The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3•5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.

Summary Background Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. Methods We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (U5MR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. Findings Global U5MR decreased from 71·2 deaths per 1000 livebirths (95% uncertainty interval [UI] 68·3–74·0) in 2000 to 37·1 (33·2–41·7) in 2019 while global NMR correspondingly declined more slowly from 28·0 deaths per 1000 live births (26·8–29·5) in 2000 to 17·9 (16·3–19·8) in 2019. In 2019, 136 (67%) of 204 countries had a U5MR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030, 154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9·65 million (95% UI 9·05–10·30) in 2000 and 5·05 million (4·27–6·02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3·76 million [95% UI 3·53–4·02]) in 2000 to 48% (2·42 million; 2·06–2·86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0·80 (95% UI 0·71–0·86) deaths per 1000 livebirths and U5MR to 1·44 (95% UI 1·27–1·58) deaths per 1...

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To meet the carbon neutrality target and Beautiful China goal, the co-control strategy of carbon emission and air pollution is crucial. The Beijing-Tianjin-Hebei region is a prominent cooperative development zone, which faces dual challenges of CO2 emission reduction and air pollution control. This study aims to find the co-benefit pathway for achieving both targets in Beijing-Tianjin-Hebei. Based on an innovative and integrated framework by linking the computable general equilibrium model, atmospheric environment analysis model and health impact assessment model, we analyze the mutual co-benefits of carbon reduction and air quality improvement by climate and environmental policies. The results show significant mutual effects of CO2 emission mitigation and air pollution reduction. From the regional view, air pollutants control and CO2 mitigation policies have a relatively higher synergistic emission reduction effect in Beijing and Tianjin than in Hebei. From the sector perspective, the energy supply and transport sectors have much higher co-effects with CO2 reduction, while climate change mitigation policies have the best co-effects with air pollution reduction in the energy supply and residential sectors. Moreover, the health benefits in the air pollution control scenario (6.0 BUSD) are higher than in the decarbonization scenario (5.7 BUSD). In addition, climate mitigation policies could have tremendous synergistic air pollution reductions, even the health benefits (5.7 BUSD) may be insufficient to offset the cost (18.7 BUSD) of climate policy in the current situation. In order to better achieve the dual climate and air quality targets at lower costs, two types of policies should be better coordinated in the decision-making process.

Objective. To explore the application of targeted nursing in the care of elderly patients with severe pneumonia and its influence on psychological state and sleep quality. Methods. 90 elderly patients with severe pneumonia treated in our hospital from January 2019 to January 2020 were chosen for the study and split into the control group and the experimental group, with 45 cases in each group. Routine nursing was performed to the control group, and the targeted nursing was introduced on this basis to the experimental group to compare their nursing satisfaction and inflammatory factor indicators, and evaluate their sleep quality and metal state by referring to the Pittsburgh Sleep Quality Index (PSQI) and Mental Status Scale in Non-Psychiatric Settings (MSSNS) before and after intervention. Results. Compared with the control group, the experimental group achieved significantly better PSQI scores (P<0.001), higher nursing satisfaction (P<0.05), and lower CRP indicators (P<0.001), TNF-a indicators (P<0.001), IL-6 indicators (P<0.005) as well as MSSNS scores (P<0.001). Conclusion. Performing targeted nursing to the elderly patients with severe pneumonia can effectively improve the clinical indexes, alleviate the negative emotions, and enhance the quality of life, which is worthy of application and promotion.