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1. Is exposure to tobacco associated with extrahepatic cholangiocarcinoma epidemics? A retrospective proportional mortality study in China

Author: Lei Hou, Jingmei Jiang, Boqi Liu, Wei Han, Yanping Wu, Xiaonong Zou, Fang Xue, Yuanli Chen, Biao Zhang, Haiyu Pang, Yuyan Wang, Zixing Wang, Yaoda Hu, and Junyao Li
Subjects: Smoking, Cholangiocarcinoma, Mortality, Population, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background Extrahepatic cholangiocarcinoma (ECC) has become one of the most rapidly increasing malignancies in China during recent decades. The relationship between tobacco exposure and ECC epidemics is unclear; this study aimed to explore this relationship. Methods We included 55,806 participants aged 30 years or older from the National Mortality and Smoking Survey of China. Smoking in participants and spouses was defined as 1 cigarette or more per day for up to 1 year. Spouses’ smoking was taken as a measure of exposure to passive smoking. Smoking information in 1980 was ascertained and outcomes were defined as ECC mortality during 1986–1988. Results We found that either passive or active smoking increased the risk of death from ECC by 20% (risk ratio [RR], 1.20; 95% confidence interval [CI], 0.99–1.47), compared with no exposure to any tobacco. This risk was a notable 98% (RR, 1.98; 95% CI, 1.49–2.64) for individuals exposed to passive plus active smoking. These findings were highly consistent among men and women. Pathology-based analyses showed dose-response relationships of ECC with pack-years for all types of smoking exposure (Ps for trend
Published: 2019
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2. Interactions between life expectancy and the incidence and mortality rates of cancer in China: a population-based cluster analysis

Author: Xiuying Gu, Rongshou Zheng, Changfa Xia, Hongmei Zeng, Siwei Zhang, Xiaonong Zou, Zhixun Yang, He Li, and Wanqing Chen
Subjects: Cancer, Incidence, Mortality, Life expectancy, China, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Abstract Background The relationship between cancer and life expectancy is well established in both developed and developing countries. China is a vast country with significant geographical differences in population structure and healthcare, and thus provides a unique opportunity to analyze the complex relationship between life expectancy and cancer incidence and mortality rates. Methods Cancer data were extracted for a total of 255 units (cities or counties) from the 2013 National Central Cancer Registry. Life expectancy data at the unit level were obtained from the National Centers for Disease Control and Prevention. Linear regression analysis was used to analyze the relationship between life expectancy and crude incidence and mortality rates of cancer. In a separate analysis, life expectancy was rated as low ( 80 years). Results Overall, the cancer incidence and mortality rates positively correlated with life expectancy in both sexes (R at 0.37 and 0.50, P
Published: 2018
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3. Changing Epidemic of Lung Cancer & Tobacco and Situation of Tobacco Control in China

Author: Xiaonong ZOU, Manman JIA, Xin WANG, and Xiuyi ZHI
Subjects: Lung neoplasms, Smoking, Secondhand smoking, Tobacco control, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Lung cancer is the leading cause of cancer death and morbidity in China. Smoking and exposure to secondhand smoking closely related to lung cancer. Recently, series policies of tobacco control and lung cancer prevention was carried out. However, burden of lung cancer is still serious, and smoking rate in male is still very high, and in never smokers exposure to secondhand smoking is still very extensive. In this paper, epidemic situation of lung cancer, smoking and second hand smoking are described, at the same time, current implementations of tobacco control policies are summarized.
Published: 2017
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4. Effect of Smoking on Lung Cancer Histology and Its Epidemiology in Chinese Male

Author: Manman JIA, Jibin LI, Hua LIN, Xiaonong ZOU, and Ping ZHAO
Subjects: Lung neoplasms, Smoking history, Histology, Epidemiology, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Background and objective Studies found that there were changes in histological subtypes of lung cancer patients in China. This study investigated the effect of smoking on lung cancer histology and its trend in Chinese male. Methods Demographic, smoking history and histological information about male lung cancer patients diagnosed or treated from 2000 to 2012 was collected from Cancer Hospital, Chinese Academy of Medical Science. Trends of histological subtypes calculated with annual percentage change (APC). Results A total of 14,106 patients with lung cancer were enrolled, with smoking 11,750 cases and non-smoking 2,356 cases. The main histological type of smoking lung cancer was squamous cell carcinoma (SCC)(39.38%), followed by adenocarcinoma (ADC)(29.85%). Among smokers, the proportion of SCC decreased from 44.19% to 35.50% (APC=-1.9%, P
Published: 2017
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5. Changing cancer survival in China during 2003–15: a pooled analysis of 17 population-based cancer registries

Author: Hongmei Zeng, PhD, Wanqing Chen, ProfMD, Rongshou Zheng, MPH, Siwei Zhang, BCh, John S Ji, ScD, Xiaonong Zou, ProfMD, Changfa Xia, MPH, Kexin Sun, PhD, Zhixun Yang, BCh, He Li, BCh, Ning Wang, MD, Renqiang Han, MD, Shuzheng Liu, PhD, Huizhang Li, MD, Huijuan Mu, MD, Yutong He, ProfPhD, Yanjun Xu, MD, Zhentao Fu, MD, Yan Zhou, MD, Jie Jiang, MD, Yanlei Yang, BCh, Jianguo Chen, MD, Kuangrong Wei, ProfMD, Dongmei Fan, BCh, Jian Wang, BCh, Fangxian Fu, BCh, Deli Zhao, BCh, Guohui Song, BCh, Jianshun Chen, ProfBCh, Chunxiao Jiang, MD, Xin Zhou, MPH, Xiaoping Gu, BCh, Feng Jin, BCh, Qilong Li, MD, Yanhua Li, BCh, Tonghao Wu, BCh, Chunhua Yan, BCh, Jianmei Dong, BCh, Zhaolai Hua, PhD, Peter Baade, ProfPhD, Freddie Bray, PhD, Ahmedin Jemal, PhD, Xue Qin Yu, PhD, and Jie He, ProfMD
Subjects: Public aspects of medicine, RA1-1270
Abstract: Summary: Background: From 2003 to 2005, standardised 5-year cancer survival in China was much lower than in developed countries and varied substantially by geographical area. Monitoring population-level cancer survival is crucial to the understanding of the overall effectiveness of cancer care. We therefore aimed to investigate survival statistics for people with cancer in China between 2003 and 2015. Methods: We used population-based data from 17 cancer registries in China. Data for the study population was submitted by the end of July 31, 2016, with follow-up data on vital status obtained on Dec 31, 2015. We used anonymised, individual cancer registration records of patients (aged 0–99 years) diagnosed with primary, invasive cancers from 2003 to 2013. Patients eligible for inclusion had data for demographic characteristics, date of diagnosis, anatomical site, morphology, behaviour code, vital status, and last date of contact. We analysed 5-year relative survival by sex, age, and geographical area, for all cancers combined and 26 different cancer types, between 2003 and 2015. We stratified survival estimates by calendar period (2003–05, 2006–08, 2009–11, and 2012–15). Findings: There were 678 842 records of patients with invasive cancer who were diagnosed between 2003 and 2013. Of these records, 659 732 (97·2%) were eligible for inclusion in the final analyses. From 2003–05 to 2012–15, age-standardised 5-year relative survival increased substantially for all cancers combined, for both male and female patients, from 30·9% (95% CI 30·6–31·2) to 40·5% (40·3–40·7). Age-standardised 5-year relative survival also increased for most cancer types, including cancers of the uterus (average change per calendar period 5·5% [95% CI 2·5–8·5]), thyroid (5·4% [3·2–7·6]), cervix (4·5% [2·9–6·2]), and bone (3·2% [2·1–4·4]). In 2012–15, age-standardised 5-year survival for all patients with cancer was higher in urban areas (46·7%, 95% CI 46·5–47·0) than in rural areas (33·6%, 33·3–33·9), except for patients with oesophageal or cervical cancer; but improvements in survival were greater for patients residing in rural areas than in urban areas. Relative survival decreased with increasing age. The increasing trends in survival were consistent with the upward trends of medical expenditure of the country during the period studied. Interpretation: There was a marked overall increase in cancer survival from 2003 to 2015 in the population covered by these cancer registries in China, possibly reflecting advances in the quality of cancer care in these areas. The survival gap between urban and rural areas narrowed over time, although geographical differences in cancer survival remained. Insight into these trends will help prioritise areas that need increased cancer care. Funding: National Key R&D Program of China, PUMC Youth Fund and the Fundamental Research Funds for the Central Universities, and Major State Basic Innovation Program of the Chinese Academy of Medical Sciences.
Published: 2018
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6. Estimates of Lung Cancer Mortality at the Province Level in China

Author: Yuanqiu LI, Min DAI, Yuanli CHEN, Siwei ZHANG, Wanqing CHEN, Zhen DAI, and Xiaonong ZOU
Subjects: Lung neoplasms, Mortality, Statistical models, China, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Background and objective At present, population-based cancer registries were not well established and epidemiologic data for cancer were limited at the province level in China. Using the available mortality data for cancer, estimation model of lung cancer was established to provide the mortality profile for the population in 31 provincial regions in China in 2008. Methods Based on the population coverage and accuracy of the available mortality for provinces, the methods used to produce mortality estimates fall into 1 of the 3 categories: data were used directly; a model was developed to calculate annual change of mortality rate based on historical and current data; relative frequency data combining with mortality for all sites were used to estimate site-specific mortality. Results The total estimated deaths of lung cancer in 2008 were 493,348 (338,346 in males and 155,002 in females) in the whole country. The age-standardized rates were highest in Jilin (52.29 per 100,000 in males and 24.68 per 100,000 in females), and the lowest rates were in Tianjin (24.12 per 100,000 in males) and Chongqing (8.72 per 100,000 in females). Conclusion The models for lung cancer mortality at the province level have been established and the data will provide valuable scientific reference for describing the epidemic of lung cancer as well as estimating other site-specific cancer mortality in China.
Published: 2011

7. Case-Spouse Control Design in Practice: An Experience in Estimating Smoking and Chronic Obstructive Pulmonary Disease Deaths in Chinese Adults

Author: Jingmei Jiang, Boqi Liu, Freddy Sitas, Xianjia Zeng, Junshi Chen, Wei Han, Xiaonong Zou, Yanping Wu, Ping Zhao, and Junyao Li
Subjects: case-control studies, China, chronic obstructive pulmonary diseases, mortality, smoking, Medicine (General), R5-920
Abstract: We assessed the effect of smoking on death from chronic obstructive pulmonary disease (COPD) in China by employing a large population-based, case-spouse control study design using data from a nationwide survey of mortality. Methods: During 1989-1991, a nationwide retrospective survey of mortality was conducted in China. For approximately 1,000,000 adults dying from all causes during 1986-1988, their surviving spouses or other informants provided detailed information about their own as well as the deceased person's smoking history. For this study, 183,393 individuals who died of COPD at age ≥ 40 years were taken as cases, while 272,984 sex-matched surviving spouses of subjects who died from any cause were taken as controls. Results: COPD death rates for smokers were more than twice as high as those of non-smokers, with a dose-response risk pattern, despite the fact that COPD death rates varied widely by region and age. Tobacco accounted for 41.4% of COPD deaths in men, but only 13.5% of those in women, who had a lower rate of smoking. Conclusion: A case-spouse control study, as an alternative design, is valid and feasible in utilizing information from population-based, retrospective mortality survey data for an analytical epidemiological study of disease etiology.
Published: 2010
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8. Estimation and Projection of Lung Cancer Incidence and Mortality in China

Author: Xiaonong ZOU, Siwei ZHANG, and Wanqing CHEN
Subjects: Lung neoplasms, Incidence, Mortality, Epidemiology, Cancer registry, China, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Background and objective The aim of this study is to analyze lung cancer epidemiological trend and estimate lung cancer burden in China. Methods Lung cancer age specific mortality and incidence rate ratios in different areas and sexes were obtained from national cancer registration database in 2004 and 2005. Cancer crude mortalities were retrieved from the database of the third national death survey, 2004-2005. Age specific incidence rates of lung cancer were calculated using mortality and M/I ratios. Annual percent change (APC) was estimated by log regression model using Joint Point software by analyzing pooled lung cancer incidence data from 10 cancer registries from 1988 to 2005. Results The total estimated new cases and deaths of lung cancer in 2005 were 536 407 and 475 768 which were higher in male than in female. There was 1.63% increase of lung cancer incidence per year from 1988 to 2005, however, the trend showed a slowdown by 0.55% annually after adjusted by age. Conclusion Lung cancer is one of major health issues in China and the burden is getting serious. Ageing population is main cause for increasing incidence and mortality of lung cancer. Effective cancer prevention and control is imperative. Especially, tobacco control should be carried out in statewide.
Published: 2010

9. Association of cancer awareness levels with the risk of cancer in rural China: A population‐based cohort study

Author: Xiaonong Zou, Xiaoqin Cao, Xibin Sun, Shangchun Jia, Jialin Wang, Wanqing Chen, Lei Fan, Jinyi Zhou, Zhenqiu Zha, Rongshou Zheng, Maomao Cao, Jufang Shi, Pengfei Luo, Hongmei Zeng, He Li, Dianqin Sun, Hengmin Ma, and Shixian Feng
Subjects: Adult, Male, China, Cancer Research, Population, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Neoplasms, Cancer screening, Humans, Medicine, Prospective Studies, 030212 general & internal medicine, Prospective cohort study, education, Early Detection of Cancer, education.field_of_study, Cancer prevention, business.industry, Hazard ratio, Cancer, Middle Aged, medicine.disease, Oncology, 030220 oncology & carcinogenesis, Cohort, Female, business, Demography, Cohort study
Abstract: BACKGROUND Evidence of the effects of cancer prevention knowledge on the risk of developing cancer remains scarce. The objective of this study was to prospectively examine the association of cancer prevention awareness levels with cancer risk in a population-based cancer screening cohort in China. METHODS This prospective cohort study included 164,341 participants aged 40 to 69 years with no history of cancer and with available information on cancer prevention core knowledge in the Esophageal, Stomach, and Liver Cancer Screening Program. Participants were recruited from 18 rural regions across 4 provinces in China from 2007 to 2014 and were followed until December 31, 2015. The core knowledge of cancer prevention content included 9 items, with a total score ranging from 0 to 100. Cox proportional hazards regression models and restricted cubic spline analysis were used to estimate hazard ratios and 95% CIs. RESULTS High cancer prevention knowledge scores were inversely associated with the overall risk of cancer (group 4 vs group 1: hazard ratio, 0.669; 95% CI, 0.576-0.776). Subgroup analysis showed that this inverse association could be observed in women, participants with lower educational or income levels, and those without a family history of cancer. Restricted cubic spline analysis exhibited a nonlinear (L-shaped) relation between cancer knowledge scores and cancer risk (overall P
Published: 2020
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10. Tobacco smoking and trends in histological subtypes of female lung cancer at the Cancer Hospital of the Chinese Academy of Medical Sciences over 13 years

Author: Ji-Bin Li, Emily Vogtmann, Yan-Ling Wu, Man-Man Jia, Qinfu Feng, Qiang Zeng, Mark Parascandola, and Xiaonong Zou
Subjects: Adult, trends, 0301 basic medicine, Pulmonary and Respiratory Medicine, China, medicine.medical_specialty, Cancer Care Facilities, lcsh:RC254-282, smoking, histology, 03 medical and health sciences, 0302 clinical medicine, Lung neoplasms, Internal medicine, Tobacco Smoking, medicine, Humans, Stage (cooking), Lung cancer, Aged, Cancer staging, business.industry, Incidence (epidemiology), Cancer, Histology, Original Articles, General Medicine, Middle Aged, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, medicine.disease, female, 030104 developmental biology, Oncology, 030220 oncology & carcinogenesis, Adenocarcinoma, Original Article, Non small cell, business
Abstract: Background Lung cancer is the leading cause of cancer mortality among women in China, and incidence and mortality continue to rise despite the fact that smoking prevalence is very low among Chinese women. Aim This study investigated tobacco smoking and trends in histological subtypes of female lung cancer in a central cancer hospital in China. Methods Demographic, smoking history and histological information on female lung cancer patients diagnosed or treated from 2000 to 2012 was collected from the Cancer Hospital, Chinese Academy of Medical Science (CHCAMS). The classification of histological subtypes and clinical stages were conducted using the ICD-O-3 and Eighth AJCC Cancer Staging Manuals. Time-trends of histological subtypes were analyzed based on annual percentage change (APC). Results Overall, 5870 female cases of lung cancer were included in the analysis. The number of female lung cancer patients increased from 509 (2000-2002) to 1744 (2011-2012). The most common histological type of lung cancer was adenocarcinoma (ADC) (72.93%), followed by small cell lung cancer (SCLC) (11.06%), squamous cell carcinoma (SCC) (8.38%) and other (7.63%). Among smokers, the proportion of SCC decreased from 40.5% to 23.7% (P = 0.005), while ADC increased from 35.7% to 50.7% (P = 0.009). In non-smokers, ADC increased from 63.1% to 80.6% (P = 0.006) and SCC decreased from 13.6% to 4.5% (P = 0.016). Among SCC cases, smokers made up a larger proportion of early stage (I/II: 47.1%) compared with late stages (III, 34.3%; IV, 18.6%). Conclusion The number of female lung cancer patients has increased in CHCAMS. In both smoking and non-smoking cases, the proportion of adenocarcinoma increased. Squamous cell carcinomas were more likely to be diagnosed in early stages among smokers.
Published: 2019
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11. Provincial-level cancer burden attributable to active and second-hand smoking in China

Author: Mark Parascandola, Hongmei Zeng, Changfa Xia, Siwei Zhang, Zhixun Yang, He Li, Wanqing Chen, Rongshou Zheng, Farhad Islami, Maigeng Zhou, Kexin Sun, Xiaonong Zou, and Lijun Wang
Subjects: Adult, Male, Mainland China, China, Health (social science), Population, 03 medical and health sciences, 0302 clinical medicine, Beijing, Neoplasms, Surveys and Questionnaires, Humans, Medicine, Prospective Studies, 030212 general & internal medicine, Sex Distribution, education, Prospective cohort study, Aged, Aged, 80 and over, education.field_of_study, 030505 public health, business.industry, Smoking, Tobacco control, Public Health, Environmental and Occupational Health, Middle Aged, Relative risk, Attributable risk, Female, Tobacco Smoke Pollution, 0305 other medical science, business, Demography
Abstract: BackgroundUnderstanding disparities in the burden of cancer attributable to smoking is crucial to inform and improve tobacco control measures. In this report, we estimate the population attributable fraction (PAF) of cancers deaths attributable to smoking at the national and provincial levels in China.MethodsUsing cancer mortality data from 978 counties, smoking data from a nationwide survey and relative risks from a prospective study of 0.5 million adults in China, we calculated the absolute (non-standardised) and standardised numbers and proportions of cancer deaths among adults 30 years and older attributable to active and second-hand smoking in 2014 across all 31 provinces in Mainland China.ResultsThe estimated number of cancer deaths attributable to smoking in China in 2014 was 342 854 among men and 40 313 among women, of which second-hand smoking accounted for 1.8% and 50.0%, respectively. Among men, the absolute PAF in China was 23.8%, ranging from 14.6% in Xinjiang to 26.8% in Tianjin; the overall standardised PAF was 22.2%, ranging from 15.7% in Xinjiang to 26.0% in Guizhou. Among women, the overall absolute and standardised PAFs were 4.8% and 4.0%, ranging from 1.8% and 1.6% in Jiangxi to 14.9% and 9.6% in Heilongjiang, respectively. Overall, provinces with the highest standardised PAFs among men were located in Southwest China and among women in the Northeast.ConclusionsComprehensive smoke-free policies in China should expand to all provinces, notably those with a higher burden of cancer attributable to smoking, instead of being mostly limited to Beijing and some other metropolitan areas.
Published: 2018
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12. Cancer incidence and mortality in China, 2014

Author: Changfa Xia, Hongmei Zeng, He Li, Zhixun Yang, Kexin Sun, Rongshou Zheng, Siwei Zhang, Xiaonong Zou, Wanqing Chen, and Jie He
Subjects: 0301 basic medicine, Cancer Research, education.field_of_study, Cancer prevention, business.industry, Incidence (epidemiology), Mortality rate, Population, Cancer, medicine.disease, Cancer registry, Causes of cancer, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Oncology, 030220 oncology & carcinogenesis, Medicine, World Standard Population, Original Article, education, business, Demography
Abstract: Background National Central Cancer Registry of China (NCCRC) updated nationwide cancer statistics using population-based cancer registry data in 2014 collected from all available cancer registries. Methods In 2017, 449 cancer registries submitted cancer registry data in 2014, among which 339 registries' data met the criteria of quality control and were included in analysis. These cancer registries covered 288,243,347 population, accounting for about 21.07% of the national population in 2014. Numbers of nationwide new cancer cases and deaths were estimated using calculated incidence and mortality rates and corresponding national population stratified by area, sex, age group and cancer type. The world Segi's population was applied for age-standardized rates. Results A total of 3,804,000 new cancer cases were diagnosed, the crude incidence rate was 278.07/100,000 (301.67/100,000 in males, 253.29/100,000 in females) and the age-standardized incidence rate by world standard population (ASIRW) was 186.53/100,000. Calculated age-standardized incidence rate was higher in urban areas than in rural areas (191.6/100,000 vs. 179.2/100,000). South China had the highest cancer incidence rate while Southwest China had the lowest incidence rate. Cancer incidence rate was higher in female for population between 20 to 54 years but was higher in male for population younger than 20 years or over 54 years. A total of 2,296,000 cancer deaths were reported, the crude mortality rate was 167.89/100,000 (207.24/100,000 in males, 126.54/100,000 in females) and the age-standardized mortality rate by world standard population (ASMRW) was 106.09/100,000. Calculated age-standardized mortality rate was higher in rural areas than in urban areas (110.3/100,000 vs. 102.5/100,000). East China had the highest cancer mortality rate while North China had the lowest mortality rate. The mortality rate in male was higher than that in female. Common cancer types and major causes of cancer death differed between age group and sex. Conclusions Heavy cancer burden and its disparities between area, sex and age group pose a major challenge to public health in China. Nationwide cancer registry plays a crucial role in cancer prevention and control.
Published: 2018
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13. Spatial and temporal patterns of nasopharyngeal carcinoma mortality in China, 1973–2005

Author: Tingting Zuo, Xiaonong Zou, Changfa Xia, Yilan Liao, Jinfeng Wang, Siwei Zhang, Xue Qin Yu, Rongshou Zheng, Hongmei Zeng, Wanqing Chen, and Zhixun Yang
Subjects: Male, China, Cancer Research, Time Factors, Treatment - Resources and Infrastructure, Biology, Cancer Type - Head and Neck, 03 medical and health sciences, Age Distribution, 0302 clinical medicine, Cause of Death, otorhinolaryngologic diseases, medicine, Humans, 030212 general & internal medicine, Mortality, Sex Distribution, Retrospective Studies, Cause of death, Nasopharyngeal Carcinoma, Carcinoma, Nasopharyngeal Neoplasms, Health Status Disparities, medicine.disease, Health Surveys, stomatognathic diseases, Oncology, Nasopharyngeal carcinoma, 030220 oncology & carcinogenesis, Linear Models, Female, Demography
Abstract: We fitted generalized linear models using data from three national retrospective surveys on cause of death in China to explore the spatial and temporal patterns of nasopharyngeal carcinoma (NPC) mortality over the period 1973 to 2005. The results suggest that there was a significant decrease in NPC mortality in China over time (p < 0.0001), the mortality rate ratio (RR) for the two later time periods were 0.59 (95% CI: 0.55-0.64) for 1990-1992 and 0.42 (95% CI: 0.39-0.45) for 2004-2005 compared to that of 1973-1975. Residents living in the South China areas have an elevated risk of mortality from NPC compared to those living in North China across all three time periods, with the RR being 4.96 (95% CI: 4.31-5.70) in 1973-1975, 12.83 (95% CI: 10.73-15.34) in 1990-1992 and 15.20 (95% CI: 12.34-18.72) in 2004-2005. Although NPC mortality in most areas of China has reduced to very low levels, the widening geographical disparities in NPC mortality are still noteworthy. It may be necessary to target public health policies to address the widening geographical disparities in NPC mortality.
Published: 2017
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14. Incidence and Mortality of Childhood Cancer in China from 2000 to 2015

Author: Xiaonong Zou, Rongshou Zheng, Ru Chen, Wenqiang Wei, Shaoming Wang, Kexin Sun, Siwei Zhang, Jie He, and Hongmei Zeng
Subjects: Pediatrics, medicine.medical_specialty, education.field_of_study, business.industry, Incidence (epidemiology), Mortality rate, Population, Cancer, medicine.disease, Cancer registry, Causes of cancer, medicine, education, business, Kidney cancer, Disease burden
Abstract: Background: Cancer is a large challenge to child health. The epidemic characteristics of childhood cancer have not been well described in recent years in China. This study aimed to reveal the patterns and trends of childhood cancer from 2000 to 2015 using cancer registry data. Methods: We extracted cancer registry data for children between 0-14 years in China from National Cancer Registry System. We used cancer registry data of high quality in 2015 to estimate current nationwide childhood cancer incidence and mortality. We applied data from 22 registries with continuous data for trend analysis from 2000 to 2015 using Joinpoint regression models. The age-standardized rates were calculated using the world Segi’s population. Findings: In 2015, about 21,300 childhood cancer cases were diagnosed. The age-standardized incidence rate by world standard population (ASIRW) was 103.2/1,000,000. The five most common cancer types were leukaemia, brain tumor, lymphoma, bone tumor and kidney cancer. About 8,800 childhood cancer deaths were reported. The age-standardized mortality rate by world standard population (ASMRW) was 42.3/1,000,000. The five most common causes of cancer deaths were leukaemia, brain tumor, lymphoma, liver cancer and bone tumor. ASIRW for leukaemia (APC=3.4%, 95%CI: 2.4%~4.3%) and brain tumor (APC=1.9%, 95%CI: 0.5%~3.4%) in boys, and the ASIRW for leukaemia (APC=2.0%, 95%CI: 0.2%~3.9%) in girls increased significantly from 2000 to 2015. The ASMRW for lymphoma decreased significantly in boys from 2000 to 2015 (APC=-7.2%, 95%CI: -11.9%~-2.4%). Interpretation: Childhood cancer disease burden is heavy in China. The uptrend of childhood cancer incidence was driven mostly by increases of incidences for leukaemia and brain tumor, suggesting urgent needs for targeted childhood cancer prevention and control plans. Funding Statement: This study was supported by the National Key Research and Development Program of China (2018YFC1311704) and Major State Basic Innovation Program of the Chinese Academy of Medical Sciences (2018-I2M-3-003). Declaration of Interests: All authors declare no competing interests.
Published: 2020
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15. Oxidation behavior of RF sputter deposited zirconium diboride thin films

Author: Xiaonong Zou
Published: 2019
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16. Additional file 1: of Is exposure to tobacco associated with extrahepatic cholangiocarcinoma epidemics? A retrospective proportional mortality study in China

Author: Hou, Lei, Jingmei Jiang, Boqi Liu, Han, Wei, Yanping Wu, Xiaonong Zou, Xue, Fang, Yuanli Chen, Zhang, Biao, Haiyu Pang, Yuyan Wang, Zixing Wang, Yaoda Hu, and Junyao Li
Abstract: Table S1. Characteristics of excluded participants. Table S2. Association between exposure and deaths owing to extrahepatic cholangiocarcinoma, considering the assumed age of marriage. (DOCX 16 kb)
Published: 2019
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17. Economic burden of lung cancer attributable to smoking in China in 2015

Author: Guoxiang Liu, Ning Wu, Xiaonong Zou, Min Dai, Ni Li, Jiansong Ren, Wanqing Chen, Le Wang, Fang Li, Kai Zhang, Wei Tang, Jufang Shi, Rong Zheng, Huiyao Huang, Mark Parascandola, Chengcheng Liu, and Kai Su
Subjects: Adult, Male, China, Health (social science), Lung Neoplasms, Psychological intervention, Gross domestic product, 03 medical and health sciences, Indirect costs, 0302 clinical medicine, Age Distribution, Cost of Illness, Environmental health, Surveys and Questionnaires, Health care, medicine, Prevalence, Tobacco Smoking, Humans, 030212 general & internal medicine, Sex Distribution, Lung cancer, Aged, Aged, 80 and over, 030505 public health, Cancer prevention, business.industry, Mortality, Premature, Tobacco control, Public Health, Environmental and Occupational Health, Health Care Costs, Middle Aged, medicine.disease, Female, Health Expenditures, 0305 other medical science, business
Abstract: BackgroundLung cancer is substantially attributable to smoking, but detailed related estimates on smoking-attributable expenditure (SAE) in China are not available yet, which could inform tobacco control and cancer prevention initiatives.MethodsA prevalence-based approach was adopted to estimate the total SAE, including direct expenditure (medical and non-medical) and indirect cost (disability and premature death). Detailed per-patient data on direct expenditure and work-loss days were acquired from a unique multicentre survey in China. Other parameters were from literatures and official reports.ResultsThe total estimated SAE of lung cancer was US$5249 million in China in 2015 (0.05 % of gross domestic product for China). The estimated direct SAE was US$1937 million (36.9 % of the total SAE), accounting for 0.29 % of total healthcare expenditure for China. The medical and non-medical direct expenditures were US$1749 million and US$188 million, respectively. The estimated indirect cost was US$3312 million (63.1 % of the total SAE), including US$377 million due to disability and US$2935 million due to premature death. The SAE increased with age, peaking at 60–64 years (US$1004 million), and was higher among men, in urban areas and in eastern China. If smoking prevalence was reduced to 20%, as is the goal of Healthy China 2030, the total SAE would be decreased by 4.9 %.ConclusionsSmoking-attributable economic burden caused by lung cancer was substantial in China in 2015, and will continue increasing given current trends in lung cancer. However, future economic burden can be prevented with implementation of effective tobacco control and other interventions.
Published: 2018

18. Changing cancer survival in China during 2003–15: a pooled analysis of 17 population-based cancer registries

Author: Guohui Song, Tonghao Wu, Yanjun Xu, Zhentao Fu, Yan Zhou, Kexin Sun, Xue Qin Yu, Chunhua Yan, Jian Wang, Jianshun Chen, Xiaonong Zou, Chunxiao Jiang, John S. Ji, Zhaolai Hua, Yanlei Yang, Dongmei Fan, Huijuan Mu, Freddie Bray, Yutong He, Xin Zhou, Peter D. Baade, Rongshou Zheng, Jie Jiang, Changfa Xia, Jianguo Chen, Wanqing Chen, Yanhua Li, Ning Wang, Qilong Li, Ahmedin Jemal, Hongmei Zeng, H.C. Li, He Li, Jianmei Dong, Fangxian Fu, Kuangrong Wei, Xiaoping Gu, Siwei Zhang, Jie He, Ren-Qiang Han, Deli Zhao, Feng Jin, Zhixun Yang, and Shuzheng Liu
Subjects: Adult, Male, 0301 basic medicine, China, Adolescent, Population, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Cancer Survivors, Neoplasms, Humans, Medicine, Registries, Young adult, Child, education, Survival rate, Aged, Aged, 80 and over, Cervical cancer, education.field_of_study, Relative survival, business.industry, lcsh:Public aspects of medicine, Infant, Newborn, Infant, Cancer, lcsh:RA1-1270, General Medicine, Middle Aged, medicine.disease, Survival Rate, 030104 developmental biology, Child, Preschool, 030220 oncology & carcinogenesis, Population study, Cancer Control, Survivorship, and Outcomes Research - Surveillance, Female, Rural area, business, Demography
Abstract: Summary Background From 2003 to 2005, standardised 5-year cancer survival in China was much lower than in developed countries and varied substantially by geographical area. Monitoring population-level cancer survival is crucial to the understanding of the overall effectiveness of cancer care. We therefore aimed to investigate survival statistics for people with cancer in China between 2003 and 2015. Methods We used population-based data from 17 cancer registries in China. Data for the study population was submitted by the end of July 31, 2016, with follow-up data on vital status obtained on Dec 31, 2015. We used anonymised, individual cancer registration records of patients (aged 0–99 years) diagnosed with primary, invasive cancers from 2003 to 2013. Patients eligible for inclusion had data for demographic characteristics, date of diagnosis, anatomical site, morphology, behaviour code, vital status, and last date of contact. We analysed 5-year relative survival by sex, age, and geographical area, for all cancers combined and 26 different cancer types, between 2003 and 2015. We stratified survival estimates by calendar period (2003–05, 2006–08, 2009–11, and 2012–15). Findings There were 678 842 records of patients with invasive cancer who were diagnosed between 2003 and 2013. Of these records, 659 732 (97·2%) were eligible for inclusion in the final analyses. From 2003–05 to 2012–15, age-standardised 5-year relative survival increased substantially for all cancers combined, for both male and female patients, from 30·9% (95% CI 30·6–31·2) to 40·5% (40·3–40·7). Age-standardised 5-year relative survival also increased for most cancer types, including cancers of the uterus (average change per calendar period 5·5% [95% CI 2·5–8·5]), thyroid (5·4% [3·2–7·6]), cervix (4·5% [2·9–6·2]), and bone (3·2% [2·1–4·4]). In 2012–15, age-standardised 5-year survival for all patients with cancer was higher in urban areas (46·7%, 95% CI 46·5–47·0) than in rural areas (33·6%, 33·3–33·9), except for patients with oesophageal or cervical cancer; but improvements in survival were greater for patients residing in rural areas than in urban areas. Relative survival decreased with increasing age. The increasing trends in survival were consistent with the upward trends of medical expenditure of the country during the period studied. Interpretation There was a marked overall increase in cancer survival from 2003 to 2015 in the population covered by these cancer registries in China, possibly reflecting advances in the quality of cancer care in these areas. The survival gap between urban and rural areas narrowed over time, although geographical differences in cancer survival remained. Insight into these trends will help prioritise areas that need increased cancer care. Funding National Key R&D Program of China, PUMC Youth Fund and the Fundamental Research Funds for the Central Universities, and Major State Basic Innovation Program of the Chinese Academy of Medical Sciences.
Published: 2018

19. Cause-specific mortality for 240 causes in China during 1990–2013: a systematic subnational analysis for the Global Burden of Disease Study 2013

Author: Guoqing Hu, Hannah Hamavid, Yong Zhao, Theo Vos, Jun She, Gelin Xu, Yuantao Hao, Daniel Dicker, Ryan M Barber, Mohsen Naghavi, Haidong Kan, Xiaonong Zou, Yu Wang, Maya S Fraser, Jun Zhu, Yingfeng Zheng, Maigeng Zhou, Haidong Wang, Peng Yin, Shicheng Yu, Jiangmei Liu, Wanqing Chen, Feng Tan, Guohong Jiang, Shiwei Liu, Alan D. Lopez, Yunning Liu, Linhong Wang, Gonghuan Yang, Xia Wan, Yichong Li, Lijing L. Yan, Matthew M Coates, Lijun Wang, Christopher J L Murray, Xiaofeng Liang, Michael R. Phillips, Chuanhua Yu, and Diego Gonzalez-Medina
Subjects: Adult, Male, Mainland China, Gerontology, China, Adolescent, Demographic transition, Poison control, History, 21st Century, Young Adult, 03 medical and health sciences, Life Expectancy, 0302 clinical medicine, Cost of Illness, Cause of Death, Environmental health, Injury prevention, Humans, Medicine, 030212 general & internal medicine, Mortality, Child, Aged, business.industry, Age Factors, Infant, Newborn, Infant, General Medicine, History, 20th Century, Middle Aged, Years of potential life lost, Demographic change, Child, Preschool, Life expectancy, Female, business, 030217 neurology & neurosurgery
Abstract: Summary Background China has experienced a remarkable epidemiological and demographic transition during the past three decades. Far less is known about this transition at the subnational level. Timely and accurate assessment of the provincial burden of disease is needed for evidence-based priority setting at the local level in China. Methods Following the methods of the Global Burden of Disease Study 2013 (GBD 2013), we have systematically analysed all available demographic and epidemiological data sources for China at the provincial level. We developed methods to aggregate county-level surveillance data to inform provincial-level analysis, and we used local data to develop specific garbage code redistribution procedures for China. We assessed levels of and trends in all-cause mortality, causes of death, and years of life lost (YLL) in all 33 province-level administrative units in mainland China, all of which we refer to as provinces, for the years between 1990 and 2013. Findings All provinces in mainland China have made substantial strides to improve life expectancy at birth between 1990 and 2013. Increases ranged from 4·0 years in Hebei province to 14·2 years in Tibet. Improvements in female life expectancy exceeded those in male life expectancy in all provinces except Shanghai, Macao, and Hong Kong. We saw significant heterogeneity among provinces in life expectancy at birth and probability of death at ages 0–14, 15–49, and 50–74 years. Such heterogeneity is also present in cause of death structures between sexes and provinces. From 1990 to 2013, leading causes of YLLs changed substantially. In 1990, 16 of 33 provinces had lower respiratory infections or preterm birth complications as the leading causes of YLLs. 15 provinces had cerebrovascular disease and two (Hong Kong and Macao) had ischaemic heart disease. By 2013, 27 provinces had cerebrovascular disease as the leading cause, five had ischaemic heart disease, and one had lung cancer (Hong Kong). Road injuries have become a top ten cause of death in all provinces in mainland China. The most common non-communicable diseases, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and cancers (liver, stomach, and lung), contributed much more to YLLs in 2013 compared with 1990. Interpretation Rapid transitions are occurring across China, but the leading health problems and the challenges imposed on the health system by epidemiological and demographic change differ between groups of Chinese provinces. Localised health policies need to be implemented to tackle the diverse challenges faced by local health-care systems. Funding China National Science & Technology Pillar Program 2013 (2013BAI04B02) and Bill & Melinda Gates Foundation.
Published: 2016
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20. Esophageal cancer statistics in <scp>C</scp> hina, 2011: Estimates based on 177 cancer registries

Author: Hongmei Zeng, Changfa Xia, Siwei Zhang, Xiaonong Zou, Wanqing Chen, Tingting Zuo, and Rongshou Zheng
Subjects: 0301 basic medicine, Pulmonary and Respiratory Medicine, Oncology, China, medicine.medical_specialty, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Epidemiology of cancer, Medicine, esophageal cancer, business.industry, Incidence (epidemiology), Cancer, Original Articles, General Medicine, Esophageal cancer, medicine.disease, mortality, Cancer registry, Surgery, 030104 developmental biology, 030220 oncology & carcinogenesis, incidence, Original Article, business
Abstract: Background Esophageal cancer has been a common cancer in China for many years. Using the most recent data collected from the National Central Cancer Registry, we present estimates of the esophageal cancer burden in China in 2011. Methods Age‐specific incidence and mortality rates by gender and area for 18 age groups were calculated based on data from 177 qualified population‐based cancer registries. The number of new cases of esophageal cancer and cancer deaths were computed by multiplying these rates by the 2011 population. Crude incidence and mortality rates of esophageal cancer were estimated. Results The estimated number of new esophageal cancer cases and deaths were 291 238 and 218 957, respectively. The crude incidence and mortality rates for esophageal cancer were 21.62/100 000 and 16.25/100 000, respectively. The age‐standardized incidence and mortality rates by world population were 15.83/100 000 and 11.62/100 000, respectively. Both the incidence and mortality rates of esophageal cancer were higher in rural areas than in urban areas, and in men than in women. The age‐specific esophageal cancer incidence and mortality rates increased with age. In China, squamous cell cancer was the most common pathological type of the disease. Conclusion Esophageal cancer remains a major public health issue in China. Primary and secondary prevention are essential for disease control.
Published: 2015
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21. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013

Author: Yong Zhao, Hadi Danawi, Bach Xuan Tran, Gene Bukhman, Vasiliki Stathopoulou, Taavi Tillmann, Nelson Alvis-Guzman, Yongmei Li, Jerry Puthenpurakal Abraham, Sudan Prasad Neupane, Jack Caravanos, Ben Schöttker, Rafael Lozano, Damian G Hoy, Yoshihiro Kokubo, Nicholas J K Breitborde, Sergey Soshnikov, Yukito Shinohara, Randall V. Martin, Michael Brainin, Fernando Perez-Ruiz, Yingfeng Zheng, Santosh Mishra, Julio Cesar Montañez Hernandez, Michael Phillips, Belinda J. Gabbe, Hebe N. Gouda, Ziad A. Memish, Rupert R A Bourne, Guoqing Hu, Emmanuel A. Ameh, Abigail McLain, Michelle L. Bell, Christopher Margono, Marissa Iannarone, Wilkister N. Moturi, Donald H. Silberberg, Carl Abelardo T. Antonio, Nataliya Foigt, Anand Dayama, Yanping Wang, Amanda J. Mason-Jones, Bolajoko O. Olusanya, Monica S. Vavilala, Katherine B Gibney, David Tanne, Sidibe S Kany Roseline, Marcella Montico, Abhishek Singh, Sarah Derrett, Alireza Esteghamati, Seok Jun Yoon, Corine Karema, Rakhi Dandona, David M. Pereira, Kazem Rahimi, Gitanjali M. Singh, Vivekanand Jha, John Hornberger, Anne M. Riederer, Kathryn H. Jacobsen, Andrea Pedroza, Lily Alexander, Fiona M. Blyth, Tommi Vasankari, Kyle J Foreman, Rana J. Asghar, Tilahun Nigatu Haregu, Yousef Khader, Rafael Alfonso-Cristancho, Suzanne Barker-Collo, Lydia S. Atkins, Simerjot K. Jassal, Mohammad Ali Sahraian, Peter Scarborough, Hans W. Hoek, E. Ray Dorsey, Muluken Dessalegn, David C. Schwebel, Gavin Shaddick, Thomas D. Fleming, Mohammad Tavakkoli, Dorairaj Prabhakaran, Mohammad H. Forouzanfar, Christopher C. Mapoma, Jost B. Jonas, Erin C Mullany, Gene F. Kwan, Johanna M. Geleijnse, Antonio Luiz Pinho Ribeiro, Roberto Tchio Talongwa, Tolesa Bekele, Jed D. Blore, Gunn Marit Aasvang, Philimon Gona, Miguel Angel Alegretti, Babak Eshrati, Mitsuru Mukaigawara, Richard F. Gillum, Odgerel Chimed-Ochir, Ubai Alsharif, Richard C. Franklin, Felix Masiye, Richard T. Burnett, Sanjay Krishnaswami, Martin McKee, John J Huang, Lucía Cuevas-Nasu, Wagner Marcenes, Walid Ammar, Knud Juel, Joseph R. Zunt, Martha M Téllez Rojo, Mamta Swaroop, Noela M Prasad, Azmeraw T. Amare, Tim Driscoll, Michael Kravchenko, Heresh Amini, Amir Sapkota, Theo Vos, Charlotte Watts, Dennis Odai Laryea, D. Alex Quistberg, Justin Beardsley, Cheng Huang, Adnan M. Durrani, Sarah V Thackway, Rita Van Dingenen, Manami Inoue, Martha Híjar, Honglei Chen, Amany H. Refaat, Yichong Li, Vineet K. Chadha, Wenzhi Wang, Louisa Degenhardt, Kingsley N. Ukwaja, Nayu Ikeda, James D. Wilkinson, Linh N Bui, Maria Hagströmer, Gonghuan Yang, Ann Kristin Knudsen, David J. Margolis, Soewarta Kosen, Hans Kromhout, Atsushi Goto, Man Mohan Mehndiratta, Thomas N. Williams, Michael Soljak, Yun Jin Kim, Hideaki Toyoshima, Jeyaraj D Pandian, Borja del Pozo-Cruz, Soufiane Boufous, Ivy Shiue, Anders Larsson, Guilherme V. Polanczyk, John Powles, Yara A. Halasa, Robin Room, Ratilal Lalloo, Carolina Batis Ruvalcaba, Panniyammakal Jeemon, Elisabete Weiderpass, Jürgen Rehm, Ejaz Ahmad Khan, Alicia Aleman, Zacharie Tsala Dimbuene, Elena Alvarez, Rachelle Buchbinder, Randah R. Hamadeh, Bryan Hubbell, Sadaf G. Sepanlou, Farhad Islami, Costas A. Christophi, Heidi Stöckl, Ismael R. Campos-Nonato, Nigel Bruce, Edward J Mills, Samuel A L Perry, Taavi Lai, Baffour Awuah, Mete Saylan, Karen J. Courville, Arindam Basu, Vanessa De la Cruz-Góngora, Teresita González de Cosío, Naohiro Yonemoto, Frida Namnyak Ngalesoni, Muluken Azage Yenesew, Atte Meretoja, Michael Brauer, Cyrus Cooper, Giorgia Giussani, Valentina S. Arsic Arsenijevic, Vasiliy Victorovich Vlassov, André Karch, Leilei Duan, Matthew M Coates, Omid Ameli, Gelin Xu, Matthias Endres, Ganesan Karthikeyan, Ione Jayce Ceola Schneider, Mohamed Hsairi, Palwasha Anwari, Mazin J. Al Khabouri, Dariush Mozaffarian, Juan R. Sanabria, Pablo M. Lavados, Sumeet S. Chugh, Johan Ärnlöv, Ivo Rakovac, Maurice Giroud, Haidong Kan, Ibrahim Abdelmageem Mohamed Ginawi, José Luis Texcalac-Sangrador, Luigi Naldi, Erica Leigh Slepak, Deena Alasfoor, James E. Saunders, Richard Matzopoulos, Talal Bakfalouni, Stein Emil Vollset, Andrea Werdecker, Lennert J. Veerman, Lorenzo Monasta, Henrica A. F. M. Jansen, Reyna A Gutiérrez, Brittany Wurtz, Luz Maria Sanchez, Lijing L. Yan, M. Patrice Lindsay, Michele Meltzer, Sanjay Basu, Steven van de Vijver, Alaa Badawi, Thomas Claßen, Young-Ho Khang, Brett M. Kissela, Jun Zhu, In-Hwan Oh, Fiona J Charlson, Maria Cecilia Bahit, Dinorah González-Castell, Rosario Cárdenas, Dan Poenaru, Sayed Saidul Alam, Mitchell T. Wallin, Harish Chander Gugnani, James Leigh, Ferrán Catalá-López, Lidia Morawska, Jim van Os, Stephanie J. London, Kaire Innos, Isabelle Romieu, Fiorella Cavalleri, Adrian Davis, Hwee Pin Phua, Chakib Nejjari, Héctor Gómez Dantés, Boris I. Pavlin, Karen Sliwa, Lynne Gaffikin, Constance D. Pond, Michael F. MacIntyre, Blake Thomson, Norberto Perico, Ronny Westerman, Samantha M. Colquhoun, Michael H. Criqui, Ana Maria Nogales Vasconcelos, Wubegzier Mekonnen, Bulat Idrisov, Ana Basto-Abreu, Andrew G. M. Bulloch, Jasvinder A. Singh, Vinod K. Paul, Emin Murat Tuzcu, Svetlana Popova, Hmwe H Kyu, Richard L. Guerrant, Mohammed I. Albittar, Srikanth Mangalam, Steven E. Lipshultz, Lela Sturua, Semaw Ferede Abera, Eduardo Bernabé, George D. Thurston, Bruno F. Sunguya, Tiffany Ku, Alejandra G. Contreras, Abdullah Sulieman Terkawi, Charles Atkinson, Ashkan Afshin, Heidi J. Larson, Abdullatif Husseini, Jose C. Adsuar, Reza Assadi, Ademola Lukman Adelekan, Joshua A. Salomon, Yousef M. Elshrek, Gokalp Kadri Yentur, Devina Nand, Narayanaswamy Venketasubramanian, Graça Maria Ferreira De Lima, Maheswar Satpathy, Fotis Topouzis, Traolach S. Brugha, Hywel C Williams, Coen H. Van Gool, Andrew H. Kemp, Awoke Misganaw, Amado D Quezada, Norito Kawakami, Bert Brunekreef, Peter Burney, Tati S. Warouw, Jongmin Lee, Inga Dora Sigfusdottir, Marcel Tanner, Solveig A. Cunningham, Benjamin O. Anderson, Tariku Jibat Beyene, Lars Barregard, Xia Wan, Giuseppe Remuzzi, Bernadette Thomas, Lilia S Pedraza, Massimo Cirillo, Alina Rodriguez, Ricky Leung, Farshad Pourmalek, K. Srinath Reddy, Charles D.A. Wolfe, Ulrich O Mueller, Neeraj Bedi, Al Artaman, Lucia Hernandez, Itamar S. Santos, C. Arden Pope, Norlinah Mohamed Ibrahim, Carlo Irwin A. Panelo, Selen Begüm Uzun, Miltiadis K. Tsilimbaris, Anwar Rafay, Daniel Dicker, Melvin Barrientos Marzan, Sajjad Ur Rahman, Mohammed O. Basulaiman, Edgar P. Simard, Mohammad T Mashal, Maysaa El Sayed Zaki, Shiwei Liu, Don C. Des Jarlais, Bo Norrving, Salvador Villalpando, Miia Kivipelto, Yang Liu, Carolina Maria Teixeira, Catalina Medina, Sudha Jayaraman, Josep Maria Haro, Diego De Leo, Angel J Paternina Caicedo, Abigail C. McKay, Eric L. Ding, Mukesh Dherani, Ljiljana Pejin Stokic, Vinay Nangia, Sukanta Saha, Juan Liang, Elisabeth Cardis, Zourkaleini Younoussi, José R Nogueira, Braden Te Ao, Vasco Manuel Pedro Machado, Lionel Racapé, Ting Wu Chuang, Shahab Khatibzadeh, E Filipa de Castro, Barthelemy Kuate Defo, Ulises Trujillo, Alan D. Lopez, Soraya Seedat, Lope H Barrero, Linhong Wang, Daniel Pope, Alexandra Brazinova, Faris Lami, Valentina Colistro, G Anil Kumar, Derek F J Fay, Haidong Wang, Hwashin H. Shin, Raimundas Lunevicius, Suzanne Polinder, Dietrich Plass, David Rojas-Rueda, Stephen S Lim, Tania G Sánchez-Pimienta, K.M. Venkat Narayan, Yuantao Hao, Jung-Chen Chang, Corina Benjet, Seyed-Mohammad Fereshtehnejad, Luciano A. Sposato, Stan Biryukov, Kunihiro Matsushita, Beth E. Ebel, Cleusa P. Ferri, Soumya Swaminathan, K. Ryan Wessells, Gustavo Velasquez-Melendez, Leslie T. Cooper, David O. Carpenter, Nancy Lopez, Bryan L. Sykes, Sandra Nolte, Murray B. Stein, Paul N. 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Mayosi, Konrad Pesudovs, Joanna Moschandreas, Ziad Nahas, James Damsere-Derry, Nsanzimana Sabin, Tonatiuh Barrientos-Gutiérrez, Ying Jiang, Andre Pascal Kengne, Peter Allebeck, Jonas Minet Kinge, Shankuan Zhu, Guy B. Marks, Daniel C Casey, Marco A Avila, Anna Roca, Lalit Dandona, Ami R. Moore, Adansi A. Amankwaa, David Gunnell, Andre Keren, Yohannes Adama Melaku, Nhung T Nguyen, Anthony D. Woolf, Mayuree Rao, Peter J. Allen, Christina Papachristou, Karzan Abdulmuhsin Mohammad, Ravi Kumar Balu, Marie Ng, Marcello Tonelli, Maziar Moradi-Lakeh, Maigeng Zhou, Emmanuela Gakidou, Mohammed K. Ali, Amanda W Pain, Dan J. Stein, Kawkab Shishani, Fortuné Gbètoho Gankpé, Howard J. Hoffman, James Scott, Nadine Steckling, Samia Alhabib, Deborah Jarvis, Kara Estep, Arsène Kouablan Adou, Ricardo Orozco, Holly Hagan, K. C. Astha, Reza Malekzadeh, Klara Dokova, Aliya Naheed, Ernst J. Kuipers, Valeria Caso, Derrick A Bennett, Andrea B. Feigl, Uche S. Uchendu, Holly E. Erskine, Shireen Sindi, Arjun Lakshmana Balaji, Francesco Saverio Violante, Monika Sawhney, Alejandra Cantoral, Ketevan Goginashvili, Raghib Ali, Fan Jiang, Robert G. Weintraub, Homie Razavi, Myriam Tobollik, Howard Hu, Emerito Jose A. Faraon, Irma Khonelidze, Patricia M. Riccio, Eun-Kee Park, Julio Cesar Campuzano, Ibrahim Abubakar, Jürgen C Schmidt, Konstantinos Stroumpoulis, Aref A. Bin Abdulhak, Graeme J. Hankey, Natan M. Bornstein, Mouhanad Hammami, Lee Richardson, Rintaro Mori, Alanur Çavlin, Ruth W Kimokoti, Samir Soneji, Mark J. Nieuwenhuijsen, John Q. Wong, Joseph Frostad, Tom Achoki, Rahman Shiri, Ashish Bhalla, Kurt Straif, Simon I. Hay, Scott B. Patten, Kalpana Balakrishnan, Awoke Misganaw Temesgen, Chandrashekhar T Sreeramareddy, Ryan M Barber, Rosana E. Norman, JianLi Wang, Siyi Shangguan, Luke Nyakarahuka, Kovin Naidoo, Charles D. H. Parry, Mercedes Colomar, H. Ross Anderson, Carlos Magis-Rodriguez, Joan M. Nolla, Muhammad Imran Nisar, Karen Devries, Andrew L. 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Thrift, Stefan Ma, Samaya Ismayilova, Evariste Gasana, Amitava Banerjee, Aslam Pervaiz, Emilie Agardh, Abraham D. Flaxman, Farshad Farzadfar, Peter W. Gething, Ileana Heredia-Pi, Boris Bikbov, Wanqing Chen, Saad B. Omer, Ruben Castro, Neeraj Bhala, Sara Sheikhbahaei, Hilton Lam, Urbano Fra Paleo, Lidia Sanchez-Riera, Alicia Elena Beatriz Lawrynowicz, Kristen Delwiche, Richard G. Ellenbogen, Max Petzold, Yuri Y Varakin, Guilherme Borges, Guohong Jiang, Francis Guillemin, Kyle R. Heuton, Yohannes Kinfu, Victoria F Bachman, Joseph A Wagner, Carlos A Castañeda-Orjuela, Leonardo Trasande, Abbas Ali Mahdi, Josef Coresh, Chuanhua Yu, Kenji Shibuya, Berrin Serdar, Laetitia Huiart, Xiaofeng Liang, Jean de Dieu Ngirabega, Takayoshi Ohkubo, Natalie Stephens, Francis Apolinary Mhimbira, Jefferson Traebert, Amiran Gamkrelidze, Kjetil Søreide, Samath D Dharmaratne, Robert P. Dellavalle, George Mugambage Ruhago, Lakshmi Vijayakumar, Joannie Lortet-Tieulent, Dipan Bose, Tania C Aburto, Saleem M Rana, Miriam Levi, Mohammad Taghi Hedayati, Rodolfo S Pagcatipunan, Ron T. Gansevoort, H. D. Hosgood, Michael Burch, Mohsen Naghavi, Vegard Skirbekk, Ayfer Pekericli, Walter Mendoza, Pengpeng Ye, Gabrielle deVeber, Ali H. Mokdad, David M. Broday, Koranteng Adofo, Zewdie Aderaw Alemu, Shifalika Goenka, Carrie Beth Peterson, Nicolas J. C. Stapelberg, Edson Serván-Mori, Anil Kaul, Foad Abd-Allah, Marek Majdan, Rahul Gupta, Giancarlo Logroscino, Kardiyoloji, Peterson, Carrie B., Laboratoire de Physique des Solides (LPS), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Wisconsin Division of Public Health, Laboratoire de psychologie sociale et de psychologie cognitive (LAPSCO), Centre National de la Recherche Scientifique (CNRS)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), London South Bank University, Metropolitan Police Service, Hong Kong Baptist University (HKBU), Institut für Informatik [München/Munich] (LMU), Ludwig-Maximilians-Universität München (LMU), Neuroépidémiologie Tropicale (NET), Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Chirurgie Thoracique et Vasculaire - Médecine vasculaire [CHU Limoges], CHU Limoges, Insight Centre for Data Analytics [Galway] (INSIGHT), National University of Ireland [Galway] (NUI Galway), Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Centre d'Investigation Clinique - Epidemiologie Clinique/essais Cliniques Nancy, Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale (INSERM), Karolinska Institute, karolinska institute, Department of Molecular Biosciences, Department of Molecular Biosciences [Oslo], Faculty of Mathematics and Natural Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO)-Faculty of Mathematics and Natural Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Ecole Polytechnique Fédérale de Lausanne (EPFL), Regional Genetic Service, St Mary's Hospital, Manchester, Laboratoire d'Ingénierie des Matériaux (LIM), Centre National de la Recherche Scientifique (CNRS), Computer Science Department [Bristol], University of Bristol [Bristol], Universität Mannheim [Mannheim], Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) (SRI-B), Computational Science and Engineering Department [Daresbury] (STFC), Science & Technologie Facilities Council, Multimedia Research Center (MRC), University of Alberta, Division of Biostatistics (Biostat - MINNEAPOLIS), University of Minnesota [Twin Cities], University of Minnesota System-University of Minnesota System, University of Southampton, Imperial College London, Neurology Department, Ichilov Medical Center, Interactions, transferts, ruptures artistiques et culturels - EA 6301 (InTRu), Université de Tours, Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Julius Center for Health Sciences and Primary Care, University Medical Center [Utrecht], Risk Assessment Sciences Institute, Utrecht University [Utrecht], Unité de Biologie Fonctionnelle et Adaptative (BFA (UMR_8251 / U1133)), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Respiratory Epidemiology and Public Health, Imperial College London-Royal Brompton Hospital-National Heart and Lung Institute [UK], CIBER de Epidemiología y Salud Pública (CIBERESP), STAR laboratory, Stanford University [Stanford], Unité de recherche Virologie et Immunologie Moléculaires (VIM), Institut National de la Recherche Agronomique (INRA), Tennent Institute of Ophthalmology, National University of Singapore (NUS), Centre de Robotique (CAOR), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Multidisciplinary Nanotechnology Centre, Swansea University, Cyprus International Institute for the Environment and Public Health, Harvard School of Public Health, Genomics Research Center, Academia Sinica, Neuro Rehab Services LLP [New Delhi], Department of Signal Theory and Communications (TSC), Univ. Politec. de Catalunya, King‘s College London, Dept. Mat. Engn. De Ma, Sao Carlos, Fed. Univ. Sao Carlos UFSCar, RESPEC (RESPEC), RESPEC, Advanced Laboratories on Embedded Systems [Roma] (ALES), Department of Biology [Miami], University of Miami [Coral Gables], Health Care, Minister Of Labour-Ministry of Labor, Health and Social Affairs, Department of Nephrology, University Medical Center, University of Groningen, Division of Human Nutrition, Wageningen University and Research Centre [Wageningen] (WUR), Spatial Ecology and Epidemiology Group, University of Oxford [Oxford], College of Medicine, University of Hail, Saudi Arabia, Laboratory of Neurologic Diseases, Mario Negri Institute, Milan, Department of Civil Engineering [Hamirpur], National Institute of Technology [Hamirpur], GEMMA — Environmental Engineering and Microbiology Research Group, Department of Hydraulic, Maritime and Environmental Engineering, Universitat Politècnica de Catalunya [Barcelona] (UPC), Department of Biosciences and Nutrition, Karolinska Institutet [Stockholm], Institut National de Recherche et d'Analyse Physico-Chimique (INRAP), Institut National de Recherche et d'Analyse Physico-chimique (Ariana, Tunisie) (INRAP), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Technologie de Belfort-Montbeliard (UTBM), Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences [Tehran] (SBUMS), Shahid Beheshti University-Shahid Beheshti University, Center for Applied Medical Research (CIMA), University of Tehran, Secretariat of the Pacific Community, Public Health Division, Sociétés, Acteurs, Gouvernement en Europe (SAGE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), College of Precision Instrument and Optoelectronics Engineering, Tianjin University, George Washington University (GW), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U912 INSERM - Aix Marseille Univ - IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Universiteit Gent [Ghent], Washington State University (WSU), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, School of Computer Science - China University of Geosciences (China University of Geosciences (East Area)), Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université Catholique de Louvain (UCL), Fachbereich Physik [Berlin], Freie Universität Berlin, Div Cyclotron & Radiopharmaceut Sci (DRDO, INMAS), Univ New Delhi, School of Physics and Astronomy, University of St Andrews [Scotland], University of Cape Town, Department of Neuroscience, Department of Computer Science and Engineering [Daejeon] (Chungnam National University), Lawrence University, Gastroenterology & Hepatology, Tata Research Development and Design Center (TRDDC), TCS Innovation Labs, University of Helsinki, Google Inc [Mountain View], Research at Google, Swedish Defense Research Agency (FOI), Servicio de Neurologia (SANTIAGO - Neurologie), Universidad del Desarrollo, Novartis Pharmaceutical Corporation, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Department of Mechanical and Automation Engineering (CAD Laboratory), The Chinese University of Hong Kong [Hong Kong], Università degli studi di Bari, Department of Health and Human Services, National Institutes of Health [Bethesda] (NIH), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), College of Information and Electrical Engineering [Beijing] (CIEE), China Agricultural University (CAU), Thales Research and Technology [Palaiseau], THALES, Department of Rheumatology and Connective Tissue Diseases, Medical University of Lublin, Barts and The London School of Medicine and Dentistry, Queen Mary University of London (QMUL), Centre d'économie de la Sorbonne (CES), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), École supérieure du professorat et de l'éducation - Académie de Grenoble [2013-2019] (ESPE Grenoble [2013-2019]), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Department of Mathematics, University of Iowa [Iowa City], College of Medicine, Alfaisal University, Saudi Ministry of Health, Institut national des recherches agricoles du Bénin, Centre de Recherches agricoles du Sud, Departments of Epidemiology and Nutrition, Unit of Human Nutrition, Agricultural University of Athens, Department of Animal Science, Pennsylvania State University (Penn State), Penn State System-Penn State System, University of Virginia, University of Virginia [Charlottesville], Epidemiology and Biostatistics Unit, Institute for Maternal and Child Health - IRCCS ‘‘Burlo Garofolo', Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Division of Cardiovascular Medicine and Channing Division of Network Medicine, Brigham and Women's Hospital [Boston], American University of Beirut [Beyrouth] (AUB), Department of Chemistry, Scientific Computing Research Unit, Department of dermatology, Milano University-Azienda Ospedaleria Ospedali Riuniti di Bergamo, Mailman School of Public Health, Columbia University [New York], The Georges Institute for International Health, The University of Sydney, Department of epidemiology and Public Health, Faculty of Medicine, Département Optique (OPT), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Universitat Pompeu Fabra [Barcelona], Center for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra [Barcelona]-Catalunya ministerio de salud, Nutriments Lipidiques et Prévention des Maladies Métaboliques, Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université de la Méditerranée - Aix-Marseille 2, Department of Neurology Lunds University Hospital Lund, Unit of Functional Bionanomaterials, School of Biosciences, University of Birmingham [Birmingham], Electrical Engineering and Computer Science Department - Case Western Reserve University, Case Western Reserve University [Cleveland], World Health Organization, Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), Nordic School of Public Health, The James Hutton Institute, Horia Hulubei National Institute for Physics and Nuclear Engineering, Department of Pediatrics, University of Washington [Seattle], Institute of Public Health, Department of Physics, Clarendon Laboratory, Center for TeleInFrastruktur (CTIF), Aalborg University [Denmark] (AAU), Physikalisches Institut [Freiburg], Albert-Ludwigs-Universität Freiburg, Savoirs, Textes, Langage (STL) - UMR 8163 (STL), Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Dept.of Computer Science, Indian Institute of Technology Madras (IIT Madras), Istituto Mario Negri Bergamo, Centro Ricerche e Trapianti Villa Camozzi, Universidade Estadual Paulista Júlio de Mesquita Filho [São José do Rio Preto] (UNESP), Laboratoire de Génie Informatique et Ingénierie de Production (LGI2P), IMT - MINES ALES (IMT - MINES ALES), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut geològic de Catalunya (IGC), Institut Geològic de Catalunya-IGC, Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physiologie et Génomique des Poissons (LPGP), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Recherche Agronomique (INRA), Politecnico di Milano [Milan] (POLIMI), Symantec, University of Oviedo, European Microsoft Innovation Center (EMIC), Microsoft Corporation [Redmond, Wash.], Technion - Israel Institute of Technology [Haifa], Laboratoire de Mécanique, Physique et Géosciences (LMPG), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU), Department of Physics, Cavendish Laboratory, University of Cambridge [UK] (CAM), Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Pierre et Marie Curie - Paris 6 (UPMC), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Departments of Applied Physics [New Haven], Yale University [New Haven], Center for Mathematical Modeling (CMM), Department of Global Health and Development, London School of Hygiene and Tropical Medicine (LSHTM), University of Occupational and Environmental Health [Kitakyushu] (UEOH), Department of Computer Science and Engineering [New Delhi], Indian Institute of Technology Delhi (IIT Delhi), Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), GlaxoSmithKline, Imperial College London-Clinical Imaging Center, Universidade Federal de Pernambuco [Recife] (UFPE), Maclean Building, Benson Lane, Crowmarsh Gifford, Centre for Ecology and Hydrology, Nanoscience Institute (NEST), Dipartimento di Fisica, Università di Pisa, Aristotle University of Thessaloniki, Laboratory Of Immune Cell Biology (LICB), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Institute of Human Genetics, Rheinische Friedrich-Wilhelms-Universität Bonn, Laboratorio Nacional de Computação Cientifica [Rio de Janeiro] (LNCC / MCT), Occupational Health Unit, Bologna University Hospital-Sant'Orsola-Malpighi Polyclinic, Royal Institute of Technology [Stockholm] (KTH ), NICTA [Eveleigh], National ICT Australia [Sydney] (NICTA), Division of Solid Mechanics, Lund University [Lund], University of Calgary, BioWare Corp, Manchester Academic Health Sciences Centre, Institut d'Histoire et de Philosophie des Sciences et des Techniques (IHPST), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Ghent University [Belgium] (UGENT), Imaging Sciences and Biomedical Engineering Division [London], Guy's and St Thomas' Hospital [London]-King‘s College London, Children’s Hospital of Philadelphia (CHOP ), Perelman School of Medicine, University of Pennsylvania [Philadelphia], Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA), École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - Faculté des Sciences et des Techniques, Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Department of Physiology, Augusta University - Medical College of Georgia, University System of Georgia (USG)-University System of Georgia (USG), Neurorestoration Group, Wolfson Centre for Age-related Diseases-King‘s College London, Electronic Navigation Research Institute (ENRI), Ministry of Land, Infrastructure, Transport and Tourism, Department of Computer Science [KAIST] (CS), Korea Advanced Institute of Science and Technology (KAIST), Centre for Undergraduate Studies, University of the Punjab, Siemens Corporate Research, Siemens AG [Munich], University of Massachusetts [Boston] (UMass Boston), University of Massachusetts System (UMASS), Department of Materials Science, Sichuan University [Chengdu] (SCU), Natl Engn Res Ctr Vegetables, Key Lab Biol & Genet Improvement Hort Crops N Chi, Beijing Acad Agr & Forestry Sci, University Hospital Puerta de Hierro, Madrid, Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Université de Franche-Comté (UFC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Technologie de Belfort-Montbeliard (UTBM), Shahid Beheshti University of Medical Sciences, École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), MOLTECH-ANJOU (MOLTECH-ANJOU), Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), Universidad de Santiago de Chile [Santiago] (USACH)-Universidad del Desarrollo, Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), École supérieure du professorat et de l'éducation - Académie de Grenoble (ESPE Grenoble), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), California Institute of Technology (CALTECH)-NASA, Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Sud - Paris 11 (UP11), Université de la Méditerranée - Aix-Marseille 2-Institut National de la Recherche Agronomique (INRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Universidad de Santiago de Chile [Santiago] (USACH), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), King‘s College London-Wolfson Centre for Age-related Diseases, Sichuan University, Universitat de Barcelona, Interne Geneeskunde, Medische Sociologie, MUMC+: MA Psychiatrie (3), MUMC+: Hersen en Zenuw Centrum (3), Psychiatrie & Neuropsychologie, CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne-Université européenne de Bretagne - European University of Brittany (UEB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Centre National de la Recherche Scientifique (CNRS), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), RS: MHeNs - R2 - Mental Health, Laboratoire de Physique des Solides ( LPS ), Université Paris-Sud - Paris 11 ( UP11 ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de psychologie sociale et de psychologie cognitive ( LAPSCO ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Centre National de la Recherche Scientifique ( CNRS ), Erosion torrentielle neige et avalanches ( UR ETGR ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Hong Kong Baptist University ( HKBU ), Institut für Informatik [München/Munich] ( LMU ), Ludwig-Maximilians-Universität München, Neuroépidémiologie Tropicale ( NET ), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut Génomique, Environnement, Immunité, Santé, Thérapeutique ( GEIST ), Université de Limoges ( UNILIM ) -Université de Limoges ( UNILIM ), Insight Centre for Data Analytics (National University of Ireland Galway (NUIG)) ( INSIGHT ), Maladies chroniques, santé perçue, et processus d'adaptation ( APEMAC ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale ( INSERM ), University of Oslo ( UiO ) -University of Oslo ( UiO ), Centro de Estudios Avanzados en Zonas Aridas ( CEAZA ), Ecole Polytechnique Fédérale de Lausanne ( EPFL ), Laboratoire d'Ingénierie des Matériaux ( LIM ), Centre National de la Recherche Scientifique ( CNRS ), Lawrence Berkeley National Laboratory [Berkeley] ( LBNL ), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) ( SRI-B ), Computational Science and Engineering Department [Daresbury] ( STFC ), Multimedia Research Center ( MRC ), University of Alberta [Edmonton], Division of Biostatistics ( Biostat - MINNEAPOLIS ), University of Minnesota [Minneapolis], University of Southampton [Southampton], Interactions, transferts, ruptures artistiques et culturels - EA 6301 ( InTRu ), Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), University Medical Center Utrecht, Biologie Fonctionnelle et Adaptative ( BFA ), Imperial College London-Royal Brompton Hospital-National Heart and Lung Institute, Unité de recherche Virologie et Immunologie Moléculaires ( VIM ), Institut National de la Recherche Agronomique ( INRA ), National University of Singapore ( NUS ), Centre de Robotique ( CAOR ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), Department of Signal Theory and Communications ( TSC ), RESPEC ( RESPEC ), Advanced Laboratories on Embedded Systems [Roma] ( ALES ), Wageningen University and Research Centre [Wageningen] ( WUR ), Universitat Politècnica de Catalunya [Barcelona] ( UPC ), Institut National de Recherche et d'Analyse Physico-Chimique ( INRAP ), Institut National de Recherche et d'Analyse Physico-chimique (INRAP-Tunisie), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) ( FEMTO-ST ), Université de Franche-Comté ( UFC ) -Centre National de la Recherche Scientifique ( CNRS ) -Ecole Nationale Supérieure de Mécanique et des Microtechniques ( ENSMM ) -Université de Technologie de Belfort-Montbeliard ( UTBM ), Tehran University, Sociétés, Acteurs, Gouvernement en Europe ( SAGE ), Université de Strasbourg ( UNISTRA ) -Centre National de la Recherche Scientifique ( CNRS ), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale ( SESSTIM - U912 INSERM - AMU - IRD ), Institut de Recherche pour le Développement ( IRD ) -Aix Marseille Université ( AMU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Washington State University ( WSU ), Laboratoire de Physique de l'ENS Lyon ( Phys-ENS ), École normale supérieure - Lyon ( ENS Lyon ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ), Institut des Sciences Chimiques de Rennes ( ISCR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Ecole Nationale Supérieure de Chimie de Rennes-Institut National des Sciences Appliquées ( INSA ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de recherche en informatique de Toulouse ( IRIT ), Institut National Polytechnique [Toulouse] ( INP ) -Université Toulouse 1 Capitole ( UT1 ) -Université Toulouse - Jean Jaurès ( UT2J ) -Université Toulouse III - Paul Sabatier ( UPS ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique ( CNRS ), Centre de Recherche en Automatique de Nancy ( CRAN ), Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), Université Catholique de Louvain ( UCL ), Freie Universität Berlin [Berlin], Div Cyclotron & Radiopharmaceut Sci ( DRDO, INMAS ), Institut de Physique Nucléaire d'Orsay ( IPNO ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ), Tata Research Development and Design Center ( TRDDC ), Laboratoire MOLTECH-Anjou [Angers] ( MOLTECH ANJOU ), Université d'Angers ( UA ) -Centre National de la Recherche Scientifique ( CNRS ), University of Helsinki [Helsinki], Swedish Defense Research Agency ( FOI ), Servicio de Neurologia ( SANTIAGO - Neurologie ), Universidad de Santiago de Chile [Santiago] ( USACH ) -Universidad del Desarrollo, Novartis Pharmaceutical Corp., East Hanover NJ 07936, USA, Laboratoire de glaciologie et géophysique de l'environnement ( LGGE ), Observatoire des Sciences de l'Univers de Grenoble ( OSUG ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Mechanical and Automation Engineering ( CAD Laboratory ), National Institutes of Health ( NIH ), Centre d'étude et de recherche en informatique et communications ( CEDRIC ), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise ( ENSIIE ) -Conservatoire National des Arts et Métiers [CNAM] ( CNAM ), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] ( Heudiasyc ), Université de Technologie de Compiègne ( UTC ) -Centre National de la Recherche Scientifique ( CNRS ), College of Information and Electrical Engineering [Beijing] ( CIEE ), China Agricultural University ( CAU ), Queen Mary University of London ( QMUL ), Centre d'économie de la Sorbonne ( CES ), Université Panthéon-Sorbonne ( UP1 ) -Centre National de la Recherche Scientifique ( CNRS ), Paris School of Economics ( PSE ), École supérieure du professorat et de l'éducation - Académie de Grenoble ( ESPE Grenoble ), Université Savoie Mont Blanc ( USMB [Université de Savoie] [Université de Chambéry] ) -Université Grenoble Alpes ( UGA ), PennState University [Pennsylvania] ( PSU ), Jet Propulsion Laboratory ( JPL ), NASA-California Institute of Technology ( CALTECH ), American University of Beirut [Beyrouth], The University of Sydney [Sydney], Département Optique ( OPT ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], Laboratoire des signaux et systèmes ( L2S ), Université Paris-Sud - Paris 11 ( UP11 ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ), Center for Research in Environmental Epidemiology ( CREAL ), Université de la Méditerranée - Aix-Marseille 2-Institut National de la Recherche Agronomique ( INRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Center for TeleInFrastruktur ( CTIF ), Aalborg University [Denmark] ( AAU ), Savoirs, Textes, Langage (STL) - UMR 8163 ( STL ), Université de Lille-Centre National de la Recherche Scientifique ( CNRS ), Indian Institute of Technology Madras ( IIT Madras ), Universidade Estadual Paulista Júlio de Mesquita ( UNESP ), Laboratoire de Génie Informatique et Ingénierie de Production ( LGI2P ), IMT - Mines Alès Ecole Mines - Télécom ( IMT - MINES ALES ), Institut geològic de Catalunya ( IGC ), Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Physiologie et Génomique des Poissons ( LPGP ), Institut National de la Recherche Agronomique ( INRA ) -Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Politecnico di Milano [Milan], European Microsoft Innovation Center ( EMIC ), Laboratoire de Mécanique, Physique et Géosciences ( LMPG ), Université Le Havre Normandie ( ULH ), Normandie Université ( NU ) -Normandie Université ( NU ), University of Cambridge [UK] ( CAM ), Laboratoire de Probabilités et Modèles Aléatoires ( LPMA ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Génétique et de Biologie Moléculaire et Cellulaire ( IGBMC ), Université de Strasbourg ( UNISTRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Center for Mathematical Modeling ( CMM ), Universidad de Santiago de Chile [Santiago] ( USACH ), London School of Hygiene and Tropical Medicine ( LSHTM ), University of Occupational and Environmental Health [Kitakyushu] ( UEOH ), Indian Institute of Technology Delhi ( IIT Delhi ), Institut de Recherche sur les Phénomènes Hors Equilibre ( IRPHE ), Aix Marseille Université ( AMU ) -Ecole Centrale de Marseille ( ECM ) -Centre National de la Recherche Scientifique ( CNRS ), Universidade Federal de Pernambuco [Recife] ( UFPE ), Nanoscience Institute ( NEST ), Laboratory Of Immune Cell Biology ( LICB ), JRC Institute for Environment and Sustainability ( IES ), European Commission - Joint Research Centre [Ispra] ( JRC ), Bonn Universität [Bonn], Laboratorio Nacional de Computação Cientifica [Rio de Janeiro] ( LNCC / MCT ), Royal Institute of Technology [Stockholm] ( KTH ), National ICT Australia [Sydney] ( NICTA ), Institut d'Histoire et de Philosophie des Sciences et des Techniques ( IHPST ), Université Panthéon-Sorbonne ( UP1 ) -Département d'Etudes Cognitives - ENS Paris ( DEC ), École normale supérieure - Paris ( ENS Paris ) -École normale supérieure - Paris ( ENS Paris ) -Centre National de la Recherche Scientifique ( CNRS ), Ghent University [Belgium] ( UGENT ), Children’s Hospital of Philadelphia ( CHOP ), Univeristy of Pennsylvania Medical School, Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique ( LHEEA ), École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Recherche en Génie Civil et Mécanique ( GeM ), Université de Nantes ( UN ) -École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Medical College of Georgia, Electronic Navigation Research Institute ( ENRI ), Department of Computer Science [KAIST] ( CS ), Korea Advanced Institute of Science and Technology ( KAIST ), Laboratoire de l'Accélérateur Linéaire ( LAL ), University of Massachusetts [Boston] ( UMass Boston ), Forouzanfar, Mohammad H, Alexander, Lily, Anderson, H. Ro, Bachman, Victoria F, Biryukov, Stan, Brauer, Michael, Burnett, Richard, Casey, Daniel, Coates, Matthew M, Cohen, Aaron, Delwiche, Kristen, Estep, Kara, Frostad, Joseph J, Kc, Astha, Kyu, Hmwe H, Moradi Lakeh, Maziar, Ng, Marie, Slepak, Erica Leigh, Thomas, Bernadette A, Wagner, Joseph, Aasvang, Gunn Marit, Abbafati, Cristiana, Ozgoren, Ayse Abbasoglu, Abd Allah, Foad, Abera, Semaw F, Aboyans, Victor, Abraham, Biju, Abraham, Jerry Puthenpurakal, Abubakar, Ibrahim, Abu Rmeileh, Niveen M. E, Aburto, Tania C, Achoki, Tom, Adelekan, Ademola, Adofo, Koranteng, Adou, Arsène K, Adsuar, José C, Afshin, Ashkan, Agardh, Emilie E, Al Khabouri, Mazin J, Al Lami, Faris H, Alam, Sayed Saidul, Alasfoor, Deena, Albittar, Mohammed I, Alegretti, Miguel A, Aleman, Alicia V, Alemu, Zewdie A, Alfonso Cristancho, Rafael, Alhabib, Samia, Ali, Raghib, Ali, Mohammed K, Alla, Françoi, Allebeck, Peter, Allen, Peter J, Alsharif, Ubai, Alvarez, Elena, Alvis Guzman, Nelson, Amankwaa, Adansi A, Amare, Azmeraw T, Ameh, Emmanuel A, Ameli, Omid, Amini, Heresh, Ammar, Walid, Anderson, Benjamin O, Antonio, Carl Abelardo T, Anwari, Palwasha, Cunningham, Solveig Argeseanu, Arnlöv, Johan, Arsenijevic, Valentina S. Arsic, Artaman, Al, Asghar, Rana J, Assadi, Reza, Atkins, Lydia S, Atkinson, Charle, Avila, Marco A, Awuah, Baffour, Badawi, Alaa, Bahit, Maria C, Bakfalouni, Talal, Balakrishnan, Kalpana, Balalla, Shivanthi, Balu, Ravi Kumar, Banerjee, Amitava, Barber, Ryan M, Barker Collo, Suzanne L, Barquera, Simon, Barregard, Lar, Barrero, Lope H, Barrientos Gutierrez, Tonatiuh, Basto Abreu, Ana C, Basu, Arindam, Basu, Sanjay, Basulaiman, Mohammed O, Ruvalcaba, Carolina Bati, Beardsley, Justin, Bedi, Neeraj, Bekele, Tolesa, Bell, Michelle L, Benjet, Corina, Bennett, Derrick A, Benzian, Habib, Bernabé, Eduardo, Beyene, Tariku J, Bhala, Neeraj, Bhalla, Ashish, Bhutta, Zulfiqar A, Bikbov, Bori, Abdulhak, Aref A. Bin, Blore, Jed D, Blyth, Fiona M, Bohensky, Megan A, Başara, Berrak Bora, Borges, Guilherme, Bornstein, Natan M, Bose, Dipan, Boufous, Soufiane, Bourne, Rupert R, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J, Brenner, Hermann, Briggs, Adam D. M, Broday, David M, Brooks, Peter M, Bruce, Nigel G, Brugha, Traolach S, Brunekreef, Bert, Buchbinder, Rachelle, Bui, Linh N, Bukhman, Gene, Bulloch, Andrew G, Burch, Michael, Burney, Peter G. J, Campos Nonato, Ismael R, Campuzano, Julio C, Cantoral, Alejandra J, Caravanos, Jack, Cárdenas, Rosario, Cardis, Elisabeth, Carpenter, David O, Caso, Valeria, Castañeda Orjuela, Carlos A, Castro, Ruben E, Catalá López, Ferrán, Cavalleri, Fiorella, Çavlin, Alanur, Chadha, Vineet K, Chang, Jung Chen, Charlson, Fiona J, Chen, Honglei, Chen, Wanqing, Chen, Zhengming, Chiang, Peggy P, Chimed Ochir, Odgerel, Chowdhury, Rajiv, Christophi, Costas A, Chuang, Ting Wu, Chugh, Sumeet S, Cirillo, Massimo, Claßen, Thomas Kd, Colistro, Valentina, Colomar, Mercede, Colquhoun, Samantha M, Contreras, Alejandra G, Cooper, Cyru, Cooperrider, Kimberly, Cooper, Leslie T, Coresh, Josef, Courville, Karen J, Criqui, Michael H, Cuevas Nasu, Lucia, Damsere Derry, Jame, Danawi, Hadi, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I, Davis, Adrian, Davitoiu, Dragos V, Dayama, Anand, de Castro, E. Filipa, De la Cruz Góngora, Vanessa, De Leo, Diego, de Lima, Graça, Degenhardt, Louisa, Del Pozo Cruz, Borja, Dellavalle, Robert P, Deribe, Kebede, Derrett, Sarah, Jarlais, Don C. De, Dessalegn, Muluken, Deveber, Gabrielle A, Devries, Karen M, Dharmaratne, Samath D, Dherani, Mukesh K, Dicker, Daniel, Ding, Eric L, Dokova, Klara, Dorsey, E. Ray, Driscoll, Tim R, Duan, Leilei, Durrani, Adnan M, Ebel, Beth E, Ellenbogen, Richard G, Elshrek, Yousef M, Endres, Matthia, Ermakov, Sergey P, Erskine, Holly E, Eshrati, Babak, Esteghamati, Alireza, Fahimi, Saman, Faraon, Emerito Jose A, Farzadfar, Farshad, Fay, Derek F. J, Feigin, Valery L, Feigl, Andrea B, Fereshtehnejad, Seyed Mohammad, Ferrari, Alize J, Ferri, Cleusa P, Flaxman, Abraham D, Fleming, Thomas D, Foigt, Nataliya, Foreman, Kyle J, Paleo, Urbano Fra, Franklin, Richard C, Gabbe, Belinda, Gaffikin, Lynne, Gakidou, Emmanuela, Gamkrelidze, Amiran, Gankpé, Fortuné G, Gansevoort, Ron T, García Guerra, Francisco A, Gasana, Evariste, Geleijnse, Johanna M, Gessner, Bradford D, Gething, Pete, Gibney, Katherine B, Gillum, Richard F, Ginawi, Ibrahim A. M, Giroud, Maurice, Giussani, Giorgia, Goenka, Shifalika, Goginashvili, Ketevan, Dantes, Hector Gomez, Gona, Philimon, de Cosio, Teresita Gonzalez, González Castell, Dinorah, Gotay, Carolyn C, Goto, Atsushi, Gouda, Hebe N, Guerrant, Richard L, Gugnani, Harish C, Guillemin, Franci, Gunnell, David, Gupta, Rahul, Gupta, Rajeev, Gutiérrez, Reyna A, Hafezi Nejad, Nima, Hagan, Holly, Hagstromer, Maria, Halasa, Yara A, Hamadeh, Randah R, Hammami, Mouhanad, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Haregu, Tilahun Nigatu, Haro, Josep Maria, Havmoeller, Rasmu, Hay, Simon I, Hedayati, Mohammad T, Heredia Pi, Ileana B, Hernandez, Lucia, Heuton, Kyle R, Heydarpour, Pouria, Hijar, Martha, Hoek, Hans W, Hoffman, Howard J, Hornberger, John C, Hosgood, H. Dean, Hoy, Damian G, Hsairi, Mohamed, Hu, Guoqing, Hu, Howard, Huang, Cheng, Huang, John J, Hubbell, Bryan J, Huiart, Laetitia, Husseini, Abdullatif, Iannarone, Marissa L, Iburg, Kim M, Idrisov, Bulat T, Ikeda, Nayu, Innos, Kaire, Inoue, Manami, Islami, Farhad, Ismayilova, Samaya, Jacobsen, Kathryn H, Jansen, Henrica A, Jarvis, Deborah L, Jassal, Simerjot K, Jauregui, Alejandra, Jayaraman, Sudha, Jeemon, Panniyammakal, Jensen, Paul N, Jha, Vivekanand, Jiang, Fan, Jiang, Guohong, Jiang, Ying, Jonas, Jost B, Juel, Knud, Kan, Haidong, Roseline, Sidibe S. Kany, Karam, Nadim E, Karch, André, Karema, Corine K, Karthikeyan, Ganesan, Kaul, Anil, Kawakami, Norito, Kazi, Dhruv S, Kemp, Andrew H, Kengne, Andre P, Keren, Andre, Khader, Yousef S, Khalifa, Shams Eldin Ali Hassan, Khan, Ejaz A, Khang, Young Ho, Khatibzadeh, Shahab, Khonelidze, Irma, Kieling, Christian, Kim, Daniel, Kim, Sungroul, Kim, Yunjin, Kimokoti, Ruth W, Kinfu, Yohanne, Kinge, Jonas M, Kissela, Brett M, Kivipelto, Miia, Knibbs, Luke D, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kose, M. Rifat, Kosen, Soewarta, Kraemer, Alexander, Kravchenko, Michael, Krishnaswami, Sanjay, Kromhout, Han, Ku, Tiffany, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kuipers, Ernst J, Kulkarni, Chanda, Kulkarni, Veena S, Kumar, G. Anil, Kwan, Gene F, Lai, Taavi, Balaji, Arjun Lakshmana, Lalloo, Ratilal, Lallukka, Tea, Lam, Hilton, Lan, Qing, Lansingh, Van C, Larson, Heidi J, Larsson, Ander, Laryea, Dennis O, Lavados, Pablo M, Lawrynowicz, Alicia E, Leasher, Janet L, Lee, Jong Tae, Leigh, Jame, Leung, Ricky, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Juan, Liang, Xiaofeng, Lim, Stephen S, Lindsay, M. Patrice, Lipshultz, Steven E, Liu, Shiwei, Liu, Yang, Lloyd, Belinda K, Logroscino, Giancarlo, London, Stephanie J, Lopez, Nancy, Lortet Tieulent, Joannie, Lotufo, Paulo A, Lozano, Rafael, Lunevicius, Raimunda, Ma, Jixiang, Ma, Stefan, Machado, Vasco M. P, Macintyre, Michael F, Magis Rodriguez, Carlo, Mahdi, Abbas A, Majdan, Marek, Malekzadeh, Reza, Mangalam, Srikanth, Mapoma, Christopher C, Marape, Marape, Marcenes, Wagner, Margolis, David J, Margono, Christopher, Marks, Guy B, Martin, Randall V, Marzan, Melvin B, Mashal, Mohammad T, Masiye, Felix, Mason Jones, Amanda J, Matsushita, Kunihiro, Matzopoulos, Richard, Mayosi, Bongani M, Mazorodze, Tasara T, Mckay, Abigail C, Mckee, Martin, Mclain, Abigail, Meaney, Peter A, Medina, Catalina, Mehndiratta, Man Mohan, Mejia Rodriguez, Fabiola, Mekonnen, Wubegzier, Melaku, Yohannes A, Meltzer, Michele, Memish, Ziad A, Mendoza, Walter, Mensah, George A, Meretoja, Atte, Mhimbira, Francis Apolinary, Micha, Renata, Miller, Ted R, Mills, Edward J, Misganaw, Awoke, Mishra, Santosh, Ibrahim, Norlinah Mohamed, Mohammad, Karzan A, Mokdad, Ali H, Mola, Glen L, Monasta, Lorenzo, Hernandez, Julio C. Montañez, Montico, Marcella, Moore, Ami R, Morawska, Lidia, Mori, Rintaro, Moschandreas, Joanna, Moturi, Wilkister N, Mozaffarian, Dariush, Mueller, Ulrich O, Mukaigawara, Mitsuru, Mullany, Erin C, Murthy, Kinnari S, Naghavi, Mohsen, Nahas, Ziad, Naheed, Aliya, Naidoo, Kovin S, Naldi, Luigi, Nand, Devina, Nangia, Vinay, Narayan, Km Venkat, Nash, Deni, Neal, Bruce, Nejjari, Chakib, Neupane, Sudan P, Newton, Charles R, Ngalesoni, Frida N, de Dieu Ngirabega, Jean, Nguyen, Grant, Nguyen, Nhung T, Nieuwenhuijsen, Mark J, Nisar, Muhammad I, Nogueira, José R, Nolla, Joan M, Nolte, Sandra, Norheim, Ole F, Norman, Rosana E, Norrving, Bo, Nyakarahuka, Luke, Oh, In Hwan, Ohkubo, Takayoshi, Olusanya, Bolajoko O, Omer, Saad B, Opio, John Nelson, Orozco, Ricardo, Pagcatipunan, Rodolfo S, Pain, Amanda W, Pandian, Jeyaraj D, Panelo, Carlo Irwin A, Papachristou, Christina, Park, Eun Kee, Parry, Charles D, Caicedo, Angel J. Paternina, Patten, Scott B, Paul, Vinod K, Pavlin, Boris I, Pearce, Neil, Pedraza, Lilia S, Pedroza, Andrea, Stokic, Ljiljana Pejin, Pekericli, Ayfer, Pereira, David M, Perez Padilla, Rogelio, Perez Ruiz, Fernando, Perico, Norberto, Perry, Samuel A. L, Pervaiz, Aslam, Pesudovs, Konrad, Peterson, Carrie B, Petzold, Max, Phillips, Michael R, Phua, Hwee Pin, Plass, Dietrich, Poenaru, Dan, Polanczyk, Guilherme V, Polinder, Suzanne, Pond, Constance D, Pope, C. Arden, Pope, Daniel, Popova, Svetlana, Pourmalek, Farshad, Powles, John, Prabhakaran, Dorairaj, Prasad, Noela M, Qato, Dima M, Quezada, Amado D, Quistberg, D. Alex A, Racapé, Lionel, Rafay, Anwar, Rahimi, Kazem, Rahimi Movaghar, Vafa, Rahman, Sajjad Ur, Raju, Murugesan, Rakovac, Ivo, Rana, Saleem M, Rao, Mayuree, Razavi, Homie, Reddy, K. Srinath, Refaat, Amany H, Rehm, Jürgen, Remuzzi, Giuseppe, Ribeiro, Antonio L, Riccio, Patricia M, Richardson, Lee, Riederer, Anne, Robinson, Margaret, Roca, Anna, Rodriguez, Alina, Rojas Rueda, David, Romieu, Isabelle, Ronfani, Luca, Room, Robin, Roy, Nobhojit, Ruhago, George M, Rushton, Lesley, Sabin, Nsanzimana, Sacco, Ralph L, Saha, Sukanta, Sahathevan, Ramesh, Sahraian, Mohammad Ali, Salomon, Joshua A, Salvo, Deborah, Sampson, Uchechukwu K, Sanabria, Juan R, Sanchez, Luz Maria, Sánchez Pimienta, Tania G, Sanchez Riera, Lidia, Sandar, Logan, Santos, Itamar S, Sapkota, Amir, Satpathy, Maheswar, Saunders, James E, Sawhney, Monika, Saylan, Mete I, Scarborough, Peter, Schmidt, Jürgen C, Schneider, Ione J. C, Schöttker, Ben, Schwebel, David C, Scott, James G, Seedat, Soraya, Sepanlou, Sadaf G, Serdar, Berrin, Servan Mori, Edson E, Shaddick, Gavin, Shahraz, Saeid, Levy, Teresa Shamah, Shangguan, Siyi, She, Jun, Sheikhbahaei, Sara, Shibuya, Kenji, Shin, Hwashin H, Shinohara, Yukito, Shiri, Rahman, Shishani, Kawkab, Shiue, Ivy, Sigfusdottir, Inga D, Silberberg, Donald H, Simard, Edgar P, Sindi, Shireen, Singh, Abhishek, Singh, Gitanjali M, Singh, Jasvinder A, Skirbekk, Vegard, Sliwa, Karen, Soljak, Michael, Soneji, Samir, Søreide, Kjetil, Soshnikov, Sergey, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Stapelberg, Nicolas J. 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Subjects: Male, Fine particulate matter, Nutrition and Disease, MESH : Sanitation, Health Behavior, Diseases, MESH: Metabolic Diseases, MESH: Global Health, 030204 cardiovascular system & hematology, MESH: Risk Assessment, Global Health, MESH : Nutritional Status, MESH: Occupational Exposure, 0302 clinical medicine, Unsafe Sex, MESH: Risk Factors, Risk Factors, Voeding en Ziekte, Medicine, Air-pollution, MESH : Female, 030212 general & internal medicine, MESH : Risk Assessment, Sanitation, Wasting, 2. Zero hunger, Factors de risc en les malalties, Medicine (all), [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, MESH : Occupational Diseases, MESH: Nutritional Status, All-cause mortality, MESH : Risk Factors, humanities, Environmental Exposure, Female, Humans, Metabolic Diseases, Nutritional Status, Occupational Diseases, Occupational Exposure, Risk Assessment, Tobacco smoking, 3. Good health, Nutritional Statu, MESH : Occupational Exposure, MESH : Metabolic Diseases, Cohort, medicine.symptom, Risk assessment, Blood-pressure, Human, MESH: Occupational Diseases, Risk factors in diseases, Coronary-heart-disease, MESH : Male, MESH: Health Behavior, MESH: Environmental Exposure, Population health, Body-mass index, 03 medical and health sciences, Household cooking, Cardiovascular-disease, Environmental health, General & Internal Medicine, parasitic diseases, Life Science, MESH: Sanitation, Risk factor, MESH : Health Behavior, VLAG, GBD2013, MESH: Humans, business.industry, Risk Factor, Global Burden of Disease Study, 79 behavioural, environmental and occupational, and metabolic risks, Long-term exposure, MESH : Humans, CAUSE-SPECIFIC MORTALITY, MESH: Male, Metabolic Disease, Occupational Disease, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, MALE BRITISH DOCTORS, Years of potential life lost, Relative risk, Malalties, MESH : Global Health, OUTDOOR AIR-POLLUTION, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, MESH : Environmental Exposure, MESH: Female
Abstract: Summary Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian metaregression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5−89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks. Funding Bill & Melinda Gates Foundation. Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the fi rst of a series of annual updates of the GBD. Risk factor quantifi cation, particularly of modifi able risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the fi rst level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular fi ltration rate. For most risks, data for exposure were synthesised with a Bayesian metaregression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5−89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks. Funding Bill & Melinda Gates Foundation.
Published: 2015
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22. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013

Author: Meghan D. Mooney, Ken Takahashi, Andrea Stewart, Jonathan C Brown, Shireen Sindi, Amany H Refaat, Ruben Castro, Sara Sheikhbahaei, Kyle R. Heuton, Gillian M. Hansen, Chante Karimkhani, Bryan K. Phillips, Ibrahim Abubakar, Yohannes Kinfu, Victoria F Bachman, Konstantinos Stroumpoulis, Megan Coggeshall, Lucía Cuevas-Nasu, Yichong Li, Vineet K. Chadha, Andrew G. M. Bulloch, Takayoshi Ohkubo, Don C. Des Jarlais, Giancarlo Logroscino, Francis Apolinary Mhimbira, Jefferson G Fernandes, Cheng Huang, Ejaz Ahmad Khan, Fortuné Gbètoho Gankpé, Roderick J Hay, Itamar S. Santos, Zanfina Ademi, Fiona J Charlson, Norlinah Mohamed Ibrahim, Anwar Rafay, Andrew L. Thorne-Lyman, Juanita A. Haagsma, Emmanuel A. Ameh, John J. McGrath, Massimo Cirillo, Wubegzier Mekonnen, Holly Hagan, Naohiro Yonemoto, Frida Namnyak Ngalesoni, Dietrich Plass, Matias Trillini, David Phillips, Braden Te Ao, Wanqing Chen, Yun Jin Kim, David Rojas-Rueda, Christina Papachristou, Andrew E. Moran, Richard A. Gosselin, Maziar Moradi-Lakeh, Soraya Seedat, Janet L Leasher, Belinda K Lloyd, Lorenzo Monasta, Bruno F. Sunguya, Eun-Kee Park, Eduardo A. Undurraga, Mohammad A. AlMazroa, Mohammad H. Forouzanfar, Young-Ho Khang, Vasiliki Stathopoulou, Dima M. Qato, James Scott, Ileana Heredia-Pi, Luca Ronfani, Haidong Kan, Tasara T. Mazorodze, Murugesan Raju, Saeid Shahraz, Taavi Tillmann, Wang Wenzhi, Neil Pearce, Eric Y. Tenkorang, Aliya Naheed, Ferrán Catalá-López, Sudan Prasad Neupane, Emily Dansereau, Michael McKee, Derrick A Bennett, Mazeda Hossain, Paul S. F. Yip, Grant Nguyen, Norberto Perico, Miguel Angel Alegretti, Babak Eshrati, Boris Bikbov, Palwasha Anwari, Guoqing Hu, Amelia Bertozzi-Villa, Peter A. Meaney, Farshad Farzadfar, Svetlana Popova, Tara Templin, Hmwe H Kyu, Uche S. Uchendu, Kebede Deribe, Sergey Soshnikov, Nobhojit Roy, Daniel Kim, Ilana N. Ackerman, Homie Razavi, Leslie T. Cooper, Sandra Nolte, David T. Felson, John J Huang, Yang Liu, Fiorella Cavalleri, Adrian Davis, Héctor Gómez Dantés, Klara Dokova, Yuantao Hao, Catalina Medina, Austin E Schumacher, Stan Biryukov, Jane Rowley, Arindam Basu, Jose C. Adsuar, Rosana E. Norman, Yousef Khader, Rafael Alfonso-Cristancho, Sukanta Saha, Simón Barquera, Diego Gonzalez-Medina, Philip B. Mitchell, Lars Barregard, Haidong Wang, Yongmei Li, Ami R. Moore, Marie Ng, Raghib Ali, Peter T. Serina, Lijing L Yan, Ayse Abbasoglu Ozgoren, Ricky Leung, Michelle L. Bell, Tim Driscoll, Azmeraw T. Amare, Farshad Pourmalek, Tea Lallukka, Benjamin O Anderson, Raimundas Lunevicius, Corine Karema, Robert G. Weintraub, Erin C Mullany, Anders Larsson, Glen Mola, Paulo A. Lotufo, Luke Nyakarahuka, Sayed Saidul Alam, Louisa Degenhardt, Hugh R. Taylor, E. 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A, Boyers, Lindsay N, Brayne, Carol E, Breitborde, Nicholas J. K, Briggs, Adam D, Brooks, Peter M, Brown, Jonathan C, Brugha, Traolach S, Buckle, Geoffrey C, Budke, Christine M, Bulloch, Andrew G, Campos Nonato, Ismael R, Carapetis, Jonathan R, Carpenter, David O, Castañeda Orjuela, Carlos A, Castro, Ruben E, Catalá López, Ferrán, Chadha, Vineet K, Chang, Jung Chen, Charlson, Fiona J, Chiang, Peggy P, Chimed Ochir, Odgerel, Christophi, Costas A, Coates, Matthew M, Coffeng, Luc E, Coggeshall, Megan S, Colquhoun, Samantha M, Cooke, Graham S, Cooper, Leslie T, Coppola, Luis M, Criqui, Michael H, Crump, John A, Cuevas Nasu, Lucia, Dargan, Paul I, Davitoiu, Dragos V, Del Pozo Cruz, Borja, Dellavalle, Robert P, Jarlais, Don C. De, Dharmaratne, Samath D, Dherani, Mukesh K, Diaz Torné, Cesar, Ding, Eric L, Dorsey, E. Ray, Driscoll, Tim R, Duber, Herbert C, Ebel, Beth E, Edmond, Karen M, Elshrek, Yousef M, Ermakov, Sergey P, Erskine, Holly E, Faraon, Emerito Jose A, Fay, Derek F, Feigin, Valery L, Felson, David T, Fereshtehnejad, Seyed Mohammad, Fernandes, Jefferson G, Ferrari, Alize J, Flaxman, Abraham D, Fleming, Thomas D, Forouzanfar, Mohammad H, Fowkes, F. Gerry R, Paleo, Urbano Fra, Franklin, Richard C, Gankpé, Fortuné G, Geleijnse, Johanna M, Gessner, Bradford D, Gibney, Katherine B, González Medina, Diego, Gosselin, Richard A, Gotay, Carolyn C, Gouda, Hebe N, Gugnani, Harish C, Gutiérrez, Reyna A, Hafezi Nejad, Nima, Halasa, Yara A, Hamadeh, Randah R, Hankey, Graeme J, Hansen, Gillian M, Harb, Hilda L, Hay, Simon I, Hay, Roderick J, Heredia Pi, Ileana B, Heuton, Kyle R, Hoek, Hans W, Hoffman, Howard J, Hosgood, H. Dean, Hotez, Peter J, Hoy, Damian G, Huang, John J, Iannarone, Marissa L, Iburg, Kim M, Jacobsen, Kathryn H, Jarvis, Deborah L, Jassal, Simerjot K, Jensen, Paul N, Jonas, Jost B, Karema, Corine K, Kassebaum, Nicholas J, Kemp, Andrew H, Kengne, Andre P, Khader, Yousef S, Khalifa, Shams Eldin A, Khan, Ejaz A, Khang, Young Ho, Kinge, Jonas M, Knibbs, Luke D, Kuipers, Ernst J, Kulkarni, Veena S, Kumar, G. Anil, Kyu, Hmwe H, Lansingh, Van C, Lawrynowicz, Alicia E. B, Leasher, Janet L, Levitz, Carly E, Lim, Stephen S, Lipshultz, Steven E, Lloyd, Belinda K, Lofgren, Katherine T, Looker, Katharine J, Lortet Tieulent, Joannie, Lotufo, Paulo A, Lucas, Robyn M, Lyons, Ronan A, Macintyre, Michael F, Mackay, Mark T, Margolis, David J, Marzan, Melvin B, Masci, Joseph R, Mashal, Mohammad T, Mayosi, Bongani M, Mazorodze, Tasara T, Mcgill, Neil W, Mcgrath, John J, Meaney, Peter A, Melaku, Yohannes A, Memish, Ziad A, Mensah, George A, Mhimbira, Francis A, Miller, Ted R, Mills, Edward J, Mitchell, Philip B, Mock, Charles N, Mohammad, Karzan A, Mokdad, Ali H, Mola, Glen L. D, Montine, Thomas J, Mooney, Meghan D, Moore, Ami R, Moradi Lakeh, Maziar, Moran, Andrew E, Moturi, Wilkister N, Moyer, Madeline L, Msemburi, William T, Mueller, Ulrich O, Mullany, Erin C, Murdoch, Michele E, Murthy, Kinnari S, Naidoo, Kovin S, Narayan, K. M. Venkat, Neupane, Sudan P, Newton, Charles R, Ngalesoni, Frida N, Nisar, Muhammad I, Norheim, Ole F, Norman, Rosana E, Oh, In Hwan, Ohno, Summer L, Olusanya, Bolajoko O, Pain, Amanda W, Pandian, Jeyaraj D, Panelo, Carlo Irwin A, Park, Eun Kee, Park, Jae Hyun, Patten, Scott B, Patton, George C, Paul, Vinod K, Pavlin, Boris I, Pereira, David M, Perez Padilla, Rogelio, Perez Ruiz, Fernando, Peterson, Carrie B, Phillips, Michael R, Phillips, Bryan K, Phillips, David E, Piel, Frédéric B, Poulton, Richie G, Prasad, Noela M, Pullan, Rachel L, Qato, Dima M, Quistberg, D. Alex, Rahman, Sajjad U, Rana, Saleem M, Reddy, K. Srinath, Ribeiro, Antonio L, Roberts, D. Allen, Rojas Rueda, David, Roth, Gregory A, Rothstein, David H, Rowley, Jane T, Ruhago, George M, Saeedi, Mohammad Y, Sampson, Uchechukwu K. A, Sanabria, Juan R, Santos, Itamar S, Schneider, Ione J, Schumacher, Austin E, Schwebel, David C, Scott, James G, Sepanlou, Sadaf G, Serina, Peter T, Servan Mori, Edson E, Shackelford, Katya A, Shrime, Mark G, Sigfusdottir, Inga D, Silberberg, Donald H, Simard, Edgar P, Singh, Jasvinder A, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Stanaway, Jeffrey D, Stein, Dan J, Stein, Murray B, Steiner, Timothy J, Stovner, Lars J, Sunguya, Bruno F, Sykes, Bryan L, Tabb, Karen M, Taylor, Hugh R, Ao, Braden J. Te, Temesgen, Awoke M, Tenkorang, Eric Y, Terkawi, Abdullah S, Thorne Lyman, Andrew L, Thrift, Amanda G, Thurston, George D, Tran, Bach X, Tuzcu, Emin M, Uchendu, Uche S, Ukwaja, Kingsley N, Undurraga, Eduardo A, Uzun, Selen B, Van Brakel, Wim H, van Gool, Coen H, Vasankari, Tommi J, Violante, Francesco S, Vlassov, Vasiliy V, Wagner, Gregory R, Waller, Stephen G, Warouw, Tati S, Weintraub, Robert G, Whiteford, Harvey A, Wilkinson, James D, Williams, Thomas N, Wolfe, Charles D, Wolock, Timothy M, Woolf, Anthony D, Yan, Lijing L, Yentür, Gökalp K, Yoon, Seok Jun, Younis, Mustafa Z, Zaki, Maysaa E, Salomon, Joshua A, Lopez, Alan D, Computational Science and Engineering Department [Daresbury] ( STFC ), Science & Technologie Facilities Council, Neuroépidémiologie Tropicale ( NET ), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut Génomique, Environnement, Immunité, Santé, Thérapeutique ( GEIST ), Université de Limoges ( UNILIM ) -Université de Limoges ( UNILIM ), Service de Chirurgie Thoracique et Vasculaire - Médecine vasculaire [CHU Limoges], CHU Limoges, Weill Cornell Medical College - Qatar, Qatar Foundation - Education City, Doha, Maladies chroniques, santé perçue, et processus d'adaptation ( APEMAC ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Centre d'Investigation Clinique - Epidemiologie Clinique/essais Cliniques Nancy, Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Karolinska Institute, karolinska institute, Centro de Estudios Avanzados en Zonas Aridas ( CEAZA ), Ecole Polytechnique Fédérale de Lausanne ( EPFL ), Wisconsin Division of Public Health, Regional Genetic Service, St Mary's Hospital, Manchester, Laboratoire d'Ingénierie des Matériaux ( LIM ), Centre National de la Recherche Scientifique ( CNRS ), Computer Science Department [Bristol], University of Bristol [Bristol], Lawrence Berkeley National Laboratory [Berkeley] ( LBNL ), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) ( SRI-B ), Multimedia Research Center ( MRC ), University of Alberta [Edmonton], Division of Biostatistics ( Biostat - MINNEAPOLIS ), University of Minnesota [Minneapolis], Laboratory of Neurologic Diseases, Mario Negri Institute, Milan, University of Southampton [Southampton], Imperial College London, Neurology Department, Ichilov Medical Center, Department of Public Health and Primary Care, Cambridge University, Interactions, transferts, ruptures artistiques et culturels - EA 6301 ( InTRu ), Université de Tours, Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Institute of Parasitology, STAR laboratory, Stanford University [Stanford], Unité de recherche Virologie et Immunologie Moléculaires ( VIM ), Institut National de la Recherche Agronomique ( INRA ), Tennent Institute of Ophthalmology, National University of Singapore ( NUS ), Multidisciplinary Nanotechnology Centre, Swansea University, Department of Computer Sciences [Scheffield], University of Sheffield [Sheffield], Cyprus International Institute for the Environment and Public Health, Harvard School of Public Health, Glasgow Centre for Physical Organic Chemistry, University of Glasgow, King‘s College London, Université Panthéon-Sorbonne - UFR Science Politique ( UP1 UFR11 ), Université Panthéon-Sorbonne ( UP1 ), National Diagnostics Centre ( NDC ), National University of Ireland [Galway] ( NUI Galway ), Arthritis Research UK Epidemiology Unit ( MANCHESTER - Arthritis Research ), University of Manchester [Manchester], CEGOT - Porto, Universidade do Porto [Porto], Advanced Laboratories on Embedded Systems [Roma] ( ALES ), Department of Biology [Miami], University of Miami [Coral Gables], Division of Human Nutrition, Wageningen University and Research Centre [Wageningen] ( WUR ), Spatial Ecology and Epidemiology Group, University of Oxford [Oxford], Department of Civil Engineering [Hamirpur], National Institute of Technology [Hamirpur], GEMMA — Environmental Engineering and Microbiology Research Group, Department of Hydraulic, Maritime and Environmental Engineering, Universitat Politècnica de Catalunya [Barcelona] ( UPC ), Institut National de Recherche et d'Analyse Physico-Chimique ( INRAP ), Institut National de Recherche et d'Analyse Physico-chimique (INRAP-Tunisie), University of Connecticut ( UCONN ), Norwegian Institute for Air Research ( NILU ), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) ( FEMTO-ST ), Université de Franche-Comté ( UFC ) -Centre National de la Recherche Scientifique ( CNRS ) -Ecole Nationale Supérieure de Mécanique et des Microtechniques ( ENSMM ) -Université de Technologie de Belfort-Montbeliard ( UTBM ), Tehran University, Friedrich-Alexander Universität Erlangen-Nürnberg ( FAU ), Secretariat of the Pacific Community, Public Health Division, Sociétés, Acteurs, Gouvernement en Europe ( SAGE ), Université de Strasbourg ( UNISTRA ) -Centre National de la Recherche Scientifique ( CNRS ), School of Physics and Astronomy, Washington State University ( WSU ), Laboratoire de Physique de l'ENS Lyon ( Phys-ENS ), École normale supérieure - Lyon ( ENS Lyon ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ), Institut de recherche en informatique de Toulouse ( IRIT ), Institut National Polytechnique [Toulouse] ( INP ) -Université Toulouse 1 Capitole ( UT1 ) -Université Toulouse - Jean Jaurès ( UT2J ) -Université Toulouse III - Paul Sabatier ( UPS ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique ( CNRS ), School of Computer Science - China University of Geosciences (China University of Geosciences (East Area)), Université Catholique de Louvain ( UCL ), Div Cyclotron & Radiopharmaceut Sci ( DRDO, INMAS ), Univ New Delhi, University of St Andrews [Scotland], University of Cape Town, Department of Neuroscience, Karolinska Institutet [Stockholm], Institut de Physique Nucléaire d'Orsay ( IPNO ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Computer Science and Engineering [Daejeon] (Chungnam National University), Lawrence University, Gastroenterology & Hepatology, Tata Research Development and Design Center ( TRDDC ), TCS Innovation Labs, Laboratoire MOLTECH-Anjou [Angers] ( MOLTECH ANJOU ), Université d'Angers ( UA ) -Centre National de la Recherche Scientifique ( CNRS ), University of Helsinki [Helsinki], Google Inc [Mountain View], Research at Google, Swedish Defense Research Agency ( FOI ), Centre de Recherche en Information Biomédicale sino-français ( CRIBS ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Laboratory of Image Science and Technology [Nanjing] ( LIST ), Southeast University [Jiangsu]-School of Computer Science and Engineering, Laboratoire de glaciologie et géophysique de l'environnement ( LGGE ), Observatoire des Sciences de l'Univers de Grenoble ( OSUG ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Centre National de la Recherche Scientifique ( CNRS ), School of Business and Informatics, University of Boras, Department of Mechanical and Automation Engineering ( CAD Laboratory ), The Chinese University of Hong Kong [Hong Kong], Università degli studi di Bari, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] ( Heudiasyc ), Université de Technologie de Compiègne ( UTC ) -Centre National de la Recherche Scientifique ( CNRS ), Department of plant pathology and microbiology - centre for sustainable pest and disease management, Rothamsted Research, RGU, Department of Rheumatology and Connective Tissue Diseases, Medical University of Lublin, Barts and The London School of Medicine and Dentistry, Queen Mary University of London ( QMUL ), Centre d'économie de la Sorbonne ( CES ), Université Panthéon-Sorbonne ( UP1 ) -Centre National de la Recherche Scientifique ( CNRS ), Paris School of Economics ( PSE ), Istituto Dalle Molle di Studi sull'Intelligenza Artificiale ( IDSIA ), Università della Svizzera italiana ( USI ) -Scuola universitaria professionale della Svizzera italiana [Manno] ( SUPSI ), Anaesthetics, Southampton University Hospital, Department of Mathematics, University of Iowa [Iowa City], College of Medicine, Alfaisal University, Saudi Ministry of Health, Institut national des recherches agricoles du Bénin, Centre de Recherches agricoles du Sud, Departments of Epidemiology and Nutrition, Unit of Human Nutrition, Agricultural University of Athens, Department of Animal Science, PennState University [Pennsylvania] ( PSU ), University of Virginia, University of Virginia [Charlottesville], Epidemiology and Biostatistics Unit, Institute for Maternal and Child Health - IRCCS ‘‘Burlo Garofolo', Jet Propulsion Laboratory ( JPL ), NASA-California Institute of Technology ( CALTECH ), Division of Cardiovascular Medicine and Channing Division of Network Medicine, Brigham and Women's Hospital [Boston], Division of Gastroenterology and Hepatology, Department of Immunology, Mayo Clinic, Department of Chemistry, Scientific Computing Research Unit, Department of dermatology, Milano University-Azienda Ospedaleria Ospedali Riuniti di Bergamo, Department of epidemiology and Public Health, Faculty of Medicine, Hong Kong Baptist University ( HKBU ), Département Optique ( OPT ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], Department of Neurology Lunds University Hospital Lund, Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux ( SAMOVAR ), Institut Mines-Télécom [Paris]-Télécom SudParis ( TSP ) -Centre National de la Recherche Scientifique ( CNRS ), Département Réseaux et Services Multimédia Mobiles ( RS2M ), Institut Mines-Télécom [Paris]-Télécom SudParis ( TSP ), Electrical Engineering and Computer Science Department - Case Western Reserve University, Case Western Reserve University [Cleveland], Institut Lumière Matière [Villeurbanne] ( ILM ), Université Claude Bernard Lyon 1 ( UCBL ), World Health Organization, Nordic School of Public Health, The James Hutton Institute, Sero, Sero consulting, Evolutionary Ecology of Infectious Disease Group, Department of Zoology, Horia Hulubei National Institute for Physics and Nuclear Engineering, Dunedin School of Medicine, University of Otago, Department of Physics, Clarendon Laboratory, Center for TeleInFrastruktur ( CTIF ), Aalborg University [Denmark] ( AAU ), Physikalisches Institut [Freiburg], Albert-Ludwigs-Universität Freiburg, Savoirs, Textes, Langage (STL) - UMR 8163 ( STL ), Université de Lille-Centre National de la Recherche Scientifique ( CNRS ), Dept.of Computer Science, Indian Institute of Technology Madras ( IIT Madras ), Istituto Mario Negri Bergamo, Centro Ricerche e Trapianti Villa Camozzi, Universidade Estadual Paulista Júlio de Mesquita ( UNESP ), Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Université Grenoble Alpes - UFR Médecine ( UGA UFRM ), Université Grenoble Alpes ( UGA ), Clinical Epidemiology and Aging Research, German Cancer Research Center, Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Symantec, European Microsoft Innovation Center ( EMIC ), Microsoft Corporation [Redmond, Wash.], Laboratoire de Mécanique, Physique et Géosciences ( LMPG ), Université Le Havre Normandie ( ULH ), Normandie Université ( NU ) -Normandie Université ( NU ), Novartis institute for tropical diseases, Institut de Génétique et de Biologie Moléculaire et Cellulaire ( IGBMC ), Université de Strasbourg ( UNISTRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Departments of Anatomy and Cell Biology, Wayne State University School of Medicine, Departments of Ophthalmology, Departments of Applied Physics [New Haven], Yale University [New Haven], Center for Mathematical Modeling ( CMM ), Universidad de Santiago de Chile [Santiago] ( USACH ), Laboratory for Atmospheric and Space Physics [Boulder] ( LASP ), University of Colorado Boulder [Boulder], University of Occupational and Environmental Health [Kitakyushu] ( UEOH ), Department of Computer Science and Engineering [New Delhi], Indian Institute of Technology Delhi ( IIT Delhi ), Institut de Recherche sur les Phénomènes Hors Equilibre ( IRPHE ), Aix Marseille Université ( AMU ) -Ecole Centrale de Marseille ( ECM ) -Centre National de la Recherche Scientifique ( CNRS ), GlaxoSmithKline, Imperial College London-Clinical Imaging Center, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, Yale School of Medicine-Yale School of Medicine-Yale Stem Cell Center, Maclean Building, Benson Lane, Crowmarsh Gifford, Centre for Ecology and Hydrology, Nanoscience Institute ( NEST ), Dipartimento di Fisica, Università di Pisa, Aristotle University of Thessaloniki, Laboratory Of Immune Cell Biology ( LICB ), National Institutes of Health ( NIH ), Institute of Human Genetics, Bonn Universität [Bonn], Occupational Health Unit, Bologna University Hospital-Sant'Orsola-Malpighi Polyclinic, Royal Institute of Technology [Stockholm] ( KTH ), Institut für Informatik [München/Munich] ( LMU ), Ludwig-Maximilians-Universität München, NICTA [Eveleigh], National ICT Australia [Sydney] ( NICTA ), Manchester Academic Health Sciences Centre, Institut d'Histoire et de Philosophie des Sciences et des Techniques ( IHPST ), Université Panthéon-Sorbonne ( UP1 ) -Département d'Etudes Cognitives - ENS Paris ( DEC ), École normale supérieure - Paris ( ENS Paris ) -École normale supérieure - Paris ( ENS Paris ) -Centre National de la Recherche Scientifique ( CNRS ), Ghent University [Belgium] ( UGENT ), German Research Centre for Geosciences - Helmholtz-Centre Potsdam ( GFZ ), Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique ( LHEEA ), École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Recherche en Génie Civil et Mécanique ( GeM ), Université de Nantes ( UN ) -École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Neurorestoration Group, King‘s College London-Wolfson Centre for Age-related Diseases, Department of Computer Science [KAIST] ( CS ), Korea Advanced Institute of Science and Technology ( KAIST ), Laboratoire de l'Accélérateur Linéaire ( LAL ), Natl Engn Res Ctr Vegetables, Key Lab Biol & Genet Improvement Hort Crops N Chi, Beijing Acad Agr & Forestry Sci, University Hospital Puerta de Hierro, Madrid, Computational Science and Engineering Department [Daresbury] (STFC), Neuroépidémiologie Tropicale (NET), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Weill Cornell Medicine [Qatar], Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale (INSERM), Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratoire d'Ingénierie des Matériaux (LIM), Centre National de la Recherche Scientifique (CNRS), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) (SRI-B), Multimedia Research Center (MRC), University of Alberta, Division of Biostatistics (Biostat - MINNEAPOLIS), University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, University of Southampton, University of Cambridge [UK] (CAM), Interactions, transferts, ruptures artistiques et culturels - EA 6301 (InTRu), Université de Tours (UT), Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Stanford University, Unité de recherche Virologie et Immunologie Moléculaires (VIM (UR 0892)), Institut National de la Recherche Agronomique (INRA), National University of Singapore (NUS), Université Paris 1 Panthéon-Sorbonne - UFR Science Politique (UP1 UFR11), Université Paris 1 Panthéon-Sorbonne (UP1), National Diagnostics Centre (NDC), National University of Ireland [Galway] (NUI Galway), Arthritis Research UK Epidemiology Unit (MANCHESTER - Arthritis Research), Universidade do Porto = University of Porto, Advanced Laboratories on Embedded Systems [Roma] (ALES), Wageningen University and Research [Wageningen] (WUR), University of Oxford, Universitat Politècnica de Catalunya [Barcelona] (UPC), Institut National de Recherche et d'Analyse Physico-Chimique (INRAP), University of Connecticut (UCONN), Norwegian Institute for Air Research (NILU), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), University of Tehran, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Sociétés, Acteurs, Gouvernement en Europe (SAGE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), The George Washington University (GW), Washington State University (WSU), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT), Université Catholique de Louvain = Catholic University of Louvain (UCL), Div Cyclotron & Radiopharmaceut Sci (DRDO, INMAS), School of Physics and Astronomy [St Andrews], Tata Research Development and Design Center (TRDDC), MOLTECH-Anjou, Université d'Angers (UA)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Swedish Defense Research Agency (FOI), Centre de Recherche en Information Biomédicale sino-français (CRIBS), Université de Rennes (UR)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratory of Image Science and Technology [Nanjing] (LIST), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Department of Mechanical and Automation Engineering (CAD Laboratory), Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC), Queen Mary University of London (QMUL), Centre d'économie de la Sorbonne (CES), Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), Université Paris 1 Panthéon-Sorbonne (UP1)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), Università della Svizzera italiana = University of Italian Switzerland (USI)-Scuola universitaria professionale della Svizzera italiana = University of Applied Sciences and Arts of Southern Switzerland [Manno] (SUPSI), Pennsylvania State University (Penn State), Penn State System-Penn State System, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Hong Kong Baptist University (HKBU), Département Optique (OPT), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Département Réseaux et Services Multimédia Mobiles (TSP - RS2M), University of Melbourne, Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), University of Otago [Dunedin, Nouvelle-Zélande], Center for TeleInFrastruktur (CTIF), Aalborg University [Denmark] (AAU), Savoirs, Textes, Langage (STL) - UMR 8163 (STL), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Indian Institute of Technology Madras (IIT Madras), Universidade Estadual Paulista Júlio de Mesquita Filho = São Paulo State University (UNESP), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Université Grenoble Alpes - UFR Médecine (UGA UFRM), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), European Microsoft Innovation Center (EMIC), Laboratoire de Mécanique, Physique et Géosciences (LMPG), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU), Novartis Institute for Tropical Diseases (NITD), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Center for Mathematical Modeling (CMM), Universidad de Chile = University of Chile [Santiago] (UCHILE), Laboratory for Atmospheric and Space Physics [Boulder] (LASP), University of Colorado [Boulder], University of Occupational and Environmental Health [Kitakyushu] (UEOH), Indian Institute of Technology Delhi (IIT Delhi), Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Yale University [New Haven]-Yale School of Medicine [New Haven, Connecticut] (YSM), Nanoscience Institute (NEST), University of Pisa - Università di Pisa, Laboratory Of Immune Cell Biology (LICB), National Institutes of Health [Bethesda] (NIH), Rheinische Friedrich-Wilhelms-Universität Bonn, Royal Institute of Technology [Stockholm] (KTH ), Institut für Informatik [München/Munich] (LMU), Ludwig-Maximilians-Universität München (LMU), National ICT Australia [Sydney] (NICTA), Institut d'Histoire et de Philosophie des Sciences et des Techniques (IHPST), Université Paris 1 Panthéon-Sorbonne (UP1)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University (UGENT), German Research Centre for Geosciences - Helmholtz-Centre Potsdam (GFZ), Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA), École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [KAIST] (CS), Korea Advanced Institute of Science and Technology (KAIST), Kardiyoloji, Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Minnesota [Twin Cities], Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Unité de recherche Virologie et Immunologie Moléculaires (VIM), Université Panthéon-Sorbonne - UFR Science Politique (UP1 UFR11), Université Panthéon-Sorbonne (UP1), Wageningen University and Research Centre [Wageningen] (WUR), Institut National de Recherche et d'Analyse Physico-chimique (Ariana, Tunisie) (INRAP), Université de Franche-Comté (UFC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Technologie de Belfort-Montbeliard (UTBM), George Washington University (GW), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, Université Catholique de Louvain (UCL), MOLTECH-ANJOU (MOLTECH-ANJOU), Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), University of Helsinki, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Università della Svizzera italiana (USI)-Scuola universitaria professionale della Svizzera italiana [Manno] (SUPSI), California Institute of Technology (CALTECH)-NASA, Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Centre National de la Recherche Scientifique (CNRS), Département Réseaux et Services Multimédia Mobiles (RS2M), Universidade Estadual Paulista Júlio de Mesquita Filho [São José do Rio Preto] (UNESP), Université Grenoble Alpes (UGA), Universidad de Santiago de Chile [Santiago] (USACH), Yale University [New Haven]-Yale University School of Medicine, Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Ghent University [Belgium] (UGENT), Université de Nantes - Faculté des Sciences et des Techniques, Grelier, Elisabeth, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Universidade do Porto, Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Université Toulouse 1 Capitole (UT1), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Università degli studi di Bari Aldo Moro (UNIBA), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Università della Svizzera italiana = University of Italian Switzerland (USI)-Scuola universitaria professionale della Svizzera italiana [Manno] (SUPSI), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne-Université européenne de Bretagne - European University of Brittany (UEB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Universiteit Gent = Ghent University [Belgium] (UGENT), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-CHU Limoges-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Belfort-Montbeliard (UTBM), Institut de Chimie du CNRS (INC)-Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Nantes (ECN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Wolfson Centre for Age-related Diseases-King‘s College London, Cell biology, Public Health, Epidemiology, Health Technology Assessment (HTA), Erasmus MC other, Pathology, and Cardiothoracic Surgery
Subjects: Gerontology, Male, CHANGING RELATION, Nutrition and Disease, MESH : Life Expectancy, MESH : Aged, ECONOMIC-DEVELOPMENT, Poison control, MESH: Global Health, Global Health, Socioeconomic Factor, Communicable Disease, MESH : Chronic Disease, Health Transition, Voeding en Ziekte, Quality-Adjusted Life Year, SELF-RATED HEALTH, MESH : Socioeconomic Factors, Medicine, MESH : Female, MESH: Mortality, Premature, 2. Zero hunger, MESH: Aged, education.field_of_study, MESH: Middle Aged, Mortality rate, Medicine (all), GBD2013 diseases, [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, General Medicine, Middle Aged, 3. Good health, MESH : Wounds and Injuries, Epidemiological transition, MESH: Quality-Adjusted Life Years, MESH: Communicable Diseases, NONCOMMUNICABLE DISEASES, Female, Quality-Adjusted Life Years, MESH: Life Expectancy, MESH: Health Transition, Human, MESH: Socioeconomic Factors, ACUTE MYOCARDIAL-INFARCTION, MESH : Male, MORTALITY TRENDS, Population, MESH : Health Transition, Communicable Diseases, Article, Life Expectancy, EUROPEAN-UNION, SDG 3 - Good Health and Well-being, General & Internal Medicine, SYSTEMATIC ANALYSIS, Disability-adjusted life year, Humans, Life Science, MESH : Middle Aged, Mortality, education, Premature, MESH : Mortality, Premature, VLAG, Aged, MESH: Humans, business.industry, Mortality, Premature, MESH: Chronic Disease, MESH : Communicable Diseases, Wounds and Injurie, MESH : Humans, MESH : Quality-Adjusted Life Years, Non-communicable disease, Chronic Disease, Socioeconomic Factors, Wounds and Injuries, medicine.disease, MESH: Male, LOW SOCIOECONOMIC-STATUS, Years of potential life lost, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Wounds and Injuries, Life expectancy, RISK-FACTORS, MESH : Global Health, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, MESH: Female, Demography
Abstract: Summary Background The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age–sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. Methods We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. Findings Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6–6·6), from 65·3 years (65·0–65·6) in 1990 to 71·5 years (71·0–71·9) in 2013, HALE at birth rose by 5·4 years (4·9–5·8), from 56·9 years (54·5–59·1) to 62·3 years (59·7–64·8), total DALYs fell by 3·6% (0·3–7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6–29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non–communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. Interpretation Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition—in which increasing sociodemographic status brings structured change in disease burden—is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions. Funding Bill & Melinda Gates Foundation. BACKGROUND: The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development. METHODS: We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time. FINDINGS: Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries. INTERPRETATION: Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition-in which increasing sociodemographic status brings structured change in disease burden-is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions. FUNDING: Bill & Melinda Gates Foundation.
Published: 2015
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23. Smoking and adult glioma: a population-based case-control study in China

Author: Boqi Liu, Haiyu Pang, Lei Hou, Yuyan Wang, Wei Han, Biao Zhang, Fang Xue, Xiaonong Zou, Yuanli Chen, Jingmei Jiang, Yanping Wu, Jun-Yao Li, Zixing Wang, and Philip C. Nasca
Subjects: Adult, Male, China, Cancer Research, medicine.medical_specialty, Population, Clinical Investigations, Population based, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Internal medicine, Glioma, medicine, Humans, education, education.field_of_study, Brain Neoplasms, business.industry, Smoking, Confounding, Case-control study, Cancer, Odds ratio, Middle Aged, medicine.disease, Confidence interval, Surgery, Oncology, Case-Control Studies, 030220 oncology & carcinogenesis, Female, Neurology (clinical), business, 030217 neurology & neurosurgery
Abstract: Background Smoking increases the risk of numerous cancers; however, an association of smoking with adult gliomas has not been found in a population. Methods This case-control study included 4556 glioma cases (ICD-9 code 191.0-191.9) aged ≥ 30 years and 9112 controls from a national survey of smoking and mortality in China in 1989-1991. Controls from 325 255 surviving spouses of all-cause deaths were randomly assigned to cases in each of 103 areas according to sex and age groups at a ratio of 2:1. Smoking information was ascertained retrospectively by interviewing surviving spouses. Results After adjustment for confounders, smoking increased the risk of glioma deaths by 11% (odds ratio [OR] = 1.11; 95% confidence interval [CI]: 1.03-1.21). Compared with non-smokers; the increased risk was 9% (OR = 1.09; 95% CI: 0.99-1.20) in men and 16% (OR = 1.16; 95% CI: 1.00-1.36) in women. The risk increased with age and doses. For individuals aged ≥ 50 years, smoking was associated with higher risk of glioma death by 25% (OR = 1.25; 95% CI: 1.15-1.38); this increased risk for smokers who smoked ≥ 20 cigarettes daily for ≥ 30 years was 53% (OR = 1.53; 95% CI: 1.34-1.74). There were similar findings in both men and women and with either pathology-based or non-pathology-based comparisons. Conclusions This study indicates that smoking is associated with glioma deaths in the Chinese population. Long-term heavy smoking could be a factor for risk stratification in individuals attending brain tumor clinics.
Published: 2015
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24. Increased lung cancer mortality rates in the Chinese population from 1973-1975 to 2004-2005: An adverse health effect from exposure to smoking

Author: Manman Jia, Gong-Huan Yang, Mu Hu, Yuan Jiang, Xiaonong Zou, and Xiu-Yi Zhi
Subjects: Gynecology, Cancer Research, medicine.medical_specialty, Adenosquamous carcinoma, business.industry, Mortality rate, Incidence (epidemiology), Public health, Cancer, medicine.disease, Oncology, medicine, Adenocarcinoma, business, Lung cancer, Demography, Sex characteristics
Abstract: BACKGROUND Lung cancer incidence and mortality rates have increased substantially in China despite improvements in clinical diagnosis and treatment approaches as well as significant advances in the implementation of tobacco-control policies in recent decades. METHODS Age-standardized mortality rates and age-specific rates of lung cancer in China were estimated for the periods 1973 to 1975, 1990 to 1992, and 2004 to 2005 using data from 3 National Death Surveys. Among patients with lung cancer who were identified from a hospital-based information system, the percentages of ever-smokers were analyzed according to histologic and demographic variables. RESULTS Age-standardized mortality from lung cancer in China dramatically increased from 7.30 per 100,000 during 1973 through 1975 to 27.62 per 100,000 during 2004 through 2005. Increases in lung cancer age-standardized mortality were consistent among men and women in urban and rural populations. Among men ages 75 to 79 years, lung cancer mortality increased remarkably to 453.67 per 100,000 in 2004 and 2005 (from 246.78 per 100,000 during 1990-1992 and from 53.65 per 100,000 during 1973-1975). Among 6674 patients with lung cancer who were identified from 2003 to 2007 from a hospital-based database, 82.97% of men were ever-smokers (73.35% of men with adenocarcinoma and 91.8% of men with squamous cell carcinoma), and 11.18% of women were ever-smokers (6% of women with adenosquamous carcinoma and 39.02% of women with squamous cell carcinoma). Differences in the numbers of ever-smokers were observed between age groups but not according to the year of diagnosis. CONCLUSIONS The consistent and rapid increases in lung cancer mortality rates observed in the Chinese population and the high prevalence of exposure to smoking in China prompt a strong call for the implementation of a comprehensive tobacco-control policy and specific public health educational strategies. Cancer 2015;121:3107-12. © 2015 American Cancer Society.
Published: 2015
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25. Traffic-related air pollution and lung cancer: A meta-analysis

Author: Xia Wan, Gongbo Chen, Gonghuan Yang, and Xiaonong Zou
Subjects: Pulmonary and Respiratory Medicine, Operations research, business.industry, Incidence (epidemiology), Air pollution, General Medicine, Strengthening the reporting of observational studies in epidemiology, medicine.disease, medicine.disease_cause, Checklist, Confidence interval, chemistry.chemical_compound, Oncology, chemistry, Meta-analysis, Environmental health, medicine, Nitrogen dioxide, Lung cancer, business
Abstract: Background We conducted a meta-analysis to evaluate the association between traffic-related air pollution and lung cancer in order to provide evidence for control of traffic-related air pollution. Methods Several databases were searched for relevant studies up to December 2013. The quality of articles obtained was evaluated by the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Statistical analysis, including pooling effective sizes and confidential intervals, was performed. Results A total of 1106 records were obtained through the database and 36 studies were included in our analysis. Among the studies included, 14 evaluated the association between ambient exposure to traffic-related air pollution and lung cancer and 22 studies involved occupational exposure to air pollution among professional drivers. Twenty-two studies were marked A level regarding quality, 13 were B level, and one was C level. Exposure to nitrogen dioxide (meta-odds ratio [OR]: 1.06, 95% confidence interval [CI]: 0.99–1.13), nitrogen oxide (meta-OR: 1.04, 95% CI: 1.01–1.07), sulfur dioxide (meta-OR: 1.03, 95% CI: 1.02–1.05), and fine particulate matter (meta-OR: 1.11, 95% CI: 1.00–1.22) were positively associated with a risk of lung cancer. Occupational exposure to air pollution among professional drivers significantly increased the incidence (meta-OR: 1.27, 95% CI: 1.19–1.36) and mortality of lung cancer (meta-OR: 1.14, 95% CI: 1.04–1.26). Conclusion Exposure to traffic-related air pollution significantly increased the risk of lung cancer.
Published: 2015
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26. Effects of active, passive, and combined smoking on cervical cancer mortality: a nationwide proportional mortality study in Chinese urban women

Author: Margaret A. Gates, Biao Zhang, Tao Lu, Yanping Wu, Xiaonong Zou, Jun-Yao Li, Boqi Liu, Fang Xue, Zixing Wang, Wei Han, Yuyan Wang, Philip C. Nasca, Jingmei Jiang, Yuanli Chen, Haiyu Pang, and Lei Hou
Subjects: Adult, Risk, China, Cancer Research, medicine.medical_specialty, Passive smoking, Uterine Cervical Neoplasms, medicine.disease_cause, Epidemiology, Humans, Medicine, Cities, Risk factor, Aged, Retrospective Studies, Gynecology, Cervical cancer, business.industry, Incidence (epidemiology), Smoking, Absolute risk reduction, Middle Aged, medicine.disease, Passive Smoke Exposure, Oncology, Spouse, Female, Tobacco Smoke Pollution, business, Demography
Abstract: To determine whether smoking, in any form, is a risk factor in the development of cervical cancer (CC) among urban Chinese women.We ascertained retrospectively the smoking habits of 1,865 women (aged 35+) who had died from CC (cases) and 48,781 who had died from causes unrelated to smoking (controls) in 24 cities using data from a large national survey of smoking and mortality in 1989-1991. We assessed the risk of smoking on CC mortality with and without considering passive smoke exposure from a spouse using a proportional mortality study design.Overall, there was a 51.0 % excess risk of death from CC among smokers. When the spouse's exposure was further considered, the RR (95 % CI) for exposed versus unexposed women was 1.28 (1.04-1.57) for passive smokers, 1.49 (1.02-2.20) for active smokers, and 1.69 (1.27-2.26) for women with both exposures (all p0.001). Significant dose-response associations were observed between smoking and CC for all categories of exposure. For example, individuals with both smoking exposure had the highest risk of CC mortality with moderate [RR = 1.67 (1.18-2.38)] and high [RR = 1.88 (1.04-3.41)] daily cigarette consumption, and they also had the highest risk with ≤15 years exposure [RR = 1.73 (1.19-2.52)] and15 years exposure [RR = 1.95 (1.15-3.32)], compared with the active and passive groups (p for trend0.001).Younger trend of CC death and the rapid increase in smoking among young women may have a profound impact on future incidence of CC. Our findings emphasize the need for preventive efforts among both women and men in China.
Published: 2015
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27. High Spicy Food Intake and Risk of Cancer: A Meta-analysis of Case-control Studies

Author: Qi Zhou, Ping Zhao, Tong-Zhang Zheng, Yuanli Chen, Haike Lei, Yu-Heng Chen, Xiaonong Zou, Jia Du, Mei He, and Hui Qiu
Subjects: 0301 basic medicine, MEDLINE, lcsh:Medicine, Cochrane Library, Cancer Incidence, 03 medical and health sciences, Eating, 0302 clinical medicine, Risk Factors, Stomach Neoplasms, Environmental health, Case–control Studies, Meta-analysis, Spicy Food, Confidence Intervals, Odds Ratio, Medicine, Humans, Food science, Spices, business.industry, Incidence (epidemiology), Incidence, Meta Analysis, lcsh:R, Case-control study, Cancer, General Medicine, Odds ratio, medicine.disease, 030104 developmental biology, 030220 oncology & carcinogenesis, Case-Control Studies, business, Spicy food intake
Abstract: Background: Studies on the association between spicy food intake and cancer risk have reported inconsistent results. We quantitatively assessed this association by conducting a meta-analysis based on evidence from case–control studies. Methods: PubMed, EMBASE, and the Cochrane Library were searched for eligible publications. Combined odds ratios (OR s) with their 95% confidence interval (CI) were calculated using a random- or fixed-effects model. The methodological quality of the included articles was assessed using the Newcastle–Ottawa scale (NOS). All data were analyzed using STATA 11.0 software (version 11.0; StataCorp., College Station, TX, USA). Subgroup analyses were also performed with stratification by region, sex, number of cases, cancer subtype, source of the control group, and NOS score. Results: A total 39 studies from 28 articles fulfilled the inclusion criteria for the meta-analysis (7884 patients with cancer and 10,142 controls). Comparison of the highest versus lowest exposure category in each study revealed a significant OR of 1.76 (95% CI = 1.35–2.29) in spite of significant heterogeneity (P < 0.001). In the subgroup analyses, this positive correlation was still found for gastric cancer, different regions, different numbers of cases, different sources of the control group, and high-quality articles (NOS score of ≥ 7). However, no statistically significant association was observed for women, esophageal cancer, gallbladder cancer, or low-quality articles (NOS score of
Published: 2017

28. [Changing Epidemic of Lung CancerTobacco and Situation of Tobacco Control in China]

Author: Xiaonong, Zou, Manman, Jia, Xin, Wang, and Xiuyi, Zhi
Subjects: Male, China, Lung Neoplasms, 吸烟与肺癌重点号, Smoking, Tobacco, Humans, Female, Tobacco Smoke Pollution
Abstract: Lung cancer is the leading cause of cancer death and morbidity in China. Smoking and exposure to secondhand smoking closely related to lung cancer. Recently, series policies of tobacco control and lung cancer prevention was carried out. However, burden of lung cancer is still serious, and smoking rate in male is still very high, and in never smokers exposure to secondhand smoking is still very extensive. In this paper, epidemic situation of lung cancer, smoking and second hand smoking are described, at the same time, current implementations of tobacco control policies are summarized.肺癌居我国恶性肿瘤死亡和发病的首位。肺癌与吸烟和二手烟暴露密切相关。近年来，我国采取了一系列控烟和肺癌防治措施，但肺癌负担依然严重，男性吸烟率仍居高不下，非吸烟者二手烟暴露十分广泛。本文对我国近年来肺癌、吸烟和二手烟暴露的流行现状进行描述，同时对我国目前所实施的控烟措施进行了综述。.
Published: 2017

29. Cancer survival in China, 2003-2005: A population-based study

Author: Rongshou Zheng, Wanqing Chen, Guohui Song, Xibin Sun, Jianmei Dong, Suqin Huang, Michel P Coleman, Yong-Zhou Shen, Ning Wang, Lingbin Du, Jianguo Chen, Hongmei Zeng, Xue Qin Yu, Feng Jin, Guoping Guo, Ming Wu, Fengdong Zhu, Deli Zhao, Jingao Tang, Jian Wang, Liang Yu, Kuangrong Wei, Xiaoping Gu, Yanhua Li, Siwei Zhang, Jianshun Chen, Hengming Ge, Limei Zhang, Xiaoping Yang, Yuming Guo, Xiaonong Zou, Yutong He, Peter D. Baade, and Qilong Li
Subjects: Cancer Research, education.field_of_study, medicine.medical_specialty, Relative survival, business.industry, Population, Cancer, Esophageal cancer, medicine.disease, Confidence interval, Cancer registry, Surgery, Oncology, Medicine, Rural area, business, education, Liver cancer, Demography
Abstract: Limited population-based cancer registry data available in China until now has hampered efforts to inform cancer control policy. Following extensive efforts to improve the systematic cancer surveillance in this country, we report on the largest pooled analysis of cancer survival data in China to date. Of 21 population-based cancer registries, data from 17 registries (n = 138,852 cancer records) were included in the final analysis. Cases were diagnosed in 2003-2005 and followed until the end of 2010. Age-standardized relative survival was calculated using region-specific life tables for all cancers combined and 26 individual cancers. Estimates were further stratified by sex and geographical area. The age-standardized 5-year relative survival for all cancers was 30.9% (95% confidence intervals: 30.6%-31.2%). Female breast cancer had high survival (73.0%) followed by cancers of the colorectum (47.2%), stomach (27.4%), esophagus (20.9%), with lung and liver cancer having poor survival (16.1% and 10.1%), respectively. Survival for women was generally higher than for men. Survival for rural patients was about half that of their urban counterparts for all cancers combined (21.8% vs. 39.5%); the pattern was similar for individual major cancers except esophageal cancer. The poor population survival rates in China emphasize the urgent need for government policy changes and investment to improve health services. While the causes for the striking urban-rural disparities observed are not fully understood, increasing access of health service in rural areas and providing basic health-care to the disadvantaged populations will be essential for reducing this disparity in the future.
Published: 2014
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30. Incidence and mortality of female breast cancer in China, 2009

Author: Hongmei Zeng, Wanqing Chen, Rongshou Zheng, Siwei Zhang, and Xiaonong Zou
Subjects: Pulmonary and Respiratory Medicine, Gerontology, education.field_of_study, Cancer prevention, business.industry, Incidence (epidemiology), Mortality rate, Population, Cancer, General Medicine, medicine.disease, Cancer registry, Breast cancer, Oncology, medicine, Rural area, education, business, Demography
Abstract: Background The National Cancer Registration of China provides annual updates on female breast cancer incidence and mortality. Methods Data on female breast cancer incidence and mortality was obtained from the population-based cancer registries around China. Based on the criteria of data quality, 72 registries' data was included for further analysis. Incidence and mortality rates of female breast cancer were calculated and stratified by age, sex, and geographical area. Results Female population coverage over 72 cancer registries was 42 238 968, with 28 503 924 in urban areas and 13 735 044 in rural areas. The crude cancer incidence rate in all areas was 42.55/100 000, and the age-standardize rates by Chinese population and World population were 23.16/100 000 and 28.99/100 000, respectively. The incidence rates in urban areas were much higher than those in rural areas. The crude cancer mortality was 10.24/100 000 in all areas, and age-standardized mortality rates by China and World population were 4.94/100 000 and 6.56/100 000, respectively. Age-adjusted mortality rates in urban areas were also higher than those in rural areas. Age specific incidence rates reached highest at the age group of 50–54, whereas the age specific mortality rates were highest in the age group of 85 and above. Conclusion Breast cancer was the most common cancer found in Chinese women in 2009 and the disease was more prevalent in urban areas than in rural areas. Systematic interventions of cancer prevention and control are needed.
Published: 2013
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31. Lung cancer incidence and mortality in China, 2009

Author: Rongshou Zheng, Wanqing Chen, Jie He, Xiaonong Zou, Siwei Zhang, and Ping Zhao
Subjects: Pulmonary and Respiratory Medicine, Oncology, medicine.medical_specialty, business.industry, Incidence (epidemiology), General Medicine, medicine.disease, Internal medicine, Epidemiology of cancer, medicine, Lung cancer, China, business
Published: 2013
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32. Cancer incidence and mortality in China, 2013

Author: Tingting Zuo, Zhixun Yang, Hongmei Zeng, Rongshou Zheng, Wanqing Chen, Changfa Xia, Siwei Zhang, Jie He, and Xiaonong Zou
Subjects: 0301 basic medicine, Adult, Male, Cancer Research, medicine.medical_specialty, China, Time Factors, Adolescent, Colorectal cancer, Causes of cancer, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Age Distribution, Cause of Death, Neoplasms, Epidemiology of cancer, medicine, Humans, Registries, Sex Distribution, Stomach cancer, Child, Aged, Gynecology, Aged, 80 and over, Cancer prevention, business.industry, Incidence, Infant, Newborn, Cancer, Infant, Health Status Disparities, Esophageal cancer, Middle Aged, medicine.disease, Cancer registry, 030104 developmental biology, Oncology, 030220 oncology & carcinogenesis, Child, Preschool, Female, business, Demography
Abstract: Objective National Central Cancer Registry of China (NCCRC) updated nationwide statistics of cancer incidence and mortality in China using population-based cancer registration data in 2013 from all available cancer registries. Methods In 2016, 255 registries' data were qualified and included in this analysis. We estimated numbers of new cancer cases and deaths in China in 2013 using age-specific rates and corresponding national population stratified by area, sex, age group (0, 1–4, 5–9, 10–14…85+) and cancer type. The world Segi's population was applied for age-standardized rates. All rates were expressed per 100,000 person-year. Results A total of 3,682,000 new cancer cases and 2,229,300 cancer deaths were estimated in China in 2013. Cancers of lung, female breast, stomach, liver, colon-rectum and esophagus were the most common cancers, accounting for about half of all cancer new cases. Lung cancer, liver cancer, stomach cancer, esophageal cancer, colorectal cancer were the five leading causes of cancer death, accounting for about 60% of all cancer deaths. The cancer patterns showed differences not only between male and female, but also among different geographic regions in China. For overall cancers, the age-standardized incidence rates were stable during the past decades in male, but significantly increased by 2.2% per year in female. Conclusions Cancer poses a major threat to public health and the cancer burden keep raising in China. The annual updated cancer statistics can provide scientific basis for cancer prevention and control.
Published: 2017

33. Cancer incidence and mortality in China, 2006

Author: Wanqing Chen, Siwei Zhang, Xiaonong Zou, and Ping Zhao
Subjects: Oncology, Gerontology, Cancer Research, medicine.medical_specialty, Colorectal cancer, business.industry, Mortality rate, Cancer, Esophageal cancer, medicine.disease, Breast cancer, Internal medicine, Epidemiology of cancer, medicine, Original Article, Cumulative incidence, Stomach cancer, business
Abstract: Objective: To describe the cancer incidence and mortality rates in 2006 and evaluate the cancer burden in China. Methods: Cancer registration data in 2006 from 34 cancer registries were collected, evaluated and pooled to calculate cancer incidence and mortality rates. The data analyses included mortality to incidence ratio (MI), morphological verification percentage (MV%) and proportion of death certification only (DCO%). Cumulative incidence and mortality rates were calculated using crude data, age-standardized data, and specific data for cancer site, age, sex and area (urban or rural). Results: In 2006, 34 registries with qualified registration data covered a total population of 59,567,322 (46,558,108 in urban areas and 13,009,214 in rural areas). The crude and age-standardized cancer incidence rates were 273.66 per 100,000 and 190.54 per 100,000, respectively. The crude and age-standardized cancer mortality rates were 175.70 per 100,000 and 117.67 per 100,000, respectively. Cancers of lung, stomach, colon and rectum, liver, and breast in female were the five most common forms of cancer in China, which accounted for 58.99% of all new cancer cases. Lung cancer was the leading cause of cancer death, followed by stomach cancer, liver cancer, esophageal cancer and colorectal cancer. Conclusion: Cancer is still an important public health issue in China with an increasing disease burden. Specifically, the incidence rates for lung cancer, colorectal cancer and breast cancer were increasing, but those for stomach cancer and esophageal cancer were decreasing. However, age-specific incidence rate remained stable, indicating that the aging population was the major source of the increasing cancer burden.
Published: 2011
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34. Tobacco Smoking and Trends in Histological Subtypes of Female Lung Cancer at The Cancer Hospital of The Chinese Academy of Medical Sciences Over 13 Years

Author: Mark Parascandola, Qinfu Feng, Q. Zeng, E. Vogtmann, M. Jia, and Xiaonong Zou
Subjects: Oncology, Cancer Research, medicine.medical_specialty, business.industry, Incidence (epidemiology), Mortality rate, Cancer, medicine.disease, Smoking history, Internal medicine, medicine, Adenocarcinoma, Non small cell, business, Lung cancer, Cancer staging
Abstract: Background: Smoking among Chinese women accounts for a small proportion, but the incidence and mortality rates of female lung cancer is increasing in recent years. Studies found that there were changes in histologic subtypes of lung cancer patients in China. Aim: This study investigated the tobacco smoking and trends in histologic subtypes of female lung cancer in a cancer hospital in China. Methods: Demographic, smoking history and histologic information about female lung cancer patients diagnosed or treated from 2000 to 2012 was collected from Cancer Hospital, Chinese Academy of Medical Science (CHCAMS). Trends of histologic subtypes calculated with annual percentage change (APC). The distribution differences of adenocarcinoma (ADC), squamous cell carcinoma (SCC), small cell lung cancer (SCLC) and the other subtypes between smokers and nonsmokers were calculated by 7th AJCC cancer staging. Results: Totally of 5,870 female cases of lung cancer, including 630 with history of smoking and 5,240 without, were analyzed. The number of female lung cancer patients increased from 509 (2000-2002) to 1744 (2012-2013). The main histologic type of lung cancer was adenocarcinoma (ADC) (72.93%), followed by small cell lung cancer (SCLC) (11.06%), squamous cell carcinoma (SCC) (8.38%) and the other (7.63%). Among smokers, the proportion of SCC decreased from 40.5% to 23.7% (APC = -11.68%, P = 0.005), however, the ADC increased from 35.7% to 50.7% (APC = 8.63%, P = 0.009). In nonsmokers, the ADC was 76.1%, and SCC was 5.9%. ADC increased from 63.1% to 80.6% (APC = -21.33%, P = 0.006), SCC decreased from 13.6% to 4.5% (APC = 3.86%, P = 0.016). Among squamous cell carcinoma, the cases with history of smoking were more likely diagnosed at early stages (I/II: 47.1%) than those at late stages (III, 34.3%; IV, 18.6%). Conclusion: The number of female lung cancer patients was increased in CHCAMS by year of diagnosis. In both smoking and nonsmoking cases, the proportion of adenocarcinoma was increasing. Among the squamous cell carcinoma, smokers seem to find in early stages.
Published: 2018
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35. Evaluation on the incidence, mortality and tendency of lung cancer in China

Author: Wanqing Chen, Siwei Zhang, and Xiaonong Zou
Subjects: Pulmonary and Respiratory Medicine, medicine.medical_specialty, Cancer prevention, business.industry, Mortality rate, Incidence (epidemiology), Cancer, General Medicine, medicine.disease, Annual Percent Change, Cancer registry, Surgery, Oncology, Epidemiology, Medicine, business, Lung cancer, Demography
Abstract: Objective: To analyze lung cancer epidemiological trends and estimate the lung cancer burden in China. Methods: The age-specific mortality/incidence ratios in different geographical areas and for both sexes for lung cancer were obtained from the National Cancer Registration database in 2004 and 2005. Cancer crude mortality rates were retrieved from the database of the third national death survey from 2004–2005. Age-specific incidence rates of lung cancer were calculated using mortality and mortality/incidence ratios. The annual percent change was estimated with a log regression model using joinpoint software analyzing pooled lung cancer incidence data from 10 cancer registries from 1988 to 2005. Results: The total estimated new lung cancer cases and deaths in 2005 were 536 407 and 475 768 respectively, the numbers were higher for men than for women, and show an increase of 1.63% annually from 1988 to 2005. However, the trend showed a slowdown of 0.55% after being adjusted for age. Conclusions: Lung cancer is one of the major health issues in China and the burden is getting serious. Aging is the main cause for the increasing incidence and mortality of lung cancer. Effective cancer prevention and control is imperative. Tobacco control especially should be implemented in nationwide.
Published: 2010
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36. Smoking-attributable deaths and potential years of life lost from a large, representative study in China

Author: Freddy Sitas, Xianjia Zeng, Boqi Liu, Junyao Li, Wei Han, Ping Zhao, Jingmei Jiang, Xiaonong Zou, and Yanping Wu
Subjects: Adult, Male, China, medicine.medical_specialty, Health (social science), media_common.quotation_subject, Longevity, Population, Life Expectancy, Sex Factors, Cause of Death, Epidemiology, medicine, Humans, education, Aged, Retrospective Studies, media_common, Cause of death, Aged, 80 and over, education.field_of_study, business.industry, Data Collection, Smoking, Age Factors, Public Health, Environmental and Occupational Health, Case-control study, Retrospective cohort study, Middle Aged, Years of potential life lost, Case-Control Studies, Life expectancy, Female, business, Demography
Abstract: Objectives To provide a more accurate estimate of early smoking-attributable mortality and potential years of life lost using data from a representative study of 103 study areas in China. Methods Two datasets were employed as follows. Firstly, retrospective national mortality survey data, which included a population of 67 million in 103 study areas, and about 1 million adults who died in 1986–1988; secondly, nationally representative case-control comparative data was extracted from the survey data to measure the effect of smoking on age trends in smoking-attributable mortality. Potential years of life lost, and sex differences in life expectancy in smokers and non-smokers in the total population aged 35 and over were also estimated. Results Tobacco caused 11.2% (16.0% of men and 3.7% of women) of total deaths in 1987, and more than two-thirds of these excess deaths occurred between the ages of 50 and 74 years, but only less than 5% excess deaths occurred at ages under 50. Although life expectancies varied with region or sex differences, the years of life lost attributable to smoking was almost the same. Smokers at age 35 lost about 3 years of life expectancy in comparison with never smokers. The study also confirmed that more than 50% of the sex difference in life expectancy was accounted for by smoking. Conclusion Fully understanding the consequences of smoking in relation to mortality can clarify its effects on the health and longevity of the entire population.
Published: 2009
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37. Comparative study of control selection in a national population -based case-control study: Estimating risk of smoking on cancer deaths in Chinese men

Author: Jingmei Jiang, Boqi Liu, Philip C. Nasca, Wei Han, Xiaonong Zou, Xianjia Zeng, Xiaobing Tian, Yanping Wu, Ping Zhao, Junyao Li
Subjects: lcsh:R, lcsh:Medicine
Abstract: Purpose: To assess the validation of a novel control selection design by comparing the consistency between the new design and a routine design in a large case-control study that was incorporated into a nationwide mortality survey in China. Methods: A nationwide mortality study was conducted during 1989-1991. Surviving spouses or other relatives of all adults who died during 1986-1988 provided detailed information about their own as well as the deceased person's smoking history. In this study, 130,079 males who died of various smoking-related cancers at age 35 or over were taken as cases, while 103,248 male surviving spouses (same age range with cases) of women who died during the same period and 49,331 males who died from causes other than those related to smoking were used as control group 1 and control group 2, respectively. Consistency in the results when comparing cases with each of the control groups was assessed. Results: Consistency in the results was observed in the analyses using different control groups although cancer deaths varied with region and age. Equivalence could be ascertained using a 15% criterion in most cancer deaths which had high death rates in urban areas, but they were uncertain for most cancers in rural areas irrespective of whether the hypothesis testing showed significant differences or not. Conclusions: Sex-matched living spouse control design as an alternative control selection for a case-control study is valid and feasible, and the basic principles of the equivalence study are also supported by epidemiological survey data.
Published: 2009

38. The association between lung cancer incidence and ambient air pollution in China: A spatiotemporal analysis

Author: Siwei Zhang, Shanshan Li, Gail M. Williams, Wanqing Chen, Hongmei Zeng, Xiaonong Zou, Rongshou Zheng, Adrian G. Barnett, Rachel R. Huxley, and Yuming Guo
Subjects: Adult, Male, China, Lung Neoplasms, 010504 meteorology & atmospheric sciences, Meteorology, Air pollution, 010501 environmental sciences, medicine.disease_cause, 01 natural sciences, Biochemistry, Ozone, Spatio-Temporal Analysis, Air pollutants, Environmental health, Air Pollution, medicine, Humans, Lung cancer, 0105 earth and related environmental sciences, General Environmental Science, Aged, Aged, 80 and over, Air Pollutants, Ambient air pollution, Incidence (epidemiology), Incidence, Middle Aged, medicine.disease, Confidence interval, Relative risk, Female, Particulate Matter
Abstract: Background China is experiencing more and more days of serious air pollution recently, and has the highest lung cancer burden in the world. Objectives To examine the associations between lung cancer incidence and fine particles (PM2.5) and ozone in China. Methods We used 75 communities’ data of lung cancer incidence from the National Cancer Registration of China from 1990 to 2009. The annual concentrations of fine particles (PM2.5) and ozone at 0.1°×0.1° spatial resolution were generated by combing remote sensing, global chemical transport models, and improvements in coverage of surface measurements. A spatial age-period-cohort model was used to examine the relative risks of lung cancer incidence associated with the air pollutants, after adjusting for impacts of age, period, and birth cohort, sex, and community type (rural and urban) as well as the spatial variation on lung cancer incidence. Results The relative risks of lung cancer incidence related to a 10 µg/m3 increase in 2-year average PM2.5 were 1.055 (95% confidence interval (CI): 1.038, 1.072) for men, 1.149 (1.120, 1.178) for women, 1.060 (1.044, 1.075) for an urban communities, 1.037 (0.998, 1.078) for a rural population, 1.074 (1.052, 1.096) for people aged 30–65 years, and 1.111 (1.077, 1.146) for those aged over 75 years. Ozone also had a significant association with lung cancer incidence. Conclusions The increased risks of lung cancer incidence were associated with PM2.5 and ozone air pollution. Control measures to reduce air pollution would likely lower the future incidence of lung cancer.
Published: 2015

39. Female breast cancer incidence and mortality in 2011, China

Author: Manman, Jia, Rongshou, Zheng, Siwei, Zhang, Hongmei, Zeng, Xiaonong, Zou, and Wanqing, Chen
Subjects: Original Article
Abstract: Breast cancer is the most common cancer diagnosis in women. During the past 30 years, mortality of breast cancer in Chinese women showing a gradual upward trend, it has become the crucial death reasons of female.In 2014, there were 234 population-based cancer registries submitting their data of 2011 to the National Central Cancer Registry (NCCR) of China and 177 cancer registries' data were selected after quality evaluation. The selected cancer registries were classified as urban areas and rural areas, in each level. The crude incidence and mortality rates of female breast cancer were calculated by age-groups. Age-standardized rates were described by China and World standard population. And the national population data of China was used to combine with the cancer registries' data to estimate the female breast cancer burden in 2011 in China.The estimated number of female breast cancer cases was 248,620. The crude incidence rate, age-standardized rate by China and World population were 37.86 per 100,000, 28.51 per 100,000 and 26.65 per 100,000, respectively. The estimated number of female breast cancer death in 2011 of China was about 60,473. The crude, age-standardized mortalities by China population and World population were 9.21 per 100,000, 6.57 per 100,000 and 6.38 per 100,000, respectively. The incidence and mortality rates were both higher in urban areas than rural areas. Trend of age-specific incidence rates in urban and rural was similar, reaching peak at 55-59 years old. The trend of age-specific mortality rates was very similar before 60 between urban and rural areas, but after that, the urban areas curve was rapidly mounting as the age growing and much higher than rural.Breast cancer is still a major health burden for Chinese women especially in urban areas. Prevention strategies such as weight control, high-quality screening, diagnosis and treatment may help control the disease.
Published: 2015

40. Provincial-level cancer burden attributable to active and second-hand smoking in China.

Author: Changfa Xia, Rongshou Zheng, Hongmei Zeng, Maigeng Zhou, Lijun Wang, Siwei Zhang, Xiaonong Zou, Kexin Sun, Zhixun Yang, He Li, Parascandola, Mark, Farhad Islami, and Wanqing Chen
Subjects: SMOKING prevention, MORTALITY risk factors, LONGITUDINAL method, RISK assessment, SEX distribution, SMOKING, SURVEYS, TUMORS, GOVERNMENT policy, SYMPTOMS, RELATIVE medical risk
Published: 2019
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41. The mortality patterns of lung cancer between 1990 and 2013 in Xuanwei, China

Author: Weijiang Hu, Gonghuan Yang, Gongbo Chen, Hecang Huang, Xiangyun Ma, Xiaonong Zou, Hongyan Ren, Xin Sun, Bofu Ning, and Xia Wan
Subjects: Pulmonary and Respiratory Medicine, Male, Rural Population, Cancer Research, China, Lung Neoplasms, Risk Factors, Smoke, Medicine, Humans, Lung cancer, Aged, Retrospective Studies, business.industry, Mortality rate, Age specific mortality, Retrospective cohort study, medicine.disease, Coal, Oncology, Mortality data, Air Pollution, Indoor, Death registration, Female, Rural area, business, Demography
Abstract: Objectives To explore the variations in the mortality trends, especially death due to lung cancer, from 1990 to 2013 in Xuanwei City. Materials and methods Mortality data were collected in Xuanwei during the 2nd and 3rd National Retrospective Sampling Survey on Mortality and Routine Death Registration System (DRS) during 2011–2013. According to the result of the survey on under-reported deaths, mortality data from DRS during 2011–2013 were adjusted. Disease specific mortality rate, age-standardized mortality rate (ASMR) and 45Q15 were calculated in Xuanwei and compared with those in rural areas of China. Results During three periods, 1990–1992, 2004–2005 and 2011–2013, lung cancer contributed to 56.86%, 58.45% and 63.03% of deaths from all cancers respectively with a much higher proportion than rural areas nationally. The ASMR of lung cancer for males surged from 41.43/10 5 to 88.17/10 5 during 1990–2005 and it surged from 37.70/10 5 to 74.45/10 5 for females. Although they declined slightly during 2011–2013 (82.53/10 5 and 62.62/10 5 for males and females respectively), the ASMR of lung cancer among males in Xuanwei was three times of that in rural areas in China, and it was six times higher among females. The 45Q15 of lung cancer for males in Xuanwei was 3–5 times of that in rural areas of China and for females it was 7–9 times. The high-mortality areas of lung cancer were still located in Laibin, Longchang, Wanshui and Shuanglong Communities. High-mortality areas of lung cancer expanded to their surrounding areas and those in southeast. Conclusions Although indoor air pollution caused by smoky coal has been fairly well controlled, patterns of death due to lung cancer have not obviously changed. The mortality rate of lung cancer among females was similar to that among males. Therefore, further studies should be conducted to comprehensively explore the risk factors of lung cancer in Xuanwei.
Published: 2014

42. Traffic-related air pollution and lung cancer: A meta-analysis

Author: Gongbo, Chen, Xia, Wan, Gonghuan, Yang, and Xiaonong, Zou
Subjects: meta-analysis, traffic-related air pollution, Original Articles, Lung cancer, Letter to the Editor
Abstract: Background We conducted a meta-analysis to evaluate the association between traffic-related air pollution and lung cancer in order to provide evidence for control of traffic-related air pollution. Methods Several databases were searched for relevant studies up to December 2013. The quality of articles obtained was evaluated by the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Statistical analysis, including pooling effective sizes and confidential intervals, was performed. Results A total of 1106 records were obtained through the database and 36 studies were included in our analysis. Among the studies included, 14 evaluated the association between ambient exposure to traffic-related air pollution and lung cancer and 22 studies involved occupational exposure to air pollution among professional drivers. Twenty-two studies were marked A level regarding quality, 13 were B level, and one was C level. Exposure to nitrogen dioxide (meta-odds ratio [OR]: 1.06, 95% confidence interval [CI]: 0.99–1.13), nitrogen oxide (meta-OR: 1.04, 95% CI: 1.01–1.07), sulfur dioxide (meta-OR: 1.03, 95% CI: 1.02–1.05), and fine particulate matter (meta-OR: 1.11, 95% CI: 1.00–1.22) were positively associated with a risk of lung cancer. Occupational exposure to air pollution among professional drivers significantly increased the incidence (meta-OR: 1.27, 95% CI: 1.19–1.36) and mortality of lung cancer (meta-OR: 1.14, 95% CI: 1.04–1.26). Conclusion Exposure to traffic-related air pollution significantly increased the risk of lung cancer.
Published: 2014

43. The incidences and mortalities of major cancers in China, 2010

Author: Wanqing Chen, Rongshou Zheng, Siwei Zhang, Ping Zhao, Hongmei Zeng, and Xiaonong Zou
Subjects: Male, China, Oncology, Incidence, Neoplasms, Brief Report, malignant tumor, Humans, Female, Registries, Cancer registry, mortality
Abstract: To estimate the cancer incidences and mortalities in China in 2010, the National Central Cancer Registry (NCCR) of China evaluated data for the year of 2010 from 145 qualified cancer registries covering 158,403,248 people (92,433,739 in urban areas and 65,969,509 in rural areas). The estimates of new cancer cases and cancer deaths were 3,093,039 and 1,956,622 in 2010, respectively. The percentage of morphologically verified cases were 67.11%; 2.99% of incident cases were identified through death certification only, with the mortality to incidence ratio of 0.61. The crude incidence was 235.23/100,000 (268.65/100,000 in males and 200.21/100,000 in females). The age-standardized rates by Chinese standard population (ASR China) and by world standard population (ASR world) were 184.58/100,000 and 181.49/100,000, respectively, with a cumulative incidence (0-74 years old) of 21.11%. The crude cancer mortality was 148.81/100,000 (186.37/100,000 in males and 109.42/100,000 in females). The ASR China and ASR world were 113.92/100,000 and 112.86/100,000, respectively, with a cumulative mortality of 12.78%. Lung, breast, gastric, liver, esophageal, colorectal, and cervical cancers were the most common cancers. Lung, liver, gastric, esophageal, colorectal, breast, and pancreatic cancers were the leading causes of cancer deaths. The coverage of cancer registration has rapidly increased in China in recent years and may reflect more accurate cancer burdens among populations living in different areas. Given the increasing cancer burden in the past decades, China should strengthen its cancer prevention and control.
Published: 2014
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44. Cancer survival in China, 2003-2005: a population-based study

Author: Hongmei, Zeng, Rongshou, Zheng, Yuming, Guo, Siwei, Zhang, Xiaonong, Zou, Ning, Wang, Limei, Zhang, Jingao, Tang, Jianguo, Chen, Kuangrong, Wei, Suqin, Huang, Jian, Wang, Liang, Yu, Deli, Zhao, Guohui, Song, Jianshun, Chen, Yongzhou, Shen, Xiaoping, Yang, Xiaoping, Gu, Feng, Jin, Qilong, Li, Yanhua, Li, Hengming, Ge, Fengdong, Zhu, Jianmei, Dong, Guoping, Guo, Ming, Wu, Lingbin, Du, Xibin, Sun, Yutong, He, Michel P, Coleman, Peter, Baade, Wanqing, Chen, and Xue Qin, Yu
Subjects: Adult, Aged, 80 and over, Male, China, Adolescent, Incidence, Infant, Newborn, Infant, Middle Aged, Survival Rate, Young Adult, Age Distribution, Child, Preschool, Neoplasms, Humans, Female, Registries, Child, Aged
Abstract: Limited population-based cancer registry data available in China until now has hampered efforts to inform cancer control policy. Following extensive efforts to improve the systematic cancer surveillance in this country, we report on the largest pooled analysis of cancer survival data in China to date. Of 21 population-based cancer registries, data from 17 registries (n = 138,852 cancer records) were included in the final analysis. Cases were diagnosed in 2003-2005 and followed until the end of 2010. Age-standardized relative survival was calculated using region-specific life tables for all cancers combined and 26 individual cancers. Estimates were further stratified by sex and geographical area. The age-standardized 5-year relative survival for all cancers was 30.9% (95% confidence intervals: 30.6%-31.2%). Female breast cancer had high survival (73.0%) followed by cancers of the colorectum (47.2%), stomach (27.4%), esophagus (20.9%), with lung and liver cancer having poor survival (16.1% and 10.1%), respectively. Survival for women was generally higher than for men. Survival for rural patients was about half that of their urban counterparts for all cancers combined (21.8% vs. 39.5%); the pattern was similar for individual major cancers except esophageal cancer. The poor population survival rates in China emphasize the urgent need for government policy changes and investment to improve health services. While the causes for the striking urban-rural disparities observed are not fully understood, increasing access of health service in rural areas and providing basic health-care to the disadvantaged populations will be essential for reducing this disparity in the future.
Published: 2014

45. Report of cancer incidence and mortality in China, 2010

Author: Wanqing, Chen, Rongshou, Zheng, Siwei, Zhang, Ping, Zhao, Hongmei, Zeng, and Xiaonong, Zou
Subjects: Original Article
Abstract: To estimate the cancer incidences and mortalities in China in 2010.On basis of the evaluation procedures and data quality criteria described in the National Central Cancer Registry (NCCR), data from 219 cancer registries were evaluated. Data from 145 registries were identified as qualified and then accepted for the 2010 cancer registry report. The incidences and mortalities of major cancers and the overall incidence and mortality were stratified by residency (urban or rural), areas (eastern, middle, and western), gender, and age. The cancer cases and deaths were estimated based on age-specific rate and national population in 2010. The China 2010 Population Census data and Segi's world population data were used for calculating the age-standardized cancer incidence/mortality rates.Data were obtained from a total of 145 cancer registries (63 in urban areas and 82 in rural areas) covering 158,403,248 people (92,433,739 in urban areas and 65,969,509 in rural areas). The percentage of morphologically verified cases (MV%) were 67.11%; 2.99% of incident cases were identified through proportion of death certification only (DCO%), with the mortality to incidence ratio of (M/I) 0.61. The estimates of new cancer cases and cancer deaths were 3,093,039 and 1,956,622 in 2010, respectively. The crude incidence was 235.23/10(5) (268.65/10(5) in males and 200.21/10(5) in females), the age-standardized rates by Chinese standard population (ASR China) and by world standard population (ASR world) were 184.58/10(5) and 181.49/10(5), and the cumulative incidence rate (0-74 age years old) was 21.11%. The cancer incidence and ASR China were 256.41/10(5) and 187.53/10(5) in urban areas and 213.71/10(5) and 181.10/10(5) in rural areas. The crude cancer mortality in China was 148.81/10(5) (186.37/10(5) in males and 109.42/10(5) in females), the age-standardized mortalities by Chinese standard population and by world standard population were 113.92/10(5) and 112.86/10(5), and the cumulative mortality rate (0-74 age years old) was 12.78%. The cancer mortality and ASR China were 156.14/10(5) and 109.21/10(5) in urban areas 141.35/10(5) and 119.00/10(5) in rural areas, respectively. Lung cancer, female breast cancer, gastric cancer, liver cancer, esophageal cancer, colorectal cancer, and cervical cancer were the most common cancers. Lung cancer, liver cancer, gastric cancer, esophageal cancer, colorectal cancer, breast cancer, and pancreatic cancer were the leading causes of cancer deaths.The coverage of cancer registration has rapidly increased in China in recent years and may reflect more accurate cancer burdens among populations living in different areas. As the basis of cancer control program, cancer registration plays an irreplaceable role in cancer surveillance, intervention evaluation, and policy-making. Given the increasing cancer burden in the past decades, China should strengthen its cancer prevention and control.
Published: 2014

46. Lung cancer incidence and mortality in China, 2009

Author: Wanqing, Chen, Rongshou, Zheng, Siwei, Zhang, Xiaonong, Zou, Ping, Zhao, and Jie, He
Abstract: The National Central Cancer Registry (NCCR) is a governmental organization for cancer surveillance affiliated to the Bureau of Disease Control, Ministry of Health, in China. It annually collects cancer registration data from local registries and then analyzes and publishes the results to provide useful information for making anti-cancer policy, program evaluation, and etiology research. At the end of 2012, the NCCR reported cancer statistics for 2009.By mid 2012, 104 population-based cancer registries reported cancer incidence and mortality data, including demographic information, for 2009, to the NCCR. After an evaluation procedure, a total of 72 registries' data met the criteria, which was then compiled for analysis. Individual lung cancer cases were retrieved from the national database based on the International Classification of Diseases (ICD)-10 topography code as "C33, C34," including cancers of the trachea and bronchus. The crude incidence and mortality rates of lung cancer were calculated by gender, age, and location (urban/rural). China's population in 1982 and Segi's population structures were used for age-standardized rates.In cancer registration areas in 2009, lung cancer was the most common cancer in China and in urban areas, the second most common cancer in rural areas. It was the leading cause of cancer death both in males and females, urban and rural areas. The incidence and mortality rates of lung cancer were higher in males than those in females, and in urban areas than in rural areas. The age-specific incidence and mortality rates showed that both rates were relatively low for those aged under 50 years, but dramatically increased and reached a peak in the age group of 80-84 years.Lung cancer is the most common cancer in China and leading cause of cancer death. Primary and secondary prevention should be carried out in each group, such as tobacco control and early detection.
Published: 2012

47. Esophageal cancer incidence and mortality in China, 2009

Author: Wanqing, Chen, Yutong, He, Rongshou, Zheng, Siwei, Zhang, Hongmei, Zeng, Xiaonong, Zou, and Jie, He
Subjects: Original Article
Abstract: Esophageal cancer incident cases and deaths in 2009 were retrieved from national database of population based cancer registry to describe esophageal cancer burden in registration areas.In 2012, 104 population-based cancer registries reported cancer incidence and mortality data of 2009 to Chinese National Central Cancer Registry. Total 72 registries' data met the national criteria to be pooled and analyzed. The crude incidence and mortality rates of esophageal cancer were calculated by age, gender and area. China sensus in 1982 and Segi's world population were applied for age standardized rates.The crude incidence of esophageal cancer ranked fifth in all cancer sites with rate of 22.14/100,000 (30.44/100,000 for male and 13.64/100,000 for female, 14.21/100,000 in urban and 38.44/100,000 in rural). Age-standardized rates by China population (CASR) and World population (WASR) for incidence were 10.88/100,000 and 14.81/100,000 respectively. The crude mortality of esophageal cancer ranked fourth in all cancer sites with rate of 16.77/100,000 (23.29/100,000 for male and 10.11/100,000 for female, 10.59/100,000 in urban and 29.47/100,000 in rural). The CASR and WASR for mortality were 7.75/100,000 and 10.76/100,000 respectively. For both of incidence and mortality, the rates of esophageal cancer were much higher in males than in females, in rural areas than in urban areas. The overall age-specific incidence and mortality rates showed that both rates were relatively low before 45 years old, and then gradually increased, reaching peak in age group of 80-84.The burden of esophageal cancer remained high in China, especially for males in rural areas. Effective prevention and control action, such as health education, nutrition intervention and screening should be enhanced in the future.
Published: 2012

48. [Estimation and projection of lung cancer incidence and mortality in China]

Author: Wanqing, Chen, Siwei, Zhang, and Xiaonong, Zou
Subjects: Adult, Aged, 80 and over, Male, China, Lung Neoplasms, Adolescent, Incidence, Infant, Newborn, Infant, Middle Aged, 基础研究, Child, Preschool, Humans, Female, Child, Aged
Abstract: The aim of this study is to analyze lung cancer epidemiological trend and estimate lung cancer burden in China.Lung cancer age specific mortality and incidence rate ratios in different areas and sexes were obtained from national cancer registration database in 2004 and 2005. Cancer crude mortalities were retrieved from the database of the third national death survey, 2004-2005. Age specific incidence rates of lung cancer were calculated using mortality and M/I ratios. Annual percent change (APC) was estimated by log regression model using Joint Point software by analyzing pooled lung cancer incidence data from 10 cancer registries from 1988 to 2005.The total estimated new cases and deaths of lung cancer in 2005 were 536 407 and 475 768 which were higher in male than in female. There was 1.63% increase of lung cancer incidence per year from 1988 to 2005, however, the trend showed a slowdown by 0.55% annually after adjusted by age.Lung cancer is one of major health issues in China and the burden is getting serious. Ageing population is main cause for increasing incidence and mortality of lung cancer. Effective cancer prevention and control is imperative. Especially, tobacco control should be carried out in statewide.
Published: 2010

49. Comparative study of control selection in a national population-based case-control study: Estimating risk of smoking on cancer deaths in Chinese men

Author: Philip C. Nasca, Ping Zhao, Xiaonong Zou, Boqi Liu, Jingmei Jiang, Yanping Wu, Jun-Yao Li, Wei Han, Xianjia Zeng, and Xiaobing Tian
Subjects: Gerontology, Adult, Male, Risk, medicine.medical_specialty, China, epidemiologic methods, MEDLINE, Chinese men, Asian People, Neoplasms, Epidemiology, medicine, Humans, comparative study, Aged, business.industry, Mortality rate, case-control studies, Smoking, Case-control study, Cancer, General Medicine, Middle Aged, medicine.disease, Control Groups, Spouse, Control selection, Female, Rural area, business, Demography, Research Paper
Abstract: Purpose: To assess the validation of a novel control selection design by comparing the consistency between the new design and a routine design in a large case-control study that was incorporated into a nationwide mortality survey in China. Methods: A nationwide mortality study was conducted during 1989-1991. Surviving spouses or other relatives of all adults who died during 1986-1988 provided detailed information about their own as well as the deceased person's smoking history. In this study, 130,079 males who died of various smoking-related cancers at age 35 or over were taken as cases, while 103,248 male surviving spouses (same age range with cases) of women who died during the same period and 49,331 males who died from causes other than those related to smoking were used as control group 1 and control group 2, respectively. Consistency in the results when comparing cases with each of the control groups was assessed. Results: Consistency in the results was observed in the analyses using different control groups although cancer deaths varied with region and age. Equivalence could be ascertained using a 15% criterion in most cancer deaths which had high death rates in urban areas, but they were uncertain for most cancers in rural areas irrespective of whether the hypothesis testing showed significant differences or not. Conclusions: Sex-matched living spouse control design as an alternative control selection for a case-control study is valid and feasible, and the basic principles of the equivalence study are also supported by epidemiological survey data.
Published: 2009

50. Case-spouse control design in practice: an experience in estimating smoking and chronic obstructive pulmonary disease deaths in Chinese adults

Author: Ping Zhao, Junshi Chen, Freddy Sitas, Yanping Wu, Boqi Liu, Jingmei Jiang, Junyao Li, Xiaonong Zou, Wei Han, and Xianjia Zeng
Subjects: Adult, Male, Rural Population, medicine.medical_specialty, Pediatrics, China, Urban Population, MEDLINE, chronic obstructive pulmonary diseases, Pulmonary Disease, Chronic Obstructive, Age Distribution, Asian People, Risk Factors, Cause of Death, Epidemiology, medicine, Prevalence, Humans, Sex Distribution, Spouses, Cause of death, Aged, Retrospective Studies, Medicine(all), Aged, 80 and over, COPD, lcsh:R5-920, business.industry, Mortality rate, Smoking, Case-control study, Retrospective cohort study, General Medicine, Middle Aged, medicine.disease, mortality, Control Groups, Spouse, Case-Control Studies, Population Surveillance, Physical therapy, Female, business, lcsh:Medicine (General)
Abstract: Background/Purpose We assessed the effect of smoking on death from chronic obstructive pulmonary disease (COPD) in China by employing a large population-based, case-spouse control study design using data from a nationwide survey of mortality. Methods During 1989-1991, a nationwide retrospective survey of mortality was conducted in China. For approximately 1,000,000 adults dying from all causes during 1986-1988, their surviving spouses or other informants provided detailed information about their own as well as the deceased person's smoking history. For this study, 183,393 individuals who died of COPD at age ≥ 40 years were taken as cases, while 272,984 sex-matched surviving spouses of subjects who died from any cause were taken as controls. Results COPD death rates for smokers were more than twice as high as those of non-smokers, with a dose-response risk pattern, despite the fact that COPD death rates varied widely by region and age. Tobacco accounted for 41.4% of COPD deaths in men, but only 13.5% of those in women, who had a lower rate of smoking. Conclusion A case-spouse control study, as an alternative design, is valid and feasible in utilizing information from population-based, retrospective mortality survey data for an analytical epidemiological study of disease etiology.
Published: 2008

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