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Journal of Speech, Language, and Hearing Research : JSLHR logoLink to Journal of Speech, Language, and Hearing Research : JSLHR
. 2021 Feb 9;64(2):328–336. doi: 10.1044/2020_JSLHR-20-00068

The Combined Burden of Hearing Loss and Cognitive Impairment in a Group Care Setting for Older Adults

Sara K Mamo a,✉, Kara A Wheeler a
PMCID: PMC8632508  PMID: 33561351

Abstract

Purpose

The purpose of the current study is to better characterize the medical and social health characteristics of older adults in a long-term group care setting and consider the impact of the dual burden of hearing loss and cognitive impairment.

Method

This descriptive analysis of a convenience sample of 160 adults (M age = 74 years, age range: 59.8–99.7) participating in Program for All-inclusive Care for the Elderly programs in Massachusetts and Rhode Island included data from hearing testing, questionnaires, and medical chart review. Using descriptive statistics, groups are compared across a range of demographic and health variables on the categorical bases of hearing loss and cognitive status.

Results

Results suggest that hearing loss and cognitive impairment are highly prevalent among this sample of older adults. Forty-three percent of this sample has at least a mild hearing loss in the better hearing ear in addition to cognitive impairment. Descriptive analyses across demographic and health variables suggest there are few differences between those with and without cognitive impairment when compared within degree of hearing loss categories in this convenience sample. Across all participants, there was a high prevalence of other chronic conditions, most notably diabetes (59%), hypertension (90%), cardiovascular disease (80%), and depression (67%).

Conclusions

In this sample, there were not significant differences on demographic and health variables between the cognitive impairment groups when considered within their degree of hearing loss; however, the prevalence of the dual burden of hearing loss and cognitive impairment in this sample is high. Clinicians serving older adults, especially those accessing group care services, should be cognizant of the high burden of multiple chronic conditions and plan care that can be integrated into a comprehensive approach.

While no one ages in a silo, our research and our medical specialties tend to isolate each factor that contributes to aging and health so precisely that we have very little evidence to guide us in providing whole-person care (Thomas et al., 2018). In the last decade, there has been a flood of epidemiological studies examining the relationship between age-related hearing loss and a multitude of other health conditions, including cognitive decline, dementia, reduced physical function/activity, falls, depression, and loneliness (Chen et al., 2015; Davies et al., 2017; Deal et al., 2017; Fritze et al., 2016; Genther et al., 2013; Golub et al., 2019, 2017; Gurgel et al., 2014; Jiam et al., 2016; Kamil et al., 2016; Lawrence et al., 2019; Lin et al., 2011, 2013; Loughrey et al., 2018; Mick et al., 2014, 2018). The broad range of negative medical, functional, and psychosocial associations with age-related hearing loss has elevated this highly prevalent condition from an individual problem to a public health priority. Although the mechanistic pathways by which age-related hearing loss may contribute to these negative health outcomes remains unclear, the evidence of associations of age-related hearing loss and these conditions is extensive (Lin & Albert, 2014).

Regardless of the nature of the relationship between hearing, cognition, and physical health, many adults with age-related hearing loss have multiple chronic conditions that impact not only their health but also how they access and prioritize their health care. In general, 80% of adults over 65 years old have multiple chronic conditions (Tisminetzky et al., 2017; U.S. Department of Health and Human Services, 2010). A more thorough understanding of the multiple chronic conditions faced by most older adults is a critical step toward advancing intervention research and developing novel service delivery models to support communication for older adults with age-related hearing loss and multiple chronic conditions (Taylor, 2016; Tisminetzky et al., 2017). The current study considers the demographic and health profiles of a convenience sample of older adults with a high prevalence of multiple chronic conditions enrolled in a group care organization.

The Program for All-Inclusive Care for the Elderly (PACE) is a nationwide program that provides centralized, comprehensive health care for older adults. There are 134 programs operating in 31 states serving over 54,000 older adults (NPA, 2020). The PACE program receives monthly Medicare and Medicaid capitation payments for each enrollee. Enrollees can have Medicare, Medicaid, or both (CMS, 2020b). Most enrollees are dually eligible for Medicare/Medicaid services, but if they are not, they pay a monthly premium equal to the capitation payment with no other financial obligations to the program (CMS, 2020a). The eligibility criteria for PACE enrollment states that participants must be 55 years and older and deemed nursing home eligible, but not living in a nursing home, at the time of enrollment. Participants must live within the service area of a given program because providing transportation to the health center (and specialty services) is a key element of PACE. A primary mission of the PACE organization is to allow people to safely age in place by providing all primary health care services, coordinating all referral and specialty services (including transportation), and having a Day Health Center (DHC) that participants access per their care plan for health care, meals, and activity participation (Mui, 2001). In creating a centralized medical home and prescribed network of care, PACE is able to reduce the cost of care and improve health outcomes for a generally unwell population (Wieland et al., 2013).

There are several benefits of working within the PACE organization to investigate opportunities for extending hearing health care access to older adults with complex medical needs. First, the mission of the program operates from a framework of interdisciplinary care. However, as with most group care settings, audiology is not part of the full-time rehabilitation team. Thus, leaving it to the nurses, speech-language pathologists, and occupational therapists to take the lead on recognizing hearing-related communication difficulties and providing personal amplification approaches to persons with untreated hearing loss. The PACE DHC has a diverse and well-trained support staff including care aides, nurses, recreation specialists, and rehabilitation providers, which presents a strong opportunity to provide simple communication solutions to ensure participation for attendees during meals and activities.

Another benefit of working with the PACE program is that it provides access to a community population that tends to be more diverse and composed of a lower socioeconomic sample than most population-based surveys of health. A recent publication based on the Hispanic Community Health Study/Study of Latinos highlights the predominantly White population on which the epidemiological knowledge of age-related hearing loss is based (Golub et al., 2020). For example, two prospective longitudinal studies that have contributed to our knowledge about age-related hearing loss and incident dementia have samples with a racial makeup that is over 90% White (Abell et al., 2018; Lin et al., 2011). While the demographics of each PACE program varies based on the population in the service area, the urban-based sites tend to have a highly prevalent racial/ethnic minority population, which is reflected in the current sample from three PACE organizations in New England.

This article provides a descriptive analysis of a sample of PACE participants in order to shed a unique light on the health and well-being of a diverse group of older adults in a comprehensive care setting with particular focus on their hearing and cognitive status. To better illustrate these characteristics, our research objectives were as follows: (a) provide a descriptive analysis of the PACE samples across three sites and (b) conduct between-group comparisons of those with and without cognitive impairment and hearing loss. We hypothesized that, within a given hearing loss category, the additional impact of cognitive impairment would be observed in poorer medical and social health characteristics for that group.

Method

Setting

Data were collected from February 2019 until February 2020 at the following locations: Mercy LIFE PACE (West Springfield, MA), the PACE Organization of Rhode Island (Providence and Woonsocket, RI), and Upham's Elder Service Plan (UESP/PACE; Boston, MA). The size and attendance of each site varied, but all consisted of one to two large activity/dining halls, a clinic area with private rooms, meeting rooms, and office spaces.

Participants

The demographics of each PACE site generally reflect the population of older adults in their respective communities due to the enrollment requirement of living in the service area of the organization (see Table 1). All PACE participants who attend the DHC were encouraged to partake in hearing tests with the research team. Announcements were made in the mornings at the DHC for a week leading up to the hearing tests, and a sign-up sheet was posted at each PACE site. Recruitment also occurred through word of mouth at the DHC throughout the data collection period. A total of 174 PACE participants volunteered to have a hearing test. On the day of participation, members of the research team reviewed the consent form with the participant and allowed time for questions. After reviewing the consent form with the researcher, all potential participants completed a capacity to consent assessment to ensure they understood the activities to be undertaken and the voluntary nature of their participation. Thirteen participants were deemed ineligible based on their capacity assessments. Individuals who did not have the capacity to consent were excluded from the study but received an audiometric hearing test as part of routine clinical care. One participant was removed from the study after consent because they were unable to complete audiometric testing at any test frequency due to fatigue. At the time of consent, participants were invited to opt-in to participate in baseline questionnaires related to social determinants of health as well as a prospective, longitudinal medical chart review. 1 The full analytic sample is 160 participants who completed the hearing testing, while a subset of 144 participants consented to the longitudinal medical chart review. The institutional review boards of the University of Massachusetts Amherst and Trinity Health of New England approved this study.

Table 1.

Demographic characteristics across the three test sites.

Demographic characteristics Total (N = 160) Mercy LIFE PACE (n = 39) PACE of RI (n = 54) UESP/PACE (Boston)
(n = 67)
M (SD) M (SD) M (SD) M (SD)
Age, years 74.2 (8.6) 75. 2 (9.1) 73.2 (7.2) 74.4 (9.4)
n (%) n (%) n (%) n (%)
Race***
 White 61 (46) 33 (92) 18 (50) 10 (17)
 Black/AA 46 (35) 1 (3) 5 (14) 40 (67)
 Latinx 22 (17) 2 (6) 10 (28) 10 (17)
 Other 3 (2) — 3 (8) —
Education**
 Less than HS 41 (31) 7 (19) 20 (56) 14 (23)
 HS/GED 64 (48) 17 (47) 8 (22) 39 (64)
 More than HS 20 (15) 9 (25) 5 (14) 6 (10)
 Other 8 (6) 3 (8) 3 (8) 2 (3)
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Note. There are missing data for all sites for race and education because these data were only collected if participants opted in to the questionnaires or chart review portions of the study. The percentages reported are based on the number of people for whom race (n = 132) and education (n = 133) data were reported. Not all percentages add to 100% due to rounding. The em dashes indicate that there were no persons in that category. PACE = Program for All-inclusive Care for the Elderly; RI = Rhode Island; UESP = Upham's Elder Service Plan; AA = African American; HS = high school; GED = general educational development.

**

p < .01.

***

p < .001.

Procedure

Hearing Testing

All participants completed air conduction pure-tone testing. The hearing test included otoscopy and general health-related questions regarding the participant's hearing history and hearing aid (HA) use. The testing was performed using SHOEBOX audiometers (SHOEBOX Ltd) with RadioEar DD450 circumaural headphones (RadioEar) and a modified automated protocol that was administered by a research assistant. SHOEBOX continuously monitors the ambient noise during testing and indicates whether noise levels may have caused elevated threshold responses. The SHOEBOX stores the 1/3-octave band noise level present at each test frequency during threshold testing. It also has built-in response algorithms for the automated protocols to detect inconsistent responses. Air conduction thresholds were obtained at octave frequencies from 0.5 to 8 kHz using behavioral responses (i.e., hand raise). A four-frequency pure-tone average (PTA) was calculated using hearing thresholds at 500, 1000, 2000, and 4000 Hz for each participant. The PTA from the better hearing ear was used in analyses, and hearing loss categories were defined as no loss (≤ 25 dB HL), mild loss (26–40 dB HL), or moderate/severe loss (> 40 dB HL).

All English-speaking participants completed the Hearing Handicap Inventory for Elderly–Screening (HHIE-S) as part of the hearing test protocol (Ventry & Weinstein, 1983). The HHIE-S consists of 10 questions and a potential score range from 0 to 40, with higher scores suggesting more handicap; a score between 10 and 24 suggests a mild-to-moderate perceived hearing handicap, and scores of 26 or more suggest significant hearing handicap (Lichtenstein et al., 1988).

Baseline Questionnaires

At Mercy LIFE PACE and PACE RI, participants were given the opportunity to opt-in to an additional study component that included baseline questionnaires related to cognition, loneliness, social determinants of health, and instrumental activities of daily living. A full analysis of that data set will be presented in a future mixed methods report. However, germane to the current article, the scores from the memory screener (n = 62) and demographic information from the social determinants of health questionnaire (n = 72) are included in our analytic data set. The Memory Orientation Screening Test (MOST) is a general screening of cognitive wellness that is administered on an iPad (Clionsky & Clionsky, 2014). The MOST screener has a potential score range from 0 to 29, with higher scores indicative of higher cognitive function, and uses a cutoff score of 18 when screening for dementia (Clionsky & Clionsky, 2010). The MOST is positively correlated with the MMSE and Mini-Cog (Pearson r = .81 and .82, respectively) with a sensitivity of 0.85 and specificity of 0.76 for detection of dementia in a validation sample (Clionsky & Clionsky, 2010). In addition, a Pearson r of .91 (p < .001) was measured for the test–retest reliability of the MOST over a brief interval (Mdn = 48 days) in a sample of 175 patients at a geriatric psychiatry practice (Clionsky & Clionsky, 2010). The Institute of Medicine (IOM) Measures of Social and Behavioral Determinants of Health was the instrument used to assess social determinants of health (Giuse et al., 2017). The IOM Measures of Social and Behavioral Determinants of Health instrument was developed by an IOM Committee as a tool to collect pertinent psychosocial factors related to health in routine visits (Committee on the Recommended Social Behavioral Domains Measures for Electronic Health Records Board on Population Health Public Health Practice, 2015). There are 25 items that cover a range of topics such as demographics, physical and mental health, and health behaviors. In the current article, only race and ethnicity, gender, education, and smoking history data were extracted from this questionnaire.

Medical Chart Review

A cross-sectional chart review (n = 144) extracted relevant demographic and medical history details. Health details included prescribed medications and diagnosed chronic conditions such as diabetes, hypertension, cardiovascular disease, depression, frailty, and cognitive impairment. In addition, the number of falls, dates of emergency department visits, and dates of hospital admissions and discharges were collected from the previous 12 months based on the date of consent.

In order to minimize missing data, some variables were defined by self-report during questionnaires or by medical chart extraction depending on whether the participant had opted in to the questionnaires or the medical chart review or both. The cognitive impairment status was dichotomized as yes/no either based on a diagnosis in the medical chart (e.g., dementia, memory loss, or cognitive impairment/deficit) or based on a failed MOST cognitive screener during the questionnaires. Race/ethnicity data were available from both sources and were combined for analysis into the categories of White, Black/African American, Latinx, and Other. Gender (defined as male, female, or nonconforming) was available through questionnaires or medical chart review. Education history was either self-reported or available in the medical chart demographics; analysis categories were combined as (a) less than high school (HS), (b) HS or equivalent/general educational development, (c) more than HS (including vocational, associates, bachelors, and advanced degrees), and (d) other. HA use was typically discussed during the hearing test case history, but relevant HA history was also extracted during the medical chart review. Finally, smoking status was available via questionnaires or medical chart review and was classified as never, former, or current.

Statistical Analysis

Prevalence of cognitive impairment, degree of hearing loss, and frequency of relevant demographic and medical characteristics were determined using descriptive statistics. As this was a descriptive analysis of a novel sample, multiple pairwise correlations were explored to characterize the sample, for example, PTA and age as well as PTA and HHIE-S. Between-group comparisons were based on the presence or absence of cognitive impairment within each category of hearing loss—none, mild, and moderate/severe. Due to small ns and cells with missing data, the nonparametric Fisher's exact test was used to compare all categorical variables. Analysis of variance was used for group comparisons of continuous variables, and Kruskal–Wallis was used as a nonparametric alternative to analysis of variance to account for unequal variance among groups as needed. All statistical comparisons were two-sided tests with an a priori significance level of α = .05. All analyses were conducted using STATA (StataCorp LP).

Results

Of the 160 participants who completed hearing testing, 2 49 (30.6%) had no hearing loss, 56 (35.0%) had mild hearing loss, and 55 (34.4%) had moderate or worse hearing loss in their better hearing ear. Mean age at the time of hearing assessment was 74.2 years (SD = 8.6; range: 59.8–99.7 years), and the mean hearing level based on a four-frequency PTA in the better hearing ear was 35.8 dB HL (SD = 15.3; range: 7.5–91.3 dB HL). Across the entire group, better ear PTA was correlated with age, r(158) = .40, p < .001, and with self-perceived hearing handicap (HHIE-S score; r(147) = .45, p < .001).

Overall, 88 (60%) of 146 participants with cognitive status information available had an indication of cognitive impairment in their medical chart (n = 78) and/or per a failed cognitive screening measure conducted with the subset of participants who completed the questionnaire portion of the study (n = 26). Those with cognitive impairment tended to be older in the full sample, H(1) = 8.23, p = .004. There was not a significant difference in PTA in the better hearing ear among those with and without cognitive impairment, F(1, 144) = 2.72, p = .10.

The descriptive characteristics of the sample are presented as persons with and without cognitive impairment per each hearing status category (see Table 2). For almost all of the demographic and health variables compared, there were no significant differences between cognitive status groups within each hearing loss category. There was a significant age difference between the cognitive status groups within the no hearing loss category, F(1, 43) = 4.51, p = .04, and within the moderate/severe hearing loss category, F(1, 44) = 8.27, p = .006. In both cases, the cognitive impairment groups were significantly older. There was also a mean PTA difference between the cognitive impairment groups, but only in the no hearing loss category, F(1, 43) = 8.27, p = .006.

Table 2.

Demographic characteristics of a convenience sample of PACE participants who completed hearing screenings (N = 160).

Total
N = 160		 No hearing loss
 Mild hearing loss
 Moderate/severe hearing loss
No cognitive impairment
n = 20		 Cognitive impairment
n = 25		 No cognitive impairment
n = 24		 Cognitive impairment
n = 31		 No cognitive impairment
n = 14		 Cognitive impairment
n = 32
M (SD) M (SD) M (SD) M (SD) M (SD) M (SD) M (SD)
Age, years 74.2 (8.6) 67.9 (4.7)* 71.1 (5.4)* 74.1 (6.9) 73.6 (8.4) 72.0 (7.8)** 81.9 (8.7)**
Better ear
PTA (dB HL)		 35.8(15.3) 17.7 (4.5)** 21.0 (3.3)** 32.7 (4.6) 33.7 (3.9) 53.3 (13.7) 51.5 (8.8)
HHIE-S 10.4 (11.4) 5.0 (8.0) 6.1 (7.7) 6.9 (9.1) 8.5 (10.7) 17.4 (11.9) 17.5 (13.3)
n (%) n (%) n (%) n (%)
Race
 White 61 (46) 9 (45) 9 (39) 10 (50) 11 (41) 8 (80) 14 (44)
 Black/AA 46 (35) 10 (50) 9 (39) 5 (25) 10 (37) 2 (20) 10 (31)
 Latinx 21 (16) 1 (5) 4 (17) 5 (25) 5 (19) 6 (19)
 Other 4 (3) 1 (4) 1 (4) 2 (6)
Gender (No. of females) 72 (55) 12 (60) 13 (57) 13 (62) 14 (52) 3 (30) 19 (59)
Education
 Less than HS 41 (31) 1 (5) 5 (22) 6 (29) 7 (26) 3 (30) 19 (59)
 HS/GED 64 (48) 15 (75) 11 (48) 9 (43) 12 (44) 6 (60) 11 (34)
 More than HS 20 (15) 4 (20) 3 (13) 4 (19) 6 (22) 1 (10) 2 (6)
 Other 8 (6) 4 (17) 2 (10) 2 (7)
HA use
 Yes 13 (9) 1 (3) 2 (17) 10 (28)
 Previous 10 (7) 1 (4) 3 (25) 8 (22)
 No 128 (85) 18 (100) 24 (96) 25 (100) 30 (97) 7 (58) 18 (50)
Comorbidities
 Diabetes 85 (59) 12 (60) 12 (50) 17 (74) 19 (61) 9 (64) 16 (50)
 Hypertension 130 (90) 16 (80) 21 (88) 23 (100) 29 (94) 12 (86) 29 (91)
 CVD 115 (80) 14 (70) 18 (75) 16 (70) 27 (87) 11 (79) 29 (91)
 Depression 96 (67) 14 (70) 17 (71) 13 (57) 20 (65) 9 (64) 23 (72)
 Frailty 10 (7) 1 (5) 2 (8) 1 (4) 1 (3) 1 (7) 4 (13)
Smoker
 Never 41 (39) 6 (43) 10 (48) 6 (38) 7 (32) 1 (13) 11 (44)
 Former 46 (43) 5 (36) 7 (33) 7 (44) 12 (55) 5 (63) 10 (40)
 Current 19 (18) 3 (21) 4 (19) 3 (19) 3 (14) 2 (25) 4 (16)
No. of falls
 None 93 (65) 12 (60) 18 (75) 17 (74) 24 (77) 9 (64) 13 (41)
 One 23 (16) 3 (15) 2 (8) 5 (22) 2 (6) 2 (14) 9 (28)
 Two or more 28 (19) 5 (25) 4 (17) 1 (4) 5 (16) 3 (21) 10 (31)
No. of ED visits
 None 104 (72) 15 (75) 17 (71) 17 (74) 27 (87) 12 (86) 16 (50)
 One 26 (18) 2 (10) 3 (13) 5 (22) 3 (10) 1 (7) 12 (38)
 Two or more 14 (10) 3 (15) 4 (17) 1 (4) 1 (3) 1 (7) 4 (12)
No. of hospital admissions
 None 114 (79) 19 (95) 19 (79) 18 (78) 27 (87) 11 (79) 20 (63)
 One 24 (17) 1 (5) 4 (17) 3 (13) 4 (13) 2 (14) 10 (31)
 Two 6 (4) 1 (4) 2 (9) 1 (7) 2 (6)
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Note. Hearing loss defined as: no loss (≤ 25 dB HL), mild loss (26–40 dB HL), and moderate/severe loss (> 40 dB HL) in the better hearing ear calculated using a four-frequency pure-tone average (PTA) at 0.5, 1, 2, and 4 kHz. Number of falls, emergency department visits, and hospital admissions were extracted from medical charts over a 12-month period. N = 160 for age and PTA. Other characteristics have missing data: HHIE-S (n = 148); race (n = 132); gender, education (n = 133); HA use (n = 151); comorbidities, falls, emergency department (ED) visits, hospital admissions (n = 144); smoking (n = 106). Percentages are based on the number of participants with data available per category. Not all percentages add to 100% due to rounding. PACE = Program for All-inclusive Care for the Elderly; HHIE-S = Hearing Handicap Inventory for Elderly–Screening; AA = African American; No. = number; HS = high school; GED = general educational development; HA = hearing aid; CVD = cardiovascular disease.

*

p < .05.

**

p < .01.

The primary variables of interest—hearing and cognitive status—were compared across race/ethnicity categories (see Table 3). There were no group differences for hearing threshold, hearing handicap, rate of HA use, or proportion of cognitive impairments across racial/ethnic categories. A brief demographic comparison of participants across the three test sites suggests no significant difference in age, F(2, 157) = 0.63, p = .53, and significant differences in race (p < .001, Fisher's exact test) and education level (p = .001, Fisher's exact test; see Table 1). Results suggest that the population at Mercy LIFE PACE was predominately White and had more education beyond HS, PACE of RI had more participants with less than a HS degree, and UESP/PACE Boston had more Black/African American participants.

Table 3.

Hearing and cognition characteristics per race/ethnicity category.

Variable White (n = 61) Black/AA (n = 46) Latinx (n = 22)
M (SD) M (SD) M (SD)
Better ear PTA (dB HL) 36.1 (14.7) 33.4 (17.6) 34.9 (10.7)
HHIE-S a 8.7 (10.1) 9.3 (11.8) 16.8 (12.7)
n (%) n (%) n (%)
HA use b
 Yes 7 (12) 5 (11) —
 Previous 4 (7) 3 (7) 2 (5)
 No 48 (81) 38 (83) 19 (95)
Cognitive impairment 34 (56) 29 (63) 16 (73)
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Note. These data only reflect participants for whom race/ethnicity data were available and reported as White, Black/AA, or Latinx (N = 129). AA = African American; PTA = pure-tone average calculated based on four frequencies (0.5, 1, 2, and 4 kHz); HHIE-S = Hearing Handicap Inventory for Elderly–Screening; HA = hearing aid.

a

Sample sizes per race category for HHIE-S are: White = 60, Black/AA = 42, Latinx = 18.

b

There are missing data (n = 3) for HA use; percentages reported are based on the number of people for whom both race and HA use (n = 126) were reported. Not all percentages add to 100% due to rounding.

Discussion

The current data set provides a rich descriptive context from which to consider the hearing and communication needs of older adults in a group care setting. The analysis undertaken in this article sought to observe the impact of cognitive impairment among those with the same hearing loss status. Participants with cognitive impairment tended to be older, both for the full sample and per hearing loss category (at least for the “no hearing loss” and the “moderate/severe loss” groups). Within the “no hearing loss” category, there was a difference between groups for better ear PTA, but this pattern does not hold for the full sample. The lack of association between hearing threshold and cognitive status is somewhat contrary to population-based studies of hearing loss and dementia (Davies et al., 2017; Deal et al., 2017; Fritze et al., 2016; Golub et al., 2017; Gurgel et al., 2014; Lin et al., 2011). This may be explained by the high prevalence of both cognitive impairment and multiple chronic conditions across all cognitive status and hearing loss groups in this sample. Due to the nature of this convenience sample being nursing home eligible, they may have a higher prevalence of multiple chronic conditions than the general population. Despite the suggestion from the current data that the combined impact of cognitive impairment and hearing loss did not yield significant differences between groups on health outcomes, such as falls and hospital utilization, the burden of multiple chronic conditions in this sample highlights important considerations around access to and priorities for care in older adults. One consideration is that the comprehensive care approach provided by PACE might contribute to the relatively low number of falls, emergency department visits, and hospitalizations in this medically complex sample. In line with that comprehensive care approach, future intervention research designed to increase access to care for untreated hearing loss in older adults should adopt an interdisciplinary approach and a multiple chronic conditions mindset to design more inclusive interventions that recognize the medical complexity of many older adults.

Furthermore, the current sample is unique compared to most clinical and convenience samples presented in the hearing research literature given the racial/ethnic diversity of the sample. While the current sample is small (n = 160), the racial/ethnic balance is unique because there was a greater number of minority individuals (n = 99) than White individuals (n = 61). One recent study sought to investigate racial/ethnic disparities via the National Health and Nutritional Examination Surveys data, which included 1,554 adults over 70 years old with hearing data (Whites = 1165; Blacks = 227; Mexican Americans = 152), yet there were only 11 Blacks and 10 Mexican Americans who reported regular use of HAs, making statistical inferences unstable (Nieman et al., 2016). Unlike the data presented in National Health and Nutritional Examination Surveys, there was no significant difference between race/ethnicity groups in HA use in the current sample. The lack of significant differences related to hearing or cognitive status between the racial/ethnic groups in the current sample could be due to their enrollment in the PACE program, or it may be due to limited sample size, extent of multiple chronic conditions, or lack of socioeconomic variation within the PACE population, which can often interact with race/ethnicity differences (Nieman et al., 2016).

From a socioeconomic perspective, participants in the PACE program are typically dual-eligible Medicare and Medicaid recipients, which yields a lower income and more disabled population than a typical community sample. Consistent with those characteristics, we see, in this sample, individuals who face many health disparities: a high minority population, low rates of education, high rates of smoking, and high prevalence of major chronic conditions (diabetes, hypertension, cardiovascular disease, and depression; Meyer et al., 2013). While the lack of differences in the current sample between race/ethnicity groups may be due to interactions with other common sources of health disparities, such as low education, it could also be a positive side-effect of the PACE style of care. A different perspective on the similarities between race/ethnicity groups in this sample could be that the comprehensive care network provided by PACE services bridges these common health disparities in this population. In the face of such complex health conditions and needs as observed in the current sample, integrating hearing and communication support services into a comprehensive care plan, such as PACE, provides an opportunity to serve many people who might otherwise not seek audiologic care.

Characterizing this population is a necessary step for designing future research studies and clinical interventions that use novel service delivery models. One research motivation is to determine what outcome measures may be targeted in future studies of hearing care interventions designed to improve the overall health status of older adults. In terms of clinical implications, the goal of this study was to create a context from which to consider the multiple chronic conditions and health challenges that older adults may be facing in order to design aural rehabilitation plans that benefit the person and family.

Clinical Implications

In addition to the above call for integrating hearing and communication support services into a comprehensive care model, the interdisciplinary approach of integrating these services can be viewed through the lens of person/family-centered care. Providing audiologic services to medically complex older adults requires new service delivery models to increase access to this highly underserved population (National Academies of Sciences, 2016). For example, recent research with adults with age-related hearing loss and dementia has sought to rely on simple solutions (e.g., personal sound amplifiers and communication training for caregivers) that can be embedded in care services already being received by the family (Hubbard et al., 2018; Mamo, Nirmalasari, et al., 2017; Mamo, Oh, et al., 2017; Palmer et al., 2017). More broadly, experts in dementia care consistently call for a holistic approach to alleviate behavioral disturbances associated with dementia while simultaneously reducing a reliance on a pharmacological approach to managing said behaviors (Austrom et al., 2018). When audiologists serve adults with dementia, providing person/family-centered care requires that the hearing treatment options fit into to the overall care plan for the person and their caregivers. Given the interdisciplinary comprehensive care model of PACE, these organizations present an ideal opportunity to incorporate hearing and communication supports into a person-centered care approach.

Limitations

A limitation in the current study is limited control over the environment during hearing threshold testing. Nevertheless, the average 1/3-octave band noise measurements recorded on the SHOEBOX audiometer during threshold testing ranged from 27.1 dB SPL (SD = 7.7) at 4000 Hz to 34.1 dB SPL (SD = 9.4) at 500 Hz, which is appropriate given the attenuation characteristics of the DD450 circumaural transducers. While continuous monitoring of the background noise levels revealed some instances of excessive noise, the estimates of hearing thresholds and prevalence of hearing loss across the age of the current sample are consistent with the general population (Chien & Lin, 2012). Another limitation is the amount of missing data in various measures, which is a byproduct of retrospective chart review, especially given the fact that the three sites used three different electronic medical record systems resulting in inconsistencies in the reporting of some demographic and health history information. Finally, selection bias affected the characteristics of the sample, potentially yielding a sample that is somewhat less impaired than the PACE population as a whole due to the need for participants to have capacity to consent to the research study. As such, PACE participants with greater degrees of cognitive impairment were excluded from the sample.

Conclusions

The current study presents a diverse sample of adults (n = 160) with a high rate of multiple chronic conditions. While the combination of hearing loss and cognitive impairment in this sample did not suggest worse demographic characteristics, health status, or health outcomes, a majority of the sample experienced multiple chronic conditions. Rather than determining particular outcome measures of interest for future research studies, the take-home message from this data set suggests embedding hearing intervention research in a multiple chronic condition paradigm that utilizes interdisciplinary research teams. Furthermore, clinically speaking, provision of specialized services for older adults, especially those eligible for nursing home care, requires that each condition be considered as part of the whole rather than a singular problem to be treated. Considering hearing and communication support within integrated care plans, such as the PACE organization, may be the best way to support health and well-being for many medically complex older adults and provide optimal person/family-centered care.

Acknowledgments

This work was supported by National Institute on Deafness and Other Communication Disorders K23DC016855 (awarded to S. K. M.). The authors gratefully acknowledge Jessica Pearlman (UMass ISSR) for statistical consultations and the data collection efforts of Julia Read, Julia Serra, and Frank Sigismondo. The authors offer their sincerest thanks to the staff and participants at the Program for All-Inclusive Care for the Elderly centers who collaborated on this project, providing support and space to do this work.

Funding Statement

This work was supported by National Institute on Deafness and Other Communication Disorders K23DC016855 (awarded to S. K. M.). The authors gratefully acknowledge Jessica Pearlman (UMass ISSR) for statistical consultations and the data collection efforts of Julia Read, Julia Serra, and Frank Sigismondo.

Footnotes

1

Due to the number of non-English–speaking participants at UESP/PACE, the research team and the PACE providers agreed to offer hearing testing and medical chart review only, excluding the option for participation in the social health questionnaires. Consent forms were translated into Portuguese, Spanish, and Haitian Creole, and the consent process was completed with the assistance of translators to allow non-English speakers to participate.

2

Five better ear PTAs out of 160 participants were calculated based on two- (n = 2) or three-frequency (n = 3) PTAs due to participant fatigue and incomplete tests. One participant was excluded from analyses because a threshold could not be obtained at any of the audiometric frequencies. Of all test frequencies included in PTA estimations, 17% of those individual frequency thresholds may have been elevated due to excessive background noise during testing based on the continuous noise monitoring provided by the SHOEBOX audiometer.

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