Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Estimating the population exposed to a risk factor over a time window: A microsimulation modelling approach from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury.

ObjectivesBurden of disease estimation commonly requires estimates of the population exposed to a risk factor over a time window (yeart to yeart+n). We present a microsimulation modelling approach for producing such estimates and apply it to calculate the population exposed to long working hours for one country (Italy).MethodsWe developed a three-model approach: Model 1, a multilevel model, estimates exposure to the risk factor at the first year of the time window (yeart). Model 2, a regression model, estimates transition probabilities between exposure categories during the time window (yeart to yeart+n). Model 3, a microsimulation model, estimates the exposed population over the time window, using the Monte Carlo method. The microsimulation is carried out in three steps: (a) a representative synthetic population is initiated in the first year of the time window using prevalence estimates from Model 1, (b) the exposed population is simulated over the time window using the transition probabilities from Model 2; and (c) the population is censored for deaths during the time window.ResultsWe estimated the population exposed to long working hours (i.e. 41-48, 49-54 and ≥55 hours/week) over a 10-year time window (2002-11) in Italy. We populated all three models with official data from Labour Force Surveys, United Nations population estimates and World Health Organization life tables. Estimates were produced of populations exposed over the time window, disaggregated by sex and 5-year age group.ConclusionsOur modelling approach for estimating the population exposed to a risk factor over a time window is simple, versatile, and flexible. It however requires longitudinal exposure data and Model 3 (the microsimulation model) is stochastic. The approach can improve accuracy and transparency in exposure and burden of disease estimations. To improve the approach, a logical next step is changing Model 3 to a deterministic microsimulation method, such as modelling of microflows

Global, regional, and national burdens of ischemic heart disease and stroke attributable to exposure to long working hours for 194 countries, 2000-2016: A systematic analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

International audienceBACKGROUND: World Health Organization (WHO) and International Labour Organization (ILO) systematic reviews reported sufficient evidence for higher risks of ischemic heart disease and stroke amongst people working long hours (≥55 hours/week), compared with people working standard hours (35-40 hours/week). This article presents WHO/ILO Joint Estimates of global, regional, and national exposure to long working hours, for 194 countries, and the attributable burdens of ischemic heart disease and stroke, for 183 countries, by sex and age, for 2000, 2010, and 2016. METHODS AND FINDINGS: We calculated population-attributable fractions from estimates of the population exposed to long working hours and relative risks of exposure on the diseases from the systematic reviews. The exposed population was modelled using data from 2324 cross-sectional surveys and 1742 quarterly survey datasets. Attributable disease burdens were estimated by applying the population-attributable fractions to WHO’s Global Health Estimates of total disease burdens. RESULTS: In 2016, 488 million people (95% uncertainty range: 472-503 million), or 8.9% (8.6-9.1) of the global population, were exposed to working long hours (≥55 hours/week). An estimated 745,194 deaths (705,786-784,601) and 23.3 million disability-adjusted life years (22.2-24.4) from ischemic heart disease and stroke combined were attributable to this exposure. The population-attributable fractions for deaths were 3.7% (3.4-4.0) for ischemic heart disease and 6.9% for stroke (6.4-7.5); for disability-adjusted life years they were 5.3% (4.9-5.6) for ischemic heart disease and 9.3% (8.7-9.9) for stroke. CONCLUSIONS: WHO and ILO estimate exposure to long working hours (≥55 hours/week) is common and causes large attributable burdens of ischemic heart disease and stroke. Protecting and promoting occupational and workers’ safety and health requires interventions to reduce hazardous long working hours

Assessor burden, inter-rater agreement and user experience of the RoB-SPEO tool for assessing risk of bias in studies estimating prevalence of exposure to occupational risk factors: An analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

Background: As part of the development of the World Health Organization (WHO)/International Labour Organization (ILO) Joint Estimates of the Work-related Burden of Disease and Injury, WHO and ILO carried out several systematic reviews to determine the prevalence of exposure to selected occupational risk factors. Risk of bias assessment for individual studies is a critical step of a systematic review. No tool existed for assessing the risk of bias in prevalence studies of exposure to occupational risk factors, so WHO and ILO developed and pilot tested the RoB-SPEO tool for this purpose. Here, we investigate the assessor burden, inter-rater agreement, and user experience of this new instrument, based on the abovementioned WHO/ILO systematic reviews. Methods: Twenty-seven individual experts applied RoB-SPEO to assess risk of bias. Four systematic reviews provided a total of 283 individual assessments, carried out for 137 studies. For each study, two or more assessors independently assessed risk of bias across the eight RoB-SPEO domains selecting one of RoB-SPEO's six ratings (i.e., “low”, “probably low”, “probably high”, “high”, “unclear” or “cannot be determined”). Assessors were asked to report time taken (i.e. indicator of assessor burden) to complete each assessment and describe their user experience. To gauge assessor burden, we calculated the median and inter-quartile range of times taken per individual risk of bias assessment. To assess inter-rater reliability, we calculated a raw measure of inter-rater agreement (Pi) for each RoB-SPEO domain, between Pi = 0.00, indicating no agreement and Pi = 1.00, indicating perfect agreement. As subgroup analyses, Pi was also disaggregated by systematic review, assessor experience with RoB-SPEO (≤10 assessments versus > 10 assessments), and assessment time (tertiles: ≤25 min versus 26–66 min versus ≥ 67 min). To describe user experience, we synthesised the assessors’ comments and recommendations. Results: Assessors reported a median of 40 min to complete one assessment (interquartile range 21–120 min). For all domains, raw inter-rater agreement ranged from 0.54 to 0.82. Agreement varied by systematic review and assessor experience with RoB-SPEO between domains, and increased with increasing assessment time. A small number of users recommended further development of instructions for selected RoB-SPEO domains, especially bias in selection of participants into the study (domain 1) and bias due to differences in numerator and denominator (domain 7). Discussion: Overall, our results indicated good agreement across the eight domains of the RoB-SPEO tool. The median assessment time was comparable to that of other risk of bias tools, indicating comparable assessor burden. However, there was considerable variation in time taken to complete assessments. Additional time spent on assessments may improve inter-rater agreement. Further development of the RoB-SPEO tool could focus on refining instructions for selected RoB-SPEO domains and additional testing to assess agreement for different topic areas and with a wider range of assessors from different research backgrounds

Assessor burden, inter-rater agreement and user experience of the RoB-SPEO tool for assessing risk of bias in studies estimating prevalence of exposure to occupational risk factors: An analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

International audienceBackground: As part of the development of the World Health Organization (WHO)/International Labour Organization (ILO) Joint Estimates of the Work-related Burden of Disease and Injury, WHO and ILO carried out several systematic reviews to determine the prevalence of exposure to selected occupational risk factors. Risk of bias assessment for individual studies is a critical step of a systematic review. No tool existed for assessing the risk of bias in prevalence studies of exposure to occupational risk factors, so WHO and ILO developed and pilot tested the RoB-SPEO tool for this purpose. Here, we investigate the assessor burden, inter-rater agreement, and user experience of this new instrument, based on the abovementioned WHO/ILO systematic reviews. Methods: Twenty-seven individual experts applied RoB-SPEO to assess risk of bias. Four systematic reviews provided a total of 283 individual assessments, carried out for 137 studies. For each study, two or more assessors independently assessed risk of bias across the eight RoB-SPEO domains selecting one of RoB-SPEO's six ratings (i.e., "low", "probably low", "probably high", "high", "unclear" or "cannot be determined"). Assessors were asked to report time taken (i.e. indicator of assessor burden) to complete each assessment and describe their user experience. To gauge assessor burden, we calculated the median and inter-quartile range of times taken per individual risk of bias assessment. To assess inter-rater reliability, we calculated a raw measure of inter-rater agreement (P-i) for each RoB-SPEO domain, between P-i = 0.00, indicating no agreement and P-i = 1.00, indicating perfect agreement. As subgroup analyses, P-i was also disaggregated by systematic review, assessor experience with RoB-SPEO (<= 10 assessments versus > 10 assessments), and assessment time (tertiles: <= 25 min versus 26-66 min versus >= 67 min). To describe user experience, we synthesised the assessors' comments and recommendations. Results: Assessors reported a median of 40 min to complete one assessment (interquartile range 21-120 min). For all domains, raw inter-rater agreement ranged from 0.54 to 0.82. Agreement varied by systematic review and assessor experience with RoB-SPEO between domains, and increased with increasing assessment time. A small number of users recommended further development of instructions for selected RoB-SPEO domains, especially bias in selection of participants into the study (domain 1) and bias due to differences in numerator and denominator (domain 7). Discussion: Overall, our results indicated good agreement across the eight domains of the RoB-SPEO tool. The median assessment time was comparable to that of other risk of bias tools, indicating comparable assessor burden. However, there was considerable variation in time taken to complete assessments. Additional time spent on assessments may improve inter-rater agreement. Further development of the RoB-SPEO tool could focus on refining instructions for selected RoB-SPEO domains and additional testing to assess agreement for different topic areas and with a wider range of assessors from different research backgrounds

Supplementary files.docx

New global indicator for workers’ health: mortality rate from diseases attributable to selected occupational risk factors: supplementary files</p

The 2023 report of the Lancet Countdown on health and climate change: the imperative for a health-centred response in a world facing irreversible harms

The Lancet Countdown is an international research collaboration that independently monitors the evolving impacts of climate change on health, and the emerging health opportunities of climate action. In its eighth iteration, this 2023 report draws on the expertise of 114 scientists and health practitioners from 52 research institutions and UN agencies worldwide to provide its most comprehensive assessment yet.In 2022, the Lancet Countdown warned that people's health is at the mercy of fossil fuels and stressed the transformative opportunity of jointly tackling the concurrent climate change, energy, cost-of-living, and health crises for human health and wellbeing. This year's report finds few signs of such progress. At the current 10-year mean heating of 1·14°C above pre-industrial levels, climate change is increasingly impacting the health and survival of people worldwide, and projections show these risks could worsen steeply with further inaction. However, with health matters gaining prominence in climate change negotiations, this report highlights new opportunities to deliver health-promoting climate change action and a safe and thriving future for all