Incident Hearing Loss and Comorbidity: A Longitudinal Administrative Claims Study

Jennifer A Deal; Nicholas S Reed; Alexander D Kravetz; Heather Weinreich; Charlotte Yeh; Frank R Lin; Aylin Altan

doi:10.1001/jamaoto.2018.2876

. 2018 Nov 8;145(1):36–43. doi: 10.1001/jamaoto.2018.2876

Incident Hearing Loss and Comorbidity

A Longitudinal Administrative Claims Study

Jennifer A Deal ^1,^2,^3,^✉, Nicholas S Reed ^2,³, Alexander D Kravetz ⁴, Heather Weinreich ⁵, Charlotte Yeh ⁶, Frank R Lin ^1,^2,³, Aylin Altan ⁴

¹Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

²Department of Otolaryngology–Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland

³Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

⁴OptumLabs, Cambridge, Massachusetts

⁵Department of Otolaryngology–Head and Neck Surgery, University of Illinois at Chicago, Chicago

⁶AARP Services, Inc, Washington, DC

Accepted for Publication: September 8, 2018.

^✉

Corresponding Author: Jennifer A. Deal, PhD, Johns Hopkins Bloomberg School of Public Health, 2024 E Monument St, Ste 2-700, Baltimore, MD 21205 (jdeal1@jhu.edu).

Published Online: November 8, 2018. doi:10.1001/jamaoto.2018.2876

Author Contributions: Dr Altan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Reed, Kravetz, Weinreich, Yeh, Lin, Altan.

Acquisition, analysis, or interpretation of data: Deal, Reed, Kravetz, Weinreich, Yeh, Altan.

Drafting of the manuscript: Deal, Kravetz, Altan.

Critical revision of the manuscript for important intellectual content: Deal, Reed, Weinreich, Yeh, Lin, Altan.

Statistical analysis: Deal, Kravetz, Altan.

Obtained funding: Deal.

Administrative, technical, or material support: Kravetz, Yeh, Lin, Altan.

Study Supervision: Yeh, Lin, Altan.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Reed reports Scientific Advisory Board Member (nonfinancial relationship) to Clearwater Clinical. Dr Yeh reports a vendor client association with Hear USA that provides hearing aids and hearing services to AARP members. Dr Lin reports grants from National Institutes of Health and grants from Eleanor Schwartz Charitable Foundation during the conduct of the study; personal fees from Cochlear Ltd, personal fees from Amplifon, and personal fees from Boehringer Ingelheim outside the submitted work. Dr Altan is an employee of OptumLabs. AARP is a research partner and founding consumer advocate in OptumLabs and as a partner they fund two full-time equivalents to work on various projects in health care policy for the aging. Dr Altan’s work on this project was a part of that full-time equivalent allotment. However, employment with OptumLabs was not dependent on that funding and the funding support work on multiple projects being conducted at OptumLabs. No other disclosures were reported.

Funding/Support: This work was supported by AARP and AARP Services, Inc. Dr Deal was supported by NIH/NIA grant K01AG054693. Dr Lin was supported by R01AG055426, R01HL096812, R33DC015062, and the Eleanor Schwartz Charitable Foundation. Drs Deal, Reed, and Reed were supported in part by the Cochlear Center for Hearing and Public Health.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: The authors thank Tanya Natwick, BA (OptumLabs), for her assistance in final preparation of the manuscript. Ms Natwick received no additional compensation beyond that of the regular course of her employment for her assistance with this article.

^✉

Corresponding author.

PMCID: PMC6439817 PMID: 30419134

Key Points

Question

What is the association between incident hearing loss diagnosis and medical comorbidities in US adults 50 years or older?

Findings

In this retrospective, propensity-matched cohort study using administrative claims data, hearing loss was significantly associated with an increased 10-year risk of dementia (3.2 per 100 persons), depression (3.6 per 100 persons), falls (6.9 per 100 persons), and myocardial infarction (1.1 per 100 persons).

Meaning

Incident hearing loss is independently related to the risk of other medical diagnoses; mechanisms underlying these associations should be elucidated to determine if hearing loss treatment can reduce risk and maintain health in adults with hearing loss.

This retrospective, propensity-matched cohort study assesses the association between hearing loss and medical comorbidities.

Abstract

Importance

Because hearing loss is highly prevalent and treatable, determining its association with morbidity has major public health implications for disease prevention and the maintenance of health in adults with hearing loss.

Objective

To investigate the association between the diagnosis of incident hearing loss and medical comorbidities in adults 50 years or older.

Design, Setting, and Participants

Retrospective, propensity-matched cohort study using administrative claims data from commercially insured and Medicare Advantage members in a geographically diverse US health plan. Adults 50 years or older with claims for services rendered from January 1, 2000, to December 31, 2016, were observed for 2 (n = 154 414), 5 (n = 44 852), and 10 (n = 4728) years. This research was conceptualized and data were analyzed between September 2016 and November 2017.

Exposures

A claim for incident hearing loss is defined as 2 claims for hearing loss within 2 consecutive years without evidence of hearing device use, excluding claims for sudden hearing loss or hearing loss secondary to medical conditions.

Main Outcomes and Measures

Incident claims for dementia, depression, accidental falls, nonvertebral fractures, acute myocardial infarction, and stroke.

Results

After cohort matching, 48% of participants were women (n = 74 464), 61% were white (n = 93 442), and 31% (n = 48 056) were Medicare Advantage insured, with a mean (SD) age of 64 (10) years. In a multivariate-adjusted modified Poisson regression with robust standard errors, relative associations were strongest for dementia (relative risk at 5 years, 1.50; 95% CI, 1.38-1.64) and depression (relative risk at 5 years, 1.41; 95% CI, 1.26-1.58). The absolute risk of all outcomes was greater in persons with hearing loss than in those without hearing loss at all times, with the greatest risk difference observed at 10 years for all outcomes. The 10-year risk attributable to hearing loss was 3.20 per 100 persons (95% CI, 1.76-4.63) for dementia, 3.57 per 100 persons (95% CI, 1.67-5.47) for falls, and 6.88 per 100 persons (95% CI, 4.62-9.14) for depression.

Conclusions and Relevance

In this large observational study using administrative claims data, incident untreated hearing loss was associated with greater incident morbidity than no hearing loss across a range of health conditions. Future studies are needed to elucidate the mechanisms underlying these associations and to determine if treatment for hearing loss could reduce the risk of comorbidity.

Introduction

Hearing health in adults in mid-to-late life is a national priority.¹ More than 50% of US adults 60 years or older have clinically meaningful hearing loss that affects everyday communication, with more than 73 million US adults expected to be affected by 2060.^2,3

In addition to its high prevalence, hearing loss is also linked to adverse health outcomes. The consistent association of hearing loss with accelerated cognitive decline and incident dementia has been increasingly recognized,⁴ and treatment of hearing loss in mid-to-late life could prevent 9% of dementia cases globally.⁵ Hearing loss is also independently related to disability,^6,7 falls,⁸ and depressive symptoms.⁹ However, the number of studies investigating these associations is limited, and the association between hearing loss and other diseases common in older age has been less well studied.¹⁰

Biological mechanisms of hearing loss have been proposed, particularly in the context of hearing loss and cognition, suggesting that the association between hearing loss and functional outcomes in older adults may be causal.¹¹ If this association is causal, because hearing loss is prevalent and treatable, understanding the association between hearing and morbidity has major public health implications for disease prevention and health promotion.

We used OptumLabs Data Warehouse (OLDW) insurance claims data from US adults (mean [SD] age, 64 [10] years, 48% of participants were women [n = 74 464], 61% were white [n = 93 442]) to test whether an incident hearing loss diagnosis without treatment was associated with new diagnoses for comorbidities related to cognition, geriatric syndromes (eg, falls, fractures), mental health, and cardiovascular and cerebrovascular health over 2 years (n = 154 414 participants), 5 years (n = 44 852 participants), or 10 years (n = 4728 participants) of follow-up.

Methods

Study Population and Observation Periods

The OLDW is a robust, longitudinally linked, database of deidentified individual-level data. Institutional review board approval and patient informed consent were not required because the deidentified data complies with the Health Insurance Portability and Accountability Act Privacy Rule. This retrospective, propensity-matched cohort study used administrative claims data from the OLDW to identify hearing-related products sold or health services rendered from January 1, 2000, to December 31, 2016. The OLDW includes deidentified claims data for over 125 million privately insured and Medicare Advantage enrollees in a large, private, US health plan from 1993 to the present, representing a diverse population with respect to age, race/ethnicity, and geographic region. The health plan provides comprehensive insurance coverage for physician, hospital, and prescription drug services, including Part D coverage for Medicare Advantage enrollees. The database includes socioeconomic information, including race/ethnicity, household income, and education, for about 73% of enrollees. This information is derived from a nationally recognized supplier of consumer marketing data and is a compilation of public data and derived predictive data. While proprietary, imputation methods for race/ethnicity have been shown in previous studies to have moderate sensitivity (48%), excellent specificity (97%), and moderate positive predictive value (71%) for the purpose of identifying race.¹²

The analytic sample was restricted to participants 50 years or older. Three nested samples were created based on data availability for 2-, 5-, and 10-year follow-up periods. For participants with a hearing loss diagnosis, the date of the first hearing loss claim was designated as the index date. For participants with no evidence of hearing loss, the index date was set to a random date of service within the capture window. Observation time was censored at disenrollment. To focus on untreated hearing loss, participants with a hearing loss diagnosis were censored at first evidence of a hearing device claim. Participants were retained in the analytic cohort only if they had continuous enrollment in their health plan for the full length of the follow-up. The resulting samples are nonmutually exclusive; for example, participants who qualified for the 10-year follow-up cohort also qualified for the 2- and 5-year cohorts.

Outcome Variables

Primary outcomes for this study included incident dementia, depression, nonvertebral fractures, accidental falls, acute myocardial infarction, and stroke. Conditions were defined as incident if the participant had no diagnosis (or procedure, if appropriate) code for the condition based on claims during the 12 months prior to the index date. Nonvertebral fractures were defined using International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) (and mapped ICD-10-CM equivalents) and Current Procedural Terminology codes previously used to define these fracture types in a similar database.¹³ Accidental falls were identified using external causes of injury codes (ie, E codes) from ICD-9-CM as well as the ICD-10-CM equivalents. New onset of dementia, depression, myocardial infarction, and stroke were identified using code sets and disease identification algorithms provided by the Centers for Medicare and Medicaid Services Chronic Conditions Data Warehouse.¹⁴ These coding algorithms are provided to researchers using administrative claims data and for the specification of data requests for disease-based cohorts. There are algorithms for 62 chronic or disabling conditions that specify diagnosis codes, site of service, and time span. For all conditions, diagnosis codes were allowed on the primary or any secondary position on the claim.

Hearing Loss Diagnosis

Hearing loss was determined by the presence of at least 2 claims separated by no more than 730 days with an ICD-9-CM diagnosis code for hearing loss (V41.2, 306.7, 388.01, 389, 389.1x [excluding 389.12, 389.14], 389.2x) in any position during the identification period of January 1, 2000, to December 31, 2014. The date of the first claim was designated as the index date. To ensure complete information, enrollees were required to have at least 12 months of continuous enrollment prior to the index date and at least 2 years of continuous enrollment after the index date. Participants were excluded if they had evidence of hearing loss before their index date, earliest evidence of hearing loss on an inpatient claim (indicating an acute issue), a hearing device at any time before their index date or within 2 years following their index date, or if they had evidence of receiving an ototoxic drug in the 12-month period before the index date. Because the exposure of interest is age-related hearing loss, participants were excluded if they had evidence of hearing loss secondary to correctable medical conditions (ie, via surgical measures) or hearing loss fundamentally different from typical peripheral age-related hearing loss (ie, central pathology), including sudden hearing loss (ICD-9-CM code, 388.2), hyperacusis (ICD-9-CM code, 388.42), acoustic nerve disorders (ICD-9-CM code, 388.5), otorrhea (ICD-9-CM code, 388.6x), otalgia (ICD-9-CM code, 388.7x), conductive hearing loss (ICD-9-CM code, 389.0x), neural hearing loss (ICD-9-CM code, 389.12), and/or central hearing loss (ICD-9-CM code, 389.14).

Statistical Analysis

Because of suspected underlying differences in participants with and without hearing loss, matched cohorts were created for each of the 3 follow-up periods using a 2-stage process. First, participants with uncorrected hearing loss were block-matched to persons with no evidence of hearing loss on the basis of follow-up time, insurance type (commercial or Medicare Advantage), and cost deciles. Subsequently, nearest-neighbor 1:1 caliper-based greedy propensity score matching without replacement was used, with the following variables measured during the 1 year prior to the index date included in the propensity model: age,² sex, census region, net worth, race/ethnicity, education level, health care utilization, Charlson Comorbidity Index,¹⁵ number of office visits (natural log transformed, both linear and quadratic terms), number of inpatient stays, inpatient length of stay, number of emergency department visits, dementia, mild cognitive impairment, depression, stoke, myocardial infarction, coronary artery disease, breast cancer, prostate cancer, renal cell carcinoma, colorectal cancer, and baseline medical costs (evidence of any costs and total medical costs). Block matching within cost deciles was required during the first stage owing to the skewed nature of cost, which can result in poorly matched cost distributions. Within each block, caliper matching was used to match cases to the closest control with a propensity score within 0.2 SDs. Participants not matched were excluded from analysis. The quality of the matched groups was assessed using absolute standardized differences. After matching, no variable exhibited an absolute standardized difference of more than 10%, indicating that persons with and without hearing loss were balanced on baseline variables as well as follow-up time (eFigure in the Supplement).

To describe baseline characteristics, categorical variables were reported as frequencies and percentages. Univariate comparisons were conducted according to the distribution of the data, using t tests, χ² tests, and Mann-Whitney U tests when appropriate. Statistical significance was assessed at the 2-sided 5% level.

Multivariable analysis was conducted on the matched cohorts to evaluate the risk of incident comorbid conditions associated with hearing loss. Relative risks (RRs) and risk differences with 95% CIs were modeled using a modified Poisson regression with robust standard errors.¹⁶ Analysis was limited to incident cases and adjusted for the following baseline variables: age, sex, race/ethnicity, census region, net worth, Charlson Comorbidity Index, coronary artery disease, medical costs (log transformed), number of inpatient stays, inpatient length of stay, number of emergency department visits, and number of office visits. Models for a given comorbidity were adjusted for other disease outcomes.

Analytic files were created using SAS software, version 9.4 (SAS Institute). Analyses were performed using R 3.3.2 (R Core Team, 2016), including R packages ggplot2, data.table, tableone, Rcpp, Zelig, attribrisk, lmtest, sandwich, modmarg, car, ggfortify, and survival; additional R code was custom created. Matching was done in C++ and R; the code is original and was written by author A.D.K.

Results

Postmatching, 48% of participants were women (n = 74 464), 61% were white (n = 93 442), 81% had completed some college or more (n = 124 749), and 31% were Medicare Advantage insured (n = 48 056), with a mean (SD) age of 64 (10) years in the 2-year cohort; results were similar in the 5- and 10-year cohorts (Table). At baseline, 3% of the participants in the 2-year cohort had ICD-9-CM codes for dementia (n = 4293), 3% had codes for stroke (n = 3916), 11% had codes for depression (n = 16 683 ), and fewer than 1% had codes for acute myocardial infarction (n = 625; Table). At baseline, 1% of participants in the 10-year cohort had ICD-9-CM codes for dementia (n = 32), 1% had codes for stroke (n = 65), and 8% had codes for depression (n = 393). Consistent with successful matching, no clinical differences in baseline covariates were observed between the incident hearing loss and the no hearing loss groups in all 3 cohorts (Table).

Table. Postmatching Participant Baseline Characteristics.

Demographics	Follow-up Cohort, No. (%)
	2-y		5-y		10-y
	Hearing Loss (n = 77 207)	No Hearing Loss (n = 77 207)	Hearing Loss (n = 22 426)	No Hearing Loss (n = 22 426)	Hearing Loss (n = 2364)	No Hearing Loss (n = 2364)
Age, mean (SD)	63.80 (9.74)	63.79 (9.70)	61.71 (9.22)	61.70 (9.20)	61.03 (9.30)	61.05 (9.28)
Female	37 309 (48.3)	37 155 (48.1)	10 792 (48.1)	10 671 (47.6)	1150 (48.6)	1130 (47.8)
Race
Asian	1707 (2.2)	1626 (2.1)	385 (1.7)	352 (1.6)	39 (1.6)	34 (1.4)
Black	4367 (5.7)	4420 (5.7)	1312 (5.9)	1373 (6.1)	144 (6.1)	162 (6.9)
Hispanic	3933 (5.1)	4039 (5.2)	1061 (4.7)	1050 (4.7)	89 (3.8)	95 (4.0)
White	46 772 (60.6)	46 670 (60.4)	13 386 (59.7)	13 262 (59.1)	1487 (62.9)	1431 (60.5)
Unknown	20 428 (26.5)	20 452 (26.5)	6282 (28.0)	6389 (28.5)	605 (25.6)	642 (27.2)
Education
<12th grade	231 (0.3)	219 (0.3)	39 (0.2)	37 (0.2)	Masked data^a	Masked data^a
High School diploma	14 647 (19.0)	14 568 (18.9)	3937 (17.6)	3890 (17.3)	380 (16.1)	386 (16.3)
<Bachelor’s degree	31 981 (41.4)	32 166 (41.7)	9139 (40.8)	9072 (40.5)	992 (42.0)	965 (40.8)
≥Bachelor’s degree	12 068 (15.6)	11 886 (15.4)	3621 (16.1)	3594 (16.0)	444 (18.8)	430 (18.2)
Unknown	18 280 (23.7)	18 368 (23.8)	5690 (25.4)	5833 (26.0)	<546	<585
Region
Midwest	21 896 (28.4)	21 951 (28.4)	6903 (30.8)	6796 (30.3)	861 (36.4)	830 (35.1)
Northeast	14 536 (18.8)	14 323 (18.6)	3966 (17.7)	3906 (17.4)	418 (17.7)	436 (18.4)
South	31 820 (41.2)	31 929 (41.4)	9205 (41.0)	9329 (41.6)	882 (37.3)	899 (38.0)
West	8955 (11.6)	9004 (11.7)	2352 (10.5)	2395 (10.7)	203 (8.6)	199 (8.4)
Net worth, $
<25 000	2771 (3.6)	2707 (3.5)	729 (3.3)	682 (3.0)	80 (3.4)	77 (3.3)
24 000-149 000	7610 (9.9)	747 (9.6)	2038 (9.1)	1998 (8.9)	206 (8.7)	185 (7.8)
150 000-249 000	7678 (9.9)	7815 (10.1)	2047 (9.1)	2043 (9.1)	195 (8.2)	193 (8.2)
250 000-499 000	16 404 (21.2)	16 564 (21.5)	4745 (21.2)	4738 (21.1)	558 (23.6)	560 (23.7)
≥500 000	19 870 (25.7)	19 723 (25.5)	5889 (26.3)	5828 (26.0)	652 (27.6)	631 (26.7)
Unknown	22 874 (29.6)	22 951 (29.7)	6978 (31.1)	7137 (31.8)	673 (28.5)	718 (30.4)
Medicare Advantage	24 028 (31.1)	24 028 (31.1)	6025 (26.9)	6025 (26.9)	755 (31.9)	755 (31.9)
Baseline health care utilization, mean (SD)
Inpatient stays	0.14 (0.47)	0.14 (0.43)	0.12 (0.42)	0.12 (0.39)	0.10 (0.34)	0.10 (0.33)
Total inpatient d	0.79 (4.94)	0.82 (4.30)	0.61 (3.31)	0.64 (3.22)	0.54 (2.49)	0.54 (2.36)
Outpatient encounters	18.73 (18.18)	18.63 (17.84)	17.17 (16.07)	17.13 (15.67)	15.55 (14.35)	14.91 (13.33)
Emergency department visits	0.32 (0.77)	0.32 (0.75)	0.27 (0.69)	0.27 (0.66)	0.24 (0.59)	0.22 (0.54)
Medical costs, $	8311.24 (20 645.18)	8479.90 (19 165.55)	7418.90 (17 586.02)	7536.63 (15 933.56)	6365.09 (14 413.20)	6272.95 (11 928.82)
Baseline comorbidities
Charlson Comorbidity Index, mean (SD)	1.12 (1.71)	1.12 (1.68)	0.89 (1.48)	0.90 (1.47)	0.69 (1.24)	0.68 (1.20)
Dementia	2104 (2.7)	2189 (2.8)	381 (1.7)	411 (1.8)	14 (0.6)	18 (0.8)
Mild cognitive impairment	107 (0.1)	113 (0.1)	Masked data^a	Masked data^a	Masked data^a	Masked data^a
Stroke	1963 (2.5)	1953 (2.5)	466 (2.1)	437 (1.9)	35 (1.5)	30 (1.3)
Depression	8358 (10.8)	8325 (10.8)	2147 (9.6)	2109 (9.4)	201 (8.5)	192 (8.1)
Acute myocardial infarction	324 (0.4)	301 (0.4)	87 (0.4)	76 (0.3)	13 (0.5)	14 (0.6)
Coronary artery disease	8744 (11.3)	8850 (11.5)	2119 (9.4)	2195 (9.8)	208 (8.8)	224 (9.5)

Open in a new tab

^{^a}

Sample size masked owing to small sample size.

In analysis adjusted for demographics, health care utilization, and comorbidities, hearing loss diagnosis (vs no evidence of hearing loss) was associated with a 20% to 50% increased risk of all outcomes, excluding fracture at 10 years (RR, 1.15; 95% CI, 0.90-1.48) and myocardial infarction at 5 years (RR, 1.05; 95% CI, 0.92-1.21). Associations were strongest for dementia (RR at 5 years, 1.50; 95% CI, 1.38-1.64) and depression (RR at 5 years, 1.41; 95% CI, 1.26-1.58; Figure 1).

Figure 1. — Adjusted for age, sex, race/ethnicity, census region, net worth, Charlson Comorbidity Index, coronary artery disease, medical costs (log transformed), number of inpatient stays, inpatient length of stay, number of emergency department visits and number of office visits. Models for a given comorbid outcome were also adjusted for other disease outcomes; for example, models estimating the association between hearing loss and dementia were also adjusted for depression, acute myocardial infarction, and stroke. RR indicates relative risk.

The estimate of the absolute risk for all outcomes was statistically significantly greater in persons with hearing loss than in those without hearing loss for all follow-up cohorts, excluding myocardial infarction at 5 years (0.09 per 100 persons; 95% CI, −0.15 to 0.34), and fracture at 10 years (0.66 per 100 persons; 95% CI, −0.52 to 1.84) (Figure 2 and eTable in the Supplement). Compared with the 2-year and 5-year follow-up periods, the greatest risk difference was estimated at 10 years for all outcomes. The 10-year risk attributable to hearing loss was 3.20 per 100 persons (95% CI, 1.76-4.63) for dementia, 6.88 per 100 persons (95% CI, 4.62-9.14) for depression, 3.57 per 100 persons (95% CI, 1.67-5.47) for falls, 1.05 per 100 persons (95% CI, 0.04-2.07) for myocardial infarction, and 2.69 per 100 persons (95% CI, 1.03-4.35) for stroke (Figure 2).

Figure 2. — Adjusted for age, sex, race/ethnicity, census region, net worth, Charlson Comorbidity Index, coronary artery disease, medical costs (log transformed), number of inpatient stays, inpatient length of stay, number of emergency department visits, and number of office visits. Models for a given comorbid outcome were also adjusted for other disease outcomes; for example, models estimating the association between hearing loss and dementia were also adjusted for depression, acute myocardial infarction, and stroke.

Discussion

In this large observational study using administrative claims data with up to 10 years of follow-up, incident hearing loss (vs no evidence of hearing loss) was independently associated with greater incident morbidity across a range of health conditions in adults 50 years or older. The greatest relative increase in risk was estimated for dementia and depression, with hearing loss associated with an approximately 50% increase in both conditions over 5 years. The absolute risk of comorbid conditions associated with hearing loss increased with longer follow-up time, with the greatest risk estimated for depression followed by falls and dementia in the cohort observed for 10 years.

It is perhaps not surprising that the greatest RRs were estimated for those in the 5-year cohort, but the greatest risk differences were in the 10-year cohort. Although the strength of a risk factor–outcome association may diminish over the course of life, the absolute risk associated with that risk factor may still increase with advancing age.¹⁷ In contrast to relative measures of association, which give insight into etiologic associations, absolute measures have relevance for public health planning because they are interpreted as the risk of morbidity in persons with hearing loss that could be prevented with hearing loss treatment or prevention, although this interpretation assumes a causal association.

Our results are consistent with a growing body of literature linking hearing loss to adverse health outcomes in older adults. Recent meta-analyses have reported that hearing loss is associated with a 2-fold increase in risk for dementia^5,18 and cognitive impairment¹⁹ and a 70% to 80% increase in the risk of falls.⁸ Clinically, hearing loss is recognized as contributing to poorer quality of life²⁰ and depression,²¹ and hearing loss treatment may result in an improvement in self-reported depressive symptoms.²² Few studies have investigated hearing loss as a possible risk factor for other comorbid conditions.²³ Using data from the National Health Interview Survey, McKee and colleagues¹⁰ found that hearing loss was cross-sectionally associated with several medical conditions after adjustment for demographic and clinical covariates, including a 39% increase in the prevalence of stroke. Our study adds to the literature with its large sample size and up to 10 years of longitudinal follow-up.

Causal mechanistic pathways have been hypothesized to underlie the estimated associations. For dementia in particular, possible mechanisms could include the influence of distorted peripheral encoding of sound on cognitive load and changes in brain structure and/or function.¹¹ Reduced awareness of the auditory environment could potentially increase the risk of falls.²⁴ Additionally, hearing loss could be related to frailty²⁵ or lead to reduced social engagement, which in turn could increase the risk for disease.^11,26,27 Alternatively, the observed associations could be the result of underlying processes or factors that are related both to hearing loss and to the adverse outcomes (eg, microvascular disease, inflammation).^11,28 In this study, hearing loss was associated with increased risk of both myocardial infarction and stroke, although the magnitude of the risk estimated for these outcomes was less than that for dementia and depression. These results could be indicative of a common cause leading to both hearing loss and all outcomes that have vascular contributors, including dementia. In support of this hypothesis, vascular factors and markers, including hypertension,^29,30 elevated glycosylated hemoglobin levels,³¹ obesity,^31,32,33 and subclinical atherosclerosis,³⁴ have been shown to be related to a small increase in risk of hearing impairment. Hearing loss also could increase the risk of vascular outcomes through the causal mechanisms previously described, particularly increased social isolation. Increased social isolation is consistently related to all-cause mortality and cardiovascular disease in observational studies.^35,36

Importantly, the possible mechanisms relating hearing loss to comorbid outcomes are not mutually exclusive. Estimates from observational studies with inadequate adjustment for vascular markers that are unmeasured or measured with error could represent both a true causal effect as well as the confounding effect of underlying vascular disease. Although a strength of our study is the use of propensity score matching to adjust for confounding, variables included in that matching were limited to those covariates that were available, and this study relies on administrative claims diagnosis codes that are generated for the purpose of billing and payment, not for research. As an observational study, it is likely that unmeasured and residual confounding exists, highlighting the need for experimental studies of the influence of hearing loss treatment on these outcomes.

Limitations

While it provides large sample sizes and longitudinal patient histories, the use of claims data for research can present challenges.³⁷ There are limitations to the ability to identify all cases of conditions, such as hearing loss, that do not necessarily drive reimbursement. Although we attempted to maximize specificity with our definition of uncorrected hearing loss, it is likely that hearing loss is not fully captured in the claims data, particularly mild hearing loss, or that it is documented in claims only when it is severe enough to require treatment or if a patient’s health plan covers services. However, the inclusion of persons with hearing loss in our unexposed group would result in a conservative estimate of the association between hearing loss and comorbidities. It is also possible that our findings could be the result of a detection bias, in which participants who seek diagnosis for hearing loss may have a more frequent interaction with the health care system, and therefore are more likely to have claims for comorbidities. Replication of these findings in population-based studies will be important to help address this potential bias. Although our data are from a large, geographically diverse database, the study population is mostly white and wealthier than the general US population; this lack of representativeness could affect the generalizability of our findings if the factors by which our study population differs from the general population modify the association between hearing loss and comorbid conditions. If the association between hearing loss and dementia, for example, is stronger in persons of lower socioeconomic status or in those who are not white, then our results would underestimate that association and our findings are not generalizable. Additionally, accurate mortality information is not available in the data source used for this project, and so we were unable to take the competing risk of death into account into our analyses. Because absolute risk of an outcome over time is dependent on the survival function both for the outcome and for death, failure to account for competing risks may lead to biased estimates of the cumulative incidence.³⁸

In our study, individual hearing loss morbidity analyses were adjusted for all other conditions to estimate the association between hearing loss and a specific condition independent of other comorbidities. For example, the estimated association between hearing loss and dementia was adjusted for depression. However, we documented that hearing loss is strongly related to depression in this cohort, and depression is a known risk factor for dementia.⁵ If hearing loss leads to depression, and depression in turn leads to dementia (ie, depression is a mediator of the association between hearing loss and dementia), then adjustment for depression may have attenuated the estimated association between hearing loss and dementia in our study. However, even after this conservative adjustment, we documented an excess of 3 dementia diagnoses attributable to hearing loss per 100 persons over 10 years.

Conclusions

In this large observational study using administrative claims data, we found that incident hearing loss diagnosis (vs no evidence of hearing loss) was independently associated with greater incident morbidity across a range of health conditions, including dementia, depression, falls, and cardiovascular disease. Future studies are needed to elucidate the mechanisms underlying these associations and to determine if hearing loss treatment could reduce risk and maintain health in middle-aged and older adults.

Supplement.

eFigure. Absolute Standard Difference (ASD) Plots for Years 2, 5, and 10

eTable. Crude Absolute Risk per 100 Patients of Incident Comorbid Conditions in Persons with Incident Hearing Loss Diagnosis and with No Evidence of Hearing Loss and, by Follow-up Cohort (2, 5, or 10 Years)

Click here for additional data file.^{(195.1KB, pdf)}

References

1.National Academies of Sciences, Engineering, and Medicine Hearing Health Care for Adults: Priorities for Improving Access and Affordability. Washington, DC: The National Academies Press; 2016. [PubMed] [Google Scholar]
2.Lin FR, Niparko JK, Ferrucci L. Hearing loss prevalence in the United States. Arch Intern Med. 2011;171(20):1851-1852. doi: 10.1001/archinternmed.2011.506 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Goman AM, Lin FR. Prevalence of hearing loss by severity in the United States. Am J Public Health. 2016;106(10):1820-1822. doi: 10.2105/AJPH.2016.303299 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Loughrey DG, Kelly ME, Kelley GA, Brennan S, Lawlor BA. Association of age-related hearing loss with cognitive function, cognitive impairment, and dementia: a systematic review and meta-analysis. JAMA Otolaryngol Head Neck Surg. 2018;144(2):115-126. [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Livingston G, Sommerlad A, Orgeta V, et al. Dementia prevention, intervention, and care. Lancet. 2017;390(10113):2673-2734. doi: 10.1016/S0140-6736(17)31363-6 [DOI] [PubMed] [Google Scholar]
6.Chen DS, Betz J, Yaffe K, et al. ; Health ABC study . Association of hearing impairment with declines in physical functioning and the risk of disability in older adults. J Gerontol A Biol Sci Med Sci. 2015;70(5):654-661. doi: 10.1093/gerona/glu207 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Mikkola TM, Polku H, Portegijs E, Rantakokko M, Rantanen T, Viljanen A. Self-reported hearing status is associated with lower limb physical performance, perceived mobility, and activities of daily living in older community-dwelling men and women. J Am Geriatr Soc. 2015;63(6):1164-1169. doi: 10.1111/jgs.13381 [DOI] [PubMed] [Google Scholar]
8.Jiam NT, Li C, Agrawal Y. Hearing loss and falls: a systematic review and meta-analysis. Laryngoscope. 2016;126(11):2587-2596. doi: 10.1002/lary.25927 [DOI] [PubMed] [Google Scholar]
9.Mener DJ, Betz J, Genther DJ, Chen D, Lin FR. Hearing loss and depression in older adults. J Am Geriatr Soc. 2013;61(9):1627-1629. doi: 10.1111/jgs.12429 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.McKee MM, Stransky ML, Reichard A. Hearing loss and associated medical conditions among individuals 65 years and older. Disabil Health J. 2018;11(1):122-125. doi: 10.1016/j.dhjo.2017.05.007 [DOI] [PubMed] [Google Scholar]
11.Lin FR, Albert M. Hearing loss and dementia - who is listening? Aging Ment Health. 2014;18(6):671-673. doi: 10.1080/13607863.2014.915924 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.DeFrank JT, Bowling JM, Rimer BK, Gierisch JM, Skinner CS. Triangulating differential nonresponse by race in a telephone survey. Prev Chronic Dis. 2007;4(3):A60. [PMC free article] [PubMed] [Google Scholar]
13.Ray WA, Griffin MR, Fought RL, Adams ML. Identification of fractures from computerized Medicare files. J Clin Epidemiol. 1992;45(7):703-714. doi: 10.1016/0895-4356(92)90047-Q [DOI] [PubMed] [Google Scholar]
14.Centers for Medicare & Medicaid Services Chronic conditions data warehouse conditions categories. https://www.ccwdata.org/web/guest/condition-categories. Accessed April, 2018.
15.Quan H, Li B, Couris CM, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173(6):676-682. doi: 10.1093/aje/kwq433 [DOI] [PubMed] [Google Scholar]
16.Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702-706. doi: 10.1093/aje/kwh090 [DOI] [PubMed] [Google Scholar]
17.Kaplan GA, Haan MN, Wallace RB. Understanding changing risk factor associations with increasing age in adults. Annu Rev Public Health. 1999;20:89-108. doi: 10.1146/annurev.publhealth.20.1.89 [DOI] [PubMed] [Google Scholar]
18.Thomson RS, Auduong P, Miller AT, Gurgel RK. Hearing loss as a risk factor for dementia: a systematic review. Laryngoscope Investig Otolaryngol. 2017;2(2):69-79. doi: 10.1002/lio2.65 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Zheng Y, Fan S, Liao W, Fang W, Xiao S, Liu J. Hearing impairment and risk of Alzheimer’s disease: a meta-analysis of prospective cohort studies. Neurol Sci. 2017;38(2):233-239. doi: 10.1007/s10072-016-2779-3 [DOI] [PubMed] [Google Scholar]
20.Tseng YC, Liu SH, Lou MF, Huang GS. Quality of life in older adults with sensory impairments: a systematic review. Qual Life Res. 2018;27(8):1957-1971. doi: 10.1007/s11136-018-1799-2 [DOI] [PubMed] [Google Scholar]
21.Hsu WT, Hsu CC, Wen MH, et al. Increased risk of depression in patients with acquired sensory hearing loss: a 12-year follow-up study. Medicine (Baltimore). 2016;95(44):e5312. doi: 10.1097/MD.0000000000005312 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Mulrow CD, Aguilar C, Endicott JE, et al. Quality-of-life changes and hearing impairment. a randomized trial. Ann Intern Med. 1990;113(3):188-194. doi: 10.7326/0003-4819-113-3-188 [DOI] [PubMed] [Google Scholar]
23.Stam M, Kostense PJ, Lemke U, et al. Comorbidity in adults with hearing difficulties: which chronic medical conditions are related to hearing impairment? Int J Audiol. 2014;53(6):392-401. doi: 10.3109/14992027.2013.879340 [DOI] [PubMed] [Google Scholar]
24.Rumalla K, Karim AM, Hullar TE. The effect of hearing aids on postural stability. Laryngoscope. 2015;125(3):720-723. doi: 10.1002/lary.24974 [DOI] [PubMed] [Google Scholar]
25.Panza F, Solfrizzi V, Logroscino G. Age-related hearing impairment-a risk factor and frailty marker for dementia and AD. Nat Rev Neurol. 2015;11(3):166-175. doi: 10.1038/nrneurol.2015.12 [DOI] [PubMed] [Google Scholar]
26.Berkman LF, Glass T, Brissette I, Seeman TE. From social integration to health: Durkheim in the new millennium. Soc Sci Med. 2000;51(6):843-857. doi: 10.1016/S0277-9536(00)00065-4 [DOI] [PubMed] [Google Scholar]
27.Cacioppo S, Capitanio JP, Cacioppo JT. Toward a neurology of loneliness. Psychol Bull. 2014;140(6):1464-1504. doi: 10.1037/a0037618 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Shen Y, Ye B, Chen P, et al. Cognitive decline, dementia, Alzheimer’s disease and presbycusis: examination of the possible molecular mechanism. Front Neurosci. 2018;12:394. doi: 10.3389/fnins.2018.00394 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Lin BM, Curhan SG, Wang M, Eavey R, Stankovic KM, Curhan GC. Hypertension, diuretic use, and risk of hearing loss. Am J Med. 2016;129(4):416-422. doi: 10.1016/j.amjmed.2015.11.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Brant LJ, Gordon-Salant S, Pearson JD, et al. Risk factors related to age-associated hearing loss in the speech frequencies. J Am Acad Audiol. 1996;7(3):152-160. [PubMed] [Google Scholar]
31.Cruickshanks KJ, Nondahl DM, Dalton DS, et al. Smoking, central adiposity, and poor glycemic control increase risk of hearing impairment. J Am Geriatr Soc. 2015;63(5):918-924. doi: 10.1111/jgs.13401 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Curhan SG, Eavey R, Wang M, Stampfer MJ, Curhan GC. Body mass index, waist circumference, physical activity, and risk of hearing loss in women. Am J Med. 2013;126(12):1142.e1-1142.e8. doi: 10.1016/j.amjmed.2013.04.026 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Linssen AM, van Boxtel MP, Joore MA, Anteunis LJ. Predictors of hearing acuity: cross-sectional and longitudinal analysis. J Gerontol A Biol Sci Med Sci. 2014;69(6):759-765. doi: 10.1093/gerona/glt172 [DOI] [PubMed] [Google Scholar]
34.Fischer ME, Schubert CR, Nondahl DM, et al. Subclinical atherosclerosis and increased risk of hearing impairment. Atherosclerosis. 2015;238(2):344-349. doi: 10.1016/j.atherosclerosis.2014.12.031 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Leigh-Hunt N, Bagguley D, Bash K, et al. An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health. 2017;152:157-171. doi: 10.1016/j.puhe.2017.07.035 [DOI] [PubMed] [Google Scholar]
36.Hakulinen C, Pulkki-Råback L, Virtanen M, Jokela M, Kivimäki M, Elovainio M. Social isolation and loneliness as risk factors for myocardial infarction, stroke and mortality: UK biobank cohort study of 479 054 men and women. Heart. 2018;104(18):1536-1542. doi: 10.1136/heartjnl-2017-312663 [DOI] [PubMed] [Google Scholar]
37.Tyree PT, Lind BK, Lafferty WE. Challenges of using medical insurance claims data for utilization analysis. Am J Med Qual. 2006;21(4):269-275. doi: 10.1177/1062860606288774 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Berry SD, Ngo L, Samelson EJ, Kiel DP. Competing risk of death: an important consideration in studies of older adults. J Am Geriatr Soc. 2010;58(4):783-787. doi: 10.1111/j.1532-5415.2010.02767.x [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eFigure. Absolute Standard Difference (ASD) Plots for Years 2, 5, and 10

Click here for additional data file.^{(195.1KB, pdf)}

[ooi180088r1] 1.National Academies of Sciences, Engineering, and Medicine Hearing Health Care for Adults: Priorities for Improving Access and Affordability. Washington, DC: The National Academies Press; 2016. [PubMed] [Google Scholar]

[ooi180088r2] 2.Lin FR, Niparko JK, Ferrucci L. Hearing loss prevalence in the United States. Arch Intern Med. 2011;171(20):1851-1852. doi: 10.1001/archinternmed.2011.506 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r3] 3.Goman AM, Lin FR. Prevalence of hearing loss by severity in the United States. Am J Public Health. 2016;106(10):1820-1822. doi: 10.2105/AJPH.2016.303299 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r4] 4.Loughrey DG, Kelly ME, Kelley GA, Brennan S, Lawlor BA. Association of age-related hearing loss with cognitive function, cognitive impairment, and dementia: a systematic review and meta-analysis. JAMA Otolaryngol Head Neck Surg. 2018;144(2):115-126. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r5] 5.Livingston G, Sommerlad A, Orgeta V, et al. Dementia prevention, intervention, and care. Lancet. 2017;390(10113):2673-2734. doi: 10.1016/S0140-6736(17)31363-6 [DOI] [PubMed] [Google Scholar]

[ooi180088r6] 6.Chen DS, Betz J, Yaffe K, et al. ; Health ABC study . Association of hearing impairment with declines in physical functioning and the risk of disability in older adults. J Gerontol A Biol Sci Med Sci. 2015;70(5):654-661. doi: 10.1093/gerona/glu207 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r7] 7.Mikkola TM, Polku H, Portegijs E, Rantakokko M, Rantanen T, Viljanen A. Self-reported hearing status is associated with lower limb physical performance, perceived mobility, and activities of daily living in older community-dwelling men and women. J Am Geriatr Soc. 2015;63(6):1164-1169. doi: 10.1111/jgs.13381 [DOI] [PubMed] [Google Scholar]

[ooi180088r8] 8.Jiam NT, Li C, Agrawal Y. Hearing loss and falls: a systematic review and meta-analysis. Laryngoscope. 2016;126(11):2587-2596. doi: 10.1002/lary.25927 [DOI] [PubMed] [Google Scholar]

[ooi180088r9] 9.Mener DJ, Betz J, Genther DJ, Chen D, Lin FR. Hearing loss and depression in older adults. J Am Geriatr Soc. 2013;61(9):1627-1629. doi: 10.1111/jgs.12429 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r10] 10.McKee MM, Stransky ML, Reichard A. Hearing loss and associated medical conditions among individuals 65 years and older. Disabil Health J. 2018;11(1):122-125. doi: 10.1016/j.dhjo.2017.05.007 [DOI] [PubMed] [Google Scholar]

[ooi180088r11] 11.Lin FR, Albert M. Hearing loss and dementia - who is listening? Aging Ment Health. 2014;18(6):671-673. doi: 10.1080/13607863.2014.915924 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r12] 12.DeFrank JT, Bowling JM, Rimer BK, Gierisch JM, Skinner CS. Triangulating differential nonresponse by race in a telephone survey. Prev Chronic Dis. 2007;4(3):A60. [PMC free article] [PubMed] [Google Scholar]

[ooi180088r13] 13.Ray WA, Griffin MR, Fought RL, Adams ML. Identification of fractures from computerized Medicare files. J Clin Epidemiol. 1992;45(7):703-714. doi: 10.1016/0895-4356(92)90047-Q [DOI] [PubMed] [Google Scholar]

[ooi180088r14] 14.Centers for Medicare & Medicaid Services Chronic conditions data warehouse conditions categories. https://www.ccwdata.org/web/guest/condition-categories. Accessed April, 2018.

[ooi180088r15] 15.Quan H, Li B, Couris CM, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173(6):676-682. doi: 10.1093/aje/kwq433 [DOI] [PubMed] [Google Scholar]

[ooi180088r16] 16.Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702-706. doi: 10.1093/aje/kwh090 [DOI] [PubMed] [Google Scholar]

[ooi180088r17] 17.Kaplan GA, Haan MN, Wallace RB. Understanding changing risk factor associations with increasing age in adults. Annu Rev Public Health. 1999;20:89-108. doi: 10.1146/annurev.publhealth.20.1.89 [DOI] [PubMed] [Google Scholar]

[ooi180088r18] 18.Thomson RS, Auduong P, Miller AT, Gurgel RK. Hearing loss as a risk factor for dementia: a systematic review. Laryngoscope Investig Otolaryngol. 2017;2(2):69-79. doi: 10.1002/lio2.65 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r19] 19.Zheng Y, Fan S, Liao W, Fang W, Xiao S, Liu J. Hearing impairment and risk of Alzheimer’s disease: a meta-analysis of prospective cohort studies. Neurol Sci. 2017;38(2):233-239. doi: 10.1007/s10072-016-2779-3 [DOI] [PubMed] [Google Scholar]

[ooi180088r20] 20.Tseng YC, Liu SH, Lou MF, Huang GS. Quality of life in older adults with sensory impairments: a systematic review. Qual Life Res. 2018;27(8):1957-1971. doi: 10.1007/s11136-018-1799-2 [DOI] [PubMed] [Google Scholar]

[ooi180088r21] 21.Hsu WT, Hsu CC, Wen MH, et al. Increased risk of depression in patients with acquired sensory hearing loss: a 12-year follow-up study. Medicine (Baltimore). 2016;95(44):e5312. doi: 10.1097/MD.0000000000005312 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r22] 22.Mulrow CD, Aguilar C, Endicott JE, et al. Quality-of-life changes and hearing impairment. a randomized trial. Ann Intern Med. 1990;113(3):188-194. doi: 10.7326/0003-4819-113-3-188 [DOI] [PubMed] [Google Scholar]

[ooi180088r23] 23.Stam M, Kostense PJ, Lemke U, et al. Comorbidity in adults with hearing difficulties: which chronic medical conditions are related to hearing impairment? Int J Audiol. 2014;53(6):392-401. doi: 10.3109/14992027.2013.879340 [DOI] [PubMed] [Google Scholar]

[ooi180088r24] 24.Rumalla K, Karim AM, Hullar TE. The effect of hearing aids on postural stability. Laryngoscope. 2015;125(3):720-723. doi: 10.1002/lary.24974 [DOI] [PubMed] [Google Scholar]

[ooi180088r25] 25.Panza F, Solfrizzi V, Logroscino G. Age-related hearing impairment-a risk factor and frailty marker for dementia and AD. Nat Rev Neurol. 2015;11(3):166-175. doi: 10.1038/nrneurol.2015.12 [DOI] [PubMed] [Google Scholar]

[ooi180088r26] 26.Berkman LF, Glass T, Brissette I, Seeman TE. From social integration to health: Durkheim in the new millennium. Soc Sci Med. 2000;51(6):843-857. doi: 10.1016/S0277-9536(00)00065-4 [DOI] [PubMed] [Google Scholar]

[ooi180088r27] 27.Cacioppo S, Capitanio JP, Cacioppo JT. Toward a neurology of loneliness. Psychol Bull. 2014;140(6):1464-1504. doi: 10.1037/a0037618 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r28] 28.Shen Y, Ye B, Chen P, et al. Cognitive decline, dementia, Alzheimer’s disease and presbycusis: examination of the possible molecular mechanism. Front Neurosci. 2018;12:394. doi: 10.3389/fnins.2018.00394 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r29] 29.Lin BM, Curhan SG, Wang M, Eavey R, Stankovic KM, Curhan GC. Hypertension, diuretic use, and risk of hearing loss. Am J Med. 2016;129(4):416-422. doi: 10.1016/j.amjmed.2015.11.014 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r30] 30.Brant LJ, Gordon-Salant S, Pearson JD, et al. Risk factors related to age-associated hearing loss in the speech frequencies. J Am Acad Audiol. 1996;7(3):152-160. [PubMed] [Google Scholar]

[ooi180088r31] 31.Cruickshanks KJ, Nondahl DM, Dalton DS, et al. Smoking, central adiposity, and poor glycemic control increase risk of hearing impairment. J Am Geriatr Soc. 2015;63(5):918-924. doi: 10.1111/jgs.13401 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r32] 32.Curhan SG, Eavey R, Wang M, Stampfer MJ, Curhan GC. Body mass index, waist circumference, physical activity, and risk of hearing loss in women. Am J Med. 2013;126(12):1142.e1-1142.e8. doi: 10.1016/j.amjmed.2013.04.026 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r33] 33.Linssen AM, van Boxtel MP, Joore MA, Anteunis LJ. Predictors of hearing acuity: cross-sectional and longitudinal analysis. J Gerontol A Biol Sci Med Sci. 2014;69(6):759-765. doi: 10.1093/gerona/glt172 [DOI] [PubMed] [Google Scholar]

[ooi180088r34] 34.Fischer ME, Schubert CR, Nondahl DM, et al. Subclinical atherosclerosis and increased risk of hearing impairment. Atherosclerosis. 2015;238(2):344-349. doi: 10.1016/j.atherosclerosis.2014.12.031 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r35] 35.Leigh-Hunt N, Bagguley D, Bash K, et al. An overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health. 2017;152:157-171. doi: 10.1016/j.puhe.2017.07.035 [DOI] [PubMed] [Google Scholar]

[ooi180088r36] 36.Hakulinen C, Pulkki-Råback L, Virtanen M, Jokela M, Kivimäki M, Elovainio M. Social isolation and loneliness as risk factors for myocardial infarction, stroke and mortality: UK biobank cohort study of 479 054 men and women. Heart. 2018;104(18):1536-1542. doi: 10.1136/heartjnl-2017-312663 [DOI] [PubMed] [Google Scholar]

[ooi180088r37] 37.Tyree PT, Lind BK, Lafferty WE. Challenges of using medical insurance claims data for utilization analysis. Am J Med Qual. 2006;21(4):269-275. doi: 10.1177/1062860606288774 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ooi180088r38] 38.Berry SD, Ngo L, Samelson EJ, Kiel DP. Competing risk of death: an important consideration in studies of older adults. J Am Geriatr Soc. 2010;58(4):783-787. doi: 10.1111/j.1532-5415.2010.02767.x [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Incident Hearing Loss and Comorbidity

Jennifer A Deal, PhD

Nicholas S Reed, AuD

Alexander D Kravetz, PharmD

Heather Weinreich, MD, MPH

Charlotte Yeh, MD

Frank R Lin, MD, PhD

Aylin Altan, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Population and Observation Periods

Outcome Variables

Hearing Loss Diagnosis

Statistical Analysis

Results

Table. Postmatching Participant Baseline Characteristics.

Figure 1. Multivariable-Adjusted Relative Risks and 95% CIs of the Association Between Incident Untreated Hearing Loss Diagnosis and Incident Comorbid Conditions.

Figure 2. Multivariable-Adjusted Risk Differences per 100 Patients and 95% CIs of the Association Between Incident Untreated Hearing Loss Diagnosis and Incident Comorbid Conditions.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases