Summary
<h3>Background</h3> Musculoskeletal pain (MSP) at multiple anatomical sites differs from single site pain both in its risk factors and prognosis. Multisite MSP is more likely to cause sickness absence from work, but knowledge about its effect on health-related job loss (HRJL) is limited. To explore this association we analysed longitudinal data from participants aged 50–64 recruited to the Health and Employment After Fifty (HEAF) study. <h3>Method</h3> Baseline information collected by postal questionnaire from 4333 employed participants included questions about MSP in the past year at three anatomical sites (spine, upper, and lower limb). Subsequent HRJL was ascertained through a follow-up questionnaire after one year. Associations between multisite MSP (pain at ≥2 anatomical sites) and HRJL were explored using Poisson regression with robust variance and summarised by prevalence rate ratios (PRRs). <h3>Results</h3> Among 437 participants with multisite MSP at baseline, 7% left their job due to ill health, compared to 3% in 547 with single-site pain and 2% in 3349 without MSP. After accounting for potential confounders, the risk of HRJL was higher among those with multisite MSP than in those with single-site MSP (fully-adjusted PRRs 1.9 (95%CI 1.1–3.2) and 1.6 (95%CI 0.9–2.7) compared with no MSP). The population attributable fraction for single-site pain was 7%, while that of multi-site pain was 15%. <h3>Conclusions</h3> This analysis suggests that multisite MSP carries a higher risk of HRJL than single-site pain. To develop future preventive strategies, efforts should focus on understanding the drivers of multisite MSP rather than concentrating on site-specific risk factors.
Outcomes reported
Referenced by PLOS supermarket placement trial as citation 50; likely supports topic area: methods / modelling / statistics. Topics: methods / modelling / statistics Evidence type: Research article / other Source report: PLOS supermarket placement trial Ref#: PLOS supermarket placement trial #50 Original: Ntani G. Statistical approaches to the analysis of hierarchical data using simulations and real data from a study of musculoskeletal symptoms. University of Southampton; 2017.
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