Association between triglyceride/high-density lipoprotein ratio and hearing impairment in a Korean population

Lipids and Statin Medication With Sensorineural Hearing Loss: A Mendelian Randomization Study

BACKGROUND

Recent insights suggest that lipids and statin medication play a role in the development of sensorineural hearing loss (SNHL), yet the exact role remains controversial. This research applied Mendelian randomization (MR) to assess whether lipids and statin medication are associated with an increased risk of SNHL.

METHODS

A two-sample MR was used in this study. Genetic instruments were constructed from variants associated with risk factors. Data for lipids and statin medication were obtained from the IEU OpenGWAS project, and for SNHL from the Finngen research project, which comprises 32,487 individuals with SNHL and 331,736 control individuals.

RESULTS

Genetically predicted higher levels of triglycerides were associated with an increased risk of SNHL. The use of genetically predicted atorvastatin was associated with a lower risk of SNHL. Rosuvastatin has demonstrated potential in treating SNHL, yet further investigations are warranted to elucidate its relationship with SNHL. Insufficient evidence was available to suggest that the genetically predicted level of high-density lipoprotein cholesterol or low-density lipoprotein cholesterol or the use of simvastatin were associated with SNHL.

CONCLUSIONS

The study provides genetic evidence suggesting that increased levels of triglycerides in the blood could be a risk factor for SNHL and that the use of certain statin medications, including atorvastatin and rosuvastatin, could reduce the risk of SNHL. These results align with findings from previous observational studies that have linked hyperlipidemia with the risk of SNHL.

LEVEL OF EVIDENCE

According to the Oxford Centre for Evidence-Based Medicine 2011 levels of Evidence, the study has a third level of Evidence Laryngoscope, 2024.

A machine learning screening model for identifying the risk of high-frequency hearing impairment in a general population

BACKGROUND

Hearing impairment (HI) has become a major public health issue in China. Currently, due to the limitations of primary health care, the gold standard for HI diagnosis (pure-tone hearing test) is not suitable for large-scale use in community settings. Therefore, the purpose of this study was to develop a cost-effective HI screening model for the general population using machine learning (ML) methods and data gathered from community-based scenarios, aiming to help improve the hearing-related health outcomes of community residents.

METHODS

This study recruited 3371 community residents from 7 health centres in Zhejiang, China. Sixty-eight indicators derived from questionnaire surveys and routine haematological tests were delivered and used for modelling. Seven commonly used ML models (the naive Bayes (NB), K-nearest neighbours (KNN), support vector machine (SVM), random forest (RF), eXtreme Gradient Boosting (XGBoost), boosting, and least absolute shrinkage and selection operator (LASSO regression)) were adopted and compared to develop the final high-frequency hearing impairment (HFHI) screening model for community residents. The model was constructed with a nomogram to obtain the risk score of the probability of individuals suffering from HFHI. According to the risk score, the population was divided into three risk stratifications (low, medium and high) and the risk factor characteristics of each dimension under different risk stratifications were identified.

RESULTS

Among all the algorithms used, the LASSO-based model achieved the best performance on the validation set by attaining an area under the curve (AUC) of 0.868 (95% confidence interval (CI): 0.847-0.889) and reaching precision, specificity and F-score values all greater than 80%. Five demographic indicators, 7 disease-related features, 5 behavioural factors, 2 environmental exposures, 2 hearing cognitive factors, and 13 blood test indicators were identified in the final screening model. A total of 91.42% (1235/1129) of the subjects in the high-risk group were confirmed to have HI by audiometry, which was 3.99 times greater than that in the low-risk group (22.91%, 301/1314). The high-risk population was mainly characterized as older, low-income and low-educated males, especially those with multiple chronic conditions, noise exposure, poor lifestyle, abnormal blood indices (e.g., red cell distribution width (RDW) and platelet distribution width (PDW)) and liver function indicators (e.g., triglyceride (TG), indirect bilirubin (IBIL), aspartate aminotransferase (AST) and low-density lipoprotein (LDL)). An HFHI nomogram was further generated to improve the operability of the screening model for community applications.

CONCLUSIONS

The HFHI risk screening model developed based on ML algorithms can more accurately identify residents with HFHI by categorizing them into the high-risk groups, which can further help to identify modifiable and immutable risk factors for residents at high risk of HI and promote their personalized HI prevention or intervention.

Correlation between hearing impairment and the Triglyceride Glucose Index: based on a national cross-sectional study

Objective

Data from the National Health and Nutrition Examination Survey (NHANES) were used to assess the association between the triglyceride-glucose (TyG) index and hearing impairment (HI).

Methods

We used eight survey cycles from NHANES 2001-2012 and 2015-2018 to conduct this cross-sectional study. HI was designed as an dependent variable, and the TyG index was selected as an exposure factor (independent variable). The correlation between the two variables was assessed using multiple logistic regression. In order to assess whether there was a non-linear relationship between the TyG index and HI, the TyG index was distributed and a test for trend was conducted (P for trend), followed by smooth curve fitting (penalized spline) and generalized additive model (GAM) regression. We also performed a subgroup analysis to identify sensitive groups whose responses were clearly associated with independent variables.

Results

10,906 participants were finally included in the study, and those with a higher TyG index had a higher frequency of hearing impairment. There was a linear positive correlation between the TyG index and HI. For the low-frequency HI, however, this positive correlation was not statistically significant (OR = 1.05, 95% CI: 0.98, 1.14); however, it was more stable for the high-frequency HI (OR = 1.12, 95% CI: 1.03, 1.22). Additionally, as the TyG index increased, this positive association increased as well (P for trend = 0.05). The HPTA test showed a positive association with more severe HI (simultaneous) as the independent variable increased (OR = 1.14, 95% CI: 1.05-1.24), and this association was even more significant with increasing severity (P for trend 0.05). According to the subgroup analysis, the positive association between TyG index and high-frequency HI was more significant in females, 40-69 years old, without hypertension or diabetes, and when strict high-frequency HI was significant in males, females, 40-69 years old, with hypertension and diabetes.

Conclusion

Participants with a higher TyG index may have a higher risk of HI. TyG index and HI risk showed a linear relationship, which became even more significant when HPTA was included.

Association of Metabolic Syndrome with Sensorineural Hearing Loss

The prevalence of sensorineural hearing loss has increased along with increases in life expectancy and exposure to noisy environments. Metabolic syndrome (MetS) is a cluster of co-occurring conditions that increase the risk of heart disease, stroke and type 2 diabetes, along with other conditions that affect the blood vessels. Components of MetS include insulin resistance, body weight, lipid concentration, blood pressure, and blood glucose concentration, as well as other features of insulin resistance such as microalbuminuria. MetS has become a major public health problem affecting 20–30% of the global population. This study utilized health examination to investigate whether metabolic syndrome was related to hearing loss. Methods: A total of 94,223 people who underwent health check-ups, including hearing tests, from January 2010 to December 2020 were evaluated. Subjects were divided into two groups, with and without metabolic syndrome. In addition, Scopus, Embase, PubMed, and Cochrane libraries were systematically searched, using keywords such as “hearing loss” and “metabolic syndrome”, for studies that evaluated the relationship between the two. Results: Of the 94,223 subjects, 11,414 (12.1%) had metabolic syndrome and 82,809 did not. The mean ages of subjects in the two groups were 46.1 and 43.9 years, respectively. A comparison of hearing thresholds by age in subjects with and without metabolic syndrome showed that the average pure tone hearing thresholds were significantly higher in subjects with metabolic syndrome than in subjects without it in all age groups. (p < 0.001) Rates of hearing loss in subjects with 0, 1, 2, 3, 4, and 5 of the components of metabolic syndrome were 7.9%, 12.1%, 13.8%, 13.8%, 15.5% and 16.3%, respectively, indicating a significant association between the number of components of metabolic syndrome and the rate of hearing loss (p < 0.0001). The odds ratio of hearing loss was significantly higher in subjects with four components of metabolic syndrome: waist circumference, blood pressure, and triglyceride and fasting blood sugar concentrations (p < 0.0001). Conclusions: The number of components of the metabolic syndrome is positively correlated with the rate of sensorineural hearing loss.

Open-angle Glaucoma and Sensorineural Hearing Impairment in the Korean Population

PURPOSE

This study identifies the prevalence and risk factors of sensorineural hearing loss and primary open-angle glaucoma (POAG).

MATERIALS AND METHODS

Patients aged 19 years or older who had undergone both ophthalmologic examination and audiometry as part of the Korea National Health and Nutrition Examination Survey V (2010-2012) were analyzed. Hearing loss was defined as the pure-tone average over 40 decibels based on the automatic hearing test to determine the threshold of airway hearing for each frequency. We investigated the prevalence of glaucoma and hearing loss when they occurred alone or simultaneously. The risk factors for concurrent glaucoma and hearing loss were examined.

RESULT

Among the participants, 6.6% had hearing loss alone, 2.3% had glaucoma alone, and 0.5% had both glaucoma and hearing loss. The weighted prevalence of glaucoma in patients with hearing loss was 7.5%; however, the weighted prevalence of glaucoma was 3.2% among patients without hearing loss, with a significant difference (P < .001). Multivariable logistic regression analysis revealed that the risk factors associated with concurrent glaucoma and hearing loss were age (3.786 times per 10 years, P < .001) and triglyceride level (1.002 times per 1 mg/dL, P = .028).

CONCLUSION

Sensorineural hearing loss and POAG are relevant. If hearing impairment and visual impairment occur together, the quality of life of the patient is worsened and the social burden is greater. Therefore, care should be taken when treating elderly patients with glaucoma.