Association of Chlamydia trachomatis and Neisseria gonorrhoeae with female infertility: a systematic review and meta-analysis

Background Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) are commonly diagnosed sexually transmitted infections that have been associated with serious reproductive health outcomes for women. The association of CT and NG infection with female fertility is not completely established yet. This review aimed to determine the association of CT and NG with female infertility. Methods This systematic review and meta-analysis was conducted according to the PRISMA statement. We searched a range of electronic databases, including PubMed, Web of Science, Embase, and Scopus, from Sept 25, 2017 until February 1, 2021. From the 851 studies screened, 552 that failed to meet our eligibility criteria were excluded. Subsequently, we removed 290 studies for not having a possible correlation of CT and NG infections with female infertility. Nine studies comprising 1827 infertile patients met our inclusion criteria. Two investigators independently extracted a range of data. All analyses were performed using STATA (version 13.1, Stata Corp, College Station, TX, USA). Results CT infection potentiates female infertility, as 76.47% of the included studies found a positive correlation between them. However, due to the limited number of reported data, we were not able to compare NG infection prevalence in fertile and non-fertile patients. Overall prevalences of CT and NG infections among infertile patients were 12 % and 3%, respectively, while CT infection prevalence among the fertile group was 7%. Conclusion The prevalences of CT and NG infections were high in infertile women. Screening and treatment of C. trachomatis and gonococcal infections during infertility treatment might increase the pregnancy rate

Evaluation of Antibacterial Activity of Pine Tar on Periodontal Pathogenic Bacteria: An In Vitro Study

BACKGROUND: Periodontal pathogens play an important role in etiology and pathogenesis of periodontitis. Microbiological examination of sub gingival plaque is used at the present time in etiological research as well as in clinical treatment of periodontitis to select the appropriate antibiotic agent if indicated. Pine tar has been used for the treatment of various skin diseases. So the study was done to evaluate the effect of Pine Tar oil on bacteria isolated from periodontitis patients.METHODS: Plaque samples from volunteer patients were collected using sterile paper points. Robertson's Cooked Meat (RCM) medium was used for the transportation and cultivation of aerobic, microaerophilic, and anaerobic microorganisms.RESULTS: The result suggests the use of Pine tar oil for topical application in periodontal diseases. Disc diffusion analysis was sufficient enough to illustrate that 75 μl tar oil solution produced growth inhibition of microbial strains.CONCLUSION: Pine tar oil has become one of the important areas of research both in pharmaceutical and periodontal research, hence in vivo studies has to be carried out with various form of pine tar.&nbsp

Exploring the Information Needs of Somaliland Pastoralists: Design Considerations for Digital Climate Adaptation Services

Pastoralists in Somaliland are suffering the impacts of climate change, and need relevant, timely, and practical information about water resources and pastures. However, these communities are sparsely distributed and distant from decision-making centres, which impedes rapid dissemination of climate-related information that could allow them to build resilience to climate impacts. Although smartphone adoption rates are low, mobile services are widespread across Somaliland, presenting opportunities for supporting communities through mobile technologies. We interviewed 30 Somali pastoralists to understand their climate information needs, access to technology, and the potential for technology support. We also conducted a focus group with four Somali development experts to explore the cultural context and possible impacts of different design choices. Our results highlight and explore tensions around different design directions, and suggest possible ways to mitigate these. Designing systems that navigate such considerations can contribute to much-needed climate resilience for pastoralist communities in Somaliland and beyond

The Impact of Age, Gender, Temporality, and Geographical Region on the Prevalence of Obesity and Overweight in Saudi Arabia: Scope of Evidence

OBJECTIVES: The objectives of this scoping review are to estimate the prevalence of obesity and overweight in the Saudi community and in different age groups, genders, and geographical location, in addition to the change in prevalence over time. METHODS: This scoping review of evidence was conducted in accordance with the Joanna Briggs Institute methodology for scoping reviews and was reported following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The population of this review was categorized into four age groups: young adults (18-25 years), adults (26-45), (mid-life adults) (46-60) and old people (60+). Each group was then categorized by gender into males and females. We included studies of adults aged 18 years and above. The pooled prevalence of obesity and overweight of the population, based on BMI, was estimated after stratification based on the age, gender, and geographical area. In addition, the change in the prevalence of obesity/overweight over time from 2011 to 2021 was investigated from the pooled data. The Metaprop program in Stata was used for statistical analysis. RESULTS: A total of 39 studies with 640,952 participants were included in this review. The pooled prevalence of obesity and overweight in the age group of ≤25 years old, including both genders, was 30%. However, it was higher in young males (40%) compared to young females (25%). The prevalence of obesity and overweight among young adults has dropped by over 40% between 2012 and 2021. The overall pooled prevalence rate of obesity and overweight in the age groups >25 years old (adults, mid-life, and old people), including both genders, was 66%, with similar prevalence among males (68%) and females (71%). In addition, a similar prevalence was observed among both adult and old people (62% and 65%, respectively), but was higher in the mid-life group (76%). Furthermore, mid-life women had the highest prevalence among all groups (87%), compared to 77% among males in the same age group. The same difference in prevalence between the gender persisted in older females compared to older males (79% vs. 65%, respectively). There is a noticeable drop in the pooled prevalence of overweight and obesity among adults > 25 years old of over 28% between 2011 and 2021. There was no difference in the prevalence of obesity/overweight by geographical region. CONCLUSIONS: Despite the noticeable drop in the prevalence of obesity in the Saudi community, the prevalence of high BMI is high in Saudi Arabia irrespective of age, gender, or geographical location. Mid-life women have the highest prevalence of high BMI, which makes them the focus of a tailored strategy for intervention. Further research is needed to investigate which are the most effective interventions to address obesity in the country

Systematic review and meta-analysis of the effectiveness of pre-pregnancy care for women with diabetes for improving maternal and perinatal outcomes.

BACKGROUND: Pre-gestational diabetes mellitus is associated with increased risk of maternal and perinatal adverse outcomes. This systematic review was conducted to evaluate the effectiveness and safety of pre-conception care (PCC) in improving maternal and perinatal outcomes. METHODS: Databases from MEDLINE, EMBASE, WEB OF SCIENCE, and Cochrane Library were searched, including the CENTRAL register of controlled trials, and CINHAL up until March 2019, without any language restrictions, for any pre-pregnancy care aiming at health promotion, glycemic control, and screening and treatment of diabetes complications in women with type I or type II pre-gestational diabetes. Trials and observational studies were included in the review. Newcastle-Ottawa scale and the Cochrane collaboration methodology for data synthesis and analysis were used, along with the GRADE tool to evaluate the body of evidence. RESULTS: The search identified 8500 potentially relevant citations of which 40 reports of 36 studies were included. The meta-analysis results show that PCC reduced congenital malformations risk by 71%, (Risk ratio (RR) 0.29; 95% CI: 0.21-0.40, 25 studies; 5903 women; high-certainty evidence). The results also show that PCC may lower HbA1c in the first trimester of pregnancy by an average of 1.27% (Mean difference (MD) 1.27; 95% CI: 1.33-1.22; 4927 women; 24 studies, moderate-certainty evidence). Furthermore, the results suggest that PCC may lead to a slight reduction in the risk of preterm delivery of 15%, (RR 0.85; 95% CI: 0.73-0.99; nine studies, 2414 women; moderate-certainty evidence). Moreover, PCC may result in risk reduction of perinatal mortality by 54%, (RR 0.46; 95% CI: 0.30-0.73; ten studies; 3071 women; moderate-certainty evidence). There is uncertainty about the effects of PCC on the early booking for antenatal care (MD 1.31; 95% CI: 1.40-1.23; five studies, 1081 women; very low-certainty evidence) and maternal hypoglycemia in the first trimester, (RR 1.38; 95% CI: 1.07-1.79; three studies; 686 women; very low- certainty evidence). In addition, results of the meta-analysis indicate that PCC may lead to 48% reduction in the risk of small for gestational age (SGA) (RR 0.52; 95% CI: 0.37-0.75; six studies, 2261 women; moderate-certainty evidence). PCC may reduce the risk of neonatal admission to intensive care unit (NICU) by 25% (RR 0.75; 95% CI: 0.67-0.84; four studies; 1322 women; moderate-certainty evidence). However, PCC may have little or no effect in reducing the cesarean section rate (RR 1.02; 95% CI: 0.96-1.07; 14 studies; 3641 women; low-certainty evidence); miscarriage rate (RR 0.86; 95% CI: 0.70-1.06; 11 studies; 2698 women; low-certainty evidence); macrosomia rate (RR 1.06; 95% CI: 0.97-1.15; nine studies; 2787 women, low-certainty evidence); neonatal hypoglycemia (RR 0.93; 95% CI: 0.74-1.18; five studies; 880 women; low-certainty evidence); respiratory distress syndrome (RR 0.78; 95% CI: 0.47-1.29; four studies; 466 women; very low-certainty evidence); or shoulder dystocia (RR 0.28; 95% CI: 0.07-1.12; 2 studies; 530 women; very low-certainty evidence). CONCLUSION: PCC for women with pre-gestational type 1 or type 2 diabetes mellitus is effective in improving rates of congenital malformations. In addition, it may improve the risk of preterm delivery and admission to NICU. PCC probably reduces maternal HbA1C in the first trimester of pregnancy, perinatal mortality and SGA. There is uncertainty regarding the effects of PCC on early booking for antenatal care or maternal hypoglycemia during the first trimester of pregnancy. PCC has little or no effect on other maternal and perinatal outcomes

Lectin-Dependent Enhancement of Ebola Virus Infection via Soluble and Transmembrane C-type Lectin Receptors

Mannose-binding lectin (MBL) is a key soluble effector of the innate immune system that recognizes pathogen-specific surface glycans. Surprisingly, low-producing MBL genetic variants that may predispose children and immunocompromised individuals to infectious diseases are more common than would be expected in human populations. Since certain immune defense molecules, such as immunoglobulins, can be exploited by invasive pathogens, we hypothesized that MBL might also enhance infections in some circumstances. Consequently, the low and intermediate MBL levels commonly found in human populations might be the result of balancing selection. Using model infection systems with pseudotyped and authentic glycosylated viruses, we demonstrated that MBL indeed enhances infection of Ebola, Hendra, Nipah and West Nile viruses in low complement conditions. Mechanistic studies with Ebola virus (EBOV) glycoprotein pseudotyped lentiviruses confirmed that MBL binds to N-linked glycan epitopes on viral surfaces in a specific manner via the MBL carbohydrate recognition domain, which is necessary for enhanced infection. MBL mediates lipid-raft-dependent macropinocytosis of EBOV via a pathway that appears to require less actin or early endosomal processing compared with the filovirus canonical endocytic pathway. Using a validated RNA interference screen, we identified C1QBP (gC1qR) as a candidate surface receptor that mediates MBL-dependent enhancement of EBOV infection. We also identified dectin-2 (CLEC6A) as a potentially novel candidate attachment factor for EBOV. Our findings support the concept of an innate immune haplotype that represents critical interactions between MBL and complement component C4 genes and that may modify susceptibility or resistance to certain glycosylated pathogens. Therefore, higher levels of native or exogenous MBL could be deleterious in the setting of relative hypocomplementemia which can occur genetically or because of immunodepletion during active infections. Our findings confirm our hypothesis that the pressure of infectious diseases may have contributed in part to evolutionary selection of MBL mutant haplotypes

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

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions