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Travor MD, Levine ES, Catomeris AJ, Purt B, Gensheimer WG, Justin GA, Trevino JD, Haagsma JA, Colyer MH, Staudt AM. Disability-Adjusted Life Years Resulting from Ocular Injury among Deployed Service Members, 2001-2020. Ophthalmology 2024; 131:534-544. [PMID: 38008289 DOI: 10.1016/j.ophtha.2023.11.023] [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: 10/05/2023] [Revised: 11/16/2023] [Accepted: 11/20/2023] [Indexed: 11/28/2023] Open
Abstract
PURPOSE To quantify the burden of ocular injuries on deployed US service members by calculating disability-adjusted life years (DALYs). DESIGN Retrospective, observational cohort study. PARTICIPANTS US service members with ocular injuries sustained in combat zones from January 1, 2001 to May 19, 2020. METHODS Health states and duration of injuries were identified using data from the Defense and Veterans Eye Injury and Vision Registry. These health states were mapped to disability weights from the Global Burden of Disease (GBD) study. Average duration of injury or illness was calculated until remission or death. For the latter, life expectancy at age of sustaining injury, as identified from US Life Tables from the National Vital Statistics Reports 2020, was used. Using Defense Manpower Data Center reports capturing number of service members deployed per year, incidence rates were calculated for ocular injury and DALYs. MAIN OUTCOME MEASURES Disability-adjusted life years of ocular injury. RESULTS Seventeen thousand five hundred fifty-five patients sustained ocular injury that incurred DALYs. In total, these injuries resulted in 11 214 DALYs (average, 0.64 DALYs per included patient and 20.6 DALYs per 10 000 US service members per year). Severe impairment of distance vision (77.9%) and blindness (10.6%) were the primary contributors of DALYs. Although only 9.3% of patients sustained a permanent ocular injury, permanent disability accounted for 99.5% of total DALYs. The average yearly incidence rate of ocular injury was 32.0 cases per 10 000 US service members. Foreign body was the most frequent injury type (2754 occurrences), followed by abrasion (2419 occurrences) and multiple injury types (1429 occurrences). The most DALYs occurred in patients with multiple injury types (2485 DALYs), followed by abrasion (accounting for 725 DALYs) and foreign body (accounting for 461 DALYs). DISCUSSION We report higher average DALYs per case ratio among US service members compared with the general population studied by the GBD study, highlighting the differences in probabilities of permanent injury between the two studies. Our study provides understanding of the impact of ocular injuries on active-duty service members and lays the groundwork for further research and interventions to mitigate their burden. FINANCIAL DISCLOSURE(S) Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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Affiliation(s)
- Mark D Travor
- Ophthalmology Section, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire
| | - Emily S Levine
- Ophthalmology Section, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire
| | - Andrew J Catomeris
- Ophthalmology Section, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire
| | - Boonkit Purt
- Walter Reed-Uniformed Services University Department of Surgery, Uniformed Services University, Bethesda, Maryland; Department of Ophthalmology, Kellogg Eye Center, University of Michigan, Ann Arbor, Michigan
| | - William G Gensheimer
- Ophthalmology Section, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire; Ophthalmology Section, White River Junction VA Medical Center, White River Junction, Vermont
| | - Grant A Justin
- Walter Reed-Uniformed Services University Department of Surgery, Uniformed Services University, Bethesda, Maryland
| | - Jennifer D Trevino
- Department of Data Analytics and Epidemiology, The Geneva Foundation, JBSA Fort Sam Houston, San Antonio, Texas
| | - Juanita A Haagsma
- Department of Public Health, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marcus H Colyer
- Walter Reed-Uniformed Services University Department of Surgery, Uniformed Services University, Bethesda, Maryland
| | - Amanda M Staudt
- Department of Data Analytics and Epidemiology, The Geneva Foundation, JBSA Fort Sam Houston, San Antonio, Texas.
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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: 6] [Impact Index Per Article: 3.0] [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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Charalampous P, Polinder S, Wothge J, von der Lippe E, Haagsma JA. A systematic literature review of disability weights measurement studies: evolution of methodological choices. Arch Public Health 2022; 80:91. [PMID: 35331325 PMCID: PMC8944058 DOI: 10.1186/s13690-022-00860-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 03/18/2022] [Indexed: 12/13/2022] Open
Abstract
Background The disability weight is an essential factor to estimate the healthy time that is lost due to living with a certain state of illness. A 2014 review showed a considerable variation in methods used to derive disability weights. Since then, several sets of disability weights have been developed. This systematic review aimed to provide an updated and comparative overview of the methodological design choices and surveying techniques that have been used in disability weights measurement studies and how they evolved over time. Methods A literature search was conducted in multiple international databases (early-1990 to mid-2021). Records were screened according to pre-defined eligibility criteria. The quality of the included disability weights measurement studies was assessed using the Checklist for Reporting Valuation Studies (CREATE) instrument. Studies were collated by characteristics and methodological design approaches. Data extraction was performed by one reviewer and discussed with a second. Results Forty-six unique disability weights measurement studies met our eligibility criteria. More than half (n = 27; 59%) of the identified studies assessed disability weights for multiple ill-health outcomes. Thirty studies (65%) described the health states using disease-specific descriptions or a combination of a disease-specific descriptions and generic-preference instruments. The percentage of studies obtaining health preferences from a population-based panel increased from 14% (2004–2011) to 32% (2012–2021). None of the disability weight studies published in the past 10 years used the annual profile approach. Most studies performed panel-meetings to obtain disability weights data. Conclusions Our review reveals that a methodological uniformity between national and GBD disability weights studies increased, especially from 2010 onwards. Over years, more studies used disease-specific health state descriptions in line with those of the GBD study, panel from general populations, and data from web-based surveys and/or household surveys. There is, however, a wide variation in valuation techniques that were used to derive disability weights at national-level and that persisted over time. Supplementary Information The online version contains supplementary material available at 10.1186/s13690-022-00860-z.
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Affiliation(s)
- Periklis Charalampous
- Department of Public Health, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
| | - Suzanne Polinder
- Department of Public Health, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Jördis Wothge
- German Environment Agency, Section Noise Abatement of Industrial Plants and Products, Noise Impact, Wörlitzer Pl. 1, 06844, Dessau-Roßlau, Germany
| | - Elena von der Lippe
- Department of Epidemiology and Health Monitorin, Robert Koch Institute, Berlin, Germany
| | - Juanita A Haagsma
- Department of Public Health, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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Nanda L, Lobo E, Menon GR, Dhopte P, Akhouri SS, Shrivastava C, Ronghang R, Anilkumar A, Dutta A. Disability Weights Estimates From India in 2018: Measurements From Community Members From Two Distinct States of India. Front Public Health 2022; 10:752311. [PMID: 35392475 PMCID: PMC8980316 DOI: 10.3389/fpubh.2022.752311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 02/14/2022] [Indexed: 12/03/2022] Open
Abstract
Background India is undergoing a rapid demographic and epidemiologic transition. Thus demanding prioritization of diseases based on burden estimation is befitting our cultural diversity. Disability weights (DWs) by Global burden of disease (GBD) studies may not be representative. Hence, a study was conducted to estimate state-specific disability weights to capture the community health perceptions that included urban–rural settings as well as different socio-economic and literacy levels. Methods A total of 2,055 community members (participants) from two distinct states of India, Odisha and Telangana, were interviewed to assign disability weights to the selected 14 health states based on the state burden and relevance. Each health state was described to the participants using pictorial representations of the health states and valuated using visual analog scale and card sort methods. Results We noted that DWs in Odisha ranged from 0.32 (0.30–0.34) for upper limb fracture due to road traffic accident (least severe) to 0.90 (0.88–0.93) for breast cancer (most severe) among the 14 health states. While, in Telangana, diarrhea was considered least severe [DW = 0.22 (0.19–0.24)] and breast cancer remained most severe [DW = 0.85 (0.83–0.88)] as in Odisha. Marked difference in the DWs for other health states was also seen. Further, on comparison of community weights with GBD weights using Spearman correlation, we observed a low correlation (ρ = 0.104). Conclusion Our study provides community-based findings that show how participants valued noncommunicable diseases higher than short-term ailments or infectious diseases. Additionally, the low correlation between GBD also suggests the need for local disability weights rather than universal acceptance. We therefore recommend that decisions in policy-making, especially for resource allocation and priority setting, need to be based not only on expert opinion but also include community in accordance with high scientific standards.
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Affiliation(s)
- Lipika Nanda
- Indian Institute of Public Health-Hyderabad, Public Health Foundation of India, Hyderabad, India
| | - Eunice Lobo
- Indian Institute of Public Health-Bengaluru, Public Health Foundation of India, Bengaluru, India
| | - Geetha R. Menon
- National Institute of Medical Statistics, Indian Council of Medical Research, New Delhi, India
| | - Pratik Dhopte
- Health Economics and Outcome Research, Mumbai, India
| | - Shuchi Sree Akhouri
- Department of Concurrent Measurements and Learning, Care India, Patna, India
| | | | | | - Aiswarya Anilkumar
- Indian Institute of Public Health-Hyderabad, Public Health Foundation of India, Hyderabad, India
| | - Ambarish Dutta
- Indian Institute of Public Health-Bhubaneswar, Public Health Foundation of India, Bhubaneswar, India
- *Correspondence: Ambarish Dutta
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Kim YE, Jo MW, Park H, Oh IH, Yoon SJ, Pyo J, Ock M. Updating Disability Weights for Measurement of Healthy Life Expectancy and Disability-adjusted Life Year in Korea. J Korean Med Sci 2020; 35:e219. [PMID: 32657086 PMCID: PMC7358061 DOI: 10.3346/jkms.2020.35.e219] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 05/21/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The present study aimed to update the methodology to estimate cause-specific disability weight (DW) for the calculation of disability adjusted life year (DALY) and health-adjusted life expectancy (HALE) based on the opinion of medical professional experts. Furthermore, the study also aimed to compare and assess the size of DW according to two analytical methods and estimate the most valid DW from the perspective of years lost due to disability and HALE estimation. METHODS A self-administered web-based survey was conducted ranking five causes of disease. A total of 901 participants started the survey and response data of 806 participants were used in the analyses. In the process of rescaling predicted probability to DW on a scale from 0 to 1, two models were used for two groups: Group 1 (physicians and medical students) and Group 2 (nurses and oriental medical doctors). In Model 1, predicted probabilities were rescaled according to the normal distribution of DWs. In Model 2, the natural logarithms of predicted probabilities were rescaled according to the asymmetric distribution of DWs. RESULTS We estimated DWs for a total of 313 causes of disease in each model and group. The mean of DWs according to the models in each group was 0.490 (Model 1 in Group 1), 0.378 (Model 2 in Group 1), 0.506 (Model 1 in Group 2), and 0.459 (Model 2 in Group 2), respectively. About two-thirds of the causes of disease had DWs of 0.2 to 0.4 in Model 2 in Group 1. In Group 2, but not in Group 1, there were some cases where the DWs had a reversed order of severity. CONCLUSION We attempted to calculate DWs of 313 causes of disease based on the opinions of various types of medical professionals using the previous analysis methods as well as the revised analysis method. The DWs from this study can be used to accurately estimate DALY and health life expectancy, such as HALE, in the Korean population.
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Affiliation(s)
- Young Eun Kim
- Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
- Big Data Department, National Health Insurance Service, Wonju, Korea
| | - Min Woo Jo
- Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, Korea
| | - Hyesook Park
- Department of Preventive Medicine, Ewha Womans University College of Medicine, Seoul, Korea
| | - In Hwan Oh
- Department of Preventive Medicine, School of Medicine, Kyung Hee University, Seoul, Korea
| | - Seok Jun Yoon
- Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
| | - Jeehee Pyo
- Department of Preventive Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
| | - Minsu Ock
- Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, Korea
- Department of Preventive Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea.
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Hung TM, Clapham HE, Bettis AA, Cuong HQ, Thwaites GE, Wills BA, Boni MF, Turner HC. The Estimates of the Health and Economic Burden of Dengue in Vietnam. Trends Parasitol 2018; 34:904-918. [PMID: 30100203 PMCID: PMC6192036 DOI: 10.1016/j.pt.2018.07.007] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 07/13/2018] [Accepted: 07/16/2018] [Indexed: 12/31/2022]
Abstract
Dengue has been estimated to cause a substantial health and economic burden in Vietnam. The most recent studies have estimated that it is responsible for 39884 disability-adjusted life years (DALYs) annually, representing an economic burden of US$94.87 million per year (in 2016 prices). However, there are alternative burden estimates that are notably lower. This variation is predominantly due to differences in how the number of symptomatic dengue cases is estimated. Understanding the methodology of these burden calculations is vital when interpreting health economic analyses of dengue. This review aims to provide an overview of the health and economic burden estimates of dengue in Vietnam. We also highlight important research gaps for future studies.
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Affiliation(s)
- Trinh Manh Hung
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Hannah E Clapham
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Alison A Bettis
- London Centre for Neglected Tropical Disease Research, London, UK; Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St Marys Campus, Imperial College London, Norfolk Place, London W2 1 PG, UK
| | | | - Guy E Thwaites
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Bridget A Wills
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Maciej F Boni
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Hugo C Turner
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
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Teng KTY, Devleesschauwer B, Maertens De Noordhout C, Bennett P, McGreevy PD, Chiu PY, Toribio JALML, Dhand NK. Welfare-Adjusted Life Years (WALY): A novel metric of animal welfare that combines the impacts of impaired welfare and abbreviated lifespan. PLoS One 2018; 13:e0202580. [PMID: 30208045 PMCID: PMC6135394 DOI: 10.1371/journal.pone.0202580] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 08/05/2018] [Indexed: 11/30/2022] Open
Abstract
Currently, separate measures are used to estimate the impact of animal diseases on mortality and animal welfare. This article introduces a novel metric, the Welfare-Adjusted Life Year (WALY), to estimate disease impact by combining welfare compromise and premature death components. Adapting the Disability-Adjusted Life Year approach used in human health audits, we propose WALY as the sum of a) the years lived with impaired welfare due to a particular cause and b) the years of life lost due to the premature death from the same cause. The years lived with impaired welfare are the product of the average duration of each welfare impediment, reflecting the actual condition that compromises animal welfare, the probability of an incident case developing and impaired welfare weights, representing the degree of impaired welfare. The years of life lost are calculated using the standard expected lifespan at the time of premature death. To demonstrate the concept, we estimated WALYs for 10 common canine diseases, namely mitral valve disease, dilated cardiomyopathy, chronic kidney disease, diabetes mellitus, atopic dermatitis, splenic haemangiosarcoma, appendicular osteosarcoma, cranial cruciate ligament disease, thoracolumbar intervertebral disc disease and cervical spondylomyelopathy. A survey of veterinarians (n = 61) was conducted to elicit impaired welfare weights for 35 welfare impediments. Paired comparison was the primary method to elicit weights, whereas visual analogue scale and time trade-off approaches rescaled these weights onto the desired scale, from 0 (the optimal welfare imaginable) to 1 (the worst welfare imaginable). WALYs for the 10 diseases were then estimated using the impaired welfare weights and published epidemiological data on disease impacts. Welfare impediment “amputation: one limb” and “respiratory distress” had the lowest and highest impaired welfare weights at 0.134 and 0.796, rescaled with a visual analogue scale, and 0.117 and 0.857, rescaled with time trade-off. Among the 10 diseases, thoracolumbar intervertebral disc disease and atopic dermatitis had the smallest and greatest adverse impact on dogs with WALYs at 2.83 (95% UI: 1.54–3.94) and 9.73 (95% uncertainty interval [UI]: 7.17–11.8), respectively. This study developed the WALY metric and demonstrated that it summarises welfare compromise as perceived by humans and total impact of diseases in individual animals. The WALY can potentially be used for prioritisation of disease eradication and control programs, quantification of population welfare and longitudinal surveillance of animal welfare in companion animals and may possibly be extended to production animals.
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Affiliation(s)
- Kendy Tzu-Yun Teng
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia
- * E-mail:
| | - Brecht Devleesschauwer
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium
- Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | | | - Peter Bennett
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia
| | - Paul D. McGreevy
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia
| | - Po-Yu Chiu
- National Taiwan University Veterinary Hospital, Taipei, Taiwan
| | - Jenny-Ann L. M. L. Toribio
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia
| | - Navneet K. Dhand
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Camperdown, NSW, Australia
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Rutstein SE, Price JT, Rosenberg NE, Rennie SM, Biddle AK, Miller WC. Hidden costs: The ethics of cost-effectiveness analyses for health interventions in resource-limited settings. Glob Public Health 2017; 12:1269-1281. [PMID: 27141969 PMCID: PMC5303190 DOI: 10.1080/17441692.2016.1178319] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Cost-effectiveness analysis (CEA) is an increasingly appealing tool for evaluating and comparing health-related interventions in resource-limited settings. The goal is to inform decision-makers regarding the health benefits and associated costs of alternative interventions, helping guide allocation of limited resources by prioritising interventions that offer the most health for the least money. Although only one component of a more complex decision-making process, CEAs influence the distribution of health-care resources, directly influencing morbidity and mortality for the world's most vulnerable populations. However, CEA-associated measures are frequently setting-specific valuations, and CEA outcomes may violate ethical principles of equity and distributive justice. We examine the assumptions and analytical tools used in CEAs that may conflict with societal values. We then evaluate contextual features unique to resource-limited settings, including the source of health-state utilities and disability weights, implications of CEA thresholds in light of economic uncertainty, and the role of external donors. Finally, we explore opportunities to help align interpretation of CEA outcomes with values and budgetary constraints in resource-limited settings. The ethical implications of CEAs in resource-limited settings are vast. It is imperative that CEA outcome summary measures and implementation thresholds adequately reflect societal values and ethical priorities in resource-limited settings.
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Affiliation(s)
- Sarah E. Rutstein
- Department of Health Policy and Management, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Division of Infectious Diseases, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | | | | | - Stuart M. Rennie
- Department of Social Medicine, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Andrea K. Biddle
- Department of Health Policy and Management, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - William C. Miller
- Division of Infectious Diseases, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Department of Epidemiology, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
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Murray CJL, Lopez AD. Measuring global health: motivation and evolution of the Global Burden of Disease Study. Lancet 2017; 390:1460-1464. [PMID: 28919120 DOI: 10.1016/s0140-6736(17)32367-x] [Citation(s) in RCA: 109] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Revised: 08/17/2017] [Accepted: 08/22/2017] [Indexed: 11/17/2022]
Affiliation(s)
- Christopher J L Murray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
| | - Alan D Lopez
- Melbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia
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Ock M, Ko S, Lee HJ, Jo MW. Review of Issues for Disability Weight Studies. HEALTH POLICY AND MANAGEMENT 2016. [DOI: 10.4332/kjhpa.2016.26.4.352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Neethling I, Jelsma J, Ramma L, Schneider H, Bradshaw D. Disability weights from a household survey in a low socio-economic setting: how does it compare to the global burden of disease 2010 study? Glob Health Action 2016; 9:31754. [PMID: 27539894 PMCID: PMC4990533 DOI: 10.3402/gha.v9.31754] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Revised: 07/11/2016] [Accepted: 07/11/2016] [Indexed: 11/23/2022] Open
Abstract
Background The global burden of disease (GBD) 2010 study used a universal set of disability weights to estimate disability adjusted life years (DALYs) by country. However, it is not clear whether these weights can be applied universally in calculating DALYs to inform local decision-making. This study derived disability weights for a resource-constrained community in Cape Town, South Africa, and interrogated whether the GBD 2010 disability weights necessarily represent the preferences of economically disadvantaged communities. Design A household survey was conducted in Lavender Hill, Cape Town, to assess the health state preferences of the general public. The responses from a paired comparison valuation method were assessed using a probit regression. The probit coefficients were anchored onto the 0 to 1 disability weight scale by running a lowess regression on the GBD 2010 disability weights and interpolating the coefficients between the upper and lower limit of the smoothed disability weights. Results Heroin and opioid dependence had the highest disability weight of 0.630, whereas intellectual disability had the lowest (0.040). Untreated injuries ranked higher than severe mental disorders. There were some counterintuitive results, such as moderate (15th) and severe vision impairment (16th) ranking higher than blindness (20th). A moderate correlation between the disability weights of the local study and those of the GBD 2010 study was observed (R2=0.440, p<0.05). This indicates that there was a relationship, although some conditions, such as untreated fracture of the radius or ulna, showed large variability in disability weights (0.488 in local study and 0.043 in GBD 2010). Conclusions Respondents seemed to value physical mobility higher than cognitive functioning, which is in contrast to the GBD 2010 study. This study shows that not all health state preferences are universal. Studies estimating DALYs need to derive local disability weights using methods that are less cognitively demanding for respondents.
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Affiliation(s)
- Ian Neethling
- Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa;
| | - Jennifer Jelsma
- Department of Health and Rehabilitation Sciences, University of Cape Town, Cape Town, South Africa
| | - Lebogang Ramma
- Department of Health and Rehabilitation Sciences, University of Cape Town, Cape Town, South Africa
| | - Helen Schneider
- School of Public Health, University of the Western Cape, Cape Town, South Africa
| | - Debbie Bradshaw
- Burden of Disease Research Unit, South African Medical Research Council, Cape Town, South Africa
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Price JT, Wheeler SB, Stranix-Chibanda L, Hosek SG, Watts DH, Siberry GK, Spiegel HML, Stringer JS, Chi BH. Cost-Effectiveness of Pre-exposure HIV Prophylaxis During Pregnancy and Breastfeeding in Sub-Saharan Africa. J Acquir Immune Defic Syndr 2016; 72 Suppl 2:S145-53. [PMID: 27355502 PMCID: PMC5043081 DOI: 10.1097/qai.0000000000001063] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
INTRODUCTION Antiretroviral pre-exposure prophylaxis (PrEP) for the prevention of HIV acquisition is cost-effective when delivered to those at substantial risk. Despite a high incidence of HIV infection among pregnant and breastfeeding women in sub-Saharan Africa (SSA), a theoretical increased risk of preterm birth on PrEP could outweigh the HIV prevention benefit. METHODS We developed a decision analytic model to evaluate a strategy of daily oral PrEP during pregnancy and breastfeeding in SSA. We approached the analysis from a health care system perspective across a lifetime time horizon. Model inputs were derived from existing literature and local sources. The incremental cost-effectiveness ratio (ICER) of PrEP versus no PrEP was calculated in 2015 U.S. dollars per disability-adjusted life year (DALY) averted. We evaluated the effect of uncertainty in baseline estimates through one-way and probabilistic sensitivity analyses. RESULTS PrEP administered to pregnant and breastfeeding women in SSA was cost-effective. In a base case of 10,000 women, the administration of PrEP averted 381 HIV infections but resulted in 779 more preterm births. PrEP was more costly per person ($450 versus $117), but resulted in fewer disability-adjusted life years (DALYs) (3.15 versus 3.49). The incremental cost-effectiveness ratio of $965/DALY averted was below the recommended regional threshold for cost-effectiveness of $6462/DALY. Probabilistic sensitivity analyses demonstrated robustness of the model. CONCLUSIONS Providing PrEP to pregnant and breastfeeding women in SSA is likely cost-effective, although more data are needed about adherence and safety. For populations at high risk of HIV acquisition, PrEP may be considered as part of a broader combination HIV prevention strategy.
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Affiliation(s)
- Joan T. Price
- Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina Chapel Hill, Chapel Hill, NC
| | - Stephanie B. Wheeler
- Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Lynda Stranix-Chibanda
- Department of Pediatrics and Child Health, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe
| | - Sybil G. Hosek
- Department of Psychiatry, John Stroger Hospital of Cook County, Chicago, IL
| | - D. Heather Watts
- Office of the Global AIDS Coordinator and Health Diplomacy, U.S. Department of State, Washington, DC
| | - George K. Siberry
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD; and
| | - Hans M. L. Spiegel
- Kelly Government Services, Contractor to Prevention Sciences Program, Division of AIDS, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD
| | - Jeffrey S. Stringer
- Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina Chapel Hill, Chapel Hill, NC
| | - Benjamin H. Chi
- Division of Global Women's Health, Department of Obstetrics and Gynecology, University of North Carolina Chapel Hill, Chapel Hill, NC
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Salomon JA, Haagsma JA, Davis A, de Noordhout CM, Polinder S, Havelaar AH, Cassini A, Devleesschauwer B, Kretzschmar M, Speybroeck N, Murray CJL, Vos T. Disability weights for the Global Burden of Disease 2013 study. LANCET GLOBAL HEALTH 2015; 3:e712-23. [DOI: 10.1016/s2214-109x(15)00069-8] [Citation(s) in RCA: 565] [Impact Index Per Article: 62.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2015] [Revised: 05/07/2015] [Accepted: 06/02/2015] [Indexed: 10/22/2022]
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Haagsma JA, Maertens de Noordhout C, Polinder S, Vos T, Havelaar AH, Cassini A, Devleesschauwer B, Kretzschmar ME, Speybroeck N, Salomon JA. Assessing disability weights based on the responses of 30,660 people from four European countries. Popul Health Metr 2015; 13:10. [PMID: 26778920 PMCID: PMC4715333 DOI: 10.1186/s12963-015-0042-4] [Citation(s) in RCA: 113] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2014] [Accepted: 03/17/2015] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND In calculations of burden of disease using disability-adjusted life years, disability weights are needed to quantify health losses relating to non-fatal outcomes, expressed as years lived with disability. In 2012 a new set of global disability weights was published for the Global Burden of Disease 2010 (GBD 2010) study. That study suggested that comparative assessments of different health outcomes are broadly similar across settings, but the significance of this conclusion has been debated. The aim of the present study was to estimate disability weights for Europe for a set of 255 health states, including 43 new health states, by replicating the GBD 2010 Disability Weights Measurement study among representative population samples from four European countries. METHODS For the assessment of disability weights for Europe we applied the GBD 2010 disability weights measurement approach in web-based sample surveys in Hungary, Italy, Netherlands, and Sweden. The survey included paired comparisons (PC) and population health equivalence questions (PHE) formulated as discrete choices. Probit regression analysis was used to estimate cardinal values from PC responses. To locate results onto the 0-to-1 disability weight scale, we assessed the feasibility of using the GBD 2010 scaling approach based on PHE questions, as well as an alternative approach using non-parametric regression. RESULTS In total, 30,660 respondents participated in the survey. Comparison of the probit regression results from the PC responses for each country indicated high linear correlations between countries. The PHE data had high levels of measurement error in these general population samples, which compromises the ability to infer ratio-scaled values from discrete choice responses. Using the non-parametric regression approach as an alternative rescaling procedure, the set of disability weights were bounded by distance vision mild impairment and anemia with the lowest weight (0.004) and severe multiple sclerosis with the highest weight (0.677). CONCLUSIONS PC assessments of health outcomes in this study resulted in estimates that were highly correlated across four European countries. Assessment of the feasibility of rescaling based on a discrete choice formulation of the PHE question indicated that this approach may not be suitable for use in a web-based survey of the general population.
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Affiliation(s)
- Juanita A Haagsma
- />Department of Public Health, Erasmus MC, P.O. Box 2040, , 3000, CA Rotterdam, The Netherlands
- />Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
| | | | - Suzanne Polinder
- />Department of Public Health, Erasmus MC, P.O. Box 2040, , 3000, CA Rotterdam, The Netherlands
| | - Theo Vos
- />Institute for Health Metrics and Evaluation, University of Washington, Seattle, USA
| | - Arie H Havelaar
- />National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands
- />Emerging Pathogens Institute, University of Florida, Gainesville, Florida USA
- />Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | | | - Brecht Devleesschauwer
- />Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
| | - Mirjam E Kretzschmar
- />National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands
- />Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Niko Speybroeck
- />Institute of Health and Society (IRSS), Université catholique de Louvain, Leuven, Belgium
| | - Joshua A Salomon
- />Department of Global Health and Population, Harvard School of Public Health, Boston, USA
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Haagsma JA, Polinder S, Cassini A, Colzani E, Havelaar AH. Review of disability weight studies: comparison of methodological choices and values. Popul Health Metr 2014; 12:20. [PMID: 26019690 PMCID: PMC4445691 DOI: 10.1186/s12963-014-0020-2] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2013] [Accepted: 07/20/2014] [Indexed: 10/29/2022] Open
Abstract
INTRODUCTION The disability-adjusted life year (DALY) is widely used to assess the burden of different health problems and risk factors. The disability weight, a value anchored between 0 (perfect health) and 1 (equivalent to death), is necessary to estimate the disability component (years lived with disability, YLDs) of the DALY. After publication of the ground-breaking Global Burden of Disease (GBD) 1996, alternative sets of disability weights have been developed over the past 16 years, each using different approaches with regards to the panel, health state description, and valuation methods. The objective of this study was to review all studies that developed disability weights and to critically assess the methodological design choices (health state and time description, panel composition, and valuation method). Furthermore, disability weights of eight specific conditions were compared. METHODS Disability weights studies (1990¿2012) in international peer-reviewed journals and grey literature were identified with main inclusion criteria being that the study assessed DALY disability weights for several conditions or a specific group of illnesses. Studies were collated by design and methods and evaluation of results. RESULTS Twenty-two studies met the inclusion criteria of our review. There is considerable variation in methods used to derive disability weights, although most studies used a disease-specific description of the health state, a panel that consisted of medical experts, and nonpreference-based valuation method to assess the values for the majority of the disability weights. Comparisons of disability weights across 15 specific disease and injury groups showed that the subdivision of a disease into separate health states (stages) differed markedly across studies. Additionally, weights for similar health states differed, particularly in the case of mild diseases, for which the disability weight differed by a factor of two or more. CONCLUSIONS In terms of comparability of the resulting YLDs, the global use of the same set of disability weights has advantages, though practical constraints and intercultural differences should be taken into account into such a set.
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Affiliation(s)
- Juanita A Haagsma
- Department of Public Health, Erasmus Medical Center, Rotterdam, 3000 CA, The Netherlands
| | - Suzanne Polinder
- Department of Public Health, Erasmus Medical Center, Rotterdam, 3000 CA, The Netherlands
| | - Alessandro Cassini
- Office of the Chief Scientist, European Centre for Disease Prevention and Control, Stockholm, SE-171 83, Sweden
| | - Edoardo Colzani
- Office of the Chief Scientist, European Centre for Disease Prevention and Control, Stockholm, SE-171 83, Sweden
| | - Arie H Havelaar
- National Institute for Public Health and the Environment, Laboratory for Zoonoses and Environmental Microbiology, Bilthoven, 3720 BA, The Netherlands ; Utrecht University, Institute for Risk Assessment Sciences, Utrecht, 3508 TD, the Netherlands
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Salomon JA, Vos T, Hogan DR, Gagnon M, Naghavi M, Mokdad A, Begum N, Shah R, Karyana M, Kosen S, Farje MR, Moncada G, Dutta A, Sazawal S, Dyer A, Seiler J, Aboyans V, Baker L, Baxter A, Benjamin EJ, Bhalla K, Bin Abdulhak A, Blyth F, Bourne R, Braithwaite T, Brooks P, Brugha TS, Bryan-Hancock C, Buchbinder R, Burney P, Calabria B, Chen H, Chugh SS, Cooley R, Criqui MH, Cross M, Dabhadkar KC, Dahodwala N, Davis A, Degenhardt L, Díaz-Torné C, Dorsey ER, Driscoll T, Edmond K, Elbaz A, Ezzati M, Feigin V, Ferri CP, Flaxman AD, Flood L, Fransen M, Fuse K, Gabbe BJ, Gillum RF, Haagsma J, Harrison JE, Havmoeller R, Hay RJ, Hel-Baqui A, Hoek HW, Hoffman H, Hogeland E, Hoy D, Jarvis D, Karthikeyan G, Knowlton LM, Lathlean T, Leasher JL, Lim SS, Lipshultz SE, Lopez AD, Lozano R, Lyons R, Malekzadeh R, Marcenes W, March L, Margolis DJ, McGill N, McGrath J, Mensah GA, Meyer AC, Michaud C, Moran A, Mori R, Murdoch ME, Naldi L, Newton CR, Norman R, Omer SB, Osborne R, Pearce N, Perez-Ruiz F, Perico N, Pesudovs K, Phillips D, Pourmalek F, Prince M, Rehm JT, Remuzzi G, Richardson K, Room R, Saha S, Sampson U, Sanchez-Riera L, Segui-Gomez M, Shahraz S, Shibuya K, Singh D, Sliwa K, Smith E, Soerjomataram I, Steiner T, Stolk WA, Stovner LJ, Sudfeld C, Taylor HR, Tleyjeh IM, van der Werf MJ, Watson WL, Weatherall DJ, Weintraub R, Weisskopf MG, Whiteford H, Wilkinson JD, Woolf AD, Zheng ZJ, Murray CJL, Jonas JB. Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010. Lancet 2012; 380:2129-43. [PMID: 23245605 PMCID: PMC10782811 DOI: 10.1016/s0140-6736(12)61680-8] [Citation(s) in RCA: 883] [Impact Index Per Article: 73.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Measurement of the global burden of disease with disability-adjusted life-years (DALYs) requires disability weights that quantify health losses for all non-fatal consequences of disease and injury. There has been extensive debate about a range of conceptual and methodological issues concerning the definition and measurement of these weights. Our primary objective was a comprehensive re-estimation of disability weights for the Global Burden of Disease Study 2010 through a large-scale empirical investigation in which judgments about health losses associated with many causes of disease and injury were elicited from the general public in diverse communities through a new, standardised approach. METHODS We surveyed respondents in two ways: household surveys of adults aged 18 years or older (face-to-face interviews in Bangladesh, Indonesia, Peru, and Tanzania; telephone interviews in the USA) between Oct 28, 2009, and June 23, 2010; and an open-access web-based survey between July 26, 2010, and May 16, 2011. The surveys used paired comparison questions, in which respondents considered two hypothetical individuals with different, randomly selected health states and indicated which person they regarded as healthier. The web survey added questions about population health equivalence, which compared the overall health benefits of different life-saving or disease-prevention programmes. We analysed paired comparison responses with probit regression analysis on all 220 unique states in the study. We used results from the population health equivalence responses to anchor the results from the paired comparisons on the disability weight scale from 0 (implying no loss of health) to 1 (implying a health loss equivalent to death). Additionally, we compared new disability weights with those used in WHO's most recent update of the Global Burden of Disease Study for 2004. FINDINGS 13,902 individuals participated in household surveys and 16,328 in the web survey. Analysis of paired comparison responses indicated a high degree of consistency across surveys: correlations between individual survey results and results from analysis of the pooled dataset were 0·9 or higher in all surveys except in Bangladesh (r=0·75). Most of the 220 disability weights were located on the mild end of the severity scale, with 58 (26%) having weights below 0·05. Five (11%) states had weights below 0·01, such as mild anaemia, mild hearing or vision loss, and secondary infertility. The health states with the highest disability weights were acute schizophrenia (0·76) and severe multiple sclerosis (0·71). We identified a broad pattern of agreement between the old and new weights (r=0·70), particularly in the moderate-to-severe range. However, in the mild range below 0·2, many states had significantly lower weights in our study than previously. INTERPRETATION This study represents the most extensive empirical effort as yet to measure disability weights. By contrast with the popular hypothesis that disability assessments vary widely across samples with different cultural environments, we have reported strong evidence of highly consistent results. FUNDING Bill & Melinda Gates Foundation.
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Salomon JA. New disability weights for the global burden of disease. Bull World Health Organ 2011; 88:879. [PMID: 21124707 DOI: 10.2471/blt.10.084301] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Moodie M, Richardson J, Rankin B, Iezzi A, Sinha K. Predicting time trade-off health state valuations of adolescents in four Pacific countries using the Assessment of Quality-of-Life (AQoL-6D) instrument. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2010; 13:1014-27. [PMID: 20825621 DOI: 10.1111/j.1524-4733.2010.00780.x] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
OBJECTIVES Pacific Obesity Prevention in Communities (OPIC) is a community-based intervention project targeting adolescent obesity in Australia, New Zealand, Fiji, and Tonga. The Assessment of Quality of Life Mark 2 (AQoL-6D) instrument was completed by 15,481 adolescents to obtain a description of the quality of life associated with adolescent overweight and obesity, and a corresponding utility score for use in a cost-utility analysis of the interventions. This article describes the recalibration of this utility instrument for adolescents in each country. METHODS The recalibration was based on country-specific time trade-off (TTO) data for 30 multiattribute health states constructed from the AQoL-6D descriptive system. Senior secondary students, in a classroom setting, responded to 10 health state scenarios each. These TTO interviews were conducted for 24 groups, comprising 279 students in the four countries resulting in 2790 completed TTO scores. The TTO scores were econometrically transformed by regressing the TTO scores upon predicted scores from the AQoL-6D to produce country-specific algorithms. The latter incorporated country-specific "corrections" to the Australian adult utility weights in the original AQoL. RESULTS This article reports two methodological elements not previously reported. The first is the econometric modification of an extant multi-attribute utility instrument to accommodate cultural and other group-specific differences in preferences. The second is the use of the TTO technique with adolescents in a classroom group setting. Significant differences in utility scores were found between the four countries. CONCLUSION Statistical results indicate that the AQoL-6D can be validly used in the economic evaluation of both the OPIC interventions and other adolescent programs.
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Affiliation(s)
- Marj Moodie
- Deakin Health Economics, Population Health Strategic Research Centre, Deakin University, Melbourne, Australia.
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Hammerling U, Tallsjö A, Grafström R, Ilbäck NG. Comparative Hazard Characterization in Food Toxicology. Crit Rev Food Sci Nutr 2009; 49:626-69. [DOI: 10.1080/10408390802145617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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Abstract
This paper is concerned with how sex chromosomes and gendered experience differentially contribute to health outcomes, and how gender effects provide an under-explored avenue for health intervention. Research on gender and health is currently undermined by conflation of sex and gender in much of the epidemiologic and clinical literature. This precludes any meaningful reflection on the extent to which our genetic blueprint, versus gendered socialization, contributes to the specific health vulnerabilities of males or females. Drawing on the 2002 global disability adjusted life years (DALYs) for males and females, this paper looks at health outcomes that differentially affect males and females, and distinguishes between vulnerabilities linked to the XX or XY genotype, vulnerabilities due to gendered life experience, and vulnerabilities about which we understand relatively little. The paper highlights the dynamic and changeable nature of gendered health vulnerabilities. Given that gender-based risks are, in principle, amenable to social change, they offer untapped potential for health interventions.
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Affiliation(s)
- R C Snow
- School of Public Health and Population Studies Center, University of Michigan, Ann Arbor, MI 48109-2029, USA.
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Chapman G, Hansen KS, Jelsma J, Ndhlovu C, Piotti B, Byskov J, Vos T. The burden of disease in Zimbabwe in 1997 as measured by disability-adjusted life years lost. Trop Med Int Health 2006; 11:660-71. [PMID: 16640619 DOI: 10.1111/j.1365-3156.2006.01601.x] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To rank health problems contributing most to the burden of disease in Zimbabwe using disability-adjusted life years as the population health measure. METHODS Epidemiological information was derived from multiple sources. Population size and total number of deaths by age and sex for the year 1997 were taken from a nationwide census. The cause of death pattern was determined based on data from the Vital Registration System, which was adjusted for under-reporting of human immunodeficiency virus (HIV) and reallocation of ill-defined causes. Non-fatal disease figures were estimated based on local disease registers, surveys and routine health service data supplemented by estimates from epidemiological studies from other settings if no Zimbabwean sources were available. Disease and public health experts were consulted about the identification of the best possible sources of information, the quality of these sources and data adjustments made. RESULTS From the information collected, HIV infection emerged as the single most serious public health problem in Zimbabwe responsible for 49% of the total disease burden. A quarter of the total burden of disease was attributed to morbidity rather than premature mortality. The share of the disease burden was similar in females and males. CONCLUSION Using local sources of information to a large extent, it was possible to develop plausible estimates of the size and the relative significance of the major health problems in Zimbabwe. The disease pattern of Zimbabwe differed substantially from regional estimates for sub-Saharan Africa justifying the need for countries to develop their own burden of disease estimates.
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Affiliation(s)
- Glyn Chapman
- Department of Obstetrics and Gynaecology, School of Medicine, University of Aberdeen, Aberdeen, UK
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Jelsma J, Hansen K, de Weerdt W, de Cock P, Kind P. How do Zimbabweans value health states? Popul Health Metr 2003; 1:11. [PMID: 14678566 PMCID: PMC317383 DOI: 10.1186/1478-7954-1-11] [Citation(s) in RCA: 97] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2003] [Accepted: 12/16/2003] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND: Quality of life weights based on valuations of health states are often used in cost utility analysis and population health measures. This paper reports on an attempt to develop quality of life weights within the Zimbabwe context. METHODS: 2,384 residents in randomly selected small residential plots of land in a high-density suburb of Harare valued descriptors of 38 health states based on different combinations of the five domains of the EQ-5D (mobility, self-care, usual activities, pain or discomfort and anxiety or depression). The English version of the EQ-5D was used. The time trade-off method was used to determine the values, and 19,020 individual preferences for health states were analysed. A residual maximum likelihood linear mixed model was used to estimate a function for predicting the values of all possible combinations of levels on the five domains. The model was fit to a random subset of two-thirds of the observations, with the remaining observations reserved for analysis of predictive validity. The results were compared to a similar study undertaken in the United Kingdom. RESULTS: A credible model was developed to predict the values of states that were not valued directly. In the subset of observations reserved for validation, the mean absolute difference between predicted and observed values was 0.045. All domains of the EQ-5D were found to contribute significantly to the model, both at the moderate and severe levels. Severe pain was found to have the largest negative coefficient, followed by the inability to wash and dress oneself. CONCLUSION: Despite a generally lower education level than their European counterparts, urban Zimbabweans appear to value health states in a consistent manner, and the determination of a global method of establishing quality of life weights may be feasible and valid. However, as the relative weightings of the different domains, although correlated, differed from the standard set of weights recommended by the EuroQol Group, the locally determined coefficients should be used within the Zimbabwean context.
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Affiliation(s)
- Jennifer Jelsma
- Division of Physiotherapy, University of Cape Town, Anzio Road, Observatory, South Africa
| | - Kristian Hansen
- Department of Health Services Research, University of Copenhagen
| | - Willy de Weerdt
- Faculteit Lichamelijke Opvoeding en Kinesitherapie, Katholieke Universiteit Leuven, Belgium
| | - Paul de Cock
- Centrum voor Ontwikkelingsstoornissen, Faculteit Geneeskunde, Katholieke Universiteit, Leuven, Belgium
| | - Paul Kind
- University of York; Department of Preventive Medicine, University of Wisconsin
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Schwarzinger M, Stouthard MEA, Burström K, Nord E. Cross-national agreement on disability weights: the European Disability Weights Project. Popul Health Metr 2003; 1:9. [PMID: 14633276 PMCID: PMC317384 DOI: 10.1186/1478-7954-1-9] [Citation(s) in RCA: 52] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2003] [Accepted: 11/21/2003] [Indexed: 11/28/2022] Open
Abstract
Background Disability weights represent the relative severity of disease stages to be incorporated in summary measures of population health. The level of agreement on disability weights in Western European countries was investigated with different valuation methods. Methods Disability weights for fifteen disease stages were elicited empirically in panels of health care professionals or non-health care professionals with an academic background following a strictly standardised procedure. Three valuation methods were used: a visual analogue scale (VAS); the time trade-off technique (TTO); and the person trade-off technique (PTO). Agreement among England, France, the Netherlands, Spain, and Sweden on the three disability weight sets was analysed by means of an intraclass correlation coefficient (ICC) in the framework of generalisability theory. Agreement among the two types of panels was similarly assessed. Results A total of 232 participants were included. Similar rankings of disease stages across countries were found with all valuation methods. The ICC of country agreement on disability weights ranged from 0.56 [95% CI, 0.52–0.62] with PTO to 0.72 [0.70–0.74] with VAS and 0.72 [0.69–0.75] with TTO. The ICC of agreement between health care professionals and non-health care professionals ranged from 0.64 [0.58–0.68] with PTO to 0.73 [0.71–0.75] with VAS and 0.74 [0.72–0.77] with TTO. Conclusions Overall, the study supports a reasonably high level of agreement on disability weights in Western European countries with VAS and TTO methods, which focus on individual preferences, but a lower level of agreement with the PTO method, which focuses more on societal values in resource allocation.
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Affiliation(s)
| | - Marlies EA Stouthard
- Division of Clinical Methods and Public Health, Academic Medical Center, Amsterdam, The Netherlands
| | - Kristina Burström
- Department of Public Health Sciences, Division of Social Medicine, Karolinska Institute, Stockholm, Sweden
| | - Erik Nord
- National Institute of Public Health, Oslo, Norway
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