Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Conserving wild Arabica coffee: emerging threats and opportunities

Climate change and emerging pests and diseases are posing important challenges to global crop productivity, including that of Arabica coffee. The genetic basis of commercially used Arabica coffee cultivars is extremely narrow, and it is uncertain how much genetic diversity is present in ex situ collections. Conserving the wild Arabica coffee gene pool and its evolutionary potential present in the montane forests of SW Ethiopia is thus critically important for maintaining coffee yield and yield stability worldwide. Globally, coffee agroforestry helps to conserve forest cover and forest biodiversity that cannot persist in open agricultural landscapes, but the conservation of the wild Arabica coffee gene pool requires other priorities than those that are usually set for conserving forest biodiversity in mixed tropical landscapes. We show how forest loss and degradation, coffee management, in particular production intensification, and the introduction of cultivars, are threatening the genetic integrity of these wild populations. We propose an active land sparing approach based on strict land use zoning to conserve the genetic resources and the in situ evolutionary potential of Arabica coffee and discuss the major challenges including the development of access and benefit sharing mechanisms for ensuring long-term support to conservation.Highlights • Climate change and emerging diseases challenge global Arabica coffee production. • The wild Arabica genepool from SW Ethiopia is needed to harness coffee production. • Only in situ conservation can secure the evolutionary potential of Arabica coffee. • In situ coffee conservation can only be accomplished in strict forest reserves. • Extensive coffee production systems may secure other components of biodiversity.status: publishe

Genetic diversity among commercial arabica coffee (Coffea arabica L.) varieties in Ethiopia using simple sequence repeat markers

Ethiopia is the center of origin and genetic diversity of arabica coffee. Forty-two commercial arabica coffee varieties were developed by Jimma Agricultural Research Center (JARC) of Ethiopian Institute of Agricultural Research (EIAR) and released for production under diverse agro-ecologies of the country. Information on the level of genetic diversity among these varieties is scarce. Out of the 42 varieties, the genetic diversity of 40 widely cultivated commercial varieties was assessed using 14 simple sequence repeat (SSR) markers. These markers revealed polymorphism among the varieties. High average number of polymorphic alleles (7.5) and polymorphic information content (PIC = 80%) per locus were detected among the varieties. The genetic similarity among varieties using the Jaccard's similarity coefficient ranged from 0.14 to 0.78, with a mean of 0.38. The range of genetic similarity coefficient values in 92% of the possible pair-wise combinations varied from 0.14 to 0.50, indicating the presence of distant genetic relatedness among the varieties. Unweighted pair group method using arithmetic mean (UPGMA) clustering showed six major clusters and three singletons. Coffee varieties, belonging to the same geographic origin, were distributed across clusters. This study represents the first evidence of the presence of a high level of genetic diversity in Ethiopian commercial arabica coffee varieties. Divergent varieties with complementing traits could be crossed to develop productive hybrid coffee varieties

Semi-forest coffee cultivation and the conservation of Ethiopian Afromontane rainforest fragments

Coffea arabica shrubs are indigenous to the understorey of the moist evergreen montane rainforest of Ethiopia. Semi-forest coffee is harvested from semi-wild plants in forest fragments where farmers thin the upper canopy and annually slash the undergrowth. This traditional method of coffee cultivation is a driver for preservation of indigenous forest cover, differing from other forms of agriculture and land use which tend to reduce forest cover. Because coffee farmers are primarily interested in optimizing coffee productivity, understanding how coffee yield is maximized is necessary to evaluate how, and to what extent, coffee production can be compatible with forest conservation. Abiotic variables and biotic variables of the canopy were recorded in 26 plots within 20 forest fragments managed as semi-forest coffee systems near Jimma, SW Ethiopia. In each plot, coffee shrub characteristics and coffee yield were recorded for four coffee shrubs. Cluster and indicator species analysis were used to differentiate plant communities of shade trees. A multilevel linear mixed model approach was then used to evaluate the effect of abiotic soil variables, shade tree plant community, canopy and stand variables, coffee density and coffee shrub size variables on coffee yield. Climax species of the rainforest were underrepresented in the canopy. There were three impoverished shade tree communities, which differed in tree species composition but did not exhibit significant differences in abiotic soil variables, and did not directly influence coffee yield. Coffee yield was primarily determined by coffee shrub branchiness and basal diameter. At the stand level a reduced crown closure increased coffee yield. Yield was highest for coffee shrubs in stands with crown closure less than median (49 ± 1 %). All stands showed a reduced number of stems and a lower canopy compared to values reported for undisturbed moist evergreen montane rainforests. Traditional coffee cultivation is associated to low tree species diversity and simplified forest structure: few stems, low canopy height and low crown closure. Despite intensive human interference some of the climax species are still present and may escape local extinction if they are tolerated and allowed to regenerate. The restoration of healthy populations of climax species is critical to preserve the biodiversity, regeneration capacity, vitality and ecosystem functions of the Ethiopian coffee forests.status: publishe

Intensification of Ethiopian coffee agroforestry drives impoverishment of the Arabica coffee flower visiting bee and fly communities

Intensively managed shade coffee plantations are expanding in SW Ethiopia, at the cost of the more natural coffee agroforestry systems. Here, we investigated consequences for the potential pollinator community of Arabica coffee (Coffea arabica L.) in its natural range. We surveyed coffee flower visitors at six different sites in the Jimma region in SW Ethiopia, and compared species richness and abundance between semi-natural coffee forests and shaded coffee plantations. Overall, we found six bee (Hymenoptera: Anthophila) and twenty fly species (Diptera: Brachycera) visiting C. arabica flowers. Species richness and overall abundance of flower visitors was significantly higher in the semi-natural forests compared to the plantations. A significantly higher abundance of non-Apis bees and hoverflies (Syrphidae) visiting C. arabica flowers was observed in the semi-natural forest plots, but numbers for other Diptera and honeybees (Apis mellifera L.) did not differ significantly between the agroforestry systems. Our results show an impoverishment of the coffee flower visiting insect community in response to agricultural intensification. This suggests a functional shift of the coffee pollinator community and, hence, may influence the stability of the provided pollination ecosystem services and coffee yield in the long term. We did, however, not quantify pollination services in this study