The combined effect of cigarette smoking and occupational noise exposure on hearing loss: evidence from the Dongfeng-Tongji Cohort Study

Association of Smoke and Nicotine Product Consumption With Sensorineural Hearing Loss: A Population-Level Analysis

OBJECTIVE

To test the hypothesis that use of cigarettes or other products with either cigarette-like smoke profile or high nicotine content by young populations increases the odds of developing sensorineural hearing loss (SNHL).

STUDY DESIGN

Retrospective cohort study.

SETTING

TriNetX US Collaborative Network (2003-2022).

PATIENTS

Approximately 3.6 million patients at least 18 years old.

INTERVENTION

None.

MAIN OUTCOME MEASURES

The primary outcome of interest was diagnosis of SNHL, defined using medical billing codes ( International Classification of Diseases, Tenth Revision , Current Procedural Terminology , etc.). Cohort inclusion criteria included electronic health record entry after 2003, age 18 to 54 or 55+ years at index, and status of cigarette, noncigarette nicotine, or cannabis use. Covariates were controlled via 1:1 propensity score matching for SNHL-related conditions, including diabetes mellitus and ischemic diseases. Odds for developing SNHL were calculated against control subjects aged 18 to 54 years who have no record of nicotine/cannabis use.

RESULTS

Odds for developing SNHL are higher for people 18 to 54 years old who use any nicotine product (odds ratio [95% confidence interval], 5.91 [5.71-6.13]), cigarettes only (4.00 [3.69-4.33]), chewing tobacco only (9.04 [7.09-11.63]), or cannabis only (3.99 [3.60-4.44]) compared with control. People 55+ years old who use no products also showed increased odds for SNHL (4.73 [4.63-4.85]).

CONCLUSIONS

Both nicotine and smoke exposure seem to be strongly associated with increased odds for developing SNHL, with chewing tobacco having the strongest association.

Prevalence and risk factors of hearing loss among the middle-aged and older population in China: a systematic review and meta-analysis

PURPOSE

This paper was aimed at estimating the prevalence and risk factors of hearing loss (HL) among the middle-aged and elderly in China.

METHODS

Databases including the CQVIP (VIP) Database, Chinese National Knowledge Infrastructure (CNKI), China Biology Medicine disc (CBMdisc), Wanfang, PubMed, Web of Science, Excerpta Medica Database (Embase) and the Cochrane Library were comprehensively searched. In this review, random-effect models were used for pooling the prevalence of HL and the odds ratios (ORs) of potential risk factors.

RESULTS

34 studies were included in the meta-analysis. HL among the middle-aged and elderly in China had a pooled prevalence of 45% (95% confidence interval (CI) 40-51%). There were significant differences in the prevalence of HL between males and females (47% vs. 42%), between different screening methods by self-report and pure-tone audiometry (44% vs. 46%), between the middle-aged and the elderly (18% vs. 52%), and between the uneducated and the educated (49% vs. 36%). In urban areas, the prevalence was slightly higher than that in rural areas (50% vs. 48%). The findings suggested that the middle-aged and elderly in the South Central China region (61%, 95% CI 45-78%) and Northwest China (57%, 95% CI 55-58%) were more likely to develop HL. In addition, it was confirmed that advanced age, being male, noise exposure history, hypertension and hyperglycemia were related to a higher prevalence of HL among middle-aged and older adults.

CONCLUSION

The prevalence of HL among the middle-aged and older population in China is 45%, nearly half of the total population. It is urgent to take great efforts to raise people's awareness of HL prevention and early hearing screening.

The Effect of Active and Passive Smoking on Hearing Loss in Noise-Exposed Metal Workers

Background

Many people are exposed to cigarette smoke actively or passively. We aimed to determine the effect of active and passive smoking on hearing thresholds and hearing loss noise-exposed workers.

Methods

This cross-sectional study was conducted on 929 metal workers. We divided the workers into 3 groups according to smoking status-current smokers, nonsmokers, and passive smokers. Audiometric testing was recorded for both ears. Hearing loss was defined by 3 models. The SPSS software Version 24 was used to analyze the collected data. We used an independent t test, chi-square, Fisher exact, and analysis of variance tests and logistic regression, and the significance level was set at P ˂0.05 to interpret the relationships between variables.

Results

The hearing threshold levels at 4000 Hz, high frequencies, and low frequencies were significantly higher in smokers than nonsmokers (P < 0.05). Also, and hearing loss at the 4000 Hz (P = 0.002; odds ratio [OR] = 1.96; 95% CI = 1.27-3.03) and high frequencies (P = 0.001; OR = 2.15; 95% CI = 1.36-3.4) had a significant correlation with smoking. Hearing loss was significantly correlated with passive smoking at 4000 Hz (P < 0.001; OR = 5.87; 95% CI = 3.29-10.47), high frequencies (P < 0.001; OR = 7.16; 95% CI = 3.97-12.89) and low frequencies (P = 0.021; OR = 4.16; 95% CI = 1.12-15.43).

Conclusion

The findings show that active and passive smokers who work in noisy environments are at higher risk for noise-induced hearing loss. Therefore, smoking cessation in smoker workers and reduction of environmental exposure to cigarette smoke is necessary to reduce the exacerbation of hearing loss. Moreover, more attention should be paid to passive smokers and they should be given priority in the same programs.

Independent and Combined Associations of Sleep Duration, Bedtime, and Polygenic Risk Score with the Risk of Hearing Loss among Middle-Aged and Old Chinese: The Dongfeng-Tongji Cohort Study

Evidence available on the independent and combined associations of sleep duration, bedtime, and genetic predisposition with hearing loss was lacking. The present study included 15,827 participants from the Dongfeng-Tongji cohort study. Genetic risk was characterized by polygenic risk score (PRS) based on 37 genetic loci related to hearing loss. We conducted multivariate logistic regression models to assess the odds ratio (OR) for hearing loss with sleep duration and bedtime, as well as the joint association and interaction with PRS. Results showed that hearing loss was independently associated with sleeping ≥9 h/night compared to the recommended 7 to <8 h/night, and with bedtime ≤9:00 p.m. and >9:00 p.m. to 10:00 p.m. compared to those with bedtime >10:00 p.m. to 11:00 p.m., with estimated ORs of 1.25, 1.27, and 1.16, respectively. Meanwhile, the risk of hearing loss increased by 29% for each 5-risk allele increment of PRS. More importantly, joint analyses showed that the risk of hearing loss was 2-fold in sleep duration ≥9 h/night and high PRS, and 2.18-fold in bedtime ≤9:00 p.m. and high PRS. With significant joint effects of sleep duration and bedtime on hearing loss, we found an interaction of sleep duration with PRS in those with early bedtime and an interaction of bedtime with PRS in those with long sleep duration on hearing loss (P_int <0.05), and such relationships were more evident in high PRS. Similarly, the above relationships were also observed for age-related hearing loss and noise-induced hearing loss, particularly the latter. In addition, age-modified effects of sleep patterns on hearing loss were likewise observed, with stronger estimation among those aged <65 years. Accordingly, longer sleep duration, early bedtime, and high PRS were independently and jointly related to increased risk of hearing loss, suggesting the importance of considering both genetics and sleep pattern for risk assessment of hearing loss.

The Combined Effect of Elevated Blood Pressure and Occupational Noise Exposure on Bilateral High-Frequency Hearing Loss: Evidence From a Large Sample Cross-sectional Study

BACKGROUND

Combined effect of elevated blood pressure and occupational noise exposure on hearing loss have rarely been evaluated among Chinese population.

METHODS

This cross-sectional study was conducted in 242,811 participants. Logistic regression model was performed to estimate the independent and combined associations.

RESULTS

Compared with participants without occupational noise exposure, the risk of bilateral high-frequency hearing loss (BHFHL) was significantly higher for noise exposure 10 years or more (odds ratio [OR] = 1.29, 95% confidence interval [95% CI] = 1.23-1.35). Compared with no hypertension, participants with grade 1 hypertension had higher risk of BHFHL in all age groups (OR, 1.14; 95% CI, 1.09-1.20). As to the combined effect, the highest BHFHL risk was found in males (OR, 1.51; 95% CI, 1.37-1.67), especially among participants with grade 1 hypertension older than 50 years (OR, 1.65; 95% CI, 1.46-1.88).

CONCLUSIONS

Elevated blood pressure may synergistically influence hearing loss combined with occupational noise exposure.

Telehealth solutions for assessing auditory outcomes related to noise and ototoxic exposures in clinic and research

Nearly 1.5 billion people globally have some decline in hearing ability throughout their lifetime. Many causes for hearing loss are preventable, such as that from exposure to noise and chemicals. According to the World Health Organization, nearly 50% of individuals 12-25 years old are at risk of hearing loss due to recreational noise exposure. In the occupational setting, an estimated 16% of disabling hearing loss is related to occupational noise exposure, highest in developing countries. Ototoxicity is another cause of acquired hearing loss. Audiologic assessment is essential for monitoring hearing health and for the diagnosis and management of hearing loss and related disorders (e.g., tinnitus). However, 44% of the world's population is considered rural and, consequently, lacks access to quality hearing healthcare. Therefore, serving individuals living in rural and under-resourced areas requires creative solutions. Conducting hearing assessments via telehealth is one such solution. Telehealth can be used in a variety of contexts, including noise and ototoxic exposure monitoring, field testing in rural and low-resource settings, and evaluating auditory outcomes in large-scale clinical trials. This overview summarizes current telehealth applications and practices for the audiometric assessment, identification, and monitoring of hearing loss.

Hearing loss and its associated factors among metal workshop workers at Gondar city, Northwest Ethiopia

Introduction

Noise-induced hearing loss is a permanent sensorineural deficiency, which is caused by exposure to excessive noise sound. Although noise-induced hearing loss due to industrialization is a main public health problem in Ethiopia, studies on the prevalence and associated factors of hearing loss are scarce.

Objectives

This study aimed to assess the prevalence and associated factors of hearing loss among workers at a metal workshop in Gondar city, Northwest Ethiopia.

Methods

A cross-sectional study was employed among 300 participants using a stratified sampling technique. Data were collected using an interviewer-administered questionnaire. Bivariable and multivariable logistic regressions were conducted. In the multivariable logistic regression model, adjusted odds ratios (AOR) with a 95% confidence interval (CI) and a p &lt; 0.05 were computed to determine the level of significance.

Results

The prevalence of hearing loss among metal workshop workers was 30.7% [95% CI: (25.7, 35.7)]. Age between 30 and 44 years [AOR = 2.9; 95% CI: 1.2, 7.1], age between 45 and 65 years [AOR = 3.8; 95% CI (1.5, 9.5)], cigarette smoking [AOR = 2.3; 95% CI: 1.2, 4.5], working area noise level &gt;85 dB [AOR = 2.2; 95% CI: 1.1, 6.5], working experience of 6–10 years [AOR = 1.8; 95% CI: 1.4, 6.0], working experience &gt;10 years [AOR = 3.5; 95% CI: 1.3, 4.3], and using ear protection devices [AOR = 0.3; 95% CI: 0.1, 0.6] were significantly associated with hearing loss.

Conclusion

The prevalence of hearing loss was considerably high. This study revealed that advanced age, cigarette smoking, increased working area noise level, and working experiences were found to increase the odds of having hearing loss. Therefore, it is important to emphasize metal workshop workers that are at high risk of hearing loss and develop preventive strategies to reduce the burden of this problem. Besides, minimizing working area noise levels, proper utilization of ear protection devices, and creating awareness about the impact of hearing loss are recommended.

Hearing loss and hypertension among noise-exposed workers: a pilot study based on baseline data

This study aimed to assess the prevalence of noise-induced hearing loss (NIHL) and hypertension, and the association between NIHL and hypertension using occupational physical examination data of 42,588 noise-exposed workers from local enterprises in Yangzhou between 2015 and 2017. The average binaural high-frequency threshold on average (BHFTA), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were 23.09 ± 11.32 dB, 126.85 ± 15.94 mm Hg and 79.94 ± 11.61 mm Hg. The prevalence of NIHL and hypertension were 24.38% and 25.40%. An increased risk of NIHL and hypertension was observed in the groups of males, aged >35 years, noise exposure time >5 years, noise exposure level >85 dB(A) and smoking. 32.25% NIHL workers had hypertension. NIHL workers were at higher risk of hypertension (adjusted OR = 1.07, 95%CI = 1.02-1.13). This study shows that the noise-exposed workers have high risk of developing NIHL and hypertension.

Association of Cigarette Smoking Patterns Over 30 Years With Audiometric Hearing Impairment and Speech-in-Noise Perception: The Atherosclerosis Risk in Communities Study

IMPORTANCE

The implications of cigarette smoking and smoking cessation for hearing impairment remain unknown. Many studies on this topic have failed to account for attrition among smokers in their findings.

OBJECTIVE

To assess the association of cigarette smoking patterns with audiometric and speech-in-noise hearing measures among participants of the Atherosclerosis Risk in Communities Study.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included participants of the Atherosclerosis Risk in Communities Study from 4 US communities. The analysis includes data from visit 1 (1987-1989) through visit 6 (2016-2017); data were analyzed from March 16 through June 25, 2021. Audiometric hearing and speech-in-noise testing was offered to all participants at visit 6. Participants with incomplete audiometric data or missing data for educational level, body mass index, drinking status, a diabetes or hypertension diagnosis, or occupational noise were excluded. In addition, individuals were excluded if they self-reported as having other than Black or White race and ethnicity, or if they self-reported as having Black race or ethnicity and lived in 2 predominantly White communities.

MAIN OUTCOMES AND MEASURES

Smoking behavior was classified from visit 1 (1987-1989) to visit 6 (2016-2017) using group-based trajectory modeling based on self-reported smoking status at each clinic visit. Hearing was assessed at visit 6. An audiometric 4-frequency (0.5, 1, 2, 4 kHz) pure-tone average (PTA) was calculated for the better-hearing ear and modeled as a continuous variable. Speech-in-noise perception was assessed via the Quick Speech-in-Noise Test (QuickSIN) and modeled continuously. Attrition during the 30 years of follow-up was addressed by inverse probability of attrition weighting.

RESULTS

A total of 3414 participants aged 72 to 94 years (median [IQR] age, 78.8 [76.0-82.9] years; 2032 [59.5%] women) when hearing was measured at visit 6 (2016-2017) were included in the cohort; 766 (22.4%) self-identified as Black and 2648 (77.6%) as White individuals. Study participants were classified into 3 smoking groups based on smoking behavior: never or former smoking at baseline (n = 2911 [85.3%]), quit smoking during the study period (n = 368 [10.8%]), and persistent smoking (n = 135 [4.0%]). In fully adjusted models, persistent smoking vs never or former smoking was associated with an average 2.69 (95% CI, 0.56-4.81) dB higher PTA (worse hearing) and 1.42 (95% CI, -2.29 to -0.56) lower QuickSIN score (worse performance). Associations were stronger when accounting for informative attrition during the study period (3.53 [95% CI, 1.14-5.93] dB higher PTA; 1.46 [95% CI, -2.52 to -0.41] lower QuickSIN scores). Smoking cessation during the study (vs never or former smoking) was not associated with changes in hearing.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, persistent smoking was associated with worse audiometric hearing and speech-in-noise perception. Hearing measures among participants who quit smoking during the study period did not differ from those for never or former smokers, indicating that smoking cessation (as opposed to persistent smoking) may have benefits for hearing health.

Identifying genetic risk variants associated with noise-induced hearing loss based on a novel strategy for evaluating individual susceptibility

BACKGROUND

The overall genetic profile for noise-induced hearing loss (NIHL) remains elusive. Herein we proposed a novel machine learning (ML) based strategy to evaluate individual susceptibility to NIHL and identify the underlying genetic risk variants based on a subsample of participants with extreme phenotypes.

METHODS

Five features (age, sex, cumulative noise exposure [CNE], smoking, and alcohol drinking status) of 5,539 shipbuilding workers from large cross-sectional surveys were included in four ML classification models to predict their hearing levels. The area under the curve (AUC) and prediction accuracy were exploited to evaluate the performance of the models. Based on the prediction error of the ML models, the NIHL-susceptible group (n=150) and NIHL-resistant group (n=150) with a paradoxical relationship between hearing levels and features were separately screened, to identify the underlying variants associated with NIHL risk using whole-exome sequencing (WES). Subsequently, candidate risk variants were validated in an additional replication cohort (n=2108), followed by a meta-analysis.

RESULTS

With 10-fold cross-validation, the performances of the four ML models were robust and similar, with average AUCs and accuracies ranging from 0.783 to 0.798 and 73.7% to 73.8%, respectively. The phenotypes of the NIHL-susceptible and NIHL-resistant groups were significantly different (all p<0.001). After WES analysis and filtering, 12 risk variants contributing to NIHL susceptibility were identified and replicated. The meta-analyses showed that the A allele of CDH23 rs41281334 (odds ratio [OR]=1.506, 95% confidence interval [CI]=1.106-2.051) and the C allele of WHRN rs12339210 (OR=3.06, 95% CI=1.398-6.700) were significantly associated with increased risk of NIHL after adjustment for confounding factors.

CONCLUSIONS

This study revealed two genetic variants in CDH23 rs41281334 and WHRN rs12339210 that associated with NIHL risk, based on a promising approach for evaluating individual susceptibility using ML models.

Association of occupational noise exposure, bilateral hearing loss with atherosclerotic cardiovascular disease risk in Chinese adults

We aimed to explore the association of occupational noise exposure with atherosclerotic cardiovascular disease (ASCVD) risk in Chinese adults. We included 21,412 participants from the Dongfeng-tongji Cohort Study, occupational noise exposure was evaluated through workplace noise level and/or the job titles, hearing loss was defined as a pure-tone mean of 25 dB or higher at 0.5, 1, 2, and 4 kHz in any ear. Compared with participants without occupational noise exposure, the 10-year ASCVD risk was significantly higher for noise exposure duration ≥20 years (OR = 1.20, 95%CI = 1.05-1.32) after adjusting for potential confounders. In the subgroup analysis, the association was only statistically significant in males (OR = 1.86, 95%CI = 1.12-3.14) and participants aged equal to or over 60 years old (OR = 1.20, 95%CI = 1.05-1.33), but not in females (OR = 1.15, 95%CI = 0.71-1.92) and aged below 60 (OR = 1.51, 95%CI = 0.75-2.85). In the subsample analyses (N = 10,165), bilateral hearing loss was associated with a higher risk of 10-year ASCVD (OR = 1.72, 95%CI = 1.30-2.30), especially for participants who were males (OR = 2.40, 95%CI = 1.61-3.42) and aged equal to or over 60 (OR = 1.85, 95%CI = 1.40-2.44). The present study suggests that occupational noise exposure may be a potential risk factor for ASCVD, especially for males and older participants.

Relationship between cigarette smoking and hearing loss in China: A cross-sectional study in Zhejiang province

INTRODUCTION

Hearing loss and cigarette smoking are major challenges that affect public health in China. Revealing the effect of smoking on hearing loss in the Chinese general population is critical for hearing health protection. We investigated the relationship between smoking status and hearing loss in China, especially in stratified sex and age groups.

METHODS

A cross-sectional study was conducted on 4685 individuals aged 20– 80 years in Zhejiang province from 2016 to 2018, with audiometric testing for hearing loss and a structured questionnaire for collecting smoking status and covariates. Logistic regression was used to estimate the association between smoking and hearing loss.

RESULTS

Cigarette smoking was not significantly associated with hearing loss in females and young males. In middle-aged males, after adjusting for covariates, current smokers and past smokers had a significantly higher prevalence of speech-frequency loss (OR=1.65; 95% CI: 1.17–2.33 and OR=1.88; 95% CI: 1.11–3.17; respectively) and high-frequency hearing loss (OR=2.01; 95% CI: 1.43–2.84 and OR=2.64; 95% CI: 1.50–4.66; respectively). In older males, only past smokers had a significantly higher prevalence of speech-frequency hearing loss than never smokers (OR=2.58; 95% CI: 1.38–4.85). Regarding middle-aged and older current smokers, a dose-dependent relationship between smoking intensity and hearing loss was found. Passive smoking was not significantly associated with an increased hearing loss risk in all the three male groups.

CONCLUSIONS

The relationship between cigarette smoking and hearing loss varied according to gender and age. Therefore, the interventions for smoking need to be tailored according to age in males.

Association between Smoking and Noise-Induced Hearing Loss: A Meta-Analysis of Observational Studies

The purpose of this study was to synthesize the results of previously published observational studies through meta-analysis to clarify the association between smoking and noise-induced hearing loss (NIHL). We searched several databases as of October 2019. Based on the results of heterogeneity analysis (Q statistic and I² statistic), a fixed effect model (for no heterogeneity; Q test P > 0.1 and I² ≤ 50%) or a random effects model (for heterogeneity) was used to calculate the pooled odds ratios (ORs). We explored the potential dose-response relationship between smoking and NIHL as well. In total, 27 studies involving 30,465 participants were included. Compared with non-smokers, the pooled OR of current smokers was 2.05 (95% Confidence interval (CI): 1.71–2.46), and of former smokers was 1.11 (95% CI: 1.05–1.18). We found a curve linear association between an increasing number of pack-years (packages/day × smoking years) and risk of NIHL. The dose-response meta-analysis suggested that when the number of pack-years was less than fifteen, the risk of NIHL was increasing, and the highest combined OR was 5.25 (95% CI: 2.30–11.96) for pack-years of fifteen. After fifteen pack-years, the pooled OR had a slow decline. Our study indicated that smoking is a risk factor for NIHL. Current smokers have a higher risk than former smokers, and there is a positive dose-response relationship between smoking and NIHL.

Audiometric notch for the prediction of early occupational hearing loss and its association with the interleukin-1beta genotype

Objectives

Noise-induced hearing loss (NIHL) is a frequent and irreversible industrial-health problem, the early diagnosis of which can prevent hearing deterioration, especially of speech frequencies. This study aimed to assess hearing impairment in workers occupationally exposed to noise. Audiometric notches and IL-1β gene polymorphisms were evaluated.

Methods

The study included 98 workers employed in a textile factory. Pure-tone audiometric testing was conducted for all workers, using a manual pure-tone diagnostic audiometer, and the noise level was measured at four different work sites in a spinning section. IL-1β gene polymorphism was determined using PCR-RFLP methods.

Results

Workers were exposed to a mean noise level of 105.5 dB. As many as 27.6% of them complained of tinnitus and the majority suffered from some degree of hearing loss in either ear, but none of them exceeded 60 dB. Audiometric notches were detected in either one or both ears. Only 28.6% of workers showed the absence of notches. The TT genotype of IL-1β polymorphisms was dominant in 49% of the workers, whereas TC was predominant in 39.8% and CC in 11.2%. The CC genotype was associated with smoking (54.5%) and audiometric notches (100%). The IL-1β genotype distribution showed no significant difference with or without tinnitus.

Conclusion

This study showed an association between the CC genotype and smoking as well as audiometric notches in workers occupationally exposed to noise. Workers showing audiometric notches should be followed up regularly. Further studies are required to confirm the interrelationship amongst tinnitus, audiometric notches, and IL-1β genotypes.

Hearing Loss in Agricultural Workers Exposed to Pesticides and Noise

Agricultural workers who have concurrent exposure to pesticides and noise are at increased risk of hearing loss. We recruited 163 Thai conventional and 172 organic farmers to answer our questionnaires about personal demographics, agricultural activities, and pesticide and agricultural machinery use. This information was used to calculate the years of conventional (pesticide use) farming and the years of agricultural noise exposure, and to estimate semiquantitative metrics for pesticide exposure (cumulative intensity score-years) and cumulative noise exposure (dB(A)-years) for each conventional farmer. All participants underwent pure tone audiometric testing. The mean hearing threshold in the low-frequency band (0.5-2 kHz) and high-frequency band (3-6 kHz) were used for analysis. Years involved in conventional farming and years using agricultural machinery were associated with an increase in the average hearing threshold for the high-frequency band after controlling for age, ever exposed to industrial noise and cigarette smoking. The highest category of cumulative insecticide exposure (score-years), cumulative organophosphates exposure (score-years) and cumulative noise exposure (dB(A)-years) were also associated with an increased high-frequency band hearing threshold among conventional farmers. Results from the full cohort and the subcohort of conventional farmers support each other and the hypothesis that pesticide and noise have an additive effect on hearing, since no model interactions were significant.

Personality and Hearing Acuity: Evidence From the Health and Retirement Study and the English Longitudinal Study of Ageing

OBJECTIVE

Several determinants of age-related hearing impairment have been identified, but little is known about the predictive value of psychological factors. The present study examined whether five-factor model personality traits are prospectively associated with hearing acuity in middle-aged and older adults.

METHODS

Participants were adults aged 50 to 97 years (N > 10,000) drawn from the Health and Retirement Study (2012-2016) and the English Longitudinal Study of Ageing (2010-2014). In each sample, personality, demographic factors, health-related behaviors, body mass index, and memory function were assessed at baseline, and objective hearing acuity was measured 4 years later.

RESULTS

In both samples, higher conscientiousness and openness were associated with better hearing acuity and lower risk of impairment, whereas neuroticism was associated with a higher risk of hearing impairment. In the Health and Retirement Study and English Longitudinal Study of Ageing, respectively, 1 standard deviation (1-SD) higher conscientiousness, 1-SD higher openness, and 1-SD lower neuroticism were related to 13% to 10%, 8% to 6%, and 10% to 13% lower likelihoods of hearing impairment, respectively. In both samples, additional analyses revealed that physical activity and memory mediated the association between personality and hearing.

CONCLUSIONS

The present study provides robust evidence for an association between personality traits and hearing function. The findings broaden knowledge on risk and mitigating factors for age-related hearing impairment, which has implications for the quality of life of middle-aged and older adults.