Journal Article

A systematic review including meta-analysis of work environment and depressive symptoms

Träskman Bendz, Lil, Hammarström, Anne, Hogstedt, Christer, Aronsson, Gunnar, Marteinsdottir, Ina, Theorell, Töres, Grape, Tom, Hall, Charlotte, Skoog, Ingmar

2015

Overview

Background Depressive symptoms are potential outcomes of poorly functioning work environments. Such symptoms are frequent and cause considerable suffering for the employees as well as financial loss for the employers. Accordingly good prospective studies of psychosocial working conditions and depressive symptoms are valuable. Scientific reviews of such studies have pointed at methodological difficulties but still established a few job risk factors. Those reviews were published some years ago. There is need for an updated systematic review using the GRADE system. In addition, gender related questions have been insufficiently reviewed. Method Inclusion criteria for the studies published 1990 to June 2013: 1. European and English speaking countries. 2. Quantified results describing the relationship between exposure (psychosocial or physical/chemical) and outcome (standardized questionnaire assessment of depressive symptoms or interview-based clinical depression). 3. Prospective or comparable case-control design with at least 100 participants. 4. Assessments of exposure (working conditions) and outcome at baseline and outcome (depressive symptoms) once again after follow-up 1-5 years later. 5. Adjustment for age and adjustment or stratification for gender. Studies filling inclusion criteria were subjected to assessment of 1.) relevance and 2.) quality using predefined criteria. Systematic review of the evidence was made using the GRADE system. When applicable, meta-analysis of the magnitude of associations was made. Consistency of findings was examined for a number of possible confounders and publication bias was discussed. Results Fifty-nine articles of high or medium high scientific quality were included. Moderately strong evidence (grade three out of four) was found for job strain (high psychological demands and low decision latitude), low decision latitude and bullying having significant impact on development of depressive symptoms. Limited evidence (grade two) was shown for psychological demands, effort reward imbalance, low support, unfavorable social climate, lack of work justice, conflicts, limited skill discretion, job insecurity and long working hours. There was no differential gender effect of adverse job conditions on depressive symptoms Conclusion There is substantial empirical evidence that employees, both men and women, who report lack of decision latitude, job strain and bullying, will experience increasing depressive symptoms over time. These conditions are amenable to organizational interventions.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V
• Subject: Adult / Analysis / Arbetsmedicin och miljömedicin / Biostatistics / Bullying / Clinical Medicine / Comorbidity / Criteria / Depression / Depression - epidemiology / Depression - psychology / Employees / Environmental Health / Epidemiology / Ergonomic / Ergonomics / Female / Folkhälsovetenskap, global hälsa och socialmedicin / Gender / Health aspects / Health Status / Humans / Job Satisfaction / Job stress / Klinisk medicin / Latitude / Male / Medical and Health Sciences / Medicin och hälsovetenskap / Medicine / Medicine & Public Health / Mental depression / Mental health / Meta-analysis / Middle Aged / Occupational Diseases - epidemiology / Occupational Diseases - psychology / Occupational health / Occupational Health and Environmental Health / Prevention / Prospective Studies / Psychiatry / Psychological aspects / Psykiatri / Public Health / Public Health, Global Health and Social Medicine / Research Article / Risk Assessment / Risk factors / Sick leave / Sweden - epidemiology / Systematic review / Toxicology / Vaccine / Work environment / Work stress / Working conditions / Working hours / Workload - psychology / Workplace - psychology / Workplace - statistics & numerical data