Disease Burden and Prediction Analysis of Tracheal, Bronchus, and Lung Cancer Attributable to Residential Radon, Solid Fuels, and Particulate Matter Pollution Under Different Sociodemographic Transitions From 1990 to 2030.

BACKGROUND: This study investigated the impact of epidemiologic and sociodemographic changes in tracheal, bronchus, and lung cancer associated with residential radon, solid fuels, and particulate matter. RESEARCH QUESTION: What are the influencing factors of tracheal, bronchus, and lung cancer disease burden attributable to the three pollutants? STUDY DESIGN AND METHODS: Data were obtained from the Global Burden of Disease 2019. Age-standardized mortality rate (ASMR) and sociodemographic index (SDI) values were collected from 21 regions, and restricted cubic splines and quantile regression were used to investigate the relationship between ASMR or age-standardized disability-adjusted life years rate (ASDR), and SDI. Additionally, five countries with different SDIs were selected, and the Bayesian age-period-cohort model was used to predict the ASMR trends from 2020 to 2030. RESULTS: High SDI quintiles were associated with increased residential radon pollution. The disease burden attributed to these three pollutants was particularly severe in the middle SDI quintiles. Older adults aged 80 to 89 years had the highest age-specific mortality, and the disease burden was greater in male patients than in female patients with these cancers attributed to the pollutants. The highest ASMR attributable to particulate matter when the SDI was 0.7. As the SDI increased, the disease burden caused by radon increased, whereas the burden caused by solid fuels decreased. Projections have indicated a rise in the death burden in patients with this cancer from particulate pollution in China, India, and Uganda over the next decade. INTERPRETATION: The disease burden of tracheal, bronchus, and lung cancer attributed to the three pollutants was influenced by SDI, sex, and age. Older men are more susceptible to be affected. More preventive interventions may be required for men at younger ages to reduce the high death burden of older men. However, it is necessary to give due attention to women in specific countries in the future.

Disability weight measurement for the severity of different diseases in Wuhan, China.

BACKGROUND: Measurement of the Chinese burden of disease with disability-adjusted life-years (DALYs) requires disability weight (DW) that quantify health losses for all non-fatal consequences of disease and injury. The Global Burden of Disease (GBD) 2013 DW study indicates that it is limited by lack of geographic variation in DW data and by the current measurement methodology. We aim to estimate DW for a set of health states from major diseases in the Wuhan population. METHODS: We conducted the DW measurement study for 206 health states through a household survey with computer-assisted face-to-face interviews and a web-based survey. Based on GBD 2013 DW study, paired comparison (PC) and Population health equivalence (PHE) method was used and different PC/PHE questions were randomly assigned to each respondent. In statistical analysis, the PC data was analyzed by probit regression. The probit regression results will be anchored by results from the PHE data analyzed by interval regression on the DW scale units between 0 (no loss of health) and 1 (loss equivalent to death). RESULTS: A total of 2610 and 3140 individuals were included in the household and web-based survey, respectively. The results from the total pooled data showed health state "mild anemia" (DW = 0.005, 95% UI 0.000-0.027) or "allergic rhinitis (hay fever)" (0.005, 95% UI 0.000-0.029) had the lowest DW and "heroin and other opioid dependence, severe" had the highest DW (0.699, 95% UI 0.579-0.827). A high correlation coefficient (Pearson's r = 0.876; P < 0.001) for DWs of same health states was observed between Wuhan's survey and GBD 2013 DW survey. Health states referred to mental symptom, fatigue, and the residual category of other physical symptoms were statistically significantly associated with a lower Wuhan's DWs than the GBD's DWs. Health states with disfigurement and substance use symptom had a higher DW in Wuhan population than the GBD 2013 study. CONCLUSIONS: This set of DWs could be used to calculate local diseases burden for health policy-decision in Wuhan population. The DW differences between the GBD's survey and Wuhan's survey suggest that there might be some contextual or culture factors influencing assessment on the severity of diseases.

A Pre-Generation of Emergency Reference Plan Model of Public Health Emergencies with Case-Based Reasoning.

Background and Purpose: In the early 21st century, the coronavirus alone has ravaged the world three times. Public health emergencies have caused a tremendous negative impact on public health, daily life, and global economic development, for having the characteristics of complexity and great harm. To tackle these problems, a pre-generation of emergency reference plan model of public health emergencies is proposed to better deal with the outbreak and spread of public health events. Methods: The method is divided into three stages. First, the modified SEIR model is used to predict the attribute values of the target case. Then, the similar case sets are extracted and filtered by calculating the similarity through the cross-efficiency evaluation method with the parallel system. Finally, the multi-stage emergency effect evaluation model is conducted so that the emergency plan with the best response effect at this stage can be made for reference. Results: We collected 25 typical events of COVID-19 that occurred in 11 cities in China as historical case bases and target cases, respectively. The result of the experiment verified the feasibility and effectiveness of the proposed method. Conclusion: This paper presents a new perspective on making a public health emergency plan, which could improve the decision-making accuracy and efficiency, maximize the emergency effect and save precious time for emergency response. This model can provide rapid decision supports for decision-making for public services such as government departments, centers for disease control, medical emergency centers and transport authorities, etc.

Trends in Deaths Attributable to Smoking in China, Japan, United Kingdom, and United States From 1990 to 2019.

Objectives: This study aimed to estimate the long-term trends of deaths attributable smoking in China, Japan, the United Kingdom (UK) and the United States (US). Methods: Using 2000-2019 death data from Global Burden of Disease (GBD) 2019, we estimated age-period-cohort effects on smoking attributable mortality, and decomposed of differences in smoking-attributable deaths in 1990 and 2019 into demographic factors. Results: From 1990 to 2019, smoking-attributable deaths increased in China, which was due to population growth and demographic aging. From 1990 to 2019, both age-standardized smoking attributable mortality rates trended downward across countries. Among four countries, age rate ratios (RRs) for smoking-attributable mortality increased with age, while period and cohort RRs decreased with year. Conclusion: The age-standardized mortality rates, period effects and cohort effects of smoking attributable mortality in China, Japan, UK, and US have been declining in both sexes from 1990 to 2019, which suggests that smoke-free policies, help to quit tobacco use, improved health education, more accessible healthcare service, and increased taxes have been effective. Additionally, increased smoking attributable deaths in elderly should got more attention.

Burden of diabetes and kidney disease attributable to non-optimal temperature from 1990 to 2019: A systematic analysis from the Global Burden of Disease Study 2019.

INTRODUCTION: This study quantitatively described the disease burden of diabetes and kidney disease attributable to non-optimal temperatures and explored the influencing factors. METHODS: We quantitatively described the mortality burden of diabetes and kidney disease attributable to non-optimal temperatures in six countries (China, USA, South Africa, Australia, Iraq, Portugal), and compare trends in mortality in six countries from 1990 to 2019. We used the APC model to analyse age, period, and cohort effects on mortality in six countries. We used restricted cubic splines and quantile regression to analyse the association of SDI with mortality and YLL using data from 21 regions in the world. RESULTS: The mortality rates of diabetes and kidney disease in the six countries in 2019 were 1.72% (Australia), 1.83% (China), 2.99% (USA), 3% (Portugal), 7.45% (South Africa) and 8.71% (Iraq) attributable to non-optimal temperatures. Cold was more harmful than heat. The mortality, YLLs of diabetes and kidney disease of male were higher than females. The mortality rate showed an upwards trend with age. The period effect had little changes or showed a slight upwards trend. The cohort effect showed a downwards trend. The regions with higher mortality or YLLs rates were mainly had SDI values of 0.45-0.80. CONCLUSIONS: Among the death burdens of diabetes and kidney disease attributed to non-optimal temperatures, cold had a greater burden than heat. The burden of death was affected by sex, age, period, cohort, and SDI.

Impact of Particulate Matter on Hospitalizations for Respiratory Diseases and Related Economic Losses in Wuhan, China.

Background: Prior studies have reported the effects of particulate matter (PM) on respiratory disease (RD) hospitalizations, but few have quantified PM-related economic loss in the central region of China. This investigation aimed to assess the impacts of PM pollution on the risk burden and economic loss of patients admitted with RD. Methods: Daily cases of RD admitted to the hospital from 1 January 2015 to 31 December 2020 were collected from two class-A tertiary hospitals in Wuhan, China. Time series analysis incorporated with a generalized additive model (GAM) was adopted to assess the impacts of fine particulate matter (PM2.5) and inhalable particulate matter (PM10) exposures on patients hospitalized with RD. Stratified analyses were performed to investigate underlying effect modification of RD risk by sex, age, and season. The cost of illness (COI) approach was applied to evaluate the related economic losses caused by PM. Results: A total of 51,676 inpatients with a primary diagnosis of RD were included for the analysis. PM2.5 and PM10 exposures were associated with increased risks of hospitalizations for RD. Subgroup analysis demonstrated that men and children in the 0-14 years age group were more vulnerable to PM, and the adverse effects were promoted by low temperature in the cold season. A 152.4 million China Yuan (CNY) economic loss could be avoided if concentrations of PM2.5 and PM10 declined to 10 and 20 µg/m3, respectively. Conclusions: PM2.5 and PM10 concentrations were positively associated with RD hospitalization. Men and children were more vulnerable to PM. Effective air pollution control measures can reduce hospitalizations significantly and save economic loss substantially.

Trends in Disease Burden Attributable to Tobacco in China, 1990-2017: Findings From the Global Burden of Disease Study 2017.

In 2018, there were more than 371 million cigarette smokers and 12. 6 million electronic cigarette users, with 340.2 million non-smokers exposed to secondhand smoke (SHS) in China, which resulted in heavy tobacco-attributable disease burden. According to the definition by the Global Burden of Disease Study 2017 (GBD 2017), tobacco is a level 2 risk factor that consists of three sublevel risk factors, namely, smoking, SHS, and chewing tobacco. In this study, we aimed to evaluate the trends in deaths and disability-adjusted life years (DALYs) attributable to tobacco, smoking, SHS, and chewing tobacco by sex in China from 1990 to 2017 and to explore the leading causes of tobacco-attributable deaths and DALYs using data from the GBD 2017. From 1990 to 2017, the tobacco-attributable death rates per 100,000 people decreased from 75.65 [95% uncertainty interval (95% UI) = 56.23-97.74] to 70.90 (95% UI = 59.67-83.72) in females and increased from 198.83 (95% UI = 181.39-217.47) to 292.39 (95% UI = 271.28-313.76) in males. From 1990 to 2017, the tobacco-attributable DALY rates decreased from 2209.11 (95% UI = 1678.63-2791.91) to 1489.05 (95% UI = 1237.65-1752.57) in females and increased from 5650.42 (95% UI = 5070.06-6264.39) to 6994.02 (95% UI = 6489.84-7558.41) in males. In 2017, the tobacco-attributable deaths in China were concentrated on chronic obstructive pulmonary disease, ischemic heart disease, lung cancer, and stroke. The focus of tobacco control for females was SHS in 1990, whereas smoking and SHS were equally important for tobacco control in females in 2017. Increasing tobacco taxes and prices may be the most effective and feasible measure to reduce tobacco-attributable disease burdens.

How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs.

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this paper, we investigated why this might be so, by testing three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen and Swiss Franc-Japanese Yen exchange rates. Besides testing rising trends in these indicators at a strict level of confidence using the Kendall-tau test, we also required statistically significant early warning signals to be concurrent in the three indicators, which must rise to appreciable values. We then found for our data set the optimum parameters for discovering critical transitions, and showed that the set of critical transitions found is generally insensitive to variations in the parameters. Suspecting that negative results in the literature are the results of low data frequencies, we created time series with time intervals over three orders of magnitude from the raw data, and tested them for early warning signals. Early warning signals can be reliably found only if the time interval of the data is shorter than the time scale of critical transitions in our complex system of interest. Finally, we compared the set of time windows with statistically significant early warning signals with the set of time windows followed by large movements, to conclude that the early warning signals indeed provide reliable information on impending critical transitions. This reliability becomes more compelling statistically the more events we test.