U.S. Population Data on Hearing Loss,Trouble Hearing,and Hearing-Device Use in Adults: National Health and Nutrition Examination Survey,2011–12,2015–16,and 2017–20

The NHANES Dataset

The NHANES 2011–12, 2015–16, and 2017–20 surveys were conducted by the National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention to monitor the health and nutritional status of the civilian, non-institutionalized US population. Sex and race/ethnicity were self-reported using federal guidelines in existence at that time. Because the surveys enquired about the respondent's sex, either male or female, rather than gender, this variable is referred to here as the participant's self-reported sex. The surveys used a complex, multistage, stratified, cluster design with oversampling of targeted subgroups to produce nationally representative estimates. The specific groups oversampled varied across surveys; full details are provided by NHANES (https://wwwn.cdc.gov/nchs/nhanes/analyticguidelines.aspx#sample-design).

NHANES 2011–12, 2015–16, and 2017–20 included 5,560, 5,719, and 9,232 from each survey, respectively, who were 20 years of age or older. Of these adults, 8,795 had complete audiograms. For those ≥ 20 years old, the 2017–20 cycle included audiograms only for those 70–80 + years of age. Those with age designated as 80 + years in NHANES 2017–20 were nominally assigned an age of 80 by NCHS to protect the participant's identity. The NCHS noted that the mean age for that group in the 2017–20 survey was 85 years. The sex, age, and race/ethnicity of the 8,795 adults with complete audiograms are provided in Table 1.

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Table 1.

Demographic Breakdown (Sex, Race/Ethnicity, Age Decade) of the 8,795 Adults from NHANES 2011–12, 2015–16, and 2017–20 Included in the Analyses of Hearing Thresholds.

	Age Decade (yr)	Mexican American	Other Hispanic	Non-Hispanic White	Non-Hispanic Black	Non-Hispanic Asian	Other	Total
Males	20–29	123	81	254	197	145	38	838
	30–39	132	88	283	149	113	35	800
	40–49	84	75	243	162	109	27	700
	50–59	96	76	237	183	104	30	726
	60–69	111	105	202	220	60	14	712
	70–79	21	22	183	76	25	19	346
	80+	6	5	122	22	7	8	170
	Total	573	452	1524	1009	563	171	4292
Females	20–29	119	86	254	203	117	35	814
	30–39	121	80	263	162	117	30	773
	40–49	130	80	247	224	109	25	815
	50–59	106	112	253	222	94	14	801
	60–69	113	136	216	195	74	16	750
	70–79	23	37	175	70	37	8	350
	80+	8	3	149	30	7	3	200
	Total	620	534	1557	1106	555	131	4503

Audiometry

Audiometric testing was conducted in sound booths (model Delta 142; Acoustic Systems, Austin, TX) in the mobile examination centers (MECs), which were transported to each survey location. Ambient noise met the standards for maximum permissible ambient noise levels for ears-covered testing from 500–8000 Hz (ANSI 3.1, 1999). During testing, background noise was monitored continuously. For NHANES 2011–12 and 2015–16, hearing threshold levels (HTLs) were obtained using Interacoustics (Middlefart, Denmark) AD226 audiometers calibrated to ANSI S3.6 (1996) specifications. For the 2017–20 examination, an Audiometric Research Tool (ART) system was used which comprised National Instruments hardware and custom ART software to form a comprehensive and customizable audiometer. For tympanometry, in 2011–12, the micro audiometrics earscan (Murphy, NC) acoustic impedance tympanometer (Murphy, NC) whereas in 2015–16 and 2017–20 the Interacoustics Titan (Middelfart, Denmark) was used. All results were obtained using a 226-Hz probe frequency.

HTLs were obtained using a pulsed-tone stimulus and a standard clinical modified method of limits procedure for each ear at 500, 1000, 2000, 3000, 4000, 6000 and 8000 Hz. The first test ear varied across participants. HTLs were usually obtained using supra-aural TDH-49P headphones (Telephonics, Farmingdale, NY) but insert earphones (EARtone 3A; Etymotic Research, Elk Grove Village, IL) were used when participants had collapsing ear canals (0.6% of males and 0.4% of females). Noise was not used to mask the non-test ear. However, when marked interaural asymmetry was found (≥ 25 dB at 500 and 1000 Hz or ≥ 40 dB at the other frequencies), the poorer ear was re-tested with insert earphones which have greater interaural attenuation than the headphones.

The surveys were approved by the National Center for Health Statistics Institutional Review Board, and all participants provided written consent. The audiometry examination was conducted by trained NHANES health technicians and included otoscopy, tympanometry, and air-conduction pure-tone audiometry. The entire NHANES protocols, including the survey instruments and data-coding procedures, and the complete dataset are publicly available online at https://www.cdc.gov/nchs/nhanes.

For the small number of individuals for whom there was evidence of a collapsed canal with headphones or a concern about cross-over detection of the pure-tone signal in the better ear when presented to the worse ear without masking, the HTLs obtained with insert earphones were available. Less than 0.6% of adults with complete audiograms had collapsed canals that required use of insert earphones. The number of thresholds re-tested with insert earphones due to cross-hearing concerns varied with frequency but never involved more than 1% of the HTLs for a given ear and frequency. When HTLs measured with insert earphones were available, these values were used.

Although the 8,795 adults in the dataset had complete audiograms, in some cases the HTLs could not be established because they were beyond the limits of the audiometer. These were coded in the NHANES datasets with values of “666.” Overall, this occurred less than 0.5% of the time across ears and frequencies except for the HTLs at higher frequencies (≥ 3000 Hz) for the oldest age groups, 60–69, 70–79, and 80 + years. Specifically, the population-weighted prevalence of “666” values among the 80 + age group were 2.5, 3.5, 8.1, and 26.4% at 3000, 4000, 6000, and 8000 Hz, respectively, for the left ear and 2.2, 3.2, 6.6, and 27.8%, respectively, for the right ear. For the 70–79-year-olds, “666” values were entered for the left ear for 1.6, 3.4, and 11.1% of the cases for 4000, 6000, and 8000 Hz, respectively, whereas these rates were 0.9, 3.3, and 10.1% of the cases, respectively, for the right ear. For the 60–69-year age group, the prevalence of “666” values exceeded 1% only at 6000 (1.3%) and 8000 Hz (1.2%) for the right ear and at 8000 Hz (1.3%) for the left ear. Also, it was generally the case that, for a given age group, males had greater occurrences of “666” entries than females. To maximize use of the available data, all “666” entries were recoded with values of 126 dB HL, a value just exceeding the maximum audiometer output of 120 dB HL across frequency and datasets.

Interview Questions and Examination Data

The interview question used to define the presence of hearing trouble was the following (AUQ054): “Which statement best describes your hearing (without a hearing aid or other listening device)? Would you say that your hearing is excellent, good, that you have a little trouble, moderate trouble, a lot of trouble, or are deaf?” The responses to this question have been analyzed in several prior studies of various NHANES datasets with responses of “excellent” or “good” considered as reflective of no trouble hearing and all other responses, from “a little trouble” through “deaf” considered as reflective of varying degrees of hearing trouble (e.g., Choi et al., 2016; Goman et al., 2020; Kamil et al., 2015). This same question and dichotomization of responses was also employed in several other surveys outside of the NHANES (e.g., Caban et al., 2005; Dillard et al., 2022; Marrone et al., 2019; McKee et al., 2018; Zelaya et al., 2015). This same criterion was employed in the present analyses and is justified additionally below.

Other hearing-related interview questions examined here concerned the frequency of difficulty following conversation in noise (AUQ 100/101) and how frequently hearing caused frustration when talking (AUQ110). Each of these questions included responses of always, usually, at least half the time, seldom, and never. In addition, device-related questions included queries about whether the respondent ever used hearing aids or cochlear implants (AUQ146/148), with the 2017–20 survey adding personal sound amplifiers to the question (AUQ630). These were Yes/No questions with follow-up questions as to which type of device had been used. Very few indicated use of cochlear implants or personal sound amplifiers in response to these questions. As a result, only responses about hearing aid use are presented here. In the 2011–12 and 2015–16 NHANES surveys, those who responded affirmatively about hearing aid use were asked about the frequency of hearing aid use over the past year (AUQ152). Those answering always to seldom were considered current hearing aids users and those who replied never were added to those who ever used hearing aids rather than treated as current hearing aid users. For the 2017–20 NHANES survey, AUQ153 had a similar follow-up question for frequency of hearing-aid use, but only over the preceding two weeks and responses were in terms of hours per day (< 1 to ≥ 8 h per day) with never being the last response alternative. Those answering never were handled as in the other two surveys. Finally, respondents were asked (AUQ154/156) whether they ever used assistive listening devices (Yes/No response) with these devices defined as “…FM systems, closed-captioned television, amplified telephone, relay services, or a sign-language interpreter” with “instant or text message” and “live video streaming” added, along with the qualification “because of hearing loss” in NHANES 2017–20.

In addition to including demographic variables of sex, age, and race/ethnicity in the fully adjusted logistic-regression analyses, measures of education level, diabetes, hypertension, smoking, noise exposure, cerumen impaction, and tympanogram abnormalities were included, with several of these additional hearing-loss risk factors defined as in Hoffman et al. (2017) for the analyses of the NHANES 2011–12 data. Specifically, participants were classified positive for diabetes and assigned a value of 1 (0 if negative) if they answered “yes” to “ever been told by a doctor or other health professional that you have diabetes” or “now taking diabetic pills to lower blood sugar” or had a 2-h fasting glucose readings ≥ 200 mg/dl at the time of the NHANES exam. Participants were classified positive for hypertension and assigned a value of 1 (0 if negative) if they answered “yes” to “Have you ever been told you have high blood pressure?” or “Are you taking a prescription for hypertension?” or, if during the MEC exam, the average of four blood pressure measurements was > 140 mmHg (systolic) or > 90 mmHg (diastolic). Smoking history was defined as “nonsmoker” (assigned 0) if the respondent answered “no” to “Have you smoked at least 100 cigarettes in your life?” Current and former smokers were divided into two groups,  < 20 pack-years (assigned 1) and ≥20 pack-years (assigned 2). Although Hoffman et al. (2017) included education level as a covariate, the NHANES 2017–20 dataset coded the education level for adults differently from prior cycles. The education levels for the two earlier datasets were recoded to match those for 2017–20. Specifically, education levels were: (1) less than 9^th grade; (2) 9^th to 11^th grade; (3) high-school graduate (including General Education Diploma, GED); (4) some college, including associates degree; and (5) college graduate.

In addition to those measures included in Hoffman et al. (2017), two other measures were generated. One was based on the presence of impacted cerumen, defined as no portion of the eardrum being visible upon otoscopic examination by the technician. An additional measure was included to quantify the status of the middle ear. Tympanograms were designated as abnormal if the tympanogram width exceeded 150 daPa, middle-ear pressure was ≤ −200 daPa, or static compliance was less than 0.2 ml (Shanks & Shohet, 2009; Wiley et al., 1996). Only those tympanograms judged subsequently by an audiologist to be of good or adequate quality were included. Because the otoscopic and tympanogram measures were ear-specific, the logistic-regression analyses for PTA4 were also ear-specific. That is, the logistic-regression analyses evaluated the effects of various variables on the better-ear PTA4 using otoscopy and tympanograms for the better ear.

Given the possible effect of income on the use of hearing aids and ALDs, a measure of annual family income was included. NHANES 2017–20 only included income information as an income-to-poverty ratio, information that is also included in the other two NHANES surveys. As a result, this was the income measure applied across all three NHANES surveys. NHANES used poverty guidelines, which vary by family size and geographic location, published annually by the U.S. Department of Health and Human Services. Population quintiles were generated to establish the following five levels of income based on the family income to poverty ratio: (1) ratio < 1.0; (2) 1 ≤ ratio < 2; (3) 2 ≤ ratio < 3.5; (4) 3.5 ≤ ratio <5; (5) ratio = 5.

Data Analysis

All prevalence estimates and statistical analyses presented here were performed in accordance with the National Health and Nutrition Examination Survey: Analytic Guidelines, 2011–2014 and 2015–2016 published online on December 14, 2018, by the NCHS and National Health and Nutrition Examination Survey, 2017-March 2020 Prepandemic File: Sample Design, Estimation, and Analytic Guidelines (Akinbami et al., 2022). Statistical analyses were performed using SAS version 9.4 (SAS Institute, Inc., Cary, NC). This included the use of masked strata and cluster variables for the design and the use of the adjusted sample weights provided for each participant by the NCHS. Sample weights for the 2011–12 and 2015–16 datasets were adjusted as recommended when combined (each cycle's 2-year weights divided by 2) whereas the sample weights for the 2017–2020 dataset were unaltered. This treatment of sample weights arises from the focus on HTLs which were obtained from adults with non-overlapping age ranges across the NHANES datasets: adults 20 to 69 years of age in the two earlier NHANES datasets versus adults 70 to 80 + years in the most recent dataset. In addition, as recommended by the NCHS, the lowest common denominator guided the choice of which set of sample weights to use and, given the focus on audiometric data attained in the MEC, the MEC sample weights were used here.

The full set of data from 35,287 adults was included in the dataset to be analyzed with restriction to those at least 20 years of age and with completed audiograms designated via domain specifications in the SAS analyses. Variance estimation was accomplished using the recommended Taylor-series linearization method. The 95% confidence intervals were those generated by SAS 9.4 based on standard errors estimated by linear interpolation of a normal distribution [i.e., standard error = ((p*q)/N)^1/2, where p is the proportion of interest, 0.5 for the median, and q = 1−p, also 0.5 for the case of the median, and N is the number of cases]. Hoffman et al. (2010) noted that the standard error and resulting confidence intervals derived from such standard errors provided appropriate estimates of the confidence intervals.

Several binary logistic-regression analyses were performed to identify factors affecting the presence of hearing loss, either as defined audiometrically or for by self-report, and the self-reported use of hearing aids or ALDs. The “better-ear PTA4” was established by computing the PTA4 for each ear and then selecting the minimum of the two values as the “better ear” value (Stevens et al., 2013; WHO, 1991, 2021).

It is challenging to identify a goodness-of-fit metric for logistic-regression models applied to complex survey data like NHANES. SAS Version 9.4 (SAS Institute, Inc., Cary, NC) was used here. The SAS output provides a test of the global null hypothesis (Beta = 0) and this test was significant for all of the logistic-regression models provided here [minimum F (14.6, 832.4) = 19.6, p < .0001; second-order Rao-Scott design correction applied]. The “max-rescaled R²” statistic, a pseudo-R² value, ranged from 0.20 to 0.53 indicating reasonable fits. Finally, the concordance between predicted and observed probabilities for the logistic-regression models ranged from 75.1 to 95.1%, further supporting good fits for all models.

A minimum events-per-variable ratio of 10 is frequently recommended for logistic-regression analyses to ensure stability of the solution (Harrell et al., 1984, 1996; Peduzzi et al., 1996), although this guideline was not developed from consideration of complex survey designs such as that employed by NHANES. All events-per-variable ratios exceeded 20.

Self-Reported Hearing Trouble

Figure 1 provides the prevalence of each response for item AUQ054, General Condition of Hearing. In Figure 1 and elsewhere, blue vertical bars present data for males and pink vertical bars present data for females. Also, unless noted otherwise, error bars in Figure 1 and elsewhere represent 95% confidence intervals. In Figure 1, and other figures with prevalence estimates, percentages and confidence intervals are provided in tabular form in the supplementary materials.

The aggregate data from all 8,793 adults with responses to this item in the surveys appear in the bottom right panel whereas the other panels show the results segregated by age decade. From age 20 to 59 years (left panels), the predominant responses were either “excellent” or “good” with the response distributions gradually shifting to greater degrees of hearing difficulty with increase in age decade. About 75–80% of U.S. adults reported their hearing to be either “excellent” or “good,” the remainder indicating some amount of trouble hearing, from “a little” to “deaf.”

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Figure 1.

Prevalence of self-reported hearing trouble for males and females for each age decade and for all males and females (“Total”). In all figures, error bars = 95% confidence intervals.

Although a cut-off point of at least “a little trouble” has been applied consistently in many prior studies of other NHANES datasets, the cut-off point was further evaluated here before proceeding. To do this, responses to separate questions about the frequency of hearing difficulty for conversations in noise and the frequency of frustration with hearing while talking were examined. The response choices ranged from always (1) to never (5) for both questions, such that higher scores were associated with less frequent problems. For the question about difficulty for conversations in noise, median responses (95% confidence intervals in parentheses) using these ordinal scales were 3.84 (3.75, 3.93) and 2.47 (2.35, 2.61) for the no-trouble-hearing and trouble-hearing subgroups, respectively. For the question about frustration with hearing while talking, median responses were 4.35 (4.29, 4.41) and 3.30 (3.17, 3.43) for the no-trouble-hearing and trouble-hearing subgroups, respectively. The medians were nearly identical for males and females. For both questions and both males and females, the medians of the trouble-hearing subgroup were significantly lower than those for the no-trouble-hearing subgroup indicating that problems were significantly more frequent for those who had reported trouble hearing. The difference between subgroup medians was at least one point on each 5-point scale. For both the males and females and both questions, the subgroup with no reported trouble hearing exhibited median scores approximating “seldom” (4.0), whereas the subgroup reporting trouble hearing gave median responses approximating “about half the time” (3.0) or “usually” (2.0). These data from responses to questions pertaining to hearing, but independent of the question about overall trouble hearing, support the criterion used to form the no-trouble-hearing and trouble-hearing subgroups.

Figure 2 shows the percentage of males and females in each age decade, as well as across all ages (“ALL”), with self-reported trouble hearing. For both males (blue) and females (pink) the prevalence of trouble hearing increased steadily across age groups. Overall, about 26% of males and a little over 20% of females, aged 20 to 80 + years, had self-reported trouble hearing.

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Figure 2.

Prevalence of self-reported trouble hearing among U.S. adults 20 to 80 + years of age.

Audiometric Hearing Loss

Figure 3 shows the prevalence of each WHO-HI grade for males and females for each age decade and overall (“Total”) for the 8,795 adults with complete audiograms. As was observed for self-reported trouble hearing, the distributions are concentrated at “normal” over the range 20–59 years of age (left panels) and then begin to spread across grades between 60 and 80 + years of age. Very few males or females 80 + years of age had normal hearing as defined audiometrically. The aggregate data in the lower right panel indicate that about 80% of males and 85% of females had normal hearing based on the WHO-HI grade system. The balance mostly fell in the “mild” or “moderate” WHO-HI grades.

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Figure 3.

Prevalence of each WHO-HI grade among U.S. males and females for each age decade and overall (“Total”).

Figure 4 shows the prevalence of impaired hearing, defined as better-ear PTA4 ≥ 20 dB HL, for U.S. males and females for each age decade and in aggregate (“ALL”). As expected, the prevalence of impaired hearing increased with age decade for both males and females. Females consistently had a lower prevalence of impaired hearing for each age decade and in aggregate. Overall, about 23% of adult males and 17% of adult females between the ages of 20 and 80 + years had impaired hearing.

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Figure 4.

Prevalence of impaired hearing based on WHO-HI criteria for U.S. males and females.

There are many similarities in the prevalence patterns for males and females, across age decades, and in aggregate, for self-reported trouble hearing (Figures 1 and 2) and WHO-HI-defined impaired hearing (Figures 3 and 4). To compare these two classification systems, each of the 6-point classification scales was converted to a 5-point scale. For self-reported trouble hearing, the “excellent” and “good” responses were combined, as collectively they correspond to the single WHO-HI grade of “normal”. For the WHO-HI grade system, very small percentages were found for the two most severe impairments, “severe” and “profound” (Figure 3) and these two were combined. Overall, the population-weighted correlation between the two classification scales was r = 0.61, indicating about 37% shared variance between self-reported and audiometrically quantified hearing ability.

The variables that affected the odds of having self-reported trouble hearing or audiometrically defined impaired hearing were examined using binomial logistic regression. Several demographic, health, and noise-exposure variables were found to be significant. Figure 5 shows the odds ratios (ORs) for self-reported trouble hearing and better-ear PTA4 ≥ 20 dB HL. For these logistic-regression analyses and others presented below, tables of type-3 main effects and ORs are given in the Appendix.

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Figure 5.

Fully adjusted odds ratios (ORs) for the effect of several variables on the presence of trouble hearing (unfilled circles) and audiometric hearing loss (filled circles). Those ORs for which the 95% CIs do not cross the vertical dashed line at OR = 1.0 are significant at p < .05. Note. Additional information is provided in Tables A1 and A2.

The two most obvious effects on the odds of having trouble hearing are seen for age and race/ethnicity. The odds of having trouble hearing steadily and significantly increased for each age decade relative to the youngest decade. For race/ethnicity, four of the five ORs showed significant decreases in the odds of having trouble hearing relative to Non-Hispanic Whites (NHW). Only the OR for the Other-Non-Hispanic race/ethnicity (Oth) failed to differ from NHW. The smallest ORs were observed for Non-Hispanic Blacks and Asians (NHB, NHA). The next largest ORs in Figure 5 for trouble hearing were for positive histories of exposure to loud noise, both at work and off-work. Positive histories of noise exposure increased the odds of having trouble hearing by 50–75%. In addition, a positive history of hypertension, a positive history of diabetes, and lower education level all increased the odds of having self-reported hearing trouble by about 20–40%.

There are large increases in the odds of PTA4 ≥ 20 dB HL with increasing age decade. Whereas those aged 70 to over 80 years had about 10 times higher odds of having self-reported trouble hearing relative to 20- to 29-year-olds, the odds of audiometric hearing loss in these oldest age decades were at least 100 times higher than for the youngest age decade. For race/ethnicity, the OR for PTA4 ≥ 20 dB HL was only significantly lower for Non-Hispanic Blacks relative to Non-Hispanic Whites, the odds being about 50% lower. Level of education was the variable with the next largest effect on the odds for PTA4 ≥ 20 dB HL. Those with less than a college degree had significantly higher odds for PTA4 ≥ 20 dB HL than those with a college degree. A positive history of diabetes, work and off-work exposure to loud noise, better-ear cerumen impaction, and abnormal tympanograms in the better ear also significantly increased the odds for PTA4 ≥ 20 dB HL.

Use of Hearing Aids and ALDs

 Prevalence estimates for various definitions of device usage are shown in Figure 6. Although not shown in Figure 6, the prevalence of current hearing-aid use was about 80–85% lower than the estimates shown for ever-using hearing aids. The two left panels depict the prevalence of ever using hearing aids (top) or ALDs (bottom) for each sex and age decade with aggregate values shown at the far right in each panel (ALL). The top-right panel shows the prevalence for ever having used both hearing aids and ALDs whereas the bottom right panel shows the prevalence for ever having used either of these devices. The prevalence estimates for using both devices in the top-right panel were only valid for the oldest age group and the aggregate data as the relative standard error exceeded 30% for the other age decades, due to small number of individuals who reported using both devices.

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Figure 6.

Prevalence of hearing-aid and ALD use for those who reported only use of hearing aids (top left), only ALDs (bottom left), both (top right), or either (bottom right). Missing prevalence estimates in each panel are all those for which the relative standard error exceeded 30%. HA = hearing aid.

The prevalence of device use increased steadily with age decade whether for hearing aids (top left) or ALDs (bottom left). The prevalence of ALD use was higher than that of hearing-aid use for those 59 years of age and younger, but this trend reversed among those in their 70 s and 80 s. Overall, the prevalence of device use was generally less than about 6%.

Binary logistic-regression analyses were performed for current hearing aid use, ever using hearing aids, and ever using ALDs. Given the moderate correlation between trouble hearing and PTA4 noted previously, collinearity concerns precluded the use of both these measures in multi-variable logistic-regression analyses. Unadjusted ORs were determined for trouble hearing and PTA4 alone and in combination for current hearing-aid use and ever using hearing aids or ALDs. In all the logistic-regression models for device use, the ORs for trouble hearing were five to twenty times larger than those for PTA4. This was also true when PTA4 replaced trouble hearing as the sole measure of impaired hearing in the multi-variable logistic-regression analyses. The ORs for PTA4 were significant, but considerably smaller than those for trouble hearing, while the ORs for the other variables in the model were largely unchanged when PTA4 replaced trouble hearing. As a result, only the models that used trouble hearing as a covariate are shown in all subsequent multi-variable logistic-regression analyses of device use.

Figure 7 shows the ORs for each of the three fully adjusted logistic-regression analyses of variables affecting device use. Generally, the pattern of ORs in Figure 7 was very similar whether current hearing-aid use (grey circles) or ever using hearing aids (black circles) was the dependent variable. Trouble hearing had the largest ORs for hearing-aid use, followed by age. For age, those 60 years of age and older had about 5–30 times greater odds of using hearing aids than those in their 20 s. Much smaller but significant ORs emerged for sex, males having greater odds for using hearing aids than females, race/ethnicity, both Mexican Americans and Non-Hispanic Black having lower odds for current hearing-aid use than Non-Hispanic Whites, and diabetes increasing the odds for hearing-aid use. A positive history of smoking for at least 20 pack-years significantly decreased the odds of hearing-aid use. This most likely reflects an underlying attitude toward one's own health rather than smoking per se decreasing the odds of hearing-aid use by reducing the need for hearing assistance.

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Figure 7.

Fully adjusted ORs for the effect of several variables on the current use of hearing aids (HA; grey circles), ever using HA (black circles), and ever using ALDs (white circles). Note. Additional information is provided in Tables A3 and A4.

For ever-using ALDs (unfilled circles), the ORs in Figure 7 follow a pattern that differs considerably from those found for the use of hearing aids. For example, although the ORs for trouble hearing and age were again the largest, the sizes of the ORs for ALD use were considerably smaller than for hearing-aid use. In addition, the OR for sex was not significant, whereas the ORs for education level were significant for ALD use. Those with less than some college education had significantly lower odds of using ALDs than college graduates. Race/ethnicity was also significant, Non-Hispanics of Other races having greater odds of using ALDs than Non-Hispanic Whites.

Unmet HHC Needs

 This section presents estimates of the percentage of those with hearing needs who are not currently using hearing aids or have never used hearing devices. Such individuals are considered here to have unmet HHC needs. Because not all those who have ever used either device will still be using devices and because not all will have obtained sufficient benefit to eliminate their HHC needs, the estimates of “unmet HHC needs” described here are likely to be conservative.

Figure 8 shows the prevalence of unmet HHC needs for males (blue, top) and females (pink, bottom) when those needs were defined based on either self-reported trouble hearing (right panels) or better-ear PTA4 ≥ 20 dB HL (left panels). Results are shown for meeting those HHC needs through current hearing aid use, by ever using hearing aids, or by ever using ALDs. Although there are some differences between males and females and between device types, the overall pattern of results in all four panels is very similar. Unmet HHC needs were greatest below 70 years of age and the prevalence did not vary greatly for adults in the age range 20–69 years. Unmet HHC needs decreased considerably for the oldest two age decades due primarily to the greater uptake of devices by these two age groups (Figure 6). Overall, across all U.S. adults 20 to 80 + years of age with hearing difficulties, measured either audiometrically or by self-report, about 80–85% have unmet HHC needs.

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Figure 8.

Prevalence of unmet HHC needs based on either self-reported hearing trouble (right panels) or audiometrically measured hearing impairment (left panels). Data are shown separately for males (top panels) and females (bottom panels) and for current hearing aid use, ever using hearing aids, or ever using ALDs. HA = hearing aid.

Figure 9 shows the prevalence of unmet HHC needs for varying degrees of audiometric hearing impairment (left panels) and different definitions of trouble hearing (right panels). Insufficient data were available for those with greater severities of hearing loss or hearing trouble. Unmet HHC needs are greatest among those with mild hearing loss and those reporting a little trouble hearing and unmet needs decrease as severity of hearing loss and hearing trouble increase. Even for moderate levels of impairment or trouble, 60–80% have HHC needs unmet by hearing-aid use. Regardless of hearing loss severity or amount of trouble hearing, ALDs are used much less frequently than hearing aids to meet those HHC needs.

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Figure 9.

As Figure 8, but with prevalence of unmet HHC needs as a function of severity of hearing loss (left) or trouble hearing (right).

With a focus on variables that might affect unmet HHC needs based on hearing-aid use, two additional logistic-regression analyses were performed. In both cases, need for help was defined audiometrically as better-ear PTA4 ≥ 20 dB HL. Of the 8,795 adults with complete audiograms, 1,768 had better-ear PTA4 ≥ 20 dB HL and 1,601 with complete data were included in the logistic-regression analyses of unmet HHC needs. Of the 1,601 adults with PTA4 ≥ 20 dB HL, those who met those HHC needs included 234 who had ever used hearing aids and 192 who were currently using hearing aids. The focus of these analyses was on the relatively smaller group, those with met HHC needs. What variables affected the odds for meeting HHC needs?

Figure 10 shows the results of the logistic-regression analyses of met HHC needs. For these analyses, variables affecting the odds for meeting HHC needs were identified among the 1,601 adults with hearing loss. Generally, the solutions for both current-use of ever-used hearing aids were very similar. Trouble hearing had the highest OR, those having perceived hearing trouble being 50–70 times more likely to currently be using or ever-used hearing aids than those without perceived trouble hearing. Age was the next strongest factor that emerged from these analyses, those 30 to 69 years of age having significantly lower odds for hearing-aid use than those 80 years of age and older. Neither the 20–29-year-olds nor the 70–79-year-olds had ORs that differed significantly from those 80 years of age and older. For the younger group, few had HHC needs based on PTA4 (Figure 4) and for the older group many met those needs with hearing aids (Figure 6). Race/ethnicity had some significant effects, reducing the odds for hearing-aid use for some groups relative to Non-Hispanic Whites (NHW), especially for current hearing-aid use. The presence of diabetes slightly increased the odds whereas the presence of hypertension slightly decreased the odds for hearing-aid use. Finally, there were no significant effects of sex, level of education, or family income.

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Figure 10.

Fully adjusted odds ratios ORs for the effect of several variables on met HHC needs either through current use of hearing aids (HA; grey circles) or ever using HA (black circles). Note. Additional information is provided in Tables A5 and A6.

Figure 11 presents the estimated numbers of adults with unmet HHC needs based on a total population estimate of 234.2 million adults in the U.S. in the age range 20 to 80 + years from 2011 through 2020. Unmet HHC needs were defined based on the audiogram (top panel) or trouble hearing (bottom panel) and never using hearing aids. The lowest number of adults with unmet HHC needs was found for an audiometric definition of need (top panel) with about 21 million males and 17 million females having unmet HHC needs. For unmet HHC needs based on trouble hearing (bottom panel), about 23 million males and 19 million females had unmet HHC needs.

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Figure 11.

Estimated number of adults with unmet HHC needs defined based on audiometric hearing loss (top) or perceived hearing trouble (bottom) and ever using HA as meeting those needs.

Regardless of how unmet HHC needs are defined, millions of U.S. adults with hearing difficulties have unmet HHC needs in the prevailing HHC system. An interesting feature of the data shown in Figure 11 is that the age range with the greatest number of males and females with unmet HHC needs is 50 to 69 years. Although the prevalence estimates of self-reported and audiometrically measured hearing difficulties were both highest among the oldest adults, these same adults took up hearing aids (and ALDs) at the highest rate. The net effect was for the oldest two age decades to have fewer adults with unmet HHC needs compared to those aged 50–69 years. Unmet HHC needs are lowest for those 20–39 years of age largely because their HHC needs are much lower for these younger adults (Figures 2 and 4).