Evaluation of the value of conventional and unconventional lipid parameters for predicting the risk of diabetes in a non-diabetic population

Update on the clinical applications of SGLTis: Insight to benefits beyond hypoglycemic and cardiorenal protection

Sodium glucose cotransporter inhibitor (SGLTi) drugs have been widely used in clinical practice. In addition to their benefits in hyperglycemia, heart failure (HF), and kidney disease, their effects on obesity, metabolic dysfunction-associated steatotic liver disease (MASLD, formerly named nonalcoholic fatty liver disease [NAFLD]), polycystic ovarian syndrome (PCOS), abnormal lipid metabolism, hyperuricemia, obstructive sleep apnea syndrome (OSAS), anemia, and syndrome of inappropriate antidiuresis (SIAD, formerly named syndrome of inappropriate antidiuretic hormone [SIADH]) have been explored. In this review, we searched the data of clinical randomized controlled trials (RCTs) and meta-analyses of SGLTis in patients with diabetes from the PubMed library between January 1, 2020, and February 1, 2024. According to our review, certain SGLTis exhibit relatively superior clinical safety and effectiveness for treating the abovementioned diseases. Proper utilization of SGLTis in these patients can provide additional medication options for patients with different disease scenarios. However, studies of SGLTis in these diseases are relatively rare, with shortcomings such as small sample sizes and short intervention periods. Therefore, further large-scale, long-term, well-designed studies are needed to clarify the findings.

Remnant cholesterol, but not other traditional lipids or lipid ratios, is independently and positively related to future diabetes risk in Chinese general population: A 3 year cohort study

AIMS

Very few cohort studies are available about the relation between remnant cholesterol (RC) and diabetes. Based on a prospective cohort survey, this research aimed at investigating if high RC was related to a future diabetes risk in the Chinese population, as well as to compare the association between RC, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglycerides (TG), TG/HDL-C, LDL-C/HDL-C, TC/HDL-C, and non-high-density lipoprotein cholesterol (non-HDL-C), and future diabetes risk.

MATERIALS AND METHODS

6,700 baseline normoglycemic participants of the REACTION study's Beijing center were recruited in 2011-2012 and followed up in 2015. Multivariate Cox regression analyses were performed to explore the relationship of RC, HDL-C, LDL-C, TC, TG, LDL-C/HDL-C, TG/HDL-C, TC/HDL-C, and non-HDL-C and a future diabetes risk.

RESULTS

After potential confounders were adjusted for, only RC (HR 1.134, 95% CI 1.016-1.267, P = 0.025) was positively related to a future diabetes risk, and only HDL-C (HR 0.728, 95% CI 0.578-0.918, P = 0.007) was negatively related to a future diabetes risk. The rest of the lipid parameters were not related to a future risk of diabetes. Sensitivity and stratification analyses revealed that the relation between RC and future diabetes risk was stable. RC and future diabetes risk were still positively correlated even when the HDL-C was ≥1.04 mmol/L (HR 1.167, 95% CI 1.050-1.297, P = 0.004).

CONCLUSIONS

It was RC, but not other lipid parameters, that was independently and positively related to a future risk of diabetes among the Chinese general population. Moreover, the relationship between RC and diabetes risk was stable, even with appropriate levels of HDL-C.

Association between RC/HDL-C ratio and risk of non-alcoholic fatty liver disease in the United States

Background

The occurrence of non-alcoholic fatty liver disease (NAFLD) is increasing worldwide. The link between serum remnant cholesterol (RC) to high-density lipoprotein cholesterol (HDL-C) ratio and NAFLD remains unclear. Therefore, we sought to clarify the relationship between the RC/HDL-C ratio and the NAFLD.

Methods

Data for our cross-sectional study came from the 2017-2018 National Health and Nutrition Examination Survey (NHANES) with 2,269 participants. Associations between RC/HDL-C levels and the prevalence of NAFLD and hepatic fibrosis were evaluated using adjusted multivariate logistic regression analyses. A generalized additive model examined the non-linear relationship between RC/HDL-C and the probability of developing NAFLD.

Results

Among 2,269 participants, 893 (39.36%) were diagnosed with NAFLD. In each of the three models, RC/HDL-C and NAFLD had a strong positive statistical relationship: model 1 (OR = 9.294, 95%CI: 6.785, 12.731), model 2 (OR = 7.450, 95%CI: 5.401, 10.278), and model 3 (OR = 2.734, 95%CI: 1.895, 3.944). In addition, the subgroup analysis by gender and BMI suggested that RC/HDL-C showed a positive correlation with NAFLD. The RC/HDL-C ratio was positively correlated with the degree of liver steatosis. There was an inverted U-shaped connection between the prevalence of NAFLD and RC/HDL-C, with an inflection point of 0.619 for all participants and 0.690 for men. Receiver operating characteristic (ROC) analysis showed that the predictive value of RC/HDL-C for NAFLD (area under the curve: 0.7139; 95%CI: 0.6923, 0.7354; P < 0.001), was better than traditional lipid parameters.

Conclusion

Increased RC/HDL-C levels are independently associated with an increased risk of NAFLD and the severity of liver steatosis in the American population. In addition, the RC/HDL-C ratio can be used as a simple and effective non-invasive biomarker to identify individuals with a high risk of NAFLD.

Elevated triglyceride/high-density lipoprotein-cholesterol ratio as a risk factor for progression to prediabetes: a 5-year retrospective cohort study in Japan

Purpose

The triglyceride-to-high-density lipoprotein-cholesterol (TG/HDL-C) ratio is considered an alternative marker for insulin resistance. This longitudinal retrospective study investigated the relationship between TG/HDL-C ratio and the risk of progression to prediabetes.

Methods

We investigated 24,604 Japanese participants (14,609 men and 9,995 women) who underwent annual medical health checkups in 2017 (baseline) and 2022. All participants had no diabetes and prediabetes at baseline. No lipid-lowering medications were taken during the follow-up period. Participants were divided into four groups according to the quartiles of TG/HDL-C ratio at baseline. Multivariable-adjusted Cox regression analysis was conducted to examine hazard ratios (HRs) of progression to prediabetes. Receiver operating characteristic curves were used to determine the optimal cutoff value of TG/HDL-C ratio for prediction of prediabetes.

Results

Compared with the lowest TG/HDL-C ratio quartile (Q1) group, the adjusted HRs (95% confidence intervals (CI)) of progression to prediabetes in the Q2, Q3, and Q4 groups, respectively, were 1.17 (0.92-1.47), 1.26 (1.01-1.56), and 1.77 (1.41-2.23) for men and 1.07 (0.60-1.11), 1.19 (1.08-1.29), and 1.58 (1.18-2.31) for women. For every 1 unit increase in TG/HDL-C ratio, the adjusted HRs (95% CI) for progression to prediabetes was 1.09 (1.04-1.13) in men and 1.10 (1.04-1.15) in women. The optimal TG/HDL-C ratio cutoffs were 1.71 and 0.97 in men and women, respectively, but the area under the curve was > 0.70 in both sexes.

Conclusion

High TG/HDL-C ratio is a risk factor for progression to prediabetes in Japanese men and women, but it had low discriminative ability in predicting prediabetes risk.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01329-8.

The association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio with type 2 diabetes mellitus: recent findings from NHANES 2007-2018

OBJECTIVE

This study aims to assess the relationship between NHHR (non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio) and Type 2 diabetes mellitus (T2DM) in US adults, using National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2018.

METHODS

This study explored the connection between NHHR and T2DM by analyzing a sample reflecting the adult population of the United States (n = 10,420; NHANES 2007-2018). NHHR was characterized as the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol. T2DM was defined based on clinical guidelines. This research used multivariable logistic models to examine the connection between NHHR and T2DM. Additionally, it included subgroup and interaction analyses to assess variations among different groups. Generalized additive models, smooth curve fitting, and threshold effect analysis were also employed to analyze the data further.

RESULTS

The study included 10,420 subjects, with 2160 diagnosed with T2DM and 8260 without. The weighted multivariate logistic regression model indicated an 8% higher probability of T2DM for each unit increase in NHHR (OR: 1.08, 95% CI: 1.01-1.15) after accounting for all covariates. Subgroup analysis outcomes were uniform across various categories, demonstrating a significant positive relationship between NHHR and T2DM. Interaction tests showed that the positive link between NHHR and T2DM remained consistent regardless of age, body mass index, smoking status, moderate recreational activities, hypertension, or stroke history, with all interaction P-values exceeding 0.05. However, participants' sex appeared to affect the magnitude of the connection between NHHR and T2DM (interaction P-value < 0.05). Also, a nonlinear association between NHHR and T2DM was discovered, featuring an inflection point at 1.50.

CONCLUSIONS

Our study suggests that an increase in NHHR may be correlated with a heightened likelihood of developing T2DM. Consequently, NHHR could potentially serve as a marker for estimating the probability of T2DM development.

Traditional and Non-Traditional Lipid Parameters in Relation to Parenchymal Hemorrhage Following Endovascular Treatment for Acute Ischemic Stroke in Anterior Circulation

Purpose

Lipid-lowering therapy is integral in acute ischemic stroke (AIS), yet the connection between lipid parameters and parenchymal hemorrhage (PH) after endovascular treatment (EVT) for AIS is not well-defined. This research aims to assess the association between various lipid parameters and the PH risk following EVT.

Patients and Methods

We examined a database of patients who underwent EVT for AIS between September 2021 and May 2023 retrospectively. Traditional and non-traditional lipid parameters were documented. PH was identified on dual energy computed tomography images within 48 h. We employed logistic regression analysis and restricted cubic splines to examine the association between various lipid parameters and the risk of PH. The predictive capacity of the lipid parameters for PH was evaluated by comparing the area under the curve.

Results

The study included 384 patients, 65 of whom (17.7%) developed PH. After adjusting for potential confounders, only triglyceride was associated with PH among the traditional lipid parameters, while all non-traditional lipid parameters were related to PH. Based on ROC curve, the ratio of remnant cholesterol to high-density lipoprotein cholesterol (RC/HDL-C) exhibited the highest predictive capability for PH. Furthermore, our analysis revealed a significant nonlinear correlation between triglyceride, non-high-density lipoprotein cholesterol, RC, RC/HDL-C and PH risk.

Conclusion

In assessing the risk of PH after EVT, non-traditional lipid parameters are often superior to traditional lipid parameters. It is recommended that routine evaluation of non-traditional lipid parameters could also be conducted in clinical practice as well.

Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort

BACKGROUND

Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk.

METHODS

We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes.

RESULTS

Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI.

CONCLUSION

Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

Use of lipid ratios to predict vascular target organ damage in youth

BACKGROUND

Elevated lipid levels are risk factors for early atherosclerosis. Lipid ratios have emerged as potentially stronger predictors of adverse cardiovascular changes and atherogenic cholesterol. Risk stratification in youth with obesity or type 2 diabetes may be improved by using lipid ratios. We sought to determine if lipid ratios would identify abnormalities in arterial structure and stiffness in adolescents and young adults.

METHODS

A total of 762 youth aged 10-24 years had laboratory, anthropometric, blood pressure, and carotid intima-media thickness and arterial stiffness data collected. Subjects were stratified into tertiles (low, mid, high) of lipid ratios and non-high-density lipoprotein cholesterol (HDL-C). Vascular outcomes by tertile were assessed by analyses of variance. General linear models were constructed for each lipid value and included demographics, risk factors, and vascular measures. Correlations between lipid markers, vascular measures, and low-density lipoprotein (LDL) particle size and number were conducted.

RESULTS

There was a progressive increase in arterial thickness and stiffness across all three lipid ratios and non-HDL-C. The triglyceride to HDL-C (TG/HDL-C) ratio remained an independent predictor of arterial thickness and stiffness after adjusting for other cardiovascular risk factors. TG/HDL-C had the highest correlations with arterial stiffness and small, dense LDL.

CONCLUSIONS

Arterial stiffness is increased in youth with high lipid ratios with TG/HDL-C being the most consistent marker of vascular changes. These data suggest that identification of high TG/HDL-C in these individuals may lead to earlier intervention to prevent atherosclerotic cardiovascular disease.

A nonlinear relationship between the triglycerides to high-density lipoprotein cholesterol ratio and stroke risk: an analysis based on data from the China Health and Retirement Longitudinal Study

OBJECTIVE

The connection between triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio and stroke risk is controversial. Our goal was to explore this relationship in individuals aged 45 and older enrolled in the China Health and Retirement Longitudinal Study (CHARLS).

METHODS

Our analysis encompassed 10,164 participants from the CHARLS cohorts. We applied the Cox proportional-hazards regression model to evaluate the potential correlation between the TG/HDL-C ratio and stroke incidence. Using a cubic spline function and smooth curve fitting within the Cox model allowed us to unearth a possible non-linear pattern in this relationship. We also conducted thorough sensitivity and subgroup analyses to deepen our understanding of the TG/HDL-C ratio's impact on stroke risk.

RESULTS

Adjusting for various risk factors, we observed a significant link between the TG/HDL-C ratio and increased stroke risk in individuals aged 45 and above (HR: 1.03, 95% CI 1.00-1.05, P = 0.0426). The relationship appeared non-linear, with an inflection at a TG/HDL-C ratio of 1.85. Ratios below this threshold indicated a heightened stroke risk (HR: 1.28, 95% CI 1.06-1.54, P = 0.0089), while ratios above it did not show a significant risk increase (HR: 1.01, 95% CI 0.98-1.04, P = 0.6738). Sensitivity analysis confirmed the robustness of these findings. Notably, non-smokers exhibited a stronger correlation between the TG/HDL-C ratio and stroke risk compared to past and current smokers.

CONCLUSION

Our investigation revealed a significant, yet non-linear, association between the TG/HDL-C ratio and the incidence of stroke among individuals aged 45 and above. Specifically, we found that stroke risk increased in correlation with TG/HDL-C ratio below the threshold of 1.85. These insights may guide healthcare providers in advising and developing more effective strategies for stroke prevention in this demographic.

Association of remnant cholesterol and newly diagnosed early-onset type 2 diabetes mellitus in Chinese population: A retrospective cross-sectional study

BACKGROUND

With the increasing incidence of diabetes worldwide, patients diagnosed with diabetes has been getting younger. Previous studies have shown that high remnant cholesterol (RC) level leads to an increased risk of cardiovascular disease events. However, the relationship between RC levels and newly diagnosed early-onset type 2 diabetes mellitus (T2DM) is unknown. This study aimed to explore the association between RC and newly diagnosed early-onset T2DM.

METHODS

A total of 606 patients newly diagnosed with early-onset T2DM and 619 gender-matched subjects with normal blood glucose levels were retrospectively enrolled in this study. All T2DM patients showed onset age of 18-40 years. Binary logistic regression analysis was performed to analyze independent risk factors and receiver operating characteristic (ROC) analysis was used to explore the predictive value of RC and other unconventional lipids. Moreover, the correlation between RC and insulin resistance in patients with newly diagnosed early-onset T2DM was also examined with binary logistic regression analysis and Spearman correlation analysis.

RESULTS

Increased RC level was an independent risk factor for early-onset T2DM (p < .05). The area under the curve on ROC analysis of RC was 0.805, 95% confidence interval (CI) was 0.781 ~ 0.826, sensitivity was 82.18% and specificity was 66.24%, which showed higher predictive value than those of triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and total cholesterol (TC)/HDL-C ratio. Cutoff value of RC was 0.32 mmol/L. Level of RC in early-onset T2DM patients with moderate or severe insulin resistance was significantly higher than that in patients with mild insulin resistance (p < .0001). No difference in RC levels was found between patients with moderate and severe insulin resistance (p > .05). RC was still correlated with insulin resistance after adjusting the conventional lipid parameters (TG, TC, HDL-C, and low-density lipoprotein cholesterol) using partial correlation analysis.

CONCLUSION

RC level was higher in patients with early-onset T2DM and was correlated to the degree of insulin resistance as well. Patients aged 18-40 years with RC >0.32 mmol/L showed an increased risk of developing T2DM.

Short-chain chlorinated paraffin (SCCP) exposure and type 2 diabetes risk: A population-based case-control study in East China

Exposure to persistent organic pollutants may be associated to type 2 diabetes, but the studies on associations between short-chain chlorinated paraffin (SCCP) exposure and type 2 diabetes risk in humans are still scarce. Here, we conducted a case-control study involving 344 participants in Shandong Province, East China, to explore the effects of SCCPs on type 2 diabetes risk and their correlations with glycemic biomarker and serum lipid parameters. SCCPs were detected in all serum samples with a median concentration of 24 ng mL-1 in cases and 19 ng mL-1 in controls. Exposure to C10-CPs, C11-CPs, and ΣSCCPs were positively associated with the risk of type 2 diabetes after adjusting for confounders. The associations remained consistent in stratified analyses but stronger in male participants and obese individuals. In the control group, there were significant and positive correlations between SCCP exposure and levels of total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-C), total lipid, and non-high-density lipoprotein-cholesterol. Significant joint effects on SCCP exposure and lipid parameters were observed in females when analyzed by the quantile-based g-computation model, and C10-CPs showed the highest contribution. Mediation analysis showed that LDL-C had significant mediation effects on the associations between C10-CPs, C11-CPs, and ΣSCCPs exposure and risk of type 2 diabetes. Moreover, TC and high-density lipoprotein-cholesterol were mediators in the relationship between C11-CPs and type 2 diabetes. Taken together, our study revealed that human exposure to SCCPs may increase the risk of type 2 diabetes and disrupt lipid metabolism.

Nonlinear relationship between untraditional lipid parameters and the risk of prediabetes: a large retrospective study based on Chinese adults

BACKGROUND

Abnormal lipid metabolism poses a risk for prediabetes. However, research on lipid parameters used to predict the risk of prediabetes is scarce, and the significance of traditional and untraditional lipid parameters remains unexplored in prediabetes. This study aimed to comprehensively evaluate the association between 12 lipid parameters and prediabetes and their diagnostic value.

METHODS

This cross-sectional study included data from 100,309 Chinese adults with normal baseline blood glucose levels. New onset of prediabetes was the outcome of concern. Untraditional lipid parameters were derived from traditional lipid parameters. Multivariate logistic regression and smooth curve fitting were used to examine the nonlinear relationship between lipid parameters and prediabetes. A two-piecewise linear regression model was used to identify the critical points of lipid parameters influencing the risk of prediabetes. The areas under the receiver operating characteristic curve estimated the predictive value of the lipid parameters.

RESULTS

A total of 12,352 participants (12.31%) were newly diagnosed with prediabetes. Following adjustments for confounding covariables, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol were negatively correlated with prediabetes risk. Conversely, total cholesterol, triglyceride (TG), lipoprotein combine index (LCI), atherogenic index of plasma (AIP), non-HDL-C, atherogenic coefficient, Castelli's index-I, remnant cholesterol (RC), and RC/HDL-C ratio displayed positive correlations. In younger adults, females, individuals with a family history of diabetes, and non-obese individuals, LCI, TG, and AIP exhibited higher predictive values for the onset of prediabetes compared to other lipid profiles.

CONCLUSION

Nonlinear associations were observed between untraditional lipid parameters and the risk of prediabetes. The predictive value of untraditional lipid parameters for prediabetes surpassed that of traditional lipid parameters, with LCI emerging as the most effective predictor for prediabetes.

Magnitude and time course of insulin resistance accumulation with the risk of cardiovascular disease: an 11-years cohort study

BACKGROUND

The risk of cardiovascular disease (CVD) depended on the magnitude and exposure duration of insulin resistance (IR). This study aimed to investigate the associations of cumulative metabolic score for IR (cumMETS-IR) with incident CVD, and to further explore the modulated effects of time course of METS-IR accumulation.

METHODS

We enrolled 47,270 participants without CVD and underwent three examinations during 2006-2010 from the Kailuan study. CumMETS-IR from 2006 to 2010 were calculated as the mean values of METS-IR between consecutive examinations multiplying by time intervals between visits. Time course of METS-IR accumulation was calculated as the slope of METS-IR versus time. Hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD risk were calculated with multivariable-adjusted Cox regressions.

RESULTS

During a median follow-up of 10.99 years, we identified 3184 cases of incident CVD. The risk of incident CVD increased with increasing cumMETS-IR (HR, 1.77; 95% CI 1.58-1.98 for the Q4 versus Q1 group), exposure duration (HR, 1.60; 95% CI 1.45-1.77 for 6 years versus 0 years), and cumulative burden (HR, 1.49; 95% CI 1.37-1.61 for burden ≥ 0 versus < 0). A positive slope was associated with 14% higher risk of CVD (HR, 1.14; 95% CI 1.07-1.22). When combining cumMETS-IR and slope, those with cumMETS-IR ≥ median (142.78) and slope ≥ 0 had the highest risk of CVD (HR,1.38; 95% CI 1.25-1.53).

CONCLUSIONS

The risk of CVD increased with elevated cumMETS-IR and an increasing trend over time, emphasizing the importance of maintaining optimal METS-IR levels across life span.

Independent and interactive associations between greenness and ambient pollutants on novel glycolipid metabolism biomarkers: A national repeated measurement study

This study aims to investigate the independent and interactive effects of greenness and ambient pollutants on novel glycolipid metabolism biomarkers. A repeated national cohort study was conducted among 5085 adults from 150 counties/districts across China, with levels of novel glycolipid metabolism biomarkers of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c measured. Exposure levels of greenness and ambient pollutants (including PM1, PM2.5, PM10, and NO2) for each participant were determined based on their residential location. Linear mixed-effect and interactive models were used to evaluate the independent and interactive effects between greenness and ambient pollutants on the four novel glycolipid metabolism biomarkers. In the main models, the changes [β (95% CIs)] of TyG index, TG/HDL-c, TC/HDL-c, and non-HDL-c were -0.021 (-0.036, -0.007), -0.120 (-0.175, -0.066), -0.092 (-0.122, -0.062), and -0.445 (-1.370, 0.480) for every 0.1 increase in NDVI, and were 0.004 (0.003, 0.005), 0.014 (0.009, 0.019), 0.009 (0.006, 0.011), and 0.067 (-0.019, 0.154) for every 1 μg/m3 increase in PM1. Results of interactive analyses demonstrated that individuals living in low-polluted areas could get greater benefits from greenness than those living in highly-polluted areas. Additionally, the results of mediation analyses revealed that PM2.5 mediated 14.40% of the association between greenness and the TyG index. Further research is needed to validate our findings.

The Relationship Between Non-HDL-C /HDL-C Ratio (NHHR) and Vitamin D in Type 2 Diabetes Mellitus

Purpose

The objective of this research was to examine the relationship between non-HDL cholesterol/HDL cholesterol ratio (NHHR) and vitamin D in type 2 diabetes mellitus (T2DM).

Patients and Methods

This study enrolled 617 T2DM participants. Participants were separated into two groups: no vitamin D deficiency and vitamin D deficiency. Participants were split into two categories: individuals who had a high NHHR and those with a low NHHR, with the median NHHR serving as the cut-off. Eventually, the study participants were classified into two groups by gender, which were further classified into vitamin D deficient and non-vitamin D deficient groups.

Results

NHHR values were substantially greater in vitamin D deficient group than in the non-deficient group in both male and female T2DM patients (P<0.05). The high NHHR group displayed substantially lower vitamin D levels than the low NHHR group [16.21 (12.55,21.35) vs 19.05 (14.59,24.07), P<0.001]. NHHR was discovered to be negatively and independently associated with vitamin D levels, and there was no sex difference.

Conclusion

For the first time, our research revealed a negative relationship between NHHR and vitamin D in patients with T2DM.

Assessing temporal differences of baseline body mass index, waist circumference, and waist-height ratio in predicting future diabetes

Objective

Obesity is the prominent modifiable risk factor known to influence the occurrence and progression of diabetes other than age, and the objective of this study was to evaluate and compare the predictive value of three simple baseline anthropometric indicators of obesity, body mass index (BMI), waist circumference (WC), and waist-height ratio (WHtR), for the occurrence of diabetes at different time points in the future.

Methods

The study subjects were 12,823 individuals with normoglycemic at baseline who underwent health screening and had measurements of BMI, WC, and WHtR. The outcome of interest was new-onset diabetes during follow-up. Time-dependent receiver operator characteristics (ROC) curves of baseline BMI, WC, and WHtR for predicting the risk of diabetes in the next 2 to 12 years were constructed and their area under the ROC curves (AUCs) and corresponding optimal threshold values were calculated for each time point, which were used to compare the accuracy and stability of the above three indicators for predicting the occurrence of diabetes in different future periods.

Results

During a median follow-up period of 7.02 years, with a maximum follow-up of 13 years, 320 new-onset diabetes were recorded. After adjusting for confounders and comparing standardized hazard ratios (HRs), WC was shown to be the best simple anthropometric indicator of obesity reflecting diabetes risk in all models, followed by WHtR. Time-dependent ROC analysis showed that WC had the highest AUC in predicting the occurrence of diabetes in the short term (2-5 years), and WHtR had the highest AUC in predicting the occurrence of diabetes in the medium to long term (6-12 years), while in any time point, both WC and WHtR had higher AUC than BMI in predicting future diabetes. In addition, we found relatively larger fluctuations in the thresholds of BMI and WC for predicting diabetes over time, while the thresholds of WHtR consistently remained between 0.47-0.50; comparatively speaking, WHtR may have greater application value in predicting future diabetes.

Conclusions

Our analysis sustained that central obesity is a more important predictor of diabetes, and in clinical practice, we proposed measuring WHtR as a useful tool for predicting future diabetes.

Association of Advanced Lipoprotein Subpopulation Profiles with Insulin Resistance and Inflammation in Patients with Type 2 Diabetes Mellitus

Plasma lipoproteins exist as several subpopulations with distinct particle number and size that are not fully reflected in the conventional lipid panel. In this study, we sought to quantify lipoprotein subpopulations in patients with type 2 diabetes mellitus (T2DM) to determine whether specific lipoprotein subpopulations are associated with insulin resistance and inflammation markers. The study included 57 patients with T2DM (age, 61.14 ± 9.99 years; HbA1c, 8.66 ± 1.60%; mean body mass index, 35.15 ± 6.65 kg/m²). Plasma lipoprotein particles number and size were determined by nuclear magnetic resonance spectroscopy. Associations of different lipoprotein subpopulations with lipoprotein insulin resistance (LPIR) score and glycoprotein acetylation (GlycA) were assessed using multi-regression analysis. In stepwise regression analysis, VLDL and HDL large particle number and size showed the strongest associations with LPIR (R² = 0.960; p = 0.0001), whereas the concentrations of the small VLDL and HDL particles were associated with GlycA (R² = 0.190; p = 0.008 and p = 0.049, respectively). In adjusted multi-regression analysis, small and large VLDL particles and all sizes of lipoproteins independently predicted LPIR, whereas only the number of small LDL particles predicted GlycA. Conventional markers HbA1c and Hs-CRP did not exhibit any significant association with lipoprotein subpopulations. Our data suggest that monitoring insulin resistance-induced changes in lipoprotein subpopulations in T2DM might help to identify novel biomarkers that can be useful for effective clinical intervention.

The longitudinal association of remnant cholesterol with diabetes in middle-aged and elderly Chinese: A nationwide population-based cohort study

BACKGROUND AND AIMS

The association between remnant cholesterol (RC) and diabetes remains unclear in Chinese.

METHODS AND RESULTS

We used the data of 9464 Chinese adults aged ≥45 years from the China Health and Retirement Longitudinal Study (CHARLS). Estimated RC level was calculated as total cholesterol minus high-density lipoprotein cholesterol minus low-density lipoprotein cholesterol. Cox proportional hazard models and restricted cubic spline models were used to assess the relationships between RC and diabetes.

RESULTS

After 6 years of follow-up, a total of 777 respondents experienced new-onset diabetes. In multivariable-adjusted analyses, the adjusted hazard ratios (95 % confidence intervals) for the highest versus lowest quartile of RC was 1.45 (1.19-1.75) for risk of diabetes, and each 1-SD increase of RC (19.52 mg/dl) was associated with 9 % (HRs = 1.09; 1.03-1.15) increased risk of diabetes. There were also significant linear associations between RC level and diabetes (P for linearity <0.001).

CONCLUSION

Elevated RC levels were positively associated with increased risk of diabetes in Chinese adult population, suggesting that RC could be considered as a preferential predictor and treatment target of diabetes in Chinese population. Future prospective studies are needed to verify our findings and to assess the effect of RC-lowering interventions in diabetes prevention.

NHHR: An Important Independent Risk Factor for Patients with STEMI

Background

In this study, we investigated whether the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) is associated with the development of acute ST-segment elevation myocardial infarction (STEMI).

Methods

889 STEMI patients who had not previously received lipid-lowering therapy were selected as the test group and 120 patients with less than 50% coronary stenosis were selected as the control group. All patients completed the related blood tests the morning after admission, and Gensini scores were based on coronary angiography results. The differences were compared using a t-test, rank sum test, chi-square test and logistic regression analysis. Linear regression analysis was used to study the correlation between variables. Receiver Operating Characteristic (ROC) curves were used to validate the predictive value of NHHR for STEMI.

Results

NHHR was shown to be a significant independent risk factor for STEMI according to binary logistic regression analysis (OR = 0.163, 95% CI: 0.065-0.411, p < 0.05). There were shown to be differences in the NHHR depending on the gender of the STEMI patients (z = -1.663, p < 0.1). Linear regression analysis revealed a stronger correlation between NHHR and Gensini score (r = 0.394, p < 0.05) in the test group. Finally, we demonstrated that NHHR has a good predictive effect on STEMI, using an ROC curve (Area Under Curve (AUC): 0.818, 95% CI: 0.777-0.859, p < 0.05).

Conclusions

NHHR is a good predictor of coronary artery disease severity in STEMI patients and an important independent risk factor for STEMI, especially for patients who have not received lipid-lowering treatment in the past, and male STEMI patients need more stringent lipids management than female STEMI patients.

Relationship of the metabolic score for insulin resistance and the risk of stroke in patients with hypertension: A cohort study

BACKGROUND

The current status of the dose-response relationship between the metabolic score for insulin resistance (METS-IR) and new-onset stroke in hypertensive patients and its subtypes is unclear. This study aimed to determine the association between METS-IR and incident stroke and its subtypes within a cohort of Chinese hypertensive patients.

METHODS

A total of 14032 hospitalized patients with hypertension from January 1, 2010, to December 31, 2021, were included in this retrospective cohort study. Cox models and restricted cubic splines were applied to determine the association between METS-IR and the risk of stroke.

RESULTS

During a median follow-up of 4.80 years, 1067 incident stroke cases occurred. Patients in the highest quartile group of METS-IR levels exhibited a higher risk of stroke (HR, 1.80; 95% CI, 1.50-2.17) and ischemic stroke (HR, 1.96; 95% CI, 1.60-2.42) than those in the lowest quartile group. However, no significant associations were observed between METS-IR and the risk of hemorrhagic stroke. Restricted cubic spline analysis suggested a nearly J-shaped association between METS-IR and risk of stroke and ischemic stroke (P for nonlinearity < 0.001). METS-IR did produce a significant improvement in the C statistic when added to the basic model (from 0.637 to 0.664, P < 0.001). Notably, the addition of METS-IR to the basic model resulted in a significant improvement in predicting incident total stroke and ischemic stroke.

CONCLUSIONS

This cohort study suggests a relationship between METS-IR and the risk of stroke and ischemic stroke. Further studies are required to elucidate the underlying mechanisms.