Cancer Epidemiology Unit, University of Oxford, Oxford, UK.
BMC Med Res Methodol. 2011 Jan 17;11:7. doi: 10.1186/1471-2288-11-7.
Data on lifetime exposures are often self-reported in epidemiologic studies, sometimes many years after the relevant age. Validity of self-reported data is usually inferred from their agreement with measured values, but few studies directly quantify the likely effects of reporting errors in body size and reproductive history variables on estimates of disease-exposure associations.
The MRC National Survey of Health and Development (NSHD) and the Million Women Study (MWS) are UK population-based prospective cohorts. The NSHD recruited participants at birth in 1946 and has followed them at regular intervals since then, whereas the MWS recruited women in middle age. For 541 women who were participants in both studies, we used statistical measures of association and agreement to compare self-reported MWS data on body size throughout life and reproductive history, obtained in middle age, to NSHD data measured or reported close to the relevant ages. Likely attenuation of estimates of linear disease-exposure associations due to the combined effects of random and systematic errors was quantified using regression dilution ratios (RDRs).
Data from the two studies were very strongly correlated for current height, weight and body mass index, and age at menopause (Pearson r = 0.91-0.95), strongly correlated for birth weight, parental heights, current waist and hip circumferences and waist-to-height ratio (r = 0.67-0.80), and moderately correlated for age at menarche and waist-to-hip ratio (r = 0.52-0.57). Self-reported categorical body size and clothes size data for various ages were moderately to strongly associated with anthropometry collected at the relevant times (Spearman correlations 0.51-0.79). Overall agreement between the studies was also good for most quantitative variables, although all exhibited both random and systematic reporting error. RDRs ranged from 0.66 to 0.86 for most variables (slight to moderate attenuation), except weight and body mass index (1.02 and 1.04, respectively; little or no attenuation), and age at menarche, birth weight and waist-to-hip ratio (0.44, 0.59 and 0.50, respectively; substantial attenuation).
This study provides some evidence that self-reported data on certain anthropometric and reproductive factors may be adequate for describing disease-exposure associations in large epidemiological studies, provided that the effects of reporting errors are quantified and the results are interpreted with caution.
在流行病学研究中,寿命暴露数据通常是自我报告的,有时是在相关年龄之后的很多年。自我报告数据的有效性通常是从它们与测量值的一致性推断出来的,但很少有研究直接量化在身体大小和生殖历史变量的报告错误对疾病-暴露关联估计的可能影响。
英国国民健康与发展调查(NSHD)和百万妇女研究(MWS)是英国基于人群的前瞻性队列研究。NSHD 在 1946 年出生时招募参与者,并从那时起定期随访他们,而 MWS 则在中年招募女性。对于 541 名同时参加这两项研究的女性,我们使用关联和一致性的统计指标,将中年时获得的 MWS 关于终生身体大小和生殖历史的自我报告数据与 NSHD 接近相关年龄时测量或报告的数据进行比较。使用回归稀释比(RDR)量化由于随机和系统误差的综合影响而导致线性疾病-暴露关联估计值衰减的可能性。
两项研究的数据非常强相关,包括当前身高、体重和体重指数,以及绝经年龄(Pearson r = 0.91-0.95),与出生体重、父母身高、当前腰围和臀围以及腰高比(r = 0.67-0.80)强相关,与初潮年龄和腰臀比(r = 0.52-0.57)中度相关。不同年龄的自我报告分类身体大小和衣服大小数据与相关时间收集的人体测量数据中度至高度相关(Spearman 相关性 0.51-0.79)。大多数定量变量的研究之间的总体一致性也很好,尽管所有变量都表现出随机和系统报告误差。大多数变量的 RDR 范围为 0.66-0.86(轻度至中度衰减),除了体重和体重指数(分别为 1.02 和 1.04;几乎没有或没有衰减)以及初潮年龄、出生体重和腰臀比(分别为 0.44、0.59 和 0.50;大量衰减)。
这项研究提供了一些证据,表明自我报告的某些人体测量和生殖因素的数据可能足以描述大型流行病学研究中的疾病-暴露关联,前提是量化报告错误的影响并谨慎解释结果。