Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.
Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.
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DOI：
10.1016/s0140-6736(18)32225-6
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发表时间：
2018-11-10
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通讯作者：
GBD 2017 Risk Factor Collaborators
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作者：
GBD 2017 Risk Factor Collaborators
2017年全球疾病、伤害和风险因素负担研究（GBD）比较风险评估（CRA）是一种风险因素量化的综合方法，为综合风险和风险-结果关联的证据提供了有用的工具。在每年的GBD研究中，我们都会更新GBD CRA，以纳入改进的方法，新的风险和风险-结果对，以及关于风险暴露水平和风险-结果关联的新数据。我们使用为GBD先前迭代开发的CRA框架，按年龄组、性别、年份和地点估计1990年至2017年84种行为、环境和职业以及代谢风险或风险组的暴露水平和趋势、归因死亡和归因残疾调整生命年（DADs）。本研究纳入了476个符合GBD研究标准的风险-结局对，以获得令人信服或可能的因果关系证据。我们从46749项随机对照试验、队列研究、家庭调查、人口普查数据、卫星数据和其他来源中提取了相对风险和暴露估计值。 我们使用统计模型来汇总数据，调整偏倚，并纳入协变量。使用理论最低风险暴露水平（TMREL）的反事实情景，我们估计了可归因于给定风险的死亡和伤残的比例。我们通过对社会人口指数（SDI）与风险加权暴露流行率之间的关系进行建模，并通过SDI估计预期暴露水平和风险归因负担，探索了发展与风险暴露之间的关系。最后，我们通过将这些变化分解为六个主要的变化驱动因素来探索风险归因的时间变化：（1）人口增长;（2）人口年龄结构的变化;（3）暴露于环境和职业风险的变化;（4）暴露于行为风险的变化;（5）暴露于代谢风险的变化。以及（6）由于所有其他因素引起的变化，近似为风险删除的死亡率和DALY率，其中风险删除率是我们降低GBD 2017中包含的所有风险因素的TMREL暴露水平时观察到的比率。2017年，3410万（95%不确定性区间[UI] 33.3 - 35.0）例死亡和12.1亿（1.14 - 1.28）例DAF可归因于GBD风险因素。在全球范围内，61.0%（59.6 - 62.4）的死亡和48.3%（46.3 - 50.2）的死亡归因于GBD 2017风险因素。当按危险因素可归因的舒张压排序时，高收缩压（SBP）是首要危险因素，占1040万（9·39-11·5）死亡和2.18亿（198-237）丹麦人，其次是吸烟（7.1亿[6.83 - 7.37]例死亡和1.82亿[173-193]例糖尿病），空腹血糖高（653万[5.23 - 8.23]人死亡，1.71亿[144-201]人死亡），高体重指数（体重指数; 4.72百万[2.99 - 6.70]人死亡，1.48亿[98·6-202]人死亡），出生体重的妊娠期短（1.43百万[1.36 - 1.51]人死亡，1.39亿[131-147]人死亡）。总的来说，2007年至2017年期间，风险归因的DADs下降了4.9%（3.3 - 6.5）。在没有人口变化（即人口增长和老龄化）的情况下，风险暴露和风险删除的DADs的变化将导致DADs在此期间下降23.5%。相反，在风险暴露和风险删除的数据没有变化的情况下，人口统计学的变化将导致数据在此期间增加18.6%。1990年至2017年期间，全球不安全饮用水和家庭空气污染的观测风险暴露水平与基于SDI的预期暴露水平的比率（O/E比率）有所增加。这一结果表明，发展的速度比人口中潜在风险结构的变化更快。相反，吸烟和饮酒的O/E比率几乎普遍下降，这表明，对于给定的SDI，这些风险的暴露正在下降。2017年，年龄标准化DALY率的主要4级风险因素是四个超级地区的高SBP：中欧，东欧和中亚;北非和中东;南亚;东南亚，东亚和大洋洲。高收入超级区域的主要风险因素是吸烟，拉丁美洲和加勒比是高BMI，撒哈拉以南非洲是不安全性行为。在撒哈拉以南非洲，不安全性行为的O/E比率非常高，而在北非和中东，酒精使用的O/E比率非常低。通过量化风险因素的暴露水平和趋势以及由此产生的疾病负担，这一评估可以深入了解过去的政策和方案努力在哪些方面可能取得成功，并突出强调当前公共卫生行动的优先事项。行为、环境和职业风险的减少在很大程度上抵消了人口增长和老龄化对绝对负担趋势的影响。相反，不断增加的代谢风险和人口老龄化可能会继续在全球一级推动非传染性疾病的增加趋势，这既是一个公共卫生挑战，也是一个机遇。我们看到，风险暴露水平和风险归因负担在时空上存在相当大的异质性。虽然发展水平是这种异质性的基础，但O/E比率显示了各国相对于其发展水平表现过度或表现不佳的风险。因此，这些比率提供了一个基准工具，以帮助集中地方决策。我们的研究结果加强了风险暴露监测和流行病学研究的重要性，以评估风险和健康结果之间的因果关系，并强调了GBD研究在综合数据以得出全面和可靠的结论，帮助制定良好的政策和战略卫生规划方面的有用性。比尔和梅林达·盖茨基金会。
The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning. Bill & Melinda Gates Foundation.