The National Population Health Survey's assessment of depression risk factor associations: a simulation study assessing vulnerability to bias.

S B Patten
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Abstract

Background: In Canada, the major source of longitudinal information on major depression epidemiology has been the National Population Health Survey (NPHS). However, the timing of NPHS interviews may raise concerns about the quality of its estimates. Specifically, the NPHS interview assesses major depressive episodes (MDE) in the year before an interview, whereas the interviews are conducted 2 years apart. The objective of this study was to determine whether this aspect of the NPHS can be expected to introduce bias into longitudinal estimates of risk factor associations.

Methods: A simulation model was used to represent the underlying epidemiology and the expected results of a study adopting the NPHS approach to assessment of MDE. The model was used to explore the extent of the resulting distortion of estimates across a range of underlying hazard ratios.

Results: The simulations indicated that the timing and coverage of depression interviews in the NPHS would not introduce substantial bias. The model suggested that incidence would be underestimated as a result of episodes being missed, but that this would not substantially distort estimates of association.

Conclusion: The timing of interviews in the NPHS is not expected to cause biased relative risk estimates. NPHS estimates may, of course, be influenced by other sources of bias.

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全国人口健康调查对抑郁症风险因素关联的评估:一项评估易受偏见影响的模拟研究。
背景:在加拿大,重度抑郁症流行病学纵向信息的主要来源是全国人口健康调查(NPHS)。然而,国家卫生服务体系访谈的时机可能会引起对其估计质量的担忧。具体而言,NPHS访谈评估的是访谈前一年的重度抑郁发作(MDE),而访谈间隔两年进行。本研究的目的是确定NPHS的这一方面是否会在风险因素关联的纵向估计中引入偏差。方法:采用NPHS方法对MDE进行评估,采用模拟模型来代表潜在流行病学和预期结果。该模型用于探索在一系列潜在风险比中产生的估计失真的程度。结果:模拟结果表明,NPHS中抑郁症访谈的时间和覆盖范围不会引入实质性偏差。该模型表明,由于错过了发作,发病率将被低估,但这不会严重扭曲对相关性的估计。结论:NPHS的访谈时间预计不会导致有偏倚的相对风险估计。当然,国家公共卫生服务计划的估计可能会受到其他偏见来源的影响。
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来源期刊
Chronic Diseases and Injuries in Canada
Chronic Diseases and Injuries in Canada PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
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