Reasons why osteoarthritis predicts mortality: path analysis within a Cox proportional hazards model.

To identify potentially modifiable factors that mediate the association between symptomatic osteoarthritis (OA) and premature mortality. A population-based prospective cohort study; primary care medical record data were linked to self-report information collected by questionnaire in adults aged 50 years and over (n=10 415). OA was defined by primary care consultation and moderate-to-severe pain interference in daily life. A Cox proportional hazards analysis determined the total effect (TE) of OA on mortality after adjustment for potential confounders. Within the Cox model, path analysis was used to decompose the TE to assess the indirect and direct effects for selected potential mediators (anxiety, depression, unrefreshed sleep and walking frequency). Results are expressed as HRs with 95% CIs derived from bootstrap resampling. OA was significantly associated with mortality (TE-adjusted HR 1.14; 95% CI 1.00 to 1.29). The indirect effects for walking frequency were 1.05 (95% CI 1.04 to 1.06), depression 1.02 (95% CI 1.02 to 1.03), anxiety 1.01 (95% CI 1.00 to 1.02) and unrefreshed sleep 1.01 (95% CI 1.00 to 1.01). The analysis indicates that encouraging people to walk and 'get out and about' in addition to targeting OA could be protective against excessive mortality. The findings also suggest that depression, anxiety and unrefreshed sleep have a role in premature mortality for people with OA; however, this has low clinical significance. © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Citation

Ross Wilkie, Simran Singh Parmar, Milica Blagojevic-Bucknall, Diane Smith, Martin J Thomas, Bethany Jane Seale, Gemma Mansell, George Peat. Reasons why osteoarthritis predicts mortality: path analysis within a Cox proportional hazards model. RMD open. 2019;5(2):e001048

Mesh Tags

PMID: 31798954

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