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RESEARCH AND PRACTICE |
Ellen E. Freeman, Beatriz Muñoz, and Sheila K. West are with the Dana Center for Preventive Ophthalmology, Wilmer Eye Institute, Johns Hopkins University, Baltimore, Md. Stephen J. Gange is with the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore.
Correspondence: Requests for reprints should be sent to Sheila West, Dana Center for Preventive Ophthalmology, Room 129, Wilmer Eye Institute, Johns Hopkins University, 600 N Wolfe St, Baltimore, MD 21205 (e-mail: shwest{at}jhmi.edu).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Objectives. Given the importance of driving in American society, older non-drivers may be unable to meet basic needs while living independently. We assessed whether not driving is an independent risk factor for entering long-term care (LTC) institutions.
Methods. Data were used from 1593 older adults who participated in the Salisbury Eye Evaluation cohort study and completed an additional telephone survey. Questions on driving status and LTC entry were obtained by self/proxy report. Cox time-dependent regression procedures were used to adjust for demographic and health factors.
Results. Former and never drivers had higher hazards of LTC entry after adjustment for demographic and health variables (hazard ratio [HR]=4.85; 95% confidence interval [CI]=3.26, 7.21; and HR=3.53; 95% CI=1.89, 6.58, respectively). Also, having no other drivers in the house was an independent risk factor for LTC entry (HR=1.72; 95% CI=1.15, 2.57).
Discussion. Older adults are expected to make good decisions about when to stop driving, but the hardships imposed on older adults by not driving are not widely recognized. Innovative strategies to improve transportation options for older adults should be considered.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Ideally, the public transportation system, including buses, railways, and shuttles, could provide an alternative to driving for older adults. However, an estimated 40% of older adults in rural areas have no access to public transportation services and another 25% have negligible access.2 Two national studies estimate that older people use public transportation for only 2% to 3% of their trips.3,4 Many elderly people instead rely on informal transportation support from friends and family5 but at the same time may feel concerned about being a burden to others and thus, limit their activities.
Certain subgroups of older adults may be more susceptible to transportation problems after giving up driving. For example, one study of older people with dementia who had recently given up driving found that those who were unmarried or with no other licensed drivers in the household were more likely to report transportation problems.5 Other populations who may be more susceptible to problems are those in rural areas, where there may be little or no public transportation.
Some older adults may have no other choice but to enter long-term care (LTC) institutions because of transportation problems, despite being otherwise able to function independently inside the home. Entry into LTC is extremely expensive, as the average annual cost for nursing home admission is now $69 000 and the average annual cost of assisted living entry is $30 000.6
Some studies have examined the consequences of driving cessation and have found them to include increased levels of depression7,8 and decreased out-of-home activity levels.9 Whether driving status increases a person’s risk of LTC entry is unknown, although such factors as "needing aid to get around"10 and "getting out" less than daily,11 which may include not driving, have been associated with nursing home entry in previous studies.
The purpose of this study was to assess whether not driving was an independent risk factor for entering LTC in a small city on the eastern shore of Maryland. To accomplish this aim, we utilized data from the Salisbury Eye Evaluation (SEE) project, a prospective population-based cohort study collecting data over 8 years.12
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METHODS |
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Baseline data (round 1) were collected between 1993 and 1995. Follow-up data were collected at 2 years (round 2), 6 years (round 3), and 8 years (round 4) after baseline.
Questionnaire and Clinic Examination
Interviewer-administered questionnaires collected data from participants at each of the 4 rounds. They asked questions on demographic information, medical history, and driving history. At each round, proxies were identified who could be contacted for information about the participant. Questions on driving history asked about having ever driven, miles driven in the past year, and having stopped driving. Participants were asked if a physician had ever told them that they had any of 15 possible medical conditions like diabetes, high blood pressure, cancer, arthritis, or fracture. They were also asked if they needed help with such care needs as eating, bathing, dressing, or getting around the home. Cognitive status was measured with the Mini-Mental State Examination, in which higher scores indicate better cognition.16 Depressive symptoms were assessed with the General Health Questionnaire part D.17
An additional questionnaire was administered by telephone in the summer of 2003 to improve data on driving and entry into LTC. Participants or their proxies were asked the month and year that driving had stopped and how many other people who lived with the participant were able to drive a car at the times of each of the 4 rounds. Participants were also asked if they had entered LTC, if the duration had been more than 3 months, and the type of LTC facility. We were not able to obtain data on noninstitutional LTC services. Subject–proxy agreement was found to be very good for the questions on other drivers in the house at each of 4 rounds (
0.8), date of driving cessation (Pearson r= 0.9), and date of LTC entry (Pearson r= 0.9) in a subsample of 39 individuals and their designated proxies.
Definitions
The date of driving cessation was obtained in the following way: the participant or proxy was asked in 2003 if he/she/participant had driven in the last 6 months (or the last 6 months before death). If not, the month and year of the last time the participant drove were used as the date of driving cessation. If participants had driven in the last 6 months (or 6 months before death), they were coded as drivers for the entire follow-up.
LTC was defined as entry for more than 3 months into a nursing home, assisted living facility, or retirement home that offered meals or transportation services. A nursing home was defined as an institution offering skilled nursing services, an assisted living facility as a building with connected units in which meals and unskilled nursing services were offered, and a retirement home as independent, unconnected units in which meals or transportation services were offered. If a person lived in a retirement home without meals or transportation services, the person was not considered to be in LTC for the purposes of this analysis. The 3-month time requirement was intended to filter out individuals who only entered an institution for recuperation from an acute event or someone who entered for hospice care. Thus, if someone entered LTC for 3 months or less, the person was not considered to have entered LTC for these analyses.
Depressive symptoms were defined as a report of 1 or more affirmative responses, using binary scoring, out of 7 questions on part D of the General Health Questionnaire.
Statistical Analysis
Those we were unable to contact for the summer 2003 survey were compared with those we were able to contact. Age-adjusted logistic regression was used to determine if any differences between the 2 groups that differed in contact status were due solely to age. Next, baseline characteristics were compared by driving status (never, former, and current drivers) and by LTC entry status (no entry, entry into nursing home, entry into assisted living or retirement home). Age-adjusted polychotomous logistic regression was used to determine if any differences between the 3 groups were solely because of age.
The crude risk of ever entering a LTC facility was calculated by comparing the cumulative incidence of LTC entry among those at baseline who reported never, former, or current driving. We used Kaplan–Meier estimates and a Cox regression model to compare the impact of driving status on time until long-term care entry. Time zero was entry into the SEE study. Those who had not entered LTC by June 2003 were censored at that time or (if deceased) at their date of death. On the basis of several prospective cohort studies, the risk of nursing home entry is thought to be a function of demographic factors (like age and race), social factors (like marital status, size of social network), and health variables (like needing help with activities of daily living [ADLs], cognitive impairment, stroke).10,11,18–22 Therefore, to try to isolate the relation of driving variables and LTC entry, we adjusted with Cox regression for potential confounders including age, gender, race, marital status, needing help with ADLs, cognitive functioning, number of comorbid conditions, and depressive symptoms. Variables that changed with time (driving status, marital status, ADL help, cognitive status, depressive symptoms, number of comorbid conditions, other drivers in the house) were entered into the model as time dependent by splitting the observation time for each individual into periods when the exposure values were constant. There were 11 individuals who stopped driving the same month and year as they entered LTC. To be conservative, these individuals were considered current drivers for their entire follow-up (their exposure was not changed).
Having no other drivers in the house was assessed as an independent risk factor as well as an effect modifier through stratification and the inclusion of an interaction term. Other variables that were evaluated for effect modification included needing ADL help, gender, cognitive impairment, age category, and race.
Secondary analyses were conducted to determine if the relation between driving status and LTC entry differed by type of LTC (nursing home compared with non–nursing home). Sensitivity analyses were done to determine if excluding those participants who may have been cognitively impaired (more than 3 errors on the Short Portable Mental Status Questionnaire23) at the time of the summer 2003 survey affected the results.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Of the 1593 individuals from whom we obtained interviews about LTC entry, at baseline 1347 (85%) were current drivers, 160 (10%) were former drivers, and 86 (5%) never drove (Table 1
). The proportion of never drivers and former drivers at baseline who entered LTC was 17% and 13%, respectively, and the proportion of current drivers who entered was 8% (Table 1). Former drivers and those who never drove tended to be older and were more likely to be female, African American, cognitively impaired, and depressed than current drivers. In addition, former drivers were more likely to have a greater average number of co-morbidities and to have been more likely to need help with ADLs than current drivers (Table 1). Of the 1347 current drivers at baseline, 299 (22%) stopped driving during the study. The percentage of participants with no other drivers in the house increased in each round from 33% in round 1 to 47% by round 4. The percentage also differed by gender, as 58% of women had no other drivers in the house by round 4 compared with 29% of men.
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). Those who entered a non–nursing home type of LTC were also older, more likely to be female and White, less likely to be cognitively impaired, and less likely to have had other drivers in the house than those who did not enter LTC (Table 2).
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, the Kaplan–Meier time-to-event curves are plotted by driving status at baseline. The curves that represent the former and never drivers show a shorter time to LTC entry compared with the current drivers (logrank test, P< .001).
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, Model 1). Also, individuals with no other drivers in the house were also more likely to enter LTC than those with 1 or more other drivers in the house (HR=1.72, 95% CI=1.15, 2.57). Driving status did not modify the relation between no other drivers in the house and LTC entry. In fact, no statistically significant interaction terms were identified.
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Because 15% (n=232) of the participants were married or living together, the probability of entering LTC may not have been independent among participants. Therefore, a sensitivity analysis was done to exclude the second member of the household in a random fashion. The associations between the driving variables and LTC entry were essentially unchanged.
When those individuals who may have had cognitive impairment at the time of our follow-up telephone survey (missed more than 3 questions on the Short Portable Mental Status Questionnaire) were excluded from the analysis (n = 64), the results were essentially unchanged. These results provided reassurances that the data we collected from this older population were not affected by cognitive impairment.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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We evaluated the concern that someone who stops driving may do so for poor health reasons and that the association between former drivers and LTC entry is due to the residual confounding of health factors rather than the inability to drive. If this were true, we would not expect to see an association between never drivers and LTC entry. However, never drivers were also more likely to enter LTC, and the never drivers were in better health at baseline than the former drivers. In addition, we adjusted for such variables as ADL help, number of co-morbidities, depressive symptoms, and cognitive impairment in a time-dependent manner, and the association between driving and LTC entry remained strong. However, driving cessation may in part be a marker for severity of these health conditions, because once driving status was entered into the model, the relation with ADL help was no longer significant, and the hazard ratios were attenuated for the other health variables as well. Alternately, it may be that driving cessation acts as an intervening variable in the pathway from these health variables to LTC entry.
We were unable to contact 36% of individuals to ask about LTC entry or availability of other drivers in the house in the summer 2003 survey. Therefore, it is important to determine if selection bias influenced our results. Those we were unable to contact tended to be older and sicker and less likely to have other adults in the house. These factors suggest that they were probably more likely to have entered LTC than those we were able to contact. We have some data to support this assumption. SEE data that are available on the 8-year risk of nursing home admission indicate that those we were unable to contact were more likely to enter a nursing home than those we were able to contact (10% vs 3%). In addition, those we were unable to contact were more likely to be nondrivers at baseline. Therefore, the inclusion of these individuals in the study likely would have resulted in a stronger association between nondrivers and LTC entry. Also, because those whom we were unable to contact were less likely to have other adults in the house, it is reasonable to assume that they were probably also less likely to have other drivers in the house. Therefore, it is likely that our association between no other drivers in the house and LTC entry would also be upheld.
The retrospective nature of the 2003 survey on LTC entry, driving cessation, and whether there were other drivers in the house may also be a limitation. Because of the older study population and the 10-year follow-up time, there is likely to be some measurement error. However, given the life impact of events such as LTC entry and driving cessation and the objective nature of our question on how many other drivers were in the house, we think there was minimal difficulty with recall. Indeed, research has indicated that the ability to remember autobiographical event dates does not decline with age.24 Also, our interviewers used probes based on available information to help participants narrow down the time frame if a date was required. Another challenge was that we had to use proxies for 31% of the participants. However, we found good correlation and agreement for the questions that we asked on a subsample of participants, and proxies have been used successfully before in research studies of older adults.25–27
Data on noninstitutional LTC services that include home and community-based services were not available in the SEE data. Future work could examine whether driving status is also related to the use of these services, as well as whether the use of these services acts as a moderator on the relation between driving status and entry into institutional LTC.
Salisbury is a semirural town of about 40000 people located on the eastern shore of Maryland. At the time of this study, there was no formal public transportation. The results of this study may only generalize to other areas similar to Salisbury. For example, not driving in an urban environment, where one could potentially walk to the corner store for groceries, may not be associated with an increased risk of LTC entry. Future research should attempt to confirm this finding and to examine whether the relation between driving and LTC entry holds in urban environments as well.
In summary, our data suggest that being a nondriver increases the risk of entering LTC, which can be a significant drain on financial resources. This information could be used to better prepare older adults, their families, and society for the difficult circumstances that can result from not being able to drive. We expect older adults to make good decisions about when they should stop driving, but we fail to fully recognize the hardships that not being able to drive places on an older adult. One way to aid older adults without transportation options is to develop better public transportation programs specifically targeting older adults. One successful model program in Maine is called the Independent Transportation Network, which offers prearranged, paid, shared rides 7 days a week, 24 hours a day.28 Other strategies by families, organizations, and governments to improve the transportation options for older adults should be developed to ensure road safety and living independence for as long as safely desired.
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Acknowledgments |
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Human Participant Protection
Approval for this study came from The Johns Hopkins University Joint Committee on Clinical Investigation, and informed consent was obtained for all participants.
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Footnotes |
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Contributors
E. E. Freeman and S. K. West contributed to the study’s design, data collection, and analysis, and to the writing of the article. S. J. Gange and B. Muñoz contributed primarily to the design and analysis.
Accepted for publication August 24, 2005.
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References |
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