Change in global burden of unintentional drowning from 1990 to 2019 and its association with social determinants of health: findings from the Global Burden of Disease Study 2019.

OBJECTIVE: To systematically analyse global, regional and national burden change of unintentional drowning from 1990 to 2019, and to further quantify the contribution of social determinants of health (SDH) on the change. DESIGN: Data from the Global Burden of Disease Study 2019 were used in this study. SETTING AND PARTICIPANTS: Individuals of all ages and genders from 204 countries and territories. MAIN OUTCOME MEASURES: The main outcomes were the age-standardised rates (ASRs) of mortality and disability-adjusted life-years (DALYs) of unintentional drowning. The percentage change in the ASRs were used to estimate the joint effect of SDH on trends in global burden of drowning. RESULTS: We observed that the global burden of unintentional drowning declined markedly from 1990 to 2019, with age-standardised mortality rate and DALYs rate decreasing by 61.5% and 68.2%, respectively. Women, children, middle Socio-Demographic Index (SDI) countries, South-East Asia and Western Pacific region had higher reduction. At national level, greater reductions were observed in Armenia and Republic of Korea, but significant increases in Cabo Verde and Vanuatu. We found that every one percentile increase in six SDHs (Gross Domestic Product (GDP) per person, SDI, educational attainment, health spending, health workers and urbanisation) was associated with a decrease of 0.15% and 0.16% in drowning age-standardised mortality rate and DALYs rate globally, respectively. Health spending and GDP per capita were the main contributors to the reduction of drowning globally. CONCLUSIONS: The global burden of unintentional drowning significantly declined in the past three decades, and the improvement of SDHs such as GDP per capita and health spending mainly contributed to the decrease. Our findings indicate that improvement of SDHs is critical for drowning prevention and control.

Age-specific disparity in life loss per death attributable to ambient temperature: A nationwide time-series study in China.

Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006-2017. YLL was divided into three age groups (0-64 years, 65-74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0-64 years, 65-74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.

Urban-rural disparity of the short-term association of PM2.5 with mortality and its attributable burden.

Although studies have investigated the associations between PM2.5 and mortality risk, evidence from rural areas is scarce. We aimed to compare the PM2.5-mortality associations between urban cities and rural areas in China. Daily mortality and air pollution data were collected from 215 locations during 2014-2017 in China. A two-stage approach was employed to estimate the location-specific and combined cumulative associations between short-term exposure to PM2.5 (lag 0-3 days) and mortality risks. The excess risks (ER) of all-cause, respiratory disease (RESP), cardiovascular disease (CVD), and cerebrovascular disease (CED) mortality for each 10 µg/m3 increment in PM2.5 across all locations were 0.54% (95% confidence interval [CI]: 0.38%, 0.70%), 0.51% (0.10%, 0.93%), 0.74% (0.50%, 0.97%), and 0.52% (0.20%, 0.83%), respectively. Slightly stronger associations for CVD (0.80% versus 0.60%) and CED (0.61% versus 0.26%) mortality were observed in urban cities than in rural areas, and slightly greater associations for RESP mortality (0.51% versus 0.43%) were found in rural areas than in urban cities. A mean of 2.11% (attributable fraction [AF], 95% CI: 1.48%, 2.76%) of all-cause mortality was attributable to PM2.5 exposure in China, with a larger AF in urban cities (2.89% [2.12%, 3.67%]) than in rural areas (0.61% [-0.60%, 1.84%]). Disparities in PM2.5-mortality associations between urban cities and rural areas were also found in some subgroups classified by sex and age. This study provided robust evidence on the associations of PM2.5 with mortality risks in China and demonstrated urban-rural disparities of PM2.5-mortality associations for various causes of death.

Hospitalization Costs of COVID-19 Cases and Their Associated Factors in Guangdong, China: A Cross-Sectional Study.

Background: The ongoing COVID-19 pandemic has brought significant challenges to health system and consumed a lot of health resources. However, evidence on the hospitalization costs and their associated factors in COVID-19 cases is scarce. Objectives: To describe the total and components of hospitalization costs of COVID-19 cases, and investigate the associated factors of costs. Methods: We included 876 confirmed COVID-19 cases admitted to 33 designated hospitals from January 15th to April 27th, 2020 in Guangdong, China, and collected their demographic and clinical information. A multiple linear regression model was performed to estimate the associations of hospitalization costs with potential associated factors. Results: The median of total hospitalization costs of COVID-19 cases was $2,869.4 (IQR: $3,916.8). We found higher total costs in male (% difference: 29.7, 95% CI: 15.5, 45.6) than in female cases, in older cases than in younger ones, in severe cases (% difference: 344.8, 95% CI: 222.5, 513.6) than in mild ones, in cases with clinical aggravation than those without, in cases with clinical symptoms (% difference: 47.7, 95% CI: 26.2, 72.9) than those without, and in cases with comorbidities (% difference: 21.1%, 21.1, 95% CI: 4.4, 40.6) than those without. We also found lower non-pharmacologic therapy costs in cases treated with traditional Chinese medicine (TCM) therapy (% difference: -47.4, 95% CI: -64.5 to -22.0) than cases without. Conclusion: The hospitalization costs of COVID-19 cases in Guangdong were comparable to the national level. Factors associated with higher hospitalization costs included sex, older age, clinical severity and aggravation, clinical symptoms and comorbidities at admission. TCM therapy was found to be associated with lower costs for some non-pharmacologic therapies.

The association of compound hot extreme with mortality risk and vulnerability assessment at fine-spatial scale.

The frequency and intensity of compound hot extremes will be likely to increase in the context of global warming. Epidemiological studies have demonstrated the adverse effect of simple hot extreme events on mortality, but little is known about the effects of compound hot extremes on mortality. Daily meteorological, demographic, and mortality data during 2011-2017 were collected from 160 streets in Guangzhou City, China. We used distributed lag non-linear model (DLNM) to analyze the associations of different hot extremes with mortality risk in each street. Street-specific associations were then combined using a meta-analysis approach. To assess the spatial distribution of vulnerability to compound hot extremes, vulnerable characteristics at street level were selected using random forest model, and then we calculated and mapped spatial vulnerability index (SVI) at each street in Guangzhou. At street level, compared with normal day, compound hot extreme significantly increased mortality risk (relative risk(RR)=1.43, 95%CI:1.28-1.59) with higher risk for female (RR=1.54 [1.35-1.76]) and the elderly(RR for aged 65-74=1.41 [1.14-1.74]; RR for ≥75years=1.63 [1.45-1.84]) than male (RR=1.32 [1.15-1.52]) and population <65 years (RR=1.01 [0.83-1.22]). Areas with high vulnerability were in the urban center and the edge of suburban. High proportion of population over 64 years old in urban center, and high proportions of outdoor workers and population with illiteracy in suburban areas were the determinants of spatial vulnerability. We found that compound hot extreme significantly increased mortality risk at street level, which is modified by socio-economic and demographic factors. Our findings help allocate resources targeting vulnerable areas at fine-spatial scale.°.