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A relationship between tobacco smoking and hearing loss has been reported; associations with cannabis smoking are unknown. In this cross-sectional population-based study, we examined relationships between hearing loss and smoking (tobacco, cannabis, or co-drug use).We explored the relationship between hearing loss and smoking among 2705 participants [mean age = 39.41 (SE: 0.36) years] in the National Health and Nutrition Examination Survey (2011 to 12; 2015 to 16). Smoking status was obtained via questionnaire; four mutually exclusive groups were defined: nonsmokers, current regular cannabis smokers, current regular tobacco smokers, and co-drug users. Hearing sensitivity (0.5 to 8 kHz) was assessed, and two puretone averages (PTAs) computed: low- (PTA 0.5,1,2 ) and high-frequency (PTA 3,4,6,8 ). We defined hearing loss as threshold15 dB HL. Multivariable logistic regression was used to examine sex-specific associations between smoking and hearing loss in the poorer ear (selected based on PTA 0.5,1,2 ) adjusting for age, sex, race/ethnicity, hypertension, diabetes, education, and noise exposure with sample weights applied.In the age-sex adjusted model, tobacco smokers had increased odds of low- and high-frequency hearing loss compared with non-smokers [odds ratio (OR) = 1.58, 95% confidence ratio (CI): 1.05 to 2.37 and OR = 1.97, 95% CI: 1.58 to 2.45, respectively]. Co-drug users also had greater odds of low- and high-frequency hearing loss [OR = 2.07, 95% CI: 1.10 to 3.91 and OR = 2.24, 95% CI: 1.27 to 3.96, respectively]. In the fully adjusted multivariable model, compared with non-smokers, tobacco smokers had greater odds of high-frequency hearing loss [multivariable adjusted odds ratio = 1.64, 95% CI: 1.28-2.09]. However, in the fully adjusted model, there were no statistically significant relationships between hearing loss (PTA 0.5,1,2 or PTA 3,4,6,8 ) and cannabis smoking or co-drug use.Cannabis smoking without concomitant tobacco consumption is not associated with hearing loss. However, sole use of cannabis was relatively rare and the prevalence of hearing loss in this population was low, limiting generalizability of the results. This study suggests that tobacco smoking may be a risk factor for hearing loss but does not support an association between hearing loss and cannabis smoking. More definitive evidence could be derived using physiological measures of auditory function in smokers and from longitudinal studies.

Background The United States Preventative Service Taskforce recently determined that there was insufficient evidence to recommend hearing screening in adults. Purpose To determine the age to screen adults in the U.S. for hearing loss and identify factors related to increased odds of hearing loss. Research Design Epidemiological Cross-Sectional Study. Study Sample Data from 3,409 individuals aged 20–69 years(y) were analyzed from the 1999–2000 and 2000–2002 cycles of the National Health and Nutrition Examination Survey (NHANES). Data Collection and Analysis Hearing sensitivity from 0.5–8 kHz was assessed and hearing loss was defined as pure tone average 0.5, 1, 2, 4 kHz (PTA4) > 15 dBHL for the worse ear. Thresholds were examined separately for men and women in 2-year intervals. A multivariate ordinal regression model adjusting for age, sex, race/ethnicity, and education was used to examine relationship to determinants. Results Slight (>15 dBHL) hearing loss based on threshold at a single audiometric frequency was first evident in males aged 28–29y. For females, this occurred at age 34–35y. The age at which average PTA4 increased above 15 dBHL (slight hearing loss) was 46–47y for males and 56–57y for females. Multivariate ordinal regression revealed the following “high risk” factors: increased age, male sex, tinnitus, perceived hearing loss, and diabetes. Conclusions For the function of primary prevention, these data suggest screening should initiate at ∼30y for males and 35y for females, the ages when average hearing thresholds at a single frequency can be classified as slight hearing loss. For secondary prevention, the recommended screening ages are higher – 45y for males and 55y for females. Hearing screening is recommended for asymptomatic adults, especially those with high risk factors. Our results also highlight the limitations of PTA4 in identifying early indices of hearing loss.

Background Numerous cardiometabolic factors may underlie risk of hearing loss. Modifiable risk factors such as non-optimal blood pressure (BP) are of interest. Purpose To investigate early auditory evoked potentials (AEPs) in persons with nonoptimal BP. Research Design A cross-sectional nonexperimental study was performed. Study Sample Fifty-two adults (18–55 years) served as subjects. Individuals were classified as having optimal (systolic [S] BP Data Collection and Analysis Behavioral thresholds from 0.25 to 16 kHz were collected. Threshold auditory brain stem responses (ABRs) were recorded using rarefaction clicks (17.7/second) from 80 dB nHL to wave V threshold. Electrocochleograms were obtained with 90 dB nHL 7.1/second alternating clicks and assessed for summating and compound action potentials (APs). Outcomes were compared via independent samples t tests. Linear mixed effects models for behavioral thresholds and ABR wave latencies were constructed to account for potential confounders. Results Wave I and III latencies were comparable between optimal and non-optimal BP groups. Wave I was prolonged in hypertensive versus optimal BP subjects at stimulus level 70 dB nHL (p = 0.016). ABR wave V latencies were prolonged in non-optimal BP at stimulus level 80 dB nHL (p = 0.048) and in HTN at levels of 80, 50, and 30 dB nHL (all p Conclusion Elevated BP and more specifically, HTN was associated with subtle AEP abnormalities. This study provides preliminary evidence that nonoptimal BP, and more specifically HTN, may be related to auditory neural dysfunction; larger confirmatory studies are warranted.

Purpose Cannabis is a widely used drug both medically and recreationally. The aim of this study was to determine if cannabis smoking is associated with changes in auditory function, as measured by behavioral hearing thresholds and/or distortion product otoacoustic emissions (DPOAEs). Method We investigated hearing thresholds and 2f 1 –f 2 DPOAEs in 20 cannabis smokers and 20 nonsmokers between 18 and 28 years old. Behavioral thresholds were obtained from 0.25 to 16 kHz. DPOAEs were measured using discrete tones between f 2 of 0.5 and 19.03 kHz using an f 2 /f 1 ratio of 1.22 and L 1 /L 2 = 65/55 dB SPL. Thresholds and DPOAE amplitudes were compared between groups using linear mixed-effects models with sex and frequency as predictors. Results Behavioral thresholds in smokers did not differ significantly between smokers and nonsmokers (all p s > .05). Although not significant, long-term smokers exhibited poorer thresholds than short-term smokers and nonsmokers. Smokers generally exhibited lower DPOAE amplitudes than nonsmokers, although the differences were not significant. Male smokers had significantly poorer DPOAE amplitudes than male nonsmokers in the low frequencies (f 2 ≤ 2 kHz; p = .0245). Conclusion Results indicate that smoking cannabis may negatively alter the function of outer hair cells in young men. This subtle cochleopathology is evident in the absence of measurable differences in behavioral hearing thresholds between cannabis smokers and nonsmokers.

The association between hearing loss and risk factors for cardiovascular disease, including high blood pressure (BP), has been evaluated in numerous studies. However, data from population- and laboratory-based studies remain inconclusive. Furthermore, most prior work has focused on the effects of BP level on behavioral hearing sensitivity. In this study, we investigated cochlear integrity using distortion product otoacoustic emissions (DPOAEs) in persons with subtle elevation in BP levels (nonoptimal BP) hypothesizing that nonoptimal BP would be associated with poorer cochlear function.Sixty individuals [55% male, mean age = 31.82 (SD = 11.17) years] took part in the study. The authors measured pure-tone audiometric thresholds from 0.25 to 16 kHz and computed four pure-tone averages (PTAs) for the following frequency combinations (in kHz): PTA0.25, 0.5, 0.75, PTA1, 1.5, 2, 3, PTA4, 6, 8, and PTA10, 12.5, 16. DPOAEs at the frequency 2f1-f2 were recorded for L1/L2 = 65/55 dB SPL using an f2/f1 ratio of 1.22. BP was measured, and subjects were categorized as having either optimal BP (systolic/diastolic120 and80 mm Hg) or nonoptimal BP (systolic ≥120 or diastolic ≥80 mm Hg or use of antihypertensives). Between-group differences in behavioral thresholds and DPOAE levels were evaluated using 95% confidence intervals. Pearson product-moment correlations were run to assess the relationships between: (1) thresholds (all four PTAs) and BP level and (2) DPOAE [at low (f2 ≤ 2 kHz), mid (f22 kHz and ≤10 kHz), and high (f210 kHz) frequency bins] and BP level. Linear mixed-effects models were constructed to account for the effects of BP status, stimulus frequency, age and sex on thresholds, and DPOAE amplitudes.Significant positive correlations between diastolic BP and all four PTAs and systolic BP and PTA0.25, 0.5, 0.75 and PTA4, 6, 8 were observed. There was not a significant effect of BP status on hearing thresholds from 0.5 to 16 kHz after adjustment for age, sex, and frequency. Correlations between diastolic and systolic BP and DPOAE levels were statistically significant at the high frequencies and for the relationship between diastolic BP and DPOAE level at the mid frequencies. Averaged across frequency, the nonoptimal BP group had DPOAE levels 1.50 dB lower (poorer) than the optimal BP group and differences were statistically significant (p = 0.03).Initial findings suggest significant correlations between diastolic BP and behavioral thresholds and diastolic BP and mid-frequency DPOAE levels. However, adjusted models indicate other factors are more important drivers of impaired auditory function. Contrary to our hypothesis, we found that subtle BP elevation was not associated with poorer hearing sensitivity or cochlear dysfunction. We consider explanations for the null results. Greater elevation in BP (i.e., hypertension itself) may be associated with more pronounced effects on cochlear function, warranting further investigation. This study suggests that OAEs may be a viable tool to characterize the relationship between cardiometabolic risk factors (and in particular, stage 2 hypertension) and hearing health.

Purpose Cannabis is widely used for medicinal and recreational purposes. Studies have evaluated its health benefits and consequences, although there is limited work on its effects on the auditory system. In this exploratory study, we evaluate the effects of cannabis smoking on early auditory evoked potentials. Method We investigated auditory brainstem response (ABR) and electrocochleography waveforms in 18 cannabis smokers (44% women, 54% men; M age = 23.06 years, range: 21–28 years) and 19 nonsmoker controls (63% women, 37% men; M age = 23.74 years, range: 21–33 years). Threshold ABRs were recorded using rarefaction clicks at a rate of 17.7/s from 80 dB nHL to Wave V threshold. Resulting amplitudes and latencies for Waves I, III, and V were compared via independent-samples t tests. Electrocochleograms obtained with 90 dB nHL (7.1/s) alternating clicks were assessed for summating and compound action potentials, which were compared between groups using independent-samples t tests. Results ABR Wave I amplitudes were significantly lower in smokers ( M = 0.14 μV, SD = 0.11) compared to nonsmokers ( M = 0.21 μV, SD = 0.10, p = .039) at 80 dB nHL. Wave V latencies were significantly delayed in smokers at 80 dB nHL. Wave I and III latencies did not differ significantly between the two groups. Summating potential/compound action potential ratios were significantly elevated in smokers ( M = 0.30, SD = 0.04) versus nonsmokers ( M = 0.21, SD = 0.05, p = .042). Conclusion We identified significant differences in electrophysiological outcomes between cannabis smokers and nonsmokers. Cannabis smoking may have a subtle neurotoxic effect on the auditory system. Larger confirmatory studies are warranted.

Undergraduate research experience has been shown to enhance student learning and improve persistence in science, technology, engineering, and mathematics (STEM). Researchers studying undergraduate ...

Hearing loss is a highly prevalent chronic condition. In addition to age, sex, noise exposure, and genetic predisposition, cardiovascular disease and its antecedents may precipitate hearing loss. Of emerging interest is the connection between diabetes and auditory dysfunction. Cross-sectional studies consistently suggest that prevalence of hearing loss is higher in persons with diabetes compared with those without diabetes, especially among younger persons. Furthermore, longitudinal studies have demonstrated higher incidence of hearing loss in persons with diabetes compared to those without diabetes. These findings seem to hold for both type 1 and type 2 diabetes, although considerably more population-based evidence is available for type 2 diabetes. Data on gestational diabetes and hearing outcomes are limited, as are data relating diabetes to otologic sequelae such as fungal infection. Here, we examine evidence from epidemiologic studies of diabetes and hearing loss and consider clinical and laboratory data where population-based data are lacking.

Undergraduate research experiences may increase persistence in STEM majors. We describe a research program that targets first-year students selected for their curiosity and attitudes towards science. We explain the implementation of the program over 3 years and present evaluation data using a group of matched controls. Participants and controls pursued STEM degrees at equivalent rates, but participants were significantly more involved in research. Initial laboratory interest and mentor pairing may have played a role in this finding. Female participants, particularly those with male laboratory mentors, engaged in more research than men.

Introduction: Over 30 million Americans suffer from hearing loss (HL). Studies suggest that established cardiovascular disease (CVD) risk factors may contribute to the pathophysiology of the inner ear. However, the aggregate effect of CVD risk factors on hearing is not well understood. Hypothesis: We hypothesized that high CVD risk burden is associated with worse hearing. Methods: We assessed younger (ages 18-34) and older (ages 55-64) Hispanic Community Health Study / Study of Latinos participants who underwent audiometry in 2008-11. After excluding those with conductive pathology and asymmetric HL, we randomly chose one ear for analysis. Puretone thresholds were obtained at 0.5-8 kHz; puretone average (PTA) was calculated using thresholds at 0.5, 1, 2, and 4 kHz. Low CVD risk burden was defined as having all of: blood pressure (BP) 160/>100 mmHg (or antihypertensive use); and total cholesterol >240 mg/dL (or statin use). By age group and sex, we estimated hearing thresholds per frequency with linear regression models adjusted for noise exposure. Least squares estimates were calculated using strata-specific means of covariates. Estimates were compared via t-tests. Data were weighted for all analyses and accounted for clustering. Results: Among younger and older individuals in the target population (51.9% female), 28.8% had low and 5.5% had high CVD risk. Younger men with high CVD risk had worse PTA than young men with low risk (7.7 dB HL [7.0-8.4] vs. 10.5 dB HL [8.4-12.5], p =0.02), and had significantly worse thresholds at 1,3,4,6 kHz than those with low risk ( Figure ). There was no difference in PTA or thresholds at any frequency by CVD risk burden in young women, older men, or older women. Conclusions: CVD risk burden is associated with HL among young men, but not young women or older adults. CVD risk burden may be useful for identifying young men at risk for HL.

Today’s science, technology, engineering, and mathematics (STEM) graduate students and postdoctoral fellows are tomorrow’s new faculty members; but these junior academicians often receive limited pedagogical training. We describe four iterations of an entry-level program with a low time commitment, Mentored Discussions of Teaching (MDT). The program is designed to introduce participants to pedagogical issues and literature in STEM disciplines and foster related discussions. It consists of group meetings, classroom observations, and discussions with faculty members. Program components were generally highly rated and valuable, even for those with prior teaching experience. We have found that this program is also an effective way to engage faculty members in the teaching aspects of students’ professional development.

Purpose Distortion product otoacoustic emissions (DPOAEs) are a by-product of active cochlear processes that lead to the compressive nonlinearity of healthy ears. The most commonly studied emission is at the frequency 2f 1 –f 2 , but there has been recent interest in using the quadratic distortion product at the frequency f 2 –f 1 to detect cochleopathies including endolymphatic hydrops. Before the DPOAE at f 2 –f 1 can be applied clinically in any capacity, optimal stimulus parameters for its elicitation must be established. Method We investigated stimulus parameters for the DPOAEs at f 2 –f 1 and 2f 1 –f 2 in 23 adults with normal hearing. Logarithmically swept tones between approximately 0.6 and 20 kHz (L 1 = L 2 = 70 dB SPL) served as the higher frequency stimulus (f 2 ). DPOAEs were measured for 6 f 2 /f 1 ratios: 1.14, 1.18, 1.22, 1.30, 1.32, and 1.36. Results Both DPOAEs were consistently measurable. In line with previous investigations, the highest levels of the DPOAE at 2f 1 –f 2 were generated between f 2 /f 1 ratios of 1.14–1.22, with a peak in the level ratio function at 1.22. In contrast, f 2 –f 1 was less influenced by ratio, although the narrowest ratio (1.14) produced slightly higher levels across frequency. Conclusion The DPOAE at f 2 –f 1 is measurable in individuals with normal hearing up to f 2 of 20 kHz at narrow f 2 /f 1 ratios. Measurements at additional stimulus levels and in subjects with hearing impairment will be needed before clinical implementation.

Hearing thresholds have been shown to exhibit periodic minima and maxima, a pattern known as threshold microstructure. Microstructure has previously been linked to spontaneous otoacoustic emissions (SOAEs) and normal cochlear function. However, SOAEs at high frequencies (>4 kHz) have been associated with hearing loss or cochlear pathology in some reports. Microstructure would not be expected near these high-frequency SOAEs. Psychophysical tuning curves (PTCs), the expression of frequency selectivity, may also be altered by SOAEs. Prior comparisons of tuning between ears with and without SOAEs demonstrated sharper tuning in ears with emissions. Here, threshold microstructure and PTCs were compared at SOAE frequencies ranging between 1.2 and 13.9 kHz using subjects without SOAEs as controls. Results indicate: (1) Threshold microstructure is observable in the vicinity of SOAEs of all frequencies; (2) PTCs are influenced by SOAEs, resulting in shifted tuning curve tips, multiple tips, or inversion. High frequency SOAEs show a greater effect on PTC morphology. The influence of most SOAEs at high frequencies on threshold microstructure and PTCs is consistent with those at lower frequencies, suggesting that high-frequency SOAEs reflect the same cochlear processes that lead to SOAEs at lower frequencies.

Hearing loss is one of the world’s leading chronic health conditions and becomes increasingly prevalent in older adults, exceeding 90% in individuals over 80 years old.1–3 For many, it results in psychosocial consequences including depression and social isolation.4–6 Decreases in health-related quality of life have also been reported,7 and although it is not thought of as a life-threatening health condition, hearing loss causes communication interference that can substantially affect social integration, functional ability, and self-image. Furthermore, it may impede safety by limiting an individual’s ability to hear warning signals and sirens (e.g., in agricultural settings8). Noise-induced hearing loss further poses a significant public health problem, as approximately 10% of U.S. adults (22 million) between 20–69 years old have permanent hearing loss due to exposure to loud noise at work or during leisure activities.9 Research conducted over the last two decades has brought attention to the ototoxic effects of medications and chemicals and their potentially synergistic effects with noise.10–13 In some occupational settings such as refinery, paint industry, aviation industry, military, and fire service, it is common to encounter exposure to both noise and ototoxic chemicals,14 making early detection and intervention critical. Please refer to companion papers exploring noise induced hearing loss by Hong and colleagues as well as ototoxicity by Campo and colleagues. A growing number of factors associated with increased risk of hearing loss in adulthood include: gender,15 genetic susceptibility,16 racial/ethnic groups,17,18 and other diseases such as risk factors associated with cardiovascular disease (e.g., history of hypercholesterolemia, diet, and smoking).19–22 Diabetes (both Types I and II) has been associated with prevalent hearing loss.23,24 Evaluation of hearing loss associated with the combined effects of these risk factors requires tests that can fully evaluate the auditory system, from the cochlea to the higher auditory centers; however, there is no “gold standard” audiological test protocol available for this purpose at this time. The objective of this review is to discuss the tools commonly used in the clinic and present emerging strategies to aid in the early identification of hearing loss in adults. Audiological evaluation of pediatric populations requires a unique set of considerations that are beyond the scope of this paper (for review and pediatric evaluation recommendations, see Harlor et al., 200925). Hearing loss continues to be a chronic disease that significantly impacts quality of life and work productivity, especially for workers who labor in noisy environments.26 The disease also places a significant financial burden on society, as it is estimated the lifetime cost of severe to profound hearing loss exceeds $250,000 per patient in the U.S.27 mostly due to losses in work productivity. Increased awareness and understanding of hearing loss identification and prevention will help mitigate the detrimental consequences of hearing impairment on individuals and society. This paper will provide a basic appreciation of hearing loss assessment needed for this promotion and advancement in hearing health.

Purpose A reduction in hearing sensitivity is often considered to be a normal age-related change. Recent studies have revisited prior ways of thinking about sensory changes over time, uncovering health variables other than age that play a significant role in sensory changes. Method In this cross-sectional study, cardiovascular (CV) health, pure-tone thresholds at 1000 to 4000 Hz, and distortion product otoacoustic emissions (DPOAEs), with and without contralateral noise, were measured in 101 participants age 10–78 years. Results Persons in the “old” age category (49–78 years) had worse pure-tone hearing sensitivity and DPOAEs than persons in the younger age categories ( p < .05), affirming an age effect. Although hearing decline occurred in all persons in all CV fitness categories of every age group, those with low CV fitness in the old age group had significantly worse pure-tone hearing at 2000 and 4000 Hz ( p Conclusions Results of the current study elucidate the potentially positive impact of CV health on hearing sensitivity over time. This finding was particularly robust among older adults.

Age-related hearing loss (ARHL, or presbycusis) results from neural and/or cochlear degeneration. A taxonomy distinguishing presbycusis subtypes according to site of lesion was originally proposed by linking audiometric results to histopathological findings. In most cases, the pathology is complex and audiometry and word recognition scores (WRS) are insufficient to characterize pathologies of the auditory periphery. Several sophisticated tests of auditory function, with some specifically designed to inspect cochlear or neural status (e.g., distortion product otoacoustic emissions [DPOAEs] and auditory brainstem response [ABR]) are available but not in routine use to distinguish between presbycutic subtypes. There are no in vivo methods in place to identify contributing pathologies and their relative dominance in individual instances of presbycusis. However, the promise of upcoming therapies (genetic, pharmaceutical, etc.) cannot be realized without accurate identification of presbycusis subtypes. The goal of the present study was to investigate possible improvements in differential categorization of presbycutic subtypes. We explored a test battery composed of behavioral (audiometry and speech testing) and physiological (ABR, DPOAEs, and electrocochleography) assays in presbycutic ears to ask if improvements beyond the gold standard (behavioral thresholds through 8 kHz and word recognition) are possible. Data from 10 hearing impaired (HI) individuals were compared to those from 21 normal hearing (NH) adults. Exploratory factor and hierarchical cluster analyses (EFA and HCA respectively) were used to evaluate phenotyping strategies. The EFA revealed three factors (highest audible frequency (HAF), pure-tone average (PTA), and 2f 1 -f 2(High) DPOAEs) that accounted for most of the variability in hearing outcomes among the 31 participants. Hierarchical cluster analysis using the gold standard and enhanced multivariate approach revealed: (1) The clinical gold standard distinguished NH and HI participants, but failed to find commonalities among individuals with similar hearing profiles and (2) The enhanced test battery grouped participants with similar profiles, presumably indicating an underlying relationship in pathophysiology. Model data support the feasibility of a finer-grained categorization of presbycusis than is available in current practice, although more data are needed to understand the complexities of phenotyping.