Abstract
Background
We examined the associations between dual impairments in visual and hearing acuity and aging-related cognitive decline.
Methods
This was a longitudinal study of adults who had visual and hearing acuity and cognitive function assessed in 1992–1996 and were followed for up to 24 years (mean = 7.3 years), with up to five additional cognitive assessments. Visual impairment was defined as vision worse than 20/40, hearing impairment as pure-tone average thresholds >25 dB. Associations were tested using linear mixed-effects regressions.
Results
Of 1,383 participants, 293 had visual impairment, 990 had a hearing impairment and 251 had both deficits. In fully adjusted models, low visual acuity was associated with poorer Mini-Mental State Examination (MMSE; β = −0.29) and Trail-Making Test Part B (Trails B; β = 13.22) performance, and with faster declines in MMSE (β = −0.12) and Trails B (β = 1.84). The combination of low visual and low hearing acuity was associated with poorer MMSE (β = −0.44) and Trails B (β = 11.20) scores, and with faster declines in MMSE (β = −0.19), Trails B (β = 3.50), and Verbal Fluency Test (VFT; β = −0.14) performance. Associations were similar in men and women.
Conclusion
Impairments in both vision and hearing are associated with a more rapid decline in cognitive function with aging.
Keywords: vision; hearing; sensory impairments; cognitive aging, older people
Key points
Impairments in vision and hearing have been independently associated with cognitive decline.
Few studies have examined dual sensory impairments in association with cognitive decline, with mixed results.
In this study, individuals with low visual and hearing acuity performed poorly on cognitive tests.
Individuals with dual sensory impairments had faster rates of cognitive decline than those with normal hearing and vision.
Introduction
Visual impairment affects more than 12 million adults over the age of 40 in the USA, including one million who are blind, three million who have vision impairment after correction and eight million who have vision impairment due to uncorrected refractive error [1]. Eye diseases that impact vision become more prevalent with increasing age [2], as do impairments in visual acuity [3]. Age is also the strongest predictor of hearing loss; one-third of adults aged 65–74 have hearing loss and nearly half of those older than 75 have difficulty hearing [4,5].
Impairments in vision and hearing have been independently associated with cognitive decline, and with the risk of mild cognitive impairment or dementia [6–8], though not in all studies [9–11]. In the Rancho Bernardo Study of Healthy Aging (RBS), on which this study is based, even mild hearing impairment was associated with greater age-related cognitive decline [12]. Few studies, however, have considered the impacts of dual sensory impairment including concurrent vision and hearing loss on cognition [9,11], and to our knowledge, no studies have examined sex differences in dual sensory impairment and cognitive function.
The purpose of this study was to examine the associations of visual acuity alone and dual impairments in visual and hearing acuity with longitudinal cognitive test performance, overall and by sex, among a well-characterised cohort of community-dwelling older adults. In our prior study [12], we found that increasing degree of hearing impairment was associated with the increasing cognitive decline with age. Here, we hypothesised that lower visual acuity would also be associated with cognitive decline and that age-related cognitive decline would be strongest among adults with impairments in both modalities.
Methods
Study population
The RBS is a community-based prospective cohort study established in 1972–1974 when 82% of adult residents of Rancho Bernardo (San Diego, CA) were enrolled. Participants were predominantly white and middle to upper-middle class; more than half had attended college [13]. In 1992–1996, 1,781 adults participated in a clinic visit in which cognitive function and visual and hearing acuity were assessed. Of these, 73 were excluded for missing cognitive data, 292 for missing visual acuity data, and 33 for missing hearing acuity data resulting in a final analytic sample of 1,383. This study was approved by the San Diego State University Institutional Review Board. All participants provided written informed consent prior to participation at each visit.
Cognitive assessment
Cognitive function was assessed in 1992–1996 and about every 4 years thereafter using a battery of standardised neuropsychological tests. The last cognitive assessment occurred in 2014–2016, providing up to six assessments over the 24 year follow-up period (mean follow-up for this sample was 7.3 (SD = 6.4) years). The survey included the Mini-Mental State Examination (MMSE), a measure of global cognitive function scored from 0 to 30 with greater scores indicating higher cognitive function [14], the Trail-Making Test Part B (Trails B) of the Halsted Reitan Battery [15], a measure of executive function and psychomotor processing speed scored as the time (seconds) needed to complete the task, and the Verbal Fluency Test (VFT), a category fluency task and measure of verbal semantic fluency scored as the number of unique animals named in 1 min [16]. Mild cognitive impairment was defined as a score greater than 2.0 standard deviations (SD) below the sex-, age-, and education-adjusted mean for MMSE based on normative data from the National Alzheimer’s Coordinating Center Uniform Data Set [17]. A retest variable defined as 1 for individuals who had previously performed the cognitive tests, 0 otherwise, was included to control for practice-related differences in performance [18].
Vision assessment
Visual acuity was assessed using the Bailey-Lovie chart with acuity scores converted into logarithm of the minimum angle of resolution (logMAR) notation [19]. Participants were tested at a distance of 2 m with the participant wearing their presenting optical correction, if any. Low visual acuity was defined as vision worse than 20/40 in the better eye (logMAR > 0.30) [20,21]. At the time of the visual acuity assessment, participants reported on self-perceived difficulties with near vision.
Hearing assessment
Hearing acuity was assessed with a Welch Allyn portable audiometer, as previously reported [12]. Hearing ability was tested at thresholds of 40, 25 and 20 dB at frequencies of 500, 1,000, 2,000 and 4,000 Hz. If a participant was unable to hear the tone at 40 dB, a value of 50 dB was assigned and measurement was stopped. The pure-tone auditory (PTA) threshold was calculated as the average threshold across the four frequencies for each ear. The PTA of the better-hearing ear was used to define hearing categories as normal hearing acuity (PTA ≤ 25 dB) or low hearing acuity (PTA > 25 dB) [22].
Covariate assessment
Potential confounders of the associations between visual and hearing acuity and cognitive function were assessed by questionnaire and by clinical measurement. Covariates from the questionnaire included: marital status, education (high school or less, some college or college graduate), alcohol consumption (non-drinker, daily, 3-4 drinks per week, 1-2 drinks per week, 1-2 drinks per month, or <1 drink per month), smoking status (never, former or current smoker), self-rated general health (excellent, very good, good or fair or poor), participation in exercise ≥3 times per week (no or yes), self-rated physical functioning (no limitations, some limitations, or large or extremely limited) and history of heart disease (no or yes) or diabetes (defined by self-report of physician diagnosis, fasting plasma glucose ≥126 mg/dl, 2-h post-challenge glucose ≥200 mg/dl, or use of diabetes medications; no or yes). Body mass index (BMI, kg/m2) was calculated from measured height and weight.
Statistical analysis
We used linear mixed-effects models to examine the associations of baseline visual acuity and dual impairments in visual and hearing acuity with baseline as well as longitudinal cognitive test performance. Linear mixed-effect models are able to handle missing data and inconsistent measurement intervals within and across participants allowing us to use all available data for each participant. In analyses of visual acuity and cognitive test performance, independent variables included time since baseline in years, time-squared, an indicator of low visual acuity, an indicator of low hearing acuity, an interaction term between low visual acuity and time and covariates. In analyses of dual sensory impairments and cognitive test performance, independent variables included time, joint indicators of visual and hearing acuity (normal visual acuity and normal hearing acuity [referent], low visual acuity and normal hearing acuity, normal visual acuity and low hearing acuity and low visual acuity and low hearing acuity), interaction terms between each of the visual/hearing acuity indicators and time, and covariates. In sensitivity analyses, we excluded participants who self-rated their general health as fair or poor at baseline (n = 137) and those who were missing self-rated general health (n = 3) to address the possibility that any dual sensory impairment associations are due to differences in overall health. We also examined the impact of cognitive impairment at baseline by excluding participants whose baseline scores were more than two SDs below the expected MMSE score normalised for age, education and sex (n = 131), or age- and sex-normalised scores for individuals missing education data (n = 9) [17].
Models were fit using PROC MIXED in SAS version 9.4 (SAS Institute Inc., Cary, NC). We examined effect measure modification by conducting sex-stratified analyses and by including statistical interactions (3-way and all 2-way interactions between acuity group, time and sex) in the regression models.
Results
The characteristics of the RBS participants included in this study are reported in Table 1. The majority of participants were women (60.9%), married (70.5%), and had some college education or greater (71.6%). The mean age at the time of the study visit in 1992–1996 was 74.4 (SD = 9.4) years. Of the full sample, 21.2% had low visual acuity. The proportions of adults with low visual acuity increased with increasing age, with decreasing self-rated general health, and with poorer physical functioning. Low visual acuity was more prevalent among women, among adults with heart disease, and among adults with diabetes. Overall, participants completed a mean of 2.9 (SD = 1.6) cognitive assessments over a mean follow-up of 7.3 (SD = 6.4) years. Over half (54%) of the participants completed three or more cognitive assessments and 70% had two or more cognitive assessments over the follow-up. Participants with normal visual acuity completed a mean of 3.1 (SD = 1.6) cognitive assessments over a mean follow-up of 8.1 (SD = 6.5) years, and participants with low visual acuity completed a mean of 2.2 (SD = 1.4) assessments over a mean follow-up of 4.3 (SD = 5.0) years.
Table 1 .
Characteristics of Rancho Bernardo Study participants overall and by sex and baseline visual acuity (n = 1,383)
| Visual acuitya | |||||
|---|---|---|---|---|---|
| Males (n = 541) | Females (n = 842) | ||||
| Overall | Low (n = 89) | Normal (n = 452) | Low (n = 204) | Normal (n = 638) | |
| Characteristic | n (%) | n (%) | n (%) | n (%) | n (%) |
| Age (years) | |||||
| <69 | 412 (29.8) | 7 (7.9) | 164 (36.3) | 17 (8.3) | 224 (35.1) |
| 70–79 | 534 (38.6) | 23 (25.8) | 186 (41.2) | 75 (36.8) | 250 (39.2) |
| 80+ | 437 (31.6) | 59 (66.3) | 102 (22.6) | 112 (54.9) | 164 (25.7) |
| Mean (SD) | 74.4 (9.4) | 81.6 (7.0) | 72.9 (8.7) | 79.6 (7.0) | 72.8 (9.7) |
| Marital status | |||||
| Married | 974 (70.5) | 78 (88.6) | 400 (88.7) | 101 (49.5) | 395 (61.9) |
| Widowed | 322 (23.3) | 8 (9.1) | 30 (6.7) | 97 (47.5) | 187 (29.3) |
| Single | 85 (6.2) | 2 (2.3) | 21 (4.7) | 6 (2.9) | 56 (8.8) |
| Missing | 2 | 1 | 1 | 0 | 0 |
| Education | |||||
| High school or less | 388 (28.4) | 19 (21.8) | 70 (15.7) | 71 (34.8) | 228 (36.1) |
| Some college | 431 (31.5) | 23 (26.4) | 119 (26.7) | 70 (34.3) | 219 (34.7) |
| College graduate | 549 (40.1) | 45 (51.7) | 257 (57.6) | 63 (30.9) | 184 (29.2) |
| Missing | 15 | 2 | 6 | 0 | 7 |
| Alcohol consumption | |||||
| Non-drinker | 209 (15.2) | 15 (16.9) | 46 (10.3) | 40 (19.7) | 108 (17.0) |
| Daily | 482 (35.1) | 27 (30.3) | 204 (45.5) | 62 (30.5) | 189 (29.8) |
| 3-4 per week | 142 (10.3) | 12 (13.5) | 53 (11.8) | 11 (5.4) | 66 (10.4) |
| 1-2 per week | 180 (13.1) | 14 (15.7) | 59 (13.2) | 24 (11.8) | 83 (13.1) |
| 1-2 per month | 182 (13.2) | 11 (12.4) | 44 (9.8) | 32 (15.8) | 95 (15.0) |
| <1 per month | 180 (13.1) | 10 (11.2) | 42 (9.4) | 34 (16.7) | 94 (14.8) |
| Missing | 8 | 0 | 4 | 1 | 3 |
| Smoking status | |||||
| Never smoker | 581 (42.3) | 26 (29.2) | 136 (30.3) | 100 (49.5) | 319 (50.3) |
| Former smoker | 695 (50.6) | 60 (67.4) | 283 (63.0) | 88 (43.6) | 264 (41.6) |
| Current smoker | 98 (7.1) | 3 (3.4) | 30 (6.7) | 14 (6.9) | 51 (8.0) |
| Missing | 9 | 0 | 3 | 2 | 4 |
| Self-rated general health | |||||
| Excellent | 296 (21.4) | 10 (11.4) | 111 (24.6) | 33 (16.3) | 142 (22.3) |
| Very good | 592 (42.9) | 34 (38.6) | 189 (41.9) | 77 (37.9) | 292 (45.8) |
| Good | 355 (25.7) | 24 (27.3) | 115 (25.5) | 65 (32.0) | 151 (23.7) |
| Fair or poor | 137 (9.9) | 20 (22.7) | 36 (8.0) | 28 (13.8) | 53 (8.3) |
| Missing | 3 | 1 | 1 | 1 | 0 |
| Exercise, ≥3 times per week | |||||
| No | 380 (27.6) | 27 (30.3) | 94 (20.9) | 60 (29.6) | 199 (31.3) |
| Yes | 997 (72.4) | 62 (69.7) | 355 (79.1) | 143 (70.4) | 437 (68.7) |
| Missing | 6 | 0 | 3 | 1 | 2 |
| Body mass index (kg/m2) | |||||
| <25.0 | 745 (54.0) | 45 (51.1) | 186 (41.2) | 126 (62.1) | 388 (60.9) |
| 25.0–29.9 | 498 (36.1) | 35 (39.8) | 215 (47.6) | 63 (31.0) | 185 (29.0) |
| ≥30.0 | 137 (9.9) | 8 (9.1) | 51 (11.3) | 14 (6.9) | 64 (10.0) |
| Missing | 3 | 1 | 0 | 1 | 1 |
| Mean (SD) | 25.2 (4.0) | 25.5 (4.0) | 26.2 (3.5) | 24.3 (3.8) | 24.7 (4.2) |
| Self-rated physical functioning | |||||
| No limitations | 682 (49.5) | 28 (31.8) | 224 (49.6) | 92 (45.8) | 338 (53.0) |
| Some limitations | 626 (45.4) | 48 (54.5) | 205 (45.4) | 95 (47.3) | 278 (43.6) |
| Large or extremely limited | 71 (5.1) | 12 (13.6) | 23 (5.1) | 14 (7.0) | 22 (3.4) |
| Missing | 4 | 1 | 0 | 3 | 0 |
| History of heart disease | |||||
| No | 836 (60.7) | 44 (49.4) | 261 (58.1) | 113 (55.7) | 418 (65.7) |
| Yes | 541 (39.3) | 45 (50.6) | 188 (41.9) | 90 (44.3) | 218 (34.3) |
| Missing | 6 | 0 | 3 | 1 | 2 |
| History of diabetes | |||||
| No | 1,137 (82.2) | 61 (68.5) | 365 (80.8) | 160 (78.4) | 551 (86.4) |
| Yes | 246 (17.8) | 28 (31.5) | 87 (19.2) | 44 (21.6) | 87 (13.6) |
| Hearing acuity | |||||
| Normal | 393 (28.4) | 8 (9.0) | 98 (21.7) | 34 (16.7) | 253 (39.7) |
| Low | 990 (71.6) | 81 (91.0) | 354 (78.3) | 170 (83.3) | 385 (60.3) |
| Difficulties with reading | |||||
| No | 1,247 (90.7) | 61 (68.5) | 417 (92.9) | 164 (81.2) | 605 (95.3) |
| Yes | 128 (9.3) | 28 (31.5) | 32 (7.12) | 38 (18.8) | 30 (4.7) |
| Missing | 8 | 0 | 3 | 2 | 3 |
| Follow-up time (yrs), 90th percentile | 14.90 | 8.00 | 15.17 | 13.75 | 15.21 |
aVisual acuity was categorised as low, >20/40 in the better eye (logMAR > 0.30) and normal, ≤ 20/40 in the better eye (logMAR ≤ 0.30).
The results from the linear mixed-effects models examining the associations between baseline impairment in visual acuity and cognitive test performance are reported in Table 2. In base models, low visual acuity was associated with poorer baseline performance on the MMSE (β = −0.36, SE = 0.13) and Trails B tests (β = 14.35, SE = 3.63) and with a faster rates of decline (MMSE β = −0.11, SE = 0.02; Trails B β = 1.82, SE = 0.56). In fully adjusted models, the estimates for the main effects of low visual acuity were attenuated for MMSE (β = −0.29, SE = 0.13) and Trails B (β = 13, SE = 3.61). The rate of decline in MMSE (β = −0.12, SE = 0.02) and Trails B (β = 1.84, SE = 0.56) was similar in fully adjusted models as in the base models. None of the interactions including sex were statistically significant (Table 2 and Supplementary Figure S1).
Table 2 .
Associations of impairments in visual acuity with longitudinal cognitive test performance among participants of the Rancho Bernardo Study of Healthy Aging, overall and by sex (n = 1,383)
| MMSE | Overall | Males | Females | |||
|---|---|---|---|---|---|---|
| β (SE) | P | β (SE) | P | β (SE) | P | |
| Base modela | ||||||
| Time | −0.17 (0.01) | <0.01 | −0.17 (0.02) | <0.01 | −0.17 (0.02) | <0.01 |
| Time2 | 0.006 (0.001) | <0.01 | 0.005 (0.001) | <0.01 | 0.006 (0.001) | <0.01 |
| Low visual acuity | −0.36 (0.13) | 0.01 | −0.38 (0.25) | 0.13 | −0.33 (0.16) | 0.04 |
| Visual acuity × time | −0.11 (0.02) | <0.01 | −0.12 (0.05) | 0.01 | −0.11 (0.02) | <0.01 |
| P Visual acuity × sex = 0.22 | ||||||
| P Visual acuity × time × sex = 0.96 | ||||||
| Fully adjusted modelb | ||||||
| Time | −0.17 (0.01) | <0.01 | −0.18 (0.02) | <0.01 | −0.17 (0.02) | <0.01 |
| Time2 | 0.006 (0.001) | <0.01 | 0.006 (0.001) | <0.01 | 0.006 (0.001) | <0.01 |
| Low visual acuity | −0.29 (0.13) | 0.02 | −0.27 (0.24) | 0.26 | −0.28 (0.15) | 0.07 |
| Visual acuity × time | −0.12 (0.02) | <0.01 | −0.13 (0.05) | <0.01 | −0.12 (0.02) | <0.01 |
| P Visual acuity × sex = 0.24 | ||||||
| P Visual acuity × time × sex = 0.95 | ||||||
| Trails B | ||||||
| Base Modela | ||||||
| Time | 1.52 (0.33) | <0.01 | 1.25 (0.45) | 0.01 | 1.59 (0.43) | <0.01 |
| Time2 | 0.10 (0.02) | <0.01 | 0.09 (0.03) | <0.01 | 0.11 (0.03) | <0.01 |
| Low visual acuity | 14.35 (3.63) | <0.01 | 22.26 (6.16) | <0.01 | 11.07 (4.52) | 0.01 |
| Visual acuity × time | 1.82 (0.56) | <0.01 | 2.58 (1.16) | 0.03 | 1.56 (0.68) | 0.02 |
| P Visual acuity × sex = 0.28 | ||||||
| P Visual acuity × time × sex = 0.59 | ||||||
| Fully adjusted modelb | ||||||
| Time | 1.53 (0.33) | <0.01 | 1.24 (0.45) | 0.01 | 1.59 (0.43) | <0.01 |
| Time2 | 0.10 (0.02) | <0.01 | 0.10 (0.03) | <0.01 | 0.12 (0.03) | <0.01 |
| Low visual acuity | 13.21 (3.61) | <0.01 | 18.96 (6.22) | <0.01 | 10.37 (4.48) | 0.02 |
| Visual acuity × time | 1.84 (0.56) | <0.01 | 2.60 (1.16) | 0.03 | 1.60 (0.68) | 0.02 |
| P Visual acuity × sex = 0.67 | ||||||
| P Visual acuity × time × sex = 0.59 | ||||||
| VFT | ||||||
| Base modela | ||||||
| Time | −0.28 (0.03) | <0.01 | −0.29 (0.04) | <0.01 | −0.28 (0.04) | <0.01 |
| Time2 | 0.000 (0.002) | 0.98 | 0.000 (0.003) | 0.96 | 0.001 (0.002) | 0.72 |
| Low visual acuity | −0.57 (0.30) | 0.06 | −1.35 (0.57) | 0.02 | −0.20 (0.34) | 0.56 |
| Visual acuity × time | −0.03 (0.04) | 0.44 | −0.14 (0.09) | 0.13 | −0.03 (0.04) | 0.53 |
| P Visual acuity × sex = 0.11 | ||||||
| P Visual acuity × time × sex = 0.32 | ||||||
| Fully adjusted modelb | ||||||
| Time | −0.28 (0.03) | <0.01 | −0.30 (0.04) | <0.01 | −0.29 (0.04) | <0.01 |
| Time2 | 0.000 (0.002) | 0.97 | 0.000 (0.003) | 0.86 | 0.001 (0.002) | 0.61 |
| Low visual acuity | −0.36 (0.30) | 0.23 | −1.23 (0.59) | 0.04 | 0.01 (0.34) | 0.98 |
| Visual acuity × time | −0.04 (0.04) | 0.33 | −0.14 (0.09) | 0.13 | −0.04 (0.04) | 0.42 |
| P Visual acuity ×x sex = 0.17 | ||||||
| P Visual acuity × time × sex = 0.35 | ||||||
Note: Visual acuity was categorised as low, logMAR > 0.30 in the better eye and normal, logMAR ≤ 0.30 in the better eye.
aBase model: adjusted for age (continuous in years), sex (male, female), education (high school or less, some college, college graduate) and retest (0, 1), as appropriate.
bFully adjusted model: adjusted for base model variables plus marital status (married, widowed, single), alcohol consumption (non-drinker, daily, 3-4 per week, 1-2 per week, 1-2 per month, <1 per month), smoking status (never smoker, former smoker, current smoker), self-rated general health (excellent, very good, good, fair or poor), exercise, ≥3 times per week (no, yes), body mass index (<25.0, 25.0–29.9, ≥30.0 kg/m2), self-rated physical functioning (no limitations, some limitations, large or extremely limited), history of heart disease (no, yes), history of diabetes (no, yes) and hearing acuity (normal, low), as appropriate.
The characteristics of the study participants categorised into four groups based on both visual and hearing acuity are reported in Supplementary Table S1. One-fourth (25.4%) of the sample had normal visual and normal hearing acuity, 53.4% had normal visual acuity and low hearing acuity, 3.0% had low visual acuity and normal hearing acuity and 18.1% had dual sensory impairments. Compared to those with no visual or hearing impairments, participants with dual sensory impairments were 15 years older on average (mean age = 81.5 vs. 66.6 years), more likely to be male, and had a higher prevalence of heart disease and diabetes. They were also more likely to report large or extreme limitations in physical functioning and to self-rate their health as fair or poor. Participants with normal visual and normal hearing acuity completed a mean of 3.5 (SD = 1.6) cognitive assessments over a mean follow-up of 10.3 (SD = 6.7) years, and participants with low visual and low hearing acuity completed a mean of 2.0 (SD = 1.2) cognitive assessments over a mean of 3.6 (SD = 4.3) years.
The results from the linear mixed-effects models examining the associations between baseline impairments in visual and hearing acuity and longitudinal cognitive test performance are reported in Table 3 and shown in Figure 1. In fully adjusted models, low visual and low hearing acuity was associated with poorer MMSE (β = −0.44, SE = 0.18) and Trails B (β = 11.20, SE = 4.97) performance at baseline. MMSE (β = −0.19, SE = 0.03), Trails B (β = 3.50, SE = 0.71) and VFT (β = −0.14, SE = 0.05) performance decreased at a faster rate among adults with low visual and low hearing acuity. The performance deficits at baseline for the MMSE and Trails B among those with dual sensory impairments were equivalent to an additional 5.7 and 3.2 years of age, respectively, relative to individuals with normal vision and hearing. Additionally, the yearly effect of vision and hearing impairment on the rates of decline in MMSE and Trails B performance was equivalent to an additional 2.4 and 1.0 years of age, respectively. None of the interactions including sex were statistically significant (Table 2 and Supplementary Table S2).
Table 3 .
Associations of impairment in visual and hearing acuity and longitudinal cognitive test performance among participants of the Rancho Bernardo Study of Healthy Aging (n = 1,383)
| Base modela | Fully adjusted modelb | |||
|---|---|---|---|---|
| MMSE | β (SE) | P | β (SE) | P |
| Time | −0.13 (0.02) | <0.01 | −0.14 (0.02) | <0.01 |
| Time2 | 0.005 (0.001) | <0.01 | 0.006 (0.001) | <0.01 |
| Visual/hearing acuity | ||||
| Normal/low | 0.00 (0.13) | 0.99 | −0.03 (0.13) | 0.80 |
| Low/normal | 0.36 (0.31) | 0.24 | 0.32 (0.29) | 0.28 |
| Low/low | −0.50 (0.18) | 0.01 | −0.44 (0.18) | 0.01 |
| Visual/hearing acuity × time | ||||
| Normal/Low × time | −0.04 (0.01) | <0.01 | −0.05 (0.01) | <0.01 |
| Low/Normal × time | −0.09 (0.03) | 0.01 | −0.09 (0.03) | 0.01 |
| Low/Low × time | −0.18 (0.03) | <0.01 | −0.19 (0.03) | <0.01 |
| Trails B | ||||
| Time | 0.59 (0.41) | 0.15 | 0.57 (0.41) | 0.17 |
| Time2 | 0.11 (0.02) | <0.01 | 0.12 (0.02) | <0.01 |
| Visual/hearing acuity | ||||
| Normal/low | −5.59 (3.72) | 0.13 | −5.18 (3.67) | 0.16 |
| Low/normal | −1.24 (8.38) | 0.88 | 0.37 (8.30) | 0.96 |
| Low/low | 12.51 (4.99) | 0.01 | 11.20 (4.97) | 0.02 |
| Visual/hearing acuity × time | ||||
| Normal/low × time | 1.31 (0.37) | <0.01 | 1.37 (0.37) | <0.01 |
| Low/normal × time | 1.15 (0.96) | 0.23 | 1.14 (0.97) | 0.24 |
| Low/low × time | 3.45 (0.71) | <0.01 | 3.50 (0.71) | <0.01 |
| VFT | ||||
| Time | −0.24 (0.03) | <0.01 | −0.24 (0.03) | <0.01 |
| Time2 | −0.001 (0.002) | 0.67 | −0.001 (0.002) | 0.70 |
| Visual/hearing acuity | ||||
| Normal/low | 0.14 (0.31) | 0.66 | 0.19 (0.31) | 0.54 |
| Low/normal | −0.46 (0.70) | 0.52 | −0.67 (0.70) | 0.34 |
| Low/low | −0.46 (0.41) | 0.27 | −0.12 (0.41) | 0.77 |
| Visual/hearing Acuity × time | ||||
| Normal/Low × time | −0.05 (0.03) | 0.06 | −0.06 (0.03) | 0.03 |
| Low/Normal × time | 0.06 (0.07) | 0.38 | 0.05 (0.07) | 0.44 |
| Low/Low × time | −0.13 (0.05) | 0.01 | −0.14 (0.05) | 0.01 |
Note: Visual acuity was categorised as low, logMAR > 0.30 in the better eye and normal, logMAR ≤ 0.30 in the better eye. Hearing acuity was categorised as low, pure-tone average threshold > 25 and normal, pure-tone average threshold ≤25.
aBase model: adjusted for age (continuous in years), sex (male, female), education (high school or less, some college, college graduate) and retest (0, 1), as appropriate.
bFully adjusted model: adjusted for base model variables plus marital status (married, widowed, single), alcohol consumption (non-drinker, daily, 3-4 per week, 1-2 per week, 1-2 per month, <1 per month), smoking status (never smoker, former smoker, current smoker), self-rated general health (excellent, very good, good, fair or poor), exercise, ≥3 times per week (no, yes), body mass index (<25.0, 25.0–29.9, ≥30.0 kg/m2), self-rated physical functioning (no limitations, some limitations, large or extremely limited), history of heart disease (no, yes) and history of diabetes (no, yes).
Figure 1 .
Modelled trajectories of cognitive function test performance over time as a function of baseline visual/hearing acuity [black line, normal visual and normal hearing acuity (n = 351); gray solid line, normal visual and low hearing acuity (n = 739); gray dashed line, low visual and normal hearing acuity (n = 42); red line, low visual and low hearing acuity (n = 251)] in the Rancho Bernardo Study of Healthy Aging. Plots are based on model coefficients adjusted for age, sex, education and practice effect. The axis for Trails B is reversed so that for all tests, downward sloping lines represent declining performance. Trajectories are plotted to the 90th percentile of follow-up time for each visual/hearing acuity group.
Similar results were obtained in sensitivity analyses excluding 140 participants with fair or poor or missing self-rated general health (Supplementary Table S3). In sensitivity analyses excluding 140 participants with cognitive impairment at baseline, baseline differences in cognitive test performance by sensory impairment were attenuated and no longer statistically significant; however, the rates of decline in cognitive test performance remained elevated among those with low visual acuity, and with dual impairments in visual and hearing acuity (Supplementary Table S4).
Discussion
In this study of older adults with repeated cognitive assessments, low visual acuity was associated with poorer cognitive test performance and faster rates of cognitive decline compared to normal visual acuity. The greatest declines in cognitive test performance were observed among adults with dual impairments in visual and hearing acuity, while adults with neither impairment performed best over time. Although vision and hearing impairments were more prevalent in women than in men, associations did not appreciably differ between men and women.
The results of our analysis of vision impairment and cognitive decline are consistent with previous cohort studies [6,7,10,23–27]. In the Health ABC Study, for example, visual impairment was associated with a greater decline in MMSE scores and with greater risk of developing cognitive impairment over 9 years of follow-up [6]. In the Beaver Dam Offspring Study, visual impairment was associate with a 2.5-fold increase in the 10-year cumulative incidence of cognitive impairment [23], and in the Maastricht Aging Study, poor baseline visual acuity was associated with poorer performance on most cognitive measures examined, but not the VFT [27].
To date, at least two studies have examined concurrent visual and hearing impairment in association with the cognitive decline with conflicting results. Among 1,636 women aged 69+ who participated in the Study of Osteoporotic Fractures (SOF) between 1992 and 1994, baseline visual impairment was associated with a 78% increase in the odds of cognitive decline and dual sensory impairment was associated with a 119% increase in the odds of cognitive decline over the mean follow-up of 4.4 years [11]. In contrast to our findings and those of SOF, dual sensory impairment was not associated with the subsequent decline in cognition in the Blue Mountains Eye Study, a population-based cohort study conducted among 1,605 Australians aged 49+ years [9]. Reasons for these discrepancies may be due to differences in the study populations; participants in the Blue Mountains Eye Study were younger at baseline, and thus there was a lower prevalence of visual impairment. Furthermore, the Blue Mountains Eye Study was underpowered to examine dual sensory impairments in vision and hearing as only 93 participants had dual sensory impairments in their study. The SOF study also used a higher threshold for hearing impairment and only tested hearing at one frequency, perhaps underestimating the influence of hearing loss. Our results of lower cognitive function among adults with both visual and hearing acuity impairments extend prior findings to a slightly longer mean follow-up with multiple cognitive assessments. Additionally, to our knowledge, this is the first study to evaluate sex-differences in dual impairments in vision and hearing acuity and cognitive function.
Four hypotheses have been proposed linking sensory function and cognition: (i) the sensory deprivation hypothesis; (ii) the resource allocation hypothesis; (iii) the common cause hypothesis; and the (iv) the performance disadvantage hypothesis [27]. This study was not designed to test any one hypothesis, but it is important to consider the possible influence of the fourth hypothesis on our results. Our study technicians ensured that participants were able to hear and understand all instructions and that their visual and hearing abilities were sufficient to complete tests. Additionally, all test materials were presented in larger than standard newsprint font. Nevertheless, it is possible that sensory difficulties may have contributed to poorer performance on the MMSE and the Trails B. Our measure of visual acuity is distance vision; near vision is more relevant to performance on these tests. The overwhelming majority of participants (91%) did not report difficulties reading ordinary newsprint; including the majority (77%) of participants with low visual acuity. However, in our study, impairments in visual acuity were not associated with performance on the VFT, the only non-vision dependent cognitive test, although impairments in both visual and hearing acuity were associated with more rapid decline in VFT performance over time. The finding that participants with low sensory acuity had a poorer physical function and were more likely to have diabetes and heart disease could be consistent with a common underlying factor that affects health, sensory acuity and cognitive performance. However, adjusting for health-related covariates and excluding participants with fair or poor self-rated general health did not change the results.
Strengths of our study include the long longitudinal follow-up, multiple assessments of cognitive function, and objective assessments of vision and hearing. However, several limitations should be noted. First, we examined only one aspect of vision and we were underpowered to examine more severe vision impairment. Other impairments such as reduced contrast sensitivity [7,24] and near vision [26] have also associated with age-related cognitive decline and should be integrated in future studies. Furthermore, the use of presenting visual acuity may have biased our results either towards the null if this misclassification is non-differential with respect to cognitive function, or away from the null if participants with reduced cognitive function are less likely to recognise that they have inadequate correction or do not take the initiative to have their vision assessed and corrected. Second, the RBS is composed of primarily educated, Northern European-American adults from a single community. Therefore, the results of this study may not be generalizable to other populations. Third, our test battery contained only three cognitive function tests; no tests of memory or working memory were included, and while the estimates reported here are small; however, over time these deficits can accumulate and at the population-level even small effects can have large impacts. Last, survival bias may have resulted in an underestimate of the association between sensory impairments and cognitive function if adults with greater impairments failed to return for subsequent assessments.
Conclusions
In this study, we report that women and men with low visual and hearing acuity performed more poorly and had faster rates of cognitive decline than those with normal hearing and vision. These findings indicate that it may be important to identify older adults with sensory impairments as they may be at increased risk of cognitive decline, particularly when impairments are observed in more than one modality. Further study is needed to determine whether correction for visual impairments, such as cataract surgery [28–31] or use of hearing aids [32] may alleviate risk of cognitive decline.
Supplementary Material
Contributor Information
Jr Humberto Parada, Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA, USA; University of California San Diego, Moores Cancer Center, La Jolla, CA, USA.
Gail A Laughlin, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA.
Mingan Yang, Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA, USA.
Frances R Nedjat-Haiem, School of Social Work, San Diego State University, San Diego, CA, USA.
Linda K McEvoy, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, School of Medicine, San Diego, CA, USA.
Ethical standards
All procedures performed in the Rancho Bernardo Study of Healthy Aging involving human participants were in accordance with the ethical standards of the Institutional Review Boards of the University of California, San Diego and were in compliance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This study was approved by the San Diego State University Institutional Review Board.
Ethical approval
Informed consent was obtained from all individual participants included in the study.
Declaration of Conflicts of Interest
None.
Declaration of Funding
H.P. was supported by the National Cancer Institute (K01 CA234317), the SDSU/UCSD Comprehensive Cancer Center Partnership (U54 CA132384 and U54 CA132379), and the Alzheimer’s Disease Resource Center for advancing Minority Aging Research at the University of California San Diego (P30 AG059299). L.K.M. and G.A.L. were supported by the National Institute on Aging (R01 AG062483). Sponsor’s Role: The sponsors and funding agency played no role in the design, methods, data collections, analysis and preparation of this article. Data collection for the Rancho Bernardo Study of Healthy Aging (RBS) was provided primarily by the National Institutes of Health (including grant numbers: HV012160, AA021187, AG028507, AG007181, DK31801, HL034591, HS06726 and HL089622). Archiving and sharing of RBS data were supported by National Institute on Aging (AG054067). RBS data are available through the RBS website: https://knit.ucsd.edu/ranchobernardostudy/
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