The impact of hearing impairment and hearing aid use on progression to mild cognitive
impairment in cognitively healthy adults: An observational cohort study

Bucholc, M., Bauermeister, S., Kaur, D., McClean, P. L., & Todd, S. (2022). The impact of hearing impairment
and hearing aid use on progression to mild cognitive impairment in cognitively healthy adults: An observational
cohort study. Alzheimer's and Dementia: Translational Research and Clinical Interventions, 8(1), 1-12. Article
e12248. Advance online publication. https://doi.org/10.1002/trc2.12248
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DOI:
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Download date: 06/10/2024

Received: 10 May 2021

Revised: 25 November 2021

Accepted: 15 December 2021

Published online: 22 February 2022

DOI: 10.1002/trc2.12248

RESEARCH ARTICLE

The impact of hearing impairment and hearing aid use on
progression to mild cognitive impairment in cognitively healthy
adults: An observational cohort study
Magda Bucholc1
Stephen Todd4

Sarah Bauermeister2

Daman Kaur3

Paula L. McClean3

1

Cognitive Analytics Research Lab, School ofComputing, Engineering & Intelligent Systems,
Ulster University, Londonderry, UK

Abstract
Introduction: We assessed the association of self-reported hearing impairment and2

Department of Psychiatry, University of
Oxford, Oxford, UK

hearing aid use with cognitive decline and progression to mild cognitive impairment

3(MCI).

Northern Ireland Centre for Stratified
Medicine, Biomedical Sciences ResearchInstitute, Ulster University, Londonderry, UK

4Altnagelvin Area Hospital, Western Healthand Social Care Trust, Londonderry, UK

Methods: We used a large referral-based cohort of 4358 participants obtained fromthe National Alzheimer’s Coordinating Center. The standard covariate-adjusted Cox
proportional hazards model, the marginal structural Cox model with inverse probability weighting, standardized Kaplan-Meier curves, and linear mixed-effects models

Correspondence
Magda Bucholc, Cognitive Analytics ResearchLab, School of Computing, Engineering & Intelligent Systems, Ulster University, Londonderry
BT48 7JL, UK.
E-mail: m.bucholc@ulster.ac.uk
Funding information
European Union INTERREG VA Programme,
Grant/Award Number: INT-VA/052; Global
Challenge Research Fund; Alzheimer’s
Research UK; Dementias Platform UK supported by the Medical Research Council,
Grant/Award Number: MR/L023784/2;
NIA/NIH, Grant/Award Number: U01
AG016976; NIA, Grant/Award Number: P30
AG019610

were applied to test the hypotheses.
Results: Hearing impairment was associated with increased risk of MCI (standardized hazard ratio [HR] 2.58, 95% confidence interval [CI: 1.73 to 3.84], P = .004) andan accelerated rate of cognitive decline (P < .001). Hearing aid users were less likely
to develop MCI than hearing-impaired individuals who did not use a hearing aid (HR0.47, 95% CI [0.29 to 0.74], P = .001). No difference in risk of MCI was observed
between individuals with normal hearing and hearing-impaired adults using hearing
aids (HR 0.86, 95% CI [0.56 to 1.34], P = .51).
Discussion: Use of hearing aids may help mitigate cognitive decline associated withhearing loss.
KEYWORDS

cognitive decline, cognitive impairment, dementia, dementia prevention, hearing aid, hearing
impairment, hearing loss, mild cognitive impairment, preventive intervention

1

BACKGROUND

estimates for those aged 65 or over ranging between 16% and 23%1
and the annual conversion rate to dementia and Alzheimer’s disease

Mild cognitive impairment (MCI) describes a condition associated with(AD) of 9.6% and 8.1%, respectively.2

demonstrable decline in cognitive abilities greater than normal age-

While numerous studies have investigated the impact of inter-

related changes but not severe enough to meet diagnostic criteria forventions aimed at preventing the onset of dementia in individ-

dementia.1 MCI is common among older adults, with the prevalenceuals with MCI, including exercise,3 antidepressant treatment4 ,This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any
medium, provided the original work is properly cited and is not used for commercial purposes.
© 2022 The Authors. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer’s Association
Alzheimer’s Dement. 2022;8:e12248.
https://doi.org/10.1002/trc2.12248

wileyonlinelibrary.com/journal/trc2

1 of 122 of 12BUCHOLC ET AL.

non-invasive brain stimulation,5 stress reduction,6 and the optimal control of vascular risk factors,7 there is a need for further
research aimed at identifying prevention strategies earlier in thedementia process. The multidomain Finnish Geriatric Intervention
Study to Prevent Cognitive Impairment and Disability (FINGER)
intervention trial, combining lifestyle interventions, drug treatment, and cognitive training, demonstrated a beneficial effect oflifestyle intervention against cognitive decline among individuals
with elevated risk of developing dementia.8 On the other hand, thefindings of the Multidomain Alzheimer Preventive Trial (MAPT) and
the Prevention of Dementia by Intensive Vascular Care (PreDIVA)
randomized clinical trial (RCT) showed no significant impact of themultidomain lifestyle interventions on cognitive decline and incident

HIGHLIGHTS∙ Hearing loss is associated with higher risk of mild cognitive
impairment (MCI).
∙ Hearing loss is associated with accelerated cognitive
decline.
∙ Hearing aid use is associated with lower risk of MCI andslower cognitive decline.
∙ People with normal hearing and hearing aid users have
similar risk of MCI.
∙ Quality audiology screening might prove an effective
dementia prevention strategy.

all-cause dementia, respectively.9,10 Additional research is needed toensure a robust evidence base and provide insight into the potentialof different lifestyle interventions aimed at preventing cognitive
decline and the hypothesized mechanisms of change underlying theseinterventions.

RESEARCH IN CONTEXTHearing impairment is the third most common chronic health condi-

1. Systematic Review: The authors reviewed the litera-tion, with the prevalence of about 33% in individuals aged 65 years andture using PubMed. Although several studies evaluatedolder.11 Hearing loss and cognitive impairment often occur together,

the relationship between hearing impairment and cog-

which creates the question of whether cognitive decline is caused bynitive decline, only two studies, with contradictory find-hearing loss and thus whether audiological rehabilitation through hear-ings, have assessed the risk of developing mild cogni-

ing aids or cochlear implants can reduce the risk of cognitive deteri-tive impairment (MCI) in adults with and without hearing

oration. The Lancet Commission on Dementia Prevention, Interven-

loss. The longitudinal studies investigating the association

tion, and Care estimated that failure to treat hearing impairment may

between hearing aid use and cognitive decline are scarceaccount for up to 9% of dementia cases, assuming that there is in fact

while no study has examined the role of hearing aids ina causal relationship between auditory and cognitive decline.12 Sev-

healthy-to-MCI conversion.

eral observational studies demonstrated that hearing impairment is

2. Interpretation: Our findings show that hearing loss

associated with accelerated cognitive decline13–16 and a higher riskincreases the risk of incident MCI while hearing aid

of incident dementia.12,15,17 Furthermore, Lin et al.17 found a strong

use robustly reduces progression to MCI. Our findings

connection between the severity of hearing loss and dementia risk,

highlight the importance of taking a proactive approachwith individuals suffering from mild to severe hearing loss having a

toward addressing hearing decline over time.

2- to 5-fold increased risk of incident all-cause dementia compared to

3. Future Directions: The article proposes a framework

those with normal hearing. The potential mechanistic hypotheses thatfor the generation of new hypotheses. Examples include

could account for this association include the cognitive load theory; therandomized clinical trials further exploring the relation-changes in brain structure caused by the impoverished sensory input

ship between auditory impairment and cognition and theand decreased social interaction.18

hypothesized mechanisms that could account for thisBased on these reports, hearing rehabilitative strategies have been

association.

proposed as a way to restore deficits in cognitive function. The growing evidence from observational studies shows that hearing aid use
is associated with better cognition, slower cognitive decline,15,19–21
and reduced risk of developing all-cause dementia.19 No significant

exploring the relationship between auditory impairment and cognition

effect of hearing aid use on cognition was found in some studies.22,23

are ongoing.25–27

The discrepancies in the results across studies may arise from differ-

Although there have been many studies that included cognitively

ences in the design, population size, selection bias, and methodologi-

normal adults as part of the study sample, when investigating the asso-

cal approaches used. To date, limited information on the effect of hear-ciation between hearing loss and cognitive decline or dementia as aning treatment on cognitive function is available from RCTs. So far, theoutcome, few studies have examined the impact of hearing impair-

preliminary results from the Aging and Cognitive Health Evaluation

ment and hearing aid use on incident MCI.28,29 MCI is important toin Elders (ACHIEVE) study demonstrated a significant effect of hear-consider as an earlier outcome on the trajectory of cognitive decline

ing aid use on composite memory scores after 6 months of follow-up;

that could further improve our ability to identify which early detec-

however, improvement in other cognitive outcomes (language, execu-

tion measures, or combination of measures, obtained among individ-

tive function, global function) was not observed.24 Few RCTs further

uals increase or decrease the likelihood of progression from normal

3 of 12BUCHOLC ET AL.

cognition to the onset of clinical symptoms associated with cognitive

test performance. Records with missing codes were excluded from theimpairment.

analysis. Hearing aid use was also established based on self-report.

The aim of the present study was 3-fold: (1) to examine the impact

Hearing aid users were subsequently asked if the hearing aid pro-of hearing impairment on cognitive function and progression to MCI

vided them with “functionally normal hearing.” The positive responsein cognitively healthy individuals; (2) to investigate the relationshipto this question implied that a participant did not demonstrate aamong the use of hearing aids, incident MCI, and cognitive decline;

reduced ability to carry out everyday activities, such as listening or

and (3) to compare time to incident MCI and rate of cognitive decline

talking, when wearing a hearing aid. All considered participants using

between individuals with normal hearing and hearing-impaired partic-

hearing aids reported functionally normal hearing when wearing a

ipants that used hearing aids.

device.

2

2.3

METHODS

2.1

Study design and participants

Statistical analysis

We used the two-sided t-test and Wilcoxon rank sum test to examine
bivariate associations between predictor variables and outcomes for

The cohort we studied were volunteers followed up approximately

normally and non-normally distributed continuous variables, respec-

annually at National Institute on Aging-funded Alzheimer’s Disease

tively. The Shapiro-Wilk test was used to determine whether the data

Research Centers (ADRCs). The National Alzheimer’s Coordinating

significantly deviated from a normal distribution. Group comparisonsCenter (NACC) maintains a database of standardized clinical and neu-

for categorical measures were performed using the Chi-square test.

ropathological information collected from these ADRCs.30 Consent

Survival analysis was conducted to compare the time to the inci-

was obtained from all participants at each ADRC under local institu-

dence of MCI between exposure groups for three primary outcomestional review oversight board. Data used in this study was the Uniform(Figure 1B). First, we investigated the impact of hearing impairment

Data Set (UDS) including visits conducted between September 2005

on the progression from healthy to MCI (Scenario 1). Second, we mea-

and December 2018. The UDS data are collected using a standard-

sured the association between hearing aid use and progression fromized evaluation of participants enrolled in ADRC clinics and recorded

healthy to MCI (Scenario 2). Third, we examined the significance of thedirectly on UDS forms (hard copy or electronic) during the evalua-potential impact of hearing aid use by comparing the risk of incident

tion process. Details about design, implementation, and rationale for

MCI diagnosis in participants experiencing no hearing loss and hearing-

the UDS have been published elsewhere.31 Data from individuals with

impaired subjects that used hearing aids (Scenario 3). Time to MCI con-normal cognition, 40 years of age or older at their first visit, with atversion was measured from the baseline visit until the date when aleast one follow-up visit, served as the initial sample for our study. The

patient was diagnosed with MCI or until the last registered visit forrecords with incomplete clinical information were disregarded. Fig-

those who were lost to follow-up (censored observations), with timeure 1A shows a flowchart for the inclusion of participants and researchmeasured in years since start of follow-up. The censoring dates werescenarios considered in this study.

defined as (1) the year of the NACC data freeze or (2) the year on which
the patient’s data were no longer available.
For the present analysis, we used two different survival models to

2.2

Procedures

evaluate the impact of hearing loss and hearing aid use on progression from cognitively healthy to MCI, namely, the standard Cox propor-

MCI incidence was determined based on the clinical diagnosis madetional hazards model (as benchmark), adjusted for baseline covariates,by a single clinician or through a consensus process. Diagnoses of MCI

and the marginal structural Cox (MSC) model with inverse probability

were established using the modified Petersen criteria.32 In addition,weighting (IPW).34 Herein, we refer to the standard covariate-adjusted

the longitudinally measured Clinical Dementia Rating Sum of Boxes

Cox proportional hazards model and the MSC model with IPW as the(CDR-SB) score was used to examine changes in cognitive performancestandard Cox model and IP-weighted MSC model, respectively. IPW

in six domains: memory, orientation, judgment and problem solving,is a technique commonly used in survey sampling to adjust for sam-community affairs, home and hobbies, and personal care.33 The CDR-

ple selection bias and the potential confounding effects of both time-

SB was administered and scored by trained staff within their respective

varying and baseline covariates.34 As such, the method creates a so-

ADRCs.

called pseudo-population in which (1) the exposure is independent of

Self-reported hearing loss was evaluated through the response to

the measured covariates and (2) drop-out is not related to the mea-

the single question, “Without a hearing aid(s), is the subject’s hear-

sured exposure and covariates and thus, potential selection bias due

ing functionally normal?” No information on the degree of hearing

to loss to follow-up is accounted for. As a result, unlike the standard

loss was provided in the NACC-UDS. Although it was not reported

Cox model, the IP-weighted MSC model allows for the estimation of theto NACC whether participants with hearing impairment were wear-

hazard ratio that can be interpreted, under certain assumptions (i.e.,

ing their hearing aids during cognitive testing, ADRCs were expected

well-defined exposures, the absence of unmeasured confounding, cor-

to use missing codes if it was indicated that hearing loss affected

rect model specification, and positivity), in the same way as the hazard

4 of 12BUCHOLC ET AL.

F I G U R E 1 Flow diagram indicating (A) the selection of study participants and (B) schematic presentation of research scenarios considered in
the study. Scenario 1 investigates the impact of hearing impairment on the progression from cognitively healthy to mild cognitive impairment(MCI). Scenario 2 examines the effect of hearing aid use on the progression from cognitively healthy to MCI. Scenario 3 compares the risk ofincident MCI diagnosis in participants with normal hearing and hearing-impaired subjects that used hearing aids. Data from 4358 participants, notdiagnosed with cognitive impairment, 40 years of age or older, having more than one Alzheimer’s Disease Research Center visit served as theinitial sample for our study (Scenario 1). This included 450 subjects with hearing impairment and 3908 subjects without hearing impairment.
Among 450 participants with hearing impairment, 313 were classified as hearing aid users and 137 as non-users of hearing aids (Scenario 2).
Information on hearing loss and hearing aid usage was collected via self-reportratio is obtained in a RCT, in which no confounding and no loss to follow-

based on the inverse of each participant’s probability of the expo-

up are observed.34

sure, given the values of baseline (age at baseline, sex, years of edu-

We tested the proportionality of hazards assumption using thecation, and years smoked) and time-varying covariates (hypertension,Schoenfeld residuals.35 The results suggested no meaningful depar-

diabetes, hypercholesterolemia, alcohol dependence, stroke, heart

ture from proportional hazards (P > .05). To account for events that

attack/cardiac arrest, BMI, GDS score, and hearing aid status in Sce-occurred on the same date, we used Efron’s approximation, which wasnario 1).38 To test for potential non-linear dependence in the data, wepreviously shown to perform well in the presence of ties.36 The stan-compared the model with only a linear term against the model withdard Cox model was adjusted for the baseline values of covariates

linear and cubic spline terms using a likelihood ratio test. The linear-including age, sex, years of education, diabetes, hypertension, hyper-

ity assumption was satisfied for all continuous variables. Because somecholesterolemia, years smoked, alcohol dependence, stroke, heart

participants were lost to follow-up throughout the study period, we

attack/cardiac arrest, body mass index (BMI), Geriatric Depression

also included censoring weights in the estimation process to accountScale (GDS) score, and hearing aid status (Scenario 1). BMI was catego-for selection bias due to loss to follow-up. To increase statistical effi-

rized as underweight (<20.0 kg/m2 ), normal (≥20.0 and <27.5 kg/m2 ),ciency, the weights were stabilized. Next, the IP-weighted MSC modelor overweight (≥27.5 kg/m2 ), based on the suggestion that higher cut-

was fitted by weighting participants according to their estimatedoff points may be more appropriate for older adults.37 GDS scores

exposure and censoring weights, with outcome time to incident MCI,

were categorized as no depression (<5) and depression (≥5). For theand the hearing impairment or hearing aid status as the sole covari-

IP-weighted MSC model, we first calculated the exposure weights,

ate. Using standardization by IP weights, we estimated standardized

5 of 12BUCHOLC ET AL.

hazard ratios and Kaplan-Meier (KM) survival curves. For all analyses,(interquartile range: 63 to 73). The baseline characteristics of partici-

the reported P-values were two-sided and differences with P < .05

pants are shown in Table 1.

were considered statistically significant.

Given Scenario 1, participants with hearing impairment were signifi-

Additionally, to assess the impact of hearing impairment and hearing

cantly older (P < .001), more educated (P = .01), and had a higher mean

aid usage on cognitive function, we performed longitudinal analyses for

CDR-SB score (P = .001) than individuals with normal hearing. A higher

Scenarios 1 to 3 using linear mixed effects models with individual CDR-

proportion of them were females (P < .001) and suffered from hyper-

SB test scores as dependent variables (Models 1 to 3, respectively).39

cholesterolemia (P = .001) and heart attack/cardiac arrest (P < .001).

Suitability for using a multilevel modeling approach was assessed by

In Scenario 2, non-users of hearing aids had fewer years of education

testing an “unconditional model” (“intercept only” model) in the first(P = .002) and were more likely to suffer from diabetes (P < .001), com-

instance. Because the model showed significant between-participant

pared to participants using hearing aids. In Scenario 3, participants withvariation (P < .001), the use of multilevel modeling was supported.

normal hearing were significantly younger (P < .001), predominantly

The effect of time, exposure allocation (i.e., hearing impairment or

female (P < .001), less educated (P < .001), and had a lower mean CDR-

hearing aid status) were included as fixed effects. The inclusion of

SB score (P = .02) than hearing aid users. A lower proportion of themother covariates and time by exposure group interaction was judged

suffered from hypercholesterolemia (P = .03) and heart attack/cardiac

against the model fit. Random intercepts and random slopes werearrest (P < .001), whereas the percentage of those with diabetes wasmodeled for each subject. We confirmed that all models, including

higher (P = .03).

the random intercept and the random slope, fitted the data significantly better than models incorporating only fixed effects (P < .001).
The Akaike information criterion (AIC) was applied to evaluate the3.2

Survival curves

most plausible model in the set of models being tested.40 In all subsequent analyses, the significance of fixed and random effect param-

IP-adjusted KM survival curves were constructed to compare the tim-

eters was evaluated using stepwise selection that started with the fulling of incident MCI for different exposure conditions in Scenarios 1

model, then dropped predictor terms sequentially. Two-tailed P-values

to 3 (Figure 2). The comparison of these curves with the unadjusted

were obtained using Kenward-Roger approximations for degrees of

KM estimates shows that although they have similar spread in Sce-

freedom.40

nario 2 (Figure 2B), the large drop in the survival plot in Scenario 1(Figure 2A) and a higher estimate of the survival probability for hearing aid users in Scenario 3 (Figure 2C) were driven by the implementa-

2.4

Sensitivity analysis

tion of IP weights. Because the median survival time was not reachedat the time of report for some exposure groups in Scenarios 1 to 3, we

Sensitivity analysis for unmeasured confounding was performed toused the restricted mean survival time (RMST) as an alternative mea-

study the effect of potential unmeasured covariates on the standard-

sure of participants’ survival profile over time. We defined RMST as theized hazard ratios (HRs), in Scenarios 1 to 3, in IP-weighted MSC

average event-free survival time up to the maximum possible follow-

models.41 We varied the assumed prevalence rates for the confounderup time of any participant within the design. As such, in Scenario 1, theamong the exposed (10%, 15%, and 20% of the population) and unex-

estimated RMST (standard error [SE]) for individuals with normal hear-

posed groups (10%, 15%, and 20% of the population), and used three

ing and those with hearing loss was 9.87 (SE: 0.06) and 7.29 (SE: 0.17;

different values of HR (0.5, 1.5, and 2.0) for the association between the

P < .001), respectively. The 5-year IP-weighted rates of MCI-free sur-confounder and the outcome. This allowed us to assess how the infer-

vival were 82.9% (95% confidence interval [CI], 81.7% to 84.1%) forences on the effects of exposures can be altered through an unknown

participants with normal hearing and 62.2%, (95% CI, 53.6% to 72.1%)

variable under different simulations.

for participants with hearing loss. In Scenario 2, the RMST was 9.35 (SE:0.16) for hearing aid users and 7.61 (SE: 0.31) for non-users of hearing
aids while IP-weighted event-free survival at 5 years was 87.5% (95%3

RESULTS

CI, 83.8% to 91.3%) and 69.4% (95% CI, 61.9% to 77.8%), respectively.
In Scenario 3, the between-group difference in RMST was 0.07 years

3.1

Participant characteristics

and not statistically significant (P = .62).

We analyzed a total of 4358 participants with no cognitive impairment
at baseline. This included 450 (10.3%) subjects with hearing impairment and 3908 (89.7%) subjects without hearing impairment. Among

3.3
Standard Cox model adjusted for baseline
covariates

450 participants with hearing impairment, 313 were classified as hearing aid users while 137 were not using hearing aids. Out of 4358 par-The standard Cox model adjusting for baseline covariates found that,ticipants, 416 converted to MCI during follow-up. The mean follow-up

compared to participants with normal hearing, those suffering fromtime was 4 years (standard deviation: 2.8, range: 2 to 12). The ages ofhearing loss were at significantly higher risk of incident MCI (HR 2.50,

the participants ranged from 40 to 80 years, with a median of 68 years

95% CI, 1.72 to 3.63, P < .001; Scenario 1). A significantly reduced risk

6 of 12TA B L E 1

BUCHOLC ET AL.

Demographic characteristics of participants
Scenario 1

Scenario 2

Hearing
impairment

Normalhearing

Sex, n (%),
female219 (48.7)2775 (71.0)

Age, median(IQR)

73 (68-77)

68 (63-73)

Scenario 3

P-value

Hearing aid
used

Hearing aid
not usedP-value< .001149 (47.6)

70 (51.1).54< .00173 (69-77)

72 (67-76).07

Normalhearing

Hearing
impairment,
hearing aid used

P-value2775 (71.0)

149 (47.6)< .00173 (69-77)< .00168 (63-73)

Education,mean (SD)a16.2 (2.9)

15.8 (2.8).01

16.5 (2.7)

15.5 (3.3).002

15.8 (2.8)

16.5 (2.7)< .001

CDR-SB,mean (SD)0.14 (0.46)

0.07 (0.30).001

0.13 (0.44)

0.17 (0.51).46

0.07 (0.30)

0.13 (0.44).02

BMI score, n
(%)

.20

.89

.28

<20

13 (2.9)

127 (3.3)

10 (3.2)

3 (2.2)127 (3.3)

10 (3.2)

20–27

234 (52.0)1853 (47.4)

163 (52.1)

71 (51.8)

1853 (47.4)

163 (52.1)≥27

203 (45.1)

1928 (49.3)

140 (44.7)

63 (46.0)

1928 (49.3)

140 (44.7)

GDS score, n
(%)

.24

.81

.43

<5

429 (95.3)

3768 (96.4)

299 (95.5)

130 (94.9)

3768 (96.4)

299 (95.5)≥5

21 (4.7)140 (3.6)

14 (4.5)7 (5.1)140 (3.6)

14 (4.5)

52 (11.6)475 (12.1).76

25 (8.0)27 (19.7)< .001475 (12.1)

25 (8.0).03

214 (47.6)
Hypertension,n (%)

1810 (46.3).62

145 (46.3)

69 (50.4).471810 (46.3)

145 (46.3)

1

256 (56.9)
Hypercholesterolemia,n (%)

1913 (49.0).001

173 (55.3)

83 (60.6).301913 (49.0)

173 (55.3)

.03

.38

9.0 (13.9)

8.5 (13.1).53

Diabetes, n(%)

Smoking,mean (SD)

8.9 (13.7)

9.0 (13.9).90

8.5 (13.1)

9.8 (15.2)

Alcoholdependence, n(%)

23 (5.1)

126 (3.2).05

16 (5.1)

7 (5.1)1

126 (3.2)

16 (5.1).1

Stroke, n (%)

8 (1.8)41 (1.1).16

7 (2.2)1 (0.7).45

41 (1.1)

7 (2.2).09Heart
32 (7.1)
attack/cardiac
arrest, n(%)

113 (2.9)< .00123 (7.3)

9 (6.6).84

113 (2.9)

23 (7.3)< .0010 (0)< .001–––Hearing aid
use, n (%)

313 (69.6)–

Abbreviations: BMI, body mass index; CDR-SB, Clinical Dementia Rarting Sum of Boxes; GDS, Geriatric Depression Scale; IQR, interquartile range; SD, standard deviation.
aMeasured as the number of years of education completed.

of MCI was associated with the use of hearing aids (HR 0.31, 95% CI,
0.19 to 0.53, P < .001; Scenario 2). No statistically significant differ-

3.4
Inverse probability weighted marginal
structural Cox model

ences in time to incident MCI diagnosis were found between hearingimpaired individuals that used hearing aids and those with no hearing

All standardized HR estimates were similar to the HRs obtained from

impairment (HR 0.85, 95% CI, 0.59 to 1.23, P = .4; Scenario 3). HR esti-

the standard Cox model (Table 2). After fitting the MSC model by

mates for all considered covariates are summarized in Table 2.

weighting participants according to their estimated exposure and7 of 12BUCHOLC ET AL.

TA B L E 2
to MCI

Unweighted and IPW HR and 95% CIs for the effect of hearing loss and hearing aid use on the progression from cognitively healthy

Scenario 1
HR (95% CI)

Scenario 2
P-valueHR (95% CI)

Scenario 3
P-valueHR (95% CI)

P-valueStandard Cox proportional hazards model adjusted for baseline covariates
Exposure of interest
Hearing impairment: No
Hearing impairment: Yes
Hearing aid use: No

Reference
2.50 (1.72, 3.63)––< .001
–

–

–

–

–

–

–

–

–

–

–

–

Reference
0.31 (0.19, 0.53)< 0.001

Hearing aid use: Yes––

Hearing impairment: No

–

–

–

–

Hearing aid use: Yes

–

–

–

–

0.85 (0.59, 1.23)

0.4

0.004

1.06 (1.05, 1.08)< 0.001

Reference

Covariates
Age, years

1.06 (1.05, 1.08)< .0011.08 (1.02, 1.13)

Education, years

0.96 (0.93, 0.99).03

0.98 (0.90, 1.06).58

0.96 (0.93, 0.99).03

CDR-SB score1.68 (1.48, 1.91)< .001

1.88 (1.28, 2.75).001

1.66 (1.46, 1.90)< .001

Sex: Female

0.73 (0.59, 0.90).003

1.08 (0.64, 1.84).77

0.71 (0.59, 1.23).002

BMI score
20–27

Reference

Reference

Reference<20

1.47 (0.92, 2.35).1

1.34 (0.30,5.95).7

1.47 (0.91, 2.38)

.11

≥27

0.79 (0.64, 0.98).03

0.95 (0.56, 1.61).84

0.77 (0.61, 0.95).02

GDS score<5≥5Reference

Reference

Reference

1.65 (1.05, 2.60).03

0.79 (0.23, 2.66).7

1.82 (1.14, 2.89).01

Diabetes, Yes

1.16 (0.88, 1.54).3

0.94 (0.46, 1.92).86

1.16 (0.86, 1.57).32

Hypertension, Yes

1.16 (0.94, 1.44).17

1.19 (0.68, 2.06).55

1.17 (0.93, 1.46).18

Hypercholesterolemia, Yes

1.04 (0.84, 1.27).74

1.05 (0.63, 1.77).85

1.06 (0.85, 1.31).62

Smoking, years

1.00 (0.99, 1.01).63

1.01 (0.99, 1.02).59

1.00 (0.99, 1.01).44

Alcohol dependence, Yes

1.32 (0.80, 2.19).28

0.33 (0.04, 2.58).3

1.40 (0.83, 2.35).21

Stroke, Yes

2.15 (1.20, 3.84).01

0.78 (0.10, 6.02).81

2.07 (1.13, 3.79).02

0.30 (0.07, 1.30).11

1.11 (0.69, 1.78)

Heart attack/cardiac arrest, Yes

0.95 (0.60, 1.51).82

Hearing aid use, Yes

0.37 (0.23, 0.60)< .001

.68

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

–

Marginal structural Cox model with inverse probability (IP) weightinga
Exposure of interest
Hearing impairment: No
Hearing impairment: Yes
Hearing aid use: No

Reference
2.58 (1.73, 3.84)–< .001–

Reference

Hearing aid use: Yes––

Hearing impairment: No––

0.47 (0.29, 0.74)
–

–

.001

Hearing aid use: Yes

–

–

–

–

Reference
0.86 (0.56, 1.34).51

Abbreviations: 95% CI, 95% confidence interval; BMI, body mass index; CDR-SB, Clinical Dementia Rating Sum of Boxes; GDS, Geriatric Depression Scale;HR, hazard ratio; IPW, inverse probability weighting; MCI, mild cognitive impairment.
aIP weighted to account for confounding of exposure due to baseline covariates (age at baseline, sex, years of education, and years smoked), time-varying
covariates (hypertension, diabetes, hypercholesterolemia, alcohol dependence, stroke, heart attack/cardiac arrest, BMI, GDS score, hearing aid status [Scenario 1]), and selection bias due to drop out.
Scenario 1 investigates the impact of hearing impairment on the progression from cognitively healthy to MCI.
Scenario 2 examines the effect of hearing aid use on the progression from cognitively healthy to MCI.
Scenario 3 compares the risk of incident MCI diagnosis in participants with normal hearing and hearing-impaired subjects that used hearing aids.

8 of 12BUCHOLC ET AL.

sured confounding bias. Therefore, we conducted sensitivity analysis
for unmeasured confounding to further assess the robustness of ourresults (Table 3). Sensitivity analysis for unmeasured confounding performed for Scenario 1 showed that hearing-impaired individuals wereat substantially higher risk of developing MCI compared to participants
with normal hearing for all considered values of the strength of theconfounder–outcome association, and the prevalence of potential confounder in the population. The results of sensitivity analyses obtainedfor Scenarios 2 and 3 were also consistent with those from the primary analysis; that is, the use of hearing aids was associated with lower
risk of incident MCI in Scenario 2 and no difference in time to incident
MCI was observed between patients with normal hearing and hearingimpaired individuals using hearing aids in Scenario 3.

3.6

Longitudinal changes in cognitive function

In a complementary analysis, we assessed the impact of hearing impairment and hearing aid usage on cognitive function in Scenarios 1 to
3 using linear mixed effects models (Model 1 to 3, respectively) with
CDR-SB scores as dependent variables. In Model 1, for every 1-yearincrease, CDR-SB increased by 0.01 (P < .001). On average, individuals with hearing impairment tended to have 0.1 points higher CDR-SB
score compared to those without hearing loss (P < .001). Participants
with normal hearing also showed less time-related decline than individuals with hearing loss (P = .004). Accordingly, the annual rate of change
in CDR-SB was 0.012 points higher for individuals with hearing loss.
Within Model 2, we found a significant effect of hearing aid status on
the CDR-SB score (P = .01). The CDR-SB score reported for hearingimpaired participants using hearing aids was, on average, 0.07 points
lower than for non-users of hearing aids. The mean annual rate of
F I G U R E 2 Unadjusted and inverse probability weighted
Kaplan-Meier (KM) survival curves showing cumulative mild cognitive
impairment (MCI)-free survival differences between: (A) participants
with and without hearing loss (Scenario 1), (B) participants using and
not using hearing aids (Scenario 2), (C) individuals with normal hearing
and hearing-impaired participants that used hearing aids (Scenario 3)

change in CDR-SB for users and non-users of hearing aids was 0.04 and0.08 points, respectively. In Model 3, we observed a significant effectof follow-up time on the CDR-SB score (P < .001), with the annual rateof change in CDR-SB of 0.006 points. Temporal changes in the CDR-SB
score for individuals without hearing loss and hearing-impaired adults
using hearing aids were statistically insignificant (P = .16).

censoring weights, individuals with hearing loss were found to be atsubstantially higher risk of incident MCI (HR 2.58, 95% CI, 1.73 to 3.84,

4

DISCUSSION

P < .001), compared to those with normal hearing (Scenario 1). In addition, the use of hearing aids was associated with a lower risk of healthy-

Our study reveals that hearing impairment is independently associ-to-MCI conversion (HR 0.47, 95% CI, 0.29 to 0.74, P = .001; Scenario 2).

ated with accelerated cognitive decline and higher risk of incident MCI.

We found no statistically significant differences in risk of incident MCI

Hearing aid use is linked to lower rates of cognitive decline and reduced

between participants with normal hearing and hearing-impaired adults

risk of incident MCI, with hearing aid users having more than 50%

that reported use of hearing aids (HR 0.86, 95% CI, 0.56 to 1.34, P = .51;

lower risk of MCI, compared to those not using hearing aids. Impor-

Scenario 3).

tantly, we demonstrated that no significant differences in risk of developing MCI and cognitive decline exist between participants experiencing no hearing loss and those diagnosed with hearing impairment using

3.5

Sensitivity analysis

hearing aids. This implies that use of hearing aids may help mitigate
cognitive decline associated with hearing loss, offering an actionable

Although IP-weighted MSC models fully account for measured con-strategy to reduce the incidence of MCI. Sensitivity analyses did not

founders and selection bias, they may still be susceptible to unmea-

affect the results of our primary analysis; hearing loss increases the risk

9 of 12BUCHOLC ET AL.

TA B L E 3

Sensitivity analysis for unmeasured confounding in a marginal structural Cox model with IPW
HR adjusted for unmeasured confounder (95% CI)aPrevalence of unmeasured confounder (%)

Unmeasured
confounder HR
0.5

Unmeasured
confounder HR
1.5

Unmeasured
confounder HR
2.0

Scenario 1
Normal hearing

Hearing impairment

10

10

2.58 (1.73,3.84)

2.65 (1.78,3.94)

2.72 (1.83,4.05)

15

2.51 (1.69,3.74)

2.58 (1.73,3.84)

2.65 (1.78,3.95)

20

2.44 (1.64,3.64)

2.51 (1.69,3.74)

2.58 (1.73,3.84)

10

2.58 (1.73,3.84)

2.52 (1.69,3.75)

2.46 (1.65,3.67)

15

2.64 (1.77,3.93)

2.58 (1.73,3.84)

2.52 (1.69,3.75)

20

2.70 (1.81,4.02)

2.64 (1.77,3.93)

2.58 (1.73,3.84)

10

2.58 (1.73,3.84)

2.47 (1.66,3.67)

2.36 (1.59,3.52)

15

20

15

2.70 (1.81,4.01)

2.58 (1.73,3.84)

2.47 (1.66,3.68)

20

2.81 (1.89,4.19)

2.69 (1.81,4.01)

2.58 (1.73,3.84)

Scenario 2
Hearing aid used

Hearing aid not used

10100.47 (0.29,0.74)

0.48 (0.30,0.76)

0.49 (0.31,0.78)

15

0.45 (0.28,0.72)

0.47 (0.29,0.74)

0.48 (0.30,0.76)

20

0.44 (0.28,0.70)

0.45 (0.28,0.72)

0.47 (0.29,0.74)

100.47 (0.29,0.74)

0.46 (0.29,0.73)

0.44 (0.28,0.71)

15

20

15

0.48 (0.30,0.76)

0.47 (0.29,0.74)

0.46 (0.29,0.73)

20

0.49 (0.31,0.78)

0.48 (0.30,0.76)

0.47 (0.29,0.74)

100.47 (0.29,0.74)

0.45 (0.28,0.71)

0.43 (0.27,0.68)

15

0.49 (0.31,0.78)

0.47 (0.29,0.74)

0.45 (0.28,0.71)

20

0.51 (0.32,0.81)

0.49 (0.31,0.78)

0.47 (0.29,0.74)

0.86 (0.56,1.34)

0.89 (0.57,1.37)

0.91 (0.59,1.41)

Scenario 3
Normal hearing

Hearing aid used

10

10

15

20

15

0.84 (0.54,1.30)

0.86 (0.56,1.34)

0.89 (0.57,1.37)

20

0.82 (0.53,1.27)

0.84 (0.54,1.30)

0.86 (0.56,1.34)

10

0.86 (0.56,1.34)

0.84 (0.55,1.31)

0.82 (0.53,1.28)

15

0.88 (0.57,1.37)

0.86 (0.56,1.34)

0.84 (0.55,1.31)

20

0.90 (0.58,1.40)

0.88 (0.57,1.37)

0.86 (0.56,1.34)

10

0.86 (0.56,1.34)

0.83 (0.53,1.28)

0.79 (0.51,1.23)

15

0.90 (0.58,1.40)

0.86 (0.56,1.34)

0.83 (0.53,1.28)

20

0.94 (0.61,1.46)

0.90 (0.58,1.39)

0.86 (0.56,1.34)

Abbreviations: CI, confidence interval; HR, hazard ratio; IPW, inverse probability weighting.
Notes: The selected prevalence rates for the unmeasured confounder among the exposed group were 10%, 15%, and 20% of the population. Three different
values of HR, namely 0.5, 1.5, and 2.0, for the association between the confounder and the outcome were used. The prevalence of the unmeasured confounderin the unexposed group was varied from 10% to 20% to determine the extent to which its distribution under these conditions would need to be imbalanced toinfluence the statistical significance of the primary analysis. All models accounted for fixed-time covariates (age at baseline, sex, years of education, and years
smoked), time-varying covariates (diagnosis of hypertension, diabetes, and hypercholesterolemia; alcohol dependence; stroke; heart attack/cardiac arrest;
body mass index; Geriatric Depression Scale score; and hearing aid status [in Scenario 1]) and selection bias due to loss to follow-up.

10 of 12

BUCHOLC ET AL.

of incident MCI while hearing aid use robustly reduces progression to

was impacted by their hearing loss, there is a risk that hearing loss may

MCI. The exposure effect of hearing loss and the treatment effect of

have confounded cognition results for some participants. Moreover,hearing aids on incident MCI reported using the standard Cox model,

even though standard criteria and procedures were applied across all

persisted after adjusting for time-dependent and time-independent

ADRCs, there may be some differences in diagnostic definitions andfactors, and selection bias due to loss to follow-up in MSC model withvariability in recruitment strategies implemented by each ADRC.

IPW and after accounting for unmeasured confounding.

Finally, education level and income of ADRC cohort participants are

Our results are consistent with several observational studies thatlikely higher than the national average and they are predominantly

showed a significant association between hearing loss and accelerated

White. Participants who chose to use hearing aids may have differedcognitive decline.13–16 Although Heywood et al.28 reported that hear-from those who did not by factors including higher socioeconomic sta-

ing loss was not associated with significantly higher risk of develop-

tus and education. Therefore, compared to an RCT in which expo-

ing MCI, their model was not adjusted for hearing aid use. Given thatsure is randomly assigned, the characteristics of participants in ouruse of hearing aids may help mitigate cognitive decline, hearing aid

study were unbalanced between exposed and unexposed groups. To

usage should be incorporated as a confounding factor when analyzing

address the bias, due to non-randomized exposure allocation, poten-changes in cognitive function. Alternatively, the impact of hearing loss

tial confounding effects of both time-varying and baseline covariates

on cognition should be assessed by comparing participants with nor-and selection bias due to drop out, we implemented the IPW approachmal hearing and participants with hearing loss not using hearing aids.

to fit the MSC model. The IP weighting allowed us to assign expo-

As such, Amieva et al.15 found a significant difference in the rate ofsure/treatment independently of the counterfactual responses andchange in cognitive scores between hearing-impaired individuals notconditional on observed covariates and calculate statistics standard-using hearing aids and controls while indicating no difference in cogni-

ized to a pseudo-population in which the exposure was independent oftive decline between subjects with hearing loss using hearing aids andthe measured confounders. Although the implementation of the IPW-

controls.

adjusted MSC models accounted for a large set of measured covari-

The potential beneficial treatment effect of hearing aids on cogni-

ates, selected based on evidence from previous work, there is still ative decline observed in our study is consistent with conclusions of pre-chance that our study may include unmeasured confounding factors

vious work.19,21,42,43 In a prospective interventional study involving 34

that were unintentionally omitted from the analysis. These unmea-

elderly participants with hearing loss, cognitive function was signifi-

sured confounders could possibly bias causal inferences in our analysis.

cantly improved after 3 months of hearing aid use.42 Sarant et al.43

To account for the impact of potential unmeasured confounding bias on

showed that treatment of hearing loss led to improvements in cogni-

the associations, we performed the sensitivity analysis for unmeasured

tion and self-reported listening disability after 18 months of hearing

confounding. Given that our conclusions remained robust over a wide

aid use, with >97% of participants reporting significant improvements

range of plausible assumptions, thus reducing the number of interpre-in executive function. Hearing aid use was also associated with lower

tations of our findings, the causal nature of the observed associations

risk of incident dementia in individuals with MCI.19 The percentage ofis more defensible.

participants who had not developed dementia 5 years after the base-More research is needed to better understand the relationshipline MCI diagnosis was shown to be significantly higher for users (33%)

between hearing impairment and changes in cognitive ability and thethan non-users of hearing aids (19%).19

role of hearing rehabilitative strategies in mitigating these effects.

The interpretation of results of our study should be made in light

While waiting for further studies with more objective measurementof several limitations. First, the categorization of participants reliedof audiological deficits facts on the audiological side to complement

solely on self-reported measures of hearing loss and hearing aid use.

the cognitive data, the present study provides an important support

Although this may not be a limitation, as indicated in Oosterloo et al.,44

for links among hearing impairment, hearing aid use, and progression

discrepancies between self-reported hearing and audiometric assess-to MCI in cognitively healthy adults. Although causality remains to be

ment have been observed in other previous work.45 Further reported

determined, we carefully infer that increased access to quality hearing

difficulties with using self-report to estimate prevalence of hearing

health care might prove an effective preventive intervention to miti-

loss include people with similar hearing deficits reporting less dis-gate the impending dementia epidemic.

ability and handicap as their age increases.46 Due to unavailability of
data, we were unable to examine the impact of the degree of hearing

ACKNOWLEDGMENTS

impairment and measurement of how often hearing aids were used, orThis work was supported by the Dr George Moore Endowment forwhether they were appropriately fitted, on the observed associations.

Data Science at Ulster University (Magda Bucholc); European Union

In addition, given that hearing aid users wait an average of 7 to 10 years

INTERREG VA Program (Magda Bucholc, Paula L. McClean, Stephen

to seek help for hearing loss,47,48 some of the study participants that

Todd, Daman Kaur); Alzheimer’s Research UK (Magda Bucholc, Sarah

reported functionally normal hearing when using hearing aids might

Bauermeister); Dementias Platform UK supported by the Medical

have had limited awareness of what functionally normal hearing is by

Research Council MR/L023784/2 (Sarah Bauermeister). The NACC

the time they began to use hearing aids.

database is funded by NIA/NIH Grant U01 AG016976. NACC data

Although ADRC staff were trained and instructed to report on

are contributed by the NIA-funded ADRCs: P30 AG019610 (PI Eric

whether they felt participants’ ability to answer the CDR-SB questions

Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P50 AG008702

BUCHOLC ET AL.

(PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD),
P50 AG047266 (PI Todd Golde, MD, PhD), P30 AG010133 (PIAndrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD),
P50 AG005134 (PI Bradley Hyman, MD, PhD), P50 AG016574 (PIRonald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30
AG008051 (PI Thomas Wisniewski, MD), P30 AG013854 (PI Robert
Vassar, PhD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161(PI David Bennett, MD), P50 AG047366 (PI Victor Henderson, MD,
MS), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PIFrank LaFerla, PhD), P50 AG005131 (PI James Brewer, MD, PhD), P50
AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG053760 (PIHenry Paulson, MD, PhD), P30 AG010124 (PI John Trojanowski, MD,
PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena
Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P30 AG049638(PI Suzanne Craft, PhD), P50 AG005136 (PI Thomas Grabowski, MD),
P50 AG033514 (PI Sanjay Asthana, MD, FRCP), P50 AG005681 (PIJohn Morris, MD), P50 AG047270 (PI Stephen Strittmatter, MD, PhD).
CONFLICTS OF INTEREST
All authors declare that they have no competing interests.
AUTHOR CONTRIBUTIONS
Magda Bucholc, Paula L. McClean, Sarah Bauermeister, Stephen Todd
contributed to study design. Magda Bucholc did the data analysis
and data interpretation. Magda Bucholc drafted the manuscript. Sarah
Bauermeister, Daman Kaur, Paula L. McClean, and Stephen Todd critically reviewed the manuscript. All authors had full access to all the datain the study and had final responsibility for the decision to submit for
publication.
DATA AVAILABILITY STATEMENT
Data can be obtained through the National Alzheimer’s Coordinating
Center data request process (https://naccdata.org/requesting-data/
data-request-process).
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How to cite this article: Bucholc M, Bauermeister S, Kaur D,
McClean PL, Todd S. The impact of hearing impairment andhearing aid use on progression to mild cognitive impairment incognitively healthy adults: An observational cohort study.
Alzheimer’s Dement. 2022;8:e12248.
https://doi.org/10.1002/trc2.12248