Jaganathan Suganthi, Stafoggia Massimo, Rajiva Ajit, Mandal Siddhartha, Dixit Shweta, de Bont Jeroen, Wellenius Gregory A, Lane Kevin J, Nori-Sarma Amruta, Kloog Itai, Prabhakaran Dorairaj, Prabhakaran Poornima, Schwartz Joel, Ljungman Petter
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Health Analytics Research and Trends, Ashoka University, Sonipat, India; Centre for Chronic Disease Control, New Delhi, India.
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy.
Lancet Planet Health. 2024 Dec;8(12):e987-e996. doi: 10.1016/S2542-5196(24)00248-1.
In 2019, the Global Burden of Diseases, Injuries, and Risk Factors Study attributed 0·98 million deaths to ambient air pollution in India based on potentially inappropriate exposure-response functions from countries with low air pollution levels. Instead, using data from India, we investigated long-term exposure to PM and all-cause mortality with a causal inference method.
We collected national counts of annual mortality from 2009 to 2019 from the Civil Registration System at the district level to calculate annual district-level mortality rate as our main outcome and obtained annual PM concentrations from a high-resolution spatiotemporal model. We applied an extended version of the difference-in-differences design by use of generalised additive models with quasi-Poisson distribution, including indicator variables and separate time trends for spatial administrative divisions. PM concentrations obtained at 1 km × 1 km spatial resolution across the country were used to calculate annual district-level mean PM concentrations. Similarly, we collected confounders at the district level, such as mean and SD of quarterly temperatures, gross domestic product per capita, population aged 60 years or older, clean cooking fuel usage, literacy in women, and median age. The spatial unit of analysis was administrative division.
The annual median population-weighted PM was 38·9 μg/m (5-95th percentile 19·7-71·8 μg/m). The full population lived in areas with PM concentrations exceeding the 5 μg/m annual mean recommended in the WHO guidelines, and 1·1 billion of 1·4 billion (81·9% of the total population) lived in areas above the Indian National Ambient Air Quality Standards for annual mean PM not exceeding 40 μg/m. A 10 μg/m increase in annual PM concentration was associated with an 8·6% (95% CI 6·4-10·8) higher annual mortality. Based on the Indian National Ambient Air Quality Standards, a total of 3·8 million (95% CI 2·9-4·9) deaths between 2009 and 2019 were attributable to PM, amounting to 5·0% (3·8-6·4) of total mortality. Based on the WHO guidelines, a total of 16·6 million (13·0-21·8) deaths were attributable to PM, amounting to 24·9% (19·5-32·5) of total mortality.
Our difference-in-differences approach allowed us to assess the full extent of registered deaths in the most populated country in the world, which has high levels of air pollution. We provide new evidence of increased mortality risk from long-term PM, which emphasises the need for tighter regulatory standards to potentially substantially reduce mortality across India.
Swedish Research Council for Sustainable Development.
2019年，全球疾病、伤害及风险因素负担研究基于空气污染水平较低国家可能不适用的暴露-反应函数，将印度09.8万例死亡归因于环境空气污染。相反，我们利用印度的数据，采用因果推断方法研究了长期暴露于细颗粒物（PM）与全因死亡率之间的关系。
我们从地区层面的民事登记系统收集了2009年至2019年的全国年度死亡人数计数，以计算地区层面的年度死亡率作为主要结果，并从高分辨率时空模型中获取年度PM浓度。我们应用了差异-in-差异设计的扩展版本，使用具有准泊松分布的广义相加模型，包括指示变量和空间行政区划的单独时间趋势。利用全国范围内1 km×1 km空间分辨率获取的PM浓度来计算地区层面的年度平均PM浓度。同样，我们收集了地区层面的混杂因素，如季度温度的均值和标准差、人均国内生产总值、60岁及以上人口、清洁烹饪燃料使用情况、女性识字率和年龄中位数。分析的空间单位是行政区划。
年度人口加权PM中位数为38.9 μg/m³（第5-95百分位数为19.7-71.8 μg/m³）。全体人口居住在PM浓度超过世界卫生组织指南建议的年均5 μg/m³的地区，14亿人口中的11亿（占总人口的81.9%）居住在年均PM不超过40 μg/m³的印度国家环境空气质量标准之上的地区。年度PM浓度每增加10 μg/m³，年度死亡率就会升高8.6%（95%置信区间6.4-10.8）。根据印度国家环境空气质量标准，2009年至2019年期间共有380万（95%置信区间290-490）例死亡可归因于PM，占总死亡率的5.0%（3.8-6.4）。根据世界卫生组织指南，共有1660万（1300-2180）例死亡可归因于PM，占总死亡率的24.9%（19.5-32.5）。
我们的差异-in-差异方法使我们能够评估世界上人口最多且空气污染水平高的国家登记死亡的全部情况。我们提供了长期PM导致死亡风险增加的新证据，强调需要更严格的监管标准，以可能大幅降低印度的死亡率。
瑞典可持续发展研究理事会。
