Abstract
Objectives
Prepregnancy body mass index (BMI) and gestational weight gain (GWG) are known determinants of maternal and child health; calculating both requires an accurate measure of prepregnancy weight. We compared self-reported prepregnancy weight to measured weights to assess reporting bias by maternal and clinical characteristics.
Methods
We conducted a retrospective cohort study among pregnant women using electronic health records (EHR) data from Kaiser Permanente Northwest, a non-profit integrated health care system in Oregon and southwest Washington State. We identified women age ≥ 18 years who were pregnant between 2000 and 2010 with self-reported prepregnancy weight, ≥ 2 measured weights between ≤ 365-days-prior-to and ≤ 42-days-after conception, and measured height in their EHR. We compared absolute and relative difference between self-reported weight and two “gold-standards”: (1) weight measured closest to conception, and (2) usual weight (mean of weights measured 6-months-prior-to and ≤ 42-days-after conception). Generalized-estimating equations were used to assess predictors of misreport controlling for covariates, which were obtained from the EHR or linkage to birth certificate.
Results
Among the 16,227 included pregnancies, close agreement (± 1 kg or ≤ 2%) between self-reported and closest-measured weight was 44% and 59%, respectively. Overall, self-reported weight averaged 1.3 kg (SD 3.8) less than measured weight. Underreporting was higher among women with elevated BMI category, late prenatal care entry, and pregnancy outcome other than live/stillbirth (p < .05). Using self-reported weight, BMI was correctly classified for 91% of pregnancies, but ranged from 70 to 98% among those with underweight or obesity, respectively. Results were similar using usual weight as gold standard.
Conclusions for Practice
Accurate measure of prepregnancy weight is essential for clinical guidance and surveillance efforts that monitor maternal health and evaluate public-health programs. Identification of characteristics associated with misreport of self-reported weight can inform understanding of bias when assessing the influence of prepregnancy BMI or GWG on health outcomes.
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Data Availability
The study protocol is available upon request.
Code Availability
The statistical analysis programming code is available upon request.
References
Bannon, A. L., Waring, M. E., Leung, K., Masiero, J. V., Stone, J. M., Scannell, E. C., & Moore Simas, T. A. (2017). Comparison of self-reported and measured pre-pregnancy weight: Implications for gestational weight gain counseling. Maternal and Child Health Journal, 21(7), 1469–1478. https://doi.org/10.1007/s10995-017-2266-3
Dietz, P. M., Rizzo, J. H., England, L. J., Callaghan, W. M., Vesco, K. K., Bruce, F. C., Bulkley, J. E., Sharma, A. J., & Hornbrook, M. C. (2012). Early term delivery and health care utilization in the first year of life. The Journal of Pediatrics, 161(2), 234–239. https://doi.org/10.1016/j.jpeds.2012.02.005
Ferrara, A., Weiss, N. S., Hedderson, M. M., Quesenberry, C. P., Jr., Selby, J. V., Ergas, I. J., Peng, T., Escobar, G. J., Pettitt, D. J., & Sacks, D. A. (2007). Pregnancy plasma glucose levels exceeding the American Diabetes Association thresholds, but below the National Diabetes Data Group thresholds for gestational diabetes mellitus, are related to the risk of neonatal macrosomia, hypoglycaemia and hyperbilirubinaemia. Diabetologia, 50(2), 298–306. https://doi.org/10.1007/s00125-006-0517-8
Goldstein, R. F., Abell, S. K., Ranasinha, S., Misso, M., Boyle, J. A., Black, M. H., Li, N., Hu, G., Corrado, F., Rode, L., Kim, Y. J., Haugen, M., Song, W. O., Kim, M. H., Bogaerts, A., Devlieger, R., Chung, J. H., & Teede, H. J. (2017). Association of gestational weight gain with maternal and infant outcomes: A systematic review and meta-analysis. JAMA, 317(21), 2207–2225. https://doi.org/10.1001/jama.2017.3635
Han, E., Abrams, B., Sridhar, S., Xu, F., & Hedderson, M. (2016). Validity of self-reported pre-pregnancy weight and body mass index classification in an integrated health care delivery system. Paediatric and Perinatal Epidemiology, 30(4), 314–319. https://doi.org/10.1111/ppe.12286
He, X., Hu, C., Chen, L., Wang, Q., & Qin, F. (2014). The association between gestational weight gain and substantial weight retention 1-year postpartum. Archives of Gynecology and Obstetrics, 290(3), 493–499. https://doi.org/10.1007/s00404-014-3235-3
Headen, I., Cohen, A. K., Mujahid, M., & Abrams, B. (2017). The accuracy of self-reported pregnancy-related weight: A systematic review. Obesity Reviews, 18(3), 350–369. https://doi.org/10.1111/obr.12486
Hornbrook, M. C., Whitlock, E. P., Berg, C. J., Callaghan, W. M., Bachman, D. J., Gold, R., Bruce, F. C., Dietz, P. M., & Williams, S. B. (2007). Development of an algorithm to identify pregnancy episodes in an integrated health care delivery system. Health Services Research, 42(2), 908–927. https://doi.org/10.1111/j.1475-6773.2006.00635.x
Kesmodel, U. S. (2018). Information bias in epidemiological studies with a special focus on obstetrics and gynecology. Acta Obstetricia et Gynecologica Scandinavica, 97(4), 417–423. https://doi.org/10.1111/aogs.13330
Lash, T. L., Abrams, B., & Bodnar, L. M. (2014). Comparison of bias analysis strategies applied to a large data set. Epidemiology, 25(4), 576–582. https://doi.org/10.1097/EDE.0000000000000102
Lash, T. L., Fox, M. P., MacLehose, R. F., Maldonado, G., McCandless, L. C., & Greenland, S. (2014). Good practices for quantitative bias analysis. International Journal of Epidemiology, 43(6), 1969–1985. https://doi.org/10.1093/ije/dyu149
Lash, T. L., Schmidt, M., Jensen, A. O., & Engebjerg, M. C. (2010). Methods to apply probabilistic bias analysis to summary estimates of association. Pharmacoepidemiology and Drug Safety, 19(6), 638–644. https://doi.org/10.1002/pds.1938
MacLehose, R. F., & Gustafson, P. (2012). Is probabilistic bias analysis approximately Bayesian? Epidemiology, 23(1), 151–158. https://doi.org/10.1097/EDE.0b013e31823b539c
Oken, E., Taveras, E. M., Kleinman, K. P., Rich-Edwards, J. W., & Gillman, M. W. (2007). Gestational weight gain and child adiposity at age 3 years. American Journal of Obstetrics and Gynecology, 196(4), 322–328. https://doi.org/10.1016/j.ajog.2006.11.027
Orsama, A. L., Mattila, E., Ermes, M., van Gils, M., Wansink, B., & Korhonen, I. (2014). Weight rhythms: Weight increases during weekends and decreases during weekdays. Obesity Facts, 7(1), 36–47. https://doi.org/10.1159/000356147
Oza-Frank, R., Gilson, E., Keim, S. A., Lynch, C. D., & Klebanoff, M. A. (2014). Trends and factors associated with self-reported receipt of preconception care: PRAMS, 2004–2010. Birth, 41(4), 367–373. https://doi.org/10.1111/birt.12122
Rasmussen, K. M., Yaktine, A. L. , & Institute of Medicine (US) and National Research Council (US) Committee to Reexamine IOM Pregnancy Weight Guidelines (Eds.). (2009). Weight gain during pregnancy: Reexamining the guidelines. National Academies Press.
Satpathy, H. K., Fleming, A., Frey, D., Barsoom, M., Satpathy, C., & Khandalavala, J. (2008). Maternal obesity and pregnancy. Postgraduate Medicine, 120(3), E01-09. https://doi.org/10.3810/pgm.2008.09.1920
Sharma, A. J., Vesco, K. K., Bulkley, J., Callaghan, W. M., Bruce, F. C., Staab, J., Hornbrook, M. C., & Berg, C. J. (2015). Associations of gestational weight gain with preterm birth among underweight and normal weight women. Maternal and Child Health Journal, 19(9), 2066–2073. https://doi.org/10.1007/s10995-015-1719-9
Stevens-Simon, C., Roghmann, K. J., & McAnarney, E. R. (1992). Relationship of self-reported prepregnant weight and weight gain during pregnancy to maternal body habitus and age. Journal of the American Dietetic Association, 92(1), 85–87
Funding
Research reported in this publication was funded by Contract # CDC 200-2016-M-91914, “Assessment of Self-Reported Weight,” from the Centers for Disease Control and Prevention (awarded to Dr. Bulkley).
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All authors contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.
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The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or Kaiser Permanente.
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All procedures performed in this study were in accordance with the ethical standards of the 1964 Helsinki declaration and its later amendments. The Kaiser Permanente Northwest Institutional Review Board (IRB) approved this study and granted a waiver of informed consent. The IRB at the Centers for Disease Control and Prevention also approved the study.
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Sharma, A.J., Bulkley, J.E., Stoneburner, A.B. et al. Bias in Self-reported Prepregnancy Weight Across Maternal and Clinical Characteristics. Matern Child Health J 25, 1242–1253 (2021). https://doi.org/10.1007/s10995-021-03149-9
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DOI: https://doi.org/10.1007/s10995-021-03149-9