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Pulse pressure and coronary mortality in elderly men and women from general population

Journal of Human Hypertension volume 16, pages 611–620 (2002)Cite this article

Abstract

The aim of this work was to evaluate whether pulse pressure (PP) in elderly people is a better predictor of coronary mortality than systolic and diastolic blood pressure taken alone. For this aim, 3282 elderly subjects aged ⩾65 years were studied in a population-based frame. Blood pressure was repeatedly measured and averaged; historical data, anthropometrics, blood tests and 14-year coronary mortality were recorded. Statistics included analysis of covariance, Cox analysis and bivariate vectorial analysis. Coronary mortality in women was predicted by PP (1.01 excess risk/mm Hg PP) and was significantly higher in the 3rd than in the 1st tertile of PP (relative risk 2.90); neither systolic nor diastolic pressure taken alone influenced mortality. When systolic and diastolic pressures were both entered into a Cox model, the former had a positive and the latter a negative effect on survival, confirming a prognostic role of PP. For any given level of systolic pressure, mortality was inversely associated with diastolic pressure. Finally, the mean vector representing both systolic and diastolic pressures of non-surviving women was characterised by higher systolic and lower diastolic components than in non-surviving. No significant trend of mortality in relation to either systolic blood pressure or PP was observed in men. In conclusion, the combination of systolic and diastolic pressure called PP is an independent predictor of coronary mortality in elderly females, and a better predictor than systolic or diastolic pressure alone.

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Author information

Authors and Affiliations

  1. Department of Clinical and Experimental Medicine, University of Padova, Via Giustiniani, 2–35128, Padova, Italy

    E Casiglia, V Tikhonoff, A Mazza & A C Pessina

  2. Department of Medical and Surgical Sciences, University of Padova, Via Ospedale Civile, 105–35128, Padova, Italy

    A Piccoli

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  1. E Casiglia
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  2. V Tikhonoff
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  3. A Mazza
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  4. A Piccoli
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  5. A C Pessina
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Corresponding author

Correspondence to E Casiglia.

Appendix

Appendix

For readers less familiar with multivariate analysis, we report the basic definitions of multivariate confidence intervals as well as formulae for their calculations in the particular case of the assumption of the bivariate normal distribution for blood pressure vector (BP = DBP on x axis, SBP on y axis).

Confidence interval is the inferential statistical interval for a given parameter (such as a mean value) investigated. It is the region in the parameter space to which is assigned the probability 100(1−α)% (α is some fixed probability, typically 0.05) that the parameter vector lies within. The confidence interval of the mean of the univariate normal distribution is formed by two values (limits), while the interval of the mean vector of the multinormal distribution is an ellipsoid centred at the mean vector, which reduces to a hypersphere when the correlation coefficients between pairs of variables are zero.23

When the confidence ellipsoids of two mean vectors overlap, the null hypothesis of equality of the two mean vectors cannot be rejected with the significance level α (ie., non-significant Hotelling's T2 test). The confidence interval becomes smaller with increasing sample size, and in a very large population the confidence interval converges to the parameter vector (ie, the mean vector point). The 95% confidence ellipses of several BP mean (bivariate) vectors are depicted in Figure 4.

Calculations

Both approximate and exact methods are available for calculations of confidence ellipses of a bivariate normal distribution. Our modified version of the exact methods utilizes common statistics of the simple linear correlation analysis. Given n pairs of observations x and y, with standard deviations sx and sy and correlation coefficient r, and for a given probability level α (for example, α = 0.05), take the Snedecor's Fα value with 2 and n-2 degrees of freedom. The semi-axes L1 and L2 and the slopes b1 and b2 = −1/b1 of the axes of the 100(1−α) % confidence ellipses can be calculated using equations (1) and (2), respectively:

L1 L2 = √K ⋅ √(n − 1) (sx2 + sy2) + √[(n − 1)(sx2 + sy2)]2 − 4 (n − 1)2(1 − r2) sx2 sy2 (1)

where, K = F/ n · (n − 2) for confidence ellipses

b, −1/b = (sy2 − sx2) / 2 r sx sy ± √1 + [(sy2 − sx2) / 2 r sx sy]2 (2)

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Casiglia, E., Tikhonoff, V., Mazza, A. et al. Pulse pressure and coronary mortality in elderly men and women from general population. J Hum Hypertens 16, 611–620 (2002). https://doi.org/10.1038/sj.jhh.1001461

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