The evidence about the effect of non-essential metal mixture on fasting plasma glucose (FPG) levels among older adults without diabetes is limited. This study aims to estimate the individual and joint relationship between five non-essential metals and FPG levels in Chinese older adults without diabetes. This study included 2362 older adults without diabetes. Urinary concentrations of five non-essential metals, i.e., cesium (Cs), aluminum (Al), thallium (Tl), cadmium (Cd), and arsenic (As), were detected by inductively coupled plasma mass spectrometry (ICP-MS). The associations of single metals and the metal mixture with FPG levels were assessed using linear regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-metal linear regression models showed positive associations of urinary Al (β = 0.016, 95%CI: 0.001-0.030) and Cs (β = 0.018, 95%CI: 0.006-0.031) with FPG levels. When comparing the 2th, 3th, and 4th quartiles of urine Cs to its 1th quartile, the significant associations between Cs and FPG levels were found and presented as an "inverted U" trend (β: 0.034; β:0.054; β: 0.040; all P<0.05). BKMR analyses showed urinary level of Cs exhibited an "inverted U" shape association with FPG levels. Moreover, the FPG levels increased linearly with the raised levels of the non-essential metal mixture, and the posterior inclusion probability (PIP) of Cs was the highest (0.92). Potential positive interaction of As and Cs on FPG levels was found in BKMR model. Stratified analysis displayed significant interactions of hyperlipidemia and urine Cs or Tl on FPG levels. An inverse U-shaped association between Cs and FPG was found, individually and as mixture. The FPG levels increased with the raised levels of the non-essential metal mixture, and Cs was the most contributor to FPG levels. Further research is required to confirm the correlation between non-essential metals and FPG levels and to clarify the underlying mechanisms.
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http://dx.doi.org/10.1007/s11356-023-29503-8 | DOI Listing |
BMC Med Res Methodol
December 2024
Department of Military Health Statistics, Faculty of Preventive Medicine, Air Force Medical University/Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, Xi'an, Shaanxi, China.
Background: Accurate fasting plasma glucose (FPG) trend prediction is important for management and treatment of patients with type 2 diabetes mellitus (T2DM), a globally prevalent chronic disease. (Generalised) linear mixed-effects (LME) models and machine learning (ML) are commonly used to analyse longitudinal data; however, the former is insufficient for dealing with complex, nonlinear data, whereas with the latter, random effects are ignored. The aim of this study was to develop LME, back propagation neural network (BPNN), and mixed-effects NN models that combine the 2 to predict FPG levels.
View Article and Find Full Text PDFDiabetes Res Clin Pract
December 2024
Department of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China. Electronic address:
Aims: This study aimed to assess the prevalence of IH and diabetes, as well as insulin secretion, insulin sensitivity, and related curve patterns in subjects with different glucose tolerance categories according to the diagnostic criteria established by the American Diabetes Association (ADA) and the more recently published International Diabetes Federation (IDF) guidelines.
Methods: We used data of 5,387 adult participants from the Shanghai High-risk Diabetic Screen (SHiDS) study. All participants underwent a five-point 75 g oral glucose tolerance test (OGTT).
Diabetes Ther
December 2024
School of Medicine, Keele University, Staffordshire, UK.
Introduction: We previously reported sex differences in the distribution of glycated haemoglobin (HbA1c) for men/women aged < 50 years vs older individuals, with implications for delayed diabetes diagnosis. Here, we explored whether this pattern was also seen in matched fasting plasma glucose (FPG) levels.
Methods: We extracted data on same-day, paired HbA1c and FPG levels from clinical biochemistry laboratory databases from Mersey and West Lancashire Teaching Hospitals NHS Trust (n = 10,153) and Cambridge University Hospitals NHS Foundation Trust (n = 10,022) between Jan 2019 and Dec 2023.
Biol Trace Elem Res
December 2024
Sección de Medicina Molecular y Traslacional, Centro de Investigación en Ciencias de La Salud y Biomedicina, Universidad Autónoma de San Luis Potosí, Avda Sierra Leona 550, CP 78210, San Luis Potosí, S.L.P., México.
The biological role of zinc-alpha 2-glycoprotein (ZAG) has been associated with lipid mobilization, although this is not entirely clear. The study's aim was to examine the serum levels of ZAG and zinc (Zn) and the Zn/ZAG in a population of children with overweight (OW) and obesity (OB), and their relationship with biochemical parameters. Our study was a cross-sectional analysis of a group of Mexican children aged 6-10 (n = 72).
View Article and Find Full Text PDFAgeing Res Rev
December 2024
School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100026, China. Electronic address:
Background: Despite increasing global awareness of dementia, reliable estimates of the disease burden associated with Early-Onset Dementia (EOD) remain insufficiently quantified. This study aims to estimate the disease burden of EOD, analyze the burden attributable to risk factors from 1990 to 2021, and project these trends to 2050 at global, regional, and national levels, providing essential data to inform public health policy.
Methods: By utilising data from the GBD 2021 database, this study analysed metrics such as age-standardized prevalence (ASPR), mortality (ASMR), and disability-adjusted life years (AS-DALYs) for EOD.
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