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 of emergency abdominal surgery in high-, middle- and low-income countries

Background: Surgical mortality data are collected routinely in high-income countries, yet virtually no low- or middle-income countries have outcome surveillance in place. The aim was prospectively to collect worldwide mortality data following emergency abdominal surgery, comparing findings across countries with a low, middle or high Human Development Index (HDI). Methods: This was a prospective, multicentre, cohort study. Self-selected hospitals performing emergency surgery submitted prespecified data for consecutive patients from at least one 2-week interval during July to December 2014. Postoperative mortality was analysed by hierarchical multivariable logistic regression. Results: Data were obtained for 10 745 patients from 357 centres in 58 countries; 6538 were from high-, 2889 from middle- and 1318 from low-HDI settings. The overall mortality rate was 1⋅6 per cent at 24 h (high 1⋅1 per cent, middle 1⋅9 per cent, low 3⋅4 per cent; P < 0⋅001), increasing to 5⋅4 per cent by 30 days (high 4⋅5 per cent, middle 6⋅0 per cent, low 8⋅6 per cent; P < 0⋅001). Of the 578 patients who died, 404 (69⋅9 per cent) did so between 24 h and 30 days following surgery (high 74⋅2 per cent, middle 68⋅8 per cent, low 60⋅5 per cent). After adjustment, 30-day mortality remained higher in middle-income (odds ratio (OR) 2⋅78, 95 per cent c.i. 1⋅84 to 4⋅20) and low-income (OR 2⋅97, 1⋅84 to 4⋅81) countries. Surgical safety checklist use was less frequent in low- and middle-income countries, but when used was associated with reduced mortality at 30 days. Conclusion: Mortality is three times higher in low- compared with high-HDI countries even when adjusted for prognostic factors. Patient safety factors may have an important role. Registration number: NCT02179112 (http://www.clinicaltrials.gov)

Understanding Corrosion Degradation Processes of a Multi-Component CoNiCrAlY-Coating System

The thermal insulation and integrity of the thermal barrier coating is hampered by the formation of mixed oxide at intermediate bond coat. The existing reported work correlates growth of mixed oxide to the microstructural and phase changes. The track mostly used to study these changes is scanning electron microscopy, X-ray diffraction, and electrochemical testing. Oxide growth is principally an electrochemical process; hence a thirst exists to study this aspect by using advanced electrochemical techniques. In this study scanning electrochemical microscopy is used to reveal the electrochemical activity in the closest vicinity of the surface. A raster scan of 500 &micro;m area was carried out by microelectrode in an electrolyte at a distance of 5 &micro;m above the surface to record the current profile. The activity at the surface was confirmed by current distance curves. The tip of the microelectrode was approached from 60 &micro;m height to 2 &micro;m above the surface. The current&ndash;distance curves for the coating without heat-treatment show an active surface while the heat-treated one show non active surface. The average coating electrochemical response was further studied by polarization curves impedance spectroscopy. The X-ray photoelectron spectroscopy results show that oxidation and formation of the mixed oxide increase with polarization

An efficient S-box design scheme for image encryption based on the combination of a coset graph and a matrix transformer

Modern block ciphers deal with the development of security mechanisms to meet the security needs in several fields of application. The substitution box, which is an important constituent in block ciphers, necessarily has sufficient cryptographic robustness to counter different attacks. The basic problem with S-box design is that there is no evident pattern in its cryptographic properties. This study introduces a new mathematical algorithm for developing S-box based on the modular group coset graphs and a newly invented mathematical notion "matrix transformer". The proficiency of the proposed S-box is assessed through modern performance evaluation tools, and it has been observed that the constructed S-box has almost optimal features, indicating the effectiveness of the invented technique

Evaluation of Mechanical and Microstructural Properties and Global Warming Potential of Green Concrete with Wheat Straw Ash and Silica Fume

Cement and concrete are among the major contributors to CO2 emissions in modern society. Researchers have been investigating the possibility of replacing cement with industrial waste in concrete production to reduce its environmental impact. Therefore, the focus of this paper is on the effective use of wheat straw ash (WSA) together with silica fume (SF) as a cement substitute to produce high-performance and sustainable concrete. Different binary and ternary mixes containing WSA and SF were investigated for their mechanical and microstructural properties and global warming potential (GWP). The current results indicated that the binary and ternary mixes containing, respectively, 20% WSA (WSA20) and 33% WSA together with 7% SF (WSA33SF7) exhibited higher strengths than that of control mix and other binary and ternary mixes. The comparative lower apparent porosity and water absorption values of WSA20 and WSA33SF7 among all mixes also validated the findings of their higher strength results. Moreover, SEM&ndash;EDS and FTIR analyses has revealed the presence of dense and compact microstructure, which are mostly caused by formation of high-density calcium silicate hydrate (C-S-H) and calcium hydroxide (C-H) phases in both blends. FTIR and TGA analyses also revealed a reduction in the portlandite phase in these mixes, causing densification of microstructures and pores. Additionally, N2 adsorption isotherm analysis demonstrates that the pore structure of these mixes has been densified as evidenced by a reduction in intruded volume and a rise in BET surface area. Furthermore, both mixes had lower CO2-eq intensity per MPa as compared to control, which indicates their significant impact on producing green concretes through their reduced GWPs. Thus, this research shows that WSA alone or its blend with SF can be considered as a source of revenue for the concrete industry for developing high-performance and sustainable concretes

Lithium extraction from high magnesium salt lake brine with an integrated membrane technology

Lithium extraction is a great challenge from the high magnesium content salt solution. In this work, an integrated polyamide tight ultrafiltration (UF) and nanofiltration (NF) membranes are systematically investigated to separate Li+ from a high magnesium salt solution. Tight ultrafiltration UA001 and nanofiltration NF270 mem-branes in the integrated-cascade system not only increased Li+ permeation to 82.5 % but also enhanced the high Mg2+ retention to 94.6 % from the ternary salt solution of LiCl and MgCl2. The solution-diffusion transport model was also developed to calculate the real retention of Li+ and Mg2+, under constant pressure mode. The separation efficiency SFLi/Mg for the ternary salt solution of LiCl + MgCl2 + H2O was more than 15 at a constant pressure of 25 bars with an integrated membrane process, which was higher as compared to single-stage UF and NF270 membranes. Moreover, the high Mg2+/Li+ ratio was also reduced from 30 to 1.9 in the integrated-cascade membrane process

Lithium extraction from high magnesium salt lake brine with an integrated membrane technology

Lithium extraction is a great challenge from the high magnesium content salt solution. In this work, an integrated polyamide tight ultrafiltration (UF) and nanofiltration (NF) membranes are systematically investigated to separate Li+ from a high magnesium salt solution. Tight ultrafiltration UA001 and nanofiltration NF270 mem-branes in the integrated-cascade system not only increased Li+ permeation to 82.5 % but also enhanced the high Mg2+ retention to 94.6 % from the ternary salt solution of LiCl and MgCl2. The solution-diffusion transport model was also developed to calculate the real retention of Li+ and Mg2+, under constant pressure mode. The separation efficiency SFLi/Mg for the ternary salt solution of LiCl + MgCl2 + H2O was more than 15 at a constant pressure of 25 bars with an integrated membrane process, which was higher as compared to single-stage UF and NF270 membranes. Moreover, the high Mg2+/Li+ ratio was also reduced from 30 to 1.9 in the integrated-cascade membrane process

Computer-Aided Slope Stability Analysis of a Landslide&mdash;A Case Study of Jhika Gali Landslide in Pakistan

The present research study has been undertaken to carry out slope stability evaluation of the Jhika Gali landslide in Pakistan using GeoStudio. For this purpose, the site geometry of the existing slope adjacent to the slided one was measured and samples were collected from the site. The in-situ moisture content was 14% and dry unit weight was 18.63 kN/m3. Unconfined compression tests and unconsolidated-undrained (UU) triaxial tests were performed on samples reconstituted at in-situ dry unit weight, standard Proctor and modified Proctor maximum dry unit weights. The test results show that the shear strength and deformation parameters, i.e., undrained shear strength, angle of internal friction and deformation modulus decreased from 200 kPa to 90 kPa, 23&deg; to 12&deg; and 51 MPa to 32 MPa, respectively, with an increase in the percentage of saturation from 35% to 95% at a specific dry unit weight. The slope was also modeled in GeoStudio for limit equilibrium analysis, and slope stability analysis was performed using the values of undrained shear strength and the angle of internal friction as determined in the laboratory at varying degrees of saturation. The limit equilibrium analysis showed that the factor of safety reduces from 1.854 to 0.866 as the saturation of material increases from 35% to 95%. The results also suggest that, as the percentage of saturation increases above 85%, the soil loses its shear strength significantly and gains in bulk unit weight, so at this stage the material starts sliding. Additionally, slope stability analysis was carried out by changing the slope geometry in three different ways, i.e., by reducing the height of the slope, adding a counterweight at the toe of the slope and by making benches on the slope. The results of GeoStudio analysis showed that the slope will be stable even above 85% degree of saturation

Prediction of Mechanical Properties of Fly-Ash/Slag-Based Geopolymer Concrete Using Ensemble and Non-Ensemble Machine-Learning Techniques

The emission of greenhouse gases and natural-resource depletion caused by the production of ordinary Portland cement (OPC) have a detrimental effect on the environment. Thus, an alternative means is required to produce eco-friendly concrete such as geopolymer concrete (GPC). However, GPC has a complex cementitious matrix and an ambiguous mix design. Aside from that, the composition and proportions of materials utilized may have an impact on the compressive strength. Similarly, the use of robust and efficient machine-learning (ML) approaches is now required to forecast the strength of such a composite cementitious matrix. As a result, this study anticipated the compressive strength of GPC with waste resources using ensemble and non-ensemble ML algorithms. This was accomplished through the use of Anaconda (Python). To build a strong ensemble learner by integrating weak learners, adaptive boosting, random forest (RF), and ensemble learner bagging were employed. Furthermore, ensemble learners were utilized on non-ensemble or weak learners, such as decision trees (DT) and support vector machines (SVM) via regression. The data encompassed 156 statistical samples in which nine variables, namely superplasticizer (kg/m3), fly ash (kg/m3), ground granulated blast-furnace slag (GGBS), temperature (&deg;C), coarse and fine aggregate (kg/m3), sodium silicate (Na2SiO3), and sodium hydroxide (NaOH), were chosen to anticipate the results. Exploring it in depth, twenty sub-models with ensemble boosting and bagging approaches were trained, and tuning was performed to achieve the highest possible coefficient of determination (R2). Moreover, cross K-Fold validation analysis and statistical checks were performed via indicators for the evaluation of the models. The result revealed that ensemble approaches yielded robust performance compared to non-ensemble algorithms. Generally, an ensemble learner with the RF and bagging approach on a DT yielded robust performance by achieving a better R2 as 0.93, and with the lowest statistical errors. The communal model in artificial-intelligence analysis, on average, improved the accuracy of the model

Multi-Objective Optimization of Micro-Milling Titanium Alloy Ti-3Al-2.5V (Grade 9) Using Taguchi-Grey Relation Integrated Approach

This study aims to optimize the cutting parameters for the micro-milling of titanium grade 9 (Ti-3Al-2.5V). The research employs Grey Relational Analysis (GRA) and Response Surface Methodology (RSM) techniques to find the optimal combination of cutting parameters to simultaneously minimize surface roughness, burr width, burr length, and tool wear, which are selected process outcomes. The findings from Grey Relational Analysis (GRA) identify experiment number 6, with cutting conditions of f (µm/tooth) = 0.45, Vc (m/min) = 25, and ap (µm) = 60, as the most productive experiment. Analysis of variance (ANOVA) is conducted to assess the significance and influence of the process cutting parameters on different process outcomes. ANOVA reveals that the feed rate and cutting speed are the most influential input parameters, with a contribution ratio (CR) of 24.08% and 14.62%, respectively. Furthermore, ANOVA indicates that the interaction among the process parameters also significantly influences the process outcomes alongside the individual cutting parameters. The optimized combination of cutting parameters obtained through the RSM technique produces superior results in terms of reducing the process outcomes. Compared to the best run identified by Grey Relational Analysis, there is a remarkable 36.25% reduction in burr width and an 18.41% reduction in burr length, almost half of the reduction achieved in burr width. Additionally, there is a 16.11% and 14.60% reduction in surface roughness and tool wear, respectively