Modelos de innovación en el sector agroalimentario mexicano

The increasing loss of competitiveness in the Mexican agricultural/food sector, the deterioration of natural resources and thepersistence of poverty in the rural environment, can hardly beovercome if the linear innovation model, which has dominatedthe development approach adopted in the agricultural/food sphere,is not changed. Based on various case studies, the need to gobeyond the vertical character of this model is argued, and torecognize that innovation is a social process in which multipleactors or nodes, each with different resources, capacities andabilities, interact and co-develop new knowledge with greatpotential to generate changes that create wealth. The real challengeis in valuing the power of networks as an innovation mechanism.La creciente pérdida de competitividad del sector agroalimentariomexicano, el deterioro de los recursos naturales y la persistenciade la pobreza en el medio rural, difícilmente pueden sersuperados si no se trasciende el modelo lineal de innovación queha dominado el enfoque de desarrollo adoptado en el ámbitoagroalimentario. Con base a diversos estudios de caso, se fundamentala necesidad de superar el carácter vertical de este modeloy reconocer que la innovación es un proceso social en el quemúltiples actores o nodos, cada uno con diferentes recursos, capacidadesy habilidades, interactúan y co-desarrollan nuevos conocimientoscon gran potencial para generar cambios creadoresde riqueza. El verdadero desafío está en valorar el poder de lasredes como mecanismo de innovación

Cobertura financiera de la banca de desarrollo para el sector rural de México: FIRA y Financiera Rural

En México, el financiamiento al sector rural se sustenta en los Fideicomisos Instituidos en Relación a la Agricultura y en la Finan - ciera Rural, instituciones que conforman la banca de desarrollo para este sector y cuyo propósito esencial es el fomento productivo. Este trabajo analiza la cobertura financiera de la banca de desarrollo en el sector rural en sus dimensiones de amplitud, profundidad, alcance y permanencia. Por la investigación se concluye que la banca de desarrollo del sector rural ha priorizado su sostenibilidad financiera, concentrándose en la amplitud y con pocos logros en alcance y profundidad, lo cual refleja un limitado desempeño como institución de fomento

Presencia de productos orgánicos en Twitter desde la perspectiva del análisis de redes sociales

El objetivo de esta investigación fue analizar cómo está estructurada la red de actores que hablan de productos orgánicos en Twitter y, a través de la identificación de actores clave, conocer la influencia que ejercen dentro de las redes; al hacerlo, desarrollamos ideas significativas que permitan a los usuarios de medios sociales mejorar su interacción y posición dentro de la red. Se buscaron y descargaron los datos de los términos #organico(a) y #organicos(as) por un periodo de seis meses. Para su procesamiento y estudio, se utilizó el enfoque teórico y metodológico del análisis de redes sociales (ARS). La red general se formó por 14,329 tweets únicos, publicados por 6,667 usuarios, configurando una red de 6,521 vínculos directos. Para entender con mayor detalle las interacciones, se segmentó la red con base en dos tipos de relaciones: (1) retweets y (2) menciones o respuestas, ambas redes mostraron estructuras diferentes. Se encontró que el conjunto de relaciones que estructuran la red social está asociado a productos, países y temas, así como a diversos actores clave. Además, la expresión de los orgánicos en Twitter sigue de cerca la visión general de considerarse benéficos para la salud y el medio ambiente.The objective of this research was to analyse how the network of actors talking about organic products on Twitter is structured and, through the identification of key players, to assess the influence they exert within the networks. Doing this, we develop meaningful ideas that allow social media users to improve their interaction and position on networks. The data of the terms #organico(a) and #organicos(as) were searched and downloaded for a six-month period. For its processing and study, the theoretical and methodological approach of social networks analysis (SNA) was used. The general network was formed by 14,329 unique tweets, published by 6,667 users, shaping a network with 6,521 direct links. To understand the interactions in greater detail, the network was segmented based on two types of relationships: (1) retweets and (2) mentions or replies to, both networks showed different structures. It was found that the set of relationships that structure the social network is associated with products, countries, and topics, as well as several key players. Furthermore, the expression of organic on Twitter closely follows the general vision of being considered beneficial for health as well as the environment.O objetivo desta pesquisa foi analisar como se estrutura a rede de atores que falam sobre produtos orgânicos no Twitter e, por meio da identificação dos atores-chave, conhecer a influência que eles exercem nas redes; Ao fazer isso, desenvolvemos ideias significativas que permitem aos usuários de mídia social melhorar sua interação e posição na rede. Os dados dos termos #organico (a) e #organicos (as) foram pesquisados ​​e baixados por um período de seis meses. Para seu processamento e estudo, utilizou-se a abordagem teórico-metodológica da análise de redes sociais (ARS). A rede geral foi composta por 14.329 tweets únicos, publicados por 6.667 usuários, perfazendo uma rede de 6.521 links diretos. Para compreender mais detalhadamente as interações, a rede foi segmentada com base em dois tipos de relacionamento: (1) retuítes e (2) menções ou respostas, ambas as redes apresentavam estruturas diferentes. Constatou-se que o conjunto de relações que estruturam a rede social está associado a produtos, países e temas, bem como a diversos atores-chave. Além disso, a expressão do orgânico no Twitter segue de perto a visão geral de ser considerado benéfico à saúde e ao meio ambiente

Restricciones para orientar a resultados los programas de desarrollo rural en México

The objective of this study was to specify the influence of sectorial planning and evaluation on the design and budgeting of programs linked to rural development and their impact on their improvement. For this, the Integral Program for Rural Development (Programa Integral de Desarrollo Rural, PIDR) by SAGARPA was analyzed, and its relation with normative instruments; in addition, interviews were performed with key actors involved in the processes of design and budgeting of programs directed at the rural sector. It was found that the six-year-term sectorial planning is formally an exercise ordered with accurate diagnoses, with explicit objectives and goals. However, it is not considered in the design and budget allocation of each program; rather, these result from the annual negotiation of the federal government with political groups from the House of Representatives, the Mexican Council on Rural Sustainable Development, the Association of Rural Development Ministers, and unionized producers’ organizations, among others. It is concluded that the instruments of planning, monitoring and control do not guarantee the design and budgeting of results oriented rural development programs.El objetivo de esta investigación fue precisar la influencia de la planeación sectorial y de la evaluación sobre el diseño y presupuestación de los programas vinculados al desarrollo rural y su impacto en la mejora de los mismos. Para ello se analizó el Programa Integral de Desarrollo Rural (PIDR) de la SAGARPA y su relación con los instrumentos normativos; además, se realizaron entrevistas a actores clave involucrados en los procesos de diseño y presupuestación de los programas dirigidos al sector rural. Se encontró que formalmente la planeación sectorial sexenal es un ejercicio ordenado con diagnósticos precisos, con objetivos y metas explícitas. No obstante, no se considera en el diseño y la asignación presupuestal de cada programa; estos más bien resultan de la negociación anual del gobierno federal con los grupos políticos de la Cámara de Diputados, el Consejo Mexicano de Desarrollo Rural Sustentable, la Asociación de Secretarios de Desarrollo Rural y las organizaciones gremiales de productores, entre otros. Se concluye que los instrumentos de planeación, seguimiento y control no garantizan el diseño y presupuestación de programas de desarrollo rural orientados a resultados

Lecciones de la promoción de proyectos caprinos a través del programa estratégico de seguridad alimentaria en Guerrero, México

The impact of goat projects promoted by the Strategic Food Security Program (Programa Estratégico para la Seguridad Alimentaria, PESA) in regions of high marginality in Guerrero, México, was analyzed. A survey was performed in 316 family production units out of a register of 2093 units supported during the 2007-2009 period. The information was gathered in January 2011, in average 20.6 months after having received the first subsidy for the purchase of breeding stock and infrastructure. Of the flocks, 48.9 % were still growing, 13.8 % were stable, 29.8 % were decreasing and only 7.5 % had disappeared. This apparent good performance is consequence of the PESA design, which guarantees support for three years for those who maintain the flocks, independently of their viability. However, the results show that subsidies did not increase the productive capacity, nor did they generate greater wealth or employment, since the net value of impacts (sales, personal consumption and capitalization, minus costs in feed and medicines) in the flocks that were growing was only 14.8 USD annually. It is recommended to promote small-scale livestock production only in regions with vocation for the activity and with producers who have a minimal supply of fodder resources and experience.Se analizó el impacto de los proyectos caprinos promovidos por el Programa Estratégico para la Seguridad Alimentaria (PESA) en regiones de alta marginalidad de Guerrero, México. Se realizó una encuesta en 316 unidades de producción familiar de un padrón de 2093 apoyadas en el periodo 2007-2009. La información se recabó en enero de 2011; en promedio 30.6 meses después de haber recibido el primer subsidio para la adquisición de pie de cría e infraestructura. De los rebaños, 48.9 % se mantenían creciendo, 13.8 % estables, 29.8 % decreciendo y sólo 7.5 % habían desaparecido. Este aparente buen desempeño es consecuencia del diseño del PESA, que garantiza apoyos durante tres años a quien mantenga los rebaños, ello con independencia de su viabilidad. Sin embargo, los resultados muestran que los subsidios no aumentaron la capacidad productiva, ni generaron mayor riqueza o empleos, ya que en los rebaños que estaban creciendo el valor neto de los impactos (ventas, autoconsumo y capitalización, menos costos en alimentos y medicinas) fue de apenas 14.8 USD anuales. Se recomienda promover la ganadería en pequeña escala sólo en regiones con vocación para la actividad y con productores que cuenten con una dotación mínima de recursos forrajeros y experiencia

Amaranth production in Tulyehualco Xochimilco, Mexico City

During 2010-2019 amaranth has been cultivated in at least 11 states in Mexico, in Mexico City is grown in the municipalities of Xochimilco, Milpa Alta and Tláhuac, highlighting Xochimilco for harvested area and production with 82.9 ha and 91.7 t which represents 60.4% and 55.6% respectively. The objective of the research is to know the form of production and commercialization of amaranth in Tulyehualco, Xochimilco to identify and propose improvement actions. The information was obtained through the application of a survey through a non-probability sampling for convenience, with the criterion of selection of individuals who were willing to be surveyed, and the survey was applied from September to December 2019, to 35 producers, 3 marketers and 4 transformers. The production of amaranth is carried out in two ways, by means of chapin and directly, by its traditional way of producing it the crop is ancestral in those areas, so there is a millenary knowledge of the families that are dedicated to the planting of the crop. Amaranth production has a positive cost benefit ratio R (B / C), however in direct sowing production this is better. Planting with a seedbed (Chapin) has higher costs and yield, however, this does not compensate the producer in profits. For a potential impact at the amaranth production level, the adoption of technologies related to density, nutrition and technical recommendations for pest and disease control.Objective: To know the form of production and commercialization of amaranth in Tulyehualco, Xochimilco, to identify and propose improvement actions. Methodology: During 2010-2019, amaranth was cultivated in at least 11 states in Mexico, while in Mexico City it is grown in the municipalities of Xochimilco, Milpa Alta and Tláhuac. Xochimilco stands out due to harvested area and production, with 82.9 ha and 91.7 t which represents 60.4% and 55.6% respectively. The information was obtained through the application of a survey through non-probability sampling for convenience, with the selection criterion of individuals who were willing to be surveyed, and the survey was applied from September to December 2019, to n=35 producers, n=3 marketers and n=4 transformers. Amaranth production is carried out in two ways, by means of chapin and directly, and due to its traditional way of producing the crop is ancestral in those areas, so there is a millenary knowledge of the families that are dedicated to planting the crop. Results: Amaranth production has a positive cost benefit ratio R (B / C) although production is better in direct sowing. Planting with a seedbed (Chapin) has higher costs and yield, however, this does not compensate the producer in profits. Conclusions: For a potential impact at the level of amaranth production, the adoption of technologies related to density, nutrition and technical recommendations for pest and disease control is necessar

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

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

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030