To Örebro University

OBJECTIVE: To examine the effects of drug treatment for attention deficit/hyperactivity disorder (ADHD) on suicidal behaviours, substance misuse, accidental injuries, transport accidents, and criminality.

DESIGN: Emulation of target trials.

SETTING: Linkage of national registers in Sweden, 2007-20.

PARTICIPANTS: People aged 6-64 years with a new diagnosis of ADHD, who either started or did not start drug treatment for ADHD within three months of diagnosis.

MAIN OUTCOME MEASURES: First and recurrent events of five outcomes over two years after ADHD diagnosis: suicidal behaviours, substance misuse, accidental injuries, transport accidents, and criminality.

RESULTS: Of 148581 individuals with ADHD (median age 17.4 years; 41.3% female), 84282 (56.7%) started drug treatment for ADHD, with methylphenidate being the most commonly prescribed at initiation (74515; 88.4%). Drug treatment for ADHD was associated with reduced rates of the first occurrence of suicidal behaviours (weighted incidence rates 14.5 per 1000 person years in the initiation group versus 16.9 in the non-initiation group; adjusted incidence rate ratio 0.83, 95% confidence interval 0.78 to 0.88), substance misuse (58.7 v 69.1 per 1000 person years; 0.85, 0.83 to 0.87), transport accidents (24.0 v 27.5 per 1000 person years; 0.88, 0.82 to 0.94), and criminality (65.1 v 76.1 per 1000 person years; 0.87, 0.83 to 0.90), whereas the reduction was not statistically significant for accidental injuries (88.5 v 90.1 per 1000 person years; incidence rate ratio 0.98, 0.96 to 1.01). The reduced rates were more pronounced among individuals with previous events, with incidence rate ratios ranging from 0.79 (0.72 to 0.86) for suicidal behaviours to 0.97 (0.93 to 1.00) for accidental injuries. For recurrent events, drug treatment for ADHD was significantly associated with reduced rates of all five outcomes, with incidence rate ratios of 0.85 (0.77 to 0.93) for suicidal behaviours, 0.75 (0.72 to 0.78) for substance misuse, 0.96 (0.92 to 0.99) for accidental injuries, 0.84 (0.76 to 0.91) for transport accidents, and 0.75 (0.71 to 0.79) for criminality.

CONCLUSIONS: Drug treatment for ADHD was associated with beneficial effects in reducing the risks of suicidal behaviours, substance misuse, transport accidents, and criminality but not accidental injuries when considering first event rate. The risk reductions were more pronounced for recurrent events, with reduced rates for all five outcomes. This target trial emulation study using national register data provides evidence that is representative of patients in routine clinical settings.

Background: For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions.

Methods: The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010–23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution.

Findings: Total numbers of global DALYs grew 6·1% (95% UI 4·0–8·1), from 2·64 billion (2·46–2·86) in 2010 to 2·80 billion (2·57–3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0–14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31–1·61) global DALYs in 2010, increasing to 1·80 billion (1·63–2·03) in 2023, alongside a concurrent 4·1% (1·9–6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176–209] DALYs), stroke (157 million [141–172]), and diabetes (90·2 million [75·2–107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0–107·5]), depressive disorders (26·3% [11·6–42·9]), and diabetes (14·9% [7·5–25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837–917) in 2010 to 681 million (642–736) in 2023, and a 25·8% (22·6–28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7–61·0) for diarrhoeal diseases, 42·9% (38·0–48·0) for HIV/AIDS, and 42·2% (23·6–56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6–22·0) and 24·8% (7·4–36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7–19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18–1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation—with high SBP accounting for 8·4% (6·9–10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories—behavioural, metabolic, and environmental and occupational—risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8–37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0–11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023—eg, declining by 54·4% (38·7–65·3) for unsafe sanitation, 50·5% (33·3–63·1) for unsafe water source, and 45·2% (25·6–72·0) for no access to handwashing facility, and by 44·9% (37·3–53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [–2·7 to 15·6]; non-significant).

Interpretation: Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors—eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG—including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic—the complex interaction of multiple health risks, social determinants, and systemic challenges—will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity.

Background: Subclinical psychotic symptoms (SPS) are common among college students and can lead to future mental health issues. However, it is still not clear which specific childhood trauma, stressors and health factors lead to SPSs, partly due to confounding factors and multicollinearity.

Objective: To use machine learning to find the main predictors of SPS among university students, with special attention to gender differences.

Methods: A total of 21 208 university students were surveyed regarding SPS and a wide range of stress-related factors, including academic pressure, interpersonal difficulties and abuse. Nine machine learning models were used to predict SPS. We examined the relationship between SPS and individual stressors using χ 2 tests, multicollinearity analysis and Pearson heatmaps. Feature engineering, t-distributed stochastic neighborhood embedding (t-SNE) and Shapley Additive Explanation values helped identify the most important predictors. We also assessed calibration with calibration curves and Brier scores, and evaluated clinical usefulness with decision curve analysis (DCA) to provide a thorough assessment of the models. In addition, we validated this model using independent external data.

Findings: The Extreme Gradient Boosting (XGBoost) model had the best prediction results, with an Area Under the Curve (AUC) of 0.89, and validated with external data. It also showed good calibration, and DCA indicated clear clinical benefit. Interpersonal difficulties, academic pressure and emotional abuse emerged as the strongest predictors of SPS. Gender-stratified analyses revealed that academic pressure and emotional abuse affected males more, while health issues like chest pain and menstrual pain were stronger predictors for females.

Conclusions: Machine learning models effectively identified key stressors associated with SPS in university students. These findings highlight the importance of gender-sensitive approaches for the early detection and prevention of psychotic symptoms.

Clinical implications: SPSs in college students can be predicted by interpersonal difficulties, academic stress and childhood emotional abuse. This information can help mental health professionals develop better ways to prevent and address SPSs.

Stimulants such as methylphenidate (MPH) are the first-line pharmacological treatment for attention-deficit/hyperactivity disorder (ADHD). Although stimulants are effective at a group level, individual response varies, which advocates for tailored treatment approaches. Prior studies suggested that neurobiological measures following a single dose of stimulants are indicative of longer-term clinical response. To expand these findings, we tested whether an association between acute and longer-term treatment response can also be identified using measures commonly used in clinic. Sixty adults with ADHD completed clinico-neuropsychological measures, including the Barkley Adult ADHD Rating Scale-IV (BAARS-IV) and the Quantitative behavior (Qb) test, following a single dose of MPH (20 mg) and placebo. These measures were repeated after two-month MPH treatment to ascertain response. We tested associations between single-dose and longer-term response using univariate and multivariable (Lasso) regression approaches. We also ran correlations between predicted and true outcome measures. Univariate regressions showed significant associations between single-dose and two-month improvement in BAARS hyperactivity/impulsivity and Qb scores (all p < 0.001 but Qb activity, p = 0.006). Multivariable models including acute response and baseline clinicodemographic measures yielded significant correlations between predicted and actual values for all BAARS-IV and Qb scores at follow-up, except for BAARS inattention and Qb activity. Most had large/very large effect size (up to r = 0.69). These findings suggest that specific clinico-neuropsychological changes following a single dose of MPH may be indicative of longer-term treatment response, especially when combined with pre-treatment clinico-demographic characteristics. Once validated in larger and more heterogeneous samples, these results may support more informed and individualized treatment approaches for ADHD.

Background: Concerns about the cardiovascular safety of medications used for the treatment of attention-deficit hyperactivity disorder (ADHD) remain. We aimed to compare the effects of pharmacological treatments for ADHD on haemodynamic values and electrocardiogram (ECG) parameters in children, adolescents, and adults.

Methods: For this systematic review and network meta-analysis, we searched 12 electronic databases, including Cochrane CENTRAL, Embase, PubMed, and the WHO International Clinical Trials Registry Platform, from database inception to Jan 18, 2024, for published and unpublished randomised controlled trials comparing amphetamines, atomoxetine, bupropion, clonidine, guanfacine, lisdexamfetamine, methylphenidate, modafinil, or viloxazine against each other or placebo. Primary outcomes were change in systolic blood pressure (SBP) and diastolic blood pressure (DBP), measured in mm Hg, and pulse, measured in beats per minute, at timepoints closest to 12 weeks, 26 weeks, and 52 weeks. Summary data were extracted and pooled in random-effects network meta-analyses. Certainty of evidence was assessed with the Confidence in Network Meta-Analysis (CINeMA) framework. This study was registered with PROSPERO, CRD42021295352. Before study initiation, we contacted representatives of a UK-based charity of people with lived experience of ADHD—the ADHD Foundation—regarding the relevance of the topic and the appropriateness of the outcomes chosen.

Findings: 102 randomised controlled trials with short-term follow-up (median 7 weeks [IQR 5–9]) were included, encompassing 13 315 children and adolescents (aged ≥5 years and <18 years; mean age 11 years [SD 3]; of available data, 9635 [73%] were male and 3646 [27%] were female; of available data, 289 [2%] were Asian, 1719 [15%] were Black, and 8303 [71%] were White) and 9387 adults (≥18 years, mean age 35 years [11]; of available data, 5064 [57%] were male and 3809 [43%] were female; of available data, 488 [6%] were Asian, 457 [6%] were Black, and 6372 [79%] were White). Amphetamines, atomoxetine, lisdexamfetamine, methylphenidate, and viloxazine led to increments in haemodynamic values in children and adolescents, adults, or both. In children and adolescents, mean increase against placebo ranged from 1·07 (95% CI 0·36–1·79; moderate CINeMA confidence) with atomoxetine to 1·81 (1·05–2·57; moderate) with methylphenidate for SBP; from 1·93 (0·74–3·11; high) with amphetamines to 2·42 (1·69–3·15; low) with methylphenidate for DBP; and from 2·79 (1·05–4·53; moderate) with viloxazine to 5·58 (4·67–6·49; high) with atomoxetine for pulse. In adults, mean increase against placebo ranged from 1·66 (95% CI 0·38–2·93; very low) with methylphenidate to 2·3 (0·66–3·94; very low) with amphetamines for SBP; from 1·60 (0·29–2·91; very low) with methylphenidate to 3·07 (0·69–5·45; very low) with lisdexamfetamine for DBP; and from 4·37 (3·16–5·59; very low) with methylphenidate to 5·8 (2·3–9·3; very low) with viloxazine for pulse. Amphetamines, lisdexamfetamine, or methylphenidate were not associated with larger increments in haemodynamic values compared with atomoxetine or viloxazine in either children and adolescents or adults. Guanfacine was associated with decrements in haemodynamic values in children and adolescents (mean decrease against placebo of –2·83 [95% CI –3·8 to –1·85; low CINeMA confidence] in SBP, –2·08 [–3 to –1·17; low] in DBP, and –4·06 [–5·45 –2·68; moderate] in pulse) and adults (mean decrease against placebo of –10·1 [–13·76 to –6·44; very low] in SBP, –7·73 [–11·88 to –3·58; very low] in DBP, and –6·83 [–10·85 to –2·81; very low] in pulse). Only four RCTs informed on effects in the medium term and none on the long term.

Interpretation: Practitioners should monitor blood pressure and pulse in patients with ADHD treated with any pharmacological intervention, and not stimulants only. Given the short duration of available randomised controlled trials, new research providing insights on the causal effects of ADHD medications on cardiovascular parameters in the longer term should be funded. Funding National Institute for Health and Care Research.

In youth, lithium is an effective medication for mood disorders, particularly for mixed and manic episodes of bipolar disorder, and is generally well-tolerated. In some clinical contexts, lithium is used off-label to manage other conditions. We conducted a scoping review of studies on the efficacy/effectiveness and safety/tolerability of lithium for treating youths with psychiatric conditions other than mood disorders or neurological disorders. We searched EMBASE, MEDLINE, PsycINFO, PubMed, and ClinicalTrials.gov up to March 31, 2025, with no restrictions on language or document type. We included studies of any design involving children and adolescents (mean age up to 18) treated with lithium, either as monotherapy or in combination with other psychotropic agents. We assessed study quality using the appropriate NHLBI tools and visually summarized the results with a heat map displaying sample size by study design and conditions, as well as the timeline of included studies’ publication years. From 2,687 records initially identified, after de-duplication removal and screening, 367 full-text reports were assessed, and 41 studies were included in the review, grouped by type of psychiatric or neurological disorder, most of which had a small sample. Among the assessed studies, 60% of were considered of “fair” quality and 40% of “poor” quality. Overall, although the clinical use of lithium beyond bipolar disorder in youth is increasing, the underlying evidence base remains limited. More rigorous research based on RCTs and observational studies with designs aimed at reducing confounding are needed to guide clinical practice.

Background: Randomised controlled trials (RCTs) evaluating ADHD medications often use strict eligibility criteria, potentially limiting generalisability to patients in real-world clinical settings. We aimed to identify the proportion of individuals with ADHD who would be ineligible for medication RCTs and evaluate differences in treatment patterns and clinical and functional outcomes between RCT-eligible and RCT-ineligible individuals.

Methods: We used multiple Swedish national registries to identify individuals with ADHD, aged at least 4 years at the age of diagnosis, initiating pharmacological treatment between Jan 1, 2007, and Dec 31, 2019, with follow-up up to Dec 31, 2020. Hypothetical RCT ineligibility was established using exclusion criteria from the international MED-ADHD dataset, including 164 RCTs of ADHD medications. Cox models evaluated differences in medication switching and discontinuation within 1 year between eligible and ineligible individuals. Quasi-Poisson models compared eligible and ineligible individuals on rates of psychiatric hospitalisations, injuries or accidents, and substance use disorder within 1 year of initiating ADHD medications. People with lived experience of ADHD were not involved in the research and writing process.

Findings: Of 189 699 individuals included in the study cohort (112 153 men and boys [59%] and 77 546 women and girls [41%]; mean age 21·52 years [SD 12·83; range 4–68]) initiating ADHD medication, 53% (76 477 [74%] of 103 023 adults [aged >17 years], 12 658 [35%] of 35 681 adolescents [aged 13–17 years], and 10 643 [21%] of 50 995 children [aged <13 years]) would have been ineligible for RCT participation. Ethnicity data were not available. Ineligible individuals had a higher likelihood of treatment switching (hazard ratio 1·14, 95% CI 1·12–1·16) and a decreased likelihood of medication discontinuation (0·96, 0·94–0·98) compared with eligible individuals. Individuals ineligible for RCTs had significantly higher rates of psychiatric hospitalisations (ncidence rate ratio 9·68, 95% CI 9·57–9·78) and specialist care visits related to substance use disorder (14·78, 14·64–14·91), depression (6·00, 5·94–6·06), and anxiety (11·63, 11·56–11·69).

Interpretation: Individuals ineligible for ADHD medication trials face higher risks of adverse outcomes. This study provides the first empirical evidence for the limited generalisability of ADHD RCTs to real-world clinical populations, by applying eligibility criteria extracted from a comprehensive dataset of RCTs to a large real-world cohort. Triangulating evidence from RCTs and real-world studies is crucial to inform rigorous evidence-based treatment guidelines.

BACKGROUND: Understanding the relationship between mental and physical health conditions is crucial for developing comprehensive healthcare strategies. The putative existence of a general disease factor (d-factor) that underlies the vulnerability to both physical and mental conditions could have important implications for our approach to health assessment and treatment.

OBJECTIVE: To investigate the presence and characteristics of a general d-factor in children and adolescents.

METHODS: This Swedish registry-based cross-sectional study included children and adolescents born between 1996 and 2003 with follow-up until 2013. We extracted data on 25 mental and physical health conditions according to the ICD-10 system. To determine the optimal dimensional structure of these conditions, several competing measurement models were tested, including correlated factors, one factor, various bifactor specifications and bifactor exploratory structural equation modelling (ESEM).

FINDINGS: The study cohort included 776 667 individuals (mean age 13.96 years, IQR=11.96-16.04; 51% male). The bifactor ESEM model, including a general d-factor and specific mental and physical health factors, provided the best fit to the data compared to alternative models (Comparative Fit Index=0.971, Tucker-Lewis Index=0.962, root mean square error of approximation=0.007 (0.007-0.007)). The d-factor accounted for substantial variance (ω_h=0.582, explained common variance (ECV)=0.498), while specific mental (ω_hs=0.377, ECV=0.373) and physical (ω_hs=0.423; ECV=0.130) factors also indicated additional significant unique contributions.

CONCLUSIONS: This study provided evidence for a multidimensional structure of health in children and adolescents, characterised by a general d-factor underlying both mental and physical conditions, alongside distinct domain-specific factors. These findings have important implications for clinical practice, providing evidence that suggests the need for more integrated approaches to health assessment and treatment that consider the interconnectedness of mental and physical health.

Background

Comprehensive, comparable, and timely estimates of demographic metrics—including life expectancy and age-specific mortality—are essential for evaluating, understanding, and addressing trends in population health. The COVID-19 pandemic highlighted the importance of timely and all-cause mortality estimates for being able to respond to changing trends in health outcomes, showing a strong need for demographic analysis tools that can produce all-cause mortality estimates more rapidly with more readily available all-age vital registration (VR) data. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is an ongoing research effort that quantifies human health by estimating a range of epidemiological quantities of interest across time, age, sex, location, cause, and risk. This study—part of the latest GBD release, GBD 2023—aims to provide new and updated estimates of all-cause mortality and life expectancy for 1950 to 2023 using a novel statistical model that accounts for complex correlation structures in demographic data across age and time.

Methods

We used 24 025 data sources from VR, sample registration, surveys, censuses, and other sources to estimate all-cause mortality for males, females, and all sexes combined across 25 age groups in 204 countries and territories as well as 660 subnational units in 20 countries and territories, for the years 1950–2023. For the first time, we used complete birth history data for ages 5–14 years, age-specific sibling history data for ages 15–49 years, and age-specific mortality data from Health and Demographic Surveillance Systems. We developed a single statistical model that incorporates both parametric and non-parametric methods, referred to as OneMod, to produce estimates of all-cause mortality for each age-sex-location group. OneMod includes two main steps: a detailed regression analysis with a generalised linear modelling tool that accounts for age-specific covariate effects such as the Socio-demographic Index (SDI) and a population attributable fraction (PAF) for all risk factors combined; and a non-parametric analysis of residuals using a multivariate kernel regression model that smooths across age and time to adaptably follow trends in the data without overfitting. We calibrated asymptotic uncertainty estimates using Pearson residuals to produce 95% uncertainty intervals (UIs) and corresponding 1000 draws. Life expectancy was calculated from age-specific mortality rates with standard demographic methods. For each measure, 95% UIs were calculated with the 25th and 975th ordered values from a 1000-draw posterior distribution.FindingsIn 2023, 60·1 million (95% UI 59·0–61·1) deaths occurred globally, of which 4·67 million (4·59–4·75) were in children younger than 5 years. Due to considerable population growth and ageing since 1950, the number of annual deaths globally increased by 35·2% (32·2–38·4) over the 1950–2023 study period, during which the global age-standardised all-cause mortality rate declined by 66·6% (65·8–67·3). Trends in age-specific mortality rates between 2011 and 2023 varied by age group and location, with the largest decline in under-5 mortality occurring in east Asia (67·7% decrease); the largest increases in mortality for those aged 5–14 years, 25–29 years, and 30–39 years occurring in high-income North America (11·5%, 31·7%, and 49·9%, respectively); and the largest increases in mortality for those aged 15–19 years and 20–24 years occurring in Eastern Europe (53·9% and 40·1%, respectively). We also identified higher than previously estimated mortality rates in sub-Saharan Africa for all sexes combined aged 5–14 years (87·3% higher in GBD 2023 than GBD 2021 on average across countries and territories over the 1950–2021 period) and for females aged 15–29 years (61·2% higher), as well as lower than previously estimated mortality rates in sub-Saharan Africa for all sexes combined aged 50 years and older (13·2% lower), reflecting advances in our modelling approach. Global life expectancy followed three distinct trends over the study period. First, between 1950 and 2019, there were considerable improvements, from 51·2 (50·6–51·7) years for females and 47·9 (47·4–48·4) years for males in 1950 to 76·3 (76·2–76·4) years for females and 71·4 (71·3–71·5) years for males in 2019. Second, this period was followed by a decrease in life expectancy during the COVID-19 pandemic, to 74·7 (74·6–74·8) years for females and 69·3 (69·2–69·4) years for males in 2021. Finally, the world experienced a period of post-pandemic recovery in 2022 and 2023, wherein life expectancy generally returned to pre-pandemic (2019) levels in 2023 (76·3 [76·0–76·6] years for females and 71·5 [71·2–71·8] years for males). 194 (95·1%) of 204 countries and territories experienced at least partial post-pandemic recovery in age-standardised mortality rates by 2023, with 61·8% (126 of 204) recovering to or falling below pre-pandemic levels. There were several mortality trajectories during and following the pandemic across countries and territories. Long-term mortality trends also varied considerably between age groups and locations, demonstrating the diverse landscape of health outcomes globally.

Interpretation

This analysis identified several key differences in mortality trends from previous estimates, including higher rates of adolescent mortality, higher rates of young adult mortality in females, and lower rates of mortality in older age groups in much of sub-Saharan Africa. The findings also highlight stark differences across countries and territories in the timing and scale of changes in all-cause mortality trends during and following the COVID-19 pandemic (2020–23). Our estimates of evolving trends in mortality and life expectancy across locations, ages, sexes, and SDI levels in recent years as well as over the entire 1950–2023 study period provide crucial information for governments, policy makers, and the public to ensure that health-care systems, economies, and societies are prepared to address the world's health needs, particularly in populations with higher rates of mortality than previously known. The estimates from this study provide a robust framework for GBD and a valuable foundation for policy development, implementation, and evaluation around the world.

Background

Timely and comprehensive analyses of causes of death stratified by age, sex, and location are essential for shaping effective health policies aimed at reducing global mortality. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides cause-specific mortality estimates measured in counts, rates, and years of life lost (YLLs). GBD 2023 aimed to enhance our understanding of the relationship between age and cause of death by quantifying the probability of dying before age 70 years (70q0) and the mean age at death by cause and sex. This study enables comparisons of the impact of causes of death over time, offering a deeper understanding of how these causes affect global populations.MethodsGBD 2023 produced estimates for 292 causes of death disaggregated by age-sex-location-year in 204 countries and territories and 660 subnational locations for each year from 1990 until 2023. We used a modelling tool developed for GBD, the Cause of Death Ensemble model (CODEm), to estimate cause-specific death rates for most causes. We computed YLLs as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. Probability of death was calculated as the chance of dying from a given cause in a specific age period, for a specific population. Mean age at death was calculated by first assigning the midpoint age of each age group for every death, followed by computing the mean of all midpoint ages across all deaths attributed to a given cause. We used GBD death estimates to calculate the observed mean age at death and to model the expected mean age across causes, sexes, years, and locations. The expected mean age reflects the expected mean age at death for individuals within a population, based on global mortality rates and the population's age structure. Comparatively, the observed mean age represents the actual mean age at death, influenced by all factors unique to a location-specific population, including its age structure. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 250-draw distribution for each metric. Findings are reported as counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2023 include a correction for the misclassification of deaths due to COVID-19, updates to the method used to estimate COVID-19, and updates to the CODEm modelling framework. This analysis used 55 761 data sources, including vital registration and verbal autopsy data as well as data from surveys, censuses, surveillance systems, and cancer registries, among others. For GBD 2023, there were 312 new country-years of vital registration cause-of-death data, 3 country-years of surveillance data, 51 country-years of verbal autopsy data, and 144 country-years of other data types that were added to those used in previous GBD rounds.

Findings

The initial years of the COVID-19 pandemic caused shifts in long-standing rankings of the leading causes of global deaths: it ranked as the number one age-standardised cause of death at Level 3 of the GBD cause classification hierarchy in 2021. By 2023, COVID-19 dropped to the 20th place among the leading global causes, returning the rankings of the leading two causes to those typical across the time series (ie, ischaemic heart disease and stroke). While ischaemic heart disease and stroke persist as leading causes of death, there has been progress in reducing their age-standardised mortality rates globally. Four other leading causes have also shown large declines in global age-standardised mortality rates across the study period: diarrhoeal diseases, tuberculosis, stomach cancer, and measles. Other causes of death showed disparate patterns between sexes, notably for deaths from conflict and terrorism in some locations. A large reduction in age-standardised rates of YLLs occurred for neonatal disorders. Despite this, neonatal disorders remained the leading cause of global YLLs over the period studied, except in 2021, when COVID-19 was temporarily the leading cause. Compared to 1990, there has been a considerable reduction in total YLLs in many vaccine-preventable diseases, most notably diphtheria, pertussis, tetanus, and measles. In addition, this study quantified the mean age at death for all-cause mortality and cause-specific mortality and found noticeable variation by sex and location. The global all-cause mean age at death increased from 46·8 years (95% UI 46·6–47·0) in 1990 to 63·4 years (63·1–63·7) in 2023. For males, mean age increased from 45·4 years (45·1–45·7) to 61·2 years (60·7–61·6), and for females it increased from 48·5 years (48·1–48·8) to 65·9 years (65·5–66·3), from 1990 to 2023. The highest all-cause mean age at death in 2023 was found in the high-income super-region, where the mean age for females reached 80·9 years (80·9–81·0) and for males 74·8 years (74·8–74·9). By comparison, the lowest all-cause mean age at death occurred in sub-Saharan Africa, where it was 38·0 years (37·5–38·4) for females and 35·6 years (35·2–35·9) for males in 2023. Lastly, our study found that all-cause 70q0 decreased across each GBD super-region and region from 2000 to 2023, although with large variability between them. For females, we found that 70q0 notably increased from drug use disorders and conflict and terrorism. Leading causes that increased 70q0 for males also included drug use disorders, as well as diabetes. In sub-Saharan Africa, there was an increase in 70q0 for many non-communicable diseases (NCDs). Additionally, the mean age at death from NCDs was lower than the expected mean age at death for this super-region. By comparison, there was an increase in 70q0 for drug use disorders in the high-income super-region, which also had an observed mean age at death lower than the expected value.

Interpretation

We examined global mortality patterns over the past three decades, highlighting—with enhanced estimation methods—the impacts of major events such as the COVID-19 pandemic, in addition to broader trends such as increasing NCDs in low-income regions that reflect ongoing shifts in the global epidemiological transition. This study also delves into premature mortality patterns, exploring the interplay between age and causes of death and deepening our understanding of where targeted resources could be applied to further reduce preventable sources of mortality. We provide essential insights into global and regional health disparities, identifying locations in need of targeted interventions to address both communicable and non-communicable diseases. There is an ever-present need for strengthened health-care systems that are resilient to future pandemics and the shifting burden of disease, particularly among ageing populations in regions with high mortality rates. Robust estimates of causes of death are increasingly essential to inform health priorities and guide efforts toward achieving global health equity. The need for global collaboration to reduce preventable mortality is more important than ever, as shifting burdens of disease are affecting all nations, albeit at different paces and scales.