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

Determining the Climate Calendar of Tourism in Sistan-Baluchestan Province, Iran

Sistan and Baluchestan Province spans five degrees latitude, with variations in natural phenomena, with cultural and historical resources and beautiful beaches in the south that have a great potential in attracting tourists. To investigate the relationship between climate and tourism, the climate index has been developed so that data are presented showing the individuals’ reactions to climate. The current study chose the tourist major cities of Iran and meteorological data was used to calculate the 20-year period up to 2012. In order to calculate the three climate indices (Predict Mean Vote - PMV, the Physiological Equivalent Temperature - PET and the Standard Effective Temperature - SET), RayMan software was used. These indices were then discussed and the spatial distribution of climatic comfort was represented in GIS environment. The most important national, religious, historical, and natural places in the province were presented and the climate calendar of tourism was identified. The results showed that tourism is concentrated in two periods, hot and cold. The cold period in southern cities such as Chabahar, Konarak and Sarbaz makes them tourist destinations, while the cities of Zahedan, Khash, Zabol, located at higher latitudes, are chosen tourist destination in spring and autumn. Summer has the highest thermal stress in the province

The Main Patterns in the Trend Change of Stomach Cancer Incidence amongst Selected African Countries

Aim. The current study aimed to investigate the trend changes of stomach cancer incidence amongst African countries and identify the main patterns. Methods. The annual reports of stomach cancer incidence rate (per 100,000 people) for males and females in 53 African countries from 1990 to 2016 were maintained from the World Health Organization archive. The growth mixture model was used for fitting the models in Mplus 7.4. The estimated linear trend in each pattern was characterized by intercept (the rate at 1990) and slope (the observed biennial trend changes), and finally, each country was grouped into a cluster with the most similar pattern. Results. Three main patterns for males and two main patterns for females were determined. For males, the first cluster, containing Cape Verde, Central African Republic, and Mauritius, showed a sharp fall, while countries in the second pattern including Algeria, Cote d'Ivoire, Egypt, Gambia, Libya, Malawi, Morocco, Namibia, Nigeria, and Tunisia were categorized in a pattern with a slight decrease, and other 43 countries were in the third pattern with a moderate falling trend. For females, 19 countries including Angola, Botswana, Burundi, Cape Verde, Central African Republic, Congo Republic, Equatorial Guinea, Ethiopia, Gabon, Kenya, Mali, Mauritius, Rwanda, Sao Tome and Principe, Sudan, Swaziland, Uganda, Zambia, and Zimbabwe were categorized in the moderate-to-high falling pattern, but the other 34 countries had a gentle downward pattern. Conclusion. Although most of the observed trends of stomach cancer were falling, only a few countries had experienced a favorable decreasing trend (three countries in male incidence and nineteen countries in female incidence). Therefore, taking effective actions to accelerate the observed falling trends seems necessary

Investigation of Antioxidant and Antimicrobial Effects of Methanolic Extracts of Berberis integerrima and Graminifolius tragopogon

Background and Objective: Medicinal plants contain a high level of antioxidant compounds such as flavonoids, phenolic, carotenoids, and tannins, which can be used to eliminate excess free radicals in the body. This study aimed to determine the total phenolic and flavonoid content and to investigate the antioxidant and antibacterial effects of Berberis integerrima and Graminifolius tragopogon methanolic extracts on some Gram-positive and Gram-negative microorganisms. Methods: In this descriptive-analytical study, methanolic extracts of B. integerrima and G. tragopogon were prepared using 80% methanol. Total phenol and flavonoid contents were determined by Folin–Ciocalteu and aluminum chloride colorimetric methods, respectively. The antioxidant capacity was assessed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity and reducing power methods. The antibacterial activity of the extracts of B. integerrima and G. tragopogon on Escherichia coli, Bacillus subtilis, Listeria monocytogenes, Staphylococcus aureus, and Salmonella typhimurium were determined by the disk diffusion method. Butylated hydroxytoluene and ciprofloxacin were used as positive controls for antioxidant activity and bacterial strains, respectively. Results: Total phenol and flavonoid compounds in the extracts of B. integerrima and G. tragopogon were 46.90±0.70 and 22.63±0.59 mg gallic acid per gram of extract and 5.61±0.01 and 46.74±0.81 mg quercetin per gram of extract, respectively. The extracts of B. integerrima and G. tragopogon showed significant antibacterial activity. B. subtilis and S. typhimurium showed the highest sensitivity and resistance to the extracts, respectively. Moreover, the extract of B. integerrima had the most potent inhibitory effect on the examined microorganisms. Conclusion: B. integerrima extract exhibits higher phenolic content, antioxidant properties, and antimicrobial activity than G. tragopogon extract

Association of Food Security with Atherogenic Glucose and Lipid Profile among Women: A Population-Based Cross-Sectional Study in Zabol, Southeast of Iran

Background and Aim: Food insecurity and poor quality of diet are among risk factors of cardiovascular diseases (CVD). The main objective of this study was to assess the association of food insecurity with atherogenic glucose and lipid profile in women. Materials and Methods: In this cross-sectional study, 630 women between 18 and 50 years of age were selected by cluster sampling and interviewed face-to-face. To assess the household’s food security status, we used a household food insecurity access scale (HFIAS) questionnaire, which its validity and reliability had been determined in the Iranian population. The serum levels of glucose (FBS), triglyceride (TG), total cholesterol (TC), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were measured and LDL/HDL, TC/HDL, and TG/HDL ratios were calculated. Results: The mean serum concentrations of TG and TG/HDL ratio were significantly higher in the women suffering from moderate and severe food insecurity compared to those in the food-secure women (p=0.002). Compared with the food secure group, women with moderate and severe food security were more likely to develop hypertriglyceridemia (adjusted OR, 1.63; p=0.018) and a high TG/HDL ratio (adjusted OR, 1.52; p=0.030). However, food security status showed no significant associations with the probability of having the impaired fasting glucose, hypercholesterolemia, high LDL, low HDL, and abnormal ratios of LDL/HDL and TC/HDL. Conclusion: Food insecurity may be associated with increased risk of hypertriglyceridemia and high TG/HDL in women

Seroprevalence of Brucellosis, Leptospirosis, and Q Fever among Butchers and Slaughterhouse Workers in South-Eastern Iran.

Zoonotic diseases can be occupational hazards to people who work in close contact with animals or their carcasses. In this cross-sectional study, 190 sera were collected from butchers and slaughterhouse workers in different regions of the Sistan va Baluchestan province, in Iran in 2011. A questionnaire was filled for each participant to document personal and behavioural information. The sera were tested for detection of specific IgG antibodies against brucellosis, leptospirosis, and Q fever (phase I and II) using commercial enzyme-linked immunosorbent assays (ELISA). The seroprevalence of brucellosis was 7.9%, leptospirosis 23.4%, and phase I and II of Q fever were 18.1% and 14.4%, respectively. The seroprevalence of Q fever and leptospirosis, but not brucellosis, varied among regions within the province (p = 0.01). Additionally, a significant relationship was found between seropositivity of Q fever and camel slaughtering (p = 0.04). Reduced seropositivity rate of brucellosis was associated with use of personal protective equipment (PPE) (p = 0.004). This study shows that brucellosis, leptospirosis and Q fever occur among butchers and slaughterhouse workers in this area

Map of Sistan va Baluchestan province in southeast Iran.

<p>Sampling from butchers and slaughterhouse workers was performed in the different counties of Sistan va Baluchestan province including: Zahak (Zh) and Zabol (Za) in the north, Zahedan (Zah), Iranshahr (Ir) and Khash (Kh) in the centre, and Saravan (Sav), Sarbaz (Sar), Nikshahr(N), Konarak (K) and Chabahar (Ch) in the south.</p

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundRegular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.MethodsThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.FindingsThe leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.InterpretationLong-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere