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Arterial pressures in a general practice.

T Wilson1, J D Merrett

  • 1Ddepartment of Medical Statistics, The Queen's University of Belfast.

Annals of Human Biology
|January 1, 1974
PubMed
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This study analyzed blood pressure in 5386 individuals, deriving age-specific prediction models. Family correlations for blood pressure were generally low, with some maternal influence observed.

Area of Science:

  • Cardiovascular Health
  • Human Genetics
  • Biostatistics

Background:

  • Blood pressure (BP) is a critical health indicator.
  • Understanding familial aggregation of BP is key to identifying genetic and environmental influences.
  • Previous studies have explored BP heritability with varying results.

Purpose of the Study:

  • To establish age- and sex-specific polynomial models for predicting systolic and diastolic blood pressure.
  • To investigate familial correlations (parent-child, sib-sib, husband-wife) for blood pressure.
  • To compare findings with existing literature and discuss potential biases.

Main Methods:

  • Recording systolic and diastolic blood pressure for 5386 general practice members.
  • Deriving polynomial regression models to predict BP and BP variance from age for each sex.

Related Experiment Videos

  • Calculating age-sex adjusted BP scores.
  • Analyzing parent-child, sib-sib, and husband-wife correlation coefficients.

    • Main Results:

    • Polynomial models were derived for predicting blood pressure and its variance based on age and sex.
    • Parent-child correlations ranged from -0.21 to 0.17, with maternal influence noted in sibships.
    • Sib-sib correlations (excluding twins) were generally below 0.13.
    • Husband-wife correlations mirrored parent-offspring correlations for couples aged 45+.

    Conclusions:

    • Familial aggregation of blood pressure in this cohort was relatively weak compared to other studies.
    • Maternal influence appears more significant than paternal or sibling influence on blood pressure.
    • The study highlights potential reasons for lower correlation coefficients and discusses possible biases in the estimates.