BACKGROUND: Little is known of the effects of obesity, body size and body composition, and blood pressure (BP) in childhood on hypertension (HBP) and cardiac structure and function in adulthood due to the lack of long-term serial data on these parameters from childhood into adulthood. In the present study, we are poised to analyze these serial data from the Fels Longitudinal Study (FLS) to evaluate the extent to which body size during childhood determines HBP and cardiac structure and function in the same individuals in adulthood through mathematical modeling. METHODS: The data were from 412 males and 403 females in the FLS. Stature and BMI parameters were estimated using the Preeze-Baines model and the third degree polynomial model to describe the timing, velocity and duration of these measure from 2 to 25 years of age. The biological parameters were related to adult BP and echocardiographic (Echo-) measurements using Generalized Linear Models (GLM). RESULTS: The parameters of stature and BMI were compared between male and female to their overall goodness of fit and their capabilities to quantify the timing, rate of increase, and duration of the growth events. For stature parameters, the age at onset and peak velocity was earlier for girls; but the peak velocity was greater in boys; the velocity at onset was about the same for boys and girls; and stature at onset, peak velocity and adult was greater for boys. For BMI parameters, boys tended to have larger BMI values than girls, but the rates of change in BMI were almost the same; there was no sex difference in the timing of BMI rebound, but there was for the age of the peak velocity of BMI and maximum BMI, both of which were earlier in girls than in boys. CONCLUSIONS: Changes in childhood stature and BMI parameters were related to adult BP and Echo-measurements more so in females than males. Also the relationship of the adult BP measurements with corresponding childhood biological parameters was stronger than the relationship for adult Echo-measurements.

BACKGROUND: Several studies have demonstrated the association between the time to hypertension event and multiple baseline measurements for adults, yet other survival cardiovascular disease (CVD) outcomes such as high cholesterol and heart attack have been somewhat less considered. The Fels Longitudinal Study (FLS) provides us an opportunity to connect adult blood pressure (BP) at certain ages to the time to first CVD outcomes. The availability of long-term serial BP measurements from FLS also potentially allows us to evaluate if the trend of the measured BP biomarkers over time predicts survival outcomes in adulthood through statistical modeling. METHODS: When the reference standard is right-censored time-to-event (survival) outcome, the C index or concordance C, is commonly used as a summary measure of discrimination between a survival outcome that is possibly right censored and a predictive-score variable, say, a measured biomarker or a composite-score output from a statistical model that combines multiple biomarkers. When we have subjects longitudinally followed up, it is of primary interest to assess if some baseline measurements predict the time-to-event outcome. Specifically, in this study, systolic blood pressure, diastolic blood pressure, as well as their variation over time, are considered predictive biomarkers, and we assess their predictive ability for certain time-to-event outcomes in terms of the C index. RESULTS: There are a few summary C index differences that are statistically significant in predicting and discriminating certain CVD metric at certain age stage, though some of these differences are altered in the presence of medicine treatment and lifestyle characteristics. The variation of systolic BP measures over time has a significantly different predicting ability comparing with systolic BP measures at certain given time point, for predicting certain survival outcome such as high cholesterol level. CONCLUSIONS: Adult systolic and diastolic BP measurements may have significantly different ability in predicting time to first CVD events. The fluctuation of BP measurements over time may have better association than BP measurement at a single baseline time point, with the time to first CVD events.