# Quantifying the Relationships: Aging, Driving Cessation, Health, and Costs

### A Project Memorandum

## **Sponsored by US DOT**

## **Office of the Secretary**

## **Transportation Policy Development**

####  {#section .unnumbered}

####  {#section-1 .unnumbered}

#### January 2004  {#january-2004 .unnumbered}

#### Introduction

The purpose of this effort was to explore the complex interrelationships
among health, economics, and driving cessations in the older adult
population. While there is a significant body of literature for each of
these areas there is not an established methodology to objectively
explore the impact of changes in demographics, health, and driving and
predict potential future impacts. Specifically this technical memorandum
proposes a conceptual basis for a methodology to:

-   Examine the impact of loss of "out of home" mobility (mobility that
    permits contact with the external world and leads to interaction
    with people outside the home), due to driving cessation, on health
    and health care costs. "Out of home" mobility makes it possible to
    contact with people, obtain services, and participate in activities.

-   Identify methods to quantify economic impacts of loss of contact
    with the larger world on the individual, family, community, and
    society.

The goals of this effort were to:

-   Identify and catalog promising data sources and methodologies to
    quantify the relationship among external mobility, health status,
    and health costs.

-   Summarize, in a project memorandum, the conclusions that can be
    drawn regarding:

    -   The relationship between health and mobility.

    ```{=html}
    <!-- -->
    ```
    -   The economic impacts of driving cessation and the resulting loss
        of contact with the outside world to the individual, family,
        community, and society.

## 

To accomplish this, a U.S. Department of Transportation team with
representatives from the Office of the Secretary, National Highway
Traffic Safety Administration, and the Volpe National Transportation
Systems Center did the following:

-   Reviewed the pertinent literature

-   Identified the most promising data sources

-   Convened and met with panels of international experts

-   Proposed a methodology that could be used to quantify the
    aging/mobility/health/cost relationships.

## 

#### Background

The 1999 TRB International Meeting on Transportation and Aging
identified the impact of loss of mobility on health as a key research
issue. Given that automobile travel is the primary source of mobility
for Americans, the cessation of driving is likely to be an event that
curtails a large portion of older Americans' contact with the larger
society.

It has been hypothesized that the cessation of driving has significant
direct and indirect health impacts. In addition to the loss of contact,
these impacts have economic consequences. However developing objective
quantitative estimates of the health and economic consequences is
problematic because a person's declining physical condition can be both
a cause and a consequence of loss of mobility. The US Department of
Transportation's Office of the Secretary's Office for Transportation
Policy initiated a project with the Volpe National Transportation
Systems Center to identify and/or develop methods for arriving at
estimates of the economic impacts of driving cessation, the major cause
of loss of external mobility.

The Volpe Center organized and convened a meeting of experts in aging
and driving cessation during the 2002 Annual Meeting of the
Transportation Research Board to identify the data and research
protocols that could address this issue (Committee on Safe Mobility of
Older Persons, 2002). The participants made the following
recommendations:

-   There is a need to specify the required research and to identify
    candidate data sources.

-   The confounding of the impact of loss of contact, or
    "out-of-the-home" mobility, due to driving cessation, on health, as
    well as the impact of health on mobility, represent a significant
    obstacle, but it is possible to discover potential methodologies.

-   To date, depressive symptoms are the only objectively established
    medical impact of driving cessation (Marottoli et al., 1997).

-   The impact of loss of external mobility is likely to differ as a
    function of age, gender, wealth, ethnic background, and/or region of
    residence.

-   Although experimental field studies are desirable, their
    implementation is challenging and, probably, impractical.

-   Analyses of data from longitudinal databases may be the most
    promising approach. However, the databases that focus on health
    contain few, if any, transportation items, and the databases focused
    on transportation contain few health items.

    -   It is possible to request that items be added to longitudinal
        studies. This approach is costly and the data would not become
        available for years.

-   Analyses that quantify the economic impacts are important in
    developing policy.

    -   For example, it would be useful to quantify the transportation
        costs incurred by providing the life sustaining treatment of
        dialysis.

The consequences of driving cessation were discussed in more depth at a
meeting held in Phoenix, AZ, in March 2002, as part of the "National
Conference on Aging & Mobility" sponsored by the Maricopa Association of
Governments. At this meeting, participants discussed the impact of loss
of external mobility and methods to improve understanding of the issue.
Participants agreed that there is a relationship among a person's sense
of autonomy, driving status, and health but agreed that the relationship
has yet to be objectively confirmed or quantified. Participants also
discussed how lost contacts can lead to a sense of isolation,
depression, and associated illnesses.

The following topics were addressed at this meeting:

-   Demographic descriptors of aging and mobility in the United States.

-   Three seminal papers on driving cessation:

    -   "Driving Cessation in Late Life: A Socially Induced Disability?"
        (Barr, 2001)

    -   "Changes in Driving Patterns and Worsening Depressive Symptoms
        Among Older Adults. " (Fonda, Wallace, & Herzong, 2001)

    -   "Statistical Relationships Between Vehicle Crash Rates, Driving
        Cessation, and Age-Related Physical or Mental Limitations." (Hu,
        Lu, & Trumble, 1997)

-   A proposed framework for developing quantitative estimates of the
    economic impact of driving cessation and resulting loss of external
    mobility.

#### Demography of Aging in America

##### 

##### In 2000, one out of eight Americans, 35 million or 12.5%, were age 65 and older. The proportion of the population age 65 and older is going to increase, relative to the other age groups, for the foreseeable future. In the year 2030 when the last of the baby boom generations reaches age 65, there will be 70 million Americans age 65 and older, one out of five, as shown in Figure 1.

![](media/image1.wmf)

Figure 1. Number of Americans 65 and older (in millions) by year
(Current Population Reports, 2000)

Females are over represented in the 65 and older population. In 2000,
there were 143 women for every 100 men age 65 and older, or 21 million
women vs. 14 million men. The sex ratio increases in the older age
groups.

![](media/image2.png)

2030

2000

Figure 2. Projected US population over 65 by gender for year 2025
compared to year 2000. (U. S. Bureau of the Census)

For example, in 2000, there were 245 women to 100 men for age 85 and
older. (Figure 2) As the relative proportion of the population age 65
and older increases, the gender differential becomes more striking as
Figure 2 shows.

In 1997 in the United States, men age 65 and older were more likely to
have a driver's license; 92% of the men had driver's licenses as
compared to 67% of the women (Organization for Economic Co-operation and
Development, 2001). With the expansion in women's expectations and
opportunities in recent decades, it is likely that women's driving
behavior will become more similar to that of men. Many more women in the
younger age cohorts hold drivers' licenses and are driving more. As a
result older women in the future will do much more driving.

# Mobility and Income

In 2000, 4.2 million Americans age 65 or older were employed, 2.4
million men and 1.8 million women. Employed older Americans represented
13% of the age 65 and older population and 3% of the U.S. labor force.
This proportion has increased in recent years [(Older Americans 2000:
Key Indicators of Well-Bei]{.underline}ng, 2000). In 2001, the civilian
non-institutional population age 65 and older represented 13% of the
population and 12.7% of this population was employed; 24.7% of people
age 65 to 69, 14.1% of people age 70-74, and 5.4% of people age 75 and
over were employed [(Household Data Annual Averages. Table 3. Employment
Status of the Civilian Noninstitutional Population by Age, Sex, and
Ra]{.underline}ce). With the increase in the age for eligibility for
Medicare beginning to impact the older population, it is likely that
these levels of employment among older people will continue if not
increase. Loss of external mobility could affect employment
opportunities among those able to work. The impact of loss of external
mobility will vary by income level to the degree that older Americans
depend on employment to sustain them economically.

> ![](media/image3.wmf)

Figure 3. Income Distribution for Households Headed by Person Age 65 or
Older in 2000, (U.S. Bureau of the Census, 2001a)

Figure 3 depicts the distribution of income for households of people age
65 and older. In 2000, income "Below the Poverty Level" for one-person
age 65 or older was \$8,259 and for a household (2 persons) age 65 and
older was \$10,419 (U.S. Bureau of the Census, 2001b). Nationally, 11.3%
of the society lived below the poverty level as compared to 10% of those
age 65 and older. However, 19% of people age 65 and older that lived
alone had incomes below the poverty level. Twelve per cent of women age
65 and older had incomes below the poverty level in 2000 as compared to
8 % of the men (Dalaker, 2001).

# 

# Health and Disabilities

With regard to health problems and disabilities (defined as a
substantial limitations in a major life activity), slightly more than
half, 55%, of Americans age 65 and older have at least one disability
and 38% of them report at least one severe disability. Gender is related
to the distribution of disability. In 1994, 25% of women age 65 and
older, 4,907,790, had at least one chronic disability as compared to
15.5% of men or 2,078,000 [(Older Americans 2000: Key Indicators of
Well-Bei]{.underline}ng, 2000).

The percent of Americans 65 or older needing assistance increases with
age. In 1998, the incidence of disabilities by age that restricted
activities was 29% for people age 65-74, 51% for people age 75 and older
and 74% for people age 80 and older (Administration on Aging). Using
1994-1995 data on respondents reporting difficulty performing any of the
Instrumental Activities of Daily Living (IADL's)[^1] and Activities of
Daily Living (ADL's),[^2] 16,421,000, or 52%, of people age 65 and
older, reported at least one disability. There are 4.5 million Americans
age 65+ who have difficulty with ADL's and 6.9 million who have
difficulty with Instrumental Activities of Daily Living IADL's.(U. S.
Bureau of the Census, 1998) People, age 65 and older, with lower income
levels and educational attainment, are much more likely to report severe
disabilities.

**Place of Residence**

The residential location of Americans age 65 and older is mainly in the
metropolitan area. More than three-quarters (77%) of the population age
65 and older live in metropolitan areas. However the largest group, 50%
lives in the suburbs and the remainder is split between central cities
27% and non-metropolitan areas. (23%) One half of the population age 65
and older currently lives in suburbs and 23% in non-metropolitan areas.
This distribution of residential locations means that three-quarters of
the older people live in the low-density settings. A low-density
lifestyle makes the need to drive and to continue to drive more
critical.

The trip making and travel rate of Americans age 65 and older continues
to increase. In 1995 they made 9.4% of all daily trips in the United
States, an increase from 7.8% in 1990 and 7.2% in 1983. In 1995 they
accounted for 7.5% of miles traveled, an increase from 6.6% in 1990, and
5.6% in 1983 (Hu & Young, 1999). By 2030, Americans 65 and older are
forecast to account for 18.9% of miles traveled, almost tripled the 1990
level (Burkhardt, Berger, Creedon, & McGavock, 2002).

There are variations in lifestyle between cohorts due to cohort
differences in life experiences. Only 67% of women age 65 and older
compared with 92% of men have a driver's license (Organization for
Economic Co-operation and Development, 2001). As a result older women
are disproportionately affected when their spouse ceases to drive. The
proportion of women with driver licenses increases in each younger
cohort (Barr, 2001).

##### 4.0 Aging In Place

##### People tend to stay in their current setting, or "age in place," until they, and/or others, recognize that they are experiencing increasing difficulty performing their daily activities. In many cases driving cessation presents a barrier to aging in place. The current practice is to propose that the older person change his/her residence and move to a location that offers more support to perform these daily activities. Such moves can be disruptive, wrenching, costly, and usually occur when an individual is most vulnerable. 

The residential location of older people who are no longer able to
drive, and/or lose their mobility, could contribute to the level of
social and economic costs they must bear. With a more diffuse
residential pattern, there are longer distances to social, recreational,
and commercial activities. Distance to, and from, social, recreational,
and commercial activities translates into resource and time costs to
mobility providers and society. It becomes more costly to provide
substitutes to individuals with mobility deficits. Conversely, when
individuals with mobility deficits are in closer proximity to activities
necessary for maintaining quality of life, it is more economical to
provide these activities.

It can be extrapolated that there may be local, regional, and national
economic effects if older adults reduce, or cease, their consumption of
goods and service after losing their mobility. Goods and services
brought to individuals become more costly as the distances to their
residences increase. The growing trend for businesses to offer home
delivery of goods and services will face the challenge of providing
their products at an affordable price.

An alternative to the home delivery of services is to augment the
domestic setting to compensate for decreased competence in performing
the activities of daily living. To the extent this is possible, more
aging in place could occur. Mynatt, Essa, et al. (2000) suggest that an
augmented environment using computers, capable of recognizing potential
crises and offering remedial measures, could enhance dwelling units to
provide older residents more support. They propose installing sensors to
monitor the older person's condition in case other parties need to be
alerted. The alerts should be appropriate and effective for an older
person. This alternative, adapting the residence rather than uprooting
an older person, addresses the safety and comfort but does not
substitute for needed mobility outside the home.

##### 5.0 Proposed Relationships: Aging, Driving Cessation, and Health 

Hu, Lu, and Trumble (Hu et al., 1997) examined the relationship among
safety, driving cessation, and age to determine:

-   How functional limitations influence older drivers decisions to
    cease driving

-   Whether drivers with age related limitations pose a risk to
    themselves or the public, and

-   Which limitations place older drivers at unacceptable risk.

They used data from the *Iowa 65+ Rural Health Study* for the years
1981-1993 and they found that:

-   Age influences driving cessation decisions in both males and
    females, but is more determinative for females.

-   Older females were more likely to stop driving than their male
    counterparts.

-   Five chronic conditions were explicitly associated with voluntary
    cessation decisions:

    -   Arthritis,

    -   Parkinson's disease,

    -   Cataracts,

    -   Stroke(s), and

    -   Heart attack.

However none of the chronic medical conditions listed above were
associated with higher vehicle crash rates. The only medical condition
associated with increased crash risk was glaucoma and this association
was most pronounced for older men. However, for older men the amount of
driving exposure and the use of anti depressants were the most
influential risk factors. The authors commented that, due to data
limitations, conclusions on the influence of drug use on crash rates for
older drivers should be examined in future studies.

They report that functional limitations, rather than the diagnosis of a
condition, influenced the cessation. Driving cessation was more likely
to be governed by incapacitation due to a physical manifestation of a
condition than by the diagnosis of the presence of a syndrome or
condition. They also report the following:

-   Driving cessation is often not a single event but is episodic.
    Episodic cessation occurs when the appearance of a physical symptom
    causes a person to stop driving; when the symptom is alleviated,
    driving is resumed.

-   The decision to cease and resume driving is often caused by life
    requirements (e.g. place of residence, employment, place chosen for
    retirement) rather than choice.

-   Males tend to postpone cessation longer than women.

Robin Barr of the National Institute on Aging examined the
interrelationships between declining health and driving cessation (Barr,
2001). His paper raises the following questions:

-   Are the social and economic conditions of the United States
    generating a new public health problem that results from the
    consequences of driving cessation?

-   Should driving be considered an ADL? If so does driving cessation
    result in the negative health effects similar to those associated
    with the inability to perform the ADLs and IADLs?

-   Can we consider loss of the ability to drive a disability?

[]{.mark}

[]{.mark}

Barr notes that, to answer these questions, we must determine if driving
cessation should be considered a disability or the loss of an important
resource.

Barr offered two hypotheses:

-   "If driving is ...\[an\] internal resource then it is possible to
    replace that resource with alternative forms of transportation. The
    alternative services may also reduce the risk of a crash that
    injures or kills the affected older adult ... \[resulting in\] a net
    reduction in health risk."

-   "If driving is itself part of independence then ... \[driving
    cessation is the\] same as the loss of other abilities ... \[Driving
    is\] critical to independence. The loss represents part of a cascade
    towards increasing dependence and death."

Based on a review of the literature, Barr concluded that driving
cessation can be considered a disability in itself because of the broad
range of effects on the former driver. This is particularly true when
the individual's residence location doesn't provide other transportation
alternatives. He also commented that an individual's decision to cease
driving is a trade-off that has profound consequences for many areas of
life and is embedded in other life choices.

##### Mechanisms have been proposed that might relate changes in driving to mental well-being. There is evidence that driving reduction and cessation among older adults leads to depressive symptoms. With regard to the health effects of driving cessation on older Americans, Marottoli (Marottoli et al., 1997) analyzed the statistical relationship between driving cessation and the incidence of depressive symptoms. They found that driving cessation was associated with an increased incidence of depressive symptoms. This relationship was empirically supported after adjusting for the potentially confounding influence of social, demographic and health related factors. 

##### 

##### The subjects in this study (Marottoli et al., 1997) were selected from a probability sample of non-institutionalized adults age 65 and older in New Haven, Connecticut called the New Haven Established Populations for Epidemiological Studies of the Elderly (EPESE) cohort. Using three waves of data collection, this study measured the incidence of depressive symptoms among three groups of subjects, i.e., subjects who continued to drive during the seven-year duration of the study, those who stopped driving during this interval, and subjects who stopped driving prior to measurement or who had never driven. The results show that subjects who ceased driving during the study's duration reported the highest level of most depressive symptoms. Depressive symptoms were measured using the Center for Epidemiological Studies-Depression (CES-D) Scale.[^3] This research builds on prior research that reported that that depression and depressive symptoms are associated with disability and mortality.

Fonda, Wallace, and Herzog (Fonda et al., 2001) conducted research to
investigate whether driving cessation or driving reduction increased the
likelihood of depressive symptoms and whether such consequences were
lessened by the presence of a spouse that continued to drive. Using the
Asset and Health Dynamics Among the Oldest Old (AHEAD) national
database, they evaluated the potential relationships among driving
reduction, driving cessation, and depression. This national database is
longitudinal in nature and follows non-institutionalized Americans born
in 1923 or earlier and their spouses (if born in 1923 or earlier). At
the time of the study individuals born in 1923 would have been 70 years
old. The prime dependent variable was an increase in depressive symptoms
as measured on the CES-D Scale (Hohout, Berkman, Evans, &
Cornoni-Huntley, 1993).

Based on the results of their work, they reached the following
conclusions:

-   People who stopped driving were at greater risk for depression than
    those that didn't stop driving.

-   People who stopped driving were at greater risk for depression than
    those who restricted their driving.

-   People who restricted their driving distances were not initially at
    greater risk for depressive symptoms as those that continued their
    normal driving practices, but people who had maintained these
    restrictions for more than two years prior were at greater risk for
    depression than those who had not restricted their driving.

-   People who ceased driving but had spouses that continued to drive
    were at greater risk of depression than those who continued to
    drive.

-   People with access to auto transportation through other drivers were
    at lesser risk for depression than those without access.

Fonda et. al. interpreted these seminal results to mean that driving is
a "self defining" activity. The cessation of driving was a "sentinel"
event associated with: a loss of autonomy resulting from a reduced
ability to accomplish both required and recreational activities; the
stigma associated with dependency, and the approach of the end of life.
They feel driving cessation can be considered a clear sign of a
transition representing a decline in physical and mental capabilities
leading to an inexorable dependence on others, a loss of personal
freedom, and death.

The loss of autonomy may be evident in the relationship between trip
type and the availability of transportation from voluntary providers.
They noted that individuals who relied on other drivers found it much
easier to ask for, and get, support for mandatory trips such as doctors
visits and much harder to ask for, and get, support for elective trips
such as social visits. They also noted that the failure of
transportation provided by a spouse to mitigate the impact of driving
cessation calls into question the usefulness of transportation programs
that are mainly focused on older persons maintaining their well being.

Driving cessation resulting from loss of driving privileges is a
concomitant of Alzheimer's disease and related dementias. Cessation
resulting from these causes was studied by Taylor and Tripodes (Taylor &
Tripodes, 2001) using data from approximately 900 California residents.
They note that loss of mobility in such cases is a particular problem.
Substitute transportation providers are almost always limited to family
members due the custodial requirements associated with such conditions.
Such individuals become almost totally dependent on their household for
mobility and support. They rarely use public transit or transportation
services. These family caregivers are not only inconvenienced in a
social sense, they may have strongly reduced opportunities to work or
have to give up work entirely. It is estimated that 10% of individuals
65 or older have or will develop these problems (National Academy on an
Aging Society, 2000).

These studies suggest that driving cessation has a major impact on older
people. They may be less able to manage their "out of home" mobility as
well as their overall health. Clearly there is a need for better
understanding of the cost of this transition and new stage of life.

####  {#section-7 .unnumbered}

#### 6.0 A Methodology for Estimating Social and Economic Costs of Driving and Mobility Cessation {#a-methodology-for-estimating-social-and-economic-costs-of-driving-and-mobility-cessation .unnumbered}

The literature on the relationship between aging and mobility lacks a
methodology for estimating the many components of the costs resulting
from reducing or stopping driving for age-related reasons. There is a
need for such a methodology that would account for the consequences of
inadequate transportation alternatives, reducing or losing external
mobility, and social interaction.

Older drivers experience the cost of driving cessation in a number of
ways. For example, they may have to pay for goods and service delivery,
find ways to substitute for inaccessible preferred goods and services,
or go without some goods and services. Additionally, the lack of
mobility \-- and the loss of its benefits \-- may accelerate the aging
process and/or bring on physical, medical, emotional conditions that
require care. This too has its costs.

Other people also bear the costs, e.g., voluntary caregivers, the
community, and society. Volunteer caregivers incur out-of-pocket costs
for expenses, such as gasoline, and opportunity costs for time not
working while providing care giving, or the loss of employment. (Taylor
& Tripodes, 2001) found that 13% of family caregivers to individuals
with age related dementia gave up work entirely.[^4] The community in
which the older driver resides may lose the value of the work or the
social activity previously pursued. The local economy may experience a
reduction in demand associated with shopping. The community and the
society may have to provide ways for older persons to access necessary
services, particularly but not limited to medical care.

Driving reduction and cessation may have some benefits. Older people are
at higher risk both to be involved and injured in a motor-vehicle crash.
Any reduction and/or cessation lowers the number of crashes and
resulting trauma, and potential permanent loss of functionality.

The core issue that needs to be addressed is what does it cost to family
and society if there are no supplementary and substitute transportation
services available to an older population as they need them. The likely
costs, due to deficient transportation substitutes, will accrue to the
society as well as the older person. Policy makers need to recognize all
the costs involved and upon whom the cost burden is likely to fall when
older people reduce or cease driving without mobility substitutes. The
costs range from direct, out-of-pocket costs to opportunity costs and
indirect costs.

There is a need for information to identify the costs and who will bear
the burden of the cost of mobility substitutes. The elements needed to
understand the cost impacts of driving cessation on health and health
care include:

-   The reasons for driving cessation.

-   How financial, social, and other resources impact mobility choices.

-   What mobility options are realistically available given potential
    residential arrangements.

-   Expectations for current and future cohort groups.

Any effort to estimate the costs and health effects of driving cessation
must recognize that they embody a complex set of variables that reflects
a range of circumstances and living arrangements as broad as in any
human activity. How to reduce these variables to a manageable set for
which data exists represents a formidable problem. Matrix 1 represents
an "n-dimensional" array of ways an older individual may fulfill his or
her transportation requirements.

It illustrates the intersection of health, social structure, and income
variables generally, but it in itself is a substantial simplification.
For some of the cells represented, modifications would be made to match
the data that is or could be made available. For purposes here, however,
they must initially be folded into an even more limited set to get to a
manageable exposition. This trade-off is reflected in the simplifying
*prototypes* discussed below.

To quantify the interrelationships, it is necessary to answer the
following questions:

-   What are the best sources of data that combine age-related heath
    status, mobility, and health care costs?

-   How do we evaluate the relationships among driving cessation,
    reduced mobility, health status, and health care costs?

-   How do we evaluate the economic impacts of non-mobility to the
    individual, family, community, and society?

Error: Reference source not found

Given the information identified above, it is possible to specify steps
to estimate the full economic costs \-- direct, opportunity, and
indirect \-- of driving cessation and mobility loss. To begin this
procedure, the analysis will make assumptions about the level of
mobility possessed by older Americans by age category. These assumptions
will be corrected as more data becomes available about the health status
of older Americans and the differential effects of cohort experiences
bring changes in older Americans, both in terms of health status and
financial resources. The following steps describe a methodology to
quantify the relationship between driving cessation and aging, health
status, and costs.

##### Step 1: Define the temporal course of driving cessation

Although the rate of driving and mobility cessation among older persons
is complex, three time sequences are assumed for the purposes of
estimating costs:

-   **Gradual:** as through the general aging process, limiting first
    driving at nighttime, on interstate highways, congested roads, etc.

-   **Episodic:** as by limiting driving for a while as from a medical
    condition then resuming.

-   **Permanent:** as from debilitating medical condition or the later
    stages of dementia.

These sequences express how individuals might reduce their driving.
However loss of driving requires finding mobility substitutions or doing
without. The percentage of Americans falling into each category must be
established. Data on ADLs and IADLs are a helpful source.

##### Step 2: Identify substitutions for driving cessation

Older people experience different amounts of mobility as their
capabilities and resources change over time. This memorandum proposes
five levels of mobility. When a person cannot provide their desired
level of mobility, they need a substitute form of mobility. The
following five prototypes are postulated as follows:

-   **Prototype 1.** This prototype refers to the ability to maintain
    established mobility patterns. It is "base case" mobility or a
    static condition**.** Here the person continues to drive, or never
    drove and has established mobility substitutes available, e.g.,
    public transportation, spouse, friends. Note, at any point in time
    and for any age cohort, there will be a segment of older people who
    continue to drive or have mobility provided to them.

-   **Prototype 2:** The person lives in his or her own residence.
    Family, friends, or other voluntary caregivers supply mobility for
    essential trips, e.g., medical appointments, and limited mobility
    for social/recreational trips. Voluntary caregivers also may shop
    for individual. In this prototype the individual receives all needed
    mobility.

-   **Prototype 3** The person lives in his or her own residence and
    purchases or receives mobility from external outside sources, i.e.,
    from professional providers (such as taxis) or public agencies for
    essential trips, but not, to any extent, for social and recreational
    trips. Goods and services are delivered to the home (presumably at a
    premium.) This prototype requires an estimate of the costs
    associated with purchased transportation such as taxi and
    paratransit usage.

-   **Prototype 4:** The person lives in his or her own residence but
    does not have access to voluntary mobility provider to supply
    mobility and is not able to purchase or acquire mobility beyond that
    required for emergency medical needs. This mobility state is
    transient.

-   **Prototype 5:** The person enters residential facility, either
    assisted living or skilled care, and substitutes for mobility are
    provided at various levels.[^5]

##### 

##### Step 3: Estimate the Magnitude of the Population by Prototype

After classifying prototypes conveying varying amounts of external
mobility, for people age 65 or older, it is necessary to estimate the
proportion of the older population that falls into each prototype. Table
1.0 distributes the age 65 and older population in 1995 using a number
of sources to estimate the size of each category. This stratification
serves as a first estimate that should be further refined. The HRS/AHEAD
(University of Michigan, 2003) data, representing a national sample,
will provide a better estimate of the joint distribution of functional
capability and living arrangements of the 65 and older population. These
distributions are the basis of the five Prototypes. In Table 1,
Prototype 5, 'a person enters a residential facility', has been
partitioned into 'assisted living' and 'skilled care' because the costs
differ.

Because the number of older people will increase with improvements in
health care and population changes such as the results of the "baby
boom," the numbers in these boxes will differ over time. Similarly, due
to the increasing number of women driving in the younger age cohorts,
the percent of older people in each of the three driving status boxes
will also change. Obviously, the number of women 'not a driver' will
decline. So, depending whether current costs of lack of mobility are to
be estimated, or future costs, the population information used needs to
coincide.

### 

**Table 1. Estimates of Population Age 65 and Older, by Mobility
Prototype, by Help Required**

+----------+--------+--------+--------+------+-------+------+-------+
|          | Total  | *      | **Pro  | **P  | **P   | *    |       |
|          |        | *"Base | totype | roto | rotot | *Pro |       |
|          |        | Case"  | 2**    | type | ype** | toty |       |
|          |        | Pro    |        | 3**  |       | pe** |       |
|          |        | totype |        |      | **4** |      |       |
|          |        | 1**    |        |      |       | *    |       |
|          |        |        |        |      |       | *5** |       |
+----------+--------+--------+--------+------+-------+------+-------+
|          |        | Home   | Home   | Home | Home  | 5a.  | 5 b.  |
|          |        |        |        |      |       | Assi | Sk    |
|          |        |        |        |      |       | sted | illed |
|          |        |        |        |      |       |      |       |
|          |        |        |        |      |       | Li   | Fac   |
|          |        |        |        |      |       | ving | ility |
+----------+--------+--------+--------+------+-------+------+-------+
| **Transp |        | None   | L      | Comp | Com   | Comp | N/A   |
| ortation |        |        | imited | lete | plete | lete |       |
| Help     |        |        |        |      |       |      |       |
| Re       |        |        |        |      |       |      |       |
| quired** |        |        |        |      |       |      |       |
+----------+--------+--------+--------+------+-------+------+-------+
| **Re     |        | no     | yes    | Yes  | no    | Yes  | N/A   |
| ceives** |        |        |        |      |       |      |       |
|          |        |        |        |      |       |      |       |
| **Transp |        |        |        |      |       |      |       |
| ortation |        |        |        |      |       |      |       |
| Help**   |        |        |        |      |       |      |       |
+----------+--------+--------+--------+------+-------+------+-------+
| **Est.   | 100%   | 72     | 18     | 2    | 2.3   | 1.4  | 4.5   |
| Perc     |        |        |        |      |       |      |       |
| entage** |        |        |        |      |       |      |       |
+----------+--------+--------+--------+------+-------+------+-------+
| **Est.   | 35     | 25     | 6      | 546  | 80    | 500, | 1,57  |
| Popu     | ,000,0 | ,270,0 | ,294,0 | ,000 | 5,000 | 000[ | 5,000 |
| lation** | 00[^6] | 00[^7] | 00[^8] | [^9] | [^10] | ^11] | [^12] |
+----------+--------+--------+--------+------+-------+------+-------+

##### Step 4: Identify Costs for Each Prototype

It is important to identify and estimate the full costs brought about by
an older person who reduces, or stops altogether, driving for
age-related reasons. There are at least four considerations in producing
this estimate.

-   Type of cost. Costs include direct 'out-of-pocket' costs as well as
    opportunity costs. For example, opportunity costs occur when a
    volunteer caregiver foregoes employment earnings for the time spent
    in volunteer caregiving. There is another category of cost due to
    loss of social interaction from reduced or loss of mobility outside
    the home. There is evidence that diminished social interaction and
    social support can lead to an increased likelihood of depression. In
    turn, depression has somatic consequences because depression has a
    physiological effect on the hypothalamic-pituitary-adrenal axis in
    the body (Thakore, 2001). This is the physiological link to the
    immune system, which makes people more prone to illness.

-   Allocation of cost. In Table 2, these costs can be placed on
    persons, enterprises, community, and society. Other classifications
    are possible. It may be helpful to break out the medical cost
    component of community and social costs.

-   A third consideration is the time span during which costs appear
    whether short or long. For example, if an older person pays to have
    goods and services brought to them, the premium paid is a short run
    cost. A long run cost occurs if an older person loses mobility
    without effective substitution and subsequently experiences a more
    rapid decline in health.

-   A final consideration is whether costs are net of benefits that
    might accrue from an older person *not* driving. For example, if an
    older person who drives is at a *high* risk of a crash due to
    age-related deficits, then, by not driving, there is an expected
    benefit to the person and to the community and society.

To the extent these four considerations can be addressed, the better the
estimation of the true, full costs of mobility loss for age-related
reasons.

### Table 2: Matrix of Mobility Prototypes by Costs

+-----------------------------+----------+--------+---------+---------+
| ######## costs              | **       |        |         |         |
|                             | Mobility |        |         |         |
|                             | Prot     |        |         |         |
|                             | otypes** |        |         |         |
+-----------------------------+----------+--------+---------+---------+
|                             | \(2\)    | \(3\)  | \(4\)   | (5a,b)  |
+-----------------------------+----------+--------+---------+---------+
|                             | **Vo     | *      | **No**  | **Resi  |
|                             | lunteers | *Purch |         | dential |
|                             | Provide  | ases** | **M     | Li      |
|                             | L        |        | obility | ving/** |
|                             | imited** | **Mobi | Pro     |         |
|                             |          | lity** | vided** | **Mob   |
|                             | **Mo     |        |         | ility** |
|                             | bility** | **     |         |         |
|                             |          | From** |         | **Pro   |
|                             |          |        |         | vided** |
|                             |          | **Pr   |         |         |
|                             |          | ofessi |         |         |
|                             |          | onal** |         |         |
|                             |          |        |         |         |
|                             |          | *      |         |         |
|                             |          | *Provi |         |         |
|                             |          | ders** |         |         |
+-----------------------------+----------+--------+---------+---------+
| # Domicile                  | Home     | Home   | Home    | **Resi  |
|                             |          |        |         | dential |
|                             |          |        |         | l       |
|                             |          |        |         | iving** |
+-----------------------------+----------+--------+---------+---------+
| **Costs to individual**     |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Cost of bringing          |          |        |         |         |
| > goods/services to people  |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Lost income to person     |          |        |         |         |
| > from not being able to    |          |        |         |         |
| > work                      |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Not able to engage in     |          |        |         |         |
| > social/recreational       |          |        |         |         |
| > activities. Possible loss |          |        |         |         |
| > in health status and      |          |        |         |         |
| > onset of depressive       |          |        |         |         |
| > symptoms                  |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Cost of bringing goods    |          |        |         |         |
| > and services to people    |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Costs to society of       |          |        |         |         |
| > transporting persons to   |          |        |         |         |
| > medical facilities        |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Loss of ability for self  |          |        |         |         |
| > care                      |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| ######### Costs To          |          |        |         |         |
| Voluntary Mobility Provider |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Out of pocket costs to    |          |        |         |         |
| > voluntary mobility        |          |        |         |         |
| > providers                 |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Lost income and work      |          |        |         |         |
| > opportunities for         |          |        |         |         |
| > voluntary providers       |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| **Costs To Society From     |          |        |         |         |
| Older Persons' Lost         |          |        |         |         |
| Mobility**                  |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Loss of older person's    |          |        |         |         |
| > participation in economy. |          |        |         |         |
| > Impact on local,          |          |        |         |         |
| > regional, and national    |          |        |         |         |
| > economy                   |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Necessity of providing    |          |        |         |         |
| > appropriate public        |          |        |         |         |
| > transportation            |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Impact on local,          |          |        |         |         |
| > regional, and national    |          |        |         |         |
| > social services and       |          |        |         |         |
| > healthcare sectors        |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| **Benefits, Societal, And   |          |        |         |         |
| Economic**                  |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Avoidance of motor        |          |        |         |         |
| > vehicle-related trauma    |          |        |         |         |
| > costs                     |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+
| > Growth of residential     |          |        |         |         |
| > living industry           |          |        |         |         |
+-----------------------------+----------+--------+---------+---------+

##### 

##### Step 5: Re-analyze Established Data Source to Extract Cost Information 

It is necessary to examine a number of data sets to identify a source
that contains enough variables and data to make it possible to estimate
the costs of reduced and lost mobility. Based on this review, it appears
that the University of Michigan's Health and Retirement Study
(HRS)/Assets and Health Dynamics Among the Oldest Old (AHEAD) dataset is
the most promising source. These two data sets, combined in 1998,
provide a national longitudinal sample documenting the experiences of
more than 22,000 Americans over the age of 50. The subjects have been
surveyed every two years since 1992, with the support of the National
Institute on Aging.

There are a number of reasons for selecting HRS/AHEAD as a source:

-   For the purposes of this study, it is comprehensive, having three
    important information elements: (1) driving and mobility status; (2)
    health status; and (3) income and consumption expenditures. The
    classification of costs depends considerably of each of these three
    elements.

-   It is a demographically representative, national sample making it
    possible to extrapolate results to the national population.

-   Being a sample, the precision of any estimate can be determined.
    This is an important consideration. Not only can the point estimate
    of a cost be determined but its confidence interval as well. It is
    also preferable to obtain as much information as possible from one
    source as possible, with known statistical properties to avoid
    estimates constructed from multiple sources.

Information about the HRS/AHEAD database:

-   **Organizations:** Sponsored by NIA and other agencies and conducted
    by the University of Michigan.

-   **Purpose:** Interplay of financial resources, retirement, and
    health.

-   **Sample:** National, initially 12,600 people from 7,600 households;
    now 22,000 households.

-   **Frequency:** 1992, 1994, 1996, 1998, 2000. Have applied for
    funding to conduct 3 additional waves of data collection.

-   **Health:** ADLs, IADLs, cognitive information, physical ailments.

-   **Transportation:** Driving reduction and cessation questions, as
    well whether spouse drives.

-   **Comments:** 398 journal articles and other publications have used
    the HRS/AHEAD data. Data contains spending and other financial
    information.

##### Access and Use of the HRS/AHEAD Data 

The structure of the AHEAD (which is part of the HRS project at
Michigan) data is set up so it could be linked to access the Health Care
Financing Administration (HCFA) data (Medicare and Medicaid expenditures
recorded by the ICD9 diagnosis code.) The two data sets can be linked
using the subject's Social Security number. The HCFA data reports the
underlying condition that led to the need for medical care. If someone
requires medical care due to an emergency such as an automobile crash,
the information is entered as an ICD9 code. The HFCA data records
whether a person is being treated for an automobile crash and makes it
possible to assign the cost of care due to a motor vehicle crash. It is
also possible to link to spouse data.[^13]

##### 

##### Information to be obtained from the HRS/AHEAD database for each Prototype includes:

**Prototype 1:** 'Base Case Prototype.' Person continues to drive or
never drove and has established mobility substitutes, e.g., public
transportation, spouse, friends. At any point in time and for any age
cohort, there will be a segment of older people who continue to drive or
have mobility provided to them. They include the older persons who drive
as well as older persons who have never driven but have adequate
mobility substitutes.

The spending patterns of the older persons in Prototype 1 who retain
self-provided mobility serve as a benchmark against which to compare the
spending patterns of the remaining categories of older persons who have
lost their ability to provide their own mobility.

**Prototype 2:** Older person lives in own residence.[^14] Family,
friends, or other voluntary caregivers supply limited mobility for
essential trips, e.g., medical appointments, and some social and
recreational trips. Voluntary caregivers also may shop for individual.
Although services may be provided, it is likely that older person
experiences indirect costs associated with the emotional impact of
driving cessation on health. These costs may be reflected in treatment
of depression or other physical, emotional, and mental that can be
linked to loss of mobility.

The voluntary caregivers, i.e., spouse/family/friends able to drive, for
this segment of the older population incur direct costs. Some caregivers
also incur opportunity costs in loss in earnings. It is estimated that
between 11 and 13% of caregivers reduce or give up work to care for
elder dependents (Tennstedt). The data on these costs may be able to be
obtained from HRS/AHEAD as well as from experts on caregiving.

Analysis should be designed to show what the net cost is to society.
There may be savings associated with the loss of mobility for older
persons at high risk of causing a motor vehicle crash. This is to be
balanced against the caregivers' opportunity costs and the older
persons' incidence of physical and mental ailments associated with
diminished self-mobility.

**Prototype 3:** An older person lives in his/her own residence and
purchases mobility from professional providers for essential trips, has
goods and services delivered, but lacks for social and recreational
trips, often including shopping. It is necessary to estimate how many
older people fall into this prototype where there are few or no
family/friends that can provide voluntary mobility services as well as
what they would purchase if they had mobility.

Any analysis should compare the estimated demands for goods and services
for the people in this prototype with what they purchased, including any
premium paid for such purchase. The premium would be a direct cost of
loss of mobility. Additionally, the value of goods and services foregone
(particularly those related to recreational and social activities) may
be an indication of the costs of loss of mobility. However, a person may
substitute other goods and services for those ideally desired but
foregone. Thus, there needs to be some adjustment made to the value of
the desired but foregone purchases.

Prototype 4: Person lives in own residence but does not have access to
voluntary mobility providers to supply mobility and is not able to
purchase, or acquire, mobility except for emergency health related
trips. This mobility state is transient.

**Prototype 5:** Person in residential facility that provides mobility
substitutes. Because facility costs vary, it is desirable to partition
those costs for both assisted-living and skilled-care facilities

# Conclusion

There is no systematic process for the estimation of the many costs that
accrue from age-related driving cessation. This memorandum describes a
methodology that could be implemented to produce such estimates. These
would be valuable input to local, state, and national policies on
age-related issues. The methodology proposed can provide a quantifiable
link between mobility and health care costs for the more than 35,000,000
older Americans and their families in our population.

One of the key steps will be to establish the various proportions of
persons 65 and older that have similar attributes (age defined cohort),
and, hence, similar needs relative to mobility. Another important step
will be to establish the relationship between driving status, mobility
alternatives, and health. For example, an expanding body of research
indicates that no longer being able to operate a motor vehicle brings on
depressive symptoms, even in the presence of other mobility
alternatives. However, objective evidence of other mental, emotional,
and physical impairments in addition to depression that are due to
licensing and/or mobility shortcomings still must be established.

# 

The methodology must be populated with data. The HRS/AHEAD data, a
national sample of persons 65 and older, is arguably the best single
source for the types of information needed: licensing, mobility options,
health status, and spending patterns. There are other data sets that may
supply additional data to estimate the full costs of loss of mobility.
These data sets are described below in the Appendix.

We expect that many of the cohorts about to enter the US aging pool will
be healthier and wealthier, possess near universal licensing, and have
transportation alternatives. There are also likely to be groups with
poor health, limited financial resources, and limited mobility. The
social, health and lifestyle characteristics of successive cohorts
turning age 65 can only be predicted imperfectly but we can be sure that
they will continue to change.

This memorandum has identified the scope of the issue, i.e., what are
the health and cost consequences of driving cessation among elderly, and
outlined a methodology to address it. While the Department of
Transportation initially recognized this issue, it will be necessary to
seek the involvement of other federal agencies to address the issue
effectively. It is likely that the anticipated results will have
consequences for the missions of a number of federal agencies. For
example, the Administration on Aging (AOA), the National Institute of
Aging (NIA), and the Centers for Disease Control (CDC) may have relevant
data as well as an interest in the results of analysis of this issue.
This issue has consequences also for advocacy groups and private sources
concerned with transportation safety and the national health such as the
Transportation Research Board (TRB) and the American Association of
Retired People (AARP).

The proposed methodology will provide the tools needed to understand,
plan for, and address these changes at the national, local, and
individual level. Due to the need to use multiple sources of data and
the complexity of the research recommended by this methodology, there is
a need to create a consortium of parties to address this issue and
produce significant results. It is apparent that the next step in the
process of implementing this methodology is to establish cooperation
with interested parties in addition to the DOT.

**Appendix**

The following are the key data sets reviewed for this memorandum:

HRS/AHEAD

> Seattle Longitudinal Study
>
> National Household Travel Survey (formerly NPTS)
>
> National Health Interview Survey, 1994
>
> Rehabilitation Engineering Research Center (RERC) on Aging, University
> of Buffalo, the State University of New York.

Their key characteristics are described below.

**HRS/AHEAD**

-   **Organizations:** Sponsored by NIA and other agencies and conducted
    by the University of Michigan.

-   **Purpose:** Interplay of financial resources, retirement, and
    health.

-   **Sample:** National, initially 12,600 people from 7,600 households;
    now 22,000 households.

-   **Frequency:** 1992, 1994, 1996, 1998, 2000. Have applied for
    funding to conduct 3 additional waves of data collection.

-   **Health:** ADLs, IADLs, cognitive information, physical ailments.

-   **Transportation:** Driving reduction and cessation questions, as
    well as whether spouse drives.

-   398 journal articles and other publications have used the HRS/AHEAD
    data. Data contains spending and other financial information.

**Seattle Longitudinal Study:**

-   **Organizations:** Penn State and University of Washington.

-   **Purpose:** Determine how people age and mechanisms for dealing
    with aging. 

-   **Sample:** Originally 4,957 Seattle, WA, residents. 

-   **Frequency:** Every 7 years.

-   **Health:** ADLs, IADLs, cognitive information. 

-   **Transportation:** Can study subject manage transportation outside
    the home by self or does she/he need assistance?  

-   **Comments:** Limited transportation information. Would have to
    infer from health status all other transportation information.

**National Household Travel Survey: 2003**

-   **Organizations:** U.S. Department of Transportation, Westat

-   **Purpose:** Determine characteristics of trip taking.

-   **Sample:** National sample of 25,000 households but not specific to
    older persons. 

-   **Frequency:** Every 5 years. 

-   **Health:** Asks if a person has a health condition that reduces
    mobility.

-   **Transportation:** Driving status, number of drivers in household,
    and trip taking. 

-   **Comments:** Limited health information.

**National Health Interview Survey, 1994 Second Supplement on Aging**:

-   **Organizations:** CDC, National Center for Chronic Disease
    Prevention and Health Promotion.

-   **Purpose:** Determine if there had been changes in disability among
    older persons since first SOA have changed.

-   **Sample:** National, cohort 70 years and older.

-   **Frequency:** 1984, 1994.

-   **Health:** Cognitive and depression, extensive physical health,
    activity levels.

-   **Transportation questions:** Frequency of driving, health
    impairment for not driving, use of public transportation, level of
    social activity.

-   **Comments:** Could determine how aging cohorts (1984 vs.1994) are
    changing.

# Rehabilitation Engineering Research Center (RERC) on Aging

-   **Organizations:** University of Buffalo, the State University of
    New York. <http://cat.buffalo.edu/rerc-aging/rerca-research.php>

```{=html}
<!-- -->
```
-   **Purpose:** Consumer Assessments Study (CAS) has explored the
    functional needs of older persons living *in the home* relative to
    assisting technology and home modifications. Findings have been
    translated into new device development, policy changes,
    dissemination activities, and education programs.

-   **Sample:** 300 home-based older persons and close to 100 persons
    living in nursing homes.

-   **Frequency:** Longitudinal, 1996-2001

```{=html}
<!-- -->
```
-   **Health:** Information for each participant, including use of
    assisting devices and difficulties with functional tasks.

-   **Transportation:** Focus on identifying assisting technologies for
    maintaining personal mobility within and outside residence

```{=html}
<!-- -->
```
-   **Comments:** Collected longitudinal data about problems of older
    persons living independently as well as problems faced by those who
    move to nursing homes and adult residences. Initiated in Western New
    York and replicated in Florida.

### References

[^1]: Instrumental Activities of Daily Living (IADL\'s): Activities
    pertaining to daily living needs such as shopping, using the
    telephone, cooking, housekeeping and taking medications. Source:
    (<http://www.arizonacaregivers.org/features_glossary.html>)

[^2]: Activities of daily living (ADL\'s) refer to an individual\'s
    daily routine of bathing, eating, dressing, grooming, toileting,
    ambulating, and other similar tasks.
    (<http://www.seniorres.com/common_pages/glossary.html>).

[^3]: The Center for Epidemiological Studies-Depression Scale (CES-D) is
    a 20-item scale for epidemiological research that was developed by
    The National Institute of Mental Health. Respondents are asked to
    choose from four possible responses in a Likert format, where "0" is
    "rarely or none of the time (less than 1 day)", and "4" is "almost
    or all of the time (5-7 days)". Scores range from 0 to 60 with
    higher scores reflecting greater levels of depressive symptoms while
    lower scores reflect lower levels of symptoms. The CES-D has 4
    separate factors: Depressive affect, somatic symptoms, positive
    affect, and interpersonal relations.

[^4]: This estimate has been found on other studies. For example, the
    National Alliance for Caregiving and Alzheimer's Association, 1999,
    reported in (Tennstedt) that up to 11% of the non-dementia
    caregivers and up to 13% of the dementia caregivers reported a
    change in employment associated with caregiving.

[^5]:
    > This prototype requires an estimate of the proportion of people in
    > assisted living who drive their own vehicles and who have mobility
    > provided by family and friends.

[^6]: In 2000 there were an estimated 35 million people in the United
    States age 65 or older. [(Older Americans 2000: Key Indicators of
    Well-Bei]{.underline}ng, 2000)

[^7]: From the population age 65 and older in 2000, 35 million,
    Prototype 1 is estimated using the proportion of people age 65 and
    older reporting excellent health in 1996, 72.2%. [(Older Americans
    2000: Key Indicators of Well-Bei]{.underline}ng, 2000)

[^8]: The estimate for the total size of Prototypes 2-4 is extrapolated
    to be 7 million based on the percentage of the age 65 and older
    population in 1990 defined as functionally dependent. (Hing & Bloom,
    1990; Hobbs & Damon, 1996[; Older Americans 2000: Key Indicators of
    Well-Bei]{.underline}ng, 2000)

[^9]: This proportion is based on the percentage of Medicare
    beneficiaries who reported only receiving formal care. [(Older
    Americans 2000: Key Indicators of Well-Bei]{.underline}ng, 2000)

[^10]: The estimate of the proportion of the age 65 and older population
    with no way to obtain care is based on the "percent reporting
    difficulty obtaining care" in the Medicare Current Beneficiary
    Survey as reported in [(Older Americans 2000: Key Indicators of
    Well-Bei]{.underline}ng, 2000) This estimate may be low. (National
    Center for Health Statistics, 1999) reports that 1.4 million people
    age 70 and older, contacted between 1994 and 1996, reported that
    they had "unmet needs" related to ADL's and IADL's.

[^11]: Is assisted living the right choice? Consumers Reports, Feature
    Report January 2001
    [Http://www.consumerreports.org](http://www.consumerreports.org/)/main

[^12]: In 1997 the nursing home residence rate for people age 65 and
    over was 45 per 1,000. [(Older Americans 2000: Key Indicators of
    Well-Bei]{.underline}ng, 2000)

[^13]: A special issue of the Journal of Gerontology, May 1987,
    describes the AHEAD data set.

[^14]: Provide data for household size for older people in Prototype 2
    as well as number of people in household of driving age and whether
    the spouse drives.