Bi-directional relation between effort‒reward imbalance and risk of neck-shoulder pain: assessment of mediation through depressive symptoms using occupational longitudinal data

Abstract

Objectives Bi-directional associations between perceived effort‒reward imbalance (ERI) at work and neck-shoulder pain have been reported. There is also evidence of associations between ERI and depressive symptoms, and between depressive symptoms and pain while the links between ERI, depressive symptoms and pain have not been tested. We aimed to assess whether depressive symptoms mediate the association between ERI and neck-shoulder pain, as well as the association between neck-shoulder pain and ERI. Methods We used prospective data from three consecutive surveys of the Swedish Longitudinal Occupational Survey of Health (SLOSH) study. ERI was assessed with a short version of the ERI questionnaire, and pain was defined as having had neck-shoulder pain that affected daily life during the past three months. Depressive symptoms were assessed with a continuous scale based on six-items of the (Hopkins) Symptom Checklist. Counterfactual mediation analyses were applied using exposure measures from 2010/2012 (T1), depressive symptoms from 2012/2014 (T2), and outcomes from 2014/2016 (T3), and including only those free of outcome at T1 and T2 (N=2876‒3239). Results ERI was associated with a higher risk of neck-shoulder pain [risk ratio (RR) for total effect 1.24, 95% confidence interval (CI) 1.02-1.50] and 40% of this total effect was mediated through depressive symptoms. Corresponding RR for association between neck-shoulder pain and ERI was 1.36 (95% CI 1.13-1.65), but the mediating role of depressive symptoms was less consistent. Conclusions Depressive symptoms appear to be an intermediate factor in the relationship between ERI and neck-shoulder pain.

Socioeconomic inequalities in health behaviors: exploring mediation pathways through material conditions and time orientation

“…The sensitivity analysis controlling for baseline material conditions (see Additional file 6 ) showed that accounting for the short-term influence of educational level on material conditions did not alter its association with material conditions 7 years later (in 2011). While this study may not have captured the influence of material conditions on the outcomes in the very short term, the fact that mediating effects were observed after the three-year gap between the measurement of material conditions and the outcomes strengthens the plausibility of the investigated pathways [ 54 ]. For these reasons, the bias introduced by the time gaps between educational level, the mediators, and the outcomes is expected to be limited and to be outweighed by the ability to draw conclusions about the investigated pathways based on correct temporal ordering of the variables.…”

Working conditions and health behavior as causes of educational inequalities in self-rated health: an inverse odds weighting approach

“…Self-rated health at baseline, country, age, sex, cohabitation and wave dummies were included as covariates. Finally, a measure of the ''proportion mediated'' (PM) on the risk ratio (RR) scale was calculated using the equation provided by VanderWeele (37,38).…”

Workplace Psychosocial Factors and Their Association With Musculoskeletal Disorders: A Systematic Review of Longitudinal Studies

“…The other reasons for exclusion are reported within the PRISMA flow diagram (Figure 1). Following the fulltext screening, a total of 47 articles were included in the study, as shown in Figure 1 (Andersen et al, 2019;Bodin et al, 2018;Bovenzi, 2009Bovenzi, , 2015Bovenzi et al, 2015Bovenzi et al, , 2016Christensen et al, 2018;Christensen & Knardahl, 2010Clausen et al, 2013;Dragioti et al, 2019;Garg et al, 2012Garg et al, , 2014Gerr et al, 2014;Halonen et al, 2018Halonen et al, , 2019Harris et al, 2011;Herin et al, 2012Herin et al, , 2014Hooftman et al, 2009;Hush et al, 2009;Janssens et al, 2014;Jun et al, 2020;Kaaria et al, 2011;Lamy et al, 2014;Lapointe et al, 2009Lapointe et al, , 2013Larsman et al, 2011;Larsman & Hanse, 2009a, 2009Lu et al, 2014;Madsen et al, 2018; Magnusson Hanson et al, 2017;Matsudaira et al, 2012;Mierswa & Kellmann, 2017;Oakman et al, 2017;Plouvier et al, 2009;Prakash et al, 2017;…”

“…The other reasons for exclusion are reported within the PRISMA flow diagram (Figure 1). Following the full-text screening, a total of 47 articles were included in the study, as shown in Figure 1 (Andersen et al, 2019; Bodin et al, 2018; Bovenzi, 2009, 2015; Bovenzi et al, 2015, 2016; Christensen et al, 2018; Christensen & Knardahl, 2010, 2014; Clausen et al, 2013; Dragioti et al, 2019; Garg et al, 2012, 2014; Gerr et al, 2014; Halonen et al, 2018, 2019; Harris et al, 2011; Herin et al, 2012, 2014; Hooftman et al, 2009; Hush et al, 2009; Janssens et al, 2014; Jun et al, 2020; Kaaria et al, 2011; Lamy et al, 2014; Lapointe et al, 2009, 2013; Larsman et al, 2011; Larsman & Hanse, 2009a, 2009; Lu et al, 2014; Madsen et al, 2018; Magnusson Hanson et al, 2017; Matsudaira et al, 2012; Mierswa & Kellmann, 2017; Neupane & Nygard, 2017; Oakman et al, 2017; Plouvier et al, 2009; Prakash et al, 2017; Shahidi et al, 2015; Smith et al, 2009; Solidaki et al, 2013; Vandergrift et al, 2012; Van Nieuwenhuyse et al, 2013; Vargas-Prada et al, 2013, 2016; Wigaeus Tornqvist et al, 2009). Most studies were conducted in Europe ( n = 34, 72%), followed by the Americas ( n = 10, 21%) and Asia/Australia ( n = 3, 7%).…”