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

The spiritual pathway of Muharram mourning in Persian cities; A case study of Ardabil

Muharram commemoration to remember sacrifices made by Imam Hussein, the grandson of the Prophet Muhammad and his companions is one of the special and deep-rooted Islamic events, tied to spirituality for centuries. These processions are often held in specific routes or ‘mourning pathways. These paths and related spaces over time, in addition to being memorable and creating identity, have become spiritual in their own ways. But the contemporary Iranian urban planning pays more attention to material aspects and has moved away from spiritual spaces. Extensive physical changes and interventions in traditional cities, as well as threats and damage to mourning pathways, highlight the need for further research. This article, using comparative-qualitative studies and bringing evidence and numerous examples from different Iranian cities and emphasizing Ardabil, has tried to interpret the collected data, while proving and introducing mourning pathways as sacred and spiritual paths, determine their spiritual dimensions and aspects. The spiritual effects of mourning before and after the events along with their margins have been studied. The results show that various sacred-religious, physical-spatial, cultural-social, historical-political and natural factors constitute mourning pathways and then the socio-cultural dimension added weight to it. On the one hand, these pathways connect spaces to history, and on the other hand, they add a special symbolic and semantic dimension that distinguishes them from other paths

SUGGESTION OF AN EQUATION OF MOTION TO CALCULATE THE DAMPING RATIO DURING EARTHQUAKE BASED ON A CYCLIC PROCEDURE

Large horizontal relative displacements are naturally caused by seismic excitation, which is able to provide collisions between two adjacent buildings due to insufficient separation distance and severe damages due to impacts, especially in tall buildings. In this paper, the impact is numerically simulated and two needed parameters are calculated, including the impact force and energy absorption. In order to calculate the mentioned parameters, mathematical study is carried out to model an unreal link element, which is logically assumed to be a spring and dashpot to determine the lateral displacement and damping ratio of the impact. For the determination of the dynamic response of the impact, a new equation of motion is theoretically suggested to the evaluate impact force and energy dissipation. In order to confirm the rendered equation, a series of parametric studies are performed and the accuracy of the formulas is confirmed

An Artificial Bee Colony algorithm approach for locating optimal switch location in cellular mobile communication network

In this research, we use Artificial Bee Colony (ABC) algorithm to solve cell to switch assignment problem (CTSAP) that is NP-hard. In CTSAP, there are cells and switches in which cells locations are predetermined. The objective of problem is optimal assigning of cells to switches with minimum cost. Here, we have two kinds of costs, handoff and cabling costs. Call handling capacity for every switches are given and equal. The model of our work is single homed that is each cell must connect to only one switch. The mathematical model is binary and nonlinear. The program is coded by MATLAB 7.8.0 (R2009a). After estimating parameters values of model, approving performance accuracy of code and adjusting control parameters, the efficiency of algorithm by determining experimental problems compared to Ant Colony Optimization (ACO) that is one of the best for solving this problem. Results show satisfactory performance of ABC algorith

Modeling the problem of courses timetabling in a small educational institute

In this paper, we will consider the problem of courses timetabling in a small educational institute. We will present the mathematical model considering six hard constraints (compelling constraints) and five soft constraints (constraints that are lot compelling, but regarding them results increasing the utility of timetable). To formulating the model we will use a type of goal programming. In this paper we will try to define decision variables, hard constraints, soft constraints and objective function in a step by step direction. Afterward we will test the model on a mathematical example

Ranking evaluation factors in hospital information systems

Objective: Hospital information systems can improve the quality of health care. Evaluations of these systems use different methods and criteria. The present study ranked the most important factors influencing evaluation in various systems. Prioritizing the essential factors can increase the efficiency of the evaluation process and reduce the cost and time of evaluation by focusing on target factors. Methods: A survey of relevant literature extracted three main factors and 29 subfactors with which to design a study framework. The suggested framework includes three factors (organization, technical, and human), seven subfactors, 17 sub-subfactors, and five sub-sub-subfactors. A questionnaire format was developed using analytical hierarchy process and 28 paired comparisons using the Saaty scale. The questionnaires were completed by ten experts in health information management and medical informatics. Results: The findings ranked human factors, with a weight of 0.55, as the most important, followed by organization (0.25), and technology (0.19). Of the subfactors, security was accrued the most points (0.617) and work flow, with a weight of 0.827, was the most important among sub-subfactors. Conclusions: This study showed that multiple criteria decision-making methods such as analytical hierarchy process have the potential for use in health research and provide positive opportunities for health domain decision-makers

A genetic variation in the adenosine A2A receptor gene (ADORA2A) contributes to individual sensitivity to caffeine effects on sleep

Caffeine is the most widely used stimulant in Western countries. Some people voluntarily reduce caffeine consumption because it impairs the quality of their sleep. Studies in mice revealed that the disruption of sleep after caffeine is mediated by blockade of adenosine A2A receptors. Here we show in humans that (1) habitual caffeine consumption is associated with reduced sleep quality in self-rated caffeine-sensitive individuals, but not in caffeine-insensitive individuals; (2) the distribution of distinct c.1083T>C genotypes of the adenosine A2A receptor gene (ADORA2A) differs between caffeine-sensitive and -insensitive adults; and (3) the ADORA2A c.1083T>C genotype determines how closely the caffeine-induced changes in brain electrical activity during sleep resemble the alterations observed in patients with insomnia. These data demonstrate a role of adenosine A2A receptors for sleep in humans, and suggest that a common variation in ADORA2A contributes to subjective and objective responses to caffeine on sleep