Lancet. 2024 May 18;403(10440):2204-2256. doi: 10.1016/S0140-6736(24)00685-8.
Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.
Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline.
In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8-63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0-45·0] in 2050) and south Asia (31·7% [29·2-34·1] to 15·5% [13·7-17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4-40·3) to 41·1% (33·9-48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6-25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5-43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5-17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7-11·3) in the high-income super-region to 23·9% (20·7-27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5-6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2-26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [-0·6 to 3·6]).
Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions.
Bill & Melinda Gates Foundation.
疾病负担的未来趋势和健康驱动因素是政策制定者和广大公众非常感兴趣的话题。这些信息可用于政策和长期健康投资、规划和优先排序。我们对作为全球疾病、伤害和风险因素研究 (GBD) 一部分生成的先前预测进行了扩展和改进,并提供了参考预测(最有可能的未来),以及如果到 2050 年消除当前水平的某些风险因素,评估疾病负担轨迹的替代情景。
使用健康主要驱动因素的预测,如社会人口指数 (SDI;人均收入、平均受教育年限和 25 岁以下总生育率的滞后分布的综合衡量标准) 和 GBD 中捕获的整套风险因素,我们提供了 204 个国家和地区、21 个 GBD 区域、7 个超区域和世界从 2022 年到 2050 年的年龄和性别特异性死亡率、丧失生命年 (YLLs)、残疾生命年 (YLDs) 和残疾调整生命年 (DALYs) 的因果特异性预测。所有分析均在因果特异性水平进行,以便只有 GBD 比较风险评估认为是因果关系的风险因素才会影响每个疾病的未来死亡率轨迹。使用 SDI 和时间作为主要协变量的混合效应模型来建模因果特异性死亡率,将因果风险因素的综合影响作为模型中的偏移量。在全因死亡率水平,我们通过使用 SDI 作为主要协变量的自回归综合移动平均模型和漂移衰减来建模残差,从而捕捉到无法解释的变化。这些全因预测通过使用级联死亡率模型在 GBD 因果层次结构的较深层次上限制因果特异性预测,从而确保因果特异性死亡率的稳健估计。对于非致命性措施(例如,腰痛),使用 SDI 作为主要协变量的混合效应模型预测发病率和患病率,从这些预测结果和 GBD 中的平均残疾权重计算 YLDs。通过用从当前水平逐步消除风险因素暴露的假设轨迹替代适当的参考轨迹,构建替代未来情景。情景是从各种风险因素集构建的:环境风险 (Safer Environment 情景)、与传染性疾病、孕产妇、新生儿和营养疾病 (CMNNs;Improved Childhood Nutrition and Vaccination 情景)、主要非传染性疾病 (NCDs;Improved Behavioural and Metabolic Risks 情景) 相关的风险以及这三个情景的综合影响。使用 Shared Socioeconomic Pathways 气候情景 SSP2-4.5 作为参考,并在 Safer Environment 情景中使用 SSP1-1.9 作为乐观替代,我们通过使用最新的政府间气候变化专门委员会温度预测和相同的两个情景的公布的环境空气污染轨迹来考虑气候变化对健康的影响。使用标准方法计算预期寿命和健康预期寿命。预测框架包括为每个位置和每个情景单独计算年龄性别特定的未来人口。每个个体未来估计的 95% 置信区间 (UI) 是从通过多阶段计算管道传播 500 次的分布中 2.5 分位数和 97.5 分位数得出的。
在参考情景预测中,全球和超区域的预期寿命从 2022 年增加到 2050 年,但与 COVID-19 大流行之前的三十年(从 2020 年开始)相比,这一增长速度较慢。未来的生命预期将在预期寿命相对较低的超区域(例如撒哈拉以南非洲)比预期寿命较高的超区域(例如高收入超区域)有更大的增长,导致在 2050 年之前的各个地点之间的预期寿命呈趋同趋势。在超区域水平,健康预期模式与预期寿命模式相似。参考情景预测发现,未来几十年健康状况将得到改善,每个 GBD 超区域的全因年龄标准化 DALY 率将下降。然而,每个超区域的总 DALY 负担(以计数衡量)将增加,这主要是由于人口老龄化和增长。我们还预测,DALY 计数和年龄标准化 DALY 率都将继续从 CMNNs 转移到 NCDs,其中最明显的转移发生在撒哈拉以南非洲(2022 年的 DALY 中有 60.1%[95%UI 56.8-63.1%]来自 CMNNs,而到 2050 年则为 35.8%[31.0-45.0%])和南亚(31.7%[29.2-34.1]至 15.5%[13.7-17.5])。这一转变反映在全球疾病负担的主要原因中,2050 年的前四位原因是缺血性心脏病、中风、糖尿病和慢性阻塞性肺疾病,而 2022 年则是缺血性心脏病、新生儿疾病、中风和下呼吸道感染。YLDs 导致的 DALYs 也同样增加,从 2022 年的 33.8%(27.4-40.3)增加到 2050 年的 41.1%(33.9-48.1),这表明整体疾病负担向发病率转移,而不是过早死亡。这种转变在撒哈拉以南非洲最为明显,从 2022 年的 20.1%(15.6-25.3)的 DALYs 归因于 YLDs 增加到 2050 年的 35.6%(26.5-43.0)。在替代未来情景的评估中,情景的综合影响(Safer Environment、Improved Childhood Nutrition and Vaccination 和 Improved Behavioural and Metabolic Risks 情景)表明,到 2050 年,DALY 负担的全球降幅为 15.4%(13.5-17.5),与参考情景相比,超区域降幅从高收入超区域的 10.4%(9.7-11.3)到北非和中东的 23.9%(20.7-27.3)不等。Safer Environment 情景在撒哈拉以南非洲的降幅最大(5.2%[3.5-6.8]),Improved Behavioural and Metabolic Risks 情景在北非和中东(23.2%[20.2-26.5]),Improved Nutrition and Vaccination 情景在撒哈拉以南非洲(2.0%[-0.6 至 3.6])。
全球范围内,2022 年至 2050 年间的预期寿命和年龄标准化疾病负担预计将有所改善,大部分疾病负担将继续从 CMNNs 转移到 NCDs。也就是说,要继续减少 CMNN 疾病负担,将取决于继续投资和强调 CMNN 疾病预防和治疗。主要是由于人口增长和老龄化,所有原因导致的死亡人数和 DALYs 总数通常会增加。通过构建某些风险因素到 2050 年消除的替代未来情景,我们表明,通过协调努力预防已确定的风险因素暴露并扩大对关键健康干预措施的获取,可以在未来大幅改善健康状况。
比尔和梅琳达盖茨基金会。