Background The role of long-term exposure to a comprehensive panel of particulate matter (PM) size fractions and extreme weather events in the development of incident arthritis remains underexplored. We aimed to evaluate their independent, combined, and interactive effects on arthritis risk in a Chinese middle-aged and older population. Methods This prospective study utilized data from two nationally representative cohorts: The China Health and Retirement Longitudinal Study and the China Family Panel Studies. A total of 13,147 participants aged ≥ 45 years without baseline arthritis were included. Annual exposures to PM1, PM2.5, PM1−2.5, PM10, PM2.5−10, and extreme weather events (low/high-temperature days, extreme rainfall/drought days, and a composite Climate Physical Risk Index [CPRI]) were estimated using high-resolution datasets. Incident arthritis was identified via self-reported physician diagnosis. Time-updated Cox proportional hazards models were used to assess associations. Weighted quantile sum (WQS) regression evaluated the mixture effect, and additive interaction models quantified synergies between PM and extreme weather. Restricted cubic spline (RCS) and threshold effect analysis were utilized to evaluate potential nonlinear associations. Results Over a median follow-up, 1,200 incident arthritis cases occurred. Each 1 µg/m³ increase in PM1, PM2.5, PM1−2.5, and PM10, was associated with hazard ratios (HRs) of 1.061 (95% CI: 1.030–1.093), 1.022 (95% CI: 1.011–1.033), 1.023 (95% CI: 1.009–1.037), and 1.004 (95% CI: 1.001–1.006), respectively. Additionally, each 1-day increase in extreme low-temperature day (LTD) was linked to HRs of 1.042 (95% CI: 1.019–1.065). The WQS mixture index yielded an HR of 1.719 (95% CI: 1.379–2.143), with PM2.5−10 contributing the largest weight (38.8%), followed by PM1−2.5 (34.7%) and LTD (25.4%). Dose-response curves revealed accelerating nonlinear relationships for PM1, PM2.5−10, LTD, extreme rainfall days (ERD), extreme drought days (EDD) and CPRI. In exploratory threshold analyses, above 40.862 µg/m³ for PM₁, the HR per 1 µg/m³ was 1.193 (95% CI: 1.131–1.259); for LTD above 17.624 days, the HR per additional day was 1.173 (95% CI: 1.147–1.199). For PM2.5₋₁₀, the threshold was 18.692 µg/m³, with a strong association below (HR = 3.276, 95% CI: 2.338–4.590) and a marginal one above (HR = 1.005, 95% CI: 1.000–1.009). Significant additive interactions were observed between LTD and both PM10 (Synergy Index [S] = 2.129, 95% CI: 1.393–2.865) and PM2.5 (S = 1.867, 95% CI: 1.208–2.526). The association between PM and arthritis was modified by smoking and geographic region. Conclusions Long-term exposure to ambient PM (across multiple size fractions) and extreme low-temperature weather are independent and synergistic risk factors for incident arthritis in middle-aged and older Chinese adults. Public health strategies targeting arthritis prevention should adopt an integrated approach addressing both air quality and climate resilience.

Synergistic effects of ambient particulate matter and extreme weather events on arthritis risk: a prospective cohort study

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2026年5月29日

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Yongbin Wang,
Weihang Liu,
Yongsheng Liao,
Ruiting Zhao,
Chunjie Xu,
Fei Lin

摘要

Background

The role of long-term exposure to a comprehensive panel of particulate matter (PM) size fractions and extreme weather events in the development of incident arthritis remains underexplored. We aimed to evaluate their independent, combined, and interactive effects on arthritis risk in a Chinese middle-aged and older population.

Methods

This prospective study utilized data from two nationally representative cohorts: The China Health and Retirement Longitudinal Study and the China Family Panel Studies. A total of 13,147 participants aged ≥ 45 years without baseline arthritis were included. Annual exposures to PM₁, PM_2.5, PM_1−2.5, PM₁₀, PM_2.5−10, and extreme weather events (low/high-temperature days, extreme rainfall/drought days, and a composite Climate Physical Risk Index [CPRI]) were estimated using high-resolution datasets. Incident arthritis was identified via self-reported physician diagnosis. Time-updated Cox proportional hazards models were used to assess associations. Weighted quantile sum (WQS) regression evaluated the mixture effect, and additive interaction models quantified synergies between PM and extreme weather. Restricted cubic spline (RCS) and threshold effect analysis were utilized to evaluate potential nonlinear associations.

Results

Over a median follow-up, 1,200 incident arthritis cases occurred. Each 1 µg/m³ increase in PM₁, PM_2.5, PM_1−2.5, and PM₁₀, was associated with hazard ratios (HRs) of 1.061 (95% CI: 1.030–1.093), 1.022 (95% CI: 1.011–1.033), 1.023 (95% CI: 1.009–1.037), and 1.004 (95% CI: 1.001–1.006), respectively. Additionally, each 1-day increase in extreme low-temperature day (LTD) was linked to HRs of 1.042 (95% CI: 1.019–1.065). The WQS mixture index yielded an HR of 1.719 (95% CI: 1.379–2.143), with PM_2.5−10 contributing the largest weight (38.8%), followed by PM_1−2.5 (34.7%) and LTD (25.4%). Dose-response curves revealed accelerating nonlinear relationships for PM₁, PM_2.5−10, LTD, extreme rainfall days (ERD), extreme drought days (EDD) and CPRI. In exploratory threshold analyses, above 40.862 µg/m³ for PM₁, the HR per 1 µg/m³ was 1.193 (95% CI: 1.131–1.259); for LTD above 17.624 days, the HR per additional day was 1.173 (95% CI: 1.147–1.199). For PM_2.5₋₁₀, the threshold was 18.692 µg/m³, with a strong association below (HR = 3.276, 95% CI: 2.338–4.590) and a marginal one above (HR = 1.005, 95% CI: 1.000–1.009). Significant additive interactions were observed between LTD and both PM₁₀ (Synergy Index [S] = 2.129, 95% CI: 1.393–2.865) and PM_2.5 (S = 1.867, 95% CI: 1.208–2.526). The association between PM and arthritis was modified by smoking and geographic region.

Conclusions

Long-term exposure to ambient PM (across multiple size fractions) and extreme low-temperature weather are independent and synergistic risk factors for incident arthritis in middle-aged and older Chinese adults. Public health strategies targeting arthritis prevention should adopt an integrated approach addressing both air quality and climate resilience.