From the Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN.
Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA.
Epidemiology. 2024 Jul 1;35(4):489-498. doi: 10.1097/EDE.0000000000001734. Epub 2024 Mar 29.
Prepregnancy body mass index (BMI) and gestational weight gain (GWG) are determinants of maternal and child health. However, many studies of these factors rely on error-prone self-reported measures.
Using data from Life-course Experiences And Pregnancy (LEAP), a US-based cohort, we assessed the validity of prepregnancy BMI and GWG recalled on average 8 years postpartum against medical record data treated as alloyed gold standard ("true") values. We calculated probabilities of being classified into a self-reported prepregnancy BMI or GWG category conditional on one's true category (analogous to sensitivities and specificities) and probabilities of truly being in each prepregnancy BMI or GWG category conditional on one's self-reported category (analogous to positive and negative predictive values).
There was a tendency toward under-reporting prepregnancy BMI. Self-report misclassified 32% (95% confidence interval [CI] = 19%, 48%) of those in LEAP with truly overweight and 13% (5%, 27%) with obesity into a lower BMI category. Self-report correctly predicted the truth for 72% (55%, 84%) with self-reported overweight to 100% (90%, 100%) with self-reported obesity. For GWG, both under- and over-reporting were common; self-report misclassified 32% (15%, 55%) with truly low GWG as having moderate GWG and 50% (28%, 72%) with truly high GWG as moderate or low GWG. Self-report correctly predicted the truth for 45% (25%, 67%) with self-reported high GWG to 85% (76%, 91%) with self-reported moderate GWG. Misclassification of BMI and GWG varied across maternal characteristics.
Findings can be used in quantitative bias analyses to estimate bias-adjusted associations with prepregnancy BMI and GWG.
孕前体重指数（BMI）和孕期体重增加（GWG）是母婴健康的决定因素。然而，许多关于这些因素的研究依赖于易出错的自我报告测量。
利用来自美国队列研究 Life-course Experiences And Pregnancy（LEAP）的数据，我们评估了产后平均 8 年回忆的孕前 BMI 和 GWG 与作为混合金标准（“真实”）值的医疗记录数据的有效性。我们根据真实类别计算了被归类为自我报告的孕前 BMI 或 GWG 类别的概率（类似于敏感性和特异性），以及根据自我报告的类别真正处于每个孕前 BMI 或 GWG 类别的概率（类似于阳性和阴性预测值）。
存在低估孕前 BMI 的趋势。自我报告错误地将 32%（95%置信区间[CI] = 19%，48%）的 LEAP 参与者的超重和 13%（5%，27%）的肥胖归入较低的 BMI 类别。自我报告正确预测了 72%（55%，84%）超重的真实情况，100%（90%，100%）肥胖的真实情况。对于 GWG，低报和高报都很常见；自我报告错误地将 32%（15%，55%）的真正低 GWG 归类为中等 GWG，将 50%（28%，72%）的真正高 GWG 归类为中等或低 GWG。自我报告正确预测了 45%（25%，67%）高 GWG 的真实情况，85%（76%，91%）中等 GWG 的真实情况。BMI 和 GWG 的分类错误在孕产妇特征上有所不同。
这些发现可用于定量偏倚分析，以估计与孕前 BMI 和 GWG 相关的偏倚调整关联。
