Suchergebnisse

BACKGROUND: Smoke-free legislation is an effective way to protect the population from the harms of secondhand smoke and has been implemented in many countries. On 31 May 2012, Tianjin became one of the few cities in China to implement smoke-free legislation. We investigated the impact of smoke-free legislation on mortality due to acute myocardial infarction (AMI) and stroke in Tianjin. METHODS: An interrupted time series design adjusting for underlying secular trends, seasonal patterns, population size changes and meteorological factors was conducted to analyse the impact of the smoke-free law on the weekly mortality due to AMI and stroke. The study period was from 1 January 2007 to 31 December 2015, with a 3.5-year postlegislation follow-up. RESULTS: Following the implementation of the smoke-free law, there was a decline in the annual trends of AMI and stroke mortality. An incremental 16% (rate ratio (RR): 0.84; 95% CI: 0.83 to 0.85) decrease per year in AMI mortality and a 2% (RR: 0.98; 95% CI: 0.97 to 0.99) annual decrease in stroke mortality among the population aged ≥35 years in Tianjin was observed. Immediate postlegislation reductions in mortality were not statistically significant. An estimated 10 000 (22%) AMI deaths were prevented within 3.5 years of the implementation of the law. CONCLUSION: The smoke-free law in Tianjin was associated with reductions in AMI mortality. This study reinforces the need for large-scale, effective and comprehensive smoke-free laws at the national level in China.

INTRODUCTION: The goal of reducing the burden of non-communicable diseases (NCDs) requires close monitoring. Our objective is to characterize the decline of premature NCD mortality in Brazil based on Global Burden of Diseases (GBD) Study 2019 estimates. METHODS: We used GBD 2019 data to estimate death rates of the four main NCDs - cardiovascular diseases, neoplasms, diabetes, and chronic respiratory diseases. We estimated the unconditional probability of death between ages 30 to 69, as recommended by the World Health Organization, as well as premature crude- and age-standardized death rates and disability-adjusted life years (DALYs) lost for these conditions. We also estimated trends in suicide (self-harm) death rates. RESULTS: From 2010 to 2019, the age-standardized unconditional probability of premature death declined -1.4%/year (UI: -1.7%;-1.0%) . Age-standardized death rates declined -1.5%/year (UI: -1.9%; -1.2%), and crude death rates -0.6%/year (UI: (-1.0%; -0.2%). Level of development correlated strongly with the rate of decline, with greatest declines occurring in the Southeast, Center West and South regions. Age-standardized mortality from self-harm declined, most notably in the elderly. CONCLUSIONS: Premature mortality due to the main NCDs has declined from 1990 in Brazil, although at a diminishing rate over time. The unconditional probability of death and the age-standardized mortality rate produced similar estimates of decline for the four main NCDs, and mirror well decline in mortality from all NCDs. Declines, especially more recent ones, fall short of the international goals. Strategic public health actions are needed. The challenge to implement them will be great, considering the political and economic instability currently faced by Brazil.

Background The burden of fatal police violence is an urgent public health crisis in the USA. Mounting evidence shows that deaths at the hands of the police disproportionately impact people of certain races and ethnicities, pointing to systemic racism in policing. Recent high-profile killings by police in the USA have prompted calls for more extensive and public data reporting on police violence. This study examines the presence and extent of under-reporting of police violence in US Government-run vital registration data, offers a method for correcting under-reporting in these datasets, and presents revised estimates of deaths due to police violence in the USA. Methods We compared data from the USA National Vital Statistics System (NVSS) to three non-governmental, open-source databases on police violence: Fatal Encounters, Mapping Police Violence, and The Counted. We extracted and standardised the age, sex, US state of death registration, year of death, and race and ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic of other races, and Hispanic of any race) of each decedent for all data sources and used a network meta-regression to quantify the rate of under-reporting within the NVSS. Using these rates to inform correction factors, we provide adjusted estimates of deaths due to police violence for all states, ages, sexes, and racial and ethnic groups from 1980 to 2019 across the USA. Findings Across all races and states in the USA, we estimate 30 800 deaths (95% uncertainty interval [UI] 30 300–31 300) from police violence between 1980 and 2018; this represents 17 100 more deaths (16 600–17 600) than reported by the NVSS. Over this time period, the age-standardised mortality rate due to police violence was highest in non-Hispanic Black people (0·69 [95% UI 0·67–0·71] per 100 000), followed by Hispanic people of any race (0·35 [0·34–0·36]), non-Hispanic White people (0·20 [0·19–0·20]), and non-Hispanic people of other races (0·15 [0·14– 0·16]). This variation is further affected by the decedent's sex and shows large discrepancies between states. Between 1980 and 2018, the NVSS did not report 55·5% (54·8–56·2) of all deaths attributable to police violence. When aggregating all races, the age-standardised mortality rate due to police violence was 0·25 (0·24–0·26) per 100 000 in the 1980s and 0·34 (0·34–0·35) per 100 000 in the 2010s, an increase of 38·4% (32·4–45·1) over the period of study. Interpretation We found that more than half of all deaths due to police violence that we estimated in the USA from 1980 to 2018 were unreported in the NVSS. Compounding this, we found substantial differences in the age-standardised mortality rate due to police violence over time and by racial and ethnic groups within the USA. Proven public health intervention strategies are needed to address these systematic biases. State-level estimates allow for appropriate targeting of these strategies to address police violence and improve its reporting. ; publishedVersion

BACKGROUND: The burden of ischemic heart disease (IHD) is high. There is limited information on the burden of IHD in identified high risk areas like Central Asia (CA) which is comprised of Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Turkmenistan, Mongolia, Uzbekistan and Tajikistan. This study addresses the burden of IHD in CA at the regional and country levels. METHODS: Using data from the latest iteration of the Global Burden of Disease Study (GBD), this study provides age-adjusted mortality, prevalence, and Disability Adjusted Life Years (DALYs) of IHD by sex in the CA region, and national levels for countries in this region from 1990 to 2017. RESULTS: The CA region has a higher IHD burden than the rest of the world over the studied period. Amongst the countries within this region, age-standardized mortality and DALY rates in Uzbekistan are the highest not only in CA but worldwide, while Armenia consistently has the lowest IHD burden in CA. Unhealthy diet, high systolic blood pressure and LDL-cholesterol are the risk factors with the highest attributable IHD DALYs. CONCLUSION: Increasing burden of IHD over time in CA can be partially explained by the economic crisis in the 1990s. There is considerable variation in IHD DALY rates among countries in the CA region. The reasons for such differences are likely multifactorial such as differences in risk factors distribution, health care effectiveness, political, social and economic factors.

BACKGROUND: Over the past few decades, economic, political, and social changes have directly and indirectly affected the health of the Mongolian population. To date, no comprehensive analysis has been conducted on the burden of diseases in this country. Thus, we aimed to describe the leading causes of death and disabling conditions and their trends between 1990 and 2019 in the Mongolian population. METHODS: We used the data from the Global Burden of Disease (GBD) 2019 study. In the current study, we examined life expectancy at birth, healthy life expectancy, the 20 leading causes of death, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted-life-years (DALYs), and the contribution of major risk factors to DALYs in Mongolia. FINDINGS: The life expectancy at birth in Mongolia has gradually increased since 1995 and reached 63.8 years for men and 72.7 for women in 2019. The highest increase in the age-standardised death rate between 1990 and 2019 occurred in alcohol use disorders (628.6%; 95% UI 10.0–1109.6) among men, and in liver cancer (129.1%; UI 65.3–222.4) among women. Ischaemic heart disease and stroke showed the highest rates of death, YLLs, and DALYs among both men and women. In 2019, the highest age-standardised rates of DALYs were attributable to high systolic blood pressure and dietary risks. INTERPRETATION: Although Mongolia saw substantial improvements across many communicable diseases, maternal and neonatal disorders, and under-5 mortality between 1990 and 2019, non-communicable diseases remained leading causes of mortality. The mortality from the most preventable causes such as injury, alcohol use, and dietary risks remain substantially high, suggesting that individual and social efforts are needed to tackle these diseases. Our analyses will support the development of policy priorities and action plans in multiple sectors to improve the overall health of the Mongolian population. FUNDING: Bill & Melinda Gates Foundation. SUPPLEMENTARY INFORMATION: The online version ...

AbstractIntroductionMisclassification of HIV deaths can substantially diminish the usefulness of cause of death data for decision‐making. In this study, we describe the methods developed by the Global Burden of Disease Study to account for the misclassified cause of death data from vital registration systems for estimating HIV mortality in 132 countries and territories.MethodsThe cause of death data were obtained from the World Health Organization Mortality Database and official country‐specific mortality databases. We implemented two steps to adjust the raw cause of death data: (1) redistributing garbage codes to underlying causes of death, including HIV/AIDS by applying methods, such as analysis of multiple cause data and proportional redistribution, and (2) reassigning HIV deaths misclassified as other causes to HIV/AIDS by examining the age patterns of underlying causes in location and years with and without HIV epidemics.ResultsIn 132 countries, during the period from 1990 to 2018, 1,848,761 deaths were reported as caused by HIV/AIDS. After garbage code redistribution in these 132 countries, this number increased to 4,165,015 deaths. An additional 1,944,291 deaths were added through correction of HIV deaths misclassified as other causes in 44 countries. The proportion of HIV deaths derived from garbage code redistribution decreased over time, from 0.4 in 1990 to 0.1 in 2018. The proportion of deaths derived from HIV misclassification correction peaked at 0.4 in 2006 and declined afterwards to 0.08 in 2018. The greatest contributors to garbage code redistribution were "immunodeficiency antibody" (ICD 9: 279‐279.1; ICD 10: D80‐D80.9) and "immunodeficiency other" (ICD 9: 279, 279.5‐279.9; ICD 10: D83‐D84.9, D89, D89.8‐D89.9), which together contributed 77% of all redistributed deaths at their peak in 1995. Respiratory tuberculosis (ICD 9: 010–012.9; ICD 10: A10‐A14, A15‐A16.9) contributed the greatest proportion of all HIV misclassified deaths (25–62% per year) over the most years.ConclusionsCorrecting for miscoding and misclassification of cause of death data can enhance the utility of the data for analyzing trends in HIV mortality and tracking progress toward the Sustainable Development Goal targets.

IMPORTANCE: US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how these amounts have changed over time. OBJECTIVE: To estimate US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. DESIGN AND SETTING: Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition. EXPOSURES: Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting. MAIN OUTCOMES AND MEASURES: National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016. RESULTS: Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product [GDP]; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by ...

BACKGROUND: Public health is a priority for the Chinese Government. Evidence-based decision making for health at the province level in China, which is home to a fifth of the global population, is of paramount importance. This analysis uses data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to help inform decision making and monitor progress on health at the province level. METHODS: We used the methods in GBD 2017 to analyse health patterns in the 34 province-level administrative units in China from 1990 to 2017. We estimated all-cause and cause-specific mortality, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), summary exposure values (SEVs), and attributable risk. We compared the observed results with expected values estimated based on the Socio-demographic Index (SDI). FINDINGS: Stroke and ischaemic heart disease were the leading causes of death and DALYs at the national level in China in 2017. Age-standardised DALYs per 100 000 population decreased by 33·1% (95% uncertainty interval [UI] 29·8 to 37·4) for stroke and increased by 4·6% (–3·3 to 10·7) for ischaemic heart disease from 1990 to 2017. Age-standardised stroke, ischaemic heart disease, lung cancer, chronic obstructive pulmonary disease, and liver cancer were the five leading causes of YLLs in 2017. Musculoskeletal disorders, mental health disorders, and sense organ diseases were the three leading causes of YLDs in 2017, and high systolic blood pressure, smoking, high-sodium diet, and ambient particulate matter pollution were among the leading four risk factors contributing to deaths and DALYs. All provinces had higher than expected DALYs per 100 000 population for liver cancer, with the observed to expected ratio ranging from 2·04 to 6·88. The all-cause age-standardised DALYs per 100 000 population were lower than expected in all provinces in 2017, and among the top 20 level 3 causes were lower than expected for ischaemic heart disease, Alzheimer's disease, ...

Through a comprehensive analysis of Italy's estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, we aimed to understand the patterns of health loss and response of the health-care system, and offer evidence-based policy indications in light of the demographic transition and government health spending in the country.