Psychosocial factors at work and sickness absence in the Gazel cohort: a prospective study.

Abstract

Objective-To test whether psychosocial factors at work are predictors of rates of sickness absence. Methods-The study population consisted of middle aged men and women employed by the French national electricity and gas company (EDF-GDF) in various occupations and followed up since 1989 by annual self administered questionnaires and independent data obtained from the medical and personnel departments of EDF-GDF. The 1995 questionnaire provided information about three psychosocial work factors: psychological demands, decision latitude, and social support at work. Sickness absence data were provided by the company's social security department. The occurrence of spells and days of absence in the 12 months after completion of the 1995 questionnaire was studied. Potential confounding variables were age, smoking, alcohol, and marital status, assessed in the 1995 questionnaire, and educational level and occupation, assessed from data provided by the personnel department. This study was restricted to the 12 555 subjects of the initial cohort who were still working and answered the self administered questionnaire in 1995. Results-Low levels of decision latitude were associated with more frequent and longer sickness absences among men and women. Low levels of social support at work increased the numbers of spells and days of absence among men only. These associations weakened after adjustment for potential confounding factors, but remained significant. Conclusion-The study indicates that psychosocial factors at work, especially decision latitude, are predictive of sickness absence. (Occup Environ Med 1998;55:735-741) Keywords: absenteeism; workplace; psychosocial factors at work; social support at work; follow up studies Sickness absence is thought to have a multifactorial aetiology, in which illness and injury may be two of many causes. In the literature, several of the factors have proved to be associated with sickness absence, including societal conditions (social insurance and security, economic fluctuations, etc), conditions specific to a given workplace or organisation (policy towards the personnel, size, and type of industry), occupational conditions-such as physical, chemical, and psychosocial stressors, seniority, educational level, and occupation-and social and demographic characteristics-that is, sex, age, marital status, number of children, social network, commuting distance to work, smoking habits, type of personality, and health.

An Accident-Risk Assessment Study of Temporary Piece Rated Workers.

“…A variety of factors have been found to be responsible for occupational accidents, either directly or indirectly. Work conditions 5) , age [6][7][8][9] , educational status, safety training 10) , experience 11) , smoking 12,13) , alcohol [14][15][16][17] , psychosocial factors 18) , shift of work 19) and weather 20) have all been designated as responsible factors. Some authors have also shown that the type of worker (temporary or permanent) 21) and speed of work 22) are also important factors in the causation of occupational accidents.…”

Intervention Study on Psychosocial Work Factors and Mental Health and Musculoskeletal Outcomes

“…Musculoskeletal disorders, including arthritis, constitute the most common chronic condition (Lawrence et al 1998) and one of the leading causes of activity limitations (National Center for Health Statistics 2007). Musculoskeletal disorders and mental health problems have reached alarming prevalence and constitute the two main motives of work absence for a certified medical condition, causing considerable loss of productivity for employers (Bourbonnais et al 2005;Karttunen 1995;Niedhammer et al 1998;Vézina et al 2006;Vinet 2004).…”

Recommendations for individual participant data meta-analyses on work stressors and health outcomes: comments on IPD-Work Consortium papers

“…The Consortium developed an approach for creating comparable job strain groups between the two questionnaires as part of the harmonization process of job strain measures across the 17 cohort data in the following way: (i) they dropped three job control items from some of their cohort data [eg, data from the Belstress (33) and GAZEL (34) studies] in which job control had been assessed with the standard nine JCQ control items in order to make the same number of items for job control as in the DCQ; (ii) they then used simple summation-based scale formulas rather than standard JCQ scale formulas for job control and job demands; and (iii) they defined high job strain based on the medians of the job control and job demands scores. This Consortium approach has been assumed by the Consortium to be free of major errors in their meta-analyses (17,18,(35)(36)(37).…”