Abstract
Abstract
Objectives
To investigate the relationship between herpes simplex virus (HSV) and hearing loss using comprehensive population-based research.
Design
This cross-sectional study utilised data from the National Health and Nutrition Examination Survey (NHANES) to examine the relationship between HSV (types 1 and 2) and hearing loss. The final sample comprised 4608 participants aged 20–49 years. Weighted multivariate regression, subgroup and sensitivity analyses were employed for statistical evaluations.
Setting
Utilising the NHANES data, this cross-sectional study provides insights into the American population aged 20–49 years.
Participants
The study includes 4608 participants from the NHANES 2011–2012 and 2015–2016 cycles, focusing on those with complete data on HSV infection and hearing assessment.
Interventions (exposure)
The study analyses the association between HSV (types 1 and 2) infection and hearing loss, using weighted multivariate regression for statistical evaluations.
Results
We observed an association between HSV-1 infection and an increased likelihood of hearing impairment (OR, 1.4 (95% CI 1.1 to 1.9)). A similar association was noted for those coinfected with HSV-1 and HSV-2 (OR, 1.6 (95% CI 1.1 to 2.3)). Similarly, higher grades of hearing loss and elevated pure-tone averages were more prevalent in these groups. Notably, the association between HSV-1 and hearing impairment was more pronounced in individuals aged 20–34 (OR, 2.1 (95% CI 1.4 to 3.3); P for interaction=0.020) and those with a body mass index (BMI) below 30 (OR, 1.8 (95% CI 1.1 to 2.8); P for interaction=0.028).
Conclusions
Our findings suggest an association between HSV-1 infection or coinfections with HSV-1 and HSV-2 and the presence of hearing impairment. The association appears particularly pronounced among younger individuals and those with a lower BMI. Further prospective research is needed to explore the causal impact of HSV on auditory function.
Keywords: Audiology, Epidemiology, VIROLOGY
STRENGTHS AND LIMITATIONS OF THIS STUDY.
The use of a large, nationally representative sample increases the generalisability of the results.
Application of rigorous statistical methods enhances the reliability of the findings.
The reliance on laboratory-confirmed herpes simplex virus (HSV) status ensures accurate assessment.
The study does not establish whether HSV infections were present from birth or acquired later, a factor that could significantly impact the results.
Introduction
The herpes simplex virus (HSV) is a viral pathogen characterised by its enveloped structure and possession of double-stranded DNA.1 HSV-1 is primarily linked to the manifestation of oral herpes, whereas HSV-2 is frequently associated with the occurrence of genital herpes.2 HSV infections are globally prevalent, with approximately 67% of individuals under 50 infected with HSV-1 and 13% of those aged 15–49 carrying HSV-2.3 4 Furthermore, HSV-1 predominates in developed nations, while HSV-2 is more prevalent in developing countries.5
Hearing loss in the adult population can be attributed to various causes, including age,6 noise,7 ototoxic medications,8 9 smoking,10 diabetes,11 autoimmune disorders12 and others. However, the potential contribution of viral infections, including HSV, to the aetiology of hearing loss is often overlooked. The WHO hearing report documented that exposure to HSV-1 and HSV-2 may be a risk factor for hearing loss across the lifespan.13 Neonatal HSV-1 infections exhibit a higher propensity for encephalitis and hearing impairment when compared with HSV-2, resulting in significant neurological complications.14,16 Previous studies have reported substantial auditory impairment linked to herpes simplex meningitis or encephalitis,17,20 and empirical evidence indicates that the HSV has deleterious effects on the cochlear and vestibular systems.21 22
Notwithstanding, despite these observations, large-scale studies investigating the association between HSV infection status and hearing loss in the general adult population are scarce. To fill this research gap, we employed data from the 2011–2012 and 2015–2016 cycles of the National Health and Nutrition Examination Survey (NHANES) to explore the relationship between HSV infections and auditory impairment among American adults between the ages of 20–49.
Materials and methods
Study design
In the present investigation, we analysed data from the NHANES,23 a comprehensive nationwide study conducted annually by the National Centre for Health Statistics in collaboration with the Centres for Disease Control and Prevention. The NHANES uses a complex, multistage probability sampling design to ensure that the individuals selected for the study accurately represent the civilian population of the USA. During the 2011–2012 and 2015–2016 NHANES cycle, a total of 19 727 individuals completed the interview, while 18 882 individuals underwent examinations. The study primarily concentrated on participants aged 20–49 years, as this was the group for which data from both audiogram assessments and HSV blood tests were available in NHANES. We excluded 13 352 individuals outside this age range and an additional 922 with missing or incomplete audiogram or HSV test data (see online supplemental table 1), resulting in a final sample size of 4608 participants. The NHANES protocol was endorsed by the National Centre for Health Statistics’ ethical review board for human subjects. All participants gave their informed written consent. As this study utilises publicly available, anonymised NHANES data, it does not require additional ethical review by the Ethics Committee of Tongji Hospital.
Patient and public involvement
None.
Audiometric testing
In the 2011–2012 and 2015–2016 NHANES cycles, a comprehensive hearing assessment was conducted on adults aged between 20 and 69 years. Individuals wearing hearing aids who were unable to remove them for the examination, as well as those experiencing significant ear discomfort during the assessment that rendered headphone usage intolerable, were excluded from this test. The assessment took place in a noise-controlled booth within a mobile examination centre (MEC). Experienced examiners measured hearing levels at seven different frequencies (0.5, 1, 2, 3, 4, 6 and 8 kHz) for each ear. The modified Hughson Westlake procedure was used for testing with the audiometer’s automated mode. It could assess from −10 to 100 dB at 500–6000 Hz, and −10 to 90 dB at 8000 Hz. Manual mode allowed testing up to 120 dB (110 dB at 8000 Hz). The equipment used included an audiometer (AD226; Interacoustics) with over-ear headphones (TDH-39; Telephonics), which were replaced by insert earphones (E•A•Rtone 3A; Etymotic Research) for those with asymmetrical hearing loss or collapsing ear canals. The surrounding noise was consistently monitored. The pure-tone average (PTA) was calculated as the average threshold across four frequencies (0.5, 1, 2 and 4 kHz). An individual was considered to have hearing impairment if they had a PTA of 20 dB or higher in at least one ear. Using the WHO classification13 and the PTA of the better-performing ear, we identified six grades of hearing impairment: mild (20–34 dB), moderate (35–49 dB), moderately severe (50–64 dB), severe (65–79 dB), profound (80–94 dB) and deaf (95 dB or above).
HSV serologic testing
In the NHANES studies conducted during the 2011–2012 and 2015–2016 periods, HSV serologic testing was performed on eligible participants aged 14–49 years for HSV-1 and 18–49 years for HSV-2. Blood specimens were obtained within a MEC. The HSV testing method used monoclonal antibodies and affinity chromatography to isolate type-specific glycoproteins, gG-1 (HSV-1) and gG-2 (HSV-2), to serve as antigens for serologic assays. Enzymatic immunodot assays were performed using a solid-phase approach, in which gG-1 or gG-2 was immobilised on a nitrocellulose disk coated with bovine serum albumin to minimise non-specific binding. After incubating the test serum, specific antibodies were allowed to bind to the antigen. A positive result was indicated by a blue dot at the centre of the disk. Reactivity with gG-1 implied HSV-1 infection, while reactivity with gG-2 indicated HSV-2 infection. In the final report, results were presented as either positive or negative, indicating the presence or absence of anti-HSV-1 or HSV-2 antibodies in the sample. An ‘Indeterminate’ outcome was interpreted as a negative result. In our analysis, we created three binary variables: HSV-1 infection (indicating positive tests for HSV-1 vs others), HSV-2 infection (indicating positive tests for HSV-2 vs others) and coinfected (denoting positive tests for both HSV-1 and HSV-2 vs others).
Covariate
The study carefully considered a variety of confounding variables to enhance the accuracy of the findings. These variables were grouped based on sociodemographic and lifestyle characteristics, medical history, hearing-related conditions and overall health status. Specific variables included age (segmented into two groups: 20–34 and 35–49 years), race/ethnicity (Hispanic, non-Hispanic black, non-Hispanic white and other), educational level (less than high school, high school graduate and more than high school), body mass index (BMI) (<25, 25–30 and ≥30), use of hearing aids or cochlear implants and exposure to noise (affirmative response to either ‘Ever exposed to very loud noise at work?’ or ‘Had off-work exposure to loud noise?’). Also considered were high blood pressure (HBP, the use of antihypertensive medication or average blood pressure of 140/90 mm Hg or higher, calculated from three separate measurements), history of cardiovascular disease (positive response to questions about congestive heart failure, coronary heart disease, angina/angina pectoris, heart attack or stroke), history of respiratory disease (positive response to having chronic bronchitis and/or emphysema) and history of cancer (affirmative response to ‘Ever told you had cancer or malignancy?’). Sleep trouble was identified by a positive response to the question, ‘Have you ever told a doctor or other health professional that you have trouble sleeping?’ Responses marked as ‘don’t know’ or ‘reject’ were treated as missing data.
In our study, we adjusted for several covariates to minimise confounding in examining the relationship between HSV infection and hearing loss. We included age, race/ethnicity and education level, recognising their dual influence on both HSV prevalence and hearing loss risk. BMI was also considered for its role in systemic inflammation and vascular health, potentially affecting cochlear function. Noise exposure, a well-known independent risk factor for hearing loss, was included to isolate the specific association of HSV. Additionally, we controlled for the use of hearing aids or cochlear implants, which correlate with demographic and health variables such as socioeconomic status and healthcare access. Other health conditions, including high blood pressure, cardiovascular, respiratory diseases, cancer and sleep disturbances, were adjusted for due to their possible impacts on hearing via physiological pathways. These adjustments aim to enhance the statistical integrity and generalisability of our findings on HSV and hearing outcomes.
Statistical analysis
In all analyses, we used weight-adjusted methods tailored to the NHANES complex survey design and adhered to established statistical reporting guidelines.23 Categorical variables were presented by counts, accompanied by weighted proportions, or by weighted proportions with associated SEs and the Rao-Scott χ2 tests were used for statistical assessment. The Wilcoxon rank-sum test was used to compare continuous variables. Depending on the data type of the response variable, we implemented distinct regression models. For the binary outcome, logistic regression was utilised to model the probability of hearing impairment, defined as a PTA of 20 dB or higher in at least one ear. Ordinal logistic regression was employed for the ordinal outcome, which involved classifying the severity of hearing impairment into six grades: mild, moderate, moderately severe, severe, profound and deaf. Finally, linear regression was used to analyse the continuous outcome variable, which measured the PTA of the better-performing ear. In the regression analyses, we adjusted for potential confounders, including age, sex, race/ethnicity, education, BMI, comorbidities (such as cardiovascular diseases, hypertension, chronic obstructive pulmonary disease, diabetes and cancer), sleep patterns and hearing-related factors (such as noise exposure and use of hearing aids or cochlear implants). A complete case analysis was conducted to manage instances of missing data (NAs). The results of the regression model analyses were presented as OR or regression coefficients (β), along with 95% CIs and corresponding p values. We also conducted stratified and interaction analyses to assess potential variations in the association between the primary exposure and outcome across distinctive subgroups and under various influencing factors. For the stratified analyses, we divided the study population into multiple, mutually exclusive subgroups based on specific characteristics or factors. In the interaction analyses, we incorporated interaction terms between the primary exposure and each potential effect modifier into the statistical models. The significance of the interaction was evaluated using the p-value for the interaction term. In the sensitivity analysis, we used the E-value to assess the robustness of our primary exposure-outcome association against potential unmeasured confounding. We used the ‘survey' package in R for analysing complex survey samples. All analyses were performed using RStudio (V. 2022.07.2+576, RStudio, Boston, MA) and R (http://www.R-project.org). A two-sided p-value of <0.05 was considered statistically significant.
Results
The NHANES 2011–2012 and 2015–2016 study analysed a sample of 4608 adults aged 20–49 years, with a weighted mean age of 34.5 years (SE: 0.3). The gender distribution was balanced, with 50.4% of participants being male. The weighted proportions for race were as follows: 18.6% Hispanic, 60.1% non-Hispanic White and 11.8% non-Hispanic Black. Missing data were observed for several variables, including hypertension (n=252), BMI (n=17) and other factors (n=4). Table 1 presents the sample sizes, weighted percentages and significance levels for discrepancies across categories, covering various sociodemographic factors, hearing-related conditions and medical history aspects. Significant differences in mean thresholds were identified when comparing control and infection statuses across all frequency ranges (figure 1).
Table 1. Demographic attributes divided by audiometric outcomes.
| No. of participants (%) | P value | |||
| Total (n=4608) | Normal hearing (n=4135) | HI (n=473) | ||
| Age, years | ||||
| 20–34 | 2509 (53.5) | 2355 (55.7) | 154 (32.7) | <0.001 |
| 35–49 | 2099 (46.5) | 1780 (44.3) | 319 (67.3) | |
| Gender | ||||
| Male | 2284 (50.4) | 1995 (48.8) | 289 (65.3) | <0.001 |
| Female | 2324 (49.6) | 2140 (51.2) | 184 (34.7) | |
| Race/ethnicity | ||||
| Hispanic | 1178 (18.6) | 1055 (18.5) | 123 (19.5) | 0.414 |
| Non-Hispanic white | 1538 (60.1) | 1362 (59.9) | 176 (61.7) | |
| Non-Hispanic black | 1034 (11.8) | 944 (12.0) | 90 (10.3) | |
| Other | 858 (9.5) | 774 (9.6) | 84 (8.5) | |
| Educational level | ||||
| Less than high school | 803 (13.4) | 678 (12.8) | 125 (19.9) | <0.001 |
| High school | 939 (19.2) | 816 (18.3) | 123 (27.1) | |
| More than high school | 2866 (67.4) | 2641 (68.9) | 225 (53.0) | |
| BMI | ||||
| <25 | 1522 (32.9) | 1402 (34.0) | 120 (22.8) | 0.006 |
| ≥25, <30 | 1373 (31.5) | 1225 (31.1) | 148 (34.6) | |
| ≥30 | 1696 (35.6) | 1493 (34.9) | 203 (42.7) | |
| Hypertension | 725 (15.3) | 608 (14.5) | 117 (22.9) | <0.001 |
| Cardiovascular disease history | 90 (1.6) | 74 (1.5) | 16 (3.3) | 0.027 |
| Respiratory disease history | 193 (4.4) | 165 (4.2) | 28 (5.4) | 0.309 |
| Diabetes mellitus | 229 (3.7) | 182 (3.4) | 47 (7.1) | 0.002 |
| Cancer history | 99 (3.3) | 82 (3.0) | 17 (5.5) | 0.045 |
| Noise exposure | 1306 (30.0) | 1121 (28.7) | 185 (42.2) | <0.001 |
| Hearing aid or cochlear implant | 25 (0.6) | 6 (0.1) | 19 (5.4) | <0.001 |
| Sleep disorder | 982 (24.5) | 863 (24.0) | 119 (28.8) | 0.072 |
| HSV infections | ||||
| HSV-1 | 2811 (54.6) | 2471 (53.6) | 340 (64.3) | 0.002 |
| HSV-2 | 892 (16.2) | 774 (15.7) | 118 (21.3) | 0.037 |
| Coinfected | 578 (9.7) | 489 (9.1) | 89 (14.5) | 0.005 |
BMI, body mass index; HI, hearing impairment; HSV, herpes simplex virus
Figure 1. Comparison of mean hearing thresholds across various frequencies in individuals with differing HSV infection statuses, accompanied by error bars. The mean threshold for a single frequency in a participant was determined by calculating the average of the values obtained from both ears. Thresholds for all frequencies (0.5, 1, 2, 3, 4, 6 and 8 kHz) tested were calculated. A weighted Wilcoxon rank-sum test was employed and the analysis revealed significant differences across all comparisons made. HSV, herpes simplex virus.
After adjusting for age, sex and race/ethnicity, participants with HSV-1 infection and those with coinfection of HSV-1 and HSV-2 were associated with a higher prevalence of hearing impairment (HSV-1: OR, 1.4 (95% CI 1.1 to 1.9); coinfected: OR, 1.6 (95% CI 1.1 to 2.3)), a greater grade of hearing loss (HSV-1: OR, 1.4 (95% CI 1.1 to 1.8); coinfected: OR, 1.6 (95% CI 1.2 to 2.2)) and elevated PTA (HSV-1: β, 1.04 (95% CI 0.33 to 1.75); coinfected: β, 1.88 (95% CI 1.04 to 2.71)) in comparison to those without HSV-1 infection and coinfection of HSV-1 and HSV-2 (table 2). These associations mostly remained consistent after further adjustments for age, sex, race/ethnicity, education, BMI, concurrent conditions (cardiovascular diseases, HBP, respiratory conditions, diabetes and cancer), sleep and hearing status (noise exposure and hearing aid or cochlear implantation). The relationship between HSV-2 infection and hearing loss was significant when defining grades of hearing loss (OR, 1.4 (95% CI 1.0 to 2.0)) and PTA (β, 1.17 (95% CI 0.45 to 1.89)) as outcomes in models adjusted for age, sex and race/ethnicity. The association between HSV-2 infection and grades of hearing loss did not reach statistical significance when additional confounders were considered.
Table 2. The relationship between hearing impairment and HSV infections.
| Model 1* | Model 2† | Model 3‡ | ||||
| OR or β (95% CI) | P value | OR or β (95% CI) | P value | OR or β (95% CI) | P value | |
| HI | ||||||
| HSV-1 | 1.4 (1.1 to 1.9) | 0.023 | 1.4 (1.0 to 1.8) | 0.031 | 1.4 (1.0 to 1.9) | 0.035 |
| HSV-2 | 1.4 (1.0 to 2.0) | 0.059 | 1.4 (1.0 to 2.0) | 0.081 | 1.3 (0.9 to 2.0) | 0.147 |
| Coinfected | 1.6 (1.1 to 2.3) | 0.010 | 1.6 (1.1 to 2.2) | 0.017 | 1.4 (0.9 to 2.1) | 0.092 |
| Grade | ||||||
| HSV-1 | 1.4 (1.1 to 1.8) | 0.021 | 1.3 (1.0 to 1.8) | 0.031 | 1.5 (1.1 to 2.0) | 0.014 |
| HSV-2 | 1.4 (1.0 to 2.0) | 0.044 | 1.4 (1.0 to 1.9) | 0.065 | 1.4 (1.0 to 2.0) | 0.079 |
| Coinfected | 1.6 (1.2 to 2.2) | 0.004 | 1.5 (1.1 to 2.1) | 0.008 | 1.5 (1.0 to 2.1) | 0.039 |
| PTA § | ||||||
| HSV-1 | 1.04 (0.33 to 1.75) | 0.008 | 0.91 (0.22 to 1.61) | 0.016 | 0.84 (0.18 to 1.50) | 0.025 |
| HSV-2 | 1.17 (0.45 to 1.89) | 0.004 | 1.06 (0.35 to 1.78) | 0.007 | 0.97 (0.35 to 1.59) | 0.008 |
| Coinfected | 1.88 (1.04 to 2.71) | <0.001 | 1.73 (0.90 to 2.55) | <0.001 | 1.47 (0.66 to 2.27) | 0.003 |
Model 1 was adjusted for age, sex, and race/ethnicity.
Model 2 was adjusted for age, sex, race/ethnicity, and education.
Model 3 was adjusted for age, sex, race/ethnicity, education, BMI, concurrent conditions (cardiovascular diseases, HBP, respiratory diseases, diabetes, and cancer), sleep, and hearing-related status (noise exposure and hearing aid or cochlear implantation).
In the regression analysis pertaining to PTA in the better ear, the regression coefficient (β) and the corresponding 95% CI CI are presented.
BMIbody mass indexHBPhigh blood pressureHIhearing impairmentHSVherpes simplex virusPTApure-tone averageβunstandardised regression coefficient
The stratified analysis demonstrated that the relationship between HSV-1 and hearing impairment was markedly stronger in individuals aged 20–34 compared with those aged 35–49 (OR, 2.1 (95% CI 1.4 to 3.3) vs 1.1 (95% CI 0.8 to 1.6); P for interaction=0.020). Additionally, a more robust association was observed in participants with a BMI<30 (OR, 1.8 (95% CI 1.1 to 2.8) vs 1.1 (95% CI 0.7 to 1.6); P for interaction=0.028). Our analysis revealed no significant interaction between HSV-1 and hearing impairment with respect to sex, race/ethnicity, education, hypertension status, noise exposure or sleep-related issues (table 3).
Table 3. Stratified and interaction analysis for the relationship between HSV infection and hearing impairment*.
| HSV-1 | HSV-2 | Coinfected | ||||
| OR (95% CI) | P value for interaction † | OR (95% CI) | P value for interaction | OR (95% CI) | P value for interaction | |
| Age, y | ||||||
| 20–34 | 2.1 (1.4 to 3.3)* | 0.020 | 1.2 (0.7 to 2.2) | 0.675 | 1.8 (0.9 to 3.6) | 0.397 |
| 35–49 | 1.1 (0.8 to 1.6) | 1.3 (0.9 to 2.0) | 1.3 (0.8 to 2.0) | |||
| Gender | ||||||
| Male | 1.2 (0.9 to 1.7) | 0.149 | 1.2 (0.6 to 2.3) | 0.460 | 1.5 (0.7 to 2.9) | 0.820 |
| Female | 1.7 (0.9 to 3.2) | 1.4 (0.9 to 2.4) | 1.3 (0.9 to 1.9) | |||
| Race/ethnicity | ||||||
| White | 1.4 (0.8 to 2.2) | 0.574 | 1.4 (0.7 to 2.7) | 0.872 | 1.4 (0.6 to 3.1) | 0.853 |
| Nonwhite | 1.5 (1.0 to 2.2)* | 1.3 (0.9 to 1.8) | 1.4 (1.0 to 2.1) | |||
| Educational level | ||||||
| < high school | 1.8 (0.8 to 3.9) | 0.888 | 2.1 (1.3 to 3.6)** | 0.236 | 2.5 (1.3 to 4.5)** | 0.220 |
| ≥ high school | 1.3 (1.0 to 1.8) | 1.1 (0.7 to 1.8) | 1.1 (0.6 to 1.8) | |||
| Hypertension | ||||||
| With | 1.7 (0.8 to 3.6) | 0.997 | 1.2 (0.6 to 2.4) | 0.119 | 1.2 (0.7 to 2.2) | 0.064 |
| Without | 1.3 (0.9 to 1.9) | 1.4 (0.9 to 2.1) | 1.5 (0.9 to 2.4) | |||
| BMI | ||||||
| <30 | 1.8 (1.1 to 2.8)* | 0.028 | 1.5 (0.8 to 2.6) | 0.460 | 1.6 (0.9 to 2.9) | 0.437 |
| ≥30 | 1.1 (0.7 to 1.6) | 1.1 (0.7 to 1.9) | 1.2 (0.7 to 2.2) | |||
| Noise exposure | ||||||
| With | 1.7 (1.0 to 2.7)* | 0.648 | 1.2 (0.7 to 2.0) | 0.465 | 1.1 (0.6 to 2.0) | 0.287 |
| Without | 1.3 (0.9 to 1.9) | 1.4 (0.8 to 2.2) | 1.6 (1.0 to 2.5) | |||
| Sleep trouble | ||||||
| With | 1.1 (0.6 to 1.8) | 0.138 | 1.4 (0.7 to 3.0) | 0.383 | 1.4 (0.7 to 2.9) | 0.707 |
| Without | 1.6 (1.1 to 2.3)* | 1.2 (0.8 to 1.7) | 1.3 (0.9 to 2.0) | |||
*, **,*, **, and *** in statistics denote p-values less than 0.05, 0.01, and 0.001 respectively, signifying increasing levels of statistical significance.
Covariates adjusted including age, sex, race/ethnicity, education, BMI, concurrent conditions (cardiovascular diseases, HBP, respiratory diseases, diabetes, cancer), sleep, and hearing-related status (noise exposure and hearing aid or cochlear implantation).
The p-value for interaction is calculated by evaluating the significance of the coefficient for the interaction term in the regression model.
BMI, body mass index; HBPhigh blood pressureHSVherpes simplex virus
Discussion
Our study revealed a significant inverse relationship between hearing ability and HSV infection, with a distinct emphasis on HSV-1. The observed associations remained significant even after adjusting for potential confounding factors such as age, sex, race/ethnicity, BMI, comorbidities (including cardiovascular diseases, hypertension, chronic obstructive pulmonary disease, diabetes and cancer), sleep patterns and hearing-related factors (including noise exposure, and the use of hearing aids or cochlear implants). Additionally, the observed relationship was notably pronounced in individuals with lower age and BMI values.
Our findings are consistent with a retrospective study that demonstrated an increased prevalence of hearing loss among children infected with HSV-1, but not HSV-2.24 Nevertheless, the available evidence remains insufficient to conclusively determine a relationship between HSV infections and hearing loss in paediatric populations.15 Furthermore, case reports have documented hearing loss in association with herpes simplex meningitis or encephalitis.16 17 20 The outcomes of hearing recovery following acyclovir therapy have been inconsistent.20 25
The exact mechanism by which HSV infection may lead to hearing impairment is not yet fully understood. These pathways remain hypothetical and require further investigation to establish a causal link. For congenital infection, murine neural stem cells infected with HSV-1 exhibit notably diminished SOX2 expression.26 This finding correlates with HSV-induced cochlear abnormalities, as SOX2 is pivotal for the development of the cochlear duct.27 Direct viral invasion is observed in the stria vascularis’ columnar epithelial cells in the HSV labyrinthitis mouse model.22 HSV antigen and DNA have been identified in the inner ears of human subjects suffering from hearing disorders, as evidenced by both autopsy and biopsy samples.28,30 This evidence implicates a potential role of HSV in inner ear pathology, leading to a consequential hearing impairment. Concurrently, HSV infections have been suggested to trigger autoimmune responses.31 32 In one case, a patient suffering from bilateral sudden sensorineural hearing loss, which was akin to Ramsay Hunt syndrome but induced by HSV and not the varicella-zoster virus, demonstrated positive autoimmune markers.33 Such an autoimmune response may be associated with the pathophysiology of autoimmune inner ear disease.
In a recent cross-sectional study,24 it was noted that ears affected by HSV-1 exhibited a 50% prevalence of moderate hearing loss in the paediatric population, while instances of mild hearing loss were less frequently observed. In contrast, in our distinct population group, about 80% of the examined ears had mild hearing loss (see online supplemental table 2). Furthermore, there was no significant difference in the grade, configuration or PTA of ears with thresholds exceeding 20 dB across different HSV infection statuses (including coinfected, HSV-1 only, HSV-2 only and uninfected groups) (see online supplemental table 2). Similarly, no significant differences were found in the occurrence rates of unilateral versus bilateral hearing loss across the HSV infection groups (see online supplemental table 3). This suggests that the characteristics of hearing loss in individual ears are not significantly influenced by the type or presence of HSV infection. However, it is important to note that these conclusions were based on a relatively small sample size, as the prevalence of hearing impairment within the total study population was quite low.
In the present study, we highlighted several strengths that lend credibility to our findings. We leveraged data from audiograms and HSV blood tests, derived from the well-regarded, population-based NHANES database. We included essential covariates in our adjusted analyses to ensure a comprehensive understanding of the relationships under scrutiny. To further validate our findings, we calculated the E value for sensitivity analyses (see online supplemental table 4), taking into account the data set’s weighting structure. Potential confounding factors related to exposure were also considered (see online supplemental figure 1). However, this study also has several limitations. The cross-sectional design prevents the establishment of causal relationships. There may be potential unaccounted or unobserved confounding variables, such as medical conditions, dietary habits, occupational status, timing of sample collection and usage of medication or substances. Additionally, the Solid-Phase Enzymatic Immunodot assay used primarily yields qualitative data indicating the presence or absence of HSV-1 and HSV-2 antibodies, which restricted our ability to adjust for antibody titre levels when significant associations were observed in adjusted models. A significant limitation of our study is the unknown timing of HSV infection, whether congenital or acquired later in life. The differentiation is critical as congenital HSV infections can lead to systemic effects and potentially more severe outcomes, including HI, compared with infections acquired postnatally. This limitation restricts our ability to fully understand the pathophysiological impacts of HSV on auditory functions and suggests a crucial area for future research, where detailed timelines of viral infection could elucidate the relationship between the timing of HSV infection and HI risk. Another limitation lies in the exclusive assessment of IgG for HSV in this study. Future research should explore primary infection, latency and reactivation scenarios to better understand the relationship between hearing and various stages of infection. For the HSV test, an ‘Indeterminate’ outcome was interpreted as a negative result, which could potentially lead to an underestimation of the true prevalence. Finally, the available data for both audiograms and HSV tests were limited to individuals aged 20–49, thereby constraining the scope for a comprehensive analysis encompassing the entire adult population.
In conclusion, our study presents evidence of an association between HSV-1 infection or coinfections of HSV-1 and HSV-2 and higher prevalence rates of hearing impairment compared with those not infected by these viruses. Notably, this association appears particularly pronounced among younger individuals and those with a lower BMI. Further research is warranted to elucidate the causal impact of HSV on auditory function, understand the underlying mechanisms and design targeted interventions.
supplementary material
Acknowledgements
We acknowledged the staff of the National Center for Health Statistics at the CDC who designed, collected and managed the NHANES data and made the data sets of NHANES available on their website for the public.
Footnotes
Funding: This work was supported by grants from the Hubei Provincial Key Research and Development Program (2022BCA006), the Wuhan Knowledge Innovation Project (2022022101015011), the National Natural Science Foundation of China (81500794) and the China Postdoctoral Science Foundation (2017M613326). There are no conflicts of interest, financial or otherwise.
Prepublication history and additional supplemental material for this paper are available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2023-083017).
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient consent for publication: Consent obtained directly from patient(s).
Ethics approval: This study involves human participants. The NCHS Research Ethics Review Board (ERB) provided protocol approval numbers for the respective survey years, including the specific protocol Number: Protocol #2011-17. Additional information about the NHANES database can be accessed at https://www.cdc.gov/nchs/nhanes/irba98.htm. All participants in the study gave their informed written consent. Given that this study involves the use of publicly available, anonymised NHANES data, it is exempt from further ethical review by the Ethics Committee of Tongji Hospital. Participants gave informed consent to participate in the study before taking part.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Contributor Information
Yingqiang Li, Email: 3282268192@qq.com.
Bo Su, Email: 17771386959@163.com.
Xiaodi Wang, Email: 416721502@qq.com.
Hanqi Chu, Email: qi7chu@163.com.
Dan Bing, Email: didibing1981@aliyun.com.
Data availability statement
No data are available.
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