BackgroundObservational studies suggest that frailty is associated with hearing loss (HL) but with inconsistent results. This study aims to examine such association and to assess its causality.Materials and methodsThe cross-sectional data from the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression models were used to assess the association between HL and frailty index (FI). Genetic variants associated with the FI and HL were obtained from a large genome-wide association study (GWAS) meta-analysis and UK Biobank GWAS. The inverse variance weighting (IVW) method was used to estimate causal effects. Sensitivity analyses were performed to further validate the robustness of results.ResultsIn this cross-sectional analysis, results support the possibility that frailty may be associated with a higher risk of developing HL, with self-reported [odds ratio (OR) = 2.813; 95% CI, 2.386, 3.317; p < 0.001], speech frequency HL (OR = 1.975; 95% CI, 1.679–2.323; p < 0.001), and high frequency HL (OR = 1.748; 95% CI, 1.459–2.094; p < 0.001). In the adjusted model, frail participants remained at high risk of HL. Mendelian randomization (MR) studies showed a bidirectional causal association between genetically predicted FI and risk of HL (FI for exposure: OR = 1.051; 95% CI, 1.020–1.083; p = 0.001; HL for exposure: OR = 1.527; 95% CI, 1.227–1.901; p < 0.001).ConclusionOur observational study found that inter-individual differences in frailty were associated with the risk of developing HL. Genetic evidence suggests a potential bidirectional causal association between FI and HL. Furthermore, the potential mechanisms of this association require investigation.
Objective Growing evidence suggests that alcohol consumption is a risk factor for hearing loss; however, the evidence has been inconsistent. This systematic review and meta-analysis aimed to evaluate the effect of alcohol consumption on hearing loss. Methods We searched several databases up to November 2021, for published articles using the keywords “alcohol drinking” and “hearing loss”. Two investigators independently conducted the study selection and data extraction. Based on the results of the heterogeneity analysis (Q statistic and I2 statistic), a fixed- or random-effects model was used to calculate the pooled odds ratios (ORs). Subgroup and sensitivity analyses were performed to assess the potential sources of heterogeneity and robustness of the pooled estimation. Publication bias in the literature was evaluated using Egger’s test. Results In total, 18 (9 cross-sectional, 5 case-control, and 4 cohort) observational studies were identified in this search; 27,849 participants were included. Compared with non-drinkers, the pooled OR of drinkers was 1.22 (95% confidence interval: 1.09–1.35). Conclusion Evidence suggests a positive association between alcohol consumption and hearing loss. Drinkers were at a higher risk than non-drinkers. Drinking limitations may be useful for preventing hearing loss.
Objectives: Occupational noise-induced hearing loss (NIHL) is one of the most prevalent occupational diseases worldwide. Few studies have been reported on applying kurtosis-adjusted noise energy (e.g., kurtosis-adjusted cumulative noise exposure, CNE-K) as a joint indicator for assessing NIHL. This study aimed to analyze the effectiveness of CNE-K in assessing occupational hearing loss associated with complex noise in typical manufacturing industries.Design: A cross-sectional survey of 1404 Chinese manufacturing workers from typical manufacturing industries was conducted. General demographic characteristics, noise exposure data, and noise-induced permanent threshold shifts (NIPTS) at 3, 4, and 6 kHz (NIPTS 346 ) were collected and analyzed. The role of kurtosis in high-frequency noiseinduced hearing loss (HFNIHL) was also analyzed. The degree of overlap of the two logistic curves (i.e., between complex noise CNE-K and HFNIHL%, and between Gaussian noise CNE and HFNIHL%) was used to evaluate the effectiveness of CNE-K, using a stratified analysis based on age, sex, industry, or job type. Results:The binary logistic regression analysis showed that in addition to age, sex, exposure duration, and Eight-hour Continuous Equivalent A-weighted Sound Pressure Level (L Aeq,8h ), kurtosis was a key factor influencing HFNIHL% in workers (odds ratio = 1.18, p < 0.05), and its odds ratio increased with an increase in kurtosis value. Multiple linear regression analysis demonstrated that the contribution of kurtosis to NIPTS 346 was second to L Aeq,8h . Complex noise led to a higher risk of NIHL than Gaussian noise at frequencies of 3, 4, 6, and 8 kHz after adjusting for age, sex, and CNE (p < 0.05). As kurtosis increased, the notch in the audiogram became deeper, and the frequency at which the notch began to deepen shifted from 3 to 1 kHz. The logistic curve between complex noise CNE-K and HFNIHL% nearly overlapped with that between Gaussian noise CNE and HFNIHL%, and the average difference in HFNIHL% between the two curves decreased from 8.1 to 0.4%. Moreover, the decrease of average difference in HFNIHL% between the two logistic curves was evident in several subgroups, such as male workers, aged <30 and 30 to 50 years, furniture and woodworking industries and gunning and nailing job types with relatively high kurtosis values.Conclusions: Kurtosis, as an indirect metric of noise temporal structure, was an important risk factor for occupational NIHL. Kurtosis-adjusted CNE metric could be more effective than CNE alone in assessing occupational hearing loss risk associated with complex noise.
Background: Observational studies have suggested that there may be an association between telomere length (TL) and hearing loss (HL). However, inferring causality from observational studies is subject to residual confounding effects, reverse causation, and bias. This study adopted a two-sample Mendelian randomization (MR) approach to evaluate the causal relationship between TL and increased risk of HL. Methods: A total of 16 single nucleotide polymorphisms (SNPs) associated with TL were identified from a genome-wide association study (GWAS) meta-analysis of 78,592 European participants and applied to our modeling as instrumental variables. Summary-level data for hearing loss (HL), age-related hearing loss (ARHL), and noise-induced hearing loss (NIHL) were obtained from the recent largest available GWAS and five MR analyses were used to investigate the potential causal association of genetically predicted TL with increased risk for HL, including the inverse-variance-weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode. In addition, sensitivity analysis, pleiotropy, and heterogeneity tests were also used to evaluate the robustness of our findings. Results: There was no causal association between genetically predicted TL and HL or its subtypes (by the IVW method, HL: odds ratio (OR) = 1.216, p = 0.382; ARHL: OR = 0.934, p = 0.928; NIHL: OR = 1.003, p = 0.776). Although heterogenous sites rs2736176, rs3219104, rs8105767, and rs2302588 were excluded for NIHL, the second MR analysis was consistent with the first analysis (OR = 1.003, p = 0.572). Conclusion: There was no clear causal relationship between shorter TLs and increased risk of HL or its subtypes in this dataset.
BackgroundNoise energy has been well-established to increase the risk of occupational noise-induced hearing loss (NIHL). However, the role of noise temporal structure (expressed by kurtosis) or its combination with energy metrics (e.g., kurtosis-adjusted cumulative noise exposure, adj-CNE) in occupational NIHL was still unclear.MethodsA cross-sectional survey of 867 Chinese workers, including 678 metal manufacturing workers and 189 workers exposed to Gaussian noise, was conducted. Noise energy metrics, including LAeq,8h and CNE, kurtosis (β), and adj-CNE were used to quantify noise exposure levels. Noise-induced permanent threshold shift at frequencies 3, 4, and 6 kHz (NIPTS346) and the prevalence of high-frequency NIHL (HFNIHL%) were calculated for each participant. The dose–response relationship between kurtosis or adj-CNE and occupational NIHL was observed.ResultsAmong 867 workers, different types of work had specific and independent noise energy and kurtosis values (p > 0.05). HFNIHL% increased with an increase in exposure duration (ED), LAeq,8h, CNE, or kurtosis (p < 0.01), and there were strong linear relationships between HFNIHL% and ED (coefficient of determination [R2] = 0.963), CNE (R2 = 0.976), or kurtosis (R2 = 0.938, when CNE < 100 dB(A)∙year). The “V” shape notching extent in NIPTS became deeper with increasing kurtosis when CNE < 100 dB(A)∙year and reached the notching bottom at the frequency of 4 or 6 kHz. The workers exposed to complex noise (β ≥ 10) had a higher risk of NIHL than those exposed to Gaussian noise (β < 10) at the frequencies of 3, 4, 6, and 8 kHz (OR > 2, p < 0.01). Moreover, HFNIHL% increased with adj-CNE (p < 0.001). There were strong linear relationships between NIHL and adj-CNE or CNE when β ≥ 10 (R2adj-CNE > R2CNE). After CNE was adjusted by kurtosis, average differences in NIPTS346 or HFNIHL% between the complex and Gaussian noise group were significantly reduced (p < 0.05).ConclusionKurtosis was a key factor influencing occupational NIHL among metal manufacturing workers, and its combination with energy metrics could assess the risk of NIHL more effectively than CNE alone.
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