ISGlobal, Universitat Pompeu Fabra, CIBER Epidemiología y Salud Pública, Barcelona, Spain.
Department of Civil and Environmental Engineering, University of Washington, WA, USA.
Environ Int. 2019 Oct;131:105033. doi: 10.1016/j.envint.2019.105033. Epub 2019 Jul 31.
Limited evidence exists on the effect of particulate air pollution on blood glucose levels. We evaluated the associations of residential and personal levels of fine particulate matter (PM) and black carbon (BC) with blood glucose and diabetic status among residents of 28 peri-urban villages in South India.
We used cross-sectional data from 5065 adults (≥18 years, 54% men) included in the Andhra Pradesh Children and Parents Study. Fasting plasma glucose was measured once in 2010-2012 and prevalent prediabetes and diabetes were defined following the American Diabetes Association criteria. We estimated annual ambient PM and BC levels at residence using land-use regression models and annual personal exposure to PM and BC using prediction models based on direct measurements from a subsample of 402 participants. We used linear and logistic nested mixed-effect models to assess the association between exposure metrics and health outcomes. For personal exposures, we stratified analyses by sex.
Mean (SD) residential PM and BC were 32.9 (2.6) μg/m and 2.5 (2.6) μg/m, respectively; personal exposures to PM and BC were 54.5 (11.5) μg/m and 5.8 (2.5) μg/m, respectively. Average (SD) fasting blood glucose was 5.3 (1.3) mmol/l, 16% of participants had prediabetes, and 5.5% had diabetes. Residential PM and BC were not associated with higher blood glucose levels. Personal PM (20 μg/m increase) and BC (1 μg/m increase) were negatively associated with blood glucose levels in women (PM: -1.93, 95%CI: -3.12, -0.73; BC: -0.63, 95%CI: -0.90, -0.37). In men, associations were negative for personal PM (-1.99, 95%CI: -3.56, -0.39) and positive for personal BC (0.49, 95%CI: -0.44, 1.43). We observed no evidence of associations between any exposure and prevalence of prediabetes/diabetes.
Our results do not provide evidence that residential exposures to PM or BC are associated with blood glucose or prevalence of prediabetes/diabetes in this population. Associations with personal exposure may have been affected by unmeasured confounding, highlighting a challenge in using personal exposure estimates in air pollution epidemiology. These associations should be further examined in longitudinal studies.
关于颗粒物空气污染对血糖水平影响的证据有限。我们评估了居住环境和个人细颗粒物（PM）和黑碳（BC）水平与印度南部 28 个近郊区村庄居民的血糖和糖尿病状况之间的关联。
我们使用了 2010-2012 年期间参加安得拉邦儿童和父母研究的 5065 名成年人（≥18 岁，54%为男性）的横断面数据。空腹血浆葡萄糖在一次测量中进行测量，并根据美国糖尿病协会的标准定义了糖尿病前期和糖尿病的患病率。我们使用基于 402 名参与者的子样本的直接测量值的预测模型，估算了居住处的年度环境 PM 和 BC 水平，并使用预测模型估算了个人 PM 和 BC 的年度暴露量。我们使用线性和逻辑嵌套混合效应模型评估暴露指标与健康结果之间的关系。对于个人暴露，我们根据性别对分析进行了分层。
住宅 PM 和 BC 的平均（SD）浓度分别为 32.9（2.6）μg/m 和 2.5（2.6）μg/m，个人 PM 和 BC 的暴露量分别为 54.5（11.5）μg/m 和 5.8（2.5）μg/m。平均（SD）空腹血糖为 5.3（1.3）mmol/L，16%的参与者患有糖尿病前期，5.5%的参与者患有糖尿病。住宅 PM 和 BC 与较高的血糖水平无关。女性的个人 PM（增加 20μg/m）和 BC（增加 1μg/m）与血糖水平呈负相关（PM：-1.93，95%CI：-3.12，-0.73；BC：-0.63，95%CI：-0.90，-0.37）。在男性中，个人 PM（-1.99，95%CI：-3.56，-0.39）和个人 BC（0.49，95%CI：-0.44，1.43）与血糖水平呈负相关。我们没有发现任何暴露与糖尿病前期/糖尿病患病率之间存在关联的证据。
我们的结果并未提供证据表明该人群住宅暴露于 PM 或 BC 与血糖或糖尿病前期/糖尿病的患病率有关。与个人暴露有关的关联可能受到未测量混杂因素的影响，突出了在空气污染流行病学中使用个人暴露估计值所面临的挑战。应在纵向研究中进一步研究这些关联。
