Centre for Implementation Science, Health Service and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United Kingdom.
CIBER Epidemiology and Public Health (CIBERESP), Madrid, Spain.
Front Public Health. 2022 Dec 2;10:1035415. doi: 10.3389/fpubh.2022.1035415. eCollection 2022.
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.
Multimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM), PM, PM, and nitrogen dioxide (NO) concentrations (μg/m-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; = 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.
Higher exposures to PM, and NO 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: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO: 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: adjOR = 1.31 (95% CI = 1.14, 1.51); NO: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM: adjOR = 1.24 (95% CI = 1.16, 1.33); NO: adjOR = 1.26 (95% CI = 1.15, 1.38)].
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.
已知长期暴露于空气污染浓度与多种非传染性疾病密切相关，但在英国，其在多种疾病中的作用尚未得到研究。我们旨在使用英国生物库队列评估长期空气污染暴露与多种疾病状态、严重程度和模式之间的关联。
多种疾病状态是基于 41 种身体和精神状况计算得出的。我们评估了每年模型化的颗粒物（PM）、PM、PM 和二氧化氮（NO）浓度（μg/m-模型到居住地址）与 364144 人（平均年龄：52.2±8.1 岁，52.6%为女性）在基线评估（2006-2010 年）中的多种疾病状态之间的横断面关联。将空气污染物分为四分位数，以评估剂量反应关联。在患有多种疾病（≥2 种疾病；n=156395）的人群中，我们评估了空气污染暴露水平与多种疾病严重程度和多种疾病模式之间的关联，这些模式是使用探索性因素分析确定的。使用调整了社会人口统计学、行为和环境指标的广义线性模型来探索关联。
较高的 PM 和 NO 暴露与多种疾病状态呈剂量依赖性相关。当我们将最高空气污染四分位数（四分位数 4：Q4）与最低四分位数（Q1）进行比较时，这些关联最强[PM：调整后的优势比（adjOR）=1.21（95%置信区间[CI]=1.18,1.24）；NO：adjOR=1.19（95%CI=1.16,1.23）]。我们还观察到空气污染暴露与多种疾病严重程度评分之间的剂量反应关联。我们确定了 11 种多种疾病模式。空气污染与多种疾病模式有关，最强的关联（Q4 与 Q1 相比）见于神经疾病（中风、癫痫、酒精/物质依赖）[PM：adjOR=1.31（95%CI=1.14,1.51）；NO：adjOR=1.33（95%CI=1.11,1.60）]和呼吸疾病（COPD、哮喘）[PM：adjOR=1.24（95%CI=1.16,1.33）；NO：adjOR=1.26（95%CI=1.15,1.38）]。
这项横断面研究提供的证据表明，暴露于空气污染可能与患有多种器官疾病有关。需要进行纵向研究来进一步探索这些关联。
