The association between vitamin D3 and diabetes in both hyperuricemia and non-hyperuricemia populations

Nonlinear relationship between oxidative balance score and hyperuricemia: analyses of NHANES 2007-2018

BACKGROUND

Limited data regarding the correlation between oxidative balance score (OBS) and hyperuricemia highlights the necessity for thorough investigations. This study aims to examine the link between OBS, which incorporates dietary and lifestyle factors, and the occurrence of hyperuricemia.

METHODS

We conducted a cross-sectional study involving 13,636 participants from the 2007-2018 National Health and Nutrition Examination Survey (NHANES). The oxidative balance score (OBS) was determined based on four lifestyle factors and sixteen dietary nutrients. We assessed the levels of serum uric acid (SUA) and the occurrence of hyperuricemia as outcomes. Weighted logistic regression and linear models were used for statistical analysis, using Restricted Cubic Splines (RCS) to examine potential nonlinear associations. Subgroup analysis and sensitivity assessments were performed to identify any variations and ensure the robustness of the findings.

RESULTS

Higher OBS was consistently correlated with decreased SUA levels and a reduced prevalence of hyperuricemia. RCS highlighted a significant negative nonlinear association, particularly in females. Subgroup analysis revealed gender-based differences and interactive correlation, providing additional insights regarding OBS and hyperuricemia relationship.

CONCLUSION

This study underscores a robust negative correlation between OBS and SUA levels as well as the incidence of hyperuricemia, emphasizing the importance of dietary and lifestyle factors. Incorporating RCS, subgroup analysis, and sensitivity assessments enhances the depth of our findings, providing valuable insights for further research.

The Heterogeneity of Symptom Burden and Fear of Progression Among Kidney Transplant Recipients: A Latent Class Analysis

Purpose

Kidney transplant recipients (KTRs) may experience symptoms that increase their fear of progression (FoP), but a dearth of research examines the issue from a patient-centered perspective. Our study aimed to first determine the category of symptom burden, then to explore the differences in characteristics of patients in different subgroups, and finally to analyze the impact of symptom subgroup on FoP.

Patients and Methods

Sociodemographic and Clinical Characteristics, Symptom Experience Scale, and Fear of Progression Questionnaire-Short Form were used. Latent class analysis was used to group KTRs according to the occurrence of symptoms. We used multivariate logistic regression to analyze the predictors of different subgroups. The differences in FoP among symptom burden subgroups were analyzed by hierarchical multiple regression.

Results

Three subgroups were identified, designated all-high (20.5%), moderate (39.9%), and all-low (39.6%) according to their symptom occurrence. Multivariate logistic regression showed that gender, post-transplant time, per capita monthly income, and hyperuricemia were the factors that distinguished and predicted the all-high subgroup (P < 0.05). Hierarchical multiple regression showed that symptom burden had a significant effect on FoP (class1 vs class3: β = 0.327, P < 0.001; class2 vs class3: β = 0.104, P = 0.046), explaining the 8.0% variance of FoP (ΔR2 = 0.080).

Conclusion

KTRs generally experience moderate or low symptom burden, and symptom burden is an influencing factor in FoP. Identifying the traits of KTRs with high symptom burden can help clinicians develop targeted management strategies and ease FoP of KTRs.

Exploring patient medication adherence and data mining methods in clinical big data: A contemporary review

BACKGROUND

Increasingly, patient medication adherence data are being consolidated from claims databases and electronic health records (EHRs). Such databases offer an indirect avenue to gauge medication adherence in our data-rich healthcare milieu. The surge in data accessibility, coupled with the pressing need for its conversion to actionable insights, has spotlighted data mining, with machine learning (ML) emerging as a pivotal technique. Nonadherence poses heightened health risks and escalates medical costs. This paper elucidates the synergistic interaction between medical database mining for medication adherence and the role of ML in fostering knowledge discovery.

METHODS

We conducted a comprehensive review of EHR applications in the realm of medication adherence, leveraging ML techniques. We expounded on the evolution and structure of medical databases pertinent to medication adherence and harnessed both supervised and unsupervised ML paradigms to delve into adherence and its ramifications.

RESULTS

Our study underscores the applications of medical databases and ML, encompassing both supervised and unsupervised learning, for medication adherence in clinical big data. Databases like SEER and NHANES, often underutilized due to their intricacies, have gained prominence. Employing ML to excavate patient medication logs from these databases facilitates adherence analysis. Such findings are pivotal for clinical decision-making, risk stratification, and scholarly pursuits, aiming to elevate healthcare quality.

CONCLUSION

Advanced data mining in the era of big data has revolutionized medication adherence research, thereby enhancing patient care. Emphasizing bespoke interventions and research could herald transformative shifts in therapeutic modalities.

The prevalence of hyperuricemia and its correlates in Zhuang nationality, Nanning, Guangxi Province

BACKGROUND

Hyperuricemia has an increasing incidence in various regions year by year, in this study, we evaluated the prevalence of hyperuricemia in a routine physical examination in Nanning, Guangxi Province, and analyzed the influencing factors of hyperuricemia, aiming to provide evidence for the prevention and treatment of hyperuricemia and related diseases.

METHODS

Data were collected from 1957 patients who underwent physical examinations at the First Affiliated Hospital of Guangxi Medical University in China since 2017. Questionnaires were structured, including subjects' demographics, lifestyle, personal history, chronic disease history, medication history, etc. UA (uricase method), TC (cholesterol oxidase method), TG (glycerol phosphate oxidase method), HDL-C (direct method), LDL-C (direct method), BUN (rate method), creatinine (sarine oxidase method), and GLU (oxidase-peroxidase method) were detected. Independent risk factors for hyperuricemia were determined by bivariate non-conditional logistic regression analysis.

RESULTS

The overall prevalence of hyperuricemia was 16.6% (19.5% in males and 14.9% in females). Gender, waist circumference, BMI, the proportion of drinking, hypertension, high education, serum concentrations of TC, TG, LDL-C, BUN, and creatinine were significantly higher and the serum concentration of HDL-C was significantly lower in patients with and without hyperuricemia (all p < 0.05). Waist circumference, BMI, BUN, and creatinine were independent risk factors for hyperuricemia.

CONCLUSION

The prevalence of hyperuricemia is very high in Guangxi. Public health lectures should be conducted to encourage people to establish a healthy lifestyle and strengthen early intervention for hyperuricemia to reduce the risk of cardio-cerebrovascular and other related diseases.

Dietary Magnesium Intake Level Modifies the Association Between Vitamin D and Insulin Resistance: A Large Cross-Sectional Analysis of American Adults

Background

Previous clinical studies and randomized controlled trials have revealed that low serum vitamin D levels are associated with the risk of developing insulin resistance. Magnesium has been reported to be a protective factor for insulin resistance, and magnesium has been considered an important co-factor for vitamin D activation. However, the effect of dietary magnesium intake on the relationship between vitamin D and the risk of developing insulin resistance has not been comprehensively investigated. Therefore, we designed this cross-sectional analysis to assess whether dietary magnesium intake modifies the association of vitamin D and insulin resistance.

Methods

A total of 4,878 participants (male: 48.2%) from 4 consecutive cycles of the National Health and Nutrition Examination Survey (2007-2014) were included in this study after a rigorous screening process. Participants were stratified by their dietary magnesium intake into low-intake (<267 mg/day) and high-intake (≥267 mg/day) groups. We assessed differences between serum vitamin D levels and the risk of developing insulin resistance (interaction test), using a weighted multivariate logistic regression to analyze differences between participants with low and high magnesium intake levels.

Results

There was a negative association between vitamin D and insulin resistance in the US adult population [OR: 0.93 (0.88-0.98)], P < 0.001. Dietary magnesium intake strengthened the association (P for interaction < 0.001). In the low dietary magnesium intake group, vitamin D was negatively associated with the insulin resistance [OR: 0.94 (0.90-0.98)]; in the high dietary magnesium intake group, vitamin D was negatively associated with insulin resistance [OR: 0.92 (0.88-0.96)].

Conclusion

Among adults in the United States, we found an independent association between vitamin D level and insulin resistance, and this association was modified according to different levels of magnesium intake.

Dietary Magnesium Intake Affects the Vitamin D Effects on HOMA-β and Risk of Pancreatic β-Cell Dysfunction: A Cross-Sectional Study

Background

Some studies have shown that, the circulating vitamin D (Vit D) concentration in the body exerts a crucial role in regulating the pancreatic β-cell function. Meanwhile, the role of magnesium is important in the synthesis of Vit D, since it is an essential element for activating Vit D. Nevertheless, there remains insufficient studies concerning whether dietary Magnesium intake influences the association between Vit D and risk of pancreatic β-cell dysfunction. Hence, this cross-sectional study aimed to assess the effect of Magnesium intake alterations on the association between serum Vit D levels and the risk of pancreatic β-cell dysfunction.

Methods

This large-scale cross-sectional study involves four cycles of National Health and Nutrition Examination Survey (NHANES) (2007–2014), with totally 4,878 participants. Groups were divided depending on the median daily intake of Magnesium, namely, the low intake group (Magnesium intake <267 Magnesium/d) and the high intake group (Magnesium intake ≥ 267 Magnesium/d). By constructing multiple multivariate linear and logistics regression models, the associations between serum Vit D levels and HOMA-β, as well as between serum Vit D levels and the risk of pancreatic β-cell dysfunction were explored at different Magnesium intakes.

Results

In this cross-sectional study, the serum Vit D level is independently correlated with the HOMA-β index [β: 0.65 (0.40–0.90)] and the risk of pancreatic β-cell dysfunction [OR: 0.95 (0.92–0.98)]. Moreover, such correlations are affected by different dietary Magnesium intakes (P for interaction < 0.001).

Conclusion

According to the results of this study, the dietary Magnesium intake influences the associations of serum Vit D levels with HOMA-β index and pancreatic β-cell dysfunction. Besides, the finding requires validation through more RCT or cohort studies.

Association between vitamin D3 levels and insulin resistance: a large sample cross-sectional study

Previous studies have shown that vitamin D3 may be a potential factor in insulin resistance, but the relationship between vitamin D3 and insulin resistance still remains controversial. At present, more research is needed to explore the relationship between vitamin D3 and insulin resistance. The samples from 2009 to 2018 in NHANES database were analyzed to Investigate the relationship and the potential mechanism. We performed a cross-sectional study of five periods in the NHANES database. Finally, 9298 participants were selected through strict inclusion and exclusion criteria, Multivariate logistic regression analysis and curve fitting were conducted to explore the relationship between vitamin D3 level and insulin resistance. Moreover, subgroup analysis was used to further prove the association. The results revealed that there was a strong association between vitamin D3 and insulin resistance (OR 0.82, 95% CI 0.72-0.93). However, subgroup analyses indicated that this correlation varied between individuals and races. There was a negative correlation between vitamin D3 level and insulin resistance, which provides a new proof for exploring the influencing factors of insulin resistance. More well-designed studies are still needed to further elaborate on these associations.

Association Between Visceral Adiposity Index and Insulin Resistance: A Cross-Sectional Study Based on US Adults

BACKGROUND

Visceral obesity index (VAI) is an empirical mathematical model used to evaluate the distribution and function of fat. Some studies have shown that VAI may be associated with the development of insulin resistance. In view of the differences in insulin resistance among different ethnic groups, this study attempts to analyze the special relationship between VAI and insulin resistance in American adults.

METHODS

We conducted a cross-sectional study through NHANES database. A total of 27309 patients over the age of 18 from the United States took part in the survey. It was divided into two groups: the IR-positive group and the IR-negative group. The association of VAI with IR was evaluated by logistic regression analyses mainly, including univariate analysis, multivariate regression analysis, curve fitting analysis and subgroup analysis.

RESULTS

The results showed that in the full-adjusted model, there is a strong positive association between VAI level and insulin resistance (OR: 1.28 (1.2~1.37), P<0.001) and there is a threshold effect.

CONCLUSIONS

This study suggests that higher VAI levels are associated with insulin resistance. VAI index may be used as a predictor of insulin resistance.

Association Between Globulin and Diabetic Nephropathy in Type2 Diabetes Mellitus Patients: A Cross-Sectional Study

BACKGROUND

With the development of economy, the living standard of people all over the world has been greatly improved, and the incidence of diabetes is also increasing. Many people with diabetes also develop other complications that reduce their quality of life. Diabetic nephropathy is a common complication of type2 diabetes. Understanding the related factors of diabetic nephropathy is greatly significant to control the occurrence of diabetic nephropathy and improve patient's life quality.

DATA AND METHODS

Data were collected from 2009 to 2018 in NHANES. Curve fitting graph was performed to investigate the association between globulin (GLB) and diabetic nephropathy(DN). Four logistic regression models were conducted to control the potential confounding factors. Subgroup analysis was carried out to assess the stability of results.

RESULTS

GLB was positively correlated with the occurrence of DN after controlling for potential confounders. Higher GLB was associated with an increased risk of diabetic nephropathy [odds ratio(OR), 1.10; 95% confidence interval (CI), 1.07-1.13, P < 0.001].

CONCLUSIONS

In this cross-sectional study, GLB was significant positively correlated with the occurrence of DN in patients with type2 diabetes mellitus.

Serum 25(OH)D Levels Modify the Association between Triglyceride and IR: A Cross-Sectional Study

BACKGROUND

Triglycerides and 25(OH)D had been reported as correlates of IR, but the results suggest substantial heterogeneity across races. In addition, little research reported on whether different 25(OH)D levels affect triglycerides and IR. Therefore, a similar study on the US population would be a great addition to the current one. This study investigated the association between triglycerides and IR at different 25(OH)D levels.

METHODS

A total of 19,926 participants were included, each containing specific indicators for the study project. IR was estimated as a HOMA-IR index ≥2.73. Four multivariate logistic regression models were developed to analyze the association between TG and IR and whether different 25(OH)D levels influenced this association. Smoothed fitting curves were plotted.

RESULTS

Triglyceride was significantly associated with IR (OR: 1.3, 95 CI %), while this association received different 25(OH)D levels (P for interaction <0.001). The effect value OR was 1.33 with the high levels, and its effect value OR was 1.28 with the low levels.

CONCLUSION

This study demonstrates that triglyceride levels are significantly associated with insulin in the US adult population and can be used as a predictor of IR. This correlation was compromised at different 25 (OH)D levels, so future studies need to be explored in more ethnically diverse contexts.

Associations between TG/HDL ratio and insulin resistance in the US population: a cross-sectional study

BACKGROUND

Clinical data on the relationship between triglycerides (TG)/HDL ratio and insulin resistance (IR) suggest that TG/HDL ratio may be a risk factor for IR. However, there is evidence that different races have different risk of developing IR. The relationship on TG/HDL ratio and IR in various populations needs to be improved. Therefore, we investigated whether TG/HDL ratio was linked to IR in different groups in the United States after controlling for other covariates.

METHODS

The current research was conducted in a cross-sectional manner. From 2009 to 2018, the National Health and Nutrition Examination Survey (NHANES) had a total of 49,696 participants, all of whom were Americans. The target-independent variable was TG/HDL ratio measured at baseline, and the dependent variable was IR. Additionally, the BMI, waist circumference, education, race, smoking, alcohol use, alanine transaminase, aspartate transaminase, and other covariates were also included in this analysis.

RESULTS

The average age of the 10,132 participants was 48.6 ± 18.4 years, and approximately 4936 (48.7%) were males. After correcting for confounders, fully adjusted logistic regression revealed that TG/HDL ratio was correlated with IR (odds ratio = 1.51, 95% CI 1.42-1.59). A nonlinear interaction between TG/HDL ratio and IR was discovered, with a point of 1.06. The impact sizes and CIs on the left and right sides of the inflection point were 6.28 (4.66-8.45) and 1.69 (1.45-1.97), respectively. According to subgroup analysis, the correlation was strong in females, alcohol users, and diabetes patients. Meanwhile, the inverse pattern was observed in the aged, obese, high-income, and smoking populations.

CONCLUSION

In the American population, the TG/HDL ratio is positively associated with IR in a nonlinear interaction pattern.

Associations of Triglycerides/High-Density Lipoprotein Cholesterol Ratio With Insulin Resistance, Impaired Glucose Tolerance, and Diabetes in American Adults at Different Vitamin D3 Levels

BACKGROUND

Previous studies have shown that vitamin D3 (VD3) may be a protective factor for diabetes mellitus (DM), while triglycerides/high-density lipoprotein (TG/HDL) may be a risk factor for diabetes. However, no existing study has elucidated the interaction between TG/HDL and VD3. Therefore, this work aimed to investigate the relationships of TG/HDL with insulin resistance (IR), impaired glucose tolerance (IGT), and DM at different VD3 levels.

METHODS

With the use of the data from five National Health and Nutrition Examination Survey (NHANES) cycles, a total of 2,929 males and 3,031 females were divided into 4 groups according to their VD3 levels. Logistic regression was performed to observe the associations of TG/HDL ratio with IR, IGT, and DM in different groups.

RESULTS

The relationships of TG/HDL with IR, IGT, and DM showed a threshold effect, with the cutoff values of 1.094, 1.51, and 1.11, respectively. On both sides of the cutoff values, the correlation was first weakened and then enhanced with the increase in VD3 levels.

CONCLUSION

TG/HDL is a risk factor for IR, IGT, and DM. Both too low and too high levels of VD3 can strengthen this association, whereas keeping VD3 at a reasonable level helps to reduce the associations of TG/HDL with IR, IGT, and DM.