Li-Mei You,* De-Chang Zhang,* Chang-Shui Lin, Qiong Lan

Department of Otolaryngology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, Fujian, 364000, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Qiong Lan, Department of Otolaryngology, Longyan First Affiliated Hospital of Fujian Medical University, No. 105, Jiuyi Northern Street, Xinluo District, Longyan, Fujian, 364000, People’s Republic of China, Email 13860239930@163.com

Background: Phthalate metabolites are pervasive in the environment and linked to various health issues. This study aimed to investigate the relationship between phthalate metabolites and hearing loss.
Methods: We conducted a cross-sectional study with 1713 participants based on the National Health and Nutrition Examination Survey 2015– 2018. Participants were defined as speech-frequency hearing loss (SFHL) or high-frequency hearing loss (HFHL). We analyzed the baseline characteristics of participants and assessed the detection rates of phthalate metabolites in samples. Phthalate metabolites with detection rates of > 85% were enrolled. Then, restricted cubic spline and multivariable logistic regression analyses were conducted to explore the association of phthalate metabolites with hearing loss. Multi-model analysis was employed to select an optimal predictive model for HFHL based on phthalate metabolites and clinical factors.
Results: Among participants, 24.518% had SFHL and 41.998% had HFHL, associated with older age, higher BMI, male, non-Hispanic white, lower physical activity levels, higher exposure to work noise, hypertension, and diabetes. Monobenzyl phthalate (MBZP) showed a positive linear association with both SFHL and HFHL. Multivariable logistic regression revealed MBZP as a significant risk factor for HFHL (odds ratio=1.339, 95% confidence interval, 1.053– 1.707). According to the area under curve (AUC) values, the logistic regression model had the best diagnostic performance of HFHL, with the highest AUC values of 0.865 in the test set. In the model, gender, diabetes, and MBZP were the top predictors of HFHL.
Conclusion: The study identified a significant association between MBZP exposure and HFHL, highlighting the need to reduce phthalate exposure.

Keywords: hearing loss, phthalate metabolites, monobenzyl phthalate, machine learning models, cross-sectional