How does employment affect cardiovascular risk? A life-course approach in the 1958 cohort

1. How does employment affect cardiovascular risk? A life-course approach in the 1958 cohort Claudia Thomas MRC Centre of Epidemiology for Child Health (Formerly: Centre for Paediatric Epidemiology & Biostatistics) UCL Institute of Child Health

2. Mid-Career fellowship • Start date: August 2007 • Duration: 2 years • Supervisor: • Professor Chris Power (ICH) • Collaborators: • Professor Heather Joshi, Centre for Longitudinal Studies, Institute of Education, London • Professor Stephen Stansfeld, Queen Mary’s School of Medicine and Dentistry, London • Professor Clyde Hertzman, University of British Columbia, Vancouver.

3. Aim To understand the role of labour market participation as a process that leads to social inequalities in cardiovascular disease. Objectives • To study the direct relationships between employment characteristics and adult cardiovascular risk markers. • To study the indirect pathways: diet, physical activity, weight gain. • Take into account social processes occurring earlier in life, such as education, that determine how individuals arrive in their occupational destinations. • Understand how the more complex patterns of labour market participation experienced by women, such as, the combined roles of work and motherhood, are related to cardiovascular disease.

4. Data • 1958 British birth cohort (National Child Development Study) • Biomedical survey at age 45y (funded by MRC) • Objective and standardised measures of biological risk factors for CVD (e.g. BP, adiposity, lipids, blood glucose, cortisol, inflammatory factors) • Life course measures: • Employment variables • Growth and weight gain • Health behaviours • Early life social processes

5. Employment and health • Unemployment long known to be related to mortality and psychological distress • Structure and organisation of paid employment also has adverse consequences for various health outcomes: • Lack of job security associated with poor self-reported health, chronic disease and psychological distress (Whitehall II) • Shift work linked to poor sleep and gastrointestinal problems • For CVD, associations found for psycho-social characteristics of work (job strain/effort reward imbalance) • Less is known about other work characteristics: • working at night or long hours - associated with CHD, diabetes and risk factors for CVD such as BMI • methodological problems: shift work definitions, selected populations, cross-sectional

6. How do adverse employment experiences increase the risk of CVD? Potential mechanisms • Health behaviours – smoking, poor diet, physical inactivity, alcoholism • Psychosocial stress - neuro-endocrine effects that adversely influence glucose and lipid metabolism (allostatic load) • Insufficient recovery – affects metabolic processes and hormone excretion. Sleep debt related to long working hours/shift work. Poor sleep associated with CVD risk and diabetes • Not mutually exclusive, e.g. • Smoke because of work hours or stress associated with work hours • Poor sleep due to shift work or due to stress associated with shift work

7. Why do adverse employment experiences increase the risk of CVD? Pre-employment factors Selection into employment “destinations” on basis of pre-existing risk for CVD earlier in life • Physical development (e.g. childhood overweight/obesity) • Cognitive/educational development (e.g. early uptake of smoking) • Socio-emotional factors (e.g. more resilient overcome adversity) Socio-economic background SEP underpins occupation, health behaviours and risk for CVD Different implications of working long hours: professional choice versus economic necessity.

8. Shift work and risk factors for CVD: new evidence from the 1958 British birth cohort To establish whether: • different types of shift work are associated with risk factors for cardiovascular disease (CVD) in mid-life (ii) associations are mediated through health behaviours

9. Outcome measures: biological risk factors for CVD at 45y Increases in: • body mass index (BMI) • waist circumference (WC) • blood pressure (systolic and diastolic) • triglycerides • total cholesterol • glycosylated haemoglobin (HbA1c) • fibrinogen • C-reactive protein (CRP) Decrease in: • high density lipoprotein (HDL) cholesterol

10. Exposures Shift work at 42y: participants reported frequency of working: • nights (10pm to 4am) • early mornings (4am to 7am) • evenings (6pm to 10pm) • weekends (Saturday or Sunday) Each type of shift work coded as: • no shift work • not this type • less often than once a month • at least once a month • at least once a week” “Any shift work” was defined as any regular employment (≥once/week) outside the hours of 7am to 6pm

11. Confounding factors • Sex (interactions examined) • Socioeconomic position (Registrar General’s SC) • Full or part time employment • Employee or self-employed Mediators Health behaviours at 42y: • Smoking (4 categories: ex-smoker to >=20 cigarettes/day) • Diet (frequency of eating fruit and veg, chips, fried food) • Physical activity (frequency of leisure activity) • Alcohol consumption (5 categories: never to most days)

12. Statistical analysis Multiple linear regression – series of models • Regression of outcome on frequency of each shift work type (dose-response relationship) • Quadratic term used to test linearity of shift work frequency variables • Adjustment for confounders (sex, full/part time, employee/self-employed) • Gender interactions – likelihood ratio statistic (LR) • Adjustment for mediators

13. Sample at 45y • 9377 participants (78% of eligible sample) • Representative of original birth population in respect of childhood social class, physical factors and key adult characteristics. • Slight under-representation from more extreme social groups (e.g. no male head of house) For this analysis: • 9085 had data on employment status at 42y; 7839 (86%) were in paid employment. • 5 were missing shift work information • Numbers with data on the outcomes varied from 7813 for BMI to 6466 for fibrinogen • No bias introduced by complete case analysis

15. Results • Early morning work most strongly associated with risk factors for CVD • Findings mainly for men • Not explained by health behaviours

16. Regression coefficients (95%CI) for early morning work and risk factors for CVD - MEN † log transformed

17. Other findings For men: • Night work associations were weaker than early morning work • BMI was higher for each type of shift work • Other than BMI, few findings for evening or weekend work For women: • Only findings were higher triglycerides for early morning and night work

18. Conclusions • Early morning work was most commonly associated with risk factors for CVD in men. • Not explained by health behaviours (although associated with smoking and poor diet) • Alternative explanations • Better measurement, e.g. cumulative measures of shift work and changes in health behaviours over adult life • Circadian disruption of metabolic processes • Other mediators “hows”: stress and sleep debt • Pre-employment factors “whys”: pre-existing risk for CVD (e.g. ↑ BMI)

19. Progress and plans 2008