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Published on: May 17, 2016
Computer simulations of blood pressure tracking
1Department of Pharmacology, University of Otago, Dunedin, New Zealand.
Insights
Blood pressure (BP) tracking shows individuals
Area of Science:
- Cardiovascular epidemiology
- Biostatistics
- Longitudinal studies
Background:
- Blood pressure (BP) tends to maintain its relative position within a population distribution over time, a phenomenon known as tracking.
- While individuals with higher BP may be predisposed to future hypertension, this epidemiological link requires further investigation.
Purpose of the Study:
- To simulate BP tracking using empirical models.
- To assess the reliability of BP tracking criteria (correlation coefficient and quintile analysis).
- To examine the relationship between BP rank and the risk of hypertension or death.
Main Methods:
- Four empirical models were used to simulate BP tracking over time.
- Models were applied to computer-generated data (n=1500) and real BP data from a longitudinal survey.
- Simulations involved cumulative BP changes over iterative 'years'.
Main Results:
- The correlation coefficient (r) for paired initial and final BP decreased over time but remained statistically significant for up to 30 'years', although the values were low.
- Quintile analysis revealed frequent movement of BP values between distribution quintiles, indicating inefficient tracking.
- Computer-derived data showed the highest relative risk of death or hypertension in the topmost BP quintile.
Conclusions:
- Despite the complexity of BP regulation, simple models can adequately describe population BP trends.
- BP tracking, while present, is inefficient in predicting long-term outcomes.
- Individuals in the highest BP quintile face an elevated risk of hypertension and mortality.
Abstract:
Individual blood pressures (BP) tend to remain in the same relative position within a population BP distribution ('tracking'). Individuals in the upper range of the distribution may be predisposed to future hypertension, but this has not been proven epidemiologically. In this study tracking was simulated by computer using 4 simple empirical models to assess commonly reported criteria of BP tracking (correlation coefficient (r) and quintile analysis) and the relationship between the rank position of BP and the subsequent development of 'hypertension' or 'death'. The four models were applied to a population (n = 1500) of normally or log-normally distributed values corresponding to BPs with a mean of 75 and SD of 10 mmHg, also generated by the computer, and to real BP data from a longitudinal population survey. Each iteration of the model represented one year. Changes in BP at each iteration were cumulative. With both normally and log-normally distributed data, r for paired initial and final BPs decreased progressively but remained statistically significant for all models, up to 30 'years'. However, r was low. The patterns resembled that found in the longitudinal survey and data obtained by submitting the initial real BP data from the same survey to the simulations. In agreement with epidemiological studies, there was frequent movement of BP values between distribution quintiles, confirming that tracking is inefficient. In the computer-derived data, the relative risk of 'death' or 'hypertension' was greatest in the topmost quintile. The results suggest that though physiological BP control mechanisms are complex, adequate description of BP trends with time in a population is possible using simple models.(ABSTRACT TRUNCATED AT 250 WORDS)
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