Optimal range of triglyceride values to estimate serum low density lipoprotein cholesterol concentration in Korean adults: the Korea National Health and Nutrition Examination Survey, 2009

Change in Postprandial Level of Remnant Cholesterol After a Daily Breakfast in Chinese Patients With Hypertension

Background: Hypertension (HBP) is usually accompanied by hypertriglyceridemia that represents the increased triglyceride-rich lipoproteins and cholesterol content in remnant lipoproteins [i.e., remnant cholesterol (RC)]. According to the European Atherosclerosis Society (EAS), high RC (HRC) is defined as fasting RC ≥0.8 mmol/L and/or postprandial RC ≥0.9 mmol/L. However, little is known about postprandial change in RC level after a daily meal in Chinese patients with HBP. Methods: One hundred thirty-five subjects, including 90 hypertensive patients (HBP group) and 45 non-HBP controls (CON group), were recruited in this study. Serum levels of blood lipids, including calculated RC, were explored at 0, 2, and 4 h after a daily breakfast. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff point of postprandial HRC. Results: Fasting TG and RC levels were significantly higher in the HBP group (P < 0.05), both of which increased significantly after a daily meal in the two groups (P < 0.05). Moreover, postprandial RC level was significantly higher in the HBP group (P < 0.05). ROC curve analysis showed that the optimal cutoff point for RC after a daily meal to predict HRC corresponding to fasting RC of 0.8 mmol/L was 0.91 mmol/L, which was very close to that recommended by the EAS, i.e., 0.9 mmol/L. Fasting HRC was found in 31.1% of hypertensive patients but not in the controls. According to the postprandial cutoff point, postprandial HRC was found in approximately half of hypertensive patients and ~1-third of the controls. Conclusion: Postprandial RC level increased significantly after a daily meal, and hypertensive patients had higher percentage of HRC at both fasting and postprandial states. More importantly, the detection of postprandial lipids could be helpful to find HRC.

Validation of the Friedewald formula for estimating low density lipoprotein cholesterol: the Korea National Health and Nutrition Examination Survey, 2009 to 2011

BACKGROUND/AIMS

The aim of this study is to compare Friedewald-estimated and directly measured low density lipoprotein cholesterol (LDL-C) values and assess the concordance in guideline risk classification between the two methods.

METHODS

The data were derived from the 2009 to 2011 Korea National Health and Nutrition Examination Survey. We included subjects with triglyceride (TG) levels < 400 mg/dL. Analysis was done for 6,454 subjects who had all lipid panels- total cholesterol, directly measured LDL-C, high density lipoprotein cholesterol (HDL-C), and TG.

RESULTS

The subjects ranged in age from 10 to 87 years old. The mean age was 41.5 ± 17.3 years. For subjects with TG < 400 mg/dL, overall concordance in guideline risk classification was 79.1%. The Friedewald formula tended to underestimate LDL-C more at higher TG or lower HDL-C levels. Especially, the percent of subjects who were misclassified into a lower risk category was 31% when TG were 200 to 299 mg/dL; and 45.6% when TG were 300 to 399 mg/dL. A greater underestimation of LDL-C occurred at higher TG and lower Friedewald-estimated LDL-C levels. Of subjects with a Friedewald-estimated LDL-C < 70 mg/dL, 55.4% had a directly measured LDL-C ≥ 70 mg/dL when TG were 200 to 399 mg/dL.

CONCLUSION

The Friedewald equation tends to underestimate LDL-C in highrisk subjects such as hypertriglyceridemia and hypo-HDL-cholesterolemia. For these individuals accurate assessment of LDL-C is crucial, and therefore additional evaluation is warranted.

Comparison of non-fasting LDL-C levels calculated by Friedewald formula with those directly measured in Chinese patients with coronary heart disease after a daily breakfast

BACKGROUND

LDL-C level can be measured by direct methods (LDL-C_M) or calculated by Friedewald formula (LDL-C_C). The aim of this study was to investigate the difference between LDL-C_M and LDL-C_C after a daily breakfast in Chinese patients with coronary heart disease (CHD).

METHODS

Three hundred and three inpatients, including 203 CHD patients (CHD group) and 100 non-CHD controls (CON group), were enrolled in this study. Serum levels of blood lipid parameters, including LDL-C_C and LDL-C_M, at 0, 2 and 4 h (h) were monitored after a daily breakfast in all subjects.

RESULTS

LDL-C_M was significantly higher than LDL-C_C in fasting state in each group and at 4 h postprandially in CHD group (P < .05). Postprandial LDL-C_M and LDL-C_C significantly decreased in each group (P < .05). Postprandial decline in LDL-C_M was significantly greater than that of LDL-C_C (P < .05). For CHD patients taking statins for ≥1 month before admission, non-fasting percent attainment of LDL-C_M or LDL-C_C was significantly higher than its fasting value, especially at 4 h (P < .05). The percent deviation of LDL-C_M from 1.8 mmol/L at 4 h was significantly different from its fasting value. However, there was no significant difference in percent deviation of LDL-C_C from 1.8 mmol/L between fasting and non-fasting states.

CONCLUSIONS

It indicated that the clinical monitoring of non-fasting LDL-C level in CHD patients could be relatively complex, and the judgement may depend not only on the method to acquire LDL-C level, but also on the evaluation method.

Martin's Equation as the Most Suitable Method for Estimation of Low-Density Lipoprotein Cholesterol Levels in Korean Adults

Background

Friedewald equation is the most widely used method for estimating low-density lipoprotein cholesterol (LDL-C) level. However, due to potential over- or underestimation, many studies have used a modified equation. This study aimed to compare estimates by 4 different equations to directly measured LDL-C concentrations in order to propose the most appropriate method for LDL-C estimation in the Korean population.

Methods

We studied data of 4,350 subjects that included total cholesterol, high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and LDL-C concentrations that had been measured at one university hospital in Seoul. We investigated 4 equations: LDL-C by Friedewald's original equation (LDL-C_F) and its 3 modifications. Pearson correlation analysis was performed to compare these estimates to the direct measurement.

Results

Pearson correlation analysis revealed a good correlation among all 4 estimated LDL-C values and the directly measured LDL-C value. The Pearson coefficients were 0.951 for LDL-C_F, 0.917 for LDL-C by Hatta equation (LDL-C_H), 0.968 for LDL-C by Puavilai equation (LDL-C_P), and 0.983 for LDL-C by Martin equation (LDL-C_M). Martin equation (LDL-C_M) resulted in the best approximation (mean difference from the direct measurement, 5.5 mg/dL; mean percentage difference from the direct measurement, 5.1%) and the best agreement with the direct measurement (86.1%). LDL-C_P resulted in the second-best approximation (mean difference, 7.0 mg/dL; mean percentage difference, 6.2%; concordance, 82.5%). LDL-C_M was found to be less influenced by TG and HDL-C levels than by LDL-C_F.

Conclusion

Estimates by Martin equation had the best agreement with direct LDL-C concentrations and both Martin and Puavilai equations were superior to Friedewald equation for estimating LDL-C concentrations in Korean adults.

Prediction of future cardiovascular disease with an equation to estimate apolipoprotein B in patients with high cardiovascular risk: an analysis from the TNT and IDEAL study

BACKGROUND

Apolipoprotein B (apoB) is known to be a more powerful predictor of cardiovascular disease than conventional lipids. We aimed to determine the clinical relevance of a newly developed equation to estimate serum apoB levels based on total cholesterol, HDL cholesterol, and triglycerides in patients with high cardiovascular risk.

METHODS

The occurrence of a major cardiovascular event (MCVE) was assessed using the data from the Treating to New Targets (TNT) and Incremental Decrease in End points through Aggressive Lipid lowering (IDEAL) trials.

RESULTS

Pooled analysis of these two data sets showed that both directly-measured apoB (HR per 1-SD (95% CI): 1.16 (1.11-1.21), P < 0.001) and apoB estimated from the eq. (HR per 1-SD (95% CI): 1.14 (1.09-1.19), P < 0.001) were significantly associated with the development of a future MCVE. Prediction of MCVEs by the apoB eq. (C statistic 0.650) was nearly identical to that of directly-measured apoB (0.651). In addition, the net reclassification indices indicated no difference in the prediction of MCVEs between models including the apoB equation and directly-measured apoB (1% (-1.3-4.0), P = 0.31).

CONCLUSIONS

Our equation to predict apoB levels showed MCVE risk prediction comparable to directly-measured apoB in high risk patients with previous coronary heart disease.

Comparison of Formulas for Calculating Low-density Lipoprotein Cholesterol in General Population and High-risk Patients with Cardiovascular Disease

Background and Objectives

Low-density lipoprotein cholesterol (LDL-C), an established cardiovascular risk factor, can be generally determined by calculation from total cholesterol, high-density lipoprotein cholesterol, and triglyceride concentrations. The aim of this study was to compare LDL-C estimations using various formulas with directly measured LDL-C in a community-based group and hospital-based group among the Korean population.

Subjects and Methods

A total of 1498 participants were classified into four groups according to triglyceride concentrations as follows: <100, 100–199, 200–299, and ≥300 mg/dL. LDL-C was calculated using the Friedewald, Chen, Vujovic, Hattori, de Cordova, and Anandaraja formulas and directly measured using a homogenous enzymatic method. Pearson's correlation coefficients, intraclass correlation coefficients (ICC), Passing & Bablok regression, and Bland-Altman plots were used to evaluate the performance of six formulas.

Results

The Friedewald formula had the highest accuracy (ICC=0.977; 95% confidence interval 0.974-0.979) of all the triglyceride ranges, while the Vujovic formula had the highest accuracy (ICC=0.876; 98.75% confidence interval 0.668–0.951) in people with triglycerides ≥300 mg/dL. The mean difference was the lowest for the Friedewald formula (0.5 mg/dL) and the percentage error was the lowest for the Vujovic formula (30.2%). However, underestimation of the LDL-C formulas increased with triglyceride concentrations.

Conclusion

The accuracy of the LDL-C formulas varied considerably with differences in triglyceride concentrations. The Friedewald formula outperformed other formulas for estimating LDL-C against a direct measurement and the Vujovic formula was suitable for hypertriglyceridemic samples; it could be used as an alternative cost-effective tool to measure LDL-C when the direct measurement cannot be afforded.

Impact of lifestyle factors on trends in lipid profiles among Korean adolescents: the Korea National Health and Nutrition Examination Surveys study, 1998 and 2010

Purpose

Only a few studies have explored nationwide trends in lipid profiles among Asian adolescents. We aimed to assess trends in lipid profiles and the associated lifestyle factors among Korean children.

Methods

We analyzed data for 2,094 adolescents who were aged 10–18 years and had participated in the Korea National Health and Nutrition Examination Surveys in 1998 and 2010.

Results

During 1998–2010, the prevalence of obesity significantly increased in boys, but no changes were observed in girls. Over this period, there was a small but significant decrease in the mean low-density lipoprotein (LDL)-cholesterol level in boys (1998, 87.5 mg/dL; 2010, 83.6 mg/dL; P=0.019) and mean triglyceride levels in girls (1998, 90.8 mg/dL; 2010, 85.8 mg/dL; P=0.020). There were no significant changes in the prevalence of dyslipidemia in boys, but a modest decrease was noted in girls (1998, 25.1%; 2010, 18.3%; P=0.052). During the study period, the prevalence of breakfast skipping decreased, whereas that of regular exercise increased in both groups. Daily total energy intake did not change between these years. In multivariable logistic regression analyses, breakfast skipping was associated with increased risk of hyper-LDL-cholesterolemia in boys (odds ratio [OR], 5.77) and hypertriglyceridemia (OR, 2.27) in girls. Regular exercise was associated with decreased risk of hypo-HDL-cholesterolemia (OR, 0.40) in boys.

Conclusion

Although the prevalence of obesity in boys increased, favorable or constant trends in lipid profiles were observed among Korean adolescents during 1998–2010. Decrease in breakfast skipping and increase in regular exercise may have contributed to these trends.

Effects of age, sex, and menopausal status on blood cholesterol profile in the korean population

Background and Objectives

To investigate age-specific and sex-specific distributions of blood cholesterol in the general Korean population.

Subjects and Methods

We analyzed data for 8284 men and 9246 women aged ≥10 years who participated in the fifth (2010-2012) Korea National Health and Nutrition Examination Survey. Age-specific means, medians, and selected percentiles were calculated for men, premenopausal women, and postmenopausal women.

Results

Median total cholesterol (TC) level increased with age across all age groups, from 147 to 196 mg/dL in males and from 159 to 210 mg/dL in females. Triglyceride (TG) levels increased with age in females; however, in males, TG levels rapidly increased during young adulthood, peaked at 50-54 years, and then decreased. High density lipoprotein-cholesterol (HDL-C) levels were higher in females than in males and decreased with increasing age in both males and females. Low density lipoprotein-cholesterol (LDL-C) levels increased with age across all age groups, from 89 to 127 mg/dL in males and from 82 to 113 mg/dL in females. Lipoprotein-cholesterol fraction (TC/HDL-C, LDL-C/HDL-C, TG/HDL-C, non-HDL-C) levels increased with age in females, but increased more rapidly in males during young adulthood and decreased after middle age.

Conclusion

Blood cholesterol levels and lipoprotein-cholesterol fractions present different distributions by age, sex, and menopausal status.