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.
Institute of Health and Society (IRSS), Université catholique de Louvain, Leuven, Belgium.
Popul Health Metr. 2015 Apr 3;13:10. doi: 10.1186/s12963-015-0042-4. eCollection 2015.
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.
背景：在使用伤残调整生命年来计算疾病负担时，需要使用伤残权重来量化与非致命结果相关的健康损失，以失能年限来表示。2012 年，全球疾病负担 2010 研究（GBD 2010）发布了一套新的全球伤残权重。该研究表明，在不同环境下，对不同健康结果的比较评估大致相似，但这一结论的意义一直存在争议。本研究旨在通过在四个欧洲国家的代表性人群样本中重复 GBD 2010 伤残权重测量研究，为一套 255 种健康状态（包括 43 种新的健康状态）估计欧洲的伤残权重。
方法：为了评估欧洲的伤残权重，我们在匈牙利、意大利、荷兰和瑞典的网络样本调查中应用了 GBD 2010 伤残权重测量方法。该调查包括配对比较（PC）和人口健康等效问题（PHE），以离散选择的形式提出。概率回归分析用于从 PC 回答中估计基数价值。为了将结果定位到 0 到 1 的伤残权重量表上，我们评估了基于 PHE 问题的 GBD 2010 缩放方法以及使用非参数回归的替代方法的可行性。
结果：共有 30660 名受访者参与了调查。对每个国家的 PC 回答的概率回归结果进行比较表明，国家之间存在高度的线性相关性。在这些一般人群样本中，PHE 数据的测量误差水平很高，这影响了从离散选择响应中推断比率标度值的能力。使用非参数回归方法作为替代重标程序，该组伤残权重的下限为轻度视力障碍和贫血，权重最低（0.004），上限为严重多发性硬化症，权重最高（0.677）。
结论：本研究中对健康结果的 PC 评估在四个欧洲国家之间产生了高度相关的估计。对基于 PHE 问题的离散选择表述的重标可行性的评估表明，这种方法可能不适合在一般人群的网络调查中使用。
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