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Background: Metal exposures are suspected to associate with the risk of hyperuricemia (HUA), but the current results are still conflicting.
Objective: To investigate the associations between multiple plasma metal exposures and HUA risk.
Methods: A cross-sectional study was conducted in 1406 Chinese Han adults who underwent routine physical examination in the Eighth Affiliated Hospital of Sun Yat-Sen University in Shenzhen. The plasma levels of 13 metals were measured by the inductively coupled plasma mass spectrometry (ICP-MS). Multivariable logistic, linear regression models, least absolute shrinkage and selection operator (LASSO) penalized regression analysis, and restricted cubic spline (RCS) models were applied to assess the associations.
Results: The median plasma uric acid concentration in HUA group (434 μmol/L) was significantly higher than that in non-HUA group (305 μmol/L). The multivariate-adjusted odds ratios (95% confidence intervals) of HUA were 1.62(1.08-2.43) for magnesium, 1.61(1.05-2.47) for copper, 1.62(1.06-2.49) for zinc, 1.87(1.26-2.81) for arsenic, 1.50(1.01-2.23) for selenium, and 1.70(1.16-2.49) for thallium based on the single-metal logistic regression models, comparing the highest versus the lowest quartile of metal levels. Further multi-metal logistic, linear regression models and the LASSO analysis all indicated positive associations of zinc, arsenic with HUA risk or uric acid levels. RCS model indicated an inverted V-shaped positive association between zinc levels and HUA risk (p for non-linearity = 0.048, p for overall association = 0.022), while arsenic levels showed a positive and linear dose-response relationship with HUA risk (p for non-linearity = 0.892, p for overall association<0.001).
Conclusions: Higher plasma levels of zinc and arsenic might increase HUA risk and showed positive dose-response relationships. Further cohort studies in larger population are required to testify our findings.
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http://dx.doi.org/10.1016/j.chemosphere.2021.132305 | DOI Listing |
J Med Internet Res
September 2025
Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Leipzig, Germany.
Background: The loss of a loved one is a common yet stressful event in later life. Internet- and mobile-based interventions have been proposed as an effective treatment approach for individuals with prolonged grief.
Objective: The AgE-health study aimed to investigate the efficacy of an eHealth intervention, trauer@ktiv, in reducing prolonged grief symptoms in a sample of older adults.
Age Ageing
August 2025
Department of Nursing Health Services Research, Graduate School of Health Care Sciences, Institute of Science Tokyo, Yushima, Bunkyo-ku, Tokyo, Japan.
Background: Little is known about how ambulatory care sensitive condition (ACSC)-related readmissions can be reduced in acute care settings.
Objective: This study examined the association between transitional care for hospitalised older patients with ACSC and ACSC-related readmissions.
Methods: This retrospective observational cohort study included patients aged 65 years and older admitted with ACSC as the primary diagnosis from 1 April 2022 to 31 January 2023, using linked data from the Diagnosis Procedure Combination and the medical functions of the hospital beds database.
Int J Comput Assist Radiol Surg
September 2025
Division of Plastic and Reconstructive Surgery, Neonatal and Pediatric Craniofacial Airway Orthodontics, Department of Surgery, Stanford University School of Medicine, 770 Welch Road, Palo Alto, CA, 94394, USA.
Background: Alveolar molding plate treatment (AMPT) plays a critical role in preparing neonates with cleft lip and palate (CLP) for the first reconstruction surgery (cleft lip repair). However, determining the number of adjustments to AMPT in near-normalizing cleft deformity prior to surgery is a challenging task, often affecting the treatment duration. This study explores the use of machine learning in predicting treatment duration based on three-dimensional (3D) assessments of the pre-treatment maxillary cleft deformity as part of individualized treatment planning.
View Article and Find Full Text PDFJ Behav Med
September 2025
Department of Psychology and Human Development, Vanderbilt University, 230 Appleton Place, Nashville, TN, 37203‑5721, USA.
Estimating statistical power is essential for designing behavioral medicine studies efficiently and conserving finite resources. Sometimes behavioral medicine researchers are interested in calculating power for 1-sided z-tests of individual parameters (e.g.
View Article and Find Full Text PDFEnviron Monit Assess
September 2025
Indira Gandhi Conservation Monitoring Centre, World Wide Fund-India, New Delhi, 110003, India.
Understanding the intricate relationship between land use/land cover (LULC) transformations and land surface temperature (LST) is critical for sustainable urban planning. This study investigates the spatiotemporal dynamics of LULC and LST across Delhi, India, using thermal data from Landsat 7 (2001), Landsat 5 (2011) and Landsat 8 (2021) resampled to 30-m spatial resolution, during the peak summer month of May. The study aims to target three significant aspects: (i) to analyse and present LULC-LST dynamics across Delhi, (ii) to evaluate the implications of LST effects at the district level and (iii) to predict seasonal LST trends in 2041 for North Delhi district using the seasonal auto-regressive integrated moving average (SARIMA) time series model.
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