Literature DB >> 20081213

Do early life exposures explain associations in mid-adulthood between workplace factors and risk factors for cardiovascular disease?

Claudia Thomas1, Chris Power.   

Abstract

BACKGROUND: Workplace factors (night work, long working hours, psychosocial work stress) have been reported to be associated with increased risk of cardiovascular disease (CVD). We investigated whether (i) workplace factors are associated with CVD risk factors independently of each other, (ii) workplace factors interact, thereby modifying associations and (iii) associations are explained by early life exposures.
METHODS: A total of 7916 employed participants in the 1958 British birth cohort underwent a clinical assessment at age 45 years. Regression analysis was used to examine associations between workplace factors and CVD risk factor levels with adjustment for early life exposures.
RESULTS: Night work was associated with adverse levels of most CVD risk factors. Working > or =48 h/week was positively associated with body mass index (BMI) and waist circumference (WC). Low job control was positively associated with glycosylated haemoglobin (HbA1c) and inflammatory factors, and inversely associated with high-density lipoprotein (HDL)-cholesterol. Low demands were positively associated with systolic blood pressure (SBP), triglycerides and inflammatory factors and inversely associated with HDL-cholesterol. Several associations were weakened when workplace factors were adjusted for each other. Night workers in low-demand jobs had higher BMI [0.78 kg/m(2); 95% confidence interval (CI) 0.35, 1.21], WC (1.49 cm; 0.45, 2.52) and SBP (1.38 mmHg; -0.04, 2.81). HDL was lower for low control plus night work (-0.04 mmol/l; -0.08, -0.01) or long hours (-0.12; -0.18, -0.69). Adjustment for early life exposures explained 30-50% of most associations, e.g. night work/low demands associations reduced by 50% for BMI and WC, and by 39% for SBP.
CONCLUSIONS: Associations between workplace factors and CVD risk factors in mid-adulthood arise in part from social and health disadvantage originating earlier in life.

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Year:  2010        PMID: 20081213     DOI: 10.1093/ije/dyp365

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  6 in total

1.  Individual and work-unit measures of psychological demands and decision latitude and the use of antihypertensive medication.

Authors:  S Daugaard; J H Andersen; M B Grynderup; Z A Stokholm; R Rugulies; Å M Hansen; A Kærgaard; S Mikkelsen; J P Bonde; J F Thomsen; K L Christensen; H A Kolstad
Journal:  Int Arch Occup Environ Health       Date:  2014-07-06       Impact factor: 3.015

2.  Work stress is associated with diabetes and prediabetes: cross-sectional results from the MIPH Industrial Cohort Studies.

Authors:  Jian Li; Marc N Jarczok; Adrian Loerbroks; Ina Schöllgen; Johannes Siegrist; Jos A Bosch; Mark G Wilson; Daniel Mauss; Joachim E Fischer
Journal:  Int J Behav Med       Date:  2013-12

3.  Social adversity in adolescence increases the physiological vulnerability to job strain in adulthood: a prospective population-based study.

Authors:  Hugo Westerlund; Per E Gustafsson; Töres Theorell; Urban Janlert; Anne Hammarström
Journal:  PLoS One       Date:  2012-04-25       Impact factor: 3.240

4.  Job demand and control in mid-life and physical and mental functioning in early old age: do childhood factors explain these associations in a British birth cohort?

Authors:  Mikaela B von Bonsdorff; Rachel Cooper; Diana Kuh
Journal:  BMJ Open       Date:  2014-10-15       Impact factor: 2.692

5.  Proximal and distal determinants of stressful work: framework and analysis of retrospective European data.

Authors:  Morten Wahrendorf; Johannes Siegrist
Journal:  BMC Public Health       Date:  2014-08-15       Impact factor: 3.295

Review 6.  Long working hours and coronary heart disease: a systematic review and meta-analysis.

Authors:  Marianna Virtanen; Katriina Heikkilä; Markus Jokela; Jane E Ferrie; G David Batty; Jussi Vahtera; Mika Kivimäki
Journal:  Am J Epidemiol       Date:  2012-09-05       Impact factor: 4.897

  6 in total

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