Risk Factors in Flux Increase CV Events and Death: More Evidence

A Korean study links visit-to-visit variability in metabolic risk factors to poor outcomes in the general population.

Risk Factors in Flux Increase CV Events and Death: More Evidence

Otherwise healthy people who have the biggest visit-to-visit swings in readings of various metabolic risk factors are at greater risk of dying and of having a cardiovascular event, a study of the Korean general population shows.

High variability in any of four risk factors—systolic blood pressure, fasting blood glucose, total cholesterol, and body mass index (BMI)—was associated with elevated risks of all-cause mortality, MI, and stroke through a median follow-up of 5.5 years, according to researchers led by Mee Kyoung Kim, MD, PhD (Yeouido St. Mary’s Hospital, Seoul, Korea).

And risks grew even larger when people had high levels of instability in multiple risk factors, the investigators report in a study published online earlier this week in Circulation.

Our results add evidence that high variability in metabolic parameters is associated with adverse health outcomes not only in diseased populations but also in relatively healthy populations, although the mechanism could be somewhat different,” Kim et al write. “These findings suggest that variability in metabolic parameters may be a prognostic surrogate marker for predicting mortality and cardiovascular outcomes.”

The authors additionally propose that interventions to reduce variability “should be another goal to prevent adverse health outcomes.”

But American Heart Association spokesperson Nieca Goldberg, MD (NYU Langone Medical Center, New York, NY), pointed out that “it’s not been shown that if you reduce variability it’ll improve outcomes.”

Nevertheless, she told TCTMD, doctors shouldn’t ignore volatility in risk factor measurements from visit to visit.

“This just adds to some of the other studies that we’ve had on weight cycling and blood pressure variability, telling us that in these situations when sometimes [a risk factor is] normal and sometimes it’s high, it’s not a benign condition. It can lead to hard events,” Goldberg said. “So I think that doctors need to pay attention not only to the patients who have persistently elevated risk factors like the ones discussed in the paper but to those in [whom readings] bump from normal to abnormal.”

Link Stronger for Mortality

Prior studies have shown that variability in blood pressure, fasting glucose, cholesterol, and body weight is associated with poor and sometimes fatal outcomes, but Kim et al set out to explore the issue looking at multiple risk factors at once in the general population.

They examined nationally representative data from the Korean National Health Insurance System on more than 6.7 million people who were free from diabetes, hypertension, or dyslipidemia at baseline and who underwent at least three health examinations between 2005 and 2012. The mean age of the cohort was about 43, and 57% were men.

For each of the four metabolic risk factors analyzed, people in the highest quartile of variability assessed using a coefficient of variation had elevated risks of all-cause mortality (by a relative 19% to 53%), MI (by a relative 7% to 16%), and stroke (by a relative 6% to 14%) during follow-up.

The highest risks were seen in participants who had high variability in multiple risk factors, “which suggests that the associations of variability of each parameter with the cardiovascular outcomes were additive,” Kim et al say. On multivariate adjustment, those with instability in four versus zero risk factors had significantly greater risks of all-cause mortality (HR 2.27; 95% CI 2.13-2.42), MI (HR 1.43; 95% CI 1.25-1.64), and stroke (HR 1.41; 95% CI 1.25-1.60).

That the relationship was stronger for mortality “implies that both cardiovascular and noncardiovascular causes of death might be affected by variability in metabolic parameters,” the authors write.

The study findings were consistent when different measures of variability were used and when analyses took into account people who developed diabetes, hypertension, or dyslipidemia during follow-up.

Mechanisms Unclear

Goldberg said that the mechanisms linking high visit-to-visit swings in risk factors to poor outcomes are not clear and that further studies are needed to see what kinds of changes occur when these fluctuations are happening. It would also be interesting to find out whether the findings of this study would be replicated in a US population, she added.

In the meantime, Goldberg said, “physicians have to be concerned about not only if a risk factor is high or low but also factor in whether or not there are variabilities in it that may adversely impact the patient’s health.”

Disclosures
  • The study was supported in part by a National Research Foundation of Korea grant funded by the Korean government.
  • Kim and Goldberg report no relevant conflicts of interest.

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