The non-linear link between non-high-density lipoprotein to high-density lipoprotein ratio and the risk of stroke in middle-aged and older adults in Chinese: a prospective cohort study from the China health and retirement longitudinal study

Objective

This study aims to assess the association between the non-HDL-c/HDL-c ratio and stroke risk among middle-aged and older adults participating in the China Health and Retirement Longitudinal Study (CHARLS).

Methods

This study conducted a prospective cohort analysis, enrolling a total of 10,183 participants who met the designated criteria from CHARLS between 2011 and 2012. We then used the Cox proportional-hazards regression model to explore the relationship between baseline non-HDL-c/HDL-c ratio and stroke risk. Using a Cox proportional hazards regression with cubic spline function, we were able to identify the non-linear relationship between the non-HDL-c/HDL-c ratio and stroke occurrence. A series of sensitivity analyses were also carried out.

Results

The average age of the participants included in this study was 59.16 ± 9.35 years, and 4,735 individuals (46.68%) were male. Over a median follow-up period of 7.0 years, a total of 1,191 people (11.70%) experienced a stroke. Using a Cox proportional hazards regression model that was fully adjusted, we found no statistically significant correlation between the non-HDL-c/HDL-c ratio and the risk of stroke (HR=1.022; 95% CI 0.964, 1.083). Nevertheless, we did observe a non-linear relationship and saturation effect between the non-HDL-c/HDL-c ratio and stroke. Employing a two-piece Cox proportional hazards regression model and a recursive algorithm, we determined an inflection point of 2.685 for the non-HDL-c/HDL-c ratio. In instances where the non-HDL-c/HDL-c ratio fell below 2.685, for every 1-unit decrease in the non-HDL-c/HDL-c ratio, the likelihood of stroke decreased by 21.4% (HR=1.214, 95% CI: 1.039-1.418). In contrast, when the non-HDL-c/HDL-c ratio exceeded 2.685, there was no statistically significant change in the risk of stroke for each unit decrease in the non-HDL-c/HDL-c ratio (HR: 0.967, 95% CI: 0.897-1.042). The consistency of these findings across multiple sensitivity analyses suggests their robustness.

Conclusion

This study unveils a non-linear relationship between the non-HDL-c/HDL-c ratio and stroke risk in middle-aged and older adults in China. Specifically, when the non-HDL-c/HDL-c ratio was below 2.685, a significant and clearly positive association with stroke risk was observed. Additionally, maintaining the non-HDL-c/HDL-c ratio below 2.685 could potentially lead to a substantial reduction in the risk of stroke.

Sex Differences in the Association Between AST/ALT and Incidence of Type 2 Diabetes in Japanese Patients with Nonalcoholic Fatty Liver Disease: A Retrospective Cohort Study

OBJECTIVES/INTRODUCTION

The purpose of the current study was to investigate the association between Aspartate Transaminase (AST)/Alanine transaminase(ALT) and type 2 diabetes (T2DM) in nonalcoholic fatty liver disease (NAFLD) patients and to determine whether there were sex differences.

METHODS

In the retrospective study, we collected data on NAFLD patients (1, 896 men and 465 women) at Murakami Memorial Hospital from 2004 to 2015. Data were stratified by sex to investigate the association between AST/ALT and T2DM incidence by sex. Multiple regression analysis, smooth curve fitting model and subgroup analysis were used to determine the correlation, non-linear relationship and threshold effect between AST/ALT and T2DM.

RESULTS

In our study, 157 men and 40 women developed T2DM at follow-up. After adjusting for risk factors, AST/ALT was significantly associated with T2DM in men with NAFLD but not in women with NAFLD. The risk of T2DM increased as the AST/ALT ratio decreased. Besides, in male NAFLD patients, AST/ALT showed a non-linear relationship with T2DM, with an inflection point value of 0.964. When the AST to ALT ratio was below the threshold (AST/ALT <0.964), AST/ALT was significantly negatively associated with T2DM (HR = 0.177, 95% CI 0.055-0.568; P = 0.0036). In contrast, when AST/ALT >0.964, no significant association was found (HR = 3.174, 95% CI 0.345-29.167; P = 0.3074). Moreover, subgroup analysis showed that GGT could alter the relationship between AST/ALT and T2DM. In the group with GGT ≤ 40, AST/ALT was strongly associated with T2DM (HR = 0.24, 95% CI 0.09-0.66; P = 0.0059).

CONCLUSIONS

These results suggested that there were sex differences in the association between AST/ALT and T2DM in NAFLD participants. A non-linear association between AST/ALT and T2DM was observed in males. AST/ALT in the normal GGT group (GGT ≤40) might better facilitate the early screening of T2DM.

Non-linear dose-response relationship between body mass index and stroke risk in middle-aged and elderly Chinese men: a nationwide Longitudinal Cohort Study from CHARLS

Objective

Body mass index (BMI) and stroke risk have been linked, but these findings are still debated. This study investigated the relationship between BMI and stroke risk in a middle-aged and elderly Chinese population.

Methods

This study used four waves of CHARLS data (2011, 2013, 2015, and 2018), including 12,161 participants. The CHARLS sample was obtained by multi-stage probability sampling and all participants were assessed by one-to-one interviews using a standardized questionnaire. We used a Cox proportional-hazards regression model to examine the relationship between BMI and stroke risk. We used Cox proportional hazards regression with cubic spline functions and smooth curve fitting to identify the non-linear relationship between them. A series of sensitivity analyses were also conducted.

Results

The multivariate Cox proportional hazards regression model identified a positive association between BMI and stroke risk (HR=1.025, 95% CI: 1.010-1.040). We also found a non-linear relationship between BMI and stroke incidence, with an inflection point at 26.63 kg/m2 for BMI. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 4.4% increase in stroke risk (HR=1.044, 95% CI: 1.019-1.069). We stratified individuals by gender to further investigate their association and found a particular non-linear relationship and saturation effect between BMI and stroke risk in men, with the inflection point at 25.94 kg/m2. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 7.6% increase in stroke risk (HR=1.076, 95% CI 1.034-1.119). The association was linear in women, with each 1 kg/m2 increase in BMI associated with a 2.1% increase in stroke risk (HR=1.021, 95% CI 1.002, 1.040).

Conclusion

In men, there was a specific non-linear association and saturation effect of BMI with stroke (inflection point of 25.94 kg/m2), while in women, there was none. When males had a BMI below 25.94 kg/m2, the risk of stroke was significantly and positively associated with BMI. By controlling BMI below 25.94 kg/m2 in men, a further decrease in BMI may promote a significant reduction in stroke risk.

Non-linear association of fasting C-peptide and uric acid levels with renal dysfunction based on restricted cubic spline in patients with type 2 diabetes: A real-world study

BACKGROUND

Previous studies had showed divergent findings on the associations of C-peptide and/or uric acid (UA) with renal dysfunction odds in patients with type 2 diabetes mellitus (T2DM). We hypothesized that there were non-linear relationships between C-peptide, UA and renal dysfunction odds. This study aimed to further investigate the relationships of different stratification of C-peptide and UA with renal dysfunction in patients with T2DM.

METHOD

We conducted a cross-sectional real-world observational study of 411 patients with T2DM. The levels of fasting C-peptide, 2h postprandial C-peptide, the ratio of fasting C-peptide to 2h postprandial C-peptide (C0/C2 ratio), UA and other characteristics were recorded. Restricted cubic spline (RCS) curves was performed to evaluated the associations of stratified C-peptide and UA with renal dysfunction odds.

RESULTS

Fasting C-peptide, C0/C2 ratio and UA were independently and significantly associated with renal dysfunction in patients with T2DM as assessed by multivariate analyses (p < 0.05). In especial, non-linear relationships with threshold effects were observed among fasting C-peptide, UA and renal dysfunction according to RCS analyses. Compared with patients with 0.28 ≤ fasting C-peptide ≤ 0.56 nmol/L, patients with fasting C-peptide < 0.28 nmol/L (OR = 1.38, p = 0.246) or fasting C-peptide > 0.56 nmol/L (OR = 1.85, p = 0.021) had relatively higher renal dysfunction odds after adjusting for confounding factors. Similarly, compared with patients with 276 ≤ UA ≤ 409 μmol/L, patients with UA < 276 μmol/L (OR = 1.32, p = 0.262) or UA > 409 μmol/L (OR = 6.24, p < 0.001) had relatively higher odds of renal dysfunction.

CONCLUSION

The renal dysfunction odds in patients with T2DM was non-linearly associated with the levels of serum fasting C-peptide and UA. Fasting C-peptide and UA might have the potential role in odds stratification of renal dysfunction.

Body mass index has a non-linear association with three-month outcomes in men with acute ischemic stroke: An analysis based on data from a prospective cohort study

Objective

Despite reports of a connection between body mass index (BMI) and stroke outcome, the findings remain debatable. In this investigation, we sought to determine whether BMI was associated with the probability of 3-month unfavorable outcomes in patients with acute ischemic stroke (AIS).

Methods

This is a second analysis based on a cohort study. 1,897 people with AIS who were treated at a hospital in South Korea from January 2010 to December 2016 were included in the study. The linear relationship between BMI and unfavorable outcomes for AIS patients was evaluated using a binary logistic regression model. The generalized additive model (GAM) and smoothed curve fitting (penalized spline approach) were employed to see if there was a non-linear association between BMI and unfavorable outcomes in patients with AIS.

Results

The binary logistic regression model did not detect any statistically significant correlation between BMI and unfavorable outcomes in AIS patients after controlling for variables. The association between them, however, was non-linear, with the BMI inflection point occurring at 23.07 kg/m2. Each 1 kg/m2 rise in BMI on the left side of the inflection point was linked to a 12% lower risk of unfavorable outcomes (OR= 0.88, 95% CI: 0.82 to 0.96, p = 0.003). We stratified the AIS patients by gender to further explore their relationship. The results showed a specific non-linear relationship and saturation effect of BMI (kg/m2) with 3-month unfavorable outcomes in male patients but not in female patients. The inflection point for BMI was 23.35 kg/m2. When BMI was below 23.35 kg/m2 in men with AIS, BMI was inversely associated with unfavorable outcomes (OR=0.89,95% CI:0.80-0.98).

Conclusion

A particular non-linear connection and saturation effect between BMI (kg/m2) and 3-month unfavorable outcomes were present in male patients with AIS but not in females. 23.35 kg/m2 was the BMI's inflection point. The probability of unfavorable outcomes was substantially and inversely associated with BMI in men with AIS when it was less than 23.35 kg/m2. Men with AIS should have a BMI of no less than 23.35 kg/m2 to reduce the probability of unfavorable outcomes following AIS.

Over the limit? Testing non-linear associations between alcohol outlets and young adults' alcohol consumption

INTRODUCTION AND AIMS

By specifying a threshold at which the number of liquor licences has the most impact on local populations, authorities can work to restrict licence approvals and help prevent alcohol-related harm.

DESIGN AND METHODS

Raine Study Generation 2 participants reported their alcohol intake at 22 years (n = 843) and liquor licences within 1600 m of participants' homes were mapped. Analyses examined associations between licences (all licences, on-premise licences, liquor stores) and alcohol intake (g ethanol per day). Two models were fitted: (i) forced a straight-line relationship; and (ii) allowed a curved relationship via restricted cubic splines.

RESULTS

The straight-line and curved models showed significant relationships with all licences (P = 0.002 and P = 0.002 respectively) and on-premise licences (P = 0.006 and P = 0.01 respectively), but not liquor stores (P = 0.065 and P = 0.13 respectively). The straight-line model indicated that alcohol consumption increased, on average, by 0.15 g per day for each additional licence and 0.17 g per day for each additional on-premise licence. The curved model indicated that consumption increased by around 0.4 g per day for each additional licence from 0 to 10, but increases were negligible for additional licences beyond 10. The curved model provided a better overall fit to the data than the straight-line model (R² 9.52% vs. 9.18%), but the improvement in fit did not quite reach statistical significance (P = 0.08). The curvature was similar, but less pronounced for on-premise licences (R² 9.11% vs. 8.95%; P = 0.23).

DISCUSSION AND CONCLUSIONS

Results suggest a possible saturation point at which additional licences have a smaller effect on the alcohol intake of 22-year-olds living in metropolitan Perth.

Ideal Standards, Acceptance, and Relationship Satisfaction: Latitudes of Differential Effects

We examined whether the relations of consistency between ideal standards and perceptions of a current romantic partner with partner acceptance and relationship satisfaction level off, or decelerate, above a threshold. We tested our hypothesis using a 3-year longitudinal data set collected from heterosexual newlywed couples. We used two indicators of consistency: pattern correspondence (within-person correlation between ideal standards and perceived partner ratings) and mean-level match (difference between ideal standards score and perceived partner score). Our results revealed that pattern correspondence had no relation with partner acceptance, but a positive linear/exponential association with relationship satisfaction. Mean-level match had a significant positive association with actor's acceptance and relationship satisfaction up to the point where perceived partner score equaled ideal standards score. Partner effects did not show a consistent pattern. The results suggest that the consistency between ideal standards and perceived partner attributes has a non-linear association with acceptance and relationship satisfaction, although the results were more conclusive for mean-level match.

Correlation and agreement: overview and clarification of competing concepts and measures

Summary: Agreement and correlation are widely-used concepts that assess the association between variables. Although similar and related, they represent completely different notions of association. Assessing agreement between variables assumes that the variables measure the same construct, while correlation of variables can be assessed for variables that measure completely different constructs. This conceptual difference requires the use of different statistical methods, and when assessing agreement or correlation, the statistical method may vary depending on the distribution of the data and the interest of the investigator. For example, the Pearson correlation, a popular measure of correlation between continuous variables, is only informative when applied to variables that have linear relationships; it may be non-informative or even misleading when applied to variables that are not linearly related. Likewise, the intraclass correlation, a popular measure of agreement between continuous variables, may not provide sufficient information for investigators if the nature of poor agreement is of interest. This report reviews the concepts of agreement and correlation and discusses differences in the application of several commonly used measures.

Hierarchical clustering of high-throughput expression data based on general dependences

High-throughput expression technologies, including gene expression array and liquid chromatography--mass spectrometry (LC-MS) and so on, measure thousands of features, i.e., genes or metabolites, on a continuous scale. In such data, both linear and nonlinear relations exist between features. Nonlinear relations can reflect critical regulation patterns in the biological system. However, they are not identified and utilized by traditional clustering methods based on linear associations. Clustering based on general dependences, i.e., both linear and nonlinear relations, is hampered by the high dimensionality and high noise level of the data. We developed a sensitive nonparametric measure of general dependence between (groups of) random variables in high dimensions. Based on this dependence measure, we developed a hierarchical clustering method. In simulation studies, the method outperformed correlation- and mutual information (MI)-based hierarchical clustering methods in clustering features with nonlinear dependences. We applied the method to a microarray data set measuring the gene expression in cell-cycle time series to show it generates biologically relevant results. The R code is available at http://userwww.service.emory.edu/~tyu8/GDHC.