Research School of Population Health, Australian National University College of Medicine Biology and Environment, Canberra, Australian Capital Territory, Australia
Demography and Sociology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
BMJ Glob Health. 2021 Jun;6(6). doi: 10.1136/bmjgh-2020-004451.
BACKGROUND: Reducing adult mortality by 2030 is a key component of the United Nations Sustainable Development Goals (UNSDGs). Monitoring progress towards these goals requires timely and reliable information on deaths by age, sex and cause. To estimate baseline measures for UNSDGs, this study aimed to use several different data sources to estimate subnational measures of premature adult mortality (between 30 and 70 years) for India in 2017. METHODS: Age-specific population and mortality data were accessed for India and its 21 larger states from the Civil Registration System and Sample Registration System for 2017, and the most recent National Family and Health Survey. Similar data on population and deaths were also procured from the Global Burden of Disease Study 2016 and the National Burden of Disease Estimates Study for 2017. Life table methods were used to estimate life expectancy and age-specific mortality at national and state level from each source. An additional set of life tables were estimated using an international two-parameter model life table system. Three indicators of premature adult mortality were derived by sex for each location and from each data source, for comparative analysis RESULTS: Marked variations in mortality estimates from different sources were noted for each state. Assuming the highest mortality level from all sources as the potentially true value, premature adult mortality was estimated to cause a national total of 2.6 million male and 1.8 million female deaths in 2017, with Bihar, Maharashtra, Tamil Nadu, Uttar Pradesh and West Bengal accounting for half of these deaths. There was marked heterogeneity in risk of premature adult mortality, ranging from 351 per 1000 in Kerala to 558 per 1000 in Chhattisgarh among men, and from 198 per 1000 in Himachal Pradesh to 409 per 1000 in Assam among women. CONCLUSIONS: Available data and estimates for mortality measurement in India are riddled with uncertainty. While the findings from this analysis may be useful for initial subnational health policy to address UNSDGs, more reliable empirical data is required for monitoring and evaluation. For this, strengthening death registration, improving methods for cause of death ascertainment and establishment of robust mortality statistics programs are a priority.
背景：到 2030 年降低成年人死亡率是联合国可持续发展目标（UNSDGs）的关键组成部分。监测这些目标的进展情况需要及时、可靠的关于年龄、性别和死因的死亡信息。为了估计 UNSDG 的基线措施，本研究旨在使用多种不同的数据来源来估计印度 2017 年的亚非拉国家成年人过早死亡率（30 至 70 岁之间）的省级指标。
方法：从印度的民事登记系统和 2017 年样本登记系统以及最近的全国家庭健康调查中获取了 2017 年印度及其 21 个较大邦的特定年龄人口和死亡率数据；从 2016 年全球疾病负担研究和 2017 年国家疾病负担估计研究中获取了类似的人口和死亡数据。使用生命表方法从每个来源在国家和邦级估计预期寿命和特定年龄死亡率。使用国际双参数模型生命表系统估计了另外一组生命表。为每个地点和每个数据源，从每个数据源中按性别衍生了三个过早成年死亡率指标，用于比较分析。
结果：每个邦的不同来源的死亡率估计都存在显著差异。假设所有来源中最高的死亡率为潜在真实值，2017 年过早成年死亡率导致印度全国男性死亡 260 万例，女性死亡 180 万例，比哈尔邦、马哈拉施特拉邦、泰米尔纳德邦、北方邦和西孟加拉邦占这些死亡人数的一半。过早成年死亡率的风险存在显著异质性，男性从喀拉拉邦的 351/1000 到恰蒂斯加尔邦的 558/1000，女性从喜马偕尔邦的 198/1000 到阿萨姆邦的 409/1000。
结论：印度的死亡率测量可用数据和估计都存在很大的不确定性。虽然本分析的结果可能对解决 UNSDG 的初始省级卫生政策有用，但需要更可靠的经验数据来进行监测和评估。为此，加强死亡登记、改进死因确定方法以及建立健全的死亡率统计方案是当务之急。
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