Análisis del rendimiento técnico de un agregado para la preparación de suelos (Original)

The research was developed at the UBPC sugarcane Carlos Manuel de Céspedes de Bartolomé Masó in March 2020 with the aim of evaluating some of the performance of the agricultural aggregate formed by the Belarus model 1523 tractor and the Grada Baldan with 24 discs, by means of of several indicators that evaluate the efficiency of the process. The method used was the analytical investigative and the technique applied to the timing for the evaluation of the whole in the grading work for the cultivation of sugarcane in alluvial soil, taking into account the behavior of the technological - exploitative and economic indices, the main ones Conclusions were: The values of use of the construction width and of the theoretical speed are well below the recommended values. The values of the shift time utilization coefficient for the aggregate are within the range recommended by the researchers consulted, and the values of the technical performance per shift of the aggregate behaved below their technical possibilities.La investigación, se desarrolló en la Unidad Básica de Producción (UBPC) cañera Carlos Manuel de Céspedes de Bartolomé Masó en el mes de marzo del 2020 con el objetivo de evaluar algunos el rendimiento del agregado agrícola formado por el tractor Belarus modelo 1523 y la Grada Baldan de 24 discos, mediante de varios indicadores que evalúan la eficiencia del proceso. El método utilizado fue el analítico investigativo y la técnica aplicada el cronometraje para la evaluación del conjunto en la labor de gradeo para el cultivo de la caña en un suelo Aluvial, teniendo en cuenta el comportamiento de los índices tecnológicos - explotativos y económicos, las principales conclusiones fueron: Los valores de aprovechamiento del ancho constructivo y de la velocidad teórica están muy por debajo de los valores recomendados. Los valores del coeficiente de aprovechamiento del tiempo de turno para el agregado se encuentran dentro del rango recomendado por investigadores consultados y los valores del rendimiento técnico por turno del agregado se comportaron por debajo de sus posibilidades técnicas

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. FUNDING: Bill & Melinda Gates Foundation

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

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Evaluación tecnológica-explotativa de los conjuntos máquina-tractor para el cultivo del frijol (Phaseolus vulgaris L.) (Original)

The research was carried out in the Agricultural-Based Business Unit belonging to the Paquito Rosales Benítez Agricultural Company, of Yara municipality, Granma province. The objective of the article is the technological-exploitative evaluation of machine-tractor sets for bean cultivation (Phaseolus vulgaris L.), for which account was taken productivity per hour of clean time (WTP), per hour of operating time (W02), per productive time (W04), per hour of fault-free shift time (Wt), per hour of exploitation time (W07 ), all of these in (ha•h-1). The main results were that, the grading and sowing activity achieves a clean time productivity of 1.91 and 1.82 ha•h-1, an operational productivity of 1.49 and 0.91 ha•h-1, and a productive productivity of 0.46 and 0.40 ha•h-1, without failures of 0.37 and 0.30 ha•h-1 and exploitative of 0.26 and 0.24 ha•h-1, with a work speed of 7.62 and 7.12 km•h-1; while the breaking and harvesting activity show the highest fuel consumption, 22 and 7 L•ha-1, and direct operating expenses, respectively.La investigación se realizó en la Unidad Empresarial de Base Agrícola perteneciente a la Empresa Agropecuaria Paquito Rosales Benítez, del Municipio Yara, provincia Granma. El artículo tiene como objetivo la evaluación tecnológica-explotativa de los conjuntos máquina- tractor para el cultivo del frijol (Phaseolus vulgaris L.), para lo cual se tuvo en cuenta la productividad por hora de tiempo limpio (WTP), por hora de tiempo operativo (W02), por tiempo productivo (W04), por hora de tiempo de turno sin fallos (Wt), por hora de tiempo de explotación (W07), todas estas en ha·h-1. Como principales resultados se obtuvo que la actividad de gradeo y siembra alcanza una productividad por tiempo limpio de 1,91 y 1,82 ha·h-1, operativo de 1,49 y 0,91 ha·h-1, productivo de 0,46 y 0,40 ha·h-1, sin fallos  de 0,37 y 0,30 ha·h-1  y  explotativo de 0,26 y 0,24 ha·h-1, con una velocidad de trabajo de 7,62 y 7,12  km·h-1; mientras que la actividad de rotura y cosecha muestra el mayor consumo de combustible,  22 y 7 L·ha-1, y gasto directo de explotación, respectivamente

Indices explotativos del agregado formado por el tractor yto 1204 y la grada 1 975 kg en el cultivo del arroz (Oryza sativa l) (Original)

The research was developed at the “La Gabina” Rice Farm belonging to EAIG, Fernando Echenique. UEB 23, Provision of Comprehensive Cautious Technical Services in the period (2018/02-2018/03). With the aim of evaluating the technological -exploitable indicators of the aggregate formed by the YTO X 1204 tractor through various indices that evaluate the efficiency of the process. The method used was the analytical research and the technique applied the photochronometry for the evaluation of the set in the work of crossing for the cultivation of rice in a Plastic Dark soil, taking into account the behavior of the technological - exploitative indices. The main conclusions were: the depth of work was higher than that recommended by some authors, although it does not significantly damage the development of the crop, The values ​​of the coefficients of use of the construction width and shift time are within those recommended by authors in this science and productivity values ​​show good efficiency in the aggregate object of analysis.La investigación se desarrolló en la Granja Agrícola Arrocera “La Gabina” perteneciente a EAIG, Fernando Echenique. UEB 23, Prestación de Servicios Técnicos Integrales Cauto en el período (2018/02- 2018/03). Con el objetivo de evaluar los indicadores tecnológicos –explotativos del agregado formado por el tractor YTO X 1204 a través de varios índices que evalúan la eficiencia del proceso. El método utilizado fue el analítico investigativo y la técnica aplicada el fotocronometraje para la evaluación del conjunto en la labor de cruce para el cultivo del arroz en un suelo Oscuro Plástico, teniendo en cuenta el comportamiento de los índices tecnológico – explotativos. Las principales conclusiones fueron: la profundidad de trabajo fue superior a la que recomiendan algunos autores, aunque no daña significativamente el desarrollo del cultivo, Los valores de los coeficientes de aprovechamiento del ancho constructivo y del tiempo de turno, están dentro de los recomendados por autores en esta ciencia y os valores de productividad muestran buena eficiencia en el agregado objeto de análisis

Análisis del rendimiento técnico de un apero de labranza. (Original)

The research was developed at the “La Gabina” Rice Farm belonging to EAIG, Fernando Echenique. UEB 23, Provision of Comprehensive Cautious Technical Services in the period (2020/03 - 2020/04). In order to analyze through the calculation, some exploitative indexes of the aggregate formed by the Belarus model 800 tractor and the ADI - 3M plow, for the cultivation of rice (Oryza sativa L). Taking into account the coefficients of use of the working width, the theoretical speed and the shift time. The method used was the analytical investigative and the technique applied the photochronometer for the evaluation of the set in the plowing work. Taking into account the behavior of the technological - exploitative indices, the main conclusions were: The values of the Technical Performance per shift of the aggregate per shift behaved below their technical possibilities, the values of the use of the working width of the aggregate were higher than those recommended by the authors and the values of use of the working speed were lower than those recommended by the Operation Manual of the plow.La investigación se desarrolló en la Granja Agrícola Arrocera “La Gabina” perteneciente a EAIG, Fernando Echenique. UEB 23, Prestación de Servicios Técnicos Integrales Cauto en el período (2020/03 - 2020/04). Con el objetivo de analizar mediante el cálculo, algunos índices explotativos del agregado formado por el tractor Belarus modelo 800 y el arado ADI – 3M, para el cultivo del arroz (Oryza sativa L). Teniendo en cuenta los coeficientes de aprovechamiento del ancho de trabajo, de la velocidad teórica y del tiempo de turno. El método utilizado fue el analítico investigativo y la técnica aplicada el fotocronometraje para la evaluación del conjunto en la labor de aradura. Teniendo en cuenta el comportamiento de los índices tecnológico – explotativos, las principales conclusiones fueron: Los valores del Rendimiento Técnico por turno del agregado por turno se comportaron por debajo de sus posibilidades técnicas, los valores del aprovechamiento del ancho de trabajo del agregado fueron superiores a los recomendados por los autores y los valores de aprovechamiento de la velocidad de trabajo fueron inferiores a los recomendados por el Manual de Explotación del arado

Análisis de la eficiencia de agregados agrícolas de última generación. (Original)

The present work was developed with the objective of analyzing by means of the calculation some indicators of work efficiency of the latest technology agricultural aggregates, partially establishing some of these for the future planning of agricultural work in the Fernando Echenique Agroindustrial Grain Company of the Granma province. To carry out the research, the standards NC 34-37: (2003), NRAG XXI: (2005) were used. The instructions and methodologies presented by Jróbostov (1977), Garrido (1989) and González (1993) were also taken into account. The design used was completely randomized. The results showed that most of the values of the efficiency indicators of these agricultural groups are below the technical possibilities. However, the working width utilization coefficient  for the floor leveler, the working speed utilization coefficient ) of the 52 disc heavy harrow and the shift time utilization coefficient ) of the median tier of 40 discs are classified as acceptable with magnitudes of 0,96; 0,82 and 0,77 respectively. It is concluded that the magnitudes of real productivity  obtained behaved below the real possibilities of the set with magnitudes 14, 65; 17, 71 and 29,1 ha turno-1 respectively. Which is due to violations of kinematic parameters during work?El presente trabajo se desarrolló con el objetivo de analizar mediante el cálculo algunos indicadores de eficiencia del trabajo de los agregados agrícolas de última tecnología, estableciendo de forma parcial algunos de estos para la planificación futura de los trabajos agrícolas en la Empresa Agroindustrial de Granos Fernando Echenique de la provincia Granma. Para la realización de la investigación se utilizaron las normas NC 34-37: (2003), NRAG XXI: (2005). También se tuvieron en cuenta las instrucciones y metodologías expuestas por Jróbostov (1977), Garrido (1989) y González (1993). El diseño utilizado fue completamente aleatorizado. Los resultaros mostró que la mayoría de los valores de los indicadores de eficiencia de estos conjuntos agrícolas se encuentran por debajo de las posibilidades técnicas. Sin embargo, el coeficiente de aprovechamiento del ancho de trabajo (εβ) para el nivelador del suelo, el coeficiente de aprovechamiento de la velocidad de trabajo (εV) de la grada pesada de 52 discos y el coeficiente de aprovechamiento del tiempo de turno (τ) de la grada mediana de 40 discos se catalogan de aceptables con magnitudes de 0,96, 0,82 y 0,77 respectivamente. Se concluye que las magnitudes de productividad real (W_r) obtenidas se comportaron por debajo de las posibilidades reales del conjunto con magnitudes 14,65; 17,71 y 29,1 ha turno-1 respectivamente. Lo cual se debe a violaciones de los parámetros cinemáticos durante el trabajo

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

BackgroundRegular, 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.MethodsThe 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.FindingsThe 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.InterpretationLong-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