Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2016 Sep 4.
Published in final edited form as: J Am Geriatr Soc. 2015 Sep 4;63(9):1774–1782. doi: 10.1111/jgs.13634

Driving with Mild Cognitive Impairment or Dementia: Cognitive Test Performance and Proxy Report of Daily Life Function in Older Women

Leslie Vaughan *, Patricia E Hogan , Stephen R Rapp *,, Elizabeth Dugan §, Richard A Marottoli ¶,**, Beverly M Snively , Sally A Shumaker *, Kaycee M Sink ††
PMCID: PMC4841465  NIHMSID: NIHMS777024  PMID: 26338449

Abstract

OBJECTIVES

To investigate associations between proxy report of cognitive and functional limitations and cognitive performance and current or former driving status in older women with mild cognitive impairment (MCI) and all-cause dementia.

DESIGN

Cross-sectional data analysis of retrospectively identified older women with adjudicated MCI and all-cause dementia in the Women’s Health Initiative Memory Study—Epidemiology of Cognitive Health Outcomes (WHIMS-ECHO).

SETTING

Academic medical center.

PARTICIPANTS

Women (mean age ± standard deviation 83.7 ± 3.5) adjudicated with MCI or dementia during Year 1, 2, 3, or 4 of the WHIMS-ECHO follow-up period (N = 385).

MEASUREMENTS

The telephone-administered cognitive battery included tests of attention, verbal learning and memory, verbal fluency, executive function, working memory, and global cognitive function plus self-report measures of depressive symptomatology. The Dementia Questionnaire (DQ) was administered to a knowledgeable proxy (family member, friend).

RESULTS

Sixty percent of women with MCI and 40% of those with dementia are current drivers. Proxy reports of functional limitations in instrumental activities of daily living (IADLs) are associated with current driving status in women with MCI, whereas performance-based cognitive tests are not. In women with dementia, proxy reports of functional limitations in IADLs and performance-based cognitive tests are associated with current driving status, as expected.

CONCLUSION

These findings have clinical implications for the importance of evaluating driving concurrently with other instrumental functional abilities in MCI and dementia. Additional work is needed to determine whether proxy report of cognitive and functional impairments should help guide referrals for driving assessment and rehabilitation or counseling for driving transition.

Keywords: aging, driving, instrumental activities of daily living, mild cognitive impairment, dementia


Driving is a complex daily life activity that, similar to other instrumental activities of daily living (IADLs), reflects age- and disease-related cognitive declines.1-3 Although a growing body of recent research on driving and cognitive impairment in older adults demonstrates that older adults with cognitive impairment are less-safe drivers than cognitively normal older adults, little is known about the current or former driving status of cognitively impaired older adults.4 Older women, in particular, may out-live their safe-driving ability by 10 and 4 years longer than men,5 because their lifespan is longer. Dementia, which in women aged 85 and older has been reported to be as prevalent as 30%, may exacerbate age-related decline in driving ability.6 There is a correspondingly greater risk of motor vehicle crashes for all drivers with dementia7-9 although this has not been studied specifically in women. Further understanding of driving patterns of women with cognitive impairment is of public health interest.

There is a paucity of research on driving retirement4 in older adults with mild cognitive impairment (MCI) and dementia. Findings from the literature on MCI and driving on driving performance are inconclusive with regard to driver safety,10 whereas there is good evidence that older drivers with dementia eventually become unsafe.1,4,11 Poorer globally rated driving performance on a road test has been reported in individuals with MCI (n = 46) than controls (n = 59). It was concluded that the driving performance of the sample with MCI was “less than optimal, but not at the level of frank impairment.” In one study, 20% to 30% of older adults with Alzheimer’s type dementia self-reported being current drivers,4 but little is known about driving prevalence in older adults with MCI.

Educational resources include the American Medical Association Physician’s Guide to Assessing and Counseling Older Drivers12 and the AARP online resources and driver safety courses. Occupational therapists who specialize in driver assessment and intervention to extend safe driving,13,14 typically through physician referral, provide supportive assistance to older drivers. Older adults may not know the best way to transition from driving to using other transportation because of a lack of referral pathways between doctors and driver rehabilitation specialists, inadequate education by healthcare providers to clients and their families, and a lack of public policies that promote accessible transportation alternatives for older adults. Finally, it is unclear whether family members of older adults with cognitive impairment are aware of unsafe driving or know how to address the issue of driving transition effectively.15-18

Proxy reports of the driving status of older adults with adjudicated mild cognitive impairment (MCI) and probable dementia in the Women’s Health Initiative Memory Study (WHIMS) were examined. Specifically, women’s current driving status, proxy reports of cognitive and functional limitations, and neurocognitive test performance were examined in the context of their demographic and health status. It was hypothesized that, although many women with dementia would have ceased driving because of cognitive limitations, a significant proportion of them would be currently driving. It was also estimated that a significantly larger percentage of women with MCI than dementia would be current drivers. Based on prior reports of the reliability and validity of the Dementia Questionnaire (DQ)19 and comparisons of the reliability of proxy, self-report, and performance-based measures of functional status in normal aging20 and MCI,1,21,22 it was estimated that proxy reports of cognitive and functional limitations might predict the driving status of women with cognitive impairment.

METHODS

Participants

Dementia-free women aged 65 to 79 who participated in the Women’s Health Initiative (WHI) Hormone Therapy (HT) clinical trials23 were recruited to participate in the Women’s Health Initiative Memory Study (WHIMS) from 1996 to 1999 (N = 7,479).24 WHIMS was an ancillary study conducted to examine the effect of estrogen alone or in combination with a progestin on global cognitive function and dementia incidence in postmenopausal women.25-28 The WHI HT trials were stopped early because of an unfavorable risk to benefit ratio,29,30 ending the randomized controlled trial, but WHIMS participants continued to be assessed using the full protocol with clinic-based cognitive assessments until 2008, when they were switched to an annual, validated telephone-based cognitive assessment [WHIMS-Epidemiology of Cognitive Health Outcomes (ECHO)]. These analyses included 2,893 women with a mean age of 82.3 ± 3.6 who underwent at least one telephone-based cognitive assessment.

Measures

The telephone-administered cognitive battery includes measures of global cognitive function, long-term memory, attention and working memory, verbal fluency, executive function, and depressive symptomatology.31 If women score less than 30 on the modified Telephone Interview for Cognitive Status (TICSm),32,33 the DQ,19 a structured interview that assesses dementia-related cognitive and behavioral status and relevant medical history, is administered to a proxy who is knowledgeable about the participant’s health status. Two independent expert adjudicators centrally adjudicate cognitive performance, proxy responses, and all prior WHIMS data using Petersen’s criteria for MCI34 and Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for dementia35 into one of three groups [no cognitive impairment, mild cognitive impairment (MCI), probable dementia] without further subclassification.24

Cognitive Test Battery

The modified TICS-m,36,37 a widely used measure of global cognitive functioning modeled after the Mini-Mental State Examination38 is a 16-item instrument with scores ranging from 0 to 50 that assesses orientation (0–9 points), attention and concentration (0–2 points), short-delay free recall (0–10 points), mental calculation (0–5 points), naming (0–4 points), repetition (0–2 points), social knowledge (0–4 points), praxis (0–2 points), opposites (0–2 points), and long-delay free recall (0–10 points);

The East Boston Memory Test (EBMT) is a measure of immediate and delayed verbal memory (0–12 points).39

The Oral Trail-Making Test is a modified version of the original Trail-Making Test (TMT),40,41 a measure of attention (Part A) and executive function (Part B), scored as time in seconds.

Verbal Fluency—Animals, a measure of verbal fluency,42 is scored as the number of uniquely and spontaneously named animals in 1 minute.

The Digit Span forward and backward subtests of the Wechsler Adult Intelligence Scale—Revised43 measure attention and working memory and are scored as the number of correct responses. Depressive symptomatology was assessed using the 15-item Geriatric Depression Scale.44

Dementia Questionnaire

The DQ is a semistructured interview comprising items that measure six domains: memory and cognition, expression (language), daily functioning, recognition of problems (insight), other medical and psychiatric difficulties, and education and demographic data.19 Compared with the results of antemortem clinical examinations, the DQ was shown to be sensitive to the presence of dementia (92.8% sensitivity), discriminate dementia from other neurological disorders causing functional impairment (89.5% specificity), and have high interrater reliability (κ = 0.96).45 Items from the memory and cognition, daily functioning, medical contacts, and other information domains were included: Did (Does) the subject have any problems with memory? Remembering people’s names? Recognizing familiar faces? Finding way about indoors? Finding way on familiar streets? Remembering a short list of items? Did (Does) the subject have any trouble with household tasks? Handling money (e.g., balancing checkbook, making change, paying bills, writing checks)? Grasping situations or explanations? Dressing or caring for self (including choosing clothes and tying shoes)? Feeding self (including cutting meat and buttering bread)? Getting out of bed and into a chair? Bathing (including getting in and out of a shower or tub and washing independently)? Ever receive medications for memory problems?

Driving Status Outcome

The primary outcome for these analyses was driving status of women who ever drove according to the proxy report on the DQ from the following items: Did she ever drive (yes/no), Did she ever stop driving (yes/no), Why did she stop driving? (gets lost or confused, poor eyesight, illness, bad coordination, slow reaction time, bad reflexes, frequent accidents, fear or nervous driving, other cognitive problems, other). For participants whose driving status was currently driving (e.g., ever drive = yes and ever stop driving = no), proxies were asked whether the participant was having any problems driving. If the proxy reported yes, he or she was queried further about the types of problems (same as above). Former drivers were those whose proxy reported ever stop driving, yes, and included the same reasons reported above for stopping driving.

Demographic Characteristics and Health Status

Demographic and health status characteristics included current age, race and ethnicity, education, annual family income, self-reported hypertension (defined as taking pills for treatment), self-reported diabetes mellitus type II, coronary artery disease (myocardial infarction, angina pectoris, revascularization procedure), adjudicated stroke (ischemic and hemorrhagic), Parkinson’s disease, visual impairment (cataracts, glaucoma, macular degeneration), and osteoarthritis. Health conditions were ascertained at baseline and during follow-up before the date that cognitive impairment was determined.

Statistical Analysis

Demographic and health status characteristics of women with any cognitive impairment (MCI or probable dementia) adjudicated using their most-recent cognitive assessment were compared according to driving status (currently driving or ceased driving) using the t-test or Wilcoxon rank-sum test for continuous variables and the chi-square test or Fisher exact test for categorical variables. The frequency of proxy-reported driving problems on the DQ in women with any cognitive impairment was reported according to driving status using the chi-square test or Fisher exact test, as was the frequency of cognitive and functional status deficits. The odds ratios (ORs) for current driving in participants with MCI or dementia according to demographic characteristics, health status, proxy report of cognitive or functional status from the DQ, and cognitive test performance were independently calculated using multiple logistic regression analyses. To further identify cognitive and functional status predictors of current driving status in women with cognitive impairment, ORs were calculated for current driving in participants with MCI or dementia using multiple logistic regression with backward elimination, with all variables with P < .25 entered as covariates into an initial model and then covariates with the highest P-values eliminated sequentially until all of the remaining covariates had P < .20. All OR models were adjusted for age, race, education, and depressive symptomatology. All analyses were conducted using SAS version 9.4 (SAS Institute, Inc., Cary, NC). All P-values were set at an alpha level of .05.

RESULTS

Women adjudicated with MCI or probable dementia during Year 1, 2, 3, or 4 of the WHIMS ECHO follow-up period were included in all analyses (N = 385). The mean time interval was 2.6 ± 2.4 months between the cognitive battery and the DQ, 6.3 ± 3.4 months between the DQ and adjudication, and 9.0 ± 4.6 overall. The frequency (percentage) of contact that the proxy reported was 77 (20.0%) lived together, 139 (36.1%) had daily contact, 87 (22.6%) had contact three or more times per week, and 82 (21.3%) had contact less than three times per week. Regarding the most-frequent type of contact, 123 (32.0%) reported mostly in-person contact, 64 (16.6%) reported mostly telephone contact, and 198 (51.4%) reported both types. Demographic factors, HT use, disease, depressive symptomatology, type of cognitive impairment, cognitive test scores, and proxy report of trouble driving of women with any cognitive impairment (MCI or probable dementia combined) were compared according to driving status (currently driving or ceased driving) (Table 1). Current drivers with any cognitive impairment were younger (83.1 ± 3.1 vs 84.3 ± 3.9, P < .001). Current and former drivers had similar percentages of women according to race (P = .07), level of education (P = .70), annual family income (P = .96), disease status (hypertension, hyperlipidemia, diabetes mellitus, coronary artery disease, Parkinson’s disease, visual impairment, or arthritis (all P > .20), and history of stroke (P = .09). Current drivers self-reported fewer depressive symptoms than former drivers median [(interquartile range (IQR)] 1(0.5–3) vs 3 (1–5). A higher percentage of current drivers had MCI (120, 60.0%) than dementia (80, 40.0%), whereas the opposite pattern held in former drivers MCI (58, 31.4%) or dementia (127, 68.6%) (P < .001). Women currently driving had significantly better global cognition according to the TICSm median (IQR) 27 (25–29) vs 25 (22–28) (P < .001), EBMT long delay median (IQR) 7 (3–8) vs 5 (0–8) (P < .002), TMT-A (seconds) median (IQR) 11 (9–12) vs 11 (9–14) (P < .01), verbal fluency—animals median (IQR) 12 (10–15) vs 11 (8–14) (P < .006), and Digit Span forward median (IQR) 6 (5–8) vs 7 (6–8) (P < .02) but not EBMT immediate recall, TMT-B (seconds) or Digit Span backward (all P > .10). Proxies reported that a lower percentage of current drivers had trouble driving (25.0%) than of former drivers (97.8%) (P < .001).

Table 1. Demographic and Health-Related Characteristics of Women with Any Cognitive Impairment (Mild Cognitive Impairment (MCI) and Probable Dementia Combined) According to Driving Status (N = 385).

Characteristic Current Drivers, n = 200 Former Drivers, n = 185 P-Value
Age, mean ± standard deviation 83.1 ± 3.1 84.3 ± 3.9 <.001
Race, n (%)
 Caucasian 172 (86.0) 170 (91.9)
 African American 17 (8.5) 13 (7.0)
 Other 11 (5.5) 2 (1.1) .07
Education, n (%)
 >High school 138 (69.0) 131 (70.8)
 ≤High school 56 (31.0) 54 (29.2) .70
Annual family income, $, n (%)
 <20,000 45 (25.6) 45 (25.6)
 20,000–49,999 106 (57.6) 99 (56.3)
 ≥50,000 33 (17.9) 32 (18.2) .96
Hormone therapy use, n (%) 97 (48.5%) 93 (50.3%) .69
Hypertension, n (%) 145 (72.5) 137 (74.1) .73
Hyperlipidemia, n (%) 78 (39.6) 73 (40.6) .85
Diabetes mellitus, n (%) 37 (18.5) 35 (18.9) .92
Coronary artery disease, n (%) 37 (18.5) 38 (20.5) .61
History of stroke, n (%) 8 (4.0) 15 (8.1) .09
Parkinson’s disease, n (%) 0 (0.0) 1 (0.6) .48
Visual impairment, n (%) 156 (78.0) 148 (81.3) .42
Arthritis, n (%) 153 (76.5) 149 (81.0) .28
Geriatric Depression Scale score, median (IQR) 1 (0.5–3) 3 (1–5) .004
Type of cognitive impairment
 MCI 120 (60.0) 58 (31.4)
 Probable dementia 80 (40.0) 127 (68.6) <.001
Cognitive test score, median (IQR)
 Modified Telephone Interview for Cognitive Status 27 (25–29) 25 (22–28) <.001
East Boston Memory Test
 Immediate recall 8 (7–9) 8 (6–9) .75
 Long delay 7 (3–8) 5 (0–8) .002
Trail-Making Test, seconds
 Part A 11 (9–12) 11 (9–14) .01
 Part B 80.5 (44.5–300) 93 (46–300) .16
Animal Fluency 12 (10–15) 11 (8–14) .006
Digit Span forward 6 (5–8) 7 (6–8) .02
Digit Span backward 5 (4–6) 5 (3–6) .70
Proxy report of trouble driving, n (%) 50 (25.0) 181 (97.8) <.001

IQR = interquartile range.

P-values based on t-test or Wilcoxon rank-sum test for continuous variables; chi-square test or Fisher exact test for categorical variables.

Women with any cognitive impairment (MCI and probable dementia combined) were compared according to driving status on frequency of driving problems that their proxy reported on the DQ (Table 2). Current women drivers with any cognitive impairment were less likely to get lost, have frequent accidents, display fearfulness when driving, display bad coordination, have other cognitive problems, have poor eyesight, or be ill (all P < .01).

Table 2. Driving Problems in Women with Any Cognitive Impairment (Mild Cognitive Impairment and Probable Dementia Combined) According to Proxy-Reported Driving Status on Dementia Questionnaire.

Current Drivers,
n = 199
Former Drivers,
n = 181
Driving Problem  n (%) P-
Value
Gets lost 17 (8.5) 38 (21.0) <.001

Frequent accidents 1 (0.5) 26 (14.4) <.001

Fearfulness 3 (1.5) 20 (11.1) <.001

Bad coordination 9 (4.5) 23 (12.7) .008

Other cognitive
problems
0 (0.0) 6 (3.3) .01

Poor eyesight 7 (3.5) 26 (14.4) <.001

Illness 1 (0.5) 10 (5.5) .007

P-value based on chi-square test or Fisher exact test.

Women with any cognitive impairment were compared according to driving status on frequency of functional limitations that their proxy reported on the DQ (Table 3). A lower percentage of current women drivers with cognitive impairment received medications for memory problems and had problems remembering people’s names, recognizing familiar faces, finding their way about indoors, finding their way on familiar streets, remembering a short list of items, performing household tasks, handling money, grasping situations or explanations, dressing or caring for themselves, feeding themselves, getting out of bed and into a chair, and bathing (all P < .01).

Table 3. Cognitive and Functional Deficits in Women with Any Cognitive Impairment (Mild Cognitive Impairment and Probable Dementia Combined) According to Proxy-Reported Driving Status on Dementia Questionnaire.

Question Current
Drivers,
n = 199
Former
Drivers,
n = 181
P-
Value
Did (does) the subject have any problems with:
 Memory? 170 (85.4) 157 (84.9) .88
 Remembering people’s
 names?
79 (40.1) 98 (53.0) .01
 Recognizing familiar
 faces?
14 (7.1) 34 (19.0) <.001
 Finding way about
 indoors?
6 (3.1) 20 (11.1) .006
 Finding way on familiar
 streets?
45 (23.4) 78 (46.7) <.001
 Remembering a short list
 of items?
77 (45.8) 105 (64.0) <.001
 Household tasks? 75 (37.9) 114 (63.0) <.001
 Handling money? 71 (37.6) 115 (64.3) <.001
 Grasping situations or
 explanations?
77 (38.9) 99 (54.7) .003
 Dressing of caring for
 self?
10 (5.1) 46 (25.1) <.001
 Feeding self? 1 (0.5) 16 (8.7) .0001
 Getting out of bed and
 into a chair?
34 (17.2) 52 (28.6) .005
 Bathing? 22 (11.4) 69 (38.6) <.001
Did she ever receive
medications for memory
problems?
27 (15.3) 65 (37.1) <.001

P-value based on chi-square test.

Table 4 presents ORs for current driving status separately for women with MCI and those with probable dementia, adjusting for age, race, education, and depressive symptoms using multiple logistic regression. Their demographic characteristics, general health status, proxy-reported functional limitations from the DQ, and the cognitive test battery were compared. In women with MCI, factors significantly associated with lower odds of continuing to drive were older age (OR = 0.87, 95% confidence interval (CI) = 0.79–0.96, P = .006), performing household tasks (OR = 0.30, 95% CI = 0.15–0.62, P = .001), grasping situations (OR = 0.44, 95% CI = 0.21–0.89, P = .02), dressing or caring for oneself (OR = 0.06, 95% CI = 0.01–1.30, P < .001), and bathing (OR = 0.20, 95% CI = 0.08–0.49, P < .001). No cognitive tests were significant (all P > .10).

Table 4. Odds of Current Driving in Women with Mild Cognitive Impairment (MCI) or Probable Dementia, Adjusted for Age, Race, Education, and Depressive Symptomatology Using Multiple Logistic Regression.

MCI, n = 178
Probable Dementia, n = 207
Characteristic aOR (95% CI) P-Value aOR (95% CI) P-Value
Demographic

 Age 0.87 (0.79–0.96) .006 0.93 (0.86–1.01) .10

 Nonwhite 1.33 (0.46–3.88) .60 2.12 (0.81–5.58) .13

 ≤High school education 1.10 (0.54–2.24) .79 1.05 (0.55–2.02) .89

 Annual family income, $ (reference < 20,000) .86 .61

 20,000–49,999 1.02 (0.45–2.33) 1.44 (0.64–3.20)

 ≥50,000 0.80 (0.28–2.31) 1.62 (0.58–4.51)

General health status

 History of stroke 0.94 (0.16–5.45) .94 0.47 (0.14–1.60) .23

 History of diabetes mellitus 1.19 (0.44–3.19) .73 0.83 (0.41–1.69) .61

 History of arthritis 0.54 (0.23–1.28) .16 0.84 (0.40–1.75) .64

Dementia Questionnaire items

 Memory and cognition

  Remembering names 1.42 (0.67–3.03) .35 0.46 (0.25–0.83) .01

  Recognizing faces 0.40 (0.12–1.32) .13 0.36 (0.15–0.90) .03

  Finding way indoors 0.13 (0.01–1.41) .09 0.40 (0.14–1.18) .10

  Finding way on familiar streets 0.56 (0.22–1.46) .24 0.45 (0.24–0.84) .01

  Remembering short list 0.68 (0.31–1.50) .34 0.65 (0.33–1.31) .23

 Daily functioning

  Household tasks 0.30 (0.15–0.62) .001 0.70 (0.37–1.33) .27

  Handling money 0.60 (0.26–1.38) .23 0.44 (0.22–0.85) .02

  Grasping situations 0.44 (0.21–0.89) .02 0.95 (0.52–1.74) .86

  Dressing or caring for self 0.06 (0.01–0.30) <.001 0.32 (0.13–0.75) .002

  Getting out of bed into a chair 0.79 (0.32–1.95) .61 0.74 (0.37–1.49) .40

  Bathing 0.20 (0.08–0.49) <.001 0.27 (0.13–0.58) <.001

Medications for memory problems 0.34 (0.11–1.05) .06 0.42 (0.21–0.81) .003

Cognitive tests

 Modified Telephone Interview for Cognitive Status 0.98 (0.87–1.11) .79 1.17 (1.07–1.27) <.001

East Boston Memory Test

 Immediate recall 0.88 (0.74–1.04) .14 1.07 (0.93–1.22) .35

 Long delay 1.03 (0.93–1.13) .62 1.11 (1.02–1.21) .02

Trail-Making Test, secondsa

 Part A 1.01 (0.92–1.11) .80 1.10 (1.01–1.19) .02

 Part B 1.00 (0.996–1.002) .36 1.00 (0.999–1.004) .12

Animal fluency 0.97 (0.90–1.05) .43 1.14 (1.05–1.22) .001

Digit Span forward 0.94 (0.79–1.11) .45 0.91 (0.81–1.03) .14

Digit Span backward 1.01 (0.87–1.17) .92 1.03 (0.92–1.16) .62

aOR = adjusted odds ratio; CI = confidence interval.

a

Scores were subtracted from 0 so that higher scores indicate better performance.

A different pattern emerged in women with probable dementia (Table 4). Factors significantly associated with lower odds of continuing to drive in these women were remembering names (OR = 0.46, 95% CI = 0.25–0.83, P = .01), recognizing faces (OR = 0.36, 95% CI = 0.15–0.90, P = .03), finding way on familiar streets (OR = 0.45, 95% CI = 0.24–0.84, P = .01), handling money (OR = 0.44, 95% CI = 0.22–0.85, P = .02), dressing or caring for oneself (OR = 0.32, 95% CI = 0.13–0.75, P = .002), bathing (OR = 0.27, 95% CI = 0.13–0.58, P < .001), and taking medications for memory problems (OR = 0.42, 95% CI = 0.21–0.81, P = .003). Better scores on TICSm (OR = 1.17, 95% CI = 1.07–1.27, P < .001), EBMT long delay (OR = 1.11, 95% CI = 1.02–1.21, P = .02), TMT-A (seconds) (OR = 1.10, 95% CI = 1.01–1.19, P = .02), and verbal fluency—animals (OR = 1.14, 95% CI = 1.05–1.22, P = .001) were associated with greater odds of continuing to drive.

Table 5 presents ORs for current driving status separately for women with MCI and those with probable dementia, adjusting for age, race, education, and depressive symptoms using multiple logistic regression with backward elimination in two models: functional limitations and cognitive tests. In MCI Model 1, lower odds of continuing to drive were significantly associated with functional limitations in household tasks (OR = 0.32, 95% CI = 0.12–0.85), grasping situations (OR = 0.30, 95% CI = 0.12–0.80), and dressing or caring for oneself (OR = 0.06, 95% CI = 0.01–0.67) (all P = .02), as well as taking medications for memory problems (OR = 0.12, 95% CI = 0.03–0.53, P = .004). In probable dementia Model 1, lower odds of continuing to drive were significantly associated with functional limitations in handling money (OR = 0.34, 95% CI = 0.13–0.86, P = .02) and taking medications for memory problems (OR = 0.32, 95% CI = 0.14–0.74, P = .008).

Table 5. Odds of Current Driving in Women with Mild Cognitive Impairment (MCI) or Probable Dementia Adjusted for Age, Race, Education, and Depressive Symptomatology Using Multiple Logistic Regression with Backward Elimination.

MCI, n = 178
Probable Dementia, n = 207
Model aOR (95% CI) P-Value aOR (95% CI) P-Value
1: Dementia Questionnaire items

 Remembering names 0.49 (0.22–1.08) .08

 Finding way on familiar streets 0.42 (0.11–1.55) .19 0.50 (0.23–1.12) .09

 Household tasks 0.32 (0.12–0.85) .02

 Handling money 0.34 (0.13–0.86) .02

 Grasping situations 0.30 (0.12–0.80) .02

 Dressing or caring for self 0.06 (0.01–0.67) .02

 Bathing 0.44 (0.13–1.50) .19 0.44 (0.16–1.18) .10

 Medications for memory problems 0.12 (0.03–0.53) .004 0.32 (0.14–0.74) .008

2: Cognitive tests

 Modified Telephone Interview for Cognitive Status 1.14 (1.03–1.26) .01

East Boston Memory Test

 Immediate recall 0.88 (0.74–1.04) .14

 Long delay 1.07 (0.97–1.17) .19

 Trail-Making Test Part A, secondsa 1.08 (0.98–1.19) .11

 Animal fluency 1.07 (0.98–1.17) .12

 Digit Span forward 0.84 (0.73–0.97) .02

aOR = adjusted odds ratio; CI = confidence interval.

All variables with P < .25 from Table 4 were entered as covariates into an initial model, then covariates with the highest P-values were eliminated sequentially until all of the remaining covariates had P < .20; age, race, education, and depression score were forced to remain in all models.

a

Scores were subtracted from 0 so that higher score indicate better performance.

In MCI Model 2, none of the cognitive tests were significantly associated with odds of continuing to drive, whereas in probable dementia Model 2, the TICSm was significantly associated (OR = 1.14, 95% CI = 1.03–1.26, P = .01). Better scores on Digit Span forward were associated with slightly lower odds of continuing to drive (OR = 0.84, 95% CI = 0.73–0.97, P = .02), probably because women with dementia had scores similar to those of women with MCI on this measure (Table 1).

DISCUSSION

This study examined proxy reports of driving status and cognitive and functional limitations, as well as cognitive performance data, of women with adjudicated MCI and probable dementia in WHIMS. A notable finding of this study was that 40% of women with dementia and 60% of women with MCI were current drivers. This is higher than some prior reports of driving status in women in the United States with Alzheimer’s type dementia (20–30%),4,46 although prevalence data on driving, dementia, and sex are sparse. In the United States, many individuals of both sexes retain their licenses into late life, although men and women aged 80 and older account for only 1.5% to 2% of all drivers, and there are more women than men currently driving in this older age group47 Driving prevalence in older adults with MCI and dementia is underresearched and deserves further investigation.

In women with MCI (after adjusting for important confounds), proxy-reported other functional limitations were associated with lower odds of continuing to drive, whereas proxy-reported cognitive limitations and cognitive test performance were not. Women with MCI who had difficulty in proxy-reported IADLs (household tasks, grasping situations) and ADLs (dressing and caring for oneself, bathing) were less likely to be current drivers; this finding held in backward elimination models. This pattern of findings demonstrates that proxy-reported difficulty in other IADLs is associated with driving status and that perhaps basic changes in self-care may be cues to family and friends that cognitive changes are occurring. It is also consistent with reports that self-reported limitations in IADLs are associated with lower odds of current driving in women without cognitive impairment.48 It is probably difficult to disentangle the meaning of proxy-reported changes in basic self-care items that measure dressing or caring for oneself in persons with MCI, because these changes could be subtle. Similarly, grasping situations that occur in the context of performing a daily life task could reflect a decline in ability to understand what to do in an unfamiliar situation (e.g., using automated checkout at the grocery store for the first time). An alternative explanation for these findings is that subtle changes in cognitive function may not be as predictive of driving behavior as other IADLs function in MCI, although one observational study cannot confirm this. An interesting topic for future research is the construct validity of proxy measures of functional status. The current study found that proxy-reported functional status (e.g., other IADLs) is associated with driving status in women with MCI.

In contrast, in women with probable dementia, proxy-reported functional limitations and proxy-reported and performance-based cognitive limitations were associated with lower odds of continuing to drive. Women with dementia who had difficulty in proxy-reported IADLs (e.g., handling money) and ADLs (e.g., dressing or caring for oneself, bathing) were less likely to be currently driving. Although causal links between IADLs could not be established in this study, prior studies have found a correlation between self-reported performance on complex IADLs such as financial management and driving.20 Proxy-reported cognitive limitations involving memory and orientation (e.g., recognizing faces, remembering names, finding way on familiar streets) were also associated with lower odds of continuing to drive. Problems with facial recognition and finding way about familiar locations are hallmarks of dementia.49 Women with dementia who performed better on tests of global cognition, verbal fluency, long-term memory, and attention were more likely to be current drivers, as expected. In separate backward elimination models controlling for age, race, education, and depressive symptomatology, proxy-reported functional limitations (handling money) were the best predictor of current driving status, followed by finding way on familiar streets. In the cognitive performance model, global cognitive function was the best predictor of current driving status, followed by short-term memory.

Older age was the only factor associated with lower odds of driving, and only in women with MCI; all other demographic and health status factors were nonsignificant predictors of continued driving in MCI and probable dementia. Proxies were in agreement that overall, current drivers had less trouble driving than individuals who had stopped driving. In addition, proxy reports on the DQ of driver problems (getting lost, having frequent accidents, displaying fearfulness when driving, displaying bad coordination, having other cognitive problems, poor eyesight, illness) were in the expected direction according to driving status, validating that individuals who have stopped driving had a greater frequency of driving problems. A limitation of the study is that the DQ was used to determine case status, limiting the assumption that these women are representative of all older women with MCI and dementia, although the cognitive data (the cutpoint on the global cognitive screening measure and the individual cognitive tests) are used as primary classification tools in the adjudication process. Although there are also limitations with self-report and proxy-reported measures, proxy reports of IADL limitations, including driving, may aid physician referral for performance-based driving assessments and evaluation by driver rehabilitation specialists such as occupational therapists.

In conclusion, a significant proportion of women with MCI and probable dementia are current drivers. When proxy reports of cognitive and functional limitations were compared with cognitive performance in women with MCI and dementia, proxy reports of other IADL and ADL limitations were associated with driving status in women with MCI, whereas all types of measures (proxy report of functional and cognitive limitations and performance-based cognitive testing) were associated with driving status in dementia. In the absence of sensitive computerized cognitive tasks, proxy reports of other functional limitations may be associated with continued driving ability in MCI and thus could prompt a discussion regarding driving transition, whereas a broader range of measurement tools may be descriptive of continued driving ability in dementia. It has not been established that drivers with MCI are unsafe. These findings have clinical implications for driving referral and assessment, in particular for choosing the type of assessment tool based on the severity of cognitive impairment. This study demonstrates the value of triangulating results obtained through multiple methods of report to ensure accurate assessment, of using proxy report of functional limitations such as driving in physician referral to driver rehabilitation specialists and of evaluating driving behavior within the context of overall daily-life function. Future work is needed to determine whether proxy report of cognitive and functional impairments including driving can guide referrals to driver rehabilitation or counseling for driving transition.

ACKNOWLEDGMENTS

WHIMS was funded by National Heart, Lung and Blood Institute Contract HHSN-268–2004–6-4221C through the initial follow-up period, WHIMS-ECHO is funded by National Institute on Aging Contract HHSN-271–2011–00004C, and the WHI program is funded by the National Heart, Lung and Blood Institute, U.S. Department of Health and Human Services. These results were presented at the Gerontological Society of America annual conference in 2013.

Sponsor’s Role: The National Institute on Aging had no role in the design or conduct of the current study; management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript.

Footnotes

Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper.

Author Contributions: Vaughan: study design, interpretation of results, writing the manuscript. Hogan: data analysis. Hogan, Rapp, Dugan, Marottoli, Snively, Shumaker, Sink: critical feedback. Sink, Rapp: study concept.

REFERENCES

  • 1.Brown LB, Ott BR. Driving and dementia: A review of the literature. J Geriatr Psychiatry Neurol. 2004;17:232–240. doi: 10.1177/0891988704269825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Gold DA. An examination of instrumental activities of daily living assessment in older adults and mild cognitive impairment. J Clin Exp Neuropsychol. 2012;34:11–34. doi: 10.1080/13803395.2011.614598. [DOI] [PubMed] [Google Scholar]
  • 3.Rajan KB, Hebert LE, Scherr PA, et al. Disability in basic and instrumental activities of daily living is associated with faster rate of decline in cognitive function of older adults. J Gerontol A Biol Sci Med Sci. 2013;68A:624–630. doi: 10.1093/gerona/gls208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Croston J, Meuser TM, Berg-Weger M, et al. Driving retirement in older adults with dementia. Top Geriatr Rehabil. 2009;25:154–162. doi: 10.1097/TGR.0b013e3181a103fd. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Foley DJ, Heimovitz HK, Guralnik JM, et al. Driving life expectancy of persons aged 70 years and older in the United States. Am J Public Health. 2002;92:1284–1289. doi: 10.2105/ajph.92.8.1284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Lucca U, Tettamanti M, Logroscino G, et al. Prevalence of dementia in the oldest old: The Monzino 80-plus population based study. Alzheimers Dement. 2015;11:258–270. doi: 10.1016/j.jalz.2014.05.1750. [DOI] [PubMed] [Google Scholar]
  • 7.Duchek JM, Carr DB, Hunt L, et al. Longitudinal driving performance in early-stage dementia of the Alzheimer type. J Am Geriatr Soc. 2003;51:1342–1347. doi: 10.1046/j.1532-5415.2003.51481.x. [DOI] [PubMed] [Google Scholar]
  • 8.Lafont S, Laumon B, Helmer C, et al. Driving cessation and self-reported car crashes in older drivers: The impact of cognitive impairment and dementia in a population-based study. J Geriatr Psychiatry Neurol. 2008;21:171–182. doi: 10.1177/0891988708316861. [DOI] [PubMed] [Google Scholar]
  • 9.Man-Son-Hing M, Marshall SC, Molnar FJ, et al. Systematic review of driving risk and the efficacy of compensatory strategies in persons with dementia. J Am Geriatr Soc. 2007;55:878–884. doi: 10.1111/j.1532-5415.2007.01177.x. [DOI] [PubMed] [Google Scholar]
  • 10.Wadley VG, Okonkwo O, Crowe M, et al. Mild cognitive impairment and everyday function: An investigation of driving performance. J Geriatr Psychiatry Neurol. 2009;22:87–94. doi: 10.1177/0891988708328215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Ott BR, Daiello LA. How does dementia affect driving in older patients? Aging Health. 2010;6:77–85. doi: 10.2217/ahe.09.83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Carr DB, Schwartzberg JG, Manning L, et al. Physician’s Guide to Assessing and Counseling Older Drivers. 2nd Ed. National Highway Traffic Safety Administration; Washington, DC: 2010. [Google Scholar]
  • 13.Kay L, Bundy A, Clemson L. Predicting fitness to drive in people with cognitive impairments by using DriveSafe and DriveAware. Arch Phys Med Rehabil. 2009;90:1514–1522. doi: 10.1016/j.apmr.2009.03.011. [DOI] [PubMed] [Google Scholar]
  • 14.Hines A, Bundy AC. Predicting driving ability using DriveSafe and DriveAware in people with cognitive impairments: A replication study. Aust Occup Ther J. 2014;61:224–229. doi: 10.1111/1440-1630.12112. [DOI] [PubMed] [Google Scholar]
  • 15.Dugan E. The Driving Dilemma. Harper Collins; New York: 2006. [Google Scholar]
  • 16.National Highway Traffic Safety Administration Driving Transitions Education: Tools, Scripts, and Practice Exercises (DOT HS 811 152) National Highway Traffic Safety Administration; Washington, DC: 2009. [Google Scholar]
  • 17.Perkinson MA, Berg-Weger ML, Carr DB, et al. Driving and dementia of the Alzheimer type: Beliefs and cessation strategies among stakeholders. Gerontologist. 2005;45:676–685. doi: 10.1093/geront/45.5.676. [DOI] [PubMed] [Google Scholar]
  • 18.Wheatley CJ, Carr DB, Marottoli RA. Consensus statements on driving for persons with dementia. Occup Ther Health Care. 2014;28:132–139. doi: 10.3109/07380577.2014.903583. [DOI] [PubMed] [Google Scholar]
  • 19.Kawas C, Segal J, Stewart WF, et al. A validation study of the Dementia Questionnaire. Arch Neurol. 1994;51:901–906. doi: 10.1001/archneur.1994.00540210073015. [DOI] [PubMed] [Google Scholar]
  • 20.Vaughan L, Giovanello K. Executive function in daily life: Age-related influences of executive processes on instrumental activities of daily living. Psychol Aging. 2010;25:343–355. doi: 10.1037/a0017729. [DOI] [PubMed] [Google Scholar]
  • 21.Albert SM, Bear-Lehman J, Burkhardt A, et al. Variation in sources of clinician-rated and self-rated instrumental activities of daily living disability. J Gerontol A Biol Sci Med Sci. 2006;61A:826–831. doi: 10.1093/gerona/61.8.826. [DOI] [PubMed] [Google Scholar]
  • 22.Farias ST, Mungas D, Jagust W. Degree of discrepancy between self and other-reported everyday functioning by cognitive status: Dementia, mild cognitive impairment, and healthy elders. Int J Geriatr Psychiatry. 2005;20:827–834. doi: 10.1002/gps.1367. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Prentice R, Rossouw J, Furberg C, et al. Design of the WHI Clinical Trial and Observational Study. Control Clin Trials. 1998;19:61–109. doi: 10.1016/s0197-2456(97)00078-0. [DOI] [PubMed] [Google Scholar]
  • 24.Shumaker SA, Reboussin BA, Espeland MA, et al. The Women’s Health Initiative Memory Study (WHIMS): A trial of the effect of estrogen therapy in preventing and slowing the progression of dementia. Control Clin Trials. 1998;19:604–621. doi: 10.1016/s0197-2456(98)00038-5. [DOI] [PubMed] [Google Scholar]
  • 25.Espeland MA, Rapp SR, Shumaker SA, et al. Conjugated equine estrogens and global cognitive function in postmenopausal women: Women’s Health Initiative Memory Study. JAMA. 2004;291:2959–2968. doi: 10.1001/jama.291.24.2959. [DOI] [PubMed] [Google Scholar]
  • 26.Rapp SR, Espeland MA, Shumaker SA, et al. The effect of estrogen plus progestin on global cognitive function in postmenopausal women: The Women’s Health Initiative Memory Study, a randomized controlled trial. JAMA. 2003;289:22663–22672. doi: 10.1001/jama.289.20.2663. [DOI] [PubMed] [Google Scholar]
  • 27.Shumaker SA, Legault C, Rapp SR, et al. Estrogen plus progestin and the incidence of dementia and mild cognitive impairment in postmenopausal women: The Women’s Health Initiative Memory Study, a randomized controlled trial. JAMA. 2003;289:2651–2662. doi: 10.1001/jama.289.20.2651. [DOI] [PubMed] [Google Scholar]
  • 28.Shumaker SA, Legault C, Kuller L, et al. Conjugated equine estrogens and incidence of probable dementia and mild cognitive impairment in postmenopausal women: Women’s Health Initiative Memory Study. JAMA. 2004;291:2947–2958. doi: 10.1001/jama.291.24.2947. [DOI] [PubMed] [Google Scholar]
  • 29.Anderson GL, Limacher M, Assaf AR, et al. Women’s Health Initiative Steering Committee. Effects of conjugated equine estrogen in postmenopausal women with hysterectomy: The Women’s Health Initiative randomized controlled trial. JAMA. 2004;291:1701–1712. doi: 10.1001/jama.291.14.1701. [DOI] [PubMed] [Google Scholar]
  • 30.Rossouw JE, Anderson GL, Prentice RL, et al. Risks and benefits of estrogen plus progestin in healthy postmenopausal women: Principal results From the Women’s Health Initiative randomized controlled trial. JAMA. 2002;288:321–333. doi: 10.1001/jama.288.3.321. [DOI] [PubMed] [Google Scholar]
  • 31.Rapp SR, Legault C, Espeland MA, et al. Validation of a cognitive assessment battery administered over the telephone. J Am Geriatr Soc. 2012;60:1616–1623. doi: 10.1111/j.1532-5415.2012.04111.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Brandt J, Spencer M, Folstein MF. The telephone interview for cognitive status. Neuropsychiatry Neuropsychol Behav Neurol. 1988;1:111–117. [Google Scholar]
  • 33.Welsh KA, Breitner JC, Magruder-Habib KM. Detection of dementia in the elderly using telephone screening of cognitive status. Neuropsychiatry Neuropsychol Behav Neurol. 1993;6:103–110. [Google Scholar]
  • 34.Petersen RC, Smith GE, Waring SC. Aging, memory, and mild cognitive impairment. Int Psychogeriatr. 1997;9(Suppl 1):65–69. doi: 10.1017/s1041610297004717. [DOI] [PubMed] [Google Scholar]
  • 35.American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association; Washington, DC: 1994. [Google Scholar]
  • 36.De Jager CA, Budge MM, Clarke R. Utility of TICS-M for the assessment of cognitive function in older adults. Int J Geriatr Psychiatry. 2003;18:318–324. doi: 10.1002/gps.830. [DOI] [PubMed] [Google Scholar]
  • 37.Knopman DS, Roberts RO, Geda YE, et al. Validation of the telephone interview for cognitive status-modified in subjects with normal cognition, mild cognitive impairment, or dementia. Neuroepidemiology. 2010;34:34–42. doi: 10.1159/000255464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Folstein MF, Folstein SE, McHugh PR. ‘Mini-mental state’ A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–198. doi: 10.1016/0022-3956(75)90026-6. [DOI] [PubMed] [Google Scholar]
  • 39.Albert M, Smith LA, Scherr PA, et al. Use of brief cognitive tests to identify individuals in the community with clinically diagnosed Alzheimer’s disease. Int J Neurosci. 1991;57:167–178. doi: 10.3109/00207459109150691. [DOI] [PubMed] [Google Scholar]
  • 40.Mrazik M, Millis S, Drane DL. The oral trail-making test: Effects of age and concurrent validity. Arch Clin neuropsychol. 2010;25:236–243. doi: 10.1093/arclin/acq006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Reitan R. Trail Making Test: Manual for Administration and Scoring. Reitan Neuropsychological Laboratory; Tucson, AZ: 1975. [Google Scholar]
  • 42.Benton A. Differential behavioral effects in frontal lobe disease. Neuropsychologia. 1968;6:53–60. [Google Scholar]
  • 43.Wechsler D. WAIS-R Manual. Psychological Corporation; New York: 1981. [Google Scholar]
  • 44.Yesavage JA. Geriatric depression scale. Psychopharm Bull. 1988;24:709–711. [PubMed] [Google Scholar]
  • 45.Ellis RJ, Jan K, Kawas C, et al. Diagnostic validity of the dementia questionnaire for Alzheimer disease. Arch Neurol. 1998;55:360–365. doi: 10.1001/archneur.55.3.360. [DOI] [PubMed] [Google Scholar]
  • 46.Talbot A, Bruce I, Cunningham CJ, et al. Driving cessation in patients attending a memory clinic. Age Ageing. 2005;34:363–368. doi: 10.1093/ageing/afi090. [DOI] [PubMed] [Google Scholar]
  • 47.U.S. Department of Transportation . Highway Statistics 2012: Licensed Drivers, Vehicle and Populations. Federal Highway Administration; Washington, DC: 2013. [Google Scholar]
  • 48.Dugan B, Lee CM. Biopsychosocial risk factors for driving cessation: Findings from the Health and Retirement Study. J Aging Health. 2013;25:1313–1328. doi: 10.1177/0898264313503493. [DOI] [PubMed] [Google Scholar]
  • 49.Della Sala S, Muggia S, Spinnler H, et al. Cognitive modelling of face processing: Evidence from Alzheimer patients. Neuropsychologia. 1995;33:675–687. doi: 10.1016/0028-3932(95)00009-r. [DOI] [PubMed] [Google Scholar]

RESOURCES