Characterizing exposure to household air pollution within the Prospective Urban Rural Epidemiology (PURE) study.
Characterizing exposure to household air pollution within the Prospective Urban Rural Epidemiology (PURE) study.
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DOI：
10.1016/j.envint.2018.02.033
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发表时间：
2018-05
影响因子：
11.8
通讯作者：
Brauer M
中科院分区：
文献类型：
--
作者：
Arku RE;Birch A;Shupler M;Yusuf S;Hystad P;Brauer M
固体燃料燃烧造成的家庭空气污染 (HAP) 是造成低收入和中等收入国家（LIC 和 MIC）疾病负担的重要因素。然而，目前的 HAP 心血管疾病负担估计是基于综合暴露反应曲线，目前尚未通过 LIC 和 MIC 的定量 HAP 研究提供信息。虽然有足够的证据支持 HAP 与呼吸系统疾病之间的因果关系，但缺乏专门研究 HAP 暴露定量测量与心血管疾病之间关系的大型队列研究。我们的目标是改进基于燃料类型的暴露代理，并通过定量测量不同地理位置和社会经济环境中不同烹饪燃料类型和条件的暴露来减少暴露错误分类。我们利用技术进步，在大型 (N~250,000) 多国 (N~26) 前瞻性城乡流行病学 [PURE] 队列研究中估算家庭和个人 PM2.5（空气动力学直径低于 2.5 微米的颗粒）暴露情况。在这里，我们详细介绍了研究方案和用于表征 HAP 暴露的创新方法及其在流行病学分析中的应用。本研究描述了 10 个 PURE 国家（孟加拉国、巴西、智利、中国、哥伦比亚、印度、巴基斯坦、南非、坦桑尼亚和津巴布韦）的农村社区参与者的 HAP PM2.5 暴露情况，这些国家的基线固体燃料使用量超过 10%。 PM2.5 监测包括对 4,500 个家庭进行 48 小时烹饪面积测量，并对 20% 选定家庭中的男女进行同步个人监测。 20% 的家庭进行重复测量，以评估季节性的影响。监测于 2017 年开始，并将持续到 2019 年。超声波个人气溶胶采样器 (UPAS) 是一种新颖、强大且廉价的基于过滤器的监测器，可通过专用手机应用程序进行编程，用于采样。烹饪区域测量的试点研究现场评估表明 UPAS 与参考哈佛冲击器之间存在高度相关性（r = 0.91；95% CI：0.84，0.95；斜率 = 0.95）。为了便于跟踪并最大限度地减少污染和分析误差，采样器采用带有条形码的过滤器和滤筒，并使用全自动称重系统在采样前和采样后对它们进行称重。只要手机连接到互联网，泵流量和压力测量值、温度和相对湿度、GPS坐标以及基于过滤器压差的半定量连续颗粒质量浓度就会自动上传到中央服务器，并自动筛选采样数据作为质量控制参数。在 48 小时的监测期内进行一项简短的调查。称重后的过滤器经过进一步分析，通过半自动、快速、经济高效的图像分析方法来估计黑碳浓度。然后，测量的 PM2.5 数据将与基线和后续收集的有关家庭特征和行为的 PURE 调查信息相结合，为所有农村 PURE 参与者（约 50,000 名）以及 10 个指数国家内不同的烹饪燃料类型开发 PM2.5 暴露的定量 HAP 模型。测量的（在子集中）和建模的暴露都将用于单独的纵向流行病学分析，以评估与心肺死亡率和疾病发病率的关联。收集的数据以及由此得出的 10 个国家多个农村社区的烹饪区域和个人 PM2.5 暴露特征将更好地为暴露评估以及未来的流行病学分析提供信息，以评估慢性 HAP 暴露与成人死亡率以及心血管和呼吸系统疾病事件的定量估计之间的关系。这将为全球 CVD 相关暴露反应分析提供更精细、更准确的暴露估计。
Household air pollution (HAP) from combustion of solid fuels is an important contributor to disease burden in low- and middle-income countries (LIC, and MIC). However, current HAP cardiovascular disease burden estimates are based on integrated exposure response curves that are not currently informed by quantitative HAP studies in LIC and MIC. While there is adequate evidence supporting causal relationships between HAP and respiratory disease, large cohort studies specifically examining relationships between quantitative measures of HAP exposure with cardiovascular disease are lacking. We aim to improve upon exposure proxies based on fuel type, and to reduce exposure misclassification by quantitatively measuring exposure across varying cooking fuel types and conditions in diverse geographies and socioeconomic settings. We leverage technology advancements to estimate household and personal PM2.5 (particles below 2.5 microns in aerodynamic diameter) exposure within the large (N~250,000) multi-country (N~26) Prospective Urban and Rural Epidemiological [PURE] cohort study. Here, we detail the study protocol and the innovative methodologies being used to characterize HAP exposures, and their application in epidemiologic analyses. This study characterizes HAP PM2.5 exposures for participants in rural communities in ten PURE countries with >10% solid fuel use at baseline (Bangladesh, Brazil, Chile, China, Colombia, India, Pakistan, South Africa, Tanzania, and Zimbabwe). PM2.5 monitoring includes 48-hour cooking area measurements in 4,500 households and simultaneous personal monitoring of male and female pairs from 20% of the selected households. Repeat measurements occur in 20% of households to assess impacts of seasonality. Monitoring began in 2017, and will continue through 2019. The Ultrasonic Personal Aerosol Sampler (UPAS), a novel, robust, and inexpensive filter based monitor that is programmable through a dedicated mobile phone application is used for sampling. Pilot study field evaluation of cooking area measurements indicated high correlation between the UPAS and reference Harvard Impactors (r = 0.91; 95% CI: 0.84, 0.95; slope=0.95). To facilitate tracking and to minimize contamination and analytical error, the samplers utilize barcoded filters and filter cartridges that are weighed pre- and post-sampling using a fully automated weighing system. Pump flow and pressure measurements, temperature and RH, GPS coordinates and semi-quantitative continuous particle mass concentrations based on filter differential pressure are uploaded to a central server automatically whenever the mobile phone is connected to the internet, with sampled data automatically screened for quality control parameters. A short survey is administered during the 48-hr monitoring period. Post-weighed filters are further analyzed to estimate black carbon concentrations through a semi-automated, rapid, cost-effective image analysis approach. The measured PM2.5 data will then be combined with PURE survey information on household characteristics and behaviours collected at baseline and during follow-up to develop quantitative HAP models for PM2.5 exposures for all rural PURE participants (~50,000) and across different cooking fuel types within the 10 index countries. Both the measured (in the subset) and the modelled exposures will be used in separate longitudinal epidemiologic analyses to assess associations with cardiopulmonary mortality, and disease incidence. The collected data and resulting characterization of cooking area and personal PM2.5 exposures in multiple rural communities from 10 countries will better inform exposure assessment as well as future epidemiologic analyses assessing the relationships between quantitative estimates of chronic HAP exposure with adult mortality and incident cardiovascular and respiratory disease. This will provide refined and more accurate exposure estimates in global CVD related exposure-response analyses.
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影响因子：
5
作者：
Meng, Qing Yu;Spector, Dalia;Colome, Steven;Turpin, Barbara
通讯作者：
Turpin, Barbara
影响因子：
10.4
作者：
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通讯作者：
Cohen A
影响因子：
10.4
作者：
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通讯作者：
Smith KR
影响因子：
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作者：
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通讯作者：
Coggon D
影响因子：
10.4
作者：
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通讯作者：
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