High Variability in Metabolic Parameters May Predict All-Cause Mortality

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High variability of fasting blood glucose and total cholesterol levels, systolic blood pressure, and BMI may be an independent predictor of cardiovascular events.
High variability of fasting blood glucose and total cholesterol levels, systolic blood pressure, and BMI may be an independent predictor of cardiovascular events.

High variability in metabolic parameters is associated with a greater risk of all-cause mortality and cardiovascular events in both low-risk and diseased populations, according to a study published in Circulation.

The investigators of this nationwide population-based cohort study sought to determine whether the variability of metabolic parameters (fasting blood glucose levels, total cholesterol, systolic blood pressure, and body mass index) had an additive effect on cardiovascular outcomes and mortality risk in the general population.

The study investigators extracted data on 6,748,773 people from the Korean National Health Insurance System who underwent 3 or more health examinations between 2005 and 2012 and were followed through the end of 2015.

Participants were free of diabetes, hypertension, and dyslipidemia at baseline, and metabolic parameters were measured at the time of examination. Variability in fasting blood glucose, cholesterol, blood pressure, and body mass index was classified using several models: the coefficient of variations, standard deviation, variability independent of the mean, and average real variability.

Participants were scored according to the number of high-variability parameters. For instance, high variability in all metabolic parameters would receive a score of 4. A Cox proportional hazards model was used to adjust for effects of age, gender, smoking status, alcohol use, exercise, income, and baseline metabolic parameters.

Of the 6.75 million participants, 54,785 (0.8%) deaths were reported during a median 5.5-year follow-up period, including 22,498 (0.3%) cases of stroke and 21,452 (0.3%) cases of myocardial infarction.

Participants with high variability in all 4 metabolic parameters were associated with the highest baseline values for fasting blood glucose, total cholesterol, blood pressure, and body mass index. These participants also demonstrated the highest prevalence of metabolic syndrome.

Comparing the the highest quartile of variability vs the lowest quartile, the investigators observed a 20% increase in risk of all-cause mortality associated with fasting blood glucose variability (hazard ratio [HR], 1.2; 95% CI, 1.18-1.23), 31% risk associated with total cholesterol variability (HR, 1.31; 95% CI, 1.28-1.34), 19% risk associated with systolic blood pressure variability (HR, 1.19; 95% CI, 1.16-1.22), and 53% risk associated with body mass index variability (HR, 1.53; 95% CI, 1.50-1.57).

Using multivariable adjusted modeling to compare low and high variability groups, risk for all-cause mortality (HR, 2.27; 95% CI, 2.13-2.42), myocardial infarction (HR, 1.43; 95% CI, 1.25-1.64), and stroke (HR, 1.41; 95% CI, 1.25-1.60) were considered significant. Similar results were found in various sensitivity analyses and when modeling for variability using standard deviations, variability independent of the mean, and average real variability.

A limitation was the observational nature of the study. Changes in body weight could not be characterized as intentional or unintentional, which along with age may influence the parameter's effect on mortality risk. Variability associated with cardiovascular risk could be influenced by factors like diet and exercise that change over time. Finally, cohort selection based on the number of health examinations may introduce bias as men and employees were more likely to submit to annual health check-ups.

The investigators concluded the risk for all-cause mortality, myocardial infarction, and stroke increased significantly with the number of high-variability metabolic parameters, even in healthy, non-diseased populations.

The investigators suggest that variability in these metabolic parameters may be used as an independent predictor or prognostic marker of mortality and cardiovascular outcomes in a low-risk population.

Reference                    

Kim MK, Han K, Park YM, et al. Associations of variability in blood pressure, glucose, cholesterol concentrations, and body mass index with mortality and cardiovascular outcomes in the general population [published online October 1, 2018.] Circulation. doi:10.1161/CIRCULATIONAHA.118.034978

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