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Kalu ME, Bello-Haas VD, Griffin M, Boamah S, Harris J, Zaide M, Rayner D, Khattab N, Abrahim S. A Scoping Review of Personal, Financial, and Environmental Determinants of Mobility Among Older Adults. Arch Phys Med Rehabil 2023; 104:2147-2168. [PMID: 37119957 DOI: 10.1016/j.apmr.2023.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 05/01/2023]
Abstract
OBJECTIVE To synthesize available evidence of factors comprising the personal, financial, and environmental mobility determinants and their association with older adults' self-reported and performance-based mobility outcomes. DATA SOURCES PubMed, EMBASE, PsychINFO, Web of Science, AgeLine, Sociological Abstract, Allied and Complementary Medicine Database, and Cumulative Index to Nursing and Allied Health Literature databases search for articles published from January 2000 to December 2021. STUDY SECTION Using predefined inclusion and exclusion criteria, multiple reviewers independently screened 27,293 retrieved citations from databases, of which 422 articles underwent full-text screening, and 300 articles were extracted. DATA EXTRACTION The 300 articles' information, including study design, sample characteristics including sample size, mean age and sex, factors within each determinant, and their associations with mobility outcomes, were extracted. DATA SYNTHESIS Because of the heterogeneity of the reported associations, we followed Barnett et al's study protocol and reported associations between factors and mobility outcomes by analyses rather than by article to account for multiple associations generated in 1 article. Qualitative data were synthesized using content analysis. A total of 300 articles were included with 269 quantitative, 22 qualitative, and 9 mixed-method articles representing personal (n=80), and financial (n=1), environmental (n=98), more than 1 factor (n=121). The 278 quantitative and mixed-method articles reported 1270 analyses; 596 (46.9%) were positively and 220 (17.3%) were negatively associated with mobility outcomes among older adults. Personal (65.2%), financial (64.6%), and environmental factors (62.9%) were associated with mobility outcomes, mainly in the expected direction with few exceptions in environmental factors. CONCLUSIONS Gaps exist in understanding the effect of some environmental factors (eg, number and type of street connections) and the role of gender on older adults' walking outcomes. We have provided a comprehensive list of factors with each determinant, allowing the creation of core outcome set for a specific context, population, or other forms of mobility, for example, driving.
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Affiliation(s)
- Michael E Kalu
- School of Rehabilitation Science, Faculty of Health Sciences, McMaster University, Hamilton, Canada.
| | - Vanina Dal Bello-Haas
- School of Rehabilitation Science, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Meridith Griffin
- Department of Health, Aging & Society, Faculty of Social Science, McMaster University, Hamilton, Canada
| | - Sheila Boamah
- School of Nursing, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Jocelyn Harris
- School of Rehabilitation Science, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Mashal Zaide
- Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Daniel Rayner
- Department of Health Science, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Nura Khattab
- Department of Kinesiology, Faculty of Sciences, McMaster University, Hamilton, Canada
| | - Salma Abrahim
- Department of Kinesiology, Faculty of Sciences, McMaster University, Hamilton, Canada
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Lei S, Zheng R, Zhang S, Huang Y, Qiao L, Song B, He Y, Du L, Wang N, Xi Y, Liu Y, Zhou J, Zhang M, Zheng Y, Zhang Y, Ju W, Wei W. Years lived with disability of cancer in China: findings from disability weights measurement with a focus on the effect of disease burden. Sci Bull (Beijing) 2023; 68:1430-1438. [PMID: 37349162 DOI: 10.1016/j.scib.2023.06.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/25/2023] [Accepted: 06/09/2023] [Indexed: 06/24/2023]
Abstract
Disability weights are crucial for quantifying health loss associated with non-fatal outcomes and were not well assessed in different countries, especially for specific cancer. Therefore, this study aimed to identify disability weights with a focus on specific cancer in a large Chinese population. Two types of web surveys were conducted, and 254 health states, including 30 new states for specific cancer, were investigated using paired comparison methods. The years lived with disability (YLDs) of cancer were calculated as the sum of the prevalence of each sequela of cancer multiplied by its relative disability weight. In total, 44,069 participants were eligible for the disability weights study. The disability weights of 254 health states were estimated. Among those, the disability weights of 18 specific cancer types varied greatly at diagnosis and primary treatment stage, with the value ranging from 0.619 (95% uncertainty interval (UI) 0.606-0.632) for brain cancer to 0.167 (95% UI 0.158-0.176) for oropharyngeal cancer. The discrepancy in YLDs calculated by different disability weights was high, and the largest gap for all cancer combined was approximately 30.14%. When calculated using the cancer-specific disability weights, a total of 1,967,830 (95% UI 1,928,880-2,008,060) YLDs of cancer were recorded in China. The disability weights of cancer varied greatly among cancer types and populations, which had considerable influence on the estimation of the disease burden. Cancer-specific disability weights could provide a more accurate evaluation of the cancer burden.
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Affiliation(s)
- Shaoyuan Lei
- Office for Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; Department of Evidence-Based Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Rongshou Zheng
- Office for Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology and Prevention, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - Yunchao Huang
- Yunnan Cancer Center/Yunnan Cancer Hospital, Kunming 650118, China
| | - Liang Qiao
- Department of Cancer Prevention and Control, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610042, China
| | - Bingbing Song
- Institute of Cancer Prevention and Treatment, Harbin Medical University/Institute of Cancer Prevention and Treatment, Heilongjiang Academy of Medical Sciences, Heilongjiang Cancer Centre, Harbin 150081, China
| | - Yutong He
- Department of Cancer Prevention and Control, Hebei Medical University Fourth Hospital, Shijiazhuang 050000, China
| | - Lingbin Du
- Department of Cancer Prevention, Cancer Hospital of the University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou 310005, China
| | - Ning Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Yunfeng Xi
- The Inner Mongolia Autonomous Region Comprehensive Center for Disease Control and Prevention, Hohhot 750306, China
| | - Yuqin Liu
- Cancer Epidemiology Research Center, Gansu Cancer Hospital, Lanzhou 730050, China
| | - Jinyi Zhou
- Department of Non-communicable Chronic Disease Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Min Zhang
- Office of Cancer Prevention and Treatment, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, China
| | - Ying Zheng
- Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yongzhen Zhang
- Department of Epidemiology, Shanxi Cancer Hospital, Taiyuan 030013, China
| | - Wen Ju
- Office for Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Wenqiang Wei
- Office for Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
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3
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Liu X, Wang F, Yu C, Zhou M, Yu Y, Qi J, Yin P, Yu S, Zhou Y, Lin L, Liu Y, Wang Q, Zhong W, Huang S, Li Y, Liu L, Liu Y, Ma F, Zhang Y, Tian Y, Yu Q, Zeng J, Pan J, Zhou M, Kang W, Zhou JY, Yu H, Liu Y, Li S, Yu H, Wang C, Xia T, Xi J, Ren X, Xing X, Cheng Q, Fei F, Wang D, Zhang S, He Y, Wen H, Liu Y, Shi F, Wang Y, Sun P, Bai J, Wang X, Shen H, Ma Y, Yang D, Mubarik S, Cao J, Meng R, Zhang Y, Guo Y, Yan Y, Zhang W, Ke S, Zhang R, Wang D, Zhang T, Nomura S, Hay SI, Salomon JA, Haagsma JA, Murray CJ, Vos T. Eliciting national and subnational sets of disability weights in mainland China: Findings from the Chinese disability weight measurement study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 26:100520. [PMID: 35910433 PMCID: PMC9335373 DOI: 10.1016/j.lanwpc.2022.100520] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
BACKGROUND The disability weight (DW) quantifies the severity of health states from disease sequela and is a pivotal parameter for disease burden calculation. We conducted a national and subnational DW measurement in China. METHODS In 2020-2021, we conducted a web-based survey to assess DWs for 206 health states in 31 Chinese provinces targeting health workers via professional networks. We fielded questions of paired comparison (PC) and population health equivalence (PHE). The PC data were analysed by probit regression analysis, and the regression results were anchored by results from the PHE responses on the DW scale between 0 (no loss of health) and 1 (health loss equivalent to death). FINDINGS We used PC responses from 468,541 respondents to estimate DWs of health states. Eight of 11 domains of health had significantly negative coefficients in the regression of the difference between Chinese and Global Burden of Disease (GBD) DWs, suggesting lower DW values for health states with mention of these domains in their lay description. We noted considerable heterogeneity within domains, however. After applying these Chinese DWs to the 2019 GBD estimates for China, total years lived with disability (YLDs) increased by 14·9% to 177 million despite lower estimates for musculoskeletal disorders, cardiovascular diseases, mental disorders, diabetes and chronic kidney disease. The lower estimates of YLDs for these conditions were more than offset by higher estimates of common, low-severity conditions. INTERPRETATION The differences between the GBD and Chinese DWs suggest that there might be some contextual factors influencing the valuation of health states. While the reduced estimates for mental disorders, alcohol use disorder, and dementia could hint at a culturally different valuation of these conditions in China, the much greater shifts in YLDs from low-severity conditions more likely reflects methodological difficulty to distinguish between health states that vary a little in absolute DW value but a lot in relative terms. FUNDING This work was supported by the National Natural Science Foundation of China [grant number 82173626], the National Key Research and Development Program of China [grant numbers 2018YFC1315302], Wuhan Medical Research Program of Joint Fund of Hubei Health Committee [grant number WJ2019H304], and Ningxia Natural Science Foundation Project [grant number 2020AAC03436].
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Affiliation(s)
- Xiaoxue Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Fang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou 221004, China
| | - Chuanhua Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
- Global Health Institute, Wuhan University, Wuhan 430072, China
- Corresponding authors.
| | - Maigeng Zhou
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, Beijing 100050, China
- Corresponding authors.
| | - Yong Yu
- School of Public Health and Management, Hubei University of Medicine, Shiyan 442000, Hubei, China
| | - Jinlei Qi
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, Beijing 100050, China
| | - Peng Yin
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, Beijing 100050, China
| | - Shicheng Yu
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuchang Zhou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China
| | - Lin Lin
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, Beijing 100050, China
| | - Yunning Liu
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, Beijing 100050, China
| | - Qiqi Wang
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenling Zhong
- Fujian Provincial Center for Disease Control and Prevention, No. 78 Jintai Road, Gulou District, Fuzhou City 350001, Fujian province, China
| | - Shaofen Huang
- Fujian Provincial Center for Disease Control and Prevention, No. 78 Jintai Road, Gulou District, Fuzhou City 350001, Fujian province, China
| | - Yanxia Li
- Liaoning Provincial Center for Disease Control and Prevention, No. 79 Jixian Street, Heping District, Shenyang City 110005, China
| | - Li Liu
- Liaoning Provincial Center for Disease Control and Prevention, No. 79 Jixian Street, Heping District, Shenyang City 110005, China
| | - Yuan Liu
- Hunan Provincial Center for Disease Control and Prevention, No. 450 first section of Middle Furong Road, Changsha City 410005, Hunan Province, China
| | - Fang Ma
- Ningxia Center for Disease Control and Prevention, No. 528 Shengli Street, Xingqing District, Yinchuan City 750004, Ningxia, China
| | - Yine Zhang
- Ningxia Center for Disease Control and Prevention, No. 528 Shengli Street, Xingqing District, Yinchuan City 750004, Ningxia, China
| | - Yuan Tian
- Ningxia Center for Disease Control and Prevention, No. 528 Shengli Street, Xingqing District, Yinchuan City 750004, Ningxia, China
| | - Qiuli Yu
- Yunnan Center for Disease Control and Prevention, No. 158 Dongsi Street, Xishan District, Kunming City 650022, Yunnan Province, China
| | - Jing Zeng
- Sichuan Center for Disease Control and Prevention, No. 6 Middle School Road, Wuhou District, Chengdu City 610041, Sichuan Province, China
| | - Jingju Pan
- Hubei Provincial Center for Disease Control and Prevention, No. 6 Zhuodaoquan North Road, Hongshan District, Wuhan City 430079, Hubei Province, China
| | - Mengge Zhou
- Hubei Provincial Center for Disease Control and Prevention, No. 6 Zhuodaoquan North Road, Hongshan District, Wuhan City 430079, Hubei Province, China
| | - Weiwei Kang
- Inner Mongolia Integrative Center for Disease Control and Prevention, No. 50 Ordos Street, Hohhot 010031, China
| | - Jin-Yi Zhou
- Jiangsu Provincial Center for disease Control and Prevention, Public Health Research Institute of Jiangsu Province, Jiangsu Road No. 172, Gulou District, Nanjing city 210009, Jiangsu Province, China
| | - Hao Yu
- Jiangsu Provincial Center for disease Control and Prevention, Public Health Research Institute of Jiangsu Province, Jiangsu Road No. 172, Gulou District, Nanjing city 210009, Jiangsu Province, China
| | - Yuehua Liu
- Heilongjiang Provincial Center for Disease Control and Prevention, No. 40 Youfang Street, Xiangfang District, Harbin City 150030, China
| | - Shaofang Li
- Henan Provincial Center for Disease Control and Prevention, No. 105 Nongye South Street, Zhengdong New District, Zhengzhou City 450016, China
| | - Huiting Yu
- Shanghai Municipal Center for Disease Control and Prevention, No. 1380 Zhongshan West Street, Changning District, Shanghai City 200051, China
| | - Chunfang Wang
- Shanghai Municipal Center for Disease Control and Prevention, No. 1380 Zhongshan West Street, Changning District, Shanghai City 200051, China
| | - Tian Xia
- Shanghai Municipal Center for Disease Control and Prevention, No. 1380 Zhongshan West Street, Changning District, Shanghai City 200051, China
| | - Jinen Xi
- Gansu Provincial Center for Disease Control and Prevention, No. 230 Donggang West Street, Chengguan District, Lanzhou City 73000, China
| | - Xiaolan Ren
- Gansu Provincial Center for Disease Control and Prevention, No. 230 Donggang West Street, Chengguan District, Lanzhou City 73000, China
| | - Xiuya Xing
- Anhui Provincial Center for Disease Control and Prevention, No. 12560 Fanhua Avenue, Economic and Technological Development District, Hefei City 230601, China
| | - Qianyao Cheng
- Anhui Provincial Center for Disease Control and Prevention, No. 12560 Fanhua Avenue, Economic and Technological Development District, Hefei City 230601, China
| | - Fangrong Fei
- Zhejiang Provincial Center for Disease Control and Prevention, No. 3399 Binsheng Street, Binjiang District, Hangzhou City 310051, China
| | - Dezheng Wang
- Tianjin Centers for Disease Control and Prevention, No. 6 Huayue Street, Hedong District, Tianjin City 300011, China
| | - Shuang Zhang
- Tianjin Centers for Disease Control and Prevention, No. 6 Huayue Street, Hedong District, Tianjin City 300011, China
| | - Yuling He
- Shanxi Center for Disease Control and Prevention, No. 6 Xiaonanguan Shuangta West Street, Yingze District, Taiyuan City 030012, China
| | - Haoyu Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Yan Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Fang Shi
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Yafeng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Panglin Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Jianjun Bai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Xuyan Wang
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Hui Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Yudiyang Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Donghui Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Sumaira Mubarik
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Jinhong Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, No. 115 Donghu Road, Wuchang District, Wuhan 430071, Hubei Province, China
| | - Runtang Meng
- Department of Preventive Medicine, School of Medicine, Hangzhou Normal University, Hangzhou 311121, Zhejiang, China
| | - Yunquan Zhang
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Yan Guo
- Wuhan Centers for Disease Control and Prevention, Wuhan 430024, Hubei, China
| | - Yaqiong Yan
- Wuhan Centers for Disease Control and Prevention, Wuhan 430024, Hubei, China
| | - Wei Zhang
- Wuhan Centers for Disease Control and Prevention, Wuhan 430024, Hubei, China
| | - Sisi Ke
- Wuhan Centers for Disease Control and Prevention, Wuhan 430024, Hubei, China
| | - Runhua Zhang
- Beijing Tiantan Hospital, Capital Medical University Beijing, China
| | - Dingyi Wang
- Institute of Clinical Medical Sciences, China-Japan Friendship Hospital; National Center for Respiratory Medicine, Beijing, China; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Tingting Zhang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100083, China
| | - Shuhei Nomura
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Japan
| | - Simon I. Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
| | - Joshua A. Salomon
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Juanita A. Haagsma
- Department of Public Health, Erasmus Medical Center, Rotterdam, Netherlands
| | | | - Theo Vos
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
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Nomura S, Yamamoto Y, Yoneoka D, Haagsma JA, Salomon JA, Ueda P, Mori R, Santomauro D, Vos T, Shibuya K. How do Japanese rate the severity of different diseases and injuries?-an assessment of disability weights for 231 health states by 37,318 Japanese respondents. Popul Health Metr 2021; 19:21. [PMID: 33892742 PMCID: PMC8063365 DOI: 10.1186/s12963-021-00253-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 04/08/2021] [Indexed: 12/03/2022] Open
Abstract
Background Disability weights (DWs) are weight factors that reflect the severity of health states for estimates of disability-adjusted life years. A new set of global DWs was published for the Global Burden of Diseases and Injuries (GBD) 2013 study, which relied on sampling from various world regions, but included little data for countries in East Asia. This study aimed to measure DWs in Japan using comparable methods, and compare the results with previous estimates from the GBD 2013 DW study. Methods We conducted a web-based survey in 2019 to estimate DWs for 231 health states for the Japanese population. The survey included five new health states but otherwise followed the method of the GBD DW measurement study. The survey consisted of 15 paired comparison (PC) questions and 3 population health equivalence questions (PHE) per respondent. We analyzed PC data using probit regression and rescaled results to DW units between 0 (equivalent to full health) and 1 (equivalent to death). Findings We considered 37,318 nationally representative respondents. The values of the resulting DWs ranged from 0.707 (95% uncertainty interval (UI) 0.527–0.842) for spinal cord injury at neck level (untreated) to 0.004 (UI 0.001–0.009) for mild anemia. High correlation between Japanese DW and GBD 2013 DW was observed, but there was considerable disagreement. Out of 226 comparable health states, 55 (24.3%) showed more than a factor-of-two difference, of which 41 (74.6%) had a higher value in Japanese DW. Many of the health states with higher DW in the Japan study were injuries, including amputation and fracture, and hearing and vision loss, while mental, behavioral, and substance use disorders generally tended to be lower. Conclusions This study has created an empirical basis for assessment of Japanese DWs of health status. The findings from this study based on the Japanese population suggest that there might be contextual differences in rating the severity of health states compared to previous surveys conducted elsewhere. Supplementary Information The online version contains supplementary material available at 10.1186/s12963-021-00253-4.
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Affiliation(s)
- Shuhei Nomura
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan. .,Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
| | | | - Daisuke Yoneoka
- Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.,Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Division of Biostatistics and Bioinformatics, Graduate School of Public Health, St. Luke's International University, Tokyo, Japan
| | - Juanita A Haagsma
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Joshua A Salomon
- Center for Primary Care and Outcomes Research, Stanford University School of Medicine, California, USA
| | - Peter Ueda
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Clinical Epidemiology Division, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
| | - Rintaro Mori
- Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Damian Santomauro
- School of Public Health, The University of Queensland, Queensland, Australia.,Queensland Centre for Mental Health Research, Queensland, Australia.,Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
| | - Theo Vos
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
| | - Kenji Shibuya
- Institute for Population Health, King's College London, London, UK
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