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Impact of Mean and Variability of High‐Density Lipoprotein‐Cholesterol on the Risk of Myocardial Infarction, Stroke, and Mortality in the General Population

Originally publishedhttps://doi.org/10.1161/JAHA.119.015493Journal of the American Heart Association. 2020;9:e015493

    Abstract

    Background

    A low level of high‐density lipoprotein‐cholesterol (HDL‐C) is a well‐known risk factor for cardiovascular events. Recent studies have also suggested that HDL‐C variability has a predictive role in patients with coronary artery disease. We investigated the combined effect of the mean and variability of HDL‐C on the risk of myocardial infarction (MI), stroke, and mortality in the general population.

    Methods and Results

    We selected 5 433 098 subjects in the Korean National Health Insurance System cohort who had no history of MI or stroke and who underwent ≥3 health examinations between 2009 and 2013. Visit‐to‐visit HDL‐C variability was calculated using the coefficient of variation, variability independent of the mean and average real variability. The low‐mean and high‐variability groups were defined as the lowest and highest quartiles of HDL‐C mean and variability, respectively. There were 27 605 cases of MI, 31 162 cases of stroke, and 50 959 deaths during the median follow‐up of 5.1±0.6 years. A lower mean or higher variability (coefficient of variation) of HDL‐C was associated with a higher risk of adverse outcomes, and the 2 measures had an additive effect. In the multivariable‐adjusted model, the hazard ratios (95% CIs) of the low‐mean/high‐variability group compared with the high‐mean/low‐variability group were 1.47 (1.41–1.54) for MI, 1.23 (1.18–1.28) for stroke, and 1.41 (1.36–1.45) for all‐cause mortality. Results were consistent when variability was modeled using variability independent of the mean or average real variability, and in various sensitivity and subgroup analyses.

    Conclusions

    Low mean and high variability of HDL‐C is associated with an increased risk of MI, stroke, and mortality.

    Clinical Perspective

    What Is New?

    • Low mean high‐density lipoprotein‐cholesterol (HDL‐C) levels and high HDL‐C variability was associated with a higher risk for myocardial infarction, stroke, and all‐cause mortality.

    • Low mean and high variability of HDL‐C had additive associations with the risk of cardiovascular outcomes and mortality in the general population.

    What Are the Clinical Implications?

    • Variability in HDL‐C may have a role in predicting cardiovascular outcomes and mortality.

    • Treatment strategies to reduce fluctuations in HDL‐C might be another goal to prevent adverse health outcomes.

    Nonstandard Abbreviations and Acronyms

    ARV average real variability

    BMI body mass index

    CV coefficient of variation

    CVD cardiovascular disease

    DM diabetes mellitus

    HDL‐C high‐density lipoprotein‐cholesterol

    HR hazard ratio

    ICD‐10International Classification of Disease, Tenth Revision

    LDL‐C low‐density lipoprotein‐cholesterol

    MI myocardial infarction

    VIM variability independent of the mean

    Introduction

    Dyslipidemia is recognized as a causative determinant of atherosclerosis. Epidemiological studies have provided evidence that low concentrations of high‐density lipoprotein‐cholesterol (HDL‐C) are associated with an increase in cardiovascular disease (CVD) and mortality.1 Although there are several well‐established risk factors for CVD, other risk factors require further clarification. Recently, a relationship has been identified between visit‐to‐visit variability in cholesterol levels and various diseases, suggesting that lipid variability is a previously unrecognized residual risk factor for various health outcomes.2, 3, 4, 5, 6 Several studies have demonstrated that the variability of low‐density lipoprotein‐cholesterol (LDL‐C) and HDL‐C is associated with a higher risk of developing CVD or of death in subjects with previous coronary artery disease.2, 3, 4, 5 Because most patients included in these studies were on statin therapy, incomplete adherence to treatment might have resulted in higher variability in cholesterol. However, because statins have a comparatively small long‐term effect on HDL‐C, medication noncompliance is a poor explanation for HDL‐C variability.3 Notably, it has also been reported that variability in one lipid measurement, such as LDL‐C, triglycerides, or HDL‐C, does not always correlate well with variability in the others. In patients with ST‐segment–elevation myocardial infarction (MI), the cholesterol efflux and anti‐inflammatory properties of HDL‐C were significantly dysfunctional.7 Therefore, it may be necessary to investigate the association between HDL‐C variability and CVD events in the general population, not in diseased patients. Because the effect of HDL‐C variability alone and in combination with absolute HDL‐C levels on the risk of CVD has never been studied, we performed this analysis using a nationwide population‐based cohort of >5 million Korean people.

    Methods

    All supporting data are available within the article and its online supplementary file.

    Data Source

    The National Health Insurance System of Korea is a single‐payer program that pays costs on the basis of the billing records of healthcare providers. Because membership of the National Health Insurance System is mandatory for all residents in Korea, its 3 main healthcare programs, National Health Insurance, Medical Aid, and Long‐Term Care Insurance, cover 100% of the >50 million people in Korea.8, 9 The National Health Insurance System includes an eligibility database (age, sex, socioeconomic variables, type of eligibility, etc), a medical treatment database (based on the accounts submitted by medical service providers for medical expenses), a health examination database (results of general health examinations and questionnaires on lifestyle and behavior), a medical care institution database (types of medical care institutions, location, equipment, and number of physicians), and information about death. Enrollees in the National Health Insurance Corporation are recommended to undergo standardized health examinations every 1 or 2 years.

    Study Population

    In our study, we screened 19 459 018 people who had undergone a health examination between 2012 and 2013 (index year). We selected 5 632 394 subjects who had undergone a health examination in the index year and ≥2 health examinations in the preceding 3 years. We excluded 435 subjects <20 years old, 34 810 subjects with missing data, and 164 051 subjects with a history of MI [International Classification of Disease, Tenth Revision (ICD‐10) codes: I21, I22] or stroke (ICD‐10 codes: I63, I64) before the index year. Finally, 5 433 098 subjects remained in our study (Figure S1). This study was approved by the Institutional Review Board of Seoul St. Mary's Hospital (No. KC18EESI0429). Anonymous and deidentified information was used for analysis, and therefore informed consent was not required.

    Measurements and Definitions

    Body mass index (BMI), a subject's body weight (kg) divided by the square of their height (m2), was measured, and obesity was defined as a BMI ≥25 kg/m2.10 Regular exercise was defined as performing >20 minutes of strenuous physical activity at least 3 times per week or >30 minutes of moderate physical activity at least 5 times per week. Household income level was dichotomized at the lowest 25% on the basis of the monthly contributions to National Health Insurance Corporation.11 We defined the presence of diabetes mellitus (DM) according to the following criteria: (1) at least 1 claim per year under ICD‐10 codes E10 through E14 and at least 1 claim per year for the prescription of antidiabetic medication, or (2) fasting glucose level ≥126 mg/dL. Hypertension was defined as (1) the presence of at least 1 claim per year under ICD‐10 codes I10 or I11 and at least 1 claim per year for the prescription of antihypertensive agents, or (2) systolic/diastolic blood pressure ≥ 140/90 mm Hg. Dyslipidemia was defined as (1) the presence of at least one claim per year under ICD‐10 code E78 and at least 1 claim per year for the prescription of a lipid‐lowering agent, or (2) total cholesterol ≥240 mg/dL.

    Definition of HDL‐C Variability

    HDL‐C variability was defined as the variability in HDL‐C values measured at different health examinations. Three indices of HDL‐C variability were used: (1) coefficient of variation (CV), (2) variability independent of the mean (VIM), and (3) average real variability (ARV). CV was calculated as 100%×[ SD/mean]. VIM was calculated as 100%×(SD/meanβ), where β is the regression coefficient, on the basis of the natural logarithm of the SD divided by the natural logarithm of the mean.12, 13 ARV was obtained by calculating the average of the absolute differences between consecutive HDL‐C measurements.14 The number of HDL‐C measurements per subject ranged from 3 (n=2 862 984, 52.7%) to 4 (n=2 570 114, 47.3%).

    Definition of Low‐Mean HDL‐C and High HDL‐C Variability

    Because HDL‐C levels differ between men and women, sex‐specific cutoff values were used (Table S1). The low‐mean HDL‐C group was defined as subjects in the lowest quartile (quartile 1) range of mean HDL‐C; the other 3 quartile groups (quartiles 2–4) were defined as having high‐mean HDL‐C. The high‐variability group was defined as those subjects in the highest quartile (quartile 4) range of HDL‐C variability; the other 3 quartile groups (quartiles 1–3) were defined as having low variability.

    Study Outcomes and Follow‐Up

    The end points of this study were newly diagnosed MI, stroke, or death. MI was defined as the recording of ICD‐10 codes I21 or I22 during hospitalization. Stroke was defined as the recording of ICD‐10 codes I63 or I64 during hospitalization with claims for brain magnetic resonance imaging or brain computerized tomography. Subjects without MI or stroke during their follow‐up period were considered to have completed the study at the date of their death or at the end of follow‐up (December 31, 2017), whichever came first. The median follow‐up period was 5.1±0.6 years.

    Statistical Analysis

    Baseline characteristics are presented as the mean±SD, median (25–75%), or n (%). Participants were classified into 4 groups according to quartiles of the mean and variability (CV) of HDL‐C. The incidence rate of outcomes was calculated by dividing the number of incident cases by the total follow‐up duration (person‐years). Hazard ratios (HRs) and 95% CI values for MI, stroke, and all‐cause mortality were analyzed using the Cox proportional hazards model. HR (95% CI) of the highest quartile (quartile 4) of HDL‐C variability was compared with that of the lower 3 quartiles (quartiles 1–3) as a reference group. HR (95% CI) of the lowest quartile (quartile 1) of mean HDL‐C was compared with that of the higher 3 quartiles (quartiles 2–4) as a reference group. The proportional hazards assumption was evaluated by the Schoenfeld residuals test using the logarithm of the cumulative hazards function based on Kaplan–Meier estimates for the quartile groups of mean or variability of HDL‐C, or groups based on the combination of mean and variability. There was no significant departure from proportionality of hazards over time. A multivariable‐adjusted proportional hazards model was applied adjusting for age, sex, BMI, alcohol drinking, smoking, regular exercise, income status, DM, hypertension, and use of lipid‐lowering agent. Sensitivity analysis was performed by excluding subjects with DM, hypertension, and dyslipidemia because the presence of these conditions or consumption of related medications could influence the HDL‐C level or its variability. Sensitivity analyses were also performed by excluding subjects with the occurrence of outcomes within 2 years of follow‐up, to account for the possibility of reverse causation. The potential effect of modification by age, sex, obesity, DM, hypertension, malignancy, and use of lipid‐lowering agents was evaluated through stratified analysis and interaction testing using a likelihood‐ratio test. Statistical analyses were performed using SAS version 9.4 (SAS Institute Inc, Cary, NC), and P<0.05 was considered to indicate significance.

    Results

    Baseline Characteristics of the Study Population

    The baseline characteristics of subjects classified according to the mean and variability (CV) of HDL‐C are described in Table 1. Subjects were classified into 4 groups: high‐mean/low‐variability group, high‐mean/high‐variability group, low‐mean/low‐variability group, and low‐mean/high‐variability group. Subjects in the low‐mean/high‐variability group were older and more likely to be female, had a higher prevalence of DM and hypertension, and were more likely to be taking a lipid‐lowering agent and to have lower income. In this group, total cholesterol and LDL‐C levels were lower, whereas triglyceride levels were higher than in the other groups. The P values for trend were <0.001 for all parameters because of the large size of the study population. Because abnormalities in HDL‐C levels are frequently accompanied by obesity or metabolic syndrome, we performed correlation analysis between HDL‐C variability and variabilities in other metabolic parameters. The correlations between the CV of HDL‐C and the CV of triglycerides (r=0.12), the CV of LDL‐C (r=0.19), the CV of fasting blood glucose (r=0.08), and the CV of BMI (r=0.06) were not robust (Table S2).

    Table 1. Baseline Characteristics of Subjects According to the Mean and Variability (CV) of HDL‐C

    High Mean/Low ariability (n=3 057 031)High Mean/High Variability (n=1 024 571)Low Mean/Low Variability (n=1 017 774)Low Mean/High Variability (n=333 722)
    Age, y43.5±11.745.7±12.546.1±11.648.3±12.5
    Sex, male2 000 432 (65.4)687 518 (67.1)682 528 (67.1)206 829 (62.0)
    Body mass index, kg/m223.4±3.223.6±3.224.9±3.224.8±3.2
    Systolic BP, mm Hg120.7±13.7122.0±14.1122.4±13.7122.9±14.0
    Diastolic BP, mm Hg75.8±9.676.6±9.776.8±9.576.9±9.6
    Fasting glucose, mg/dL95.3±18.897.0±21.999.0±23.7100.0±25.6
    Total cholesterol, mg/dL194.8±30.1194.6±31.1190.2±30.8188.2±30.9
    Triglyceride, mg/dL97 (67–141)116 (79–175)141 (97–205)150 (101–222)
    LDL‐C, mg/dL113.7±33.2112.1±35.7115.6±35.6112.6±38.0
    HDL‐C, mg/dL59.4 ±11.459.9±21.742.1±5.942.3±9.5
    HDL‐C mean, mg/dL59.4±10.160.3±14.742.1±4.842.2±5.0
    HDL‐C CV, %9.0±3.722.9±12.49.0±3.721.9±6.6
    HDL‐C VIM, %4.6±2.311.3±4.48.3±3.920.4±19.0
    HDL‐C ARV, mg/dL6.5±3.417.2±20.74.6±2.411.1±4.5
    Current smoker882 741 (28.9)312 832 (30.5)329 851 (32.4)100 773 (30.2)
    Alcohol drinking261 217 (8.5)100 534 (9.8)54 903 (5.4)19 317 (5.8)
    Regular exercise654 530 (21.4)224 762 (21.9)198 270 (19.5)66 041 (19.8)
    Income (lower 25%)496 581 (16.2)204 074 (19.9)175 051 (17.2)72 788 (21.8)
    Diabetes mellitus166 191 (5.4)80 305 (7.8)103 606 (10.2)41 857 (12.5)
    Hypertension548 832 (18.0)236 507 (23.1)248 501 (24.4)95 709 (28.7)
    On lipid‐lowering agent225 573 (7.4)102 537 (10.0)108 733 (10.7)44 963 (13.5)
    Any malignancy45 665 (1.5)18 739 (1.8)19 509 (1.9)7904 (2.4)

    Data are expressed as the mean±SD, median (25–75%), or n (%). ARV indicates average real variability; BP, blood pressure; CV, coefficient of variation; HDL‐C, high‐density lipoprotein cholesterol; LDL‐C, low‐density lipoprotein cholesterol; and VIM, variability independent of the mean.

    Risk of Myocardial Infarction According to the Mean and Variability of HDL‐C

    There were 27 605 cases of new‐onset MI (0.51%) during the follow‐up period. When the subjects were categorized into quartile groups, both low mean and high variability of HDL‐C were associated with a higher incidence rate of MI than for higher‐mean and lower‐variability groups (Figure 1A). After adjusting for age, sex, BMI, alcohol drinking, smoking, regular exercise, income status, DM, hypertension, and lipid‐lowering medication, the risk of MI was 33% higher in the low‐mean group and 13% higher in the high‐variability group, compared with the high‐mean or low‐variability groups, respectively. The HR (95% CI) for MI was 1.16 (1.13–1.20) in the high‐mean/high‐variability group, 1.36 (1.32–1.40) in the low‐mean/low‐variability group, and 1.47 (1.41–1.54) in the low‐mean/high‐variability group compared with that in the high‐mean/low‐variability group. An additive effect of the mean and variability of HDL‐C on the risk of MI was identified (Table 2).

    Figure 1.

    Figure 1. Incidence probability of myocardial infarction (A), stroke (B), and all‐cause mortality (C) according to the mean, variability, and combination of mean and variability of HDL‐C.

    HDL‐C indicates high‐density lipoprotein cholesterol.

    Table 2. Risk of MI, Stroke, and Mortality According to the Mean and Variability (CV) of HDL‐Cholesterol

    MIStrokeMortality
    Events (n)Incidence rateaHR (95% CI)Events (n)Incidence rateaHR (95% CI)Events (n)Incidence rateaHR (95% CI)
    Mean
    High mean (Q2–4)17 7840.851 (ref.)20 9901.001 (ref.)36 1951.731 (ref.)
    Low mean (Q1)98211.421.33 (1.29, 1.36)10 1721.471.13 (1.10, 1.16)14 7642.131.07 (1.05, 1.09)
    Variability
    Low variability (Q1–3)18 8550.901 (ref.)20 8621.001 (ref.)32 2731.541 (ref.)
    High variability (Q4)87501.261.13 (1.10, 1.16)10 3001.491.11 (1.09, 1.14)18 6862.691.29 (1.27, 1.31)
    Combination
    High mean/low variability11 9500.761 (ref.)13 8250.881 (ref.)22 7871.451 (ref.)
    High mean/high variability58341.121.16 (1.13, 1.20)71651.371.15 (1.11, 1.18)13 4082.561.28 (1.26, 1.31)
    Low mean/low variability69051.321.36 (1.32, 1.40)70371.351.16 (1.13, 1.20)94861.811.07 (1.04, 1.10)
    Low mean/high variability29161.711.47 (1.41, 1.54)31351.841.23 (1.18, 1.28)52783.091.41 (1.36, 1.45)

    Adjusted for age, sex, body mass index, alcohol drinking, smoking, regular exercise, income status, diabetes mellitus, hypertension, and use of lipid lowering agent. CV indicates coefficient of variation; HR, hazard ratio; and MI, myocardial infarction.

    aPer 1000 person‐years.

    Risk of Stroke According to the Mean and Variability of HDL‐C

    There were 31 162 cases of new‐onset stroke (0.57%) during the follow‐up period. Similar to MI, both low mean and high variability of HDL‐C were associated with a higher incidence rate of stroke than for higher‐mean and lower‐variability groups, respectively (Figure 1B). After multivariable adjustment, the risk of stroke was 13% higher in the low‐mean group and 11% higher in the high‐variability group than for the high‐mean or low‐variability groups, respectively. The HRs (95% CIs) for stroke were 1.15 (1.11–1.18) in the high‐mean/high‐variability group, 1.16 (1.13–1.20) in the low‐mean/low‐variability group, and 1.23 (1.18–1.28) in the low‐mean/high‐variability group than for that in the high‐mean/low‐variability group (Table 2). Again, this suggests an additive effect of mean and variability of HDL‐C on the risk of stroke.

    Risk of All‐Cause Mortality According to the Mean and Variability of HDL‐C

    There were 50 959 deaths (0.94%) during the follow‐up period. The lowest‐mean and highest‐variability quartile groups showed the highest incidence rate of mortality (Figure 1C). After multivariable adjustment, the risk of all‐cause mortality was 7% higher in the low‐mean group and 29% higher in the high‐variability group than that in the high‐mean or low‐variability groups, respectively. The HRs (95% CIs) for mortality were 1.28 (1.26–1.31) in the high‐mean/high‐variability group, 1.07 (1.04–1.10) in the low‐mean/low‐variability group, and 1.41 (1.36–1.45) in the low‐mean/high‐variability group compared with that in the high‐mean/low‐variability group (Table 2).

    Sensitivity Analysis

    The results were largely consistent when further adjusting for triglyceride levels or triglyceride variability in addition to the original model (Table S3). The results were also similar when the variability of HDL‐C was determined using VIM or ARV (Tables S4 and S5). After excluding subjects with DM, hypertension, and dyslipidemia, the respective and combined effects of mean and variability of HDL‐C on MI, stroke, and mortality were similar to those in the whole cohort (Table 3). Excluding subjects with the occurrence of outcomes within 2 years of follow‐up did not change the association between mean and variability of HDL‐C and outcomes (Table S6). Similar results were noted when performing an analysis with subjects who had participated in 4 yearly health examinations (Table S7).

    Table 3. Risk of MI, Stroke and Mortality According to the Mean and Variability (CV) of HDL‐C (Sensitivity Analysis Excluding Subjects With Diabetes Mellitus, Hypertension, and Dyslipidemia)

    MIStrokeMortality
    Events (n)Incidence rateaHR (95% CI)Events (n)Incidence rateaHR (95% CI)Events (n)Incidence rateaHR (95% CI)
    Mean
    High mean (Q2–4)83680.531 (ref.)83670.531 (ref.)16 9111.071 (ref.)
    Low mean (Q1)39110.851.31 (1.26, 1.37)33870.741.13 (1.08, 1.18)56411.221.06 (1.03, 1.10)
    Variability
    Low variability (Q1–3)87990.561 (ref.)82870.531 (ref.)15 1000.971 (ref.)
    High variability (Q4)34800.731.13 (1.09, 1.18)34670.731.13 (1.08, 1.17)74521.571.32 (1.28, 1.36)
    Combination
    High mean/low variability59340.491 (ref.)58300.481 (ref.)11 2610.931 (ref.)
    High mean/high variability24340.661.15 (1.10, 1.21)25370.691.16 (1.10, 1.21)56501.531.32 (1.28, 1.37)
    Low mean/low variability28650.811.34 (1.28, 1.40)24570.691.16 (1.11, 1.22)38391.081.07 (1.03, 1.11)
    Low mean/high variability10460.991.47 (1.37, 1.57)9300.881.23 (1.14, 1.31)18021.691.41 (1.34, 1.49)

    Adjusted for age, sex, body mass index, alcohol drinking, smoking, regular exercise and income status. CV indicates coefficient of variation; HDL‐C, high‐density lipoprotein cholesterol; HR, hazard ratio; and MI, myocardial infarction.

    aPer 1000 person‐years.

    Subgroup Analysis

    We also performed stratified analysis by age, sex, presence or absence of obesity, DM, hypertension, malignancy, and use of lipid‐lowering agents; P values for interaction are shown in Figure 2. The significant associations of a low mean and high variability of HDL‐C with the risk of MI, stroke, and all‐cause mortality were present in almost all subgroups. The association between high variability of HDL‐C and outcomes was stronger in nonobese subjects and nonusers of lipid‐lowering medications.

    Figure 2.

    Figure 2. Hazard ratios and 95% CIs for myocardial infarction, stroke, and all‐cause mortality in the lowest quartile vs the 3 higher quartiles of mean HDL‐C (A) and the highest quartile vs the 3 lower quartiles of HDL‐C variability (B) in various subgroups. Adjusted for age, sex, body mass index, alcohol drinking, smoking, regular exercise, income status, diabetes mellitus, hypertension, and use of lipid‐lowering agents.

    P values for interaction were analyzed using a likelihood‐ratio test. HDL‐C indicates high‐density lipoprotein cholesterol.

    Discussion

    In this nationwide population‐based cohort study, we demonstrated that low mean and high variability of HDL‐C are associated with the risk of all‐cause mortality, MI, and stroke during a 5‐year follow‐up period. This is the first study to clarify the relationship between HDL‐C variability and cardiovascular outcomes in the general population. We also found that the mean and variability of HDL‐C had an additive effect on the risks of all‐cause mortality, MI, and stroke.

    We previously reported that high variability in total cholesterol levels was an independent predictor of adverse cardiovascular events among the general population.6 Despite the fact that lipid parameters are closely related, the correlations between the variabilities of lipid parameters were not robust. The present study suggests that variability in HDL‐C, a widely measured cholesterol fraction, is also an indicator of a high risk of developing CVD and of all‐cause mortality. Environmental factors, including diet, smoking, alcohol intake, obesity, and physical activity, can affect HDL‐C levels.15, 16 Changes between successive evaluations (lack of physical activity, lifestyle changes, or preclinical illness) could have an impact on an individual's HDL‐C and be causally associated with adverse outcomes and HDL‐C variability. A low HDL‐C is often accompanied by obesity and elevated triglyceride levels. It is possible that BMI and triglyceride variability over time are responsible for the related variability in HDL‐C. However, we performed correlation analysis and found that the correlation coefficient between HDL‐C variability and triglycerides (r=0.12) or BMI (r=0.06) variability was relatively low. We found that the associations between HDL‐C variability and adverse outcomes persisted after adjustment for variables including alcohol drinking, smoking, physical activity, and triglyceride levels or triglyceride variability. There may also be other mechanisms that can explain the link between HDL‐C variability and adverse health outcomes.

    In terms of the risk of MI, the mean HDL‐C level seems to be more important than its variability, although high variability of HDL‐C may play a bigger role in the risk of all‐cause mortality. The multivariable adjusted HRs of the low‐mean group compared with the high‐mean group were 1.33 (1.29–1.36) for MI and 1.07 (1.05–1.09) for all‐cause mortality. The multivariable adjusted HRs of the high‐variability group compared with the low‐variability group were 1.13 (1.10–1.16) for MI and 1.29 (1.27–1.31) for all‐cause mortality. HDL‐C has been shown to have a variety of beneficial protective actions on blood vessels, and it has long been considered “good cholesterol.”1 It is well accepted that high HDL‐C levels are associated with reduced CVD and mortality, although several recent studies raised the question that extremely high HDL‐C levels might be paradoxically associated with high mortality.17, 18, 19, 20 The exact mechanism for the relationship between the high variability of HDL‐C and an increased risk of CVDs is unknown. However, high HDL‐C variability could cause plaque instability by impairing cholesterol efflux from peripheral tissues and macrophages.5 The group with a consistently high HDL‐C, that is, the high‐mean and low‐variability group, could represent a healthy population. Higher variabilities of multiple biological parameters might be observed in patients with systemic conditions and generalized frailty.21, 22 Therefore, it is possible that high cholesterol variability is an epiphenomenon of other systemic conditions that increase cardiovascular or mortality risk. Of note, on the basis of the associations between HDL‐C levels and noncardiovascular outcomes, HDL‐C is now considered to be more complicated than just being a cardiovascular risk factor.20 A previous study reported that HDL‐C variability also predicted the progression of diabetic nephropathy, including the risk of developing albuminuria.23 It was recently reported that higher HDL‐C variability is associated with incident end‐stage renal disease in the general population.24 Our results clearly indicated that subjects with a high and stable HDL‐C are least likely to develop CVD or to die, and that subjects with a low mean and high variability in HDL‐C had the highest risk of CVD and death. This suggests the important effects of both the absolute value and the variability of HDL‐C in terms of the risk of CVD and death in the general population.

    In a study of 130 patients with ST‐segment–elevation MI, both LDL‐C and HDL‐C variability were associated with increased risk for major adverse cardiac events. Each 0.01 increase in VIM of LDL‐C and HDL‐C increased the risk of major adverse cardiac events by 3.5% and 6.8%, respectively.4 Another study showed that variability in atherogenic lipoprotein levels, such as the SD of LDL‐C, was significantly associated with increased risk of coronary atheroma progression and clinical outcomes.25 However, in contrast with our findings, that study did not find any relationship between HDL‐C variability and clinical outcomes. There are several possible explanations for these different results. For example, the study populations differed (Asian versus Western population, general population versus coronary disease population). Other studies also used the SD as a variability index. However, it is known that SD is positively correlated with the mean value, and in the case of HDL‐C, mean value and variability might affect outcomes in opposite directions. Therefore, when HDL‐C variability was assessed by SD, the effect of HDL‐C variability on outcomes might disappear. The VIM and CV are more weakly correlated with the mean value than is SD.26 We compared CV, VIM, and ARV as indices of HDL‐C variability, and the results were largely consistent.

    The strengths of our study include the ability to account for multiple possible confounding factors, including lifestyle factors, metabolic factors, and previous history of disease. This is the first study to demonstrate the combined effects of mean HDL‐C and its variability on the risk of CVD and all‐cause mortality. Moreover, this study population was not composed of diseased patients but was a relatively healthy population. Our study has the strength that our findings should be applicable to many people. Tsalamandris et al27 reported that patients with DM had higher HDL‐C variability than subjects without DM. Because comorbidities and/or treatments might modulate the changes in lipid parameters during the follow‐up, we performed a sensitivity analysis after excluding those with DM, hypertension, or dyslipidemia, which also revealed similar results.

    This study did have some limitations. First, excluding participants with fewer than 3 health examinations might have been a source of selection bias. Second, the findings cannot be extrapolated to people of different ethnicities because only the Korean population was included. Third, this was not a prospective study, and the possibility of reverse causation should be considered. To overcome this issue, we performed sensitivity analyses excluding subjects with the occurrence of outcomes within 2 years of follow‐up and showed that the results were consistent. Although epidemiologic studies reported an association between low HDL‐C and adverse health outcomes, there are genetic studies and randomized clinical trials raising the issue of causality. Neither niacin, fibrate, nor cholesterylester transfer protein inhibitors, agents for increasing HDL‐C levels, reduced all‐cause mortality, coronary artery disease, or stroke in patients treated with statins.28 Lifelong low HDL‐C levels attributable to heterozygosity for loss‐of‐function mutations in ABCA1 were not associated with an increased risk of CVD.29 This finding may be related to low variability of HDL‐C attributable to lifelong low HDL‐C levels. Future studies should examine whether reducing the variability of HDL‐C decreases adverse outcomes and how this reflects the function of HDL.

    Conclusions

    In this nationwide population‐based cohort study, we observed that low mean and high variability of HDL‐C could increase the risk of all‐cause mortality, MI, and stroke. Furthermore, we demonstrated an additive effect of mean and variability of HDL‐C on CVD outcomes. The data were consistent whether CV, VIM, or ARV was used as an index of variability and in various sensitivity and subgroup analyses.

    Disclosures

    None.

    Acknowledgments

    This study was performed using the database from the National Health Insurance System (NHIS‐2018‐1‐471), and the results do not necessarily represent the opinion of the National Health Insurance Corporation.

    Footnotes

    * Correspondence to: Mee Kyoung Kim, MD, PhD, Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, #10 63‐ro, Yeongdeungpo‐gu, Seoul 07345, Korea. E‐mail:
    and
    Seung‐Hwan Lee, MD, PhD, Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, #222 Banpo‐daero, Seocho‐gu, Seoul 06591, Korea. E‐mail:

    Dr Byung‐Hun Han and Dr Kyungdo Han contributed equally to this work.

    For Disclosures, see page 9.

    References

    • 1 Rosenson RS, Brewer HB, Ansell B, Barter P, Chapman MJ, Heinecke JW, Kontush A, Tall AR, Webb NR. Translation of high‐density lipoprotein function into clinical practice: current prospects and future challenges. Circulation. 2013; 128:1256–1267.LinkGoogle Scholar
    • 2 Bangalore S, Breazna A, DeMicco DA, Wun CC, Messerli FH; TNT Steering Committee and Investigators . Visit‐to‐visit low‐density lipoprotein cholesterol variability and risk of cardiovascular outcomes: insights from the TNT trial. J Am Coll Cardiol. 2015; 65:1539–1548.CrossrefMedlineGoogle Scholar
    • 3 Waters DD, Bangalore S, Fayyad R, DeMicco DA, Laskey R, Melamed S, Barter PJ. Visit‐to‐visit variability of lipid measurements as predictors of cardiovascular events. J Clin Lipidol. 2018; 12:356–366.CrossrefMedlineGoogle Scholar
    • 4 Boey E, Gay GM, Poh KK, Yeo TC, Tan HC, Lee CH. Visit‐to‐visit variability in LDL‐ and HDL‐cholesterol is associated with adverse events after ST‐segment elevation myocardial infarction: a 5‐year follow‐up study. Atherosclerosis. 2016; 244:86–92.CrossrefMedlineGoogle Scholar
    • 5 Lee EY, Yang Y, Kim HS, Cho JH, Yoon KH, Chung WS, Lee SH, Chang K. Effect of visit‐to‐visit LDL‐, HDL‐, and non‐HDL‐cholesterol variability on mortality and cardiovascular outcomes after percutaneous coronary intervention. Atherosclerosis. 2018; 279:1–9.CrossrefMedlineGoogle Scholar
    • 6 Kim MK, Han K, Kim HS, Park YM, Kwon HS, Yoon KH, Lee SH. Cholesterol variability and the risk of mortality, myocardial infarction, and stroke: a nationwide population‐based study. Eur Heart J. 2017; 38:3560–3566.CrossrefMedlineGoogle Scholar
    • 7 Annema W, Willemsen HM, de Boer JF, Dikkers A, van der Giet M, Nieuwland W, Muller Kobold AC, van Pelt LJ, Slart RH, Van der Horst IC, et al. HDL function is impaired in acute myocardial infarction independent of plasma HDL cholesterol levels. J Clin Lipidol. 2016; 10:1318–1328.CrossrefMedlineGoogle Scholar
    • 8 Ko SH, Han K, Lee YH, Noh J, Park CY, Kim DJ, Jung CH, Lee KU, Ko KS. Task force team for the diabetes fact sheet of the Korean diabetes association. Past and current status of adult type 2 diabetes mellitus management in Korea. A National Health Insurance Service Database Analysis. Diabetes Metab J. 2018; 42:93–100.CrossrefMedlineGoogle Scholar
    • 9 Lee YH, Han K, Ko SH, Ko KS, Lee KU. Data analytic process of a nationwide population‐based study using national health information database established by National Health Insurance Service. Diabetes Metab J. 2016; 40:79–82.CrossrefMedlineGoogle Scholar
    • 10 Kim MK, Lee WY, Kang JH, Kang JH, Kim BT, Kim SM, Kim EM, Suh SH, Shin HJ, Lee KR, et al. 2014 clinical practice guidelines for overweight and obesity in Korea. Endocrinol Metab (Seoul). 2014; 29:405–409.CrossrefMedlineGoogle Scholar
    • 11 Song SO, Jung CH, Song YD, Park CY, Kwon HS, Cha BS, Park JY, Lee KU, Ko KS, Lee BW. Background and data configuration process of a nationwide population‐based study using the Korean national health insurance system. Diabetes Metab J. 2014; 38:395–403.CrossrefMedlineGoogle Scholar
    • 12 Asayama K, Kikuya M, Schutte R, Thijs L, Hosaka M, Satoh M, Hara A, Obara T, Inoue R, Metoki H, et al. Home blood pressure variability as cardiovascular risk factor in the population of Ohasama. Hypertension. 2013; 61:61–69.LinkGoogle Scholar
    • 13 Fukuda K, Kai H, Kamouchi M, Hata J, Ago T, Nakane H, Imaizumi T, Kitazono T; FSR Investigators . Day‐by‐day blood pressure variability and functional outcome after acute ischemic stroke: Fukuoka Stroke Registry. Stroke. 2015; 46:1832–1839.LinkGoogle Scholar
    • 14 Mena L, Pintos S, Queipo NV, Aizpurua JA, Maestre G, Sulbaran T. A reliable index for the prognostic significance of blood pressure variability. J Hypertens. 2005; 23:505–511.CrossrefMedlineGoogle Scholar
    • 15 Ellison RC, Zhang Y, Qureshi MM, Knox S, Arnett DK, Province MA; Investigators of the NHLBI Family Heart Study . Lifestyle determinants of high‐density lipoprotein cholesterol: the National Heart, Lung, and Blood Institute Family Heart Study. Am Heart J. 2004; 147:529–535.CrossrefMedlineGoogle Scholar
    • 16 Couillard C, Després JP, Lamarche B, Bergeron J, Gagnon J, Leon AS, Rao DC, Skinner JS, Wilmore JH, Bouchard C. Effects of endurance exercise training on plasma HDL cholesterol levels depend on levels of triglycerides: evidence from men of the Health, Risk Factors, Exercise Training and Genetics (HERITAGE) Family Study. Arterioscler Thromb Vasc Biol. 2001; 21:1226–1232.LinkGoogle Scholar
    • 17 Collaboration Prospective Studies , Lewington S, Whitlock G, Clarke R, Sherliker P, Emberson J, Halsey J, Qizilbash N, Peto R, Collins R. Blood cholesterol and vascular mortality by age, sex, and blood pressure: a meta‐analysis of individual data from 61 prospective studies with 55,000 vascular deaths. Lancet. 2007; 370:1829–1839.CrossrefMedlineGoogle Scholar
    • 18 Rhee EJ, Byrne CD, Sung KC. The HDL cholesterol/apolipoprotein A‐I ratio: an indicator of cardiovascular disease. Curr Opin Endocrinol Diabetes Obes. 2017; 24:148–153.CrossrefMedlineGoogle Scholar
    • 19 Madsen CM, Varbo A, Nordestgaard BG. Extreme high high‐density lipoprotein cholesterol is paradoxically associated with high mortality in men and women: two prospective cohort studies. Eur Heart J. 2017; 38:2478–2486.CrossrefMedlineGoogle Scholar
    • 20 Ko DT, Alter DA, Guo H, Koh M, Lau G, Austin PC, Booth GL, Hogg W, Jackevicius CA, Lee DS, et al. High‐density lipoprotein cholesterol and cause‐specific mortality in individuals without previous cardiovascular conditions: the CANHEART study. J Am Coll Cardiol. 2016; 68:2073–2083.CrossrefMedlineGoogle Scholar
    • 21 Kim MK, Han K, Park YM, Kwon HS, Kang G, Yoon KH, Lee SH. Associations of variability in blood pressure, glucose and cholesterol concentrations, and body mass index with mortality and cardiovascular outcomes in the general population. Circulation. 2018; 138:2627–2637.LinkGoogle Scholar
    • 22 Bangalore S, Fayyad R, Messerli FH, Laskey R, DeMicco DA, Kastelein JJ, Waters DD. Relation of variability of low‐density lipoprotein cholesterol and blood pressure to events in patients with previous myocardial infarction from the IDEAL trial. Am J Cardiol. 2017; 119:379–387.CrossrefMedlineGoogle Scholar
    • 23 Chang YH, Chang DM, Lin KC, Hsieh CH, Lee YJ. High‐density lipoprotein cholesterol and the risk of nephropathy in type 2 diabetic patients. Nutr Metab Cardiovasc Dis. 2013; 23:751–757.CrossrefMedlineGoogle Scholar
    • 24 Koh ES, Kim M, Kim MK, Han K, Shin SJ, Kwon HS, Park CW, Park YG, Chung S. Intra‐individual variability in high density lipoprotein cholesterol and risk of end‐stage renal disease: a nationwide population‐based study. Atherosclerosis. 2019; 286:135–141.CrossrefMedlineGoogle Scholar
    • 25 Clark D, Nicholls SJ, St John J, Elshazly MB, Kapadia SR, Tuzcu EM, Nissen SE, Puri R. Visit‐to‐visit cholesterol variability correlates with coronary atheroma progression and clinical outcomes. Eur Heart J. 2018; 39:2551–2558.CrossrefMedlineGoogle Scholar
    • 26 Levitan EB, Kaciroti N, Oparil S, Julius S, Muntner P. Relationships between metrics of visit‐to‐visit variability of blood pressure. J Hum Hypertens. 2013; 27:589–593.CrossrefMedlineGoogle Scholar
    • 27 Tsalamandris C, Panagiotopoulos S, Allen TJ, Waldrip L, Van Gaal B, Goodall I, Jerums G. Long‐term intraindividual variability of serum lipids in patients with type I and type II diabetes. J Diabetes Complications. 1998; 12:208–214.CrossrefMedlineGoogle Scholar
    • 28 Keene D, Price C, Shun‐Shin MJ, Francis DP. Effect on cardiovascular risk of high density lipoprotein targeted drug treatments niacin, fibrates, and CETP inhibitors: meta‐analysis of randomised controlled trials including 117,411 patients. BMJ. 2014; 349:g4379.CrossrefMedlineGoogle Scholar
    • 29 Frikke‐Schmidt R, Nordestgaard BG, Stene MC, Sethi AA, Remaley AT, Schnohr P, Grande P, Tybjaerg‐Hansen A. Association of loss‐of‐function mutations in the ABCA1 gene with high‐density lipoprotein cholesterol levels and risk of ischemic heart disease. JAMA. 2008; 299:2524–2532.CrossrefMedlineGoogle Scholar

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