Maternal and Child Health Journal

, Volume 19, Issue 9, pp 1925–1935 | Cite as

Maternal Recall Versus Medical Records of Metabolic Conditions from the Prenatal Period: A Validation Study

  • Paula Krakowiak
  • Cheryl K. Walker
  • Daniel J. Tancredi
  • Irva Hertz-Picciotto
Methodological Notes


To assess validity of maternally-reported diabetes and hypertensive disorders, and reliability of BMI measurements during periconception and pregnancy compared with medical records when mothers are interviewed 2–5 years after delivery. To investigate whether reporting accuracy differed by child’s case status (autism, delays, typical development). Participants were mothers of 2–5 year old children with and without neurodevelopmental disorders from the CHARGE (CHildhood Autism Risks from Genetics and the Environment) Study who had both prenatal/delivery records and telephone interviews. Sensitivity and specificity of self-report in telephone interview was assessed by comparison with medical records; agreement was evaluated by kappa statistics. Deviations in reported BMI were evaluated with Bland–Altman plots and concordance correlation coefficient (CCC). Mothers of children with neurodevelopmental disorders (autism or developmental delay) reported metabolic conditions slightly more accurately than control mothers. For diabetes, sensitivity ranged from 73 to 87 % and specificity was ≥98 % across groups. For hypertensive disorders, sensitivity ranged from 57 to 77 % and specificity from 93 to 98 %. Reliability of BMI was high (CCC = 0.930); when grouped into BMI categories, a higher proportion of mothers of delayed children were correctly classified (κwt = 0.93) compared with the autism group and controls (κwt = 0.85 and κwt = 0.84, respectively; P = 0.05). Multiparity was associated with higher discrepancies in BMI and misreporting of hypertensive disorders. For purposes of etiologic studies, self-reported diabetes and hypertensive disorders during periconception and pregnancy show high validity among mothers irrespective of child’s case status. Recall of pre-pregnancy BMI is reliable compared with self-reported values in medical records.


Validation study Diabetes Preeclampsia Hypertension Body mass index Pregnancy Neurodevelopmental disorders 



This research was supported by the National Institutes of Health (P01 ES11269 and R01 ES015359), the U.S. Environmental Protection Agency through the Science to Achieve Results (STAR) program (R829388 and R833292) and by the MIND Institute, University of California, Davis. The authors would like to thank the CHARGE Study participants and staff for their dedication and effort.

Conflict of interest

None of the authors have any financial relationships or conflict of interest relevant to this article.

Supplementary material

10995_2015_1723_MOESM1_ESM.docx (241 kb)
Supplementary material 1 (DOCX 240 kb)


  1. 1.
    Rosenberg, T. J., Garbers, S., Lipkind, H., & Chiasson, M. A. (2005). Maternal obesity and diabetes as risk factors for adverse pregnancy outcomes: Differences among 4 racial/ethnic groups. American Journal of Public Health, 95(9), 1545–1551.PubMedCentralPubMedCrossRefGoogle Scholar
  2. 2.
    Orbach, H., Matok, I., Gorodischer, R., Sheiner, E., Daniel, S., Wiznitzer, A., et al. (2013). Hypertension and antihypertensive drugs in pregnancy and perinatal outcomes. American Journal of Obstetrics and Gynecology, 208(4), 301.e1–6.PubMedCrossRefGoogle Scholar
  3. 3.
    Gaillard, R., Durmuş, B., Hofman, A., Mackenbach, J. P., Steegers, E. A., & Jaddoe, V. W. (2013). Risk factors and outcomes of maternal obesity and excessive weight gain during pregnancy. Obesity (Silver Spring), 21(5), 1046–1055.CrossRefGoogle Scholar
  4. 4.
    Walker, C. K., Krakowiak, P., Baker, A., Hansen, R. L., Ozonoff, S., & Hertz-Picciotto, I. (2014). Preeclampsia, placental insufficiency, and autism spectrum disorder or developmental delay. JAMA Pediatrics 2014 Dec 8. [Epub ahead of print].Google Scholar
  5. 5.
    Krakowiak, P., Walker, C. K., Bremer, A. A., Baker, A. S., Ozonoff, S., Hansen, R. L., & Hertz-Picciotto, I. (2012). Maternal metabolic conditions and risk for autism and other neurodevelopmental disorders. Pediatrics, 129(5), e1121–e1128.PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Lawrence, J. M., Contreras, R., Chen, W., & Sacks, D. A. (2008). Trends in the prevalence of preexisting diabetes and gestational diabetes mellitus among a racially/ethnically diverse population of pregnant women, 1999–2005. Diabetes Care, 31(5), 899–904.PubMedCrossRefGoogle Scholar
  7. 7.
    Martin, J. A., Hamilton, B. E., Ventura, S. J., Osterman, M. J., Kirmeyer, S., Mathews, T. J., & Wilson, E. C. (2013). Births: Final data for 2009. National Vital Statistics Reports, 60(1), 1–70.Google Scholar
  8. 8.
    Flegal, K. M., Carroll, M. D., Ogden, C. L., & Curtin, L. R. (2010). Prevalence and trends in obesity among US adults, 1999–2008. Journal of the American Medical Association, 303(3), 235–241.PubMedCrossRefGoogle Scholar
  9. 9.
    Ervin, R. B. (2009). Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States, 2003–2006. National Health Statistics Reports, 2009(13), 1–7.Google Scholar
  10. 10.
    Finer, L. B., & Zolna, M. R. (2011). Unintended pregnancy in the United States: Incidence and disparities, 2006. Contraception, 84(5), 478–485.PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Huerta, J. M., Tormo, M. J., Egea-Caparrós, J. M., Ortolá-Devesa, J. B., & Navarro, C. (2009). Accuracy of self-reported diabetes, hypertension and hyperlipidemia in the adult Spanish population. DINO study findings. Revista Española de Cardiología, 62(2), 143–152.PubMedCrossRefGoogle Scholar
  12. 12.
    Wada, K., Yatsuya, H., Ouyang, P., Otsuka, R., Mitsuhashi, H., Takefuji, S., et al. (2009). Self-reported medical history was generally accurate among Japanese workplace population. Journal of Clinical Epidemiology, 62(3), 306–313.PubMedCrossRefGoogle Scholar
  13. 13.
    Molenaar, E. A., Van Ameijden, E. J., Grobbee, D. E., & Numans, M. E. (2007). Comparison of routine care self-reported and biometrical data on hypertension and diabetes: Results of the Utrecht Health Project. European Journal of Public Health, 17(2), 199–205.PubMedCrossRefGoogle Scholar
  14. 14.
    Goldman, N., Lin, I. F., Weinstein, M., & Lin, Y. H. (2003). Evaluating the quality of self-reports of hypertension and diabetes. Journal of Clinical Epidemiology, 56(2), 148–154.PubMedCrossRefGoogle Scholar
  15. 15.
    Martin, L. M., Leff, M., Calonge, N., Garrett, C., & Nelson, D. E. (2000). Validation of self-reported chronic conditions and health services in a managed care population. American Journal of Preventive Medicine, 18(3), 215–218.PubMedCrossRefGoogle Scholar
  16. 16.
    Alonso, A., Beunza, J. J., Delgado-Rodríguez, M., & Martínez-González, M. A. (2005). Validation of self reported diagnosis of hypertension in a cohort of university graduates in Spain. BioMed Central Public Health, 2005(5), 94–100.CrossRefGoogle Scholar
  17. 17.
    Tormo, M. J., Navarro, C., Chirlaque, M. D., & Barber, X. (2000). Validation of self diagnosis of high blood pressure in a sample of the Spanish EPIC cohort: Overall agreement and predictive values. EPIC Group of Spain. Journal of Epidemiology and Community Health, 54(3), 221–226.PubMedCentralPubMedCrossRefGoogle Scholar
  18. 18.
    Lin, C. J., DeRoo, L. A., Jacobs, S. R., & Sandler, D. P. (2012). Accuracy and reliability of self-reported weight and height in the Sister Study. Public Health Nutrition, 15(6), 989–999.PubMedCentralPubMedCrossRefGoogle Scholar
  19. 19.
    Lee, D. H., Shin, A., Kim, J., Yoo, K. Y., & Sung, J. (2011). Validity of self-reported height and weight in a Korean population. Journal of Epidemiology, 21(1), 30–36.PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Lucca, A., & Moura, E. C. (2010). Validity and reliability of self-reported weight, height and body mass index from telephone interviews. Cadernos de Saúde Pública, 26(1), 110–122.PubMedCrossRefGoogle Scholar
  21. 21.
    Burton, N. W., Brown, W., & Dobson, A. (2010). Accuracy of body mass index estimated from self-reported height and weight in mid-aged Australian women. Australian and New Zealand Journal of Public Health, 34(6), 620–623.PubMedCrossRefGoogle Scholar
  22. 22.
    Craig, B. M., & Adams, A. K. (2009). Accuracy of body mass index categories based on self-reported height and weight among women in the United States. Maternal and Child Health Journal, 13(4), 489–496.PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Wada, K., Tamakoshi, K., Tsunekawa, T., Otsuka, R., Zhang, H., Murata, C., et al. (2005). Validity of self-reported height and weight in a Japanese workplace population. International Journal of Obesity, 29(9), 1093–1099.PubMedCrossRefGoogle Scholar
  24. 24.
    Spencer, E. A., Appleby, P. N., Davey, G. K., & Key, T. J. (2002). Validity of self-reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutrition, 5(4), 561–565.PubMedCrossRefGoogle Scholar
  25. 25.
    Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., et al. (2003). Standards for reporting of diagnostic accuracy. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. British Medical Journal, 326(7379), 41–44.PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Kottner, J., Audigé, L., Brorson, S., Donner, A., Gajewski, B. J., Hróbjartsson, A., et al. (2011). Guidelines for reporting reliability and agreement studies (GRRAS) were proposed. Journal of Clinical Epidemiology, 64(1), 96–106.PubMedCrossRefGoogle Scholar
  27. 27.
    Hertz-Picciotto, I., Croen, L. A., Hansen, R., Jones, C. R., van de Water, J., & Pessah, I. N. (2006). The CHARGE study: an epidemiologic investigation of genetic and environmental factors contributing to autism. Environmental Health Perspectives, 114(7), 1119–1125.PubMedCentralPubMedCrossRefGoogle Scholar
  28. 28.
    Pepe, M. S. (2003). The statistical evaluation of medical tests for classification and prediction. Oxford: Oxford University Press.Google Scholar
  29. 29.
    Fleiss, J. L., & Cohen, J. (1973). The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educational and Psychological Measurement, 33(3), 613–619.CrossRefGoogle Scholar
  30. 30.
    Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.PubMedCrossRefGoogle Scholar
  31. 31.
    Fleiss, J. L., Levin, B., & Paik, M. C. (2003). Statistical methods for rates and proportions (3rd ed.). Hoboken, NJ: Wiley.CrossRefGoogle Scholar
  32. 32.
    Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 1(8476), 307–310.PubMedCrossRefGoogle Scholar
  33. 33.
    Bland, J. M., & Altman, D. G. (2003). Applying the right statistics: analyses of measurement studies. Ultrasound in Obstetrics and Gynecology, 22(1), 85–93.PubMedCrossRefGoogle Scholar
  34. 34.
    Lin, L. I. (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics, 45(1), 255–268.PubMedCrossRefGoogle Scholar
  35. 35.
    Carrasco, J. L., Phillips, B. R., Puig-Martinez, J., King, T. S., & Chinchilli, V. M. (2013). Estimation of the concordance correlation coefficient for repeated measures using SAS and R. Computer Methods and Programs in Biomedicine, 109(3), 293–304.PubMedCrossRefGoogle Scholar
  36. 36.
    Olson, J. E., Shu, X. O., Ross, J. A., Pendergrass, T., & Robison, L. L. (1997). Medical record validation of maternally reported birth characteristics and pregnancy-related events: A report from the Children’s Cancer Group. American Journal of Epidemiology, 145(1), 58–67.PubMedCrossRefGoogle Scholar
  37. 37.
    Klemmensen, A. K., Olsen, S. F., Osterdal, M. L., & Tabor, A. (2007). Validity of preeclampsia-related diagnoses recorded in a national hospital registry and in a postpartum interview of the women. American Journal of Epidemiology, 166(2), 117–124.PubMedCrossRefGoogle Scholar
  38. 38.
    Coolman, M., de Groot, C. J., Jaddoe, V. W., Hofman, A., Raat, H., & Steegers, E. A. (2010). Medical record validation of maternally reported history of preeclampsia. Journal of Clinical Epidemiology, 63(8), 932–937.PubMedCrossRefGoogle Scholar
  39. 39.
    Fattah, C., Farah, N., Barry, S. C., O’Connor, N., Stuart, B., & Turner, M. J. (2010). Maternal weight and body composition in the first trimester of pregnancy. Acta Obstetricia et Gynecologica Scandinavica, 89(7), 952–955.PubMedCrossRefGoogle Scholar
  40. 40.
    Holland, E., Moore Simas, T. A., Doyle Curiale, D. K., Liao, X., & Waring, M. E. (2013). Self-reported pre-pregnancy weight versus weight measured at first prenatal visit: effects on categorization of pre-pregnancy body mass index. Maternal and Child Health Journal, 17(10), 1872–1878.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Paula Krakowiak
    • 1
    • 2
  • Cheryl K. Walker
    • 2
    • 3
  • Daniel J. Tancredi
    • 4
  • Irva Hertz-Picciotto
    • 1
    • 2
  1. 1.Divisions of Epidemiology and of Environmental and Occupational Health, Department of Public Health Sciences, School of MedicineUniversity of CaliforniaDavisUSA
  2. 2.MIND (Medical Investigations of Neurodevelopmental Disorders) InstituteUniversity of CaliforniaDavis, SacramentoUSA
  3. 3.Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, School of MedicineUniversity of CaliforniaDavisUSA
  4. 4.Department of Pediatrics, School of MedicineUniversity of CaliforniaDavisUSA

Personalised recommendations