Back
 OJPed  Vol.3 No.2 , June 2013
The predictive value of childhood blood pressure values for adult elevated blood pressure
Abstract: Because of the paucity of serial blood pressure data on the same individuals, little is known about the accuracy of elevated blood pressure (BP) in childhood for predicting hypertension (HBP) later in life. The availability of long-term serial BP data from the Fels Longitudinal Study (FLS) presents the opportunity to link HBP in adulthood directly to BP measured decades earlier in the same individuals as children. We analyzed serial data from 965 men and 1114 women in the FLS. We used an autoregressive-moving average (1, 1) [ARMA (1, 1)] longitudinal model to predict adult HBP from childhood values. For 15-year-old boys with SBP 15 mmHg and 30 mmHg above the average SBP of 90 mmHg, the probabilities of having HBP at age 35 are 0.18 and 0.33, respectively. The corresponding probabilities for 15-year-old girls are only 0.04 and 0.08. This striking sex difference in risk of HBP at age 35 between 15-year-old boys and girls indicates that the risk of developing HBP in women is low regardless of their childhood blood pressure at any age from 2 to 17 years. Men are about 4.25 times more likely to have HBP at age 35 than women over a range of SBP of 90 - 140 mmHg at age 15. The ARMA (1, 1) model allows the identification of boys at risk for HBP as adult men.
Cite this paper: Carrico, R. , Sun, S. , Sima, A. and Rosner, B. (2013) The predictive value of childhood blood pressure values for adult elevated blood pressure. Open Journal of Pediatrics, 3, 116-126. doi: 10.4236/ojped.2013.32022.
References

[1]   Rosen, B.D., Edvardsen, T., Lai, S., Castillo, E., Pan, L., Jerosch-Herold, M., et al. (2005) Left ventricular concentric remodeling is associated with decreased global and regional systolic function. Circulation, 112, 984-991. doi:10.1161/CIRCULATIONAHA104.500488

[2]   Rosner, B. and Munoz, A. (1988) Autoregressive modelling for the analysis of longitudinal data with unequally spaced examinations. Statistics in Medicine, 7, 59-71. doi:10.1002/sim.4780070110

[3]   Rosner, B., Munoz, A., Tager, I., Speizer, F. and Weiss, S. (1985) The use of an autoregressive model for the analysis of longitudinal data in epidemiologic studies. Statistics in Medicine, 4, 457-467. doi:10.1002/sim.4780040407

[4]   Beckett, L.A., Rosner, B., Roche, A.F. and Guo, S. (1992) Serial changes in blood pressure from adolescence into adulthood. American Journal of Epidemiology, 135, 1166-1177.

[5]   Sun, S.S., Grave, G.D., Siervogel, R.M., Pickoff, A.A., Arslanian, S.S. and Daniels, S.R. (2007) Systolic blood pressure in childhood predicts hypertension and metabolic syndrome later in life. Pediatrics, 119, 237-246. doi:10.1542/peds.2006-2543

[6]   US Department of Health and Human Services (2004) The fourth report of the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents. Pediatrics, 114, 555-576. doi:10.1542/peds.114.2.S2.555

[7]   Roche, A.F. (1992) Growth, maturation, and body composition: The Fels longitudinal study 1929-1991. Cambridge University Press, Cambridge. doi:10.1017/CBO9780511661655

[8]   Roche, A.F. and Sun, S. (2003) Human growth: Assessment and interpretation. Cambridge University Press, Cambridge. doi:10.1017/CBO9780511525681

[9]   Lohman, G.T., Roche, A.F. and Martorell, R. (1988) Anthropometric standardization reference manual. Human Kinetics, Champaign.

[10]   The Multiple Risk Factor Intervention Trial (MRFIT) (1976) A national study of primary prevention of coronary heart disease. JAMA, 235, 825-827. doi:10.1001/jama.1976.03260340031016

[11]   Rubin, D.B. (1976) Inference and missing data. Biometricka, 63, 581-592. doi:10.1093/bio met/63.3.581

[12]   Akaike, H. (1973) Information theory and an extension of the maximum likelihood principle, in breakthroughs in statistics Volume 1. In: Kotz, S. and Johnson, N.L., Eds., Foundations and Basic Theory, Springer-Verlag, New York, 610-624.

[13]   Akaike, H. (1987) Factor analysis and AIC. Psychometrika, 52, 317-332. doi:10.1007/BF02294359

[14]   Coca, A., Gabriel, R., de la Figuera, M., Lopez-Sendon, J.L., Fernandez, R., Sagastagoitia, J.D., et al. (1999) The impact of different echocardiographic diagnostic criteria on the prevalence of left ventricular hypertrophy in essential hypertension: The VITAE study. Ventriculo izquierdo tension arterial espana. Journal of Hypertension, 17, 1471-1480. doi:10.1097/00004872-199917100-00016

[15]   De Simone, G., Devereux, R.B., Daniels, S.R., Koren, M.J., Meyer, R.A. and Laragh, J.H. (1995) Effect of growth on variability of left ventricular mass: Assessment of allometric signals in adults and children and their capacity to predict cardiovascular risk. Journal of the American College of Cardiology, 25, 1056-1062. doi:10.1016/0735-1097(94)00540-7

[16]   Chen, X. and Wang, Y. (2008) Tracking of blood pressure from childhood to adulthood: A systematic review and meta-regression analysis. Circulation, 117, 3171-3180. doi:10.1161/CIRCU LATIONAHA.107.730366

[17]   Toschke, A.M., Kohl, L., Mansmann, U. and von Kries, R. (2010) Meta-analysis of blood pressure tracking from childhood to adulthood and implications for the design of intervention trials. Acta Paediatrica, 99, 24-29. doi:10.1111/j.1651-2227.2009.01544.x

[18]   Cook, N.R., Gillman, M.W., Rosner, B.A., Taylor, J.O. and Hennekens, C.H. (1997) Prediction of young adult blood pressure from childhood blood pressure, height, and weight. Journal of Clinical Epidemiology, 50, 571-579. doi:10.1016/S0895-4356(97)00046-2

[19]   Rosner, B., Cook, N., Portman, R., Daniels, S. and Falkner, B. (2008) Determination of blood pressure percentiles in normal-weight children: Some methodological issues. American Journal of Epidemiology, 167, 653-666. doi:10.1093/aje/kwm348

[20]   Fernandes, V.R., Edvardsen, T., Rosen, B.D., Carvalho, B., Campos, O., Cordeiro, M.A. et al. (2007) The influence of left ventricular size and global function on regional myocardial contraction and relaxation in an adult population free of cardiovascular disease: A tagged CMR study of the MESA cohort. Journal of Cardiovascular Magnetic Resonance, 9, 921-930. doi:10.1080/109 76640701693824

[21]   Muntner, P., He, J., Cutler, J.A., Wildman, R.P. and Whelton, P.K. (2004) Trends in blood pressure among children and adolescents. JAMA, 291, 2107-2013. doi:10.1001/jama.291.17.2107

[22]   Singh, G.K., Kogan, M.D. and Yu, S.M. (2009) Disparities in obesity and overweight prevalence among US immigrant children and adolescents by generational status. Journal of Community Health, 34, 271-281. doi:10.1007/s10900-009-9148-6

[23]   Din-Dzietham, R., Liu, Y., Bielo, M.V. and Shamsa, F. (2007) High blood pressure trends in children and adolescents in national surveys, 1963 to 2002. Circulation, 116, 1488-1496. doi:10.1161/CIRCULATIONAHA.106.683243

 
 
Top