Occurrence of antibiotic-resistant Staphylococcus aureus in some street-vended foods in Ogun State, Nigeria

Staff PublicationFood borne illnesses of microbial origin are a major international health problem associated with food safety and an important cause of death in developing countries. This study was carried out to investigate the occurrence of antibiotic-resistant Staphylococcus aureus in some street-vended foods in Ogun State, Southwerstern Nigeria. A total of 140 street-vended food samples which included 20 samples each of fish sausages, meat sausages, fried fish, fried meat, fried yam, moin-moin and jollof rice were purchased from vendors in three different communities (Sabo, Isale-Oko and Makun) in Sagamu, Ogun State, Nigeria. Demographic survey was carried out on the hygienic and safety attitudes cultivated by the vendors recruited for this study. Microbiological analyses were carried out on the food products to isolate typical S. aureus strains. The samples were serially diluted and dilution factors of up 10-6 were cultured on Mannitol salt agar medium employing the spread plate technique. The disc-diffusion method was employed to determine the antibiotic resistance patterns of the isolated S. aureus strains. Most vendors were aware of the heath risk associated with unhygienic practices. Percentage products contaminated ranged from 0%, as obtained from fried yam, to 40% obtained from fish sausages. Prevalence of S. aureus strains obtained from samples ranged from 0 (as in fried yam) to 5.20 + 1.2 cfu ml-1 (as obtained from jollof rice). The isolates were subjected to antibiotic susceptibility assay employing the disc diffusion technique. Results on the resistance patterns of the isolated S. aureus strains revealed that resistance was highest to gentamycin (45.8%) and lowest to cotrimoxazole (4.2%) and erythromycin (4.2%). In conclusion, street vended food samples are frequently contaminated with S. aureus and that these could serve as potential vehicle for the transmission of resistant strains of the pathogen. Increased resistance of S. aureus to certain broad spectrum antibiotics such as gentamicin and amoxicillin should stimulate the interest of researchers

Partial Purification, Characterization and Application of Bacteriocin from Bacteria Isolated Parkia biglobosa Seeds

Staff PublicationBacteriocins are proteinaceous toxins produced by bacteria to inhibit the growth of similar or closely related bacterial strains. Fermented Parkia biglobosa seeds (African locust bean) were screened for bacteriocin-producing lactic acid bacteria (LAB) with the characterization of putative bacteriocins. Bacteriocin-producing lactic acid bacteria (LAB) were identified by 16s rDNA sequencing. Molecular sizes of the bacteriocins were determined using the tricine-sodium dodecyl sulphate-polyacrylamide gel electrophoresis (tricine-SDS–PAGE) and effects of enzymes, pH, detergents and temperature on bacteriocin activity investigated, using standard procedures. Bacteriocins production and activities were measured by spectrophotometric analysis. Statistical analysis was carried out using student t-test and Analyses of Variance. Bacteriocigenic LAB isolated were Lactobacillus plantarum Z1116, Enterococcus faecium AU02 and Leuconostoc lactis PKT0003. They inhibited the growth of both Gram-positive and Gram-negative bacteria. The sizes of bacteriocins Z1116, AU02 and PKT0003 were 3.2 kDa, 10 kDa and 10 kDa, respectively. The synergistic effects of characterized bacteriocins and rifampicin tested on organisms showed significant differences (P < 0.05), as compared with the effects of only one of the two. The antimicrobial activity of the three bacteriocins was deactivated after treatment of the cell-free supernatants with proteinase K, papain, pepsin and trypsin. Parkia biglobosa seeds are, therefore, rich in LAB bacteriocins which could be explored. The biosynthetic mechanisms of LAB bacteriocins could be employed in food safety and security, preservation, peptide design, infection control and pharmacotherapy. This should help in the control of undesirable bacteria and in designing more potent and selective antimicrobial peptides

Antimicrobial potency of Euphorbia heterophylla against selected clinical isolates

Reports on the antimicrobial potentials of Euphorbia heterophylla are scanty globally. This study investigated the antimicrobial effects of E. heterophylla against microorganisms of clinical importance. Cold water, hot water, chloroform and methanol extracts of the leaf, stem and fruit of E. heterophylla were obtained. The phytochemical properties of the plant parts were determined, and antimicrobial analyses of extracts investigated against sixteen clinical isolates, in accordance with standard procedures. The microorganisms tested were nine clinical bacterial strains which included Pseudomonas aeruginosa, Pseudomonas aeruginosa NCIB 950, Salmonella typhi, Escherichia coli, Escherichia coli NCIB 86, Staphylococcus aureus, Staphylococcus aureus NCIB 8588, Klebsiella pneumoniae and Serratia marcescens, and seven fungal strains which were Candida albicans, Aspergillus fumigatus, Aspergillus flavus, Aspergillus parasiticus, Trichoderma viride, Trichophyton rubrum, and Malassezia furfur. The qualitative and quantitative phytochemical analyses of extracts revealed the presence of steroids, alkaloids, flavonoids, tannins, terpenoids and carbohydrates at varying concentrations. Pseudomonas aeruginosa, Pseudomonas aeruginosa NCIB 950 and Candida albicans were sensitive to the cold water and hot water extracts of the plant’s parts while chloroform and methanol extracts did not show antimicrobial activities against any of the organisms. The MIC of the extracts ranged from 6.25 – 25 mg/mL. This study revealed that E. heterophylla is a promising plant species that could be employed in the treatment of infections caused by P. aeruginosa and C. albicans

ANTIBIOTICS RESISTANCE PROFILE OF ESCHERICHIA COLI AND ENTEROBACTER AEROGENES ISOLATED FROM WELL WATERS IN AGO-IWOYE, SOUTHWESTERN NIGERIA

Staff PublicationEighty percent of all diseases are attributed to unsafe water with about 11.4 billion people in the world suffering from major related diseases at various times. This study was carried out to investigate the antibiotics resistance profile of Escherichia coli and Enterobacter aerogenes isolated from well waters in Ago-Iwoye, Southwestern Nigeria. Water samples were collected from ten different wells. The multiple tube fermentation technique was employed to enumerate coliforms using MacConkey broth. Nutrient agar and ethylene methylene blue (EMB) agar were used for the enumeration of Escherichia coli and Enterobacter aerogenes. Biochemical characterization was carried out using standard methods. The disk diffusion method was used to determine the antibiotics susceptibility profiles of the bacterial isolates. Results showed that wells contained most probable number (MPN) of bacteria ranging from 43 to 1,100 bacteria per 100 ml. E. coli was present in eight of the wells while E. aerogenes was present in all the wells. Wells B and C had the highest incidence of E. coli with 5.0 x 102 CFU/100ml while wells D and J had no incidence of E. coli. Occurrence of Enterobacter aerogenes was highest in well B (4.5 x102 CFU/100ml), followed by well C (4.0 x102 CFU/100ml) while the lowest occurrence was obtained from well F having a count of 2.0 x 102 CFU/100ml. E. coli was resitant to nitrofurantoin, ampicillin, cephalocidine, sulphafurazole, carbenicillin and sulfamethazole while E. aerogenes was sensitive to colistin, gentamicin and nitrofurantoin but resistant to the remaining antibiotics of the Gram negative disc. For the U4 disc, E. coli was susceptible to colistin sulphate and resistant to all other antibiotics. E. aerogenes was resistant to the entire U4 discs. The presence of E. coli and E. aerogenes suggested faecal pollution, hence the quality of the wells fell strongly below the standard of safe drinking water. Most strains of isolates showed relative resistance to antibiotics investigated in this study and this should be of great concerns to researchers

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

Antibiotic Susceptibility Profiles of Bacteria from Diabetic Foot Infections in Selected Teaching Hospitals in Southwestern Nigeria

One of the serious complications associated with diabetes is foot ulcer and this condition affects the quality of life in patients in all classes, races and ages. Chronic wounds are prone to colonization by wide array of microorganisms which could be extremely hazardous to patients if effective and timely therapeutic intervention is not made. This study was conducted to determine the antibiotic susceptibility profiles of bacteria from diabetic foot infections in southwestern Nigeria. Samples were collected from a total of 142 diabetic foot ulcer patients with moistened sterile cotton swabs. Nutrient agar, Mac-Conkey agar, blood agar and mannitol salt agar media were used for the isolation of total viable bacteria, Gram-negative non-spore forming lactose fermenters, fastidious bacteria and staphylococci, respectively. Morphological and biochemical characteristics of pure cultures were determined in accordance with standard laboratory criteria. API 20 E and API 20 NE were used for the confirmation of identity of the bacterial isolates. The disc diffusion technique was employed for the determination of antibiotic susceptibility of bacterial isolates in accordance with standard procedures. The antibiotics investigated included amikacin, amoxicillin, ampicillin, ceftazidime, cefazolin, ceftriaxone, chloramphenicol, ciprofloxacin, clindamycin, gentamicin, imipenem, linezolid, methicillin, netilmicin, ofloxacin, oxacillin, penicillin, piperacilin, sulfamethoxazole, trimethoprim and vancomycin. One hundred and seventy-seven isolates were encountered and these were characterized into eleven bacterial species. These included Staphylococcus aureus (22.03%), Pseudomonas aeruginosa (16.95%), Staphylococcus epidermidis (12.43%), Proteus mirabilis (8.48%), Klebsiella pneumoniae (7.91%), E. coli (7.35%), Staphylococcus saprophyticus (6.78%), Streptococcus pyogenes (5.65%), Morganella morganii (5.09%), Citrobacter freundii (4.52%) and Acinetobacter baumannii (2.83%). Gram-negative bacteria showed 76.99% susceptibility to the antibiotics while 22.85% was resistant. Gram-positive bacteria showed 93.75% susceptibility and 5.01% resistance to the antibiotics. This study revealed that there is no definite aetiologic bacterial agent for diabetic foot infections and many of the associated bacteria are sensitive to certain antibiotics

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundAccurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. MethodsTo estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. FindingsDuring the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. InterpretationFertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world. FundingBill & Melinda Gates Foundation

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

BackgroundEstimates 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.Methods22 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.FindingsGlobal 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.InterpretationGlobal 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

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