An association of platelet indices with blood pressure in Beijing adults: Applying quadratic inference function for a longitudinal study

Medicine (Baltimore). 2016 Sep;95(39):e4964. doi: 10.1097/MD.0000000000004964.

Abstract

The quadratic inference function (QIF) method becomes more acceptable for correlated data because of its advantages over generalized estimating equations (GEE). This study aimed to evaluate the relationship between platelet indices and blood pressure using QIF method, which has not been studied extensively in real data settings.A population-based longitudinal study was conducted in Beijing from 2007 to 2012, and the median of follow-up was 6 years. A total of 6515 cases, who were aged between 20 and 65 years at baseline and underwent routine physical examinations every year from 3 Beijing hospitals were enrolled to explore the association between platelet indices and blood pressure by QIF method. The original continuous platelet indices were categorized into 4 levels (Q1-Q4) using the 3 quartiles of P25, P50, and P75 as a critical value. GEE was performed to make a comparison with QIF.After adjusting for age, usage of drugs, and other confounding factors, mean platelet volume was negatively associated with diastolic blood pressure (DBP) (Equation is included in full-text article.)in males and positively linked with systolic blood pressure (SBP) (Equation is included in full-text article.). Platelet distribution width was negatively associated with SBP (Equation is included in full-text article.). Blood platelet count was associated with DBP (Equation is included in full-text article.)in males.Adults in Beijing with prolonged exposure to extreme value of platelet indices have elevated risk for future hypertension and evidence suggesting using some platelet indices for early diagnosis of high blood pressure was provided.

MeSH terms

  • Adult
  • Aged
  • Beijing
  • Blood Platelets*
  • Blood Pressure*
  • Female
  • Follow-Up Studies
  • Humans
  • Hypertension / blood
  • Hypertension / etiology*
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Models, Statistical*
  • Physical Examination
  • Platelet Count / statistics & numerical data*
  • Risk Factors
  • Young Adult