Multivariate analysis of the relationship of seven variables to blood pressure: Findings of the Chicago Heart Association Detection Project in Industry, 1967-1972

Jeremiah Stamler*, Peter Rhomberg, James A. Schoenberger, Richard B. Shekelle, Alan Richard Dyer, Susan Shekelle, Rose Stamler, Julia Wannamaker

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

212 Scopus citations


1. 1. As in the preceding cross-sectional study [1], four multivariate statistical methods -partial correlation, multiple cross classification, multiple logistical regression, and multiple linear regression-were used to evaluate the relationship between seven variables and blood pressure in over 21,000 employed men and women, white and black, ages 25-44 and 45-64 surveyed in almost 100 Chicago companies and organizations. The analyses were carried out separately for eight age-sex-race groups. The seven variables were relative weight, resting heart rate, plasma glucose one hr after 50 g oral load, serum uric acid and cholesterol, current cigarette smoking habit, and age. 2. 2. Consistent with the findings of the preceding report, the first three of these variables-relative weight, heart rate, and plasma glucose-were independently related to blood pressure with a high degree of consistency, with p values for statistical significance ≤0.01 or ≤0.001 in the great majority of analyses. 3. 3. Serum uric acid-a variable not evaluated in the preceding report-was also independently related to blood pressure in a great majority of the analyses with p values of ≤0.01 or ≤0.001. 4. 4. The findings with respect to serum cholesterol and blood pressure were generally negative, except for white males, an intriguing finding in view of a similar result from the preceding study. 5. 5. No positive relationship was found between cigarette smoking and blood pressure. 6. 6. Even within the narrow age bands studied-ages 25-44 and 45-64-age was significantly related to blood pressure in a great majority of analyses (p values ≤0.01 or ≤0.001), independent of the six other variables. 7. 7. As in the preceding paper, when multivariate regression equations and their coefficients, computed from this experience of an entire age-sex-race group, were used to calculate an expectation of elevated blood pressure for each person, and then persons were ordered from low to high in expectation, a high proportion of all persons with recorded elevations of blood pressure were in the highest decile and quintile of expected prevalence-e.g. for persons age 25-44 in the four sex-race groups, from 45 to 56 per cent of observed cases with diastolic pressure ≥95 mm Hg. were in the highest quintile (20 per cent) of expected prevalence. The observed prevalence of elevated blood pressure was many times greater for the highest quintile of expected prevalence than for the lowest. A similar but less effective concentration of cases of elevated blood pressure was obtained with the multiple cross classification method, by dichotomizing five of the independent variables and identifying the substratum with any three, four or all five high.

Original languageEnglish (US)
Pages (from-to)527-548
Number of pages22
JournalJournal of Chronic Diseases
Issue number10
StatePublished - Nov 1975

ASJC Scopus subject areas

  • Epidemiology


Dive into the research topics of 'Multivariate analysis of the relationship of seven variables to blood pressure: Findings of the Chicago Heart Association Detection Project in Industry, 1967-1972'. Together they form a unique fingerprint.

Cite this