Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019
Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.
Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017
Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.
Burden of injury along the development spectrum: associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017
Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm—the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.
Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017
Background There are few data comparing clinical outcome and potential indications for routine post–myocardial infarction cardiac catheterization and revascularization of patients who sustain a non–Q-wave versus Q-wave infarct after thrombolytic therapy. Methods and Results A secondary analysis of 2634 patients enrolled in the TIMI II trial with a first myocardial infarction was performed to determine 6-week and 1-year cardiac event rates and identify clinical and angiographic differences between the 1867 patients (70.9%) who evolved a Q-wave infarct and the 767 patients (29.1%) who sustained a non–Q-wave infarct after treatment with intravenous thrombolytic therapy. Male sex (85.3% versus 75.6%; P <.001) and anterior wall infarcts (53.8% versus 43.7%; P <.001) were more frequent in the Q-wave versus the non–Q-wave group. During recombinant tissue-type plasminogen activator (rTPA) infusion, a greater percentage of non–Q-wave patients (37.3% versus 23.5%; P =.001) had normalization of initial ST-segment elevation. Infarct-related artery patency (TIMI flow grade 2 or 3) ( P =.02), complete infarct-related artery reperfusion (TIMI 3 flow grade) ( P <.001), and the percentage of patients with a predischarge resting left ventricular ejection fraction >55% ( P <.001) were greater in the non–Q-wave group. New congestive heart failure during hospitalization developed more frequently in Q-wave patients (18.9% versus 11.6%; P <.001). After 42 days, the occurrences of reinfarction ( P =.76), death ( P =.76), and combined death or reinfarction ( P =.43) were similar in patients assigned to the invasive or conservative postlytic management strategy, regardless of infarct type. One-year mortality was 3.4% versus 4.4% for non–Q-wave versus Q-wave infarct type, respectively ( P =.25). Conclusions Angiographic and clinical differences were observed between patients who present with initial ST-segment elevation and evolve early non–Q-wave versus Q-wave myocardial infarcts after treatment with rTPA, heparin, and aspirin. Early mortality and adverse clinical cardiac events in these patients are not significantly different after a conservative compared with an invasive treatment strategy, regardless of whether the infarct type is non–Q wave or Q wave.