Skip to main content

Advertisement

Comparison of discrimination for cardio-metabolic risk by different cut-off values of the ratio of triglycerides to HDL cholesterol

Article metrics

Abstract

Background

The ratio of triglycerides to HDL cholesterol (TG/HDL-C ratio) is known as a good predictor for cardiovascular disease. The purpose of this study was to compare discrimination for cardiovascular risk by different cut-off values of the TG/HDL-C ratio.

Methods

Receiver operating characteristic (ROC) analysis was performed for the relationship between TG/HDL-C ratio and accumulation of cardio-metabolic risk factors including visceral obesity, hypertension and diabetes. Logistic regression analysis was performed for the relationships of TG/HDL-C ratio with cardio-metabolic risk factors using the cut-off values obtained by ROC analysis and conventional cut-off values (men, 3.75; women, 3.00).

Results

In ROC analysis, the optimal cut-off values for TG/HDL-C ratio were 2.967 in men and 2.237 in women, which were much smaller than the conventional cut-of values. Odds ratios for multiple cardio-metabolic risk factors of subjects with vs. subjects without a high TG/HDL-C ratio in men and women were 5.75 (4.43–7.46) and 18.76 (10.32–34.13), respectively, by using the new cut-off values and they were 5.03 (3.96–6.39) and 16.11 (9.20–28.20), respectively, by using the conventional cut-off values. The odds ratios for visceral obesity, hypertension and diabetes were comparable when using these two different cut-off values.

Conclusion

Cut-off values should be ideally calculated by ROC analysis. However, the discrimination power of cut-off values for the TG/HDL-C ratio calculated by ROC analysis for cardio-metabolic risk was similar to those by using the conventional cut-off values. Further studies using cardiovascular events as outcomes in the analysis may be needed to determine more suitable cut-off values of the TG/HDL-C ratio.

Introduction

Early detection of individual cardiovascular risk is important to prevent cardiovascular disease and reduce its mortality. Dyslipidemia, including hyper-LDL cholesterolemia, hypo-HDL cholesterolemia and hyper-triglyceridemia, is a major risk factor of cardiovascular disease. The ratio of LDL cholesterol to HDL cholesterol (LDL-C/HDL-C ratio) is a classical lipid index to predict coronary heart disease [1]. A more recently proposed lipid index for prediction of cardiovascular disease is the ratio of triglycerides to HDL cholesterol (TG/HDL-C ratio), which has been shown to be a better predictor than LDL-C/HDL-C ratio of myocardial infarction [2, 3] and to be associated with insulin resistance [4] and metabolic syndrome [5]. TG/HDL-C ratio has been shown to reflect small dense LDL particles [6], which are more atherogenic than larger buoyant LDL particles [7,8,9,10] and has been reported to be an independent risk factor for coronary heart disease [11, 12]. It is a merit that measurement of TG/HDL-C ratio is easy to perform, while measurement of small dense LDL particles requires complicated procedures including ultracentrifugation [13], gradient gel electrophoresis [14] and nuclear magnetic resonance imaging [15]. Thus, TG/HDL-C ratio is a useful index to predict cardiovascular risk in routine and screening examinations.

Both triglycerides and HDL cholesterol are included in the criteria of metabolic syndrome, in which the cut-off value for triglycerides used is 150 mg/dl for men and women and that for HDL cholesterol is 40 mg/dl for men and 50 mg/dl for women [16, 17]. However, various cut-off values for TG/HDL-C ratio have been proposed in previous studies [4, 18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38] as summarized in Table 1. In addition, the cut-off values were different when mg/dl and mmol/L were used as the units of triglycerides and HDL cholesterol: the TG/HDL-C value calculated using mg/dl corresponds to the product of 2.29 and the TG/HDL-C value calculated using mmol/L.

Table 1 Previous studies regarding cut-off values of the TG/HDL-C ratio.

The purpose of this study was to compare two cut-off values of TG/HDL-C ratio as a risk index for cardiovascular disease. One is a cut-off value calculated by using each cut-off value for triglycerides and HDL cholesterol, and the other is a cut-off value obtained by ROC analysis for the relationship between TG/HDL-C ratio and accumulation of three cardio-metabolic risk factors including visceral obesity, hypertension and diabetes. Then the relationships of TG/HDL-C ratio with the risk factors were compared in analyses using the two different cut-off values. There has been, to the best of our knowledge, no report on prediction of incident cardiovascular disease by using the conventional TG/HDL-C ratio calculated as a ratio of the cut-off value for triglycerides to that for HDL cholesterol. Thus, 3.75 (mg/dl/mg/dl) for men and 3.00 (mg/dl/mg/dl) for women, corresponding to 1.64 (mmol/L/mmol/L) for men and 1.31 (mmol/L/mmol/L) for women, are theoretical cut-off values for the TG/HDL-C ratio and are higher than the cut-off values obtained by ROC analysis in most of the previous studies (Table 1) and our present study. However, it was shown in this study that the discrimination power of the cut-off values for high TG/HDL-C ratio calculated by ROC analysis for cardio-metabolic risk is similar to those by using the conventional cut-off values.

Methods

Subjects

The subjects were Japanese men (n = 6914) and women (n = 3282) aged 35–40 years who had received periodic health checkup examinations at workplaces and had been registered in a population-based database in Yamagata Prefecture in Japan. This study was approved by the Ethics Committee of Yamagata University School of Medicine (No. 112 from April 2005 to March 2006, approved on March 13, 2006) and the Hyogo College of Medicine Ethics Committee (No. 3003 in 2018). A population-based database including the results of annual health checkup examinations, in which the participants were not identified, was used, and informed consent from each participant was not obtained in this study. This procedure was approved by the institutional ethics committee. Those who had been receiving drug therapy for dyslipidemia (1.1%) were excluded from subjects of this study. Histories of illness, medication, alcohol consumption, cigarette smoking, and regular exercise (almost every day with exercise for 30 min or longer per day) were surveyed by questionnaires. The subjects were divided into four groups by average cigarette consumption (nonsmokers; light smokers, 20 cigarettes or less per day; heavy smokers, more than 20 and less than 41 cigarettes per day; very heavy smokers, 41 or more cigarettes per day). Average alcohol consumption of each subject per week was reported on questionnaires. The subjects were divided into three groups (nondrinkers, occasional drinkers and regular drinkers) by frequency of drinking. Frequency of weekly alcohol drinking was categorized as “every day” (regular drinkers), “sometimes” (occasional drinkers) and “never” (nondrinkers).

Measurements

Height and body weight were measured while subjects wore light clothes at the health checkup. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Waist circumference was measured at the navel level according to the recommendation of the definition of the Japanese committee for the diagnostic criteria of metabolic syndrome [39]. Waist circumference corrected by height (waist-to-height ratio) has been proposed to be a more reasonable index than waist circumference for abdominal obesity [40]. Waist-to-height ratio has been shown to be a better discriminator than waist circumference or BMI of cardiovascular risk factors and coronary heart disease [41,42,43]. Therefore, visceral obesity was evaluated by the waist-to-height ratio in this study. The cut-off value of high waist-to-height ratio used was 0.5 [40]. Blood pressure was measured by trained nurses, who were part of the local health-checkup company, with a mercury sphygmomanometer once on the day of the health checkup after each subject had rested quietly in a sitting position. Korotkoff phase V was used to define diastolic pressure. Hypertension was defined as systolic blood pressure of ≥ 140 mmHg and/or diastolic blood pressure of ≥ 90 mmHg. In addition, subjects who were receiving drug therapy for hypertension were included in the hypertensive group regardless of blood pressure levels. Fasted blood was sampled from each subject, and serum triglycerides and HDL cholesterol were measured by enzymatic methods using commercial kits, Pureauto S TG-N and Cholestest N-HDL (Sekisui Medical Co., Ltd., Tokyo, Japan), respectively. TG/HDL-C ratio was calculated as the ratio of triglycerides (mg/dl) to HDL cholesterol (mg/dl), and the conventional cut-off value of high TG/HDL-C ratio was defined as the ratio of the cut-off value of triglycerides (150 mg/dl) to that of HDL cholesterol (40 mg/dl in men and 50 mg/dl in women), namely 3.75 and 3.00 in men and women, respectively.

Blood hemoglobin A1c was used for evaluation of hyperglycemia. Hemoglobin A1c was determined by the latex cohesion method using a commercial kit (Determiner HbA1c, Kyowa Medex, Tokyo, Japan). Hemoglobin A1c values were calibrated by using a formula proposed by the Japan Diabetes Society (JDS) as hemoglobin A1c (National Glycohemoglobin Standardization Program) (%) = 1.02 x hemoglobin A1c (JDS) (%) + 0.25 (%) [44]. Subjects with diabetes were defined as those showing high hemoglobin A1c levels (≥ 6.5%), according to the criteria for diagnosis of diabetes by the American Diabetes Association [45]. Subjects receiving drug therapy for diabetes were also included in the diabetes group. Coefficients of variation for reproducibility of each measurement were ≤ 3% for triglycerides and ≤ 5% for HDL cholesterol and hemoglobin A1c. Subjects with multiple risk factors were defined as those having high waist-to-height ratio, hypertension and diabetes.

Statistical analysis

Statistical analyses were performed using computer software programs (SPSS version 16.0 J for Windows, Chicago IL, USA and R 2.12.2). Continuous variables were compared between men and women using the unpaired Student’s t test. Since triglycerides and TG/HDL-C ratio did not show normal distributions, they were compared between the groups using the Mann-Whitney U test. Categorical variables were compared using the chi-squared test. How well the TG/HDL-C ratio could discriminate those who did and those who did not have multiple risk factors (visceral obesity, hypertension and diabetes) was evaluated by using a receiver-operating characteristic (ROC) curve. Sensitivity and specificity are the basic measures of accuracy of a diagnostic test: The sensitivity is the probability of a positive test result, while the specificity is the probability of a negative test result. A ROC curve is a plot of sensitivity versus 1 – specificity that offers a summary of sensitivity and specificity across a range of cut-off points for a continuous predictor. The optimal cut-off point was selected by maximizing Youden’s index, which is the difference between the true positive rate (sensitivity) and the false positive rate (1-specificity) in the ROC curve. Discriminability of the TG/HDL-C ratio was measured by the area under the ROC curve (AUC). The 95% confidence interval (CI) for the AUC was estimated by using the DeLong method. To adjust for the optimism of the AUC estimated in our internal cohort, the optimism-corrected AUC and its corresponding 95% CI were also estimated by using a bootstrap method [46]. In logistic regression analysis, odds ratios for visceral obesity, hypertension, diabetes and multiple risk factors were estimated in subjects with vs. subjects without a high TG/HDL-C ratio, defined by using the conventional cut-off values or the cut-off values determined in this study. In multivariate logistic regression analysis, age and histories of smoking, alcohol drinking and regular exercise were adjusted as confounding factors. All probability (p) values are 2-sided and values of p less than 0.05 were considered to indicate statistical significance.

Results

Characteristics of the subjects

Table 2 shows the characteristics of the male and female subjects. Variables related to cardiovascular disease were significantly higher in men than in women except for HDL cholesterol, which was significantly higher in women than in men. There were 310 men (4.48%) and 54 women (1.65%) who showed accumulation of three cardiovascular risk factors (visceral obesity, hypertension and diabetes).

Table 2 Characteristics of the subjects

ROC analysis for the relationships between TG/HDL-C ratio and multiple cardiovascular risk factors

Figure 1 shows results of ROC analysis for the relationships between TG/HDL-C ratio and multiple cardiovascular risk factors. The optimal cut-off values of TG/HDL-C ratio for multiple cardiovascular risk factors were 2.967 in men and 2.237 in women. These values are much smaller than the conventional cut-off values (men, 3.75; women, 3.00) calculated by using the known cut-off values of triglycerides and HDL cholesterol. The sensitivity and specificity for each cut-off value are shown in Table 3. The sensitivity and specificity for the conventional cut-off values were lower and higher, respectively, than those for the cut-off values obtained by using ROC analysis.

Fig. 1
figure1

Receiver-operating characteristic (ROC) curves for the relationships between TG/HDL-C ratio and multiple risk factors in men (A) and women (B). Cut-off values with specificity and sensitivity in parentheses are given in the figures. Area under the ROC curve: men, 0.767 (95% confidence interval: 0.741–0.793); women, 0.858 (95% confidence interval: 0.805–0.910)

Table 3 Sensitivity and specificity for relationships of multiple risk factors with high TG/HDL-C ratio defined by conventional cut-off values and new cut-off values in men and women.

We estimated optimism-corrected AUC by using a bootstrap method [46]. Consequently, the optimism-corrected AUC values for the TG/HDL-C ratio in relation to multiple risk factors were 0.764 in men and 0.855 in women and were thus almost the same (but slightly smaller) as the AUC values of 0.767 in men and 0.858 in women shown in Fig. 1, which may be due to a large sample size of the cohort used in this study.

Logistic regression analysis for the relationships between TG/HDL-C ratio and multiple cardiovascular risk factors

Table 4 shows odds ratios with their 95% confidence intervals of subjects with vs. subjects without a high TG/HDL-C ratio for multiple cardiovascular risk factors in univariate and multivariate logistic regression analyses. In the multivariate analysis, age and histories of smoking, alcohol drinking and regular exercise were used as confounding variables. All of the odds ratios were significantly higher than the reference level of 1.00. Both crude and adjusted odds ratios tended to be higher in the analysis using the new cut-off values of TG/HDL-C ratio obtained by ROC analysis than those in the analysis using the conventional cut-off values of TG/HDL-C ratio.

Table 4 Odds ratios for multiple risk factors (visceral obesity, hypertension and diabetes) in subjects with vs. subjects without a high TG/HDL-C ratio defined by conventional cut-off values and new cut-off values in men and women

Logistic regression analysis for the relationships of TG/HDL-C ratio with visceral obesity, hypertension and diabetes

Odds ratios of high TG/HDL-C ratio for visceral obesity, hypertension and diabetes are shown in Tables 5, 6 and 7, respectively. In multivariate analysis, age and histories of smoking, alcohol drinking and regular exercise were used as confounding variables (Adjusted). The crude and adjusted odds ratios for visceral obesity, hypertension and diabetes were significantly higher than the reference level in all analyses (Tables 5, 6, 7). Both crude and adjusted odds ratios for visceral obesity, hypertension and diabetes were comparable when using the conventional cut-off values and using the new cut-off values of TG/HDL-C ratio obtained by ROC analysis in this study (Tables 5, 6, 7).

Table 5 Odds ratios for high WHtR in subjects with vs. subjects without a high TG/HDL-C ratio defined by conventional cut-off values and new cut-off values in men and women
Table 6 Odds ratios for hypertension in subjects with vs. subjects without a high TG/HDL-C ratio defined by conventional cut-off values and new cut-off values in men and women
Table 7 Odds ratios for diabetes in subjects with vs. subjects without a high TG/HDL-C ratio defined by conventional cut-off values and new cut-off values in men and women

Discussion

Dyslipidemia is known to be closely associated with other major atherosclerotic risk factors such as obesity, hypertension and diabetes [47]. In order to determine the cut-off values for the TG/HDL-C ratio, a known cardiovascular risk index, ROC analysis was performed using accumulation of multiple risk factors, including visceral obesity, hypertension and diabetes, as a dependent variable in early middle-aged men and women. The optimal cut-off values obtained by the analysis were 2.967 in men and 2.237 in women, which are much smaller than the conventional cut-off values, 3.75 in men and 3.00 in women, simply calculated by using each of cut-off values for triglycerides (150 mg/dl in men and women) and HDL cholesterol (40 mg/dl in men and 50 mg/dl in women). In this study, we for the first time investigated whether the discriminating power of the TG/HDL-C ratio is different in analyses using the above two different cut-off values. The odds ratios for multiple risk factors of subjects with vs. subjects without a high TG/HDL-C ratio were slightly higher in the analysis using the cut-off values determined in this study than in the analysis using the conventional cut-off values (Table 4). When each component of the multiple risk factors, including visceral obesity, hypertension and diabetes, was used as an outcome variable in ROC analysis, the odds ratios of subjects with vs. subjects without a high TG/HDL-C ratio in men or women were not different in the analyses using the new and conventional cut-off values. Thus, similar discriminating power of the TG/HDL-C ratio for each of the components of visceral obesity, hypertension and diabetes was obtained by these different cut-off values, although the values were considerably different.

There is a gender difference in HDL cholesterol level, which is higher in women than in men, and different cut-off values for men and women are in fact used in the NCEP criteria for metabolic syndrome [17]. Therefore, it is reasonable that there is also a gender difference in cut-off values of the TG/HDL-C ratio: The values were larger in men than in women (Table 1). Thus, it is preferable to use different cut-off values of the TG/HDL-C ratio for men and women. The cut-off values for men and women estimated in the present study are relatively close to those reported by an Argentine group but are quite different from the values reported by a Japanese group (Table 1). There have been seven reports from China in which there were various cut-off values of the TG/HDL-C ratio (Table 1). Thus, there seems to be no ethnicity-related difference in the cut-offs of TG/HDL-C ratio. Age is also an important factor to determine the cut-off values, and mean ages of participants were different among the previous studies. The outcome in ROC analysis is also a determinant of the cut-off values, and insulin resistance or metabolic syndrome was an outcome used in ROC analysis in most of the previous studies (Table 1). Thus, differences in age and gender of subjects and outcome in ROC analysis might have caused the differences in cut-off values for the TG/HDL-C ratio in previous studies.

Regarding the utility of the TG/HDL-C ratio in individual risk of cardiovascular disease, dyslipidemia is a potential (usually asymptomatic) risk factor of cardiovascular disease and is often found by blood examinations. Dyslipidemia is associated with other overt cardiovascular risk factors such as obesity, hypertension and diabetes. Not only elderly people but also younger adults are affected by dyslipidemia: About 31% of adults aged 20 to 29 years and 38% of adults aged 30 to 39 years in US showed HDL cholesterol and/or triglyceride levels that were out of the ranges of levels recommended by NCEP [48]. Thus, evaluation of dyslipidemia using the TG/HDL-C ratio in an early stage of individual life and earlier correction of lifestyle are useful for predicting the occurrence of obesity, hypertension and diabetes and for preventing future cardiovascular events. However, the appropriate cut-off value for the TG/HDL-C ratio has remained to be determined.

A cut-off value should be ideally determined by ROC analysis. The cut-off value for the TG/HDL-C ratio depends on its associated outcome, and an outcome yielding a larger AUC in ROC analysis is preferable to determine the cut-off value of the TG/HDL-C ratio. A single TG/HDL-C ratio can be created by varying different combinations of triglyceride and HDL cholesterol values. The TG/HDL-C ratio level that optimally discriminated the risk of cardiovascular disease could be identified from these varying combinations. Thus, the predicted cardiovascular risks for the groups classified by using the conventional and the newer cut-off values of TG/HDL-C ratio could be contrasted. However, these cut-off values were not greatly different in their discriminating power for cardiovascular risk in the present study.

In the present study, AUC values for the TG/HDL-C ratio in relation to multiple risk factors were 0.767 in men and 0.858 in women (Fig. 1), which are generally evaluated as moderate accuracy (AUC: 0.7 ~ 0.9). In most previous studies, cut-off values of the TG/HDL-C ratio were obtained by ROC analysis using variables such as metabolic syndrome and insulin resistance that were associated cross-sectionally with the TG/HDL-C ratio [4, 18,19,20,21,22,23,24,25,26,27,28,29,30,31, 33,34,35,36,37], and there have been only a few prospective studies on cut-off values of TG/HDL-C ratio. In recent reports from Iran and China [32, 38] using prospective cohorts with outcomes of ischemic heart disease and ischemic stroke, 3.68 mg/dl/mg/dl and 2.06 mg/dl/mg/dl (corresponding to 0.9 mmol/L/mmol/L) were proposed as cut-off values of the TG/HDL-C ratio in men and women, although the AUC in those studies were not large (0.575 and 0.647). In the present study, cut-off values of the TG/HDL-C ratio, obtained by ROC analysis using accumulation of multiple risk factors as an independent outcome variable, did not show strong discriminating power for cardiovascular risk since similar odds ratios for cardiovascular risk factors were obtained in logistic regression analysis using the new cut-off values and conventional cut-off values in men and women. Therefore, the cut-off value of the TG/HDL-C ratio, as a cardiovascular risk index representing dyslipidemia, may need to be determined in prospective studies by using a more suitable outcome such as cardiovascular events in ROC analysis with high accuracy.

There are limitations of this study. The subjects were relatively young, and further studies are needed to test the influence of age on the cut-off value of TG/HDL-C ratio in ROC analysis. To our knowledge, there has been only one study on cut-off values for Japanese, in which the optimal cut-off values were calculated to be 1.50 in non-obese men and women (mean age of 60 years) and 2.20 in overweight men and women (mean age of 57 years) [22]. These cut-off values are much lower than that in the present study, and one possible reason for this is a difference in ages of subjects. Age and lifestyles including habits of smoking, alcohol drinking and regular exercise were adjusted in multivariate logistic regression analysis in the present study. However, there are other possible confounding factors, e.g., diet, nutrition and socio-economic status, influencing the relationships between TG/HDL-C ratio and cardiovascular risk factors. All of the subjects in this study were Japanese. A racial difference in the TG/HDL-C ratio has been suggested [20]. Another limitation is that only a single reading of blood pressure on a single day was used as blood pressure measurement to determine hypertension status. This study was cross-sectional in its design, and further prospective studies are needed to discuss causal relationships between the TG/HDL-C ratio and the risk of cardiovascular disease. Since the newer cut-off values are lower than the conventional cut-off values, the sensitivity and specificity of the newer cut-off values are, due to a trade-off, higher and lower, respectively, than those of the conventional cut-off values. Finally, as mentioned above, ROC analysis using a more suitable outcome is needed to determine the cut-off value of the TG/HDL-C ratio that discriminates cardiovascular risk more effectively.

Conclusions

We investigated two cut-off values of the TG/HDL-C ratio, a conventional cut-off value and a cut-off value obtained by ROC analysis. The power of these cut-off values to discriminate each of the cardio-metabolic risk factors, including visceral obesity, hypertension and diabetes, was similar, and further prospective studies using cardiovascular events as independent variables in ROC analysis may be needed to determine more suitable cut-off values of TG/HDL-C ratio.

Availability of data and materials

The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.

Abbreviations

ANCOVA:

Analysis of covariance

AUC:

Area under the ROC curve

BMI:

Body mass index

CI:

Confidence interval

HDL-C:

High density lipoprotein cholesterol

JDS:

The Japan Diabetes Society

LDL-C:

Low density lipoprotein cholesterol

LDL-C/HDL-C:

The ratio of LDL cholesterol to HDL cholesterol

RF:

Risk factors

ROC:

Receiver operating characteristic

TG:

Triglycerides

TG/HDL-C:

The ratio of triglycerides to HDL cholesterol

References

  1. 1.

    Kannel WB. Lipids, diabetes, and coronary heart disease: insights from the Framingham study. Am Heart J. 1985;110:1100–7.

  2. 2.

    Gaziano JM, Hennekens CH, O'Donnell CJ, Breslow JL, Buring JE. Fasting triglycerides, high-density lipoprotein, and risk of myocardial infarction. Circulation. 1997;96:2520–5.

  3. 3.

    Jeppesen J, Hein HO, Suadicani P, Gyntelberg F. Relation of high TG-low HDL cholesterol and LDL cholesterol to the incidence of ischemic heart disease. An 8-year follow-up in the Copenhagen male study. Arterioscler Thromb Vasc Biol. 1997;17:1114–20.

  4. 4.

    McLaughlin T, Reaven G, Abbasi F, Lamendola C, Saad M, Waters D, et al. Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am J Cardiol. 2005;96:399–404.

  5. 5.

    Cordero A, Laclaustra M, León M, Casasnovas JA, Grima A, Luengo E, et al. Comparison of serum lipid values in subjects with and without the metabolic syndrome. Am J Cardiol. 2008;102:424–8.

  6. 6.

    Dobiásová M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: correlation with lipoprotein particle size and esterification rate in apoB-lipoprotein-depleted plasma (FERHDL). Clin Biochem. 2001;34:583–8.

  7. 7.

    de Graaf J, Hak-Lemmers HL, Hectors MP, Demacker PN, Hendriks JC, Stalenhoef AF. Enhanced susceptibility to in vitro oxidation of the dense low density lipoprotein subfraction in healthy subjects. Arterioscler Thromb. 1991;11:298–306.

  8. 8.

    Tribble DL, Holl LG, Wood PD, Krauss RM. Variations in oxidative susceptibility among six low density lipoprotein subfractions of differing density and particle size. Atherosclerosis. 1992;93:189–99.

  9. 9.

    Galeano NF, Milne R, Marcel YL, Walsh MT, Levy E, Ngu'yen TD, et al. (1994). Apoprotein B structure and receptor recognition of triglyceride-rich low density lipoprotein (LDL) is modified in small LDL but not in triglyceride-rich LDL of normal size. J Biol Chem. 1994;269:511–9.

  10. 10.

    Anber V, Griffin BA, McConnell M, Packard CJ, Shepherd J. Influence of plasma lipid and LDL-subfraction profile on the interaction between low density lipoprotein with human arterial wall proteoglycans. Atherosclerosis. 1996;124:261–71.

  11. 11.

    Austin MA, Breslow JL, Hennekens CH, Buring JE, Willett WC, Krauss RM. Low-density lipoprotein subclass patterns and risk of myocardial infarction. JAMA. 1988;260:1917–21.

  12. 12.

    Gardner CD, Fortmann SP, Krauss RM. Association of small low-density lipoprotein particles with the incidence of coronary artery disease in men and women. JAMA. 1996;276:875–81.

  13. 13.

    Swinkels DW, Hak-Lemmers HL, Demacker PN. Single spin density gradient ultracentrifugation method for the detection and isolation of light and heavy low density lipoprotein subfractions. J Lipid Res. 1987;28:1233–9.

  14. 14.

    Scheffer PG, Bakker SJ, Heine RJ, Teerlink T. Measurement of LDL particle size in whole plasma and serum by high performance gel-filtration chromatography using a fluorescent lipid probe. Clin Chem. 1998;44:2148–51.

  15. 15.

    Otvos JD, Jeyarajah EJ, Bennett DW, Krauss RM. Development of a proton nuclear magnetic resonance spectroscopic method for determining plasma lipoprotein concentrations and subspecies distributions from a single, rapid measurement. Clin Chem. 1992;38:1632–8.

  16. 16.

    Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. I. Diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998;15:539–53.

  17. 17.

    National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III). JAMA. 2001;285:2486–97.

  18. 18.

    McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med. 2003;139:802–9.

  19. 19.

    Cordero A, Laclaustra M, León M, Casasnovas JA, Grima A, Luengo E, et al. MESYAS registry investigators. Comparison of serum lipid values in subjects with and without the metabolic syndrome. Am J Cardiol. 2008;102:424–8.

  20. 20.

    Li C, Ford ES, Meng YX, Mokdad AH, Reaven GM. Does the association of the triglyceride to high-density lipoprotein cholesterol ratio with fasting serum insulin differ by race/ethnicity? Cardiovasc Diabetol. 2008;7(4). https://doi.org/10.1186/1475-2840-7-4.

  21. 21.

    Hadaegh F, Hatami M, Tohidi M, Sarbakhsh P, Saadat N, Azizi F. Lipid ratios and appropriate cut off values for prediction of diabetes: a cohort of Iranian men and women. Lipids Health Dis. 2010;9:85. https://doi.org/10.1186/1476-511X-9-85.

  22. 22.

    Kawamoto R, Tabara Y, Kohara K, Miki T, Kusunoki T, Takayama S, et al. Low-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio is the best surrogate marker for insulin resistance in non-obese Japanese adults. Lipids Health Dis. 2010;9:138. https://doi.org/10.1186/1476-511X-9-138.

  23. 23.

    Sumner AE, Harman JL, Buxbaum SG, Miller BV 3rd, Tambay AV, Wyatt SB, et al. The triglyceride/high-density lipoprotein cholesterol ratio fails to predict insulin resistance in African-American women: an analysis of Jackson heart study. Metab Syndr Relat Disord. 2010;8:511–4.

  24. 24.

    Arthur FK, Adu-Frimpong M, Osei-Yeboah J, Mensah FO, Owusu L. Prediction of metabolic syndrome among postmenopausal Ghanaian women using obesity and atherogenic markers. Lipids Health Dis. 2012;11:101. https://doi.org/10.1186/1476-511X-11-101.

  25. 25.

    Liang H, Chen X, Chen Q, Wang Y, Wu X, Li Y, et al. The metabolic syndrome among postmenopausal women in rural Canton: prevalence, associated factors, and the optimal obesity and atherogenic indices. PLoS One. 2013;8(9):e74121. https://doi.org/10.1371/journal.pone.0074121.

  26. 26.

    Salazar MR, Carbajal HA, Espeche WG, Leiva Sisnieguez CE, Balbín E, Dulbecco CA, et al. Relation among the plasma triglyceride/high-density lipoprotein cholesterol concentration ratio, insulin resistance, and associated cardio-metabolic risk factors in men and women. Am J Cardiol. 2012;109:1749–53.

  27. 27.

    Chen BD, He CH, Ma YT, Yang YN, Liu F, Pan S, et al. Best anthropometric and atherogenic predictors of metabolic syndrome in the Chinese Han population in Xinjiang: The Cardiovascular Risk Survey. Ann Nutr Metab. 2014;65:280–8.

  28. 28.

    Gasevic D, Frohlich J, Mancini GBJ, Lear SA. Clinical usefulness of lipid ratios to identify men and women with metabolic syndrome: a cross-sectional study. Lipids Health Dis. 2014;13:159. https://doi.org/10.1186/1476-511X-13-159.

  29. 29.

    Unger G, Benozzi SF, Perruzza F, Pennacchiotti GL. Triglycerides and glucose index: a useful indicator of insulin resistance. Endocrinol Nutr. 2014;61:533–40.

  30. 30.

    Zhang L, Chen S, Deng A, Liu X, Liang Y, Shao X, et al. Association between lipid ratios and insulin resistance in a Chinese population. PLoS One. 2015;10(1):e0116110. https://doi.org/10.1371/journal.pone.0116110.

  31. 31.

    Chen X, He C, Ma Y, Yang Y, Liu F, Ma X, et al. Association of metabolic syndrome with various anthropometric and atherogenic parameters in the Kazakh population in China. Lipids Health Dis. 2016;15:166. https://doi.org/10.1186/s12944-016-0338-9.

  32. 32.

    Gharipour M, Sadeghi M, Dianatkhah M, Nezafati P, Talaie M, Oveisgharan S, et al. Comparison between European and Iranian cutoff points of triglyceride/high-density lipoprotein cholesterol concentrations in predicting cardiovascular disease outcomes. J Clin Lipidol. 2016;10:143–9.

  33. 33.

    Li HY, Chen BD, Ma YT, Yang YN, Ma X, Liu F, et al. Optimal cutoff of the triglyceride to high-density lipoprotein cholesterol ratio to detect cardiovascular risk factors among Han adults in Xinjiang. J Health Popul Nutr. 2016;35(1):30. https://doi.org/10.1186/s41043-016-0067-8.

  34. 34.

    Paulmichl K, Hatunic M, Højlund K, Jotic A, Krebs M, Mitrakou A, et al. Modification and validation of the triglyceride-to-HDL cholesterol ratio as a surrogate of insulin sensitivity in white juveniles and adults without diabetes mellitus: the single point insulin sensitivity estimator (SPISE). Clin Chem. 2016;62:1211–9.

  35. 35.

    Song Q, Liu X, Wang A, Wang Y, Zhou Y, Zhou W, et al. Associations between non-traditional lipid measures and risk for type 2 diabetes mellitus in a Chinese community population: a cross-sectional study. Lipids Health Dis. 2016;15:70. https://doi.org/10.1186/s12944-016-0239-y.

  36. 36.

    Abbasian M, Delvarianzadeh M, Ebrahimi H, Khosravi F. Lipid ratio as a suitable tool to identify individuals with MetS risk: a case-control study. Diabetes Metab Syndr. 2017;11(Suppl 1):S15–9.

  37. 37.

    Kang B, Yang Y, Lee EY, Yang HK, Kim HS, Lim SY, et al. Triglycerides/glucose index is a useful surrogate marker of insulin resistance among adolescents. Int J Obes. 2017;41:789–92.

  38. 38.

    Deng QW, Li S, Wang H, Zuo L, Zhang HQ, Gu ZT, et al. The short-term prognostic value of the triglyceride-to-high-density lipoprotein cholesterol ratio in acute ischemic stroke. Aging Dis. 2018;9:498–506.

  39. 39.

    Anonymous. Metabolic syndrome-definition and diagnostic criteria in Japan. J Jpn Soc Inter Med. 2005;94:794–809 (in Japanese).

  40. 40.

    Hsieh SD, Muto T. Metabolic syndrome in Japanese men and women with special reference to the anthropometric criteria for the assessment of obesity: proposal to use the waist-to-height ratio. Prev Med. 2006;42:135–9.

  41. 41.

    Lee CM, Huxley RR, Wildman RP, Woodward M. Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis. J Clin Epidemiol. 2008;61:646–53.

  42. 42.

    Gruson E, Montaye M, Kee F, Wagner A, Bingham A, Ruidavets JB, et al. Anthropometric assessment of abdominal obesity and coronary heart disease risk in men: the PRIME study. Heart. 2010;96:136–40.

  43. 43.

    Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev. 2012;13:275–86.

  44. 44.

    The Committee of Japan Diabetes Society on the diagnostic criteria of diabetes mellitus. Report of the committee on the classification and diagnostic criteria of diabetes mellitus. J Japan Diab Soc. 2010;53:450–67 in Japanese.

  45. 45.

    Anonymous: American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(Suppl 1):S62–9.

  46. 46.

    Steyerberg EW, Harrell FE Jr, Borsboom GJJM, Eijkemans MJC, Vergouwe Y, Habbema JDF. Internal validation of predictive models: Efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54:774–81.

  47. 47.

    Carr MC, Brunzell JD. Abdominal obesity and dyslipidemia in the metabolic syndrome: Importance of type 2 diabetes and familial combined hyperlipidemia in coronary artery disease risk. J Clin Endocrinol Metab. 2004;89:2601–7.

  48. 48.

    Ghandehari H, Kamal-Bahl S, Wong ND. Prevalence and extent of dyslipidemia and recommended lipid levels in US adults with and without cardiovascular comorbidities: the National Health and Nutrition Examination Survey 2003-2004. Am Heart J. 2008;156:112–9.

Download references

Acknowledgements

None.

Funding

This work was supported by a Grant-in-Aid for Scientific Research (No. 17H02184) from the Japan Society for the Promotion of Science.

Author information

IW and TD designed the project and performed data analysis. IW wrote the manuscript. All authors reviewed and edited the manuscript. All authors read and approved the final manuscript.

Correspondence to Ichiro Wakabayashi.

Ethics declarations

Ethics approval and consent to participate

The study was performed in accordance with the Declaration of Helsinki (2000) and was approved by the Hyogo College of Medicine Ethics Committee (No. 3003 in 2018).

Consent for publication

All authors approved for publication this final version of the article.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wakabayashi, I., Daimon, T. Comparison of discrimination for cardio-metabolic risk by different cut-off values of the ratio of triglycerides to HDL cholesterol. Lipids Health Dis 18, 156 (2019) doi:10.1186/s12944-019-1098-0

Download citation

Keywords

  • Cardiovascular disease
  • Cut-off values
  • Multiple risk factors
  • Receiver operating characteristic
  • Triglycerides-to-HDL cholesterol ratio