Lipid accumulation product (LAP) as a potential index to predict risk of insulin resistance in young, non-obese Asian Indian males from Southern India: observations from hyperinsulinemic-euglycemic clamp studies

Association between lipid accumulation product index and chronic kidney disease: A systematic review and meta-analysis

Diabetes mellitus and lipid metabolism disorders are increasingly recognized as key contributors to the development of chronic kidney disease (CKD). The lipid accumulation product (LAP) index, a novel marker of lipid accumulation, has potential implications for CKD risk assessment. The present meta-analysis aimed to assess the association between LAP index and CKD, with an emphasis on varying impacts in diabetic and non-diabetic populations. A comprehensive search for relevant publications was performed using PubMed/MEDLINE, Scopus, Cochrane Library, ScienceDirect and Google Scholar databases, and a meta-analysis of 17 studies was performed to investigate the relationship between LAP index and CKD. The random-effects inverse-variance model employing the DerSimonian-Laird estimator for τ² was utilized to calculate pooled odds ratios (ORs). Diagnostic accuracy was assessed using summary receiver operating characteristic (ROC) curves, with calculations of the area under the ROC curve (AUROC), sensitivity, specificity, likelihood ratios and diagnostic OR. The pooled OR for the association between higher quintiles or tertiles of LAP index and CKD was 1.098 (95% CI: 1.043-1.152), with substantial heterogeneity (I²=91.2%) and evidence of publication bias. Subgroup analysis revealed a stronger association in non-diabetic (OR=2.422, 95% CI: 1.802-3.042) compared with diabetic patients (OR=1.018, 95% CI: 0.993-1.043). The diagnostic accuracy of LAP index for CKD was moderate (AUROC=0.64), with sensitivity and specificity estimates of 0.58 and 0.63, respectively. In conclusion, in the present study, LAP index demonstrated a modest but significant association with CKD, particularly in non-diabetic patients. Despite its moderate diagnostic accuracy, the LAP index could serve as a valuable tool in CKD risk stratification, particularly when integrated with other clinical markers.

Evaluating the lipid accumulation product index as a predictor for kidney stone prevalence: insights from NHANES 2007-2018

PURPOSE

This study aimed to explore the relationship between the lipid accumulation product (LAP) index and kidney stone prevalence, utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 2007 to 2018.

METHODS

An observational study was executed employing the NHANES dataset from 2007 to 2018. Analytical methods encompassed multivariate logistic regression, restricted cubic splines (RCS), subgroup analysis, and interaction tests. Predictions were made using the receiver operating characteristic (ROC) curve and the area under the curve (AUC) values.

RESULTS

The analysis included 9744 adults aged 20 years and older. Multivariate logistic regression identified a significant positive association between log2-transformed LAP (treated as a continuous variable) and kidney stone risk across all models, with odds ratios (ORs) exceeding 1 and p values less than 0.001. Categorically, ORs escalated with increasing LAP levels, indicating a dose-response relationship. The RCS analysis confirmed a linear positive correlation between log2-transformed LAP and kidney stone risk. Subgroup analyses revealed that the log2-transformed LAP-kidney stones relationship was consistent, unaffected by stratification across the examined variables. In addition, LAP index (AUC = 0.600) proved to be a more effective predictor of kidney stones compared to body mass index (AUC = 0.584).

CONCLUSION

Elevated LAP levels are positively correlated with a higher incidence of kidney stones, signifying its potential as a risk marker for this condition. Future research should investigate the mechanisms underlying this relationship. LAP can be used as a new anthropometric index to predict kidney stones, and its predictive ability is stronger than body mass index.

Optimal obesity- and lipid-related indices for predicting type 2 diabetes in middle-aged and elderly Chinese

To investigate the screening and predicting functions of obesity- and lipid-related indices for type 2 diabetes (T2D) in middle-aged and elderly Chinese, as well as the ideal predicted cut-off value. This study's data comes from the 2011 China Health and Retirement Longitudinal Study (CHARLS). A cross-sectional study design was used to investigate the relationship of T2D and 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride- glucose index (TyG index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The unadjusted and adjusted correlations between 13 indices and T2D were assessed using binary logistic regression analysis. The receiver operating characteristic curve (ROC) was used to determine the usefulness of anthropometric indices for screening for T2D and determining their cut‑off value, sensitivity, specificity, and area under the curve (AUC). The study comprised 9488 people aged 45 years or above in total, of whom 4354 (45.89%) were males and 5134 (54.11%) were females. Among them were 716 male cases of T2D (16.44%) and 870 female cases of T2D (16.95%). A total of 13 obesity- and lipid-related indices were independently associated with T2D risk after adjusted for confounding factors (P < 0.05). According to ROC analysis, the TyG index was the best predictor of T2D among males (AUC = 0.780, 95% CI 0.761, 0.799) and females (AUC = 0.782, 95% CI 0.764, 0.799). The AUC values of the 13 indicators were higher than 0.5, indicating that they have predictive values for T2D in middle-aged and elderly Chinese. The 13 obesity- and lipid-related indices can predict the risk of T2D in middle‑aged and elderly Chinese. Among 13 indicators, the TyG index is the best predictor of T2D in both males and females. TyG-WC, TyG-BMI, TyG-WHtR, LAP, and CVAI all outperformed BMI, WC, and WHtR in predicting T2D.

The Lipid Accumulation Product Index (LAP) and the Cardiometabolic Index (CMI) Are Useful for Predicting the Presence and Severity of Metabolic Syndrome in Adult Patients with Obesity

Background: The concomitant occurrence of obesity and metabolic syndrome (MetS) causes a significant worsening of a patient's clinical condition. Indexes that employ anthropometric measurements alone or associated with blood parameters have been investigated for their ability to identify MetS. This study aimed to evaluate the diagnostic accuracy of three of these indexes, the body adiposity index (BAI), the lipid accumulation product index (LAP), and the cardiometabolic index (CMI), in a cohort of 1912 adult subjects with obesity. Methods and Results: MetS was found in 62.3% of the enrolled subjects, with a higher prevalence in males (72.5%) than females (60.9%). Receiver operating characteristic (ROC) analysis was used to define which index performed better. The BAI was found to be the lowest-performing index, with an ROC area of 0.50, a sensitivity of 30.31%, a specificity of 74.48%, and a likelihood ratio of 1.19. On the contrary, the LAP and the CMI showed a comparable ROC area of 0.82. The LAP had a sensitivity of 63.06%, a specificity of 86.55%, and a likelihood ratio of 4.69, while the CMI had a sensitivity of 67.59%, specificity of 81.55%, and a likelihood ratio of 3.66. The analysis was also performed in the group divided into males and females, with overlapping results. Conclusions: The LAP and the CMI performed better than the BAI in detecting MetS both in the general population with obesity and in the male/female subgroups. In the future, it will be important to validate these useful diagnostic tools in order to employ them in clinical practices.

Cardiometabolic risk assessment: A school-based study in Brazilian adolescent

BACKGROUND AND AIMS

Recently, new indices combining routine and low-cost anthropometric and biochemical measurements have emerged. Among them, the visceral adiposity index (VAI) and lipid accumulation product (LAP) are being investigated for the prediction of altered blood pressure (BP) and insulin resistance (IR). Therefore, this study aimed to evaluate whether visceral adiposity index (VAI) and height-corrected lipid accumulation product (HLAP) are predictors of cardiometabolic risk in Brazilian adolescents.

METHODS AND RESULTS

Data were obtained from the Cardiovascular Risk in Adolescents (ERICA) study, a cross-sectional, national, multicenter, school-based survey conducted between 2013 and 2014 in Brazil. The sample consisted of 37,815 adolescents aged 12-17 years of both genders attending the last 3 years of elementary or secondary school from public and private schools located in 273 municipalities with more than 100,000 inhabitants. A Poisson regression was performed to verify associations between VAI and HLAP indices and the presence of altered BP and IR according to sex. In addition, receiver operating characteristic curve (ROC) analysis was applied to compare the predictive ability and determine the cut-off points of the VAI and HLAP indices in identifying cardiometabolic risk obtained by altered BP and IR. The prevalences of altered BP and IR were 24.49 % (95 % confidence interval [CI]: 23.14-25.87) and 24.22 % (95 % CI: 22.70-25.80), respectively.

CONCLUSIONS

The VAI and HLAP indices are good predictors of cardiometabolic risk in Brazilian adolescents. HLAP showed better performance in identifying insulin resistance in males.

Obesity- and lipid-related indices as a predictor of type 2 diabetes in a national cohort study

Objective

Type 2 diabetes mellitus (T2DM) remains a major and widespread public health concern throughout the world. The prevalence of T2DM in the elderly has risen to the top of the list of public health concerns. In this study, obesity- and lipid-related indices were used to predict T2DM in middle-aged and elderly Chinese adults.

Methods

The data came from the China Health and Retirement Longitudinal Study (CHARLS), including 7902 middle-aged and elderly participants aged 45 years or above. The study assessed the association of obesity- and lipid-related indices and T2DM by measuring 13 indicators, including body mass index (BMI), waist circumference(WC), waist-height ratio (WHtR), conicity index(CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The association of 13 obesity- and lipid-related indices with T2DM was investigated by binary logistic regression. Additionally, the predictive anthropometric index was evaluated, and the ideal cut-off value was established using the receiver operating characteristic (ROC) curve analysis and area under the curve (AUC).

Results

The study included 7902 participants, of whom 3638(46.04) and 4264(53.96) were male and female. The prevalence of T2DM in mid-aged and old adults in China was 9.02% in males and 9.15% in females. All the above 13 indicators show a modest predictive power (AUC>0.5), which was significant for predicting T2DM in adults (middle-aged and elderly people) in China (P<0.05). The results revealed that TyG-WHtR [AUC =0.600, 95%CI: 0.566-0.634] in males and in females [AUC =0.664, 95%CI: 0.636-0.691] was the best predictor of T2DM (P<0.05).

Conclusion

Most obesity- and lipid-related indices have important value in predicting T2DM. Our results can provide measures for the early identification of T2DM in mid-aged and elderly Chinese to reduce the prevalence of T2DM and improve health.

Understanding the predictive accuracy of the InsuTAG index over other surrogate indices in normoglycaemic, non-obese males from Southern India

We aimed to evaluate the predictive accuracy of InsuTAG index against M value of the hyperinsulinaemic-Euglycaemic clamp (HEC) procedure and fasting surrogate indices of insulin sensitivity/resistance in young, normoglycaemic, Asian Indian males. HEC studies were done in young (mean age 19.7 ± 1 years), non-obese (mean BMI 19.2 ± 2.6 kg/m2), normoglycemic Asian Indian males (n = 110) and the M value was calculated. Surrogate indices namely InsuTAG index, HOMA-IR, FG-IR, QUICKI and McAuley index were calculated. Pearson's correlation and ROC-AUC at 95% CI were applied. Significant negative correlation was observed for InsuTAG index with the M value (r - 0.23, p = 0.01), McAuley index (r - 0.65, p < 0.01), QUICKI (r - 0.34, p < 0.01) and FGIR (r - 0.35, p < 0.01). Significant positive correlations of InsuTAG index were observed for BMI and waist circumference. The ROC-AUC was higher for InsuTAG index (0.75) than FGIR (0.30), QUICKI (0.31), and McAuley index (0.20). The InsuTAG cut-off value ≥ 19.13 showed 66.7% sensitivity and 69.2% specificity in this study group.

Sex Difference in the Associations among Obesity-Related Indices with Hyperuricemia in a Large Taiwanese Population Study

Hyperuricemia has been linked with the development of diabetes, gout, kidney, and cardiovascular diseases. Although obesity is associated with hyperuricemia, data on sex differences in this association are scarce. Therefore, this study was conducted to explore sex differences in the correlations among various indices of obesity with hyperuricemia in Taiwan. Data were obtained from the Taiwan Biobank and included 122,067 participants. After excluding 179 participants with missing data, the remaining 121,888 participants (men: 43,790; women: 78,098) were enrolled. The prevalence rates of hyperuricemia (defined as serum uric acid >7.0/6.0 mg/dL in men/women) were 29.8% and 13.6%, respectively (p < 0.001). Multivariable analysis revealed high values of body shape index (ABSI), waist-to-height ratio (WHtR), waist-hip ratio (WHR), lipid accumulation product (LAP), conicity index (CI), visceral adiposity index (VAI), body adiposity index (BAI), abdominal volume index (AVI), body mass index (BMI), and body roundness index (BRI) were significantly associated with hyperuricemia in both the male and female participants (all p < 0.001). The interactions between sex and all 10 of these indices were significant (all p < 0.001) for hyperuricemia. In men, LAP had the highest area under the curve (0.669), followed by BMI (0.655), VAI (0.645), AVI (0.642), BRI (0.640), WHtR (0.633), BAI (0.605), WHR (0.599), CI (0.574), and ABSI (0.510). In women, LAP also had the highest area under the curve (0.754), followed by BMI (0.728), VAI (0.724), WHtR (0.721), BRI (0.720), AVI (0.713), WHR (0.676), BAI (0.673), CI (0.626), and ABSI (0.544). In conclusion, obesity-related indices were associated with hyperuricemia in this large Taiwanese study, and sex differences were found in these associations, with stronger associations in women than in men.

Lipid accumulation product is a better predictor of metabolic syndrome in Chinese adolescents: a cross-sectional study

Aim

Confirm and compare the degree of associations of non-traditional lipid profiles and metabolic syndrome (MetS) in Chinese adolescents, determine the lipid parameter with better predictive potential, and investigate their discriminatory power on MetS.

Methods

Medical measurements, including anthropometric measurements and biochemical blood tests, were undergone among a total sample of 1112 adolescents (564 boys and 548 girls) aged from 13 to 18 years. Univariate and multivariate logistic regression analyses were applied for assessing the relationships between the levels of traditional/non-traditional lipid profiles and MetS. We performed Receiver Operating Characteristic (ROC) analyses to mensurate the effectiveness of lipid accumulation product (LAP) on the diagnosis of MetS. Meanwhile, areas under the ROC curve and the cut-off values were calculated for MetS and its components.

Results

Univariate analysis showed that all our lipid profiles were closely associated with MetS (P< 0.05). LAP index showed the closest association with MetS than the other lipid profiles. Additionally, ROC analyses indicated that the LAP index showed sufficient capabilities to identify adolescents with MetS and its components.

Conclusion

The LAP index is a simple and efficient tool to identify individuals with MetS in Chinese adolescents.

Predicting depressive symptom by cardiometabolic indicators in mid-aged and older adults in China: a population-based cross-sectional study

Objective

Depressive symptom is a serious mental illness often accompanied by physical and emotional problems. The prevalence of depressive symptom in older adults has become an increasingly important public health priority. Our study used cardiometabolic indicators to predict depressive symptom in middle-aged and older adults in China.

Methods

The data came from the China Health and Retirement Longitudinal Study 2011 (CHARLS2011), which was a cross-sectional study. The analytic sample included 8,942 participants aged 45 years or above. The study evaluated the relationship between cardiometabolic indicators and depression by measuring 13 indicators, including body mass index (BMI), waist circumference, waist-height ratio (WHtR), conicity index, visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-waist circumference, TyG-WHtR). Binary logistic regression analysis was used to examine the association between thirteen cardiometabolic indicators and depressive symptom. In addition, the receiver operating characteristic (ROC) curve analysis and area under curve (AUC) were used to evaluate the predictive anthropometric index and to determine the optimum cut-off value.

Results

The study included 8,942 participants, of whom 4,146 (46.37%) and 4,796 (53.63%) were male and female. The prevalence of depressive symptom in mid-aged and older adults in China was 41.12% in males and 55.05% in females. The results revealed that BMI [AUC = 0.440, 95%CI: 0.422-0.457], waist circumference [AUC = 0.443, 95%CI: 0.425-0.460], WHtR [AUC = 0.459, 95%CI: 0.441-0.476], LAP [AUC = 0.455, 95%CI: 0.437-0.472], BRI [AUC = 0.459, 95%CI: 0.441-0.476], CVAI [AUC = 0.449, 95%CI: 0.432-0.467], TyG-BMI [AUC = 0.447, 95%CI: 0.429-0.465], and TyG-waist circumference [AUC =0.452, 95%CI: 0.434-0.470] were weak predictors of depressive symptom (p < 0.05) in males. In females, BMI [AUC = 0.470, 95%CI: 0.453-0.486], LAP [AUC = 0.484, 95%CI: 0.467-0.500], TyG-BMI [AUC = 0.470, 95%CI: 0.454-0.487], and TyG-waist circumference [AUC =0.481, 95%CI: 0.465-0.498] were weak predictors of depressive symptom (p < 0.05). On the other side, VAI, ABSI, conicity index and TyG index could not predict depressive symptom in middle-aged and older adults.

Conclusion

Most cardiometabolic indicators have important value in predicting depressive symptom. Our results can provide measures for the early identification of depressive symptom in middle-aged and older adults in China to reduce the prevalence of depressive symptom and improve health.

Relationship Between Six Insulin Resistance Surrogates and Nonalcoholic Fatty Liver Disease Among Older Adults: A Cross-Sectional Study

Background

Non-alcoholic fatty liver disease (NAFLD) represents a large and growing public health problem. Insulin resistance (IR) plays a crucial role in the pathogenesis of NAFLD. The aim of this study was to determine the association of triglyceride-glucose (TyG) index, TyG index with body mass index (TyG-BMI), lipid accumulation product (LAP), visceral adiposity index (VAI), triglycerides/high-density lipoprotein cholesterol ratio (TG/HDL-c) and metabolic score for IR (METS-IR) with NAFLD in older adults and to compare the discriminatory abilities of these six IR surrogates for NAFLD.

Methods

This cross-sectional study included 72,225 subjects aged ≥60 years living in Xinzheng, Henan Province, from January 2021 to December 2021. The data were collected from the annual health examination dataset. Logistic regression models were used to examine the relationships between the six indicators and NAFLD risk. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different IR surrogates for NAFLD under the influence of potential risk factors.

Results

After adjusting for multiple covariates, compared with the first quintile, the odds ratios (ORs) and 95% confidence intervals (CIs) of the highest quintiles of TyG-BMI were the most obvious (OR:43.02, 95% CI:38.89-47.72), followed by the METS-IR (OR:34.49, 95% CI:31.41-37.95). Restricted cubic spline analysis reported that there were non-linear positive association and dose-response relationship between 6 IR surrogates and NAFLD risk. Compared with other IR-related indicators (LAP, TyG, TG/HDL-c and VAI), TyG-BMI showed the highest AUC (AUC:0.8059;95% CI:0.8025-0.8094). Additionally, METS-IR also had a high predictive performance for NAFLD, and the AUC was greater than 0.75 (AUC:0.7959;95% CI:0.7923-0.7994).

Conclusion

TyG-BMI and METS-IR had pronounced discrimination ability to NAFLD, which are recommended as complementary markers for the assessment of NAFLD risk both in clinic and in future epidemiological studies.

Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study

Objective

Metabolic syndrome is a common condition among middle-aged and elderly people. Recent studies have reported the association between obesity- and lipid-related indices and metabolic syndrome, but whether those conditions could predict metabolic syndrome is still inconsistent in a few longitudinal studies. In our study, we aimed to predict metabolic syndrome by obesity- and lipid-related indices in middle-aged and elderly Chinese adults.

Method

A national cohort study that consisted of 3,640 adults (≥45 years) was conducted. A total of 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), and triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, and TyG-WHtR), were recorded. Metabolic syndrome (MetS) was defined based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (2005). Participants were categorized into two groups according to the different sex. Binary logistic regression analyses were used to evaluate the associations between the 13 obesity- and lipid-related indices and MetS. Receiver operating characteristic (ROC) curve studies were used to identify the best predictor of MetS.

Results

A total of 13 obesity- and lipid-related indices were independently associated with MetS risk, even after adjustment for age, sex, educational status, marital status, current residence, history of drinking, history of smoking, taking activities, having regular exercises, and chronic diseases. The ROC analysis revealed that the 12 obesity- and lipid-related indices included in the study were able to discriminate MetS [area under the ROC curves (AUC > 0.6, P < 0.05)] and ABSI was not able to discriminate MetS [area under the ROC curves (AUC < 0.6, P > 0.05)]. The AUC of TyG-BMI was the highest in men, and that of CVAI was the highest in women. The cutoff values for men and women were 187.919 and 86.785, respectively. The AUCs of TyG-BMI, CVAI, TyG-WC, LAP, TyG-WHtR, BMI, WC, WHtR, BRI, VAI, TyG index, CI, and ABSI were 0.755, 0.752, 0.749, 0.745, 0.735, 0.732, 0.730, 0.710, 0.710, 0.674, 0.646, 0.622, and 0.537 for men, respectively. The AUCs of CVAI, LAP, TyG-WC, TyG-WHtR, TyG-BMI, WC, WHtR, BRI, BMI, VAI, TyG-index, CI, and ABSI were 0.687, 0.674, 0.674, 0.663, 0.656, 0.654, 0.645, 0.645, 0.638, 0.632, 0.607, 0.596, and 0.543 for women, respectively. The AUC value for WHtR was equal to that for BRI in predicting MetS. The AUC value for LAP was equal to that for TyG-WC in predicting MetS for women.

Conclusion

Among middle-aged and older adults, all obesity- and lipid-related indices, except ABSI, were able to predict MetS. In addition, in men, TyG-BMI is the best indicator to indicate MetS, and in women, CVAI is considered the best hand to indicate MetS. At the same time, TyG-BMI, TyG-WC, and TyG-WHtR performed better than BMI, WC, and WHtR in predicting MetS in both men and women. Therefore, the lipid-related index outperforms the obesity-related index in predicting MetS. In addition to CVAI, LAP showed a good predictive correlation, even more closely than lipid-related factors in predicting MetS in women. It is worth noting that ABSI performed poorly, was not statistically significant in either men or women, and was not predictive of MetS.

Comparison of Novel Biomarkers of Insulin Resistance With Homeostasis Model Assessment of Insulin Resistance, Its Correlation to Metabolic Syndrome in South Indian Population and Proposition of Population Specific Cutoffs for These Indices

Background The clustering of risk factors of cardiovascular disease (CVD) in individuals has been defined as Metabolic Syndrome (MetS). The major forerunner of all the components of MetS is Insulin Resistance (IR) which is measured by the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and requires the measurement of fasting plasma insulin levels. We attempted to study the performance of lipid-based biochemical markers of IR for the diagnosis of MetS and postulate a population-specific cutoff for these indices in the South Indian population. In this study, we analyzed three lipid-based indices, Triglyceride Glucose index (TyG index), triglyceride: high-Density Lipoprotein (TG:HDL) ratio, and lipid accumulation product (LAP).  Methods This was a cross-sectional study and included apparently healthy individuals presenting to our hospital for routine Master Health Checkup assessment and apparently healthy population residing in Kallindhiri, a village near Madurai. Based on the anthropometric measurements and blood investigations, Body Mass Index (BMI), Waist hip ratio, Waist height ratio, HOMA-IR, TyG index, TG:HDL ratio, and LAP were calculated. The diagnostic efficacy of these indices was compared against the presence of MetS based on the NCEP ATP III criteria. The receiver operating characteristic (ROC) Curve was performed to discriminate decision levels (cutoffs) of serum markers in early diagnosis of metabolic syndrome. The results were considered significant with a p-value less than 0.05. Results We included a total of 192 patients in our study, consisting of 36% (n=70) males and 63% (n=122) females. All the baseline characteristics except height, weight, and HDL cholesterol were comparable between the male and female groups. The values of HOMA-IR, TyG index, TG:HDL ratio, and LAP showed an increasing trend with the BMI. The mean values of HOMA-IR, TyG index, TG:HDL ratio and LAP was significantly higher in patients with MetS than in patients without MetS. Based on the ROC curve plotted for the data, a population-specific cutoff for these indices was computed. Our proposed cutoff for the South Indian population for HOMA-IR is 1.23, for TyG index is 4.65, for TG:HDL ratio is 3.44 in males and 2.6 in females and for LAP is 43.81 Conclusion The cutoffs for the novel indices of insulin resistance which have been previously studied in Caucasian populations cannot be applied to Indian populations due to distinct ethnic characteristics. The diagnostic accuracy of these novel lipid-based biomarkers of Insulin Resistance is better than the biochemical gold standard of HOMA-IR based on the ROC curve. We propose the usage of these population-specific cutoffs in routine clinical practice for early diagnosis of metabolic syndrome.

Cross-sectional and longitudinal associations between lipid accumulation product and hyperuricemia

BACKGROUND AND AIMS

Lipid accumulation product (LAP) is a novel, sex-specific, index-describing lipid over accumulation. Previous studies used baseline LAP for predicting hyperuricaemia; however, the relationship between them is unclear. We aimed to investigate the relationship between LAP and the risk of hyperuricaemia in the Central Chinese population.

METHODS AND RESULTS

This large-scale observational study comprised a cross-sectional population sample and a prospective cohort of 44,294 healthy subjects. This study examined the association between LAP and the risk of hyperuricaemia in the total sample and subgroups using multiple logistic regression analysis and multivariate cox proportional hazards model analysis. As a result, there was a dose-response relationship between LAP and the risk of hyperuricaemia. The prevalence of hyperuricaemia was 13.4% in the cross-sectional study. During 9 years of follow-up, hyperuricaemia occurred in 928 (19.8%) participants. The corresponding hazard ratios after multiple adjustments of hyperuricaemia in the second, third and fourth quartile were 1.34 (95% confidence interval [CI], 1.04-1.72), 2.01 (95% CI, 1.54-2.63), and 2.44 (95% CI, 1.80-3.30)-fold higher vs. the first quartile, respectively. Subgroup analyses showed that the association between LAP and the risk of hyperuricaemia was more pronounced in females, individuals≤49 years old and subjects with eGFR ≥60 ml/min/1.73 m².

CONCLUSION

LAP was positively related to the risk of hyperuricaemia in the Central Chinese population, particularly in women, individuals≤49 years old and adults with relatively normal renal function. These findings suggested the potential of LAP as an independent risk indicator in preventing hyperuricaemia.

Association between Health-Related Physical Fitness and Risk of Dyslipidemia in University Staff: A Cross-Sectional Study and a ROC Curve Analysis

Background: This study aimed to assess the relationship between dyslipidemia (DL) risk and health-related physical fitness (HPF) and evaluated the prognostic value of HPF for risk of DL. Methods: A total of 776 university staff members were recruited, of which 407 were females, and 369 males. Blood samples and HPF tests were collected from all participants after 12 h fasting. Results: The prevalence of DL was 41.77% and 51.49% in female and male university staff members, respectively, and there was no significant difference between genders (χ2 = 2.687, p = 0.101). According to the logistic regression analysis, age, male sex, GLU, hypertension, BMI, BF, WHtR, and LAP were significant risk factors for DL (p < 0.05), VCI and, SAR were significant protective factors for DL (p < 0.05), and SMI, GS, and VG were not significantly associated with the risk of DL. The area under the receiver-operating characteristic (ROC) curve (AUC) analysis indicated that, LAP (AUC: 0.730, 95CI%: 0.697–0.762), WHtR (AUC: 0.626, 95CI%: 0.590–0.660), and BMI (AUC: 0.599, 95CI%: 0.563–0.634) are valid predictors of DL, and LAP and WHtR perform better than BMI (Z = 8.074, p < 0.001) in predicting DL in male and female university staff members. Conclusion: The risk of DL is significantly related to body composition, cardiorespiratory fitness, and flexibility. LAP and WHtR perform better than BMI in predicting risk of DL in male and female university staff members.