Autonomic Imbalance as a Predictor of Metabolic Risks, Cardiovascular Disease, Diabetes, and Mortality

Abstract

Context: Identifying novel early predictors of metabolic disorders is essential to improving effective primary prevention.

Objectives: The objectives were to examine the contribution of two measures of autonomic imbalance, resting heart rate (RHR) and heart rate variability (HRV), on the development of five metabolic risk outcomes, and on cardiovascular disease, diabetes, and early mortality.

Design: This study was a secondary analysis of prospective data from Offspring Cohort participants (N = 1882) in the Framingham Heart Study (FHS).

Participants: Participants at FHS Exam 3 (1983-1987) with 1) age years 18 or older, and 2) data on RHR, HRV, and five measures of metabolic risk (blood pressure, fasting glucose, triglycerides, high-density lipoprotein [HDL] cholesterol, and body mass index [BMI]) at three follow-up visits over 12 years. We conducted a backward elimination variable selection procedure on a logistic regression model, using baseline RHR, HRV, age, sex, and smoking status to predict the odds of developing a specific metabolic risk.

Outcomes: Measures included hyperglycemia, high blood pressure, high triglycerides, low HDL cholesterol, and high BMI over 12 years; incident diabetes, cardiovascular disease, and early mortality over 20 years.

Results: RHR and HRV, along with sex, age, and smoking were significant predictors of high blood pressure, hyperglycemia, and a diagnosis of diabetes within 12 years. RHR and HRV also predicted the development of cardiovascular disease and early mortality for most of the sample.

Conclusions: In this community sample two measures of autonomic imbalance predicted multiple poor metabolic outcomes and mortality, making autonomic imbalance a potentially worthy target for intervention studies to reduce risks for cardiovascular disorders, diabetes, and early death.