Our data, our society, our health: a vision for inclusive and transparent health data science in the UK and beyond

The last 6 years have seen sustained investment in health data science in the United Kingdom and beyond, which should result in a data science community that is inclusive of all stakeholders, working together to use data to benefit society through the improvement of public health and well-being. However, opportunities made possible through the innovative use of data are still not being fully realised, resulting in research inefficiencies and avoidable health harms. In this paper, we identify the most important barriers to achieving higher productivity in health data science. We then draw on previous research, domain expertise, and theory to outline how to go about overcoming these barriers, applying our core values of inclusivity and transparency. We believe a step change can be achieved through meaningful stakeholder involvement at every stage of research planning, design, and execution and team-based data science, as well as harnessing novel and secure data technologies. Applying these values to health data science will safeguard a social licence for health data research and ensure transparent and secure data usage for public benefit

The burden of diseases, injuries, and risk factors by state in the USA, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides a comprehensive assessment of health and risk factor trends at global, regional, national, and subnational levels. This study aims to examine the burden of diseases, injuries, and risk factors in the USA and highlight the disparities in health outcomes across different states. Methods: GBD 2021 analysed trends in mortality, morbidity, and disability for 371 diseases and injuries and 88 risk factors in the USA between 1990 and 2021. We used several metrics to report sources of health and health loss related to specific diseases, injuries, and risk factors. GBD 2021 methods accounted for differences in data sources and biases. The analysis of levels and trends for causes and risk factors within the same computational framework enabled comparisons across states, years, age groups, and sex. GBD 2021 estimated years lived with disability (YLDs) and disability-adjusted life-years (DALYs; the sum of years of life lost to premature mortality and YLDs) for 371 diseases and injuries, years of life lost (YLLs) and mortality for 288 causes of death, and life expectancy and healthy life expectancy (HALE). We provided estimates for 88 risk factors in relation to 155 health outcomes for 631 risk–outcome pairs and produced risk-specific estimates of summary exposure value, relative health risk, population attributable fraction, and risk-attributable burden measured in DALYs and deaths. Estimates were produced by sex (male and female), age (25 age groups from birth to ≥95 years), and year (annually between 1990 and 2021). 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws (ie, 500 random samples from the estimate's distribution). Uncertainty was propagated at each step of the estimation process. Findings: We found disparities in health outcomes and risk factors across US states. Our analysis of GBD 2021 highlighted the relative decline in life expectancy and HALE compared with other countries, as well as the impact of COVID-19 during the first 2 years of the pandemic. We found a decline in the USA's ranking of life expectancy from 1990 to 2021: in 1990, the USA ranked 35th of 204 countries and territories for males and 19th for females, but dropped to 46th for males and 47th for females in 2021. When comparing life expectancy in the best-performing and worst-performing US states against all 203 other countries and territories (excluding the USA as a whole), Hawaii (the best-ranked state in 1990 and 2021) dropped from sixth-highest life expectancy in the world for males and fourth for females in 1990 to 28th for males and 22nd for females in 2021. The worst-ranked state in 2021 ranked 107th for males (Mississippi) and 99th for females (West Virginia). 14 US states lost life expectancy over the study period, with West Virginia experiencing the greatest loss (2·7 years between 1990 and 2021). HALE ranking declines were even greater; in 1990, the USA was ranked 42nd for males and 32nd for females but dropped to 69th for males and 76th for females in 2021. When comparing HALE in the best-performing and worst-performing US states against all 203 other countries and territories, Hawaii ranked 14th highest HALE for males and fifth for females in 1990, dropping to 39th for males and 34th for females in 2021. In 2021, West Virginia—the lowest-ranked state that year—ranked 141st for males and 137th for females. Nationally, age-standardised mortality rates declined between 1990 and 2021 for many leading causes of death, most notably for ischaemic heart disease (56·1% [95% UI 55·1–57·2] decline), lung cancer (41·9% [39·7–44·6]), and breast cancer (40·9% [38·7–43·7]). Over the same period, age-standardised mortality rates increased for other causes, particularly drug use disorders (878·0% [770·1–1015·5]), chronic kidney disease (158·3% [149·6–167·9]), and falls (89·7% [79·8–95·8]). We found substantial variation in mortality rates between states, with Hawaii having the lowest age-standardised mortality rate (433·2 per 100 000 [380·6–493·4]) in 2021 and Mississippi having the highest (867·5 per 100 000 [772·6–975·7]). Hawaii had the lowest age-standardised mortality rates throughout the study period, whereas Washington, DC, experienced the most improvement (a 40·7% decline [33·2–47·3]). Only six countries had age-standardised rates of YLDs higher than the USA in 2021: Afghanistan, Lesotho, Liberia, Mozambique, South Africa, and the Central African Republic, largely because the impact of musculoskeletal disorders, mental disorders, and substance use disorders on age-standardised disability rates in the USA is so large. At the state level, eight US states had higher age-standardised YLD rates than any country in the world: West Virginia, Kentucky, Oklahoma, Pennsylvania, New Mexico, Ohio, Tennessee, and Arizona. Low back pain was the leading cause of YLDs in the USA in 1990 and 2021, although the age-standardised rate declined by 7·9% (1·8–13·0) from 1990. Depressive disorders (56·0% increase [48·2–64·3]) and drug use disorders (287·6% [247·9–329·8]) were the second-leading and third-leading causes of age-standardised YLDs in 2021. For females, mental health disorders had the highest age-standardised YLD rate, with an increase of 59·8% (50·6–68·5) between 1990 and 2021. Hawaii had the lowest age-standardised rates of YLDs for all sexes combined (12 085·3 per 100 000 [9090·8–15 557·1]), whereas West Virginia had the highest (14 832·9 per 100 000 [11 226·9–18 882·5]). At the national level, the leading GBD Level 2 risk factors for death for all sexes combined in 2021 were high systolic blood pressure, high fasting plasma glucose, and tobacco use. From 1990 to 2021, the age-standardised mortality rates attributable to high systolic blood pressure decreased by 47·8% (43·4–52·5) and for tobacco use by 5·1% (48·3%–54·1%), but rates increased for high fasting plasma glucose by 9·3% (0·4–18·7). The burden attributable to risk factors varied by age and sex. For example, for ages 15–49 years, the leading risk factors for death were drug use, high alcohol use, and dietary risks. By comparison, for ages 50–69 years, tobacco was the leading risk factor for death, followed by dietary risks and high BMI. Interpretation: GBD 2021 provides valuable information for policy makers, health-care professionals, and researchers in the USA at the national and state levels to prioritise interventions, allocate resources effectively, and assess the effects of health policies and programmes. By addressing socioeconomic determinants, risk behaviours, environmental influences, and health disparities among minority populations, the USA can work towards improving health outcomes so that people can live longer and healthier lives. Funding: Bill & Melinda Gates Foundation.</p

Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy across all countries (overall mean –0·18 years [95% UI –0·22 to –0·13]), with all countries having an absolute fall in life expectancy except for Ireland, Iceland, Sweden, Norway, and Denmark, which showed marginal improvement in life expectancy, and Belgium, which showed no change in life expectancy. Across countries, the causes of death responsible for the largest improvements in life expectancy from 1990 to 2011 were cardiovascular diseases and neoplasms. Deaths from cardiovascular diseases were the primary driver of reductions in life expectancy improvements during 2011–19, and deaths from respiratory infections and other COVID-19 pandemic-related outcomes were responsible for the decreases in life expectancy during 2019–21. Deaths from cardiovascular diseases and neoplasms in 2019 were attributable to high systolic blood pressure, dietary risks, tobacco smoke, high LDL cholesterol, high BMI, occupational risks, high alcohol use, and other risks including low physical activity. Exposure to these major risk factors differed by country, with trends of increasing exposure to high BMI and decreasing exposure to tobacco smoke observed in all countries during 1990–2021. Interpretation: The countries that best maintained improvements in life expectancy after 2011 (Norway, Iceland, Belgium, Denmark, and Sweden) did so through better maintenance of reductions in mortality from cardiovascular diseases and neoplasms, underpinned by decreased exposures to major risks, possibly mitigated by government policies. The continued improvements in life expectancy in five countries during 2019–21 indicate that these countries were better prepared to withstand the COVID-19 pandemic. By contrast, countries with the greatest slowdown in life expectancy improvements after 2011 went on to have some of the largest decreases in life expectancy in 2019–21. These findings suggest that government policies that improve population health also build resilience to future shocks. Such policies include reducing population exposure to major upstream risks for cardiovascular diseases and neoplasms, such as harmful diets and low physical activity, tackling the commercial determinants of poor health, and ensuring access to affordable health services. Funding: Gates Foundation.</p

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

BackgroundFuture 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.MethodsUsing 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.FindingsIn 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]).InterpretationGlobally, 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.FundingBill & Melinda Gates Foundation.</p