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Chen S, Guo L, Wang Z, Mao W, Ge Y, Ying X, Fang J, Long Q, Liu Q, Xiang H, Wu C, Fu C, Dong D, Zhang J, Sun J, Tian L, Wang L, Zhou M, Zhang M, Qian M, Liu W, Jiang W, Feng W, Zeng X, Ding X, Lei X, Tolhurst R, Xu L, Wang H, Ziegeweid F, Glenn S, Ji JS, Story M, Yamey G, Tang S. Current situation and progress toward the 2030 health-related Sustainable Development Goals in China: A systematic analysis. PLoS Med 2019; 16:e1002975. [PMID: 31743352 PMCID: PMC7340487 DOI: 10.1371/journal.pmed.1002975] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Accepted: 10/23/2019] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The Sustainable Development Goals (SDGs), adopted by all United Nations (UN) member states in 2015, established a set of bold and ambitious health-related targets to achieve by 2030. Understanding China's progress toward these targets is critical to improving population health for its 1.4 billion people. METHODS AND FINDINGS We used estimates from the Global Burden of Disease (GBD) Study 2016, national surveys and surveillance data from China, and qualitative data. Twenty-eight of the 37 indicators included in the GBD Study 2016 were analyzed. We developed an attainment index of health-related SDGs, a scale of 0-100 based on the values of indicators. The projection model is adjusted based on the one developed by the GBD Study 2016 SDG collaborators. We found that China has achieved several health-related SDG targets, including decreasing neonatal and under-5 mortality rates and the maternal mortality ratios and reducing wasting and stunting for children. However, China may only achieve 12 out of the 28 health-related SDG targets by 2030. The number of target indicators achieved varies among provinces and municipalities. In 2016, among the seven measured health domains, China performed best in child nutrition and maternal and child health and reproductive health, with the attainment index scores of 93.0 and 91.8, respectively, followed by noncommunicable diseases (NCDs) (69.4), road injuries (63.6), infectious diseases (63.0), environmental health (62.9), and universal health coverage (UHC) (54.4). There are daunting challenges to achieve the targets for child overweight, infectious diseases, NCD risk factors, and environmental exposure factors. China will also have a formidable challenge in achieving UHC, particularly in ensuring access to essential healthcare for all and providing adequate financial protection. The attainment index of child nutrition is projected to drop to 80.5 by 2025 because of worsening child overweight. The index of NCD risk factors is projected to drop to 38.8 by 2025. Regional disparities are substantial, with eastern provinces generally performing better than central and western provinces. Sex disparities are clear, with men at higher risk of excess mortality than women. The primary limitations of this study are the limited data availability and quality for several indicators and the adoption of "business-as-usual" projection methods. CONCLUSION The study found that China has made good progress in improving population health, but challenges lie ahead. China has substantially improved the health of children and women and will continue to make good progress, although geographic disparities remain a great challenge. Meanwhile, China faced challenges in NCDs, mental health, and some infectious diseases. Poor control of health risk factors and worsening environmental threats have posed difficulties in further health improvement. Meanwhile, an inefficient health system is a barrier to tackling these challenges among such a rapidly aging population. The eastern provinces are predicted to perform better than the central and western provinces, and women are predicted to be more likely than men to achieve these targets by 2030. In order to make good progress, China must take a series of concerted actions, including more investments in public goods and services for health and redressing the intracountry inequities.
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Affiliation(s)
- Shu Chen
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Lei Guo
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Zhan Wang
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Wenhui Mao
- Duke Global Health Institute, Duke University, Durham, North Carolina, United States of America
| | - Yanfeng Ge
- Research Department of Social Development, Development Research Center, State Council of People's Republic China, Beijing, China
| | - Xiaohua Ying
- School of Public Health, Fudan University, Shanghai, China
| | - Jing Fang
- Institute for Health Sciences, Kunming Medical University, Kunming, Yunnan, China
| | - Qian Long
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Qin Liu
- School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Hao Xiang
- School of Health Sciences, Wuhan University, Wuhan, Hubei, China
| | - Chenkai Wu
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Chaowei Fu
- School of Public Health, Fudan University, Shanghai, China
| | - Di Dong
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Jiahui Zhang
- Research Department of Social Development, Development Research Center, State Council of People's Republic China, Beijing, China
| | - Ju Sun
- School of Political Science and Public Administration, Wuhan University, Wuhan, Hubei, China
| | - Lichun Tian
- School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Limin Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mei Zhang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mengcen Qian
- School of Public Health, Fudan University, Shanghai, China
| | - Wei Liu
- School of Public Health, Kunming Medical University, Kunming, Yunnan, China
| | - Weixi Jiang
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Wenmeng Feng
- Research Department of Social Development, Development Research Center, State Council of People's Republic China, Beijing, China
| | - Xinying Zeng
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiyu Ding
- Global Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Xun Lei
- School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Rachel Tolhurst
- Faculty of Clinical Sciences and International Public Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Ling Xu
- Center of Health Human Resource Development, National Health Commission, Beijing, China
| | - Haidong Wang
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
| | - Faye Ziegeweid
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
| | - Scott Glenn
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
| | - John S. Ji
- Environment Research Center, Duke Kunshan University, Kunshan, Jiangsu, China
| | - Mary Story
- Duke Global Health Institute, Duke University, Durham, North Carolina, United States of America
| | - Gavin Yamey
- Duke Global Health Institute, Duke University, Durham, North Carolina, United States of America
| | - Shenglan Tang
- Duke Global Health Institute, Duke University, Durham, North Carolina, United States of America
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Development and Application of the Chinese (Mainland) Version of Chronic Liver Disease Questionnaire to Assess the Health-Related Quality of Life (HRQoL) in Patients with Chronic Hepatitis B. PLoS One 2016; 11:e0162763. [PMID: 27631983 PMCID: PMC5025145 DOI: 10.1371/journal.pone.0162763] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Accepted: 08/29/2016] [Indexed: 02/07/2023] Open
Abstract
Objective To develop the Chinese (Mainland) version of Chronic Liver Disease Questionnaire (CLDQ) and use it to assess the health-related quality of life (HRQoL) of chronic hepatitis B (CHB) patients in China and identify the determinants of HRQoL. Methods The Chinese (Mainland) CLDQ was developed by expert consultation, focus group interviews with patients, and pilot study. The final version of questionnaire was adopted to assess the HRQoL of chronic hepatitis B outpatients enrolled from two largest infectious hospitals in Beijing. Cronbach’ s alpha was used to measure the internal consistency reliability. The construct validity was measured by factor analysis. T-test, one-way analysis of variance (ANOVA), and multi-variable linear regression were used to analyze the data. Results Cronbach’s alpha of the overall CLDQ is 0.935, ranging from 0.628 to o.881 among six subscales. Six factors were identified via factor analysis, including a new factor sleeping(SL). A total of 519 patients with CHB were included in the investigation with the final version of questionnaire, 405 of them were only with CHB, 53 with compensated cirrhosis, and 61 with decompensated cirrhosis. The CHB group scored the highest in the overall score of CLDQ (p<0.05). The score of worry (WO) domain was significantly lower in the compensated group than the CHB group (p<0.05). Decompensated cirrhosis patients scored lower than the CHB group in all CLDQ domains and the overall score (p<0.05). Stages of illness, gender, regular visits to specialized hospitals, and work status in last year were determinants of HRQoL. Conclusion The psychometric properties of the Chinese(Mainland) CLDQ is acceptable. The HRQoL of CHB patients deteriorated with disease progression. Advanced stages of CHB, female, long time absence from work after illness, and no job or retirement were determinants of poor HRQoL. Regular visits to specialized hospitals was a positive determinant of HRQoL.
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Li H, Sheng C, Liu H, Liu G, Du X, Du J, Zhan L, Li P, Yang C, Qi L, Wang J, Yang X, Jia L, Xie J, Wang L, Hao R, Xu D, Tong Y, Zhou Y, Zhou J, Sun Y, Li Q, Qiu S, Song H. An Effective Molecular Target Site in Hepatitis B Virus S Gene for Cas9 Cleavage and Mutational Inactivation. Int J Biol Sci 2016; 12:1104-13. [PMID: 27570484 PMCID: PMC4997054 DOI: 10.7150/ijbs.16064] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2016] [Accepted: 06/28/2016] [Indexed: 12/15/2022] Open
Abstract
Chronic hepatitis B infection remains incurable because HBV cccDNA can persist indefinitely in patients recovering from acute HBV infection. Given the incidence of HBV infection and the shortcomings of current therapeutic options, a novel antiviral strategy is urgently needed. To inactivate HBV replication and destroy the HBV genome, we employed genome editing tool CRISPR/Cas9. Specifically, we found a CRISPR/Cas9 system (gRNA-S4) that effectively targeted the HBsAg region and could suppress efficiently viral replication with minimal off-target effects and impact on cell viability. The mutation mediated by CRISPR/Cas9 in HBV DNA both in a stable HBV-producing cell line and in HBV transgenic mice had been confirmed and evaluated using deep sequencing. In addition, we demonstrated the reduction of HBV replication was caused by the mutation of S4 site through three S4 region-mutated monoclonal cells. Besides, the gRNA-S4 system could also reduce serum surface-antigen levels by 99.91 ± 0.05% and lowered serum HBV DNA level below the negative threshold in the HBV hydrodynamics mouse model. Together, these findings indicate that the S4 region may be an ideal target for the development of innovative therapies against HBV infection using CRISPR/Cas9.
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Affiliation(s)
- Hao Li
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Chunyu Sheng
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Hongbo Liu
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Guangze Liu
- Transgenic Engineering Research Laboratory, Infectious Disease Center, Guangzhou 458 th Hospital, Guangzhou, China
| | - Xinying Du
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Juan Du
- Lab of Blood-Borne Viruses, Beijing Institute of Transfusion Medicine, Beijing, China
| | - Linsheng Zhan
- Lab of Blood-Borne Viruses, Beijing Institute of Transfusion Medicine, Beijing, China
| | - Peng Li
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Chaojie Yang
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Lihua Qi
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Jian Wang
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Xiaoxia Yang
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Leili Jia
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Jing Xie
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Ligui Wang
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Rongzhang Hao
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Dongping Xu
- Research Center for Liver Failure, Beijing 302 nd Hospital, Beijing, China
| | - Yigang Tong
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Yusen Zhou
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | | | - Yansong Sun
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Qiao Li
- Department of Surgery, University of Michigan, Ann Arbor, MI 48109, USA
| | - Shaofu Qiu
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
| | - Hongbin Song
- Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China
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