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首页> 外文会议>Joint annual meeting of the International Society of Exposure Science and the International Society for Environmental Epidemiology >A Pathway to Diabetes? Associations between Air Pollution Exposure and Biomarkers of Inflammation and Metabolism in Nondiabetic Persons.
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A Pathway to Diabetes? Associations between Air Pollution Exposure and Biomarkers of Inflammation and Metabolism in Nondiabetic Persons.

机译：糖尿病的途径？空气污染暴露与非糖尿病人炎症和代谢生物标志物之间的关联。

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Background: While prior studies have linked air pollution (AP) and diabetes, few studies have examined potential intermediate steps, such as inflammation and altered glucose metabolism, in metabolically healthy persons. Objective: To characterize associations between AP and biomarkers of inflammation and metabolism in nondiabetics. Methods: Biomarker measures (high-sensitivity C-reactive protein [hs-CRP], adiponectin, fibrinogen, interleukin-1 receptor antagonist [IL1-RA]) were collected at baseline (t0; 2000-2003) and first follow-up (t1; 2006-2008) exams from nondiabetic participants of the Heinz Nixdorf Recall (HNR) study. Residential mean exposure to PM10, PM2.5, NO2, and accumulation mode particle number concentration (PNAM) was calculated for time windows (1- to 365-day) prior to exam using a dispersion and chemistry transport model. We fitted covariate-adjusted linear mixed effects models and ran two-pollutant models for PNAM and NO2.Results: We analyzed 6,727 observations (nt0=3,626, ntl=3,101) from 4,052 participants of the HNR study (52% women; age 45-76 years at tO). Interquartile range (IQR) increases in 365-day mean exposure to PM10, PM2.5, and PNAM were associated with higher hs-CRP levels (e.g., PM2.5: 6.6% [95% CI: 2.8,10.7] per IQR increase). Short-term exposure to all pollutants was positively associated with IL1-RA (e.g., 1-day PM10: 1.5% [0.6, 2.5] per IQR increase), with associations also seen for medium- and long-term exposures. Medium-term exposures (60- to 120-day) were negatively associated with adiponectin (e.g., 91-day PNAM: -2.2% [-3.3, -3.3] per IQR increase). No clear pattern was seen for fibrinogen. Associations for PNAM and NO2 were robust to co-pollutant adjustment. Conclusion: In nondiabetics, we observed differing temporal patterns of association between AP and biomarkers of inflammation and metabolism, indicating that several exposure windows may be relevant for evaluating potential mediators of the link between AP and diabetes.
机译：背景：尽管先前的研究已经将空气污染（AP）与糖尿病联系在一起，但是很少有研究检查了代谢健康人群的潜在中间步骤，例如炎症和葡萄糖代谢改变。目的：鉴定非糖尿病患者中AP与炎症和代谢生物标志物之间的关联。方法：在基线（t0； 2000-2003年）和首次随访（t0）时收集生物标记物（高敏C反应蛋白[hs-CRP]，脂联素，纤维蛋白原，白介素1受体拮抗剂[IL1-RA]）。 ； t1； 2006-2008）来自亨氏Nixdorf召回（HNR）研究的非糖尿病参与者的考试。使用分散和化学迁移模型，在检查前的时间窗（1到365天）中，计算了PM10，PM2.5，NO2和累积模式颗粒数浓度（PNAM）的居住平均暴露时间。我们拟合了协变量调整的线性混合效应模型，并针对PNAM和NO2运行了两种污染物模型。结果：我们分析了HNR研究的4,052名参与者（52％女性; 45岁至45岁）的6,727项观察值（nt0 = 3,626，ntl = 3,101）。至今已有76年的历史。） 365天平均暴露于PM10，PM2.5和PNAM的四分位数间距（IQR）增加与较高的hs-CRP水平相关（例如，每次IQR升高，PM2.5：6.6％[95％CI：2.8,10.7] ）。短期暴露于所有污染物与IL1-RA呈正相关（例如，每1 IQR增加1天PM10：1.5％[0.6，2.5]），中长期暴露也有相关性。中期暴露（60-120天）与脂联素呈负相关（例如，每IQR升高91天PNAM：-2.2％[-3.3，-3.3]）。纤维蛋白原未观察到清晰的图案。 PNAM和NO2的关联对共污染物调整很有效。结论：在非糖尿病患者中，我们观察到了AP与炎症和代谢生物标志物之间关联的时间模式不同，这表明几个暴露窗口可能与评估AP与糖尿病之间联系的潜在介质有关。

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