analyses from the CONSTANCES cohort

Additional file 3: Supplementary Table S3. Baseline characteristics of the employees by indicators of atypical working hours in men between 2012-2017

Additional file 1 of Atypical working hours are associated with tobacco, cannabis and alcohol use: longitudinal analyses from the CONSTANCES cohort

Additional file 1: Supplementary Table S1. The distribution of employees by periods of follow-up

Additional file 6 of Atypical working hours are associated with tobacco, cannabis and alcohol use: longitudinal analyses from the CONSTANCES cohort

Additional file 6: Supplementary Table S6. Baseline characteristics of the employees by indicators of atypical working hours in women between 2012-2017

Additional file 2 of Atypical working hours are associated with tobacco, cannabis and alcohol use: longitudinal analyses from the CONSTANCES cohort

Additional file 2: Supplementary Table S2. The principal component analysis of the qualitative food frequency questionnaire using the Varimax rotation

Additional file 4 of Atypical working hours are associated with tobacco, cannabis and alcohol use: longitudinal analyses from the CONSTANCES cohort

Additional file 4: Supplementary Table S4. Baseline characteristics of the employees by indicators of atypical working hours in women between 2012-2017

Additional file 5 of Atypical working hours are associated with tobacco, cannabis and alcohol use: longitudinal analyses from the CONSTANCES cohort

Additional file 5: Supplementary Table S5. Baseline characteristics of the employees by indicators of atypical working hours in men between 2012-2016

Odds-ratios (95%CI) for probability of depressive symptoms by quartiles of dietary patterns in women of the GAZEL cohort (n = 3132).

<p>Model 1 GEE model without interaction with time, adjusted for age in 1989.</p><p>Model 2 GEE model without interaction with time, adjusted for age in 1989, employment position at 35, professional activity, BMI, marital status, physical activity, tobacco smoking status and alcohol intake at baseline (and before if missing).</p

Conceptual framework of the relationships between CVD risk factors.

<p>The factors are grouped into 4 types based on the number of other factors predicting each of them. The numbers next to the arrows represent the number of prospective associations between or within the 4 types of factors at p<0.05 or p<0.0001 (in parenthesis).</p

Risk of non-moderate alcohol consumption according to predictive factors at baseline.

<p>Risk of non-moderate alcohol consumption according to predictive factors at baseline.</p