BACKGROUND
As employees age, their physical and mental abilities decline and work ability (WA) decreases, enhancing the risk for long-term sick leave or even premature retirement. However, the relative impact of biological and environmental determinants on WA with increasing age is still poorly understood in their complexity.
OBJECTIVE
Previous research has shown relationships between work ability (WA) and job and individual resources, as well as specific demographic and lifestyle-related variables. However, other potentially important predictors of WA, such as personality traits, biological determinants such as cardiovascular, metabolic, immunological, cognitive abilities or psychosocial factors remain unexplored. Here, a wide range of factors was systematically evaluated to extract most crucial predictors of low and high WA across the working lifespan.
METHODS
As part of the Dortmund Vital Study https://www.researchprotocols.org/2022/3/e32352, 494 participants from different occupational sectors aged between 20 and 69 years completed the Work Ability Index (WAI) assessing employee’s mental and physical resources. Thirty sociodemographic variables were grouped in four categories (social relationships, nutrition and stimulants, education and lifestyle, and work-related), and eighty biological and environmental variables were grouped in eight domains (anthropometric, cardiovascular, metabolic, immunological, personality, cognitive, stress-related, quality of life) to be related to the WAI.
RESULTS
The analyses extracted important sociodemographic factors influencing WA such as education, social activities or sleep quality and showed age-dependent and age-independent determinants of WA. Regression models explained up to 52% of the WAI variance. Negative predictors of WA were chronological and immunological age, low immunological efficiency (CD4/CD8-ratio), high BMI, neuroticism, psychosocial stress, emotional exhaustion, demands from work, daily cognitive failures, subclinical depression, and burnout symptoms. Positive predictors were maximum heart rate during ergometry, blood pressure, hemoglobin and monocyte concentration, weekly physical activity, commitment to the company, pressure to succeed and good quality of life.
CONCLUSIONS
The identified biological and environmental risk factors allow to evaluate WA in its complexity. Policymakers, employers, and occupational safety and health personnel should consider the here identified modifiable risk factors to promote healthy aging at work through focused physical, dietary, cognitive, and stress-reduced preventive programs, in addition to well-balanced working conditions. This may also increase quality of life, commitment to the job and motivation to succeed which are important factors to maintain or even enhance WA in the aging workforce and to prevent premature retirement.
CLINICALTRIAL
Clinicaltrials.gov NCT05155397; https://clinicaltrials.gov/ct2/show/NCT05155397
INTERNATIONAL REGISTERED REPORT
RR2-10.2196/32352