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Hearing loss is increasingly prevalent and poses a significant public health concern. While both aging and occupational noise exposure are recognized contributors, their interactive effects and gender-specific patterns remain underexplored. This cross-sectional study analyzed data from 135,251 employees in Jiangsu Province, China. Demographic information, noise exposure metrics, and hearing thresholds were obtained through field measurements, questionnaires, and audiometric testing. Multivariate logistic regression, restricted cubic spline modeling, and interaction analyses were conducted. Machine learning models were employed to assess feature importance. A nonlinear relationship between age and high-frequency hearing loss (HFHL) was identified, with a critical inflection point at 37.8 years. Noise exposure significantly amplified HFHL risk, particularly in older adults (OR = 2.564; 95% CI: 2.456-2.677, < 0.001), with consistent findings across genders. Men exhibited greater susceptibility at high frequencies, even after adjusting for age and co-exposures. Aging and noise exposure have a joint association with hearing loss (OR = 2.564; 95% CI: 2.456-2.677, < 0.001) and an interactive association (additive interaction: RERI = 2.075, AP = 0.502, SI = 2.967; multiplicative interaction: OR = 1.265; 95% CI: 1.176-1.36, < 0.001). And machine learning also confirmed age, gender, and noise exposure as key predictors. Aging and occupational noise exert synergistic effects on auditory decline, with distinct gender disparities. These findings highlight the need for integrated, demographically tailored occupational health strategies. Machine learning approaches further validate key risk factors and support targeted screening for hearing loss prevention.
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http://dx.doi.org/10.3390/audiolres15040091 | DOI Listing |
Brain Behav
September 2025
Radiology Department, Yantaishan Hospital, Yantai, Shandong, China.
Objective: To investigate the characteristics of brain structures in patients with noise-induced hearing loss (NIHL) using source-based morphometry (SBM) and to evaluate the correlation between abnormal brain regions and clinical data.
Methods: High-resolution 3D T1 structural images were acquired from 81 patients with NIHL and 74 age- and education level-matched healthy controls (HCs). The clinical data of all subjects were collected, including noise exposure time, monaural hearing threshold weighted values (MTWVs), Mini-Mental State Examination (MMSE), and Hamilton Anxiety Scale (HAMA) scores.
Med Phys
September 2025
Department of Radiology, Stony Brook University, New York, USA.
Background: In contrast-enhanced digital mammography (CEDM) and contrast-enhanced digital breast tomosynthesis (CEDBT), low-energy (LE) and high-energy (HE) images are acquired after injection of iodine contrast agent. Weighted subtraction is then applied to generate dual-energy (DE) images, where normal breast tissues are suppressed, leaving iodinated objects enhanced. Currently, clinical systems employ a dual-shot (DS) method, where LE and HE images are acquired with two separate exposures.
View Article and Find Full Text PDFJpn J Radiol
September 2025
Department of Radiology, the Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221002, Jiangsu, China.
Background: Stroke, frequently associated with carotid artery disease, is evaluated using carotid computed tomography angiography (CTA). Dual-energy CTA (DE-CTA) enhances imaging quality but presents challenges in maintaining high image clarity with low-dose scans.
Objectives: To compare the image quality of 50 keV virtual monoenergetic images (VMI) generated using Deep Learning Image Reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-V (ASIR-V) algorithms under a triple-low scanning protocol in carotid CTA.
Workplace Health Saf
September 2025
Care Delivery Research, Allina Health.
Background: Effective communication and collaboration among clinical and nonclinical staff are critical to the health and safety of the staff, for optimal team performance and for safe patient care. While respiratory protective equipment are routine key strategies to protect healthcare workers from exposure to select respiratory pathogens, they have been demonstrated to disrupt speech intelligibility. The COVID-19 pandemic escalated the need for and utilization of respiratory protection in all healthcare settings.
View Article and Find Full Text PDFEur J Prev Cardiol
September 2025
Department of Internal Medicine, Augusta Health Fishersville, VA, USA.