Dataset Information

Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study.

ABSTRACT:

Background

Long-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.

Methods

Multimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)_2.5, PM_coarse, PM₁₀, and nitrogen dioxide (NO₂) concentrations (μg/m³-modeled to residential address) and multimorbidity status at the baseline assessment (2006-2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.

Results

Higher exposures to PM_2.5, and NO₂ were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM_2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO₂: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM_2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO₂: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM_2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO₂: adjOR = 1.26 (95% CI = 1.15, 1.38)].

Conclusions

This cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations.

SUBMITTER: Ronaldson A

PROVIDER: S-EPMC9755180 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study.

Ronaldson Amy A Arias de la Torre Jorge J Ashworth Mark M Hansell Anna L AL Hotopf Matthew M Mudway Ian I Stewart Rob R Dregan Alex A Bakolis Ioannis I

Frontiers in public health 20221202

<h4>Background</h4>Long-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.<h4>Methods</h4>Multimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sect ...[more]

PMID: 36530697

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Dataset Information

Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study.

Background

Methods

Results

Conclusions

Publications

Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study.

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