Background: Most studies on health expectancies rely on self-reported health from surveys to measure the prevalence of disabilities or ill health in a population. At best, such studies only correct for sample selection based on a limited number of characteristics observed on the invitees. Objective: Using longitudinal data from the Trøndelag Health Study (HUNT), I investigate the extent to which adjustments for a health-related sample selection affect the age profiles for the prevalence of functional impairment (FI) and the associated disability-free life expectancy (DFLE). Methods: I estimate a probit model with sample selection under the identifying restriction that the strength of the health-related selection is of similar order to the strength of the selection on observable characteristics. I then compute the selection-adjusted FI prevalence rates and trace out the implications for DFLE using the Sullivan method. Results: The analysis confirms that poor health measured at younger ages correlates with nonresponse behaviour in later waves of the survey, and that even for a conservative lower bound for the assumed degree of health-related selection, the estimated age profiles for DFLE lie systematically below the corresponding profiles when controlling only for selection on observable characteristics. Conclusions: Health related non-response downwardly biases the raw sample prevalence rates for FI obtained from survey data and contributes to overestimating the expansion in DFLE. Contribution: I present a statistical framework for taking health-related survey non-responses into account when estimating the prevalence rate of FI. The framework can be used to gauge the sensitivity of estimated (changes in) DFLE to health-related sample selection.

中文翻译：

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在估计健康预期时纠正与健康相关的调查无答复的重要性：来自 HUNT 研究的证据（Fred Schroyen）

背景：大多数关于健康预期的研究依赖于调查中自我报告的健康状况来衡量人群中残疾或健康状况不佳的患病率。充其量，此类研究只能根据在受邀者身上观察到的有限数量的特征来纠正样本选择。目的：利用特伦德拉格健康研究 (HUNT) 的纵向数据，我调查了健康相关样本选择的调整对功能损伤 (FI) 患病率的年龄分布和相关的无残疾预期寿命的影响程度。 DFLE）。方法：我在识别限制下估计了样本选择的概率模型，即与健康相关的选择的强度与可观察特征的选择的强度具有相似的顺序。然后，我计算选择调整后的 FI 患病率，并使用沙利文方法追踪对 DFLE 的影响。结果：分析证实，年轻时测量的健康状况不佳与后期调查中的不答复行为相关，并且即使对于假设的健康相关选择程度的保守下限，DFLE 的估计年龄概况也系统地低于仅控制可观察特征的选择时的相应配置文件。结论：与健康相关的无答复使从调查数据获得的 FI 原始样本患病率出现向下偏差，并导致高估 DFLE 的扩张。贡献：我提出了一个统计框架，用于在估计 FI 患病率时考虑健康相关调查的无答复情况。该框架可用于衡量估计的 DFLE（变化）对健康相关样本选择的敏感性。