期刊
PAEDIATRIC AND PERINATAL EPIDEMIOLOGY
卷 29, 期 6, 页码 576-588出版社
WILEY-BLACKWELL
DOI: 10.1111/ppe.12245
关键词
Bias (Epidemiology); Cohort Studies; Fertility Determinants
资金
- National Institutes of Health [R21-HD050264]
- Danish Medical Research Council [271-07-0338]
- National Institutes of Health Intramural Research Training Award
- [T32-HD052458]
BackgroundEpidemiologic studies of fecundability often use retrospectively measured time-to-pregnancy (TTP), thereby introducing potential for recall error. Little is known about how recall error affects the bias and precision of the fecundability odds ratio (FOR) in such studies. MethodsUsing data from the Danish Snart-Gravid Study (2007-12), we quantified error for TTP recalled in the first trimester of pregnancy relative to prospectively measured TTP among 421 women who enrolled at the start of their pregnancy attempt and became pregnant within 12 months. We defined recall error as retrospectively measured TTP minus prospectively measured TTP. Using linear regression, we assessed mean differences in recall error by maternal characteristics. We evaluated the resulting bias in the FOR and 95% confidence interval (CI) using simulation analyses that compared corrected and uncorrected retrospectively measured TTP values. ResultsRecall error (mean=-0.11 months, 95% CI -0.25, 0.04) was not appreciably associated with maternal age, gravidity, or recent oral contraceptive use. Women with TTP>2 months were more likely to underestimate their TTP than women with TTP2 months (unadjusted mean difference in error: -0.40 months, 95% CI -0.71, -0.09). FORs of recent oral contraceptive use calculated from prospectively measured, retrospectively measured, and corrected TTPs were 0.82 (95% CI 0.67, 0.99), 0.74 (95% CI 0.61, 0.90), and 0.77 (95% CI 0.62, 0.96), respectively. ConclusionsRecall error was small on average among pregnancy planners who became pregnant within 12 months. Recall error biased the FOR of recent oral contraceptive use away from the null by 10%. Quantitative bias analysis of the FOR can help researchers quantify the bias from recall error.
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