Relations of Demographic and Clinical Factors With Cardiovascular Autonomic Function in a Population-Based Study: An Assessment By Quantile Regression

Abstract

BACKGROUND

The relationships of many factors with cardiovascular autonomic function (CVAF) outcome parameters may not be uniform across the entire distribution of the outcome. We examined how demographic and clinical factors varied with different subgroups of CVAF parameters.

METHODS

Quantile regression was applied to a cross-sectional analysis of 4,167 adults (56% male; age range, 50–84 years) from 4 ethnic groups (3,419 New Zealand European, 303 Pacific, 227 Maori, and 218 South Asian) and without diagnosed cardiac arrhythmia. Pulse rate variability (root mean square of successive differences (RMSSD) and SD of pulse intervals) and baroreflex sensitivity were response variables. Independent variables were age, sex, ethnicity, brachial and aortic blood pressure (BP) variables, body mass index (BMI), and diabetes.

RESULTS

Ordinary linear regression showed that age, sex, Pacific and Maori ethnicity, BP variables, BMI, and diabetes were associated with CVAF parameters. But quantile regression revealed that, across CVAF percentiles, the slopes for these relationships: (i) varied by more than 10-fold in several cases and sometimes changed direction and (ii) noticeably differed in magnitude often (by >3–fold in several cases) compared to ordinary linear regression coefficients. For instance, age was inversely associated with RMSSD at the 10^th percentile of this parameter (β = −0.12 ms/year, 95% confidence interval = −0.18 to −0.09 ms/year) but had a positive relationship at the 90^th percentile (β = 3.17 ms/year, 95% confidence interval = 2.50 to 4.04 ms/year).

CONCLUSIONS

The relationships of demographic and clinical factors with CVAF parameters are, in many cases, not uniform. Quantile regression provides an improved assessment of these associations.

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