19 research outputs found

    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

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    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

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    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

    Genetic assessment of the internal transcribed spacer region (its1.2) in mangifera indica l. Landraces.

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    Mango (Mangifera indica) is one of the most important tropical fruits in the world. Twenty-two genotypes of native mangoes from different regions of southern Iran (Hormozgan and Kerman) were collected and analyzed for the ribosomal genes. GC content was found to be 55.5%. Fu and Li's D* test statistic (0.437), Fu and Li's F* test statistic (0.500) and Tajima's D (1.801) were positive and nonsignificant. A total of 769 positions were identified (319 with insertion or deletion including 250 polymorphic and 69 monomorphic loci; 450 loci without any insertion or deletion including 35 Singletons and 22 haplotypes). Nucleotide diversity of 0.309 and a high genetic differentiation including Chi square of 79.8; P value of 0.3605 and df value of 76 was observed among mango genotypes studied. The numerical value of the ratio dN/dS (0.45) indicated a pure selection in the examined gene and the absence of any key changes. Cluster analysis differentiated the mango used in this research (M. indica L.) into two genotypes but could not differentiate their geographical locations. The results of this study indicated that a high genetic distance exists between HajiGholam (Manojan) and Arbabi (Rodan) genotypes and showed higher genetic diversity in mango of Rodan region. Results of present study suggested that for successful breeding, the genotypes of Rodan region mango especially Arbabi mango can be used as a gene donor and ITS can be a suitable tool for genetic evaluations of inter and intra species

    Techno−Typologie des assemblages lithiques. Garm Roud 2, un site de plein air au paléolithique supérieur (Baliran, Amol, Mazandarn).

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    International audienceIntroduction - Iranian plateau with its outstanding geographical and climatic conditions has been considered a key region in the study of Pleistocene human societies. So far numerous Paleolithic sites have been discovered throughout Iran; however, our knowledge concerning the Upper Paleolithic occupations was limited to Zagros region. The Upper Paleolithic occupations of northern Alborz Mountains and southern Caspian Sea has been remained unknown. In this context, the discovery of the open air site of Garmrud 2 by the French-Iranian Paleoanthropological Project (FIPP) in 2005 was a major breakthrough in case of filling the mentioned gaps between older Paleolithic materials and those of Mesolithic from the southeastern of the Caspian Sea (e.g., Komishan, Huto, Kamarband, Al Tepe). Materilas and Methods The southeastern of the Caspian Sea is a strategic region for those interested in prehistoric human movements and dispersions. This regain is one of the proposed migratory corridors for prehistoric societies. The studied area is located between two geographical barriers: in the north is located the Caspian Sea and in the south of the Alborz Mountains. Between these barriers, there are Mazandaran and Gilan Plains with high rate of precipitations and numerous permanent and seasonal rivers. Such geographical conditions have made these plains so fertile, and attracted human societies since prehistoric times. Even today this area represents one of the densest human populations in Iran.Results and Discussion - First, it was Carlton S. Coon who conducted several field missions at the southeastern of the Caspian Sea leading to the discovery and excavation of two famous caves of Huto and Kamarband (Coon, 1951, 1952). Later Charles McBurney from University of Cambridge followed Coon’s footsteps and excavated sites of Key-Aram I and Al Tepe (Ali Tepe). In most recent years, another Mesolithic site (Komishan Cave) was excavated in the region (Vahdati Nasab et al., 2011). The astonishing point conserving these sites chronology is the fact that none belonged to the Upper Paleolithic (Key-Aram I consist of Middle Paleolithic and Mousterian materials and the rest was assigned to the Mesolithic period). For some reasons it was believed that the Upper Paleolithic is the lost period in the north and northeastern of Alborz. Similar scenarios have been observed in Turkmenistan and Tajikistan, which provoked some researchers to claim due to some climatic obstacles of these geographical regions were abandoned during the Upper Paleolithic period. That is why the discovery of a well dated site of Garm Rud 2 could shed light on some of the key aspects of this enigma. This site, which is situated at the river cut of Garm Rud River nearby the Baliran village in Amol, has witnessed three consecutive excavations producing immense amount of data in form of lithic, bones, and shells. The absolute calibrated dating of 33878±3300 plus dominance of balde/ bladelet knapping technologies leave no room for any doubt to associate Garm Rud 2 with the Upper Paleolithic period. Evidence of fauna remains in close association with lithic materials indicates that Garm Rud 2 was a butchering station, which was occupied for a brief time period. Lithic assemblages of the first excavation season were the subject of this research. In this regard, only 2.6% of the assemblage belongs to core/core fragments. Such fact plus low quantity of cortical pieces indicate that the initial preparation stages were taken place somewhere outside of the site. Bladelets are in largest quantity followed by flakes with no secondary edge work and blades. Considerable number of flake debitage implies that they have been byproducts of bladelet/blade production sequences.Conclusion - In case of comparative studies, Garm Rud 2 represents close affinities with the two Upper Paleolithic open air sites of Sefid-Ab and Delazian both located at the southern hills of Alborz Mountains. At the same time it deviates significantly from the Upper Paleolithic cave site of Yafteh in Zagros. Prior to apply any stylistic explanations, the geomorphological formations of these sites must be taken into considerations. In addition, the site formation and usage of the sites must be taken into account. Yafteh is a Karstic cave in Zagros, which based on its strategic location and abundance number of lithic/fauna materials had been a base camp during the beginning of the Upper Paleolithic period. On the other hand, as it was mentioned earlier Garm Rud 2 was a butchering station with short occupation period; therefore, comparing lithic techno-typologies of Yafteh and Garm Rud 2 might not provide comprehensive results. Up until present Garm Rud 2 is the only well dated Upper Paleolithic settlement at the north of Iranian plateau
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