Background: The 'physical activity paradox' advocates that leisure physical activity (PA) promotes health while high occupational PA impairs health. However, this paradox can be explained by methodological limitations of the previous studies-self-reported PA measures, insufficient adjustment for socioeconomic confounding or not addressing the compositional nature of PA. Therefore, this study investigated if we still observe the PA paradox in relation to long-term sick absence (LTSA) after adjusting for the abovementioned limitations. Methods: Time spent on moderate-to-vigorous physical activity (MVPA) and remaining physical behaviors (sedentary behavior, standing, light PA and time in bed) at work and in leisure was measured for 929 workers using thigh accelerometry and expressed as isometric log-ratios (ilrs). LTSA was register-based first event of ≥6 consecutive weeks of sickness absence during 4-year follow-up. The association between ilrs and LTSA was analyzed using a Cox proportional hazards model adjusted for remaining physical behaviors and potential confounders, then separately adjusting for and stratifying by education and type of work. Results: During the follow-up, 21% of the workers experienced LTSA. In leisure, more relative MVPA time was negatively associated with LTSA (20% lower risk with 20 min more MVPA, p = 0.02). At work, more relative MVPA time was positively associated with LTSA (15% higher risk with 20 min more MVPA, p = 0.02). Results remained unchanged when further adjusted for or stratified by education and type of work. Conclusion: These findings provide further support to the 'PA paradox'.

ObjectivesThe study aimed to determine the extent to which latent trajectories of neck–shoulder pain (NSP) are associated with self-reported sick leave and work ability based on frequent repeated measures over 1 year in an occupational population.MethodsThis longitudinal study included 748 Danish workers (blue-collar, n=620; white collar, n=128). A questionnaire was administered to collect data on personal and occupational factors at baseline. Text messages were used for repeated measurements of NSP intensity (scale 0–10) over 1 year (14 waves in total). Simultaneously, self-reported sick leave (days/month) due to pain was assessed at 4-week intervals, while work ability (scale 0–10) was assessed using a single item (work ability index) at 12-week intervals over the year. Trajectories of NSP, distinguished by latent class growth analysis, were used as predictors of sick leave and work ability in generalised estimation equations with multiple adjustments.ResultsSick leave increased and work ability decreased across all NSP trajectory classes (low, moderate, strong fluctuating and severe persistent pain intensity). In the adjusted model, the estimated number of days on sick leave was 1.5 days/month for severe persistent NSP compared with 0.1 days/month for low NSP (relative risk=13.8, 95% CI 6.7 to 28.5). Similarly, work ability decreased markedly for severe persistent NSP (OR=12.9, 95% CI 8.5 to 19.7; median 7.1) compared with low NSP (median 9.5).ConclusionSevere persistent NSP was associated with sick leave and poor work ability over 1 year among workers. Preventive strategies aiming at reducing severe persistent NSP among working populations are needed.

Background Various physical work demands are shown to be associated with sickness absence. However, these studies have: (a) predominantly used self-reported data on physical work demands that have been shown to be inaccurate compared with technical measurements, (b) principally focused on various physical work demands in ‘isolation’, i.e. ignoring their co-dependency – compositional nature –, and (c) mainly used register data on long-term sickness absence. The present article describes the protocol of a study with the objective of investigating the association between technically measured compositional data on physical work demands and prospective long- and short-term register-based data on sickness absence. Methods ‘The technically measured compositional Physical wOrk DEmands and prospective association with register-based Sickness Absence study (PODESA)’ comprises data from two Danish cohorts (NOMAD and DPhacto) primarily on blue-collar workers. In the PODESA cohort, data on 1108 workers were collected at baseline (between 2011 and 2014). The cohort data comprise, e.g., self-reported information on descriptives, lifestyle, workday, and health, as well as accelerometer-based measurements of physical work demands (physical activity, movements, and postures). These baseline measurements are linked with prospective register-based data on sickness absence for up to four years after baseline. The prospective association between physical work demands and sickness absence will be analysed using a Compositional Data Analysis approach. Discussion PODESA provides a unique possibility of unravelling which combinations of physical work demands are associated with prospective sickness absence. PODESA employs technically measured information on physical work demands (taking into account the compositionality of physical work demand data) and prospective sickness absence data. The findings from PODESA can be used to develop strengthened preventive interventions for sickness absence. Results are expected in 2019–2021.

In this paper, we investigate the influence of self-reported health and register-based prescription medicine purchases on re-employment chances, and whether these health indicators measure similar aspects of health in this analysis. Data came from a 2006 Danish unemployment survey among a random sample of unemployed individuals enriched with register data (2006–2008, N=1806). The survey participants all received unemployment benefits from the welfare system and had been unemployed for more than 20 weeks at the time of the interview in 2006. We combined these data with longitudinal register data on individual prescription medicine purchases for somatic illnesses and prescription medicine purchases for mental illnesses, information on re-employment and various socio-demographic variables. We conducted binary logistic regression analyses to investigate the impact of self-reported health and prescription medicine purchases measured in 2006 on re-employment chances in 2007 and 2008. Our analyses show that unemployed workers with poor self-reported health and workers who had prescription medicine purchases for mental illnesses were less likely to be re-employed in 2007 and 2008. Furthermore, the impact of both prescription medicine purchases for somatic illnesses and for mental illnesses increased when adding self-reported health to the model although prescription purchases for somatic illnesses became statistically insignificant. The impact of prescription medicine purchases for somatic illnesses was mediated by self-reported health, whilst prescription medicine purchases for mental illnesses was only partly mediated. Finally, SRH seemed a much stronger prediction than prescription medicines. From these results, we propose, when possible, the inclusion of both an indicator of self-reported health and an indicator of mental health in studies on re-employment.