Background: Minerals and trace elements were involved in the pathogenesis and progression of diabetes. However, the association of mixed exposure to essential elements and toxic elements with gestational diabetes mellitus (GDM) is poorly understood.Objective: This study aims to examine the associations between serum calcium (Ca), iron (Fe), zinc (Zn), copper (Cu), magnesium (Mg), and cadmium (Cd) concentrations in early pregnancy and GDM risk in Chinese pregnant women.Method: A total of 1,168 pregnant women were included in this prospective cohort study. The concentrations of serum elements were measured using the polarography method before 14 gestational weeks and an oral glucose tolerance test was conducted at 24–28 gestational weeks to diagnose GDM. Binary logistic regression analysis and restricted cubic spline were applied to evaluate the association between serum individual element and GDM. Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression were used to assess the associations between mixed essential elements and Cd exposure and GDM risk.Results: The mean concentrations of Zn (124.65 vs. 120.12 μmol/L), Fe (135.26 vs. 132.21 μmol/L) and Cu (23.33 vs. 23.03 μmol/L) in the GDM group were significantly higher than those in the control group. Single-element modeling results suggested that second and fourth-quartile maternal Zn and Fe concentration, third and fourth-quartile Cu concentration and fourth-quartile Ca concentration were associated with an increased risk of GDM compared to first-quartile values. Restricted cubic spline analysis showed U-shaped and non-linear relationships between Cd and GDM. According to the BKMR models and WQS analyses, a six-element mixture was significantly and positively associated with the risk of GDM. Additionally, Cd, Zn, and Cu contributed the most strongly to the association.Conclusion: Serum Zn, Cu, Fe, and Ca exposure during early pregnancy showed a positive association with GDM in the individual evaluation. The multiple-evaluation showed that high levels of elements mixture, particularly Cd, Zn, and Cu, may promote the development of GDM.

Background: Prediabetes, impacting a third of the adult Chinese population, is linked to a variety of detrimental health outcomes. However, scant research has delved into the factors that affect a regression from prediabetes to normal glucose regulation (NGR) in middle-aged and elderly Chinese adults.Methods: We conducted a longitudinal analysis of 2,655 adults, aged 45 years and above, drawing data from wave 1 and wave 3 of the China Health and Retirement Longitudinal Study (CHARLS). We employed a stepwise logistic regression model to identify factors associated with the regression to NGR. Restricted Cubic Spline (RCS) analysis was used to evaluate the dose-response relationships between baseline fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) levels and the likelihood of regression to NGR. Attribution fraction (AF) analysis was conducted to measure the impact of modifiable factors on the regression of prediabetes. We further examined how changes in these factors were associated with regression to NGR.Results: During the 4-year follow-up, 570 of 2,655 prediabetes participants regressed to NGR. The stepwise logistic regression model identified older age, female sex, abdominal obesity (OR 0.70, 95% CI 0.57–0.86), elevated LDL-C (OR 0.69, 95% CI 0.48–0.97), higher FPG (OR 0.68, 95% CI 0.52–0.90), and higher HbA1c (OR 0.23, 95% CI 0.18–0.30) as factors associated with regression to NGR. AF analysis showed that a lower initial HbA1c was the most influential factor for regression to NGR. Additionally, evaluated blood lipid profiles reduced the odds of regression to NGR.Conclusion: This study underscores the influence of age, gender, abdominal obesity, LDL-C levels, FPG, HbA1c, and blood lipid profiles on the likelihood of regressing from prediabetes to NGR. It suggests that adopting a healthy lifestyle and preemptively mitigating these risks may be more beneficial than addressing them after they have been identified in clinical settings.

Background: The risk of atrial fibrillation (AF) is accentuated by age and comorbidities. Healthy lifestyle behaviors, based on Life’s Essential 8 (LE8), may modify the risk of new-onset AF mitigating the impact of multimorbidity. The aim of this study was to investigate the associations of LE8 with multimorbidity status, linked to AF incidence. Methods: A total of 255 280 participants free of AF were included. LE8 was assessed using eight metrics and categorized into low, moderate, and high cardiovascular health (CVH). Multimorbidity clusters were determined using latent class analysis using 36 long-term conditions (LTCs), categorized into five groups as follows: three multimorbidity clusters (noncardiovascular disease; mental health; and cardio-metabolic multimorbidity); no LTCs; and singular LTCs. The relationships between LE8 and multimorbidity status with AF incidence were evaluated using Cox models and counterfactual analyses. Results: During an average follow-up of 11.7 years (SD 2.2), 15 069 participants without AF at baseline (mean age 56.2; SD 8.1; 51.9% female and 48.1% male) developed AF. Individuals with high CVH had a 27% lower risk of AF than those with low CVH. Compared to individuals without multimorbidity, participants with singular LTC or multimorbidity clusters had higher AF risk. Up to 54.7% of the associations between multimorbidity status and AF were mediated by LE8. Counterfactual analysis showed increasing the LE8 score to 80 could reduce AF occurrence in multimorbidity individuals by 22.12% to 24.56%. Conclusion: Lower LE8 scores and multimorbidity were associated with higher AF incidence. Adherence to a healthy lifestyle, based on LE8 may prevent AF, especially in those with multimorbidity.

Background: Accumulating evidence have demonstrated that tobacco smoke exposure (TSE) causes damage to human mental issues. However, previous studies almost focus on the individual smoking exposure patterns and some inconsistent results are reported. Serum cotinine is a reliable and quantitative biomarker of TSE. This study aims to explore the association of serum cotinine with depression and sleep disorders and the potential gender differences.Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2007-2014 was used. Weighted multiple logistic regression methods, generalized additive models (GAM), and restricted cubic spline (RCS) models were used for association analyses. Moreover, gender-stratified analyses were conducted.Results: Of 12,599 individuals included in the final analysis, 1,295 had depression, 3245 had trouble sleeping and 1152 had diagnostic sleep disorders. After adjusting for potential covariates, linear relationship suggested higher serum cotinine levels were positively associated with risk of depression and sleep disorders, including self-reported trouble sleeping and diagnostic sleep disorders in the total sample and female participants, and serum cotinine levels were positively correlated with depression and trouble sleeping in male participants. Additionally, inverted L-shaped associations between serum cotinine and depression and sleep disorders were detected, and at the same cotinine level, females have a higher risk of experiencing depression and sleep disorders.Conclusions: In this study, higher serum cotinine increased the risk of depression and sleep disorders and there was stronger association in females than males. These findings provided novel evidence about how TSE affected the mental condition of the general US population.

Background: Although sarcopenia is associated with an increased risk of chronic kidney disease (CKD), its potential associations with subsequent comorbidities among patients with CKD remain unknown. Methods: This prospective study included 19,502 participants with CKD, defined as an estimated glomerular filtration rate less than 60 mL/min/1.73 m ² . Sarcopenia is characterized according to muscle strength, muscle mass, and physical performance; low muscle strength, commonly measured using handgrip strength, is considered the most important indicator. The study outcome was post-CKD comorbidity. Multivariable Cox proportional hazards models were used to analyze the effect of sarcopenia on comorbidities. Population attributable fractions (PAFs) and potential impact fractions (PIFs) were used to quantify the population-level burden and potential benefit of improving handgrip strength. Results: During a median follow-up of 10.6 years, 5,374 participants developed one comorbidity, 2,972 developed two comorbidities, and 2,434 developed three or more comorbidities. Sarcopenia was associated with a graded increase in multimorbidity risk (approximately 12, 24, and 33% higher for one, two, and three or more comorbidities, respectively, versus non-sarcopenia). Lower handgrip strength exhibited a clear exposure–response, and the lowest tertiles was associated with the greatest risk across outcomes. Among individual comorbid diseases, the strongest association was observed with osteoporosis. PAFs indicated that 5.21, 13.72, and 23.46% of cases involving one, two, or three or more comorbidities, respectively, were attributable to sarcopenia. Analysis of PIFs indicated that improving handgrip strength throughout the population (i.e., shifting lower to higher tertiles) could reduce the burden of one, two, and three or more comorbidities by approximately 12, 16, and 22%, respectively. Conclusion: The results indicate that sarcopenia, especially low handgrip strength, increases the risk of developing comorbidities, particularly osteoporosis, among patients with CKD. Quantification of PAFs and PIFs underscores the clinical and public health potential of muscle strength assessment and strength-preserving interventions to mitigate the CKD-associated comorbidity burden.

Sarcopenia has been a serious concern in the context of an increasingly aging global population. Existing detection methods for sarcopenia are severely constrained by cumbersome devices, the necessity for specialized personnel, and controlled experimental environments. In this study, we developed an innovative wearable fabric system based on conductive fabric and flexible sensor array. This fabric system demonstrates remarkable pressure-sensing capabilities, with a high sensitivity of 18.8 kPa⁻¹ and extraordinary stability. It also exhibits excellent flexibility for wearable applications. By interacting with different parts of the human body, it facilitates the monitoring of various physiological activities, such as pulse dynamics, finger movements, speaking, and ambulation. Moreover, this fabric system can be seamlessly integrated into sole to track critical indicators of sarcopenia patients, such as walking speed and gait. Clinical evaluations have shown that this fabric system can effectively detect variations in indicators relevant to sarcopenia patients, proving that it offers a straightforward and promising approach for the diagnosis and assessment of sarcopenia.