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. 2024 Feb 1;23(1):15.
doi: 10.1186/s12940-024-01057-3.

Exposure to residential traffic and trajectories of unhealthy ageing: results from a nationally-representative cohort of older adults

Affiliations

Exposure to residential traffic and trajectories of unhealthy ageing: results from a nationally-representative cohort of older adults

Sergio Gómez Del Río et al. Environ Health. .

Abstract

Background: Traffic exposure has been associated with biomarkers of increased biological ageing, age-related chronic morbidities, and increased respiratory, cardiovascular, and all-cause mortality. Whether it is associated with functional impairments and unhealthy ageing trajectories is unknown.

Methods: Nationally representative population-based cohort with 3,126 community-dwelling individuals aged ≥60 years who contributed 8,291 biannual visits over a 10 year period. Unhealthy ageing was estimated with a deficit accumulation index (DAI) based on the number and severity of 52 health deficits, including 22 objectively-measured impairments in physical and cognitive functioning. Differences in DAI at each follow-up across quintiles of residential traffic density (RTD) at 50 and 100 meters, and closest distance to a petrol station, were estimated using flexible marginal structural models with inverse probability of censoring weights. Models were adjusted for sociodemographic and time-varying lifestyle factors, social deprivation index at the census tract and residential exposure to natural spaces.

Results: At baseline, the mean (SD) age and DAI score of the participants were 69.0 (6.6) years and 17.02 (11.0) %, and 54.0% were women. The median (IQR) RTD at 50 and 100 meters were 77 (31-467) and 509 (182-1802) vehicles/day, and the mean (SD) distance to the nearest petrol station of 962 (1317) meters. The average increase in DAI (95%CI) for participants in quintiles Q2-Q5 (vs Q1) of RTD at 50 meters was of 1.51 (0.50, 2.53), 0.98 (-0.05, 2.01), 2.20 (1.18, 3.21) and 1.98 (0.90, 3.05), respectively. Consistent findings were observed at 100 meters. By domains, most of the deficits accumulated with increased RTD were of a functional nature, although RTD at 50 meters was also associated with worse self-reported health, increased vitality problems and higher incidence of chronic morbidities. Living closer to a petrol station was associated with a higher incidence of functional impairments and chronic morbidities.

Conclusions: Exposure to nearby residential traffic is associated with accelerated trajectories of unhealthy ageing. Diminishing traffic pollution should become a priority intervention for adding healthy years to life in the old age.

Keywords: Traffic pollution, Unhealthy ageing, Frailty.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Differences in health deficits accumulation as a smooth function of residential traffic density (RTD) at 50 and 100 meters and of residential nearest distance to a petrol station or a major road in the Seniors-ENRICA cohort, 2008–2010 to 2017. Curves represent average differences in deficits accumulation index at each follow-up visit (solid lines) and 95% confidence intervals (dashed lines) based on restricted cubic splines for the exposure variables at baseline. The reference values were set at the 10 th percentile of each exposure variable distribution (8.8 vehicles/day, 32.4 vehicles/day, 254.8 meters and 310 meters, respectively). Average differences were obtained from repeated measures regression models adjusted for age, sex, educational level, baseline levels of the deficit accumulation index (DAI), time-varying lifestyles, social deprivation index (SDI) at the census tract, and presence of natural spaces. Models were weighted by the inverse of the conditional probabilities of censoring given residential exposure to traffic variables, individual time-varying confounders, SDI and presence of natural spaces; and accounted for spatial correlation at the census tract and within-participant correlations induced by repeated measures and weighting. Bars represent the histograms of the exposure variables

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