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Association of long-term ambient exposure to air pollution with frailty progression and mortality: A multi-state cohort prospective study
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DOI：10.1007/s11869-026-02045-x.png)
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Abstract
En 中文
In an aging society, frailty represents a dynamic senile syndrome. Previous studies have linked air pollutants such as nitrogen oxides (NOx), nitrogen dioxide (NO2), particulate matter 2.5 (PM2.5), and particulate matter 10 (PM10) to frailty. However, the relationship between air pollution, frailty progression, and all-cause mortality remains inadequately elucidated. This prospective cohort study utilized the UK Biobank data from three waves (2006–2010, 2012–2013, 2019). Frailty was defined by five phenotypes, classifying participants as non-frail, pre-frail, or frail. Death was ascertained up to January 2022. Exposure to air pollutants—PM2.5 (≤ 2.5 μm), PM10 (≤ 10 μm), nitrogen dioxide (NO2), and nitrogen oxide (NOx)—was estimated using land-use regression models. A Discrete-time Markov multi-state model was employed to analyze transitions between non-frail, pre-frail, frail, and death. Among 27,710 participants with a mean age of 59 ± 7.7 years, during a mean follow-up of 3.45 years, a total of 32,265 status transitions were observed. Multivariable-status results showed that the HRs (95%CI) for the transition from non-frail to death were 1.06 (1.01, 1.12) for NO2, 1.05 (1.00, 1.11) for NOx, 1.07 (1.02, 1.13) for PM2.5, and 1.06 (1.01, 1.12) for PM10, respectively. For the transition from pre-frail to death, the HR (95% CI) were 1.13 (1.08, 1.19) for NO2, 1.12 (1.07, 1.17) for NOx, 1.08 (1.03, 1.13) for PM2.5, and 1.11 (1.06, 1.16) for PM10. In addition, for the air pollution score, HR (95%CI) for the transitions from non-frail to death and from pre-frail to death were 1.07 (1.02, 1.13) and 1.13 (1.08, 1.19), respectively. This study confirms that air pollution is a key variable associated with an increased risk of mortality in individuals without frailty or those in the pre-frail state.
Keywords:
Air pollution
Frailty
Mortality
Multi-state markov model
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