Cross-sectional and longitudinal associations of Iron biomarkers and cardiovascular risk factors in pre- and postmenopausal women: leveraging repeated measurements to address natural variability.

BACKGROUND: The association between iron biomarkers and cardiovascular disease risk factors (CVD-RFs) remains unclear. We aimed to (1) evaluate the cross-sectional and longitudinal associations between iron biomarkers (serum ferritin, transferrin saturation (TSAT), transferrin) and CVD-RFs among women, and (2) explore if these associations were modified by menopausal status. METHOD: Cross-sectional and longitudinal analyses including 2542 and 1482 women from CoLaus cohort, respectively. Multiple linear regression and multilevel mixed models were used to analyse the associations between Iron biomarkers and CVD-RFs. Variability of outcomes and iron markers between surveys was accessed using intraclass correlation (ICC). RESULTS: After multivariable adjustment, elevated serum ferritin levels were associated with increased insulin and glucose levels, while higher transferrin levels were linked to elevated glucose, insulin and total cholesterol, and systolic and diastolic blood pressure (p < 0.05). No association was observed between CVD-RFs and TSAT (p > 0.05). Iron biomarkers demonstrated low reliability across reproductive stages but exhibited stronger associations in the perimenopausal group. In longitudinal analysis, we found association only for transferrin with lower glucose levels [ß = - 0.59, 95% CI (- 1.10, - 0.08), p = 0.02] and lower diastolic blood pressure [ß = - 7.81, 95% CI (- 15.9, - 0.56), p = 0.04]. CONCLUSION: In cross-sectional analysis, transferrin was associated with several CVD-RFs, and the associations did not change according to menopausal status. Conversely, in the longitudinal analyses, changes in transferrin were associated only with lower glucose and diastolic blood pressure levels. These differences might stem from the substantial longitudinal variation of iron biomarkers, underscoring the need for multiple iron measurements in longitudinal analyses.

Are HOMA-IR and HOMA-B good predictors for diabetes and pre-diabetes subtypes?

BACKGROUND: To investigate the association between the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) and Homeostasis Model Assessment of Beta-cell function (HOMA-B) with the incidence of diabetes and pre-diabetes subtypes. METHODS: A total of 3101 normoglycemic people aged 20-70 years were included in the 6-year follow-up study. Multinomial logistic regression was used to calculate the incidence possibility of isolated Impaired Fasting Glucose (iIFG), isolated Impaired Glucose Tolerance (iIGT), Combined impaired fasting glucose & impaired glucose tolerance (CGI), and Diabetes Mellitus (DM) per standard deviation (SD) increment in HOMA-IR and HOMA-B in the crude and multivariable model. RESULTS: In the multivariate model, an increase in one SD change in HOMA-IR was associated with a 43, 42, 75, and 92% increased risk of iIFG, iIGT, CGI, and DM, respectively. There was a positive correlation between the increase in HOMA-B and the incidence of iIGT; however, after adjusting the results for metabolic syndrome components, it was inversely correlated with the incidence of iIFG [Odds Ratio = 0.86(0.75-0.99)]. CONCLUSIONS: HOMA-IR is positively correlated with diabetes and pre-diabetes subtypes' incidence, and HOMA-B is inversely correlated with the incidence of iIFG but positively correlated with iIGT incidence. However, none of these alone is a good criterion for predicting diabetes and pre-diabetes.

Sex specific trajectories of central adiposity, lipid indices, and glucose level with incident hypertension: 12 years Follow-up in Tehran lipid and glucose study.

AIMS: To identify sex specific trajectories of waist circumference (WC),triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C) and fasting plasma glucose (FPG) during adulthood and examine their associations with incident hypertension. METHODS: The cohort consisted of 5030 participants (2051 males) with at least 2 repeated measurement during a median of 12 years follow up. We identified trajectory groups using latent class growth mixture model, their association with hypertension was examined using multivariate Cox-regression analysis. RESULTS: We found 997 cases of hypertension (483 male). For both exposures, three distinct trajectory groups were identified in both genders. For WC, in women: low-increasing, 82.4%; high-stable, 13.4%; high-increasing, 4.2% and in men: stable, 94.6%; low-increasing, 3.6% and for high- increasing, 1.7%. For TG, in women: stable, 91.3%; decreasing, 5.9%; inverse U-shape, 2.8%; in men: stable, 89.7%; inverse U- shape, 6.2% and for decreasing, 4.1%. Regarding WC, high stable and high-increasing trajectories were associated with hypertension in the multivariate model [(hazard ratio (HR) = 1.66 (95% CI 1.26-2.20) and 2.78(1.79-3.60), respectively]. Among men, this association was shown only for the low-increasing trajectory [2.76: 1.49-5.10]. For TG, among women decreasing and inverse U-shape trajectories were significantly associated with hypertension in the multivariate model [1.32:1.01-1.76] and [2.23:1.58-3.23, respectively]. We did not find any impact of increasing trajectories of FPG and HDL-C on incident hypertension. Considering TC, all individuals followed a stable trajectory. CONCLUSION: WC dynamic changes in both gender and TG trajectory among women were significantly associated with incident hypertension.

The complementary roles of iron and estrogen in menopausal differences in cardiometabolic outcomes.

Biological hormonal changes are frequently cited as an explanatory factor of sex and menopause differences in cardiometabolic diseases (CMD) and its associated risk factors. However, iron metabolism which varies between sexes and among women of different reproductive stages could also play a role. Recent evidence suggest that iron may contribute to CMD risk by modulating oxidative stress pathways and inflammatory responses, offering insights into the mechanistic interplay between iron and CMD development. In the current review, we provide a critical appraisal of the existing evidence on sex and menopausal differences in CMD, discuss the pitfall of current estrogen hypothesis as sole explanation, and the emerging role of iron in CMD as complementary pathway. Prior to menopause, body iron stores are lower in females as compared to males, but the increase during and after menopause, is tandem with an increased CMD risk. Importantly, basic science experiments show that an increased iron status is related to the development of type 2 diabetes (T2D), and different cardiovascular diseases (CVD). While epidemiological studies have consistently reported associations between heme iron intake and some iron biomarkers such as ferritin and transferrin saturation with the risk of T2D, the evidence regarding their connection to CVD remains controversial. We delve into the factors contributing to this inconsistency, and the limitation of relying on observational evidence, as it does not necessarily imply causation. In conclusion, we provide recommendations for future studies on evaluating the potential role of iron in elucidating the sex and menopausal differences observed in CMD.

Agreement Between Mega-Trials and Smaller Trials: A Systematic Review and Meta-Research Analysis.

Importance: Mega-trials can provide large-scale evidence on important questions. Objective: To explore how the results of mega-trials compare with the meta-analysis results of trials with smaller sample sizes. Data Sources: ClinicalTrials.gov was searched for mega-trials until January 2023. PubMed was searched until June 2023 for meta-analyses incorporating the results of the eligible mega-trials. Study Selection: Mega-trials were eligible if they were noncluster nonvaccine randomized clinical trials, had a sample size over 10 000, and had a peer-reviewed meta-analysis publication presenting results for the primary outcome of the mega-trials and/or all-cause mortality. Data Extraction and Synthesis: For each selected meta-analysis, we extracted results of smaller trials and mega-trials included in the summary effect estimate and combined them separately using random effects. These estimates were used to calculate the ratio of odds ratios (ROR) between mega-trials and smaller trials in each meta-analysis. Next, the RORs were combined using random effects. Risk of bias was extracted for each trial included in our analyses (or when not available, assessed only for mega-trials). Data analysis was conducted from January to June 2024. Main Outcomes and Measures: The main outcomes were the summary ROR for the primary outcome and all-cause mortality between mega-trials and smaller trials. Sensitivity analyses were performed with respect to the year of publication, masking, weight, type of intervention, and specialty. Results: Of 120 mega-trials identified, 41 showed a significant result for the primary outcome and 22 showed a significant result for all-cause mortality. In 35 comparisons of primary outcomes (including 85 point estimates from 69 unique mega-trials and 272 point estimates from smaller trials) and 26 comparisons of all-cause mortality (including 70 point estimates from 65 unique mega-trials and 267 point estimates from smaller trials), no difference existed between the outcomes of the mega-trials and smaller trials for primary outcome (ROR, 1.00; 95% CI, 0.97-1.04) nor for all-cause mortality (ROR, 1.00; 95% CI, 0.97-1.04). For the primary outcomes, smaller trials published before the mega-trials had more favorable results than the mega-trials (ROR, 1.05; 95% CI, 1.01-1.10) and subsequent smaller trials published after the mega-trials (ROR, 1.10; 95% CI, 1.04-1.18). Conclusions and Relevance: In this meta-research analysis, meta-analyses of smaller studies showed overall comparable results with mega-trials, but smaller trials published before the mega-trials gave more favorable results than mega-trials. These findings suggest that mega-trials need to be performed more often given the relative low number of mega-trials found, their low significant rates, and the fact that smaller trials published prior to mega-trial report more beneficial results than mega-trials and subsequent smaller trials.

Potential Mediating Role of Iron Biomarkers in the Association of Sex With Glucose, Insulin, and Type 2 Diabetes.

Context: Sex-specific prevalence and incidence of type 2 diabetes (T2D) have been reported, but the underlying mechanisms are uncertain. Objective: In this study, we aimed to investigate whether iron biomarkers mediate the association between biological sex and glucose metabolism and the incidence of T2D. Methods: We used data from the general population enrolled in the prospective Prevention of REnal and Vascular ENd-stage Disease study in Groningen, The Netherlands. We measured ferritin, transferrin saturation (TSAT), hepcidin, soluble transferrin receptor (sTfR), fasting plasma glucose (FPG), fasting plasma insulin (FPI) levels, and incidence of T2D. We used multivariable regression and mediation analyses to investigate our hypothesis. All iron biomarkers, FPG, and FPI were log-transformed. Results: The mean (SD) age of the 5312 (51.3% female) individuals was 52.2 (11.6) years. Compared with males, females had lower FPG (ß = -.01; 95% CI -0.02, -0.01) and FPI (ß = -.03; 95% CI -0.05, -0.02) levels. Ferritin, hepcidin, and sTfR showed potential mediating effects on the association between sex and FPG, 21%, 5%, and 7.1%, respectively. Furthermore, these variables mediated 48.6%, 5.7%, and 3.1% of the association between sex and FPI, respectively. Alternatively, TSAT had a suppressive mediating role in the association of sex with FPG and FPI. The incidence of T2D was lower in females than in males (hazard ratio 0.58; 95% CI 0.44, 0.77), with 19.2% of this difference being mediated by ferritin. Conclusion: Iron biomarkers may partially mediate the association between sex and glucose homeostasis. Future studies addressing the causality of our findings are needed.

Changes in Iron Status Biomarkers with Advancing Age According to Sex and Menopause: A Population-Based Study.

BACKGROUND: The risk of chronic diseases increases markedly with age and after menopause. An increase in bodily iron following menopause could contribute to this phenomenon of increased risk of chronic diseases. We aimed to investigate how various iron biomarkers change with advancing age, according to sex and menopausal status. METHODS: We enrolled community-dwelling individuals with available information on ferritin, transferrin, iron, hepcidin, and soluble transferrin receptor levels from the Prevention of Renal and Vascular Endstage Disease study. The association of the iron biomarkers with age, sex, and menopausal status was investigated with linear regression models. RESULTS: Mean (SD) age of the 5222 individuals (2680 women [51.3%], among whom 907 [33.8%] were premenopausal, 529 [19.7%] perimenopausal, and 785 [29.3%] postmenopausal), was 53.4 (12.0) years. Iron biomarkers showed a constant increase in women throughout their life course, in some cases at older ages surpassing values in men who, in turn, showed consistently higher levels of iron status compared to women in most age categories. Ferritin, hepcidin, and transferrin saturation levels were 3.03, 2.92, and 1.08-fold (all p < 0.001) higher in postmenopausal women compared to premenopausal. CONCLUSIONS: We found that iron accumulates differently depending on sex, age, and menopausal status. An increased iron status was identified in women, especially during and after menopause.

A comprehensive analysis of cardiovascular mortality trends in Peru from 2017 to 2022: Insights from 183,386 deaths of the national death registry.

Background/objectives: Cardiovascular diseases are the leading cause of global mortality. Systematic studies on cardiovascular-related mortality at national and subnational levels in Peru are lacking. We aimed to describe the trends in cardiovascular-related mortality between 2017 and 2022 in Peru at national and subnational levels and by socioeconomic indicators. Subjects/methods: We used data from the Peruvian death registry 2017-2022. Using ICD-10 codes, mortality was categorized into: hypertensive-, coronary-, and cerebrovascular- related deaths. We estimated age-standardized cardiovascular-related mortality rates by sex at national and regional levels, and by natural regions (Coast, Highlands, Amazon). We estimated the change in mortality rates between 2017-2019 and 2020-2022 and explored factors that contributed to such a change. We explored ecological relationships between mortality rates and socioeconomic indicators. Findings: Overall 183,386 cardiovascular-related deaths were identified. Coronary-related deaths (37.2 %) were followed by hypertensive-related (25.1 %) and cerebrovascular-related deaths (22.6 %). Peru showed a marked increasing trend in cardiovascular-related mortality in 2020-2022 (77.8 %). The increase clustered in the Coast and Highlands, with the highest change observed in Lima (132.1 %). Mortality was highest in subjects with lower education and subjects with public health insurance. Gini coefficient was associated with lower mortality rates while unemployment was associated with higher mortality rates. Interpretation: There was a notable rise in cardiovascular-related mortality in Peru, particularly during the Covid-19 pandemic with a slight decrease in 2022. Gaining a comprehensive understanding of the factors that contribute to the increase in cardiovascular deaths in Peru will facilitate the development of precise interventions at both the national and regional levels.

Buckwheat and Cardiometabolic Health: A Systematic Review and Meta-Analysis.

Buckwheat (BW) is suggested to have beneficial effects, but evidence on how it affects cardiometabolic health (CMH) is not yet established. We aimed to assess the effects of BW and/or its related bioactive compounds on cardiovascular disease (CVD) risk markers in adults. Five databases were searched for eligible studies. Observational prospective studies, nonrandomized or randomized trials were considered if they assessed BW, rutin or quercetin-3-glucoside intake and CVD risk markers. We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reporting. We selected 16 human studies based on 831 subjects with mild metabolic disturbances, such as hypercholesterolemia, diabetes and/or overweight. Eight studies, investigating primarily grain components, were included in the meta-analyses (n = 464). High study heterogeneity was present across most of our analyses. Weighted mean difference (WMD) for subjects receiving BW supplementation, compared to controls, were - 0.14 mmol/L (95% CI: -0.30; 0.02) for total cholesterol (TC), -0.03 mmol/L (95% CI: -0.22; 0.16) for LDL cholesterol, -0.14 kg (95% CI: -1.50; 1.22) for body weight, -0.04 mmol/L (95% CI: - 0.09;0.02) for HDL cholesterol, -0.02 mmol/L (95% CI: -0.15; 0.11) for triglycerides and -0.18 mmol/L (95% CI: -0.36; 0.003) for glucose. Most of the studies (66.7%) had concerns of risk of bias. Studies investigating other CVD markers were scarce and with inconsistent findings, where available. Evidence on how BW affects CMH is limited. However, the available literature indicates that BW supplementation in mild dyslipidaemia and type 2 diabetes may provide some benefit in lowering TC and glucose, albeit non-significant. Our work highlights the need for more rigorous trials, with better methodological rigor to clarify remaining uncertainties on potential effects of BW on CMH and its utility in clinical nutrition practice.

Sex- specific clustering of metabolic syndrome components and incidence of cardiovascular disease: A latent class analysis in a population-based cohort study.

BACKGROUND: The prevalence of metabolic syndrome (MetS) is rapidly increasing in the world; also, the importance of management of MetS to decrease the risk of cardiovascular disease (CVD) has been recognized worldwide. This study aimed to explore the clusters of participants based on MetS components and its association with CVD outcomes. METHODS: We included 2598 middle-aged participants (1545 women and 1053 men), 45-65 years old, at baseline and without prior CVD history. Participants were followed up for 10years. We conducted a latent class analysis based on MetS components. Subsequently, the relationship between latent classes and the incidence of CVD was investigated using Cox regression models adjusted for the main confounders. RESULTS: During the study period, 393 (186 women and 207 men) new cases of CVD were identified among participants. In both genders, four distinct latent classes were identified: (1) Mets class (its prevalence rate in men: 19.6%, women: 27.7%), (2) Hypertension class (men: 12.1%, women: 13.7%), (3) Dyslipidemia class (men: 31.7%, women: 30.7%), (4) Low risk class (men: 39.3%, women: 30.5%). Compared with low-risk class, in both genders, Mets and hypertension classes were significant predictors of incident CVD. However, dyslipidemia class was a significant predictor just in women. CONCLUSION: We found four subclasses in both genders indicating the same patterns of MetS latent classes in men and women. However, the relationship between subclasses of MetS and incident CVD varied by gender. These results suggest that the etiology of MetS involve more than one pathway and giving equal weight to each component or using the same cut-off values in both genders need to be reconsidered.

Application of Latent Class Analysis to Identify Metabolic Syndrome Components Patterns in adults: Tehran Lipid and Glucose study.

In this study, using latent class analysis (LCA), we investigated whether there are any homogeneous subclasses of individuals exhibiting different profiles of metabolic syndrome (MetS) components. The current study was conducted within the framework of the Tehran Lipid and Glucose Study (TLGS), a population-based cohort including 6448 subjects, aged 20-50 years. We carried out a LCA on MetS components and assessed the association of some demographic and behavioral variables with membership of latent subclasses using multinomial logistic regression. Four latent classes were identified:(1) Low riskclass, with the lowest probabilities for all MetS components (its prevalence rate in men: 29%, women: 64.7%), (2) MetS with diabetes medication (men: 1%, women: 2.3%), (3) Mets without diabetes medication (men: 32%, women: 13.4%), (4) dyslipidemia (men: 38%, women: 19.6%). In men the forth subclass was more significantly associated with being smoker (odds ratio: 4.49; 95% CI: 1.89-9.97). Our study showed that subjects with MetS could be classified in sub-classes with different origins for their metabolic disorders including drug treated diabetes, those with central obesity and dyslipidemia associated with smoking.

Body mass index trajectories from adolescent to young adult for incident high blood pressure and high plasma glucose.

OBJECTIVES: To explore the association between sex-specific adiposity trajectories among Adolescents to early adulthood with incident high blood pressure (HBP) and high plasma glucose (HPG). METHODS: We studied body mass index (BMI) trajectories among1159 (male = 517) and 664 (male = 263) Iranian adolescents, aged 12-20 years, for incident HPG and HBP, respectively. Latent Class Growth Mixture Modeling (LCGMM) on longitudinal data was used to determine sex-specific and distinct BMI trajectories. Logistic regressions were applied to estimate the relationship between latent class membership with HBP and HPG, considering normal trajectory as the reference. RESULTS: For both HBP and HPG, LCGMM determined two and three distinct BMI trajectories in males and females, respectively. During a follow-up of 12Years 104 (male = 62) and 111(male = 59) cases of HPG and HBP were found, respectively. Among females, faster BMI increases (i.e. overweight to early obese trajectory) but not overweight (i.e. those with BMI = 27.3 kg/m2 at baseline) trajectories increased the risk of HPG by adjusted odds ratios (ORs), 2.74 (1.10-5.80) and 0.79 (0.22-2.82), respectively; regarding HBP, the corresponding value for overweight to late obese trajectory was 3.72 (1.37-11.02). Among males, for HBP, the overweight trajectory increased the risk [2.09 (1.04-4.03)]; however, for incident HPG, none of the trajectories showed significant risk. CONCLUSIONS: Among females, trend of increasing BMI parallel with age can be a better predictor for risk of developing HPG and HBP than those with higher BMI at baseline.

Effect of Bedtime Melatonin Administration in Patients with Type 2 Diabetes: A Triple-Blind, Placebo-Controlled, Randomized Trial.

Melatonin is widely available as over the counter product. Despite promising effects of melatonin supplementation on glycemic control, there is a significant heterogeneity between studies. The current study aimed at determining the effect of melatonin on fasting blood glucose (FBG), insulin resistance/sensitivity indices, glycosylated hemoglobin A1c (HbA1c), and high sensitivity C-reactive protein (hs-CRP) among type 2 diabetes mellitus (T2D) population during 8 weeks in a randomized, triple-blind, placebo-controlled trial. Thirty four subjects with the mean age ± standard deviation of 57.74 ± 8.57 years and 36 subjects with the mean age of 57.61 ± 9.11 years were allocated to 6 mg nightly melatonin and placebo groups, respectively. Melatonin and placebo groups were matched by age, gender, body mass index, and duration of diabetes. Also, there was no significant difference in laboratory findings except for HbA1c, which was lower in the placebo group (7.00 ± 0.89% vs 7.60 ± 1.47%, P=0.042). After trial completion, the increase of serum levels of melatonin was greater in the intervention than the placebo group (3.38 ± 1.33 vs 0.94 ± 1.28 ng/L, P=0.192). Moreover, compared to placebo group, among melatonin users, homeostasis model assessment of insulin resistance (HOMA1-IR) tended to be unfavorable at the end of follow-up [-0.51 (-1.76-0.81) vs. 0.28 (-1.24-1.74), P=0.20]; the similar trend was also shown for insulin sensitivity index (HOMA1-S) [2.33 (-3.59-12.46) vs. -2.33 (-10.61-9.16), P=0.148]. No differences were observed in FBG, HbA1C, and hs-CRP changes between the trial groups. The current study did not support the improving effect of melatonin on glucose homeostasis.

Fasting plasma glucose is a stronger predictor of diabetes than triglyceride-glucose index, triglycerides/high-density lipoprotein cholesterol, and homeostasis model assessment of insulin resistance: Tehran Lipid and Glucose Study.

AIMS: To compare the impact of triglyceride-glucose index (TyG-index), the product of fasting plasma glucose (FPG) and triglycerides (TG) with FPG, 2 h post-challenge plasma glucose (2 h-PCPG), TG/high-density lipoprotein cholesterol (TG/HDL-C), and homeostasis model assessment of insulin resistance (HOMA-IR) indices for prediction of type 2 diabetes (T2D) in Iranian adults during a median follow-up of 12 years. METHODS: Study population included 4419 (1858 men) subjects with mean age of 40.6 ± 13.2 years. Multivariable Cox proportional hazard models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) for each 1-standard deviation increase in each predictor. Areas under the receiver operating characteristics curves (AUC) and 95% CIs were calculated. RESULTS: During follow-up, 215 men and 288 women developed T2D. The multivariable HRs for FPG, 2 h-PCPG, TyG-index, HOMA-IR, HOMA2-IR, and TG/HDL-C were 2.20, 1.97, 1.71, 1.33, 1.30, and 1.35 in men and 2.13, 2.11, 1.44, 1.37, 1.32, and 1.36 in women (all P < 0.001). Among the total population, the AUC for FPG [0.752 (0.727-0.776)] was similar to 2 h-PCPG but higher than TyG-index [0.697 (0.673-0.720)], TG/HDL-C [0.644 (0.620-0.669)], HOMA-IR [0.684 (0.659-0.710)], and HOMA2-IR [0.656 (0.630-0.682)]. In men, AUC of TyG-index was higher than TG/HDL-C but did not differ with HOMA-IR indices. In women, the AUC of TyG-index was higher than HOMA2-IR and TG/HDL-C, but was similar to that of HOMA-IR. CONCLUSIONS: FPG is a stronger predictor of T2D than the TyG-index, TG/HDL-C, and HOMA-IR indices. Although TyG-index was better than TG/HDL-C in both genders, it did not rank above HOMA-IR.