Maternal and Child Health Journal

, Volume 17, Issue 2, pp 282–291 | Cite as

Self-Reported Body Weight and Height: An Assessment Tool for Identifying Children with Overweight/Obesity Status and Cardiometabolic Risk Factors Clustering

  • Noel P. T. Chan
  • Kai C. Choi
  • E. Anthony S. Nelson
  • Rita Y. T. Sung
  • Juliana C. N. Chan
  • Alice P. S. Kong


Body mass index (BMI) is commonly used for assessing body fat. Self-reported body weight and height derived BMI (SRDBMI) is a simple, low cost and non-invasive assessment tool and it may be a useful self-reported assessment tool to monitor the prevalence of overweight/obesity in community settings and for epidemiological research. We assessed the agreement of BW and BH between assessor measured and child self-reported values and evaluated the diagnostic ability of SRDBMI to identify children with overweight/obesity status and cardiometabolic risk factors (CMRFs) clustering. A cross-sectional study was conducted in school settings using a cluster sampling method. A total of 1,614 children aged 6–18 years were included in the analysis. Children were given a questionnaire to complete at home prior to the anthropometric measurements and blood taking at the schools. There was almost perfect agreement on BW, BH and BMI between self-reported and measured values [intraclass correlation coefficients ranged from 0.93 (95% CI: 0.93–0.94) to 0.99 (95% CI: 0.98–0.99)]. About half of the children reported their BW and BH absolute values within 1 kg and 2 cm of measured values, respectively. The SRDBMI demonstrated good diagnostic ability for identifying children with overweight/obesity status (sensitivity, specificity, positive and negative predictive values ranged from 0.83 to 0.98) and CMRFs clustering (AUC-ROCs values of BMI between measured and self-reported values were close ranging from 0.85 to 0.89). Self-reported BW and BH demonstrated almost perfect agreement with measured values and could substantially identify children with overweight/obesity status and CMRFs clustering.


Childhood overweight and obesity Cardiometabolic risk factors Self-reported body weight and height 


  1. 1.
    Lobstein, T., Baur, L., & Uauy, R. (2004). Obesity in children and young people: A crisis in public health. Obesity Reviews, 5, 4–85.PubMedCrossRefGoogle Scholar
  2. 2.
    World Health Organization. (2010). WHO forum and technical meeting on population-based prevention strategies for childhood obesity. Geneva, Switzerland: World Health Organization.Google Scholar
  3. 3.
    de Onis, M., Blössner, M., & Borghi, E. (2010). Global prevalence and trends of overweight and obesity among preschool children. The American Journal of Clinical Nutrition, 92(5), 1257–1264.PubMedCrossRefGoogle Scholar
  4. 4.
    So, H. K., Nelson, E., Li, A., Wong, E., Lau, J., Guldan, G., et al. (2008). Secular changes in height, weight and body mass index in Hong Kong Children. BMC Public Health, 8(1), 320.PubMedCrossRefGoogle Scholar
  5. 5.
    Leung, S. S., Cole, T. J., Tse, L. Y., & Lau, J. T. (1998). Body mass index reference curves for Chinese children. Annals of Human Biology, 25(2), 169–174.PubMedCrossRefGoogle Scholar
  6. 6.
    Ogden, C. L., Carroll, M. D., & Flegal, K. M. (2008). High body mass index for age among US children and adolescents, 2003–2006. JAMA, the Journal of the American Medical Association, 299(20), 2401–2405. doi:10.1001/jama.299.20.2401.CrossRefGoogle Scholar
  7. 7.
    Freedman, D. S., Mei, Z., Srinivasan, S. R., Berenson, G. S., & Dietz, W. H. (2007). Cardiovascular risk factors and excess adiposity among overweight children and adolescents: The Bogalusa Heart Study. The Journal of Pediatrics, 150(1), 12–17.e12. doi:10.1016/j.jpeds.2006.08.042.Google Scholar
  8. 8.
    Srinivasan, S. R., Myers, L., & Berenson, G. S. (2006). Changes in metabolic syndrome variables since childhood in prehypertensive and hypertensive subjects: The Bogalusa Heart Study. Hypertension, 48(1), 33–39.PubMedCrossRefGoogle Scholar
  9. 9.
    Sung, R. Y. T., Tong, P. C. Y., Yu, C. W., Lau, P. W. C., Mok, G. T. F., Yam, M. C., et al. (2003). High prevalence of insulin resistance and metabolic syndrome in overweight/obese preadolescent Hong Kong Chinese children aged 9–12 years. Diabetes Care, 26(1), 250–251.PubMedCrossRefGoogle Scholar
  10. 10.
    Thompson, D. R., Obarzanek, E., Franko, D. L., Barton, B. A., Morrison, J., Biro, F. M., et al. (2007). Childhood overweight and cardiovascular disease risk factors: The National Heart, Lung, and Blood Institute Growth and Health Study. The Journal of Pediatrics, 150(1), 18–25.PubMedCrossRefGoogle Scholar
  11. 11.
    Freedman, D. S., & Sherry, B. (2009). The validity of BMI as an indicator of body fatness and risk among children. Pediatrics, 124(Supplement_1), S23–S34.PubMedCrossRefGoogle Scholar
  12. 12.
    Janssen, I., Katzmarzyk, P. T., Boyce, W. F., Vereecken, C., Mulvihill, C., Roberts, C., et al. (2005). Comparison of overweight and obesity prevalence in school-aged youth from 34 countries and their relationships with physical activity and dietary patterns. Obesity Reviews, 6(2), 123–132. doi:10.1111/j.1467-789X.2005.00176.x.PubMedCrossRefGoogle Scholar
  13. 13.
    Lissau, I., Overpeck, M. D., Ruan, W. J., Due, P., Holstein, B. E., & Hediger, M. L. (2004). Body mass index and overweight in adolescents in 13 European countries, Israel, and the United States. Archives of Pediatrics and Adolescent Medicine, 158(1), 27–33. doi:10.1001/archpedi.158.1.27.PubMedCrossRefGoogle Scholar
  14. 14.
    Goodman, E., Hinden, B. R., & Khandelwal, S. (2000). Accuracy of teen and parental reports of obesity and body mass index. Pediatrics, 106(1), 52–58.PubMedCrossRefGoogle Scholar
  15. 15.
    Himes, J. H., & Faricy, A. (2001). Validity and reliability of self-reported stature and weight of US adolescents. American Journal of Human Biology: The Official Journal of the Human Biology Council, 13(2), 255–260.CrossRefGoogle Scholar
  16. 16.
    Himes, J. H., Hannan, P., Wall, M., & Neumark-Sztainer, D. (2005). Factors associated with errors in self-reports of stature, weight, and body mass index in Minnesota adolescents. Annals of Epidemiology, 15(4), 272–278.PubMedCrossRefGoogle Scholar
  17. 17.
    Strauss, R. S. (1999). Comparison of measured and self-reported weight and height in a cross-sectional sample of young adolescents. International journal of obesity and related metabolic disorders: Journal of the International Association for the Study of Obesity, 23(8), 904–908.CrossRefGoogle Scholar
  18. 18.
    Fonseca, H., Silva, A. M., Matos, M. G., Esteves, I., Costa, P., Guerra, A., et al. (2010). Validity of BMI based on self-reported weight and height in adolescents. Acta Paediatrica, 99(1), 83–88. doi:10.1111/j.1651-2227.2009.01518.x.PubMedGoogle Scholar
  19. 19.
    Larsen, J. K., Ouwens, M., Engels, R. C. M. E., Eisinga, R., & Van Strien, T. (2008). Validity of self-reported weight and height and predictors of weight bias in female college students. Appetite, 50(2–3), 386–389.PubMedCrossRefGoogle Scholar
  20. 20.
    Elgar, F. J., Roberts, C., Tudor-Smith, C., & Moore, L. (2005). Validity of self-reported height and weight and predictors of bias in adolescents. Journal of Adolescent Health, 37(5), 371–375. doi:10.1016/j.jadohealth.2004.07.014.PubMedCrossRefGoogle Scholar
  21. 21.
    Wang, Z., Patterson, C. M., & Hills, A. P. (2002). A comparison of self-reported and measured height, weight and BMI in Australian adolescents. Australian and New Zealand Journal of Public Health, 26(5), 473–478. doi:10.1111/j.1467-842X.2002.tb00350.x.PubMedCrossRefGoogle Scholar
  22. 22.
    Lee, K., Valeria, B., Kochman, C., & Lenders, C. M. (2006). Self-assessment of height, weight, and sexual maturation: validity in overweight children and adolescents. Journal of Adolescent Health, 39(3), 346–352. doi:10.1016/j.jadohealth.2005.12.016.PubMedCrossRefGoogle Scholar
  23. 23.
    Elgar, F. J., & Stewart, J. M. (2008). Validity of self-report screening for overweight and obesity. Evidence from the Canadian Community Health Survey. Canadian Journal of Public Health. Revue canadienne de sante publique, 99(5), 423–427.PubMedGoogle Scholar
  24. 24.
    Deurenberg, P., Yap, M., & vanStaveren, W. A. (1998). Body mass index and percent body fat: a meta-analysis among different ethnic groups. International Journal of Obesity and Related Metabolic Disorders, 22, 1164–1171. doi:10.1038/sj.ijo.0800741.PubMedCrossRefGoogle Scholar
  25. 25.
    Brener, N. D., McManus, T., Galuska, D. A., Lowry, R., & Wechsler, H. (2003). Reliability and validity of self-reported height and weight among high school students. Journal of Adolescent Health, 32(4), 281–287. doi:10.1016/s1054-139x(02)00708-5.PubMedCrossRefGoogle Scholar
  26. 26.
    Tokmakidis, S. P., Christodoulos, A. D., & Mantzouranis, N. I. (2007). Validity of self-reported anthropometric values used to assess body mass index and estimate obesity in Greek school children. Journal of Adolescent Health, 40(4), 305–310. doi:10.1016/j.jadohealth.2006.10.001.PubMedCrossRefGoogle Scholar
  27. 27.
    Ng, V. W. S., Kong, A. P. S., Choi, K., Ozaki, R., Wong, G. W. K., So, W. Y., et al. (2007). BMI and waist circumference in predicting cardiovascular risk factor clustering in Chinese adolescents. Obesity, 15(2), 494–503.PubMedCrossRefGoogle Scholar
  28. 28.
    Sung, R. Y. T., Yu, C. C. W., Choi, K. C., McManus, A., Li, A. M. C., Xu, S. L. Y., et al. (2007). Waist circumference and body mass index in Chinese children: cutoff values for predicting cardiovascular risk factors. International Journal of Obesity, 31, 550–558.PubMedCrossRefGoogle Scholar
  29. 29.
    Cruz, M. L., Weigensberg, M. J., Huang, T. T.-K., Ball, G., Shaibi, G. Q., & Goran, M. I. (2004). The metabolic syndrome in overweight Hispanic youth and the role of insulin sensitivity. The Journal of Clinical Endocrinology and Metabolism, 89(1), 108–113. doi:10.1210/jc.2003-031188.PubMedCrossRefGoogle Scholar
  30. 30.
    Freedman, D., Pisani, R., & Purves, R. (1998). Statistics (3rd ed.). New York: W.W. Norton.Google Scholar
  31. 31.
    Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.PubMedCrossRefGoogle Scholar
  32. 32.
    DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988). Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics, 44(3), 837–845.PubMedCrossRefGoogle Scholar
  33. 33.
    Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression. New York: Wiley.CrossRefGoogle Scholar
  34. 34.
    Hong Kong Census and Statistics Department, H.G. (2006). Hong Kong population by-census [Retrieved January 10, 2012]. Available from:
  35. 35.
    Lam, T. H., Lee, S. W., Fung, S., Ho, S. Y., Lee, P. W. H., & Stewart, S. M. (2009). Sociocultural influences on body dissatisfaction and dieting in Hong Kong girls. European Eating Disorders Review, 17(2), 152–160. doi:10.1002/erv.900.PubMedCrossRefGoogle Scholar
  36. 36.
    Cheng, T. O. (2009). Central obesity is a more sensitive predictor of cardiovascular disease than body mass index in the Chinese population. International Journal of Cardiology, 135(3), 385.PubMedCrossRefGoogle Scholar
  37. 37.
    Sung, R., So, H. K., Choi, K. C., Nelson, E., Li, A., Yin, J., et al. (2008). Waist circumference and waist-to-height ratio of Hong Kong Chinese children. BMC Public Health, 8(1), 324.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Noel P. T. Chan
    • 1
  • Kai C. Choi
    • 2
  • E. Anthony S. Nelson
    • 3
  • Rita Y. T. Sung
    • 4
  • Juliana C. N. Chan
    • 5
  • Alice P. S. Kong
    • 5
  1. 1.Rm 322, 3rd floor, William M.W. Mong Block, The School of NursingThe University of Hong KongPokfulamHong Kong
  2. 2.7th floor, The Nethersole School of Nursing, Esther Lee BuildingThe Chinese University of Hong KongShatin, N.T.Hong Kong
  3. 3.Department of PaediatricsThe Chinese University of Hong KongHong Kong SARChina
  4. 4.Clinical Skills Learning CentreThe Chinese University of Hong KongHong Kong SARChina
  5. 5.Department of Medicine and TherapeuticsThe Chinese University of Hong KongHong Kong SARChina

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