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The effect of differences in measurement procedure on the comparability of blood pressure estimates in multi-centre

Matthias B Schulze1, Anja Kroke, Rodolfo Saracci

  • 1German Institute of Human Nutrition, Department of Epidemiology, Bergholz-Rehbruecke, Germany. mschulze@www.dife.de

Blood Pressure Monitoring
|June 6, 2002
PubMed

Insights

Standardizing blood pressure measurement procedures across epidemiological studies is crucial for accurate comparisons. Methodological variations can cause significant systematic differences, impacting hypertension prevalence data.

Area of Science:

  • Epidemiology
  • Cardiovascular Health
  • Medical Measurement

Background:

  • Accurate blood pressure measurement is vital for comparing hypertension prevalence and distribution across epidemiological studies.
  • Current international guidelines lack standardization, leading to methodological variations in blood pressure measurement.
  • These variations hinder valid comparisons between study populations.

Purpose of the Study:

  • To quantitatively define systematic differences in blood pressure measurements due to procedural variations.
  • To assess the impact of these variations on data from the European Prospective Investigation into Cancer and Nutrition (EPIC) study.

Main Methods:

  • Literature review to identify and quantify systematic differences.
  • Analysis of variations related to arm used, body position, measurement count, verbal communication, cuff size, and device.
  • Application of findings to inter-center differences within the EPIC study.

Main Results:

  • Procedural differences alone can lead to systematic blood pressure measurement variations of up to 10 mmHg between study centers.
  • Systematic error ranges could be estimated for most reviewed methodological differences.
  • Unaccounted factors like arm position and diurnal variations may further influence results.

Conclusions:

  • Standardized blood pressure measurement protocols are essential for epidemiological research.
  • Methodological variations introduce significant systematic error, potentially compromising data validity.
  • Partial correction for inter-center variations in studies like EPIC may be possible, but standardization is preferred.

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