Development and validation of a prediction model for long-term sickness absence based on occupational health survey variables

Recognition During the Return-to-Work Process in Workers with Common Mental Disorders

Purpose Considering worker's perspective, the purpose of this study was twofold: (1) to document the meaning of the experience of recognition in the return to work (RTW) process of work after a sick leave due to a common mental disorder (CMD) and (2) to investigate the phenomenon of recognition for workers in the process of RTW after a sick leave due to a CMD, by evaluating the presence or absence of marks of recognition from salient RTW stakeholders stemming from different systems. Methods The Relational Caring Inquiry phenomenological method was used to explore the meaning of recognition during the return-to-work process and marks of recognition in a group of 20 workers who returned to their employment after a sick leave due to a CMD. In depth individual interviews were conducted with each participant. Results The definition of recognition that emerged from workers experiencing the RTW process is related to the behaviours and attitudes of various stakeholders, stemming from the work, health, insurance and social systems that allow them to feel appreciated, valued and respected, throughout the RTW process. Recognition was most often described as showing support, trust, respect for recovery and pace, and providing positive feedback. Conclusion The findings from this study could serve as guidelines in organizations regarding the RTW process, and in particular clarifying the roles and actions that different stakeholders could take in the workplace to stimulate expressions of meaningful recognition.

Workplace Factors Associated With Return to Work After Mild-to-Moderate Traumatic Brain Injury

OBJECTIVE

Sociodemographic and injury-related predictors for return to work (RTW) after mild-to-moderate traumatic brain injury (TBI) have been extensively explored. However, there is a knowledge gap regarding work-related predictors of RTW. The main aim of this study was to explore work-related predictors of work participation 6 and 12 months after mild-to-moderate TBI.

SETTING

Data were collected at baseline 8 to 12 weeks after injury, and 3, 6, and 12 months after baseline, at a specialized TBI rehabilitation outpatient clinic at Oslo University Hospital, Oslo, Norway.

PARTICIPANTS

Eligible patients had suffered a mild-to-moderate TBI 8 to 12 weeks previously, were employed 50% or more at time of injury, were between 18 and 60 years of age, and sick listed 50% or more at time of inclusion due to symptoms of TBI (based on the Rivermead Post-Concussion Symptoms Questionnaire). In total, 116 patients were included in a randomized controlled trial, of whom 113 were included in the 1-year analysis.

DESIGN

Patients were originally included in a randomized controlled trial. There were no between-group differences in RTW after 1 year. Thus, the participants were evaluated as one cohort in this study.

MAIN MEASURES

The primary outcome measure was work participation 1 year after study inclusion. Work-related predictors were chosen on the basis of previous research and expert opinion and entered into a multivariable linear regression model. The model controlled for sociodemographic and injury-related factors.

RESULTS

The best-fitting model explained 25% of variation in work participation at 1 year. Significant predictors were predictability, quantitative demands and rewards (recognition) at the workplace, private or public employment, symptom burden at baseline, and sex.

CONCLUSION

In this study, several work-related predictors outperformed some of the established sociodemographic and injury-related predictors of RTW after TBI, thus stressing the need for further focus and research on amendable predictors of RTW after mild-to-moderate TBI.

Sickness absence and disability pension among women with breast cancer: a population-based cohort study from Sweden

BACKGROUND

Women's return to work after diagnosis of breast cancer (BC) is becoming more prevalent. However, register-based national investigation on sickness absence (SA) and disability pension (DP) in BC women is lacking. The aim of the study was to explore SA and DP before and after a first BC diagnosis and the possibility to predict new cancer-related SA by using disease-related and sociodemographic factors.

METHODS

A longitudinal register study of the 3536 women in Sweden aged 19-64 with a first BC diagnosis in 2010 was conducted by linkage of five nationwide registers. Particularly, detailed information on SA and DP was obtained from the National Social Insurance Agency. Descriptive statistics on SA and DP 2 years before through 3 years after the BC diagnosis were performed. The risk of having a new SA spell due to BC or BC-related diagnoses was modeled using logistic regression.

RESULTS

The proportion of women with SA increased during the year following the BC diagnosis date and declined over the next 2 years to proportions before diagnosis. At the time of BC diagnosis, half of the women began a new SA spell > 14 days with cancer, cancer-related, or mental diagnosis. Disease-related and sociodemographic factors including occupational sector, living area, age, cancer stage, educational level, and number of previous SA days showed statistical significance (p < 0.05) in predicting a new SA around BC diagnosis. By using these factors, it was possible to correctly predict 67% of the new SA spell.

CONCLUSIONS

SA among women with BC was elevated mainly in the first year after diagnosis. New SA following BC diagnosis can accurately be predicted.

Strategy for finding occupational health survey participants at risk of long-term sickness absence

BACKGROUND

When resources are limited, occupational health survey participants are usually invited to consultations based on an occupational health provider's subjective considerations. This study aimed to find health survey participants at risk of long-term (i.e., ≥ 42 consecutive days) sickness absence (LTSA) for consultations with occupational health providers (OHPs).

METHODS

The data of 64 011 non-sicklisted participants in occupational health surveys between 2010 and 2015 were used for the study. In a random sample of 40 000 participants, 27 survey variables were included in decision tree analysis (DTA) predicting LTSA at 1-year follow-up. The decision tree was transferred into a strategy to find participants for OHP consultations, which was then tested in the remaining 24 011 participants.

RESULTS

In the development sample, 1358 (3.4%) participants had LTSA at 1-year follow-up. DTA produced a decision tree with work ability as first splitting variable; company size and sleep problems were the other splitting variables. A strategy differentiating by company size would find 75% of the LTSA cases in small (≤99 workers) companies and 43% of the LTSA cases in medium-sized (100-499 workers) companies. For large companies (≥500 workers), case-finding was only 25%.

CONCLUSIONS

In small and medium-sized companies, work ability and sleep problems can be used to find occupational health survey participants for OHP consultations aimed at preventing LTSA. Research is needed to further develop a case-finding strategy for large companies.

Self-Reported Variables as Determinants of Upper Limb Musculoskeletal Symptoms in Assembly Line Workers

BACKGROUND

Assembly lines work is frequently associated to work-related upper limb musculoskeletal disorders. The related disability and absenteeism make it important to implement efficient health surveillance systems. The main objective of this study was to identify self-reported variables that can determine work-related upper limb musculoskeletal symptoms-discomfort/pain-during a 6-month follow-up.

METHODS

This was a prospective study with a 6-month follow-up period, performed in an assembly line. Upper limb musculoskeletal discomfort/pain was assessed through the presence of self-reported symptoms. Uni- and multivariate logistic regression analyses were used to evaluate which self-reported variables were associated to upper limb symptoms after 6 months at the present and to upper limbs symptoms in the past month.

RESULTS

Of the 200 workers at baseline, 145 replied to the survey after 6 months. For both outcomes, "having upper limb symptoms during the previous 6 months" and "education" were possible predictors.

CONCLUSION

Our results suggest that having previous upper limb symptoms was related to its maintenance after 6 months, sustaining it as a specific determinant. It can be a hypothesis that this population had mainly workers with chronic symptoms, although our results give only limited support to self-reported indicators as determinants for upper limb symptoms. Nevertheless, the development of an efficient health surveillance system for high demanding jobs should implicate self-reported indicators, but also clinical and work conditions assessment should be accounted on the future.

Physical and psychosocial work factors as explanations for social inequalities in self-rated health

OBJECTIVE

We investigated the contribution of physical and psychosocial work factors to social inequalities in self-rated health (SRH) in a sample of Danish 40 and 50 years old occupationally active women and men.

METHODS

In this longitudinal study, the study population consisted of 3338 Danish women and men. Data were collected by postal questionnaires in 2000 (baseline) and 2006 (follow-up). The independent variable, socioeconomic position (SEP), was assessed by the highest achieved educational level at baseline. We conducted gender-stratified parallel multiple mediation analyses. In the mediation analyses, SEP was categorised as SEP I, II, III, VI and V among men. Among women, SEP was dichotomised into SEP I-IV and V. The outcome, SRH, was assessed at baseline and follow-up. A wide range of physical and psychosocial work factors were included as potential mediators.

RESULTS

We found a social gradient in SRH across all levels of SEP among men. Among women, we only found a poorer SRH among those with the lowest SEP. Mediation analyses showed that work factors together accounted for 56% of the social inequalities in SRH among men and 44% among women. In both genders, ergonomic exposures and job insecurity seemed to play the major role for social inequalities in SRH. For women only, we also found noise to contribute to the social inequalities in SRH.

CONCLUSION

Physical and psychosocial work factors partially explained social inequalities in SRH among both genders. Improvement of the working environment can potentially contribute to the reduction of social inequalities in health.

Work-relatedness of the presented health problem and sickness absence

BACKGROUND

Perception by workers of their health problems as work-related is possibly associated with sickness absence (SA). The aim of this study was to to study the relationship between perceived work-relatedness of health problems and SA among workers who visit their GP, taking the influence of other potential determinants into account and to study the influence of these determinants on SA. Design and setting prospective cohort study in 32 Dutch GP practices.

METHODS

A secondary analysis of RCT data among workers, aged 18-63 years, who visited their GP. We measured self-reported SA days in 12 months and high SA (>20 days in 12 months) and compared workers who perceived work-relatedness (WR+) with workers who did not (WR-). With multivariable linear and logistic regression models, we analyzed the influence of age, gender, experienced health, chronic illness, prior SA, number of GP consultations and perceived work ability.

RESULTS

We analyzed data of 209 workers, 31% perceived work-relatedness. Geometric mean of SA days was 1.6 (95% CI: 0.9-3.0) for WR+- workers and 1.2 (95% CI: 0.8-1.8) for WR- workers (P = 0.42). Incidence of high SA was 21.5 and 13.3%, respectively (odds ratio 1.79; 95% CI: 0.84-3.84). SA was positively associated with chronic illness, prior SA, low perceived work ability and age over 50.

CONCLUSIONS

Perceived work-relatedness was not associated with SA. SA was associated with chronic illness, prior SA, low perceived work ability and age over 50.

Associations between work environment, health status and sick leave among pregnant employees

Aims: To study the associations between and timing of psychosocial and physical work factors and health status on sick leave among Danish pregnant employees. Methods: A total of 910 pregnant women completed a questionnaire in gestational weeks 12 (baseline) and 27 (follow-up). Information about psychosocial and physical work factors and health status was obtained at baseline. Associations with sick leave ⩾14 days were estimated using logistic regression. Further, the impact of timing and duration of exposure on sick leave were examined. Results: A total of 133 women (14.6%) reported ⩾14 days of sick leave at follow-up (27 weeks of gestation). Work-related risk factors for sick leave were high work pace, low influence, low recognition, low job satisfaction, conflict in work−family balance, standing/walking, heavy lifting, and shift work/night shift. Health-related risk factors were burnout, stress, possibility of depression, low work ability, previous sick leave, and poor self-rated health. Being exposed to work-related risk factors during the first 27 weeks of pregnancy or at follow-up increased the risk of sick leave compared with those not exposed at any time or only exposed at baseline. Poor health status increased the risk if women were exposed in the first 27 weeks of pregnancy; however, high possibility of depression was also a risk factor when experienced in early pregnancy. Conclusions: Psychosocial and physical work-related risk factors and poor health status were associated with more sick leave in pregnant employees. Early adjustment of work-related risk factors at the workplace is needed to reduce sick leave.

Long-term sickness absence in a working population: development and validation of a risk prediction model in a large Dutch prospective cohort

BACKGROUND

Societal expenditures on work-disability benefits is high in most Western countries. As a precursor of long-term work restrictions, long-term sickness absence (LTSA) is under continuous attention of policy makers. Different healthcare professionals can play a role in identification of persons at risk of LTSA but are not well trained. A risk prediction model can support risk stratification to initiate preventative interventions. Unfortunately, current models lack generalizability or do not include a comprehensive set of potential predictors for LTSA. This study is set out to develop and validate a multivariable risk prediction model for LTSA in the coming year in a working population aged 45-64 years.

METHODS

Data from 11,221 working persons included in the prospective Study on Transitions in Employment, Ability and Motivation (STREAM) conducted in the Netherlands were used to develop a multivariable risk prediction model for LTSA lasting ≥28 accumulated working days in the coming year. Missing data were imputed using multiple imputation. A full statistical model including 27 pre-selected predictors was reduced to a practical model using backward stepwise elimination in a logistic regression analysis across all imputed datasets. Predictive performance of the final model was evaluated using the Area Under the Curve (AUC), calibration plots and the Hosmer-Lemeshow (H&L) test. External validation was performed in a second cohort of 5604 newly recruited working persons.

RESULTS

Eleven variables in the final model predicted LTSA: older age, female gender, lower level of education, poor self-rated physical health, low weekly physical activity, high self-rated physical job load, knowledge and skills not matching the job, high number of major life events in the previous year, poor self-rated work ability, high number of sickness absence days in the previous year and being self-employed. The model showed good discrimination (AUC 0.76 (interquartile range 0.75-0.76)) and good calibration in the external validation cohort (H&L test: p = 0.41).

CONCLUSIONS

This multivariable risk prediction model distinguishes well between older workers with high- and low-risk for LTSA in the coming year. Being easy to administer, it can support healthcare professionals in determining which persons should be targeted for tailored preventative interventions.

Predicting the duration of sickness absence spells due to back pain: a population-based study from Sweden

Objectives

We aimed to develop and validate a prediction model for the duration of sickness absence (SA) spells due to back pain (International Statistical Classification of Diseases and Related Health Problems 10th Revision: M54), using Swedish nationwide register microdata.

Methods

Information on all new SA spells >14 days from 1 January 2010 to 30 June 2012 and on possible predictors were obtained. The duration of SA was predicted by using piecewise constant hazard models. Nine predictors were selected for the final model based on a priori decision and log-likelihood loss. The final model was estimated in a random sample of 70% of the SA spells and later validated in the remaining 30%.

Results

Overall, 64 048 SA spells due to back pain were identified during the 2.5 years; 74% lasted ≤90 days, and 9% >365 days. The predictors included in the final model were age, sex, geographical region, employment status, multimorbidity, SA extent at the start of the spell, initiation of SA spell in primary healthcare and number of SA days and specialised outpatient healthcare visits from the preceding year. The overall c-statistic (0.547, 95% CI 0.542 to 0.552) suggested a low discriminatory capacity at the individual level. The c-statistic was 0.643 (95% CI 0.634 to 0.652) to predict >90 days spells, 0.686 (95% CI 0.676 to 0.697) to predict >180 spells and 0.753 (95% CI 0.740 to 0.766) to predict >365 days spells.

Conclusions

The model discriminates SA spells >365 days from shorter SA spells with good discriminatory accuracy.

Perceived and content-related emotional demands at work and risk of long-term sickness absence in the Danish workforce: a cohort study of 26 410 Danish employees

Objectives

This study aimed to examine whether high emotional demands at work predict long-term sickness absence (LTSA) in the Danish workforce and whether associations differ by perceived and content-related emotional demands.

Methods

We included 26 410 individuals from the Work Environment and Health in Denmark Study, a nationwide sample of the Danish workforce. Emotional demands at work were measured with two items: one assessing perceived emotional demands (asking how often respondents were emotionally affected by work) and one assessing content-related emotional demands (frequency of contact with individuals in difficult situations). LTSA was register based and defined as spells of ≥6 weeks. Respondents with LTSA during 2 years before baseline were excluded. Follow-up was 52 weeks. Using Cox regression, we estimated risk of LTSA per one-unit increase in emotional demands rated on a five-point scale.

Results

During 22 466 person-years, we identified 1002 LTSA cases. Both perceived (HR 1.20, 95% CI 1.12 to 1.28) and content-related emotional demands (HR 1.07, 95% CI 1.01 to 1.13) predicted risk of LTSA after adjustment for confounders. Further adjustment for baseline depressive symptoms substantially attenuated associations for perceived (HR 1.08, 95% CI 1.01 to 1.16) but not content-related emotional demands (HR 1.05, 95% CI 1.00 to 1.11). Individuals working in occupations with above-average values of both exposures had an increased risk of LTSA (HR 1.32, 95% CI 1.14 to 1.52) compared with individuals in all other job groups.

Conclusions

Perceived and content-related emotional demands at work predicted LTSA, also after adjustment for baseline depressive symptoms, supporting the interpretation that high emotional demands may be hazardous to employee’s health.

Development of Prediction Models for Sick Leave Due to Musculoskeletal Disorders

Purpose The aim of this study was to develop prediction models to determine the risk of sick leave due to musculoskeletal disorders (MSD) in non-sick listed employees and to compare models for short-term (i.e., 3 months) and long-term (i.e., 12 months) predictions. Methods Cohort study including 49,158 Dutch employees who participated in occupational health checks between 2009 and 2015 and sick leave data recorded during 12 months follow-up. Prediction models for MSD sick leave within 3 and 12 months after the health check were developed with logistic regression analysis using routinely assessed health check variables. The performance of the prediction models was evaluated with explained variance (Nagelkerke's R-square), calibration (Hosmer-Lemeshow test) and discrimination (area under the receiver operating characteristic curve, AUC) measures. Results A total of 376 (0.8%) and 1193 (2.4%) employees had MSD sick leave within 3 and 12 months after the health check. The prediction models included similar predictor variables (educational level, musculoskeletal complaints, distress, supervisor social support, work-home interference, intrinsic motivation, development opportunities, and work pace). The explained variances were 7.6% and 8.8% for the model with 3 and 12 months follow-up, respectively. Both prediction models showed adequate calibration and discriminated between employees with and without MSD sick leave 3 months (AUC = 0.761; Interquartile range [IQR] 0.759-0.763) and 12 months (AUC = 0.740; IQR 0.738-0.741) after the health check. Conclusion The prediction models could be used to determine the risk of MSD sick leave in non-sick listed employees and invite them to preventive consultations with occupational health providers.

A prediction model for duration of sickness absence due to stress-related disorders

BACKGROUND

Stress-related disorders are leading causes of long-term sickness absence (SA) and there is a great need for decision support tools to identify patients with a high risk for long-term SA due to them.

AIMS

To develop a clinically implementable prediction model for the duration of SA due to stress-related disorders.

METHODS

All new SA spells with F43 diagnosis code lasting >14 days and initiated between 2010-01-01 and 2012-06-30 were identified through data from the Social Insurance Agency. Information on baseline predictors was linked on individual level from other nationwide registers. Piecewise-constant hazard regression was used to predict the duration of the SA. Split-sample validation was used to develop and validate the model, and c-statistics and calibration plots to evaluate it.

RESULTS

Overall 83,443 SA spells, belonging to 77,173 individuals were identified. The median SA duration was 55 days (10% were >365 days). Age, sex, geographical region, employment status, educational level, extent of SA at start and SA days, outpatient healthcare visits, and multi-morbidity in the preceding 365 days were selected to the final model. The model was well calibrated. The overall c-statistics was 0.54 (95% confidence intervals: 0.53-0.54) and 0.70 (95% confidence intervals: 0.69-0.71) for predicting SA spells >365 days.

LIMITATIONS

The heterogeneity of the F43-diagnosis and the exclusive use of register-based predictors limited our possibility to increase the discriminatory accuracy of the prediction.

CONCLUSION

The final model could be implementable in clinical settings to predict duration of SA due to stress-related disorders and could satisfyingly discriminate long-term SA.

Quickscan assesses risk factors of long-term sickness absence: A cross-sectional (factorial) construct validation study

Objectives

The number of sick-listed employees has increased dramatically worldwide. Therefore, many countries aim to stimulate early and sustainable return to work opportunities to obtain better health outcomes and lower costs for disability pensions. To effectively orientate resources to patients with a high risk of not resuming work spontaneously, it is necessary to screen patients early in their sickness absence process. In this study, we validate “Quickscan”, a new instrument to assess return-to-work needs and to predict risks of long-term sick leave.

Methods

As part of the Quickscan validation process, we tested and compared the reliability and construct validity of the questionnaire in two different populations. First, we conducted a cross-sectional study in which the screening instrument was sent to sick-listed individuals in healthcare insurance. In a second cross-sectional study, sick-listed workers who consulted the occupational health physician for return-to-work assessment were asked to fill out the questionnaire. We compared both samples for descriptive statistics: frequencies, means and standard deviations. Reliability of the scales was calculated using Cronbach’s alpha. Confirmatory factor analysis was performed to evaluate the construct (factorial) validity of the studied scales using software package AMOS 24.

Results

The screening tool was shown to be an instrument with reliable scales (except for the perfectionism and health perception patient scale) in both populations. The construct validity was satisfactory: we found that the hypothesized measurement models with the theoretical factors fitted the data well in both populations. In the first sample, the model improved for scales concerning stressful life events and showed worse fit for person-related factors. Work-related factors and functioning factors both showed similar fit indices across samples. We found small differences in descriptive statistics, which we could explain by the differences in characteristics of both populations.

Conclusions

We can conclude that the instrument has considerable potential to function as a screening tool for disability management and follow-up of sick-leave, provided that some adaptations and validation tests are executed.

Predicting long-term sickness absence among employees with frequent sickness absence

PURPOSE

Frequent absentees are at risk of long-term sickness absence (SA). The aim of the study is to develop prediction models for long-term SA among frequent absentees.

METHODS

Data were obtained from 53,833 workers who participated in occupational health surveys in the period 2010-2013; 4204 of them were frequent absentees (i.e., employees with ≥ 3 SA spells in the year prior to the survey). The survey data of the frequent absentees were used to develop two prediction models: model 1 including job demands and job resources and model 2 including burnout and work engagement. Discrimination between frequent absentees with and without long-term SA during follow-up was assessed with the area under the receiver operating characteristic curve (AUC); (AUC) ≥ 0.75 was considered useful for practice.

RESULTS

A total of 3563 employees had complete data for analyses and 685 (19%) of them had long-term SA during 1-year follow-up. The final model 1 included age, gender, education, marital status, prior long-term SA, work pace, role clarity and learning opportunities. Discrimination between frequent absentees with and without long-term SA was significant (AUC 0.623; 95% CI 0.601-0.646), but not useful for practice. Model 2 showed comparable discrimination (AUC 0.624; 95% CI 0.596-0.651) with age, gender, education, marital status, prior long-term SA, burnout and work engagement as predictor variables. Differentiating by gender or sickness absence cause did not result in better discrimination.

CONCLUSIONS

Both prediction models discriminated significantly between frequent absentees with and without long-term SA during 1-year follow-up, but have to be further developed for use in healthcare practice.

Development and validation of a risk prediction model for work disability: multicohort study

Work disability affects quality of life, earnings, and opportunities to contribute to society. Work characteristics, lifestyle and sociodemographic factors have been associated with the risk of work disability, but few multifactorial algorithms exist to identify individuals at risk of future work disability. We developed and validated a parsimonious multifactorial score for the prediction of work disability using individual-level data from 65,775 public-sector employees (development cohort) and 13,527 employed adults from a general population sample (validation cohort), both linked to records of work disability. Candidate predictors for work disability included sociodemographic (3 items), health status and lifestyle (38 items), and work-related (43 items) variables. A parsimonious model, explaining > 99% of the variance of the full model, comprised 8 predictors: age, self-rated health, number of sickness absences in previous year, socioeconomic position, chronic illnesses, sleep problems, body mass index, and smoking. Discriminative ability of a score including these predictors was high: C-index 0.84 in the development and 0.83 in the validation cohort. The corresponding C-indices for a score constructed from work-related predictors (age, sex, socioeconomic position, job strain) were 0.79 and 0.78, respectively. It is possible to identify reliably individuals at high risk of work disability by using a rapidly-administered prediction score.

Relationships between work-related factors and musculoskeletal health with current and future work ability among male workers

PURPOSE

The purpose was to increase job-specific knowledge about individual and work-related factors and their relationship with current and future work ability (WA). We studied cross-sectional relationships between mental demands, physical exertion during work, grip strength, musculoskeletal pain in the upper extremities and WA and the relationships between these variables and WA 11 years later.

METHODS

We used a dataset of a prospective cohort study (1997-2008) among employees of an engineering plant (n = 157). The cohort was surveyed by means of tests and written questions on work demands, musculoskeletal health, WA score (WAS; 0-10), and mental and physical WA. Spearman correlation coefficients and logistic regression analysis were used.

RESULTS

Among manual workers, we found weak correlations between grip strength and current and future physical WA. We did not find predictors for future poor WA among the manual workers. Among the office workers, we found that musculoskeletal pain was moderately and negatively related to current WAS and physical WA. More handgrip strength related to better future WAS and physical WA. Musculoskeletal pain (OR 1.67 p < 0.01) and lower handgrip strength (OR 0.91 p < 0.05) predicted future poor WA among office workers.

CONCLUSIONS

Our results showed cross-sectional and longitudinal relationships between musculoskeletal health and work ability depending on occupation. However, the present implies that predicting work ability in the far future based on health surveillance data is rather difficult. Testing the musculoskeletal system (grip strength) and asking workers' about their musculoskeletal health seems relevant when monitoring work ability.