Pain as a predictor of incident arthritis: a 7-year prospective cohort study from the China Health and Retirement Longitudinal Study (CHARLS)
Year: 2026
Type: article
Study design: Observational Study
Abstract: While pain is conventionally viewed as a consequence of arthritis, its role as a predictor of the disease in arthritis-free individuals remains unclear. We examined the association between pre-existing pain and 7-year incident arthritis in a nationally representative cohort. We analyzed 7-year prospective data from the China Health and Retirement Longitudinal Study (CHARLS, 2011–2018). A total of 10,364 arthritis-free participants aged ≥ 45 years were included in this study, selected from 16,881 adults evaluated at the 2011 baseline. Baseline pain was assessed via self-report and categorized by pain presence and multisite burden (0, 1–2, 3–4, ≥ 5 sites). Pain dynamics (persistent, incident, resolved) were defined using 2011–2013 data. The primary outcome was physician-diagnosed arthritis by 2018. Multivariable Cox proportional hazards models were applied for analysis. Baseline pain was independently associated with increased arthritis risk over 7 years (HR = 1.81, 95% CI 1.65–1.97). A clear dose–response relationship was observed: compared with no pain, risk increased progressively with greater multisite burden, reaching HR = 2.52 (95% CI 2.22–2.86) for ≥ 5 painful sites. Participants classified as having resolved pain also had a higher risk of subsequent arthritis diagnosis (HR = 1.81, 95% CI 1.61–2.04). Associations remained robust in sensitivity analyses incorporating a 2-year lag to reduce reverse causation. Pre-existing pain, including multi-site and resolved pain, is a strong independent predictor of incident arthritis. These findings demonstrate a prospective association between pain history and subsequent arthritis diagnosis. Therefore, historical pain reports are critical indicators for early arthritis risk screening.
Source: BMC Public Health
Institution: Wenzhou Medical University
Language: English
Subfield: Pharmacology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,290
OpenAlex ID: W7221755028
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