Article

Healthy Cognitive Aging and Leisure Activities Among the Oldest Old in Japan: Takashima Study

Department of Public Health, College of Health and Human Sciences, Oregon State University, Corvallis, OR 97401, USA.
The Journals of Gerontology Series A Biological Sciences and Medical Sciences (Impact Factor: 5.42). 12/2008; 63(11):1193-200. DOI: 10.1093/gerona/63.11.1193
Source: PubMed

ABSTRACT

Little is known regarding the normative levels of leisure activities among the oldest old and the factors that explain the age-associated decline in these activities.
The sample included 303 cognitively intact community-dwelling elderly persons with no disability in Activities of Daily Living (ADL) and minimal dependency in Instrumental ADL (IADL) in Shiga prefecture, Japan. We examined (i) the nature and frequency of leisure activities, comparing the oldest old versus younger age groups; (ii) factors that explain the age-associated differences in frequencies of engagement in these activities; and (iii) domain-specific cognitive functions associated with these activities, using three summary index scores: physical and nonphysical hobby indexes and social activity index.
The oldest old (85 years old or older) showed significantly lower frequency scores in all activity indexes, compared with the youngest old (age 65-74 years). Gait speed or overall mobility consistently explained the age-associated reduction in levels of activities among the oldest old, whereas vision or hearing impairment and depressive symptoms explained only the decline in social activity. Frequency of engagement in nonphysical hobbies was significantly associated with all cognitive domains examined.
Knowing the factors that explain age-associated decline in leisure activities can help in planning strategies for maintaining activity levels among elderly persons.

Full-text

Available from: Hiroko Hayama Dodge
Genetic and Environmental Determinants of Healthy Aging
Healthy Cognitive Aging and Leisure Activities
Among the Oldest Old in Japan: Takashima Study
Hiroko H. Dodge,
1,2,3
Yoshikuni Kita,
4
Hajime Takechi,
5
Takehito Hayakawa,
6
Mary Ganguli,
7
and Hirotsugu Ueshima
4
1
Department of Public Health, College of Health and Human Sciences, Oregon State University, Corvallis.
2
Department of Neurology, Oregon Health & Science University, Portland.
3
Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pennsylvania.
4
Department of Health Science, Shiga University of Medical Science, Japan.
5
Department of Geriatric Medicine, Graduate School of Medicine, Kyoto University, Japan.
6
School of Medicine, Fukushima Medical University, Japan.
7
Department of Psychiatry, University of Pittsburgh School of Medicine, Pennsylvania.
Background. Little is known regarding the normative levels of leisure activities among the oldest old and the factors
that explain the age-associated decline in these activities.
Methods. The sample included 303 cognitively intact community-dwelling elderly persons with no disability in
Activities of Daily Living (ADL) and minimal dependency in Instrumental ADL (IADL) in Shiga prefecture, Japan. We
examined (i) the nature and frequency of leisure activities, comparing the oldest old versus younger age groups; (ii) factors
that explain the age-associated differences in frequencies of engagement in these activities; and (iii) domain-specific
cognitive functions associated with these activities, using three summary index scores: physical and nonphysical hobby
indexes and social activity index.
Results. The oldest old (85 years old or older) showed significantly lower frequency scores in all activity indexes,
compared with the youngest old (age 65–74 years). Gait speed or overall mobility consistently explained the age-
associated reduction in levels of activities among the oldest old, whereas vision or hearing impairment and depressive
symptoms explained only the decline in social activity. Frequency of engagement in nonphysical hobbies was significantly
associated with all cognitive domains examined.
Conclusions. Knowing the factors that explain age-associated decline in leisure activities can help in planning
strategies for maintaining activity levels among elderly persons.
Key Words: Oldest old—Normative data—Leisure activities—Healthy aging—Japanese cohort—Takashima Study.
C
ONTINUING engagement with life has been described
as one of the three components of successful aging (1).
Higher engagement in leisure activities appears to be
protective against cognitive decline and dementia (2–7),
although the mechanism is not fully understood (8,9).
Although some decline in activity level is expected with
advancing age, there is little information thus far on their
normative levels, and on factors (e.g., morbidities, cognitive
functions) that explain age-associated decline in leisure
activities, particularly among relatively healthy and cogni-
tively unimpaired elderly persons. As individuals 85 years
old or older (‘‘oldest-old’’) are the fastest growing segment
of the population in Japan and most industrialized countries
(10), such information can be useful for planning recrea-
tional programs to improve the quality of life of the elderly
population in the community, strategies to maintain the
activity levels among them, and to help distinguish normal
from pathological aging.
In a sample of community-dwelling, cognitively un-
impaired elderly persons in Shiga, Japan, we identified three
types of leisure activities: physically demanding activities,
nonphysical activities, and activities mostly requiring social
interactions. We hypothesized that (i) activity levels are
lower among the oldest old than the younger old, (ii) decline
in leisure activities among the oldest old is explained by
decreased physical function and lower general cognitive
function, and (iii) levels of engagement in specific leisure
activities are associated with specific domains of cognitive
function.
M
ETHODS
The survey was conducted in Takashima County, Shiga
Prefecture, located west of Biwako Lake, the largest lake in
Japan. In 2005, the county’s population was 53,950, with
25.1% 65 years old or older, higher than the national
average of 20.1%. About 7.7% of the total labor force
engages in farming, fishing, or forestry; about 35% in
1193
Journal of Gerontology: MEDICAL SCIENCES Copyright 2008 by The Gerontological Society of America
2008, Vol. 63A, No. 11, 1193–1200 Cite as: J Gerontol A Biol Sci Med Sci
Page 1
construction and manufacturing industries; and 58% in
wholesale, medical, welfare, or other service industries.
The Takashima county municipal government generated
a list of names, addresses, and telephone numbers of the
population, based on comprehensive resident registration
records. An age-stratified random sample was drawn of
residents 65 years old or older, over sampling the oldest old.
The list was generated until we reached the targeted sample
size of approximately 130 individuals each in the age groups
65–74 years, 75–84 years, and 85 years old or older, with
similar proportions for men and women. The survey was
conducted between 2005 and 2006, and approved by the
Institutional Review Boards at Shiga University of Medical
Science in Japan, the University of Pittsburgh, and the
Oregon State University.
Among 957 randomly selected individuals invited by
letter to participate in the study, a total of 391 participants
(40.8%) consented and underwent face-to-face interviews.
The participation rates varied from 32.2% (women 85 years
old or older) to 52.1% (men 65–74 years). Of persons
younger than 85 years, 41.8% of refusers indicated that they
were ‘too busy’’ to particulate. In the older age group,
41.0% of refusers were either hospitalized or ‘‘too sick’ to
participate. Registered nurses conducted the interviews after
undergoing intensive training for assessment reliability.
Surveys were conducted at participants’ homes unless they
preferred another location.
We defined as normal those participants who were free
from cognitive impairment and could live in the community
with minimal dependency on others. For the current study,
we selected community-dwelling elderly persons with test
scores 21 on the Japanese version of the Mini-Mental
State Examination (J-MMSE) (11,12), with no disabilities in
ADL tasks, and with minimal (2) IADL disabilities. The
conventional threshold MMSE score of 24 for defining
cognitive impairment was lowered to 21 in consideration of
the low educational level of the sample (mean 9.6 years of
education, corresponding to finishing middle school in
Japan). The eight IADL tasks examined were the abilities
to independently use public transportation, shop for daily
necessities, prepare meals, pay bills, handle their own
banking, use the telephone, manage their own medication,
and clean their own rooms. The first five tasks are taken
from the Tokyo Metropolitan Institute of Gerontology Index
of Competence (13). We added questions regarding abilities
for telephone usage, medication management, and cleaning
their own rooms on the basis of face validity, because of
the increasing importance of these tasks for independent
living. Interviewer nurses indicated their impression of the
accuracy of self-reported (I)ADL items.
Local nurses, area caregivers, and researchers consensu-
ally created a comprehensive list of the various types of
leisure activities conducted by the elderly persons in the
survey areas. A survey questionnaire was then developed
based on this list. For each activity, participants scored their
frequency of engagement as follows: 1 ¼not at all, 2 ¼once
per year or less, 3 ¼several times per year, 4 ¼several times
per month, 5 ¼several times per week, and 6 ¼every day or
almost every day. Summing scores for each activity
provided an ‘index score’’ for each of the three groups of
activities: physical and nonphysical hobbies and social
activity. In the statistical models, we used z-transformed
scores based on the distribution for each index to take into
account the differences in score ranges.
Domain-Specific Cognitive Functions
In addition to the J-MMSE, an indicator of general
cognitive function, Japanese cognitive tests examined and
their specific domains were as follows: (i) Digit Span
Forward and Backward (attention and working memory)
from Wechsler Adult Intelligence Scale Revised (WAIS-R)
(14); (ii) Word list immediate recall (learning/acquisition)
from the Alzheimer’s Disease Assessment Scale (ADAS)
(15); (iii) Word list delayed recall (memory) from the ADAS
(15); (iv) Block Designs-5 blocks, even numbers (visuo-
spatial ability) from the WAIS-R Block Design (14); (v)
Trail-making test A (16) (psychomotor speed); (vi) Trail-
making test B (16) (executive function); and (vii) Word
Fluency Categories: Animals and Vegetables (language)
from the Consortium to Establish a Registry for Alzheimer
Disease (CERAD) (17). The above tests are already
validated in Japan.
Other Variables
Other potential explanatory factors for age-associated
reduction in leisure activities were considered within the
following blocks: (i) Basic demographic variables: age, sex,
years of education, living arrangement (alone vs with
others); (ii) Basic physical function: vision or hearing
impairment, gait speed/mobility measured by the Timed Up
and Go (TUG) test (18,19); and (iii) Morbidity burden:
number of depressive symptoms measured by the Japanese
Geriatric Depression Scale, 15-item version (J-GDS-15)
(20), and total numbers of prescription medication.
Vision impairment was assessed by response to a question
‘what is your visual ability with your visual aid?’’ (1 ¼
Normal, 2 ¼ Can recognize a person’s face approximately
1 meter away, and 3 ¼ Unable or almost unable to see.)
Hearing was assessed by a self-report to a question ‘‘what is
your hearing ability with your hearing aid?’’ (1 ¼ No
difficulty in daily communication, 2 ¼ Can only hear loud
voices or sounds, and 3 ¼Unable or almost unable to hear.)
Participants with scores of 2 or 3 were regarded as having
vision and/or hearing impairment. The total number of pre-
scription medications was used as an objective measure of
overall morbidity and medical burden (21) and was recorded
by the study nurses, who examined the participant’s medica-
tion bottles and envelopes.
Statistical Methods
Age group differences in each of the three indexes were
first examined by t test (nonphysical and social activity
indexes) and Wilcoxon rank sum nonparametric test
(physical activity index, due to skewed distribution),
comparing the youngest age group (65–75 years) with each
of two other age groups (75–84 years and 85 years or older).
We examined factors mediating the age-associated differ-
ences in each of the three indexes using linear regression
models (outcome being nonphysical hobby and social
activity indexes) and a logistic regression model (outcome
1194 DODGE ET AL.
Page 2
being the physical activity index, the lowest 25
th
percentile
vs others). We first included in the model two age groups
(75–84 years and 85 years old or older), with the youngest
age group as a reference group, controlling for sex, years of
education, and living arrangement. In preliminary analysis,
the oldest group showed significantly lower frequency
scores in all activity indexes, compared with the youngest
group. We then added the three blocks of covariates
mentioned above separately into the model, and finally fit
a full model with all variables.
The associations between domain-specific cognitive
functions and each of three activity indexes were examined
using linear regression models with each z-transformed
cognitive test score as an outcome, controlling for covariates
mentioned above.
R
ESULTS
Among 391 potential participants interviewed, we exclud-
ed 42 persons (10.7%) who could not conduct one or more
ADL tasks, 31 persons (7.9%) with MMSE scores ,21, 12
persons (3.4%) who had two or more disabilities in IADL
tasks, and 3 persons (0.9%) with ADL/IADL responses
considered unreliable by the assessing nurses. Proportions of
persons included in the current analysis of 391 potential
participants are listed in the third row of Table 1. As
expected, the proportion declined with increasing age group.
The characteristics of the 303 participants used in the
current study are listed in Table 1. Their mean age (standard
deviation) [ranges] was 76.1 (6.9) [65.0–96.0]. The most
frequently observed IADL dependencies were meal prepa-
ration among men (n ¼ 25, 16.2%) and using public
transportation among women (n ¼ 17, 11.4%). All other
disabilities were reported by fewer than 10 participants. The
proportion of participants living in a two- or three-
generational household was 68.9%.
Table 2 shows common activities and distribution of
frequency by age groups, limited to activities in which more
than 15 participants (5% of the sample) were engaged at
least once per year. Overall, compared with the youngest old
group, the oldest group had significantly lower scores in all
three activity indexes. Notable findings include: .30% of
the oldest old also engaged in gardening every day or almost
every day; talking with the younger generation did not differ
much by age groups, possibly reflecting the high prevalence
of multigenerational households in the survey area; the
oldest old age group was much less likely to socialize with
neighbors, friends, and relatives.
Table 3 shows the results of models examining factors that
explain the reduced levels of leisure activities among the
oldest old in three indexes. In models with only demographic
variables, participants 85 years old or older had significantly
lower nonphysical and social activity index scores and also
a higher likelihood of being in the lowest 25 percentile in
physical activity index, compared with the youngest group.
Nonphysical Hobby Index
In each subsequent model, adding physical functional
indicators, morbidity burden, or general cognitive function
Table 1. Characteristics of Study Participants Based on Inclusion Criteria: MMSE 21, No ADL Disabilities, and
Minimal IADL Disabilities (2): Takashima Study 2005–2006
Age Group 65–69 70–74 75–79 80–84 85þ p Value
Total N ¼ 391 N ¼ 72 N ¼ 67 N ¼ 89 N ¼ 65 N ¼ 98
N (%) meeting inclusion criteria
Total N ¼ 303 N ¼ 68 (94.4) N ¼ 62 (92.5) N ¼ 77 (86.5) N ¼ 53 (81.5) N ¼ 43 (43.9)
Female, % 51.5 41.9 55.8 49.1 45.2 NS*
Years of education 10.6 9.7 9.5 9.2 8.9 .003
y
% Living alone 2.9 4.8 6.5 18.9 14.0 .011*
% With either vision or hearing impairment 0 3.2 3.9 7.6 53.5 ,.001*
Timed Up and Go (TUG) test 10.3 11.8 12.4 14.0 19.0 ,.001
y
Japanese Geriatric Depression Scale
(J-GDS-15), % with score 11 1.5 1.6 5.2 3.8 7.0 .471*
Total No. of prescription medication 2.5 3.4 4.0 4.3 5.6 ,.001
y
IADL disabilities, %
None 89.7 87.1 80.5 73.6 55.8 ,.001*
1 10.3 9.7 18.8 22.6 23.4
2 0 3.2 1.3 3.8 20.9
% with 21 J-MMSE 24 5.9 11.3 15.6 17.0 34.9 .001*
WAIS-R Digit Span Forward (SD) 5.89 (2.15) 5.85 (1.82) 5.92 (1.85) 5.88 (1.56) 5.30 (2.23) NS
y
WAIS-R Digit Span Backward (SD) 5.08 (1.42) 4.83 (1.19) 4.96 (1.52) 4.73 (1.46) 4.09 (1.22) .005
y
ADAS-word list immediate recall sum of
three trials (SD) 21.19 (3.24) 18.95 (3.66) 18.75 (3.74) 17.96 (3.82) 15.54 (4.31) ,.001
y
ADAS-word list delayed recall (SD) 7.52 (2.10) 6.57 (2.02) 5.97 (2.63) 5.86 (2.48) 4.42 (2.50) ,.001
y
WAIS-R Block Design–5 block designs (SD) 14.55 (4.02) 13.01 (3.46) 11.50 (4.17) 10.98 (4.33) 7.95 (4.49) ,.001
y
Trail-Making A: connections per second (SD) 0.59 (0.20) 0.41 (0.14) 0.38 (0.13) 0.36 (0.12) 0.27 (0.11) ,.001
y
Trail-Making B: connections per second (SD) 0.23 (0.07) 0.17 (0.06) 0.16 (0.06) 0.13 (0.06) 0.07 (0.06) ,.001
y
Word Fluency Category (SD) 32.37 (8.07) 29.67 (7.82) 27.86 (6.48) 26.96 (5.67) 23.47 (6.54) ,.001
y
Notes: *Pearson chi-square statistics.
y
Analysis of variance.
J-MMSE ¼ Japanese version of the Mini-Mental State Examination; ADL ¼ Activities of Daily Living; IADL ¼ Instrumental Activities of Daily Living; SD ¼
standard deviation; WAIS-R ¼ Wechsler Adult Intelligence Scale Revised; ADAS ¼ Alzheimer’s Disease Assessment Scale; NS ¼ not significant.
1195LEISURE ACTIVITIES AMONG THE OLDEST OLD
Page 3
Table 2. Frequently Engaged Activities (N ¼ 303)
Activities
Not at
all %
Once per
Year or More %
Once per Month
or More % Almost Every Day %
Nonphysical activities
Watching TV
65 Age , 75 0.7 0 0.7 98.4
75 Age , 85 1.5 0 0.7 96.9
Age 85 0 0 2.3 97.7
Listening to radio
65 Age , 75 64.2 1.5 10.0 23.8
75 Age , 85 74.6 0.7 9.2 15.3
Age 85 81.4 4.7 4.7 9.3
Reading newspaper
65 Age , 75 3.0 0 6.9 90.0
75 Age , 85 5.3 0 6.1 88.5
Age 85 9.3 0 2.3 88.4
Reading magazines
65 Age , 75 32.3 17.6 42.3 7.6
75 Age , 85 35.3 20.0 36.9 7.6
Age 85 46.5 7.0 34.8 11.6
Reading books
65 Age , 75 40.0 23.0 23.0 13.8
75 Age , 85 45.3 14.6 20.7 19.2
Age 85 60.4 4.6 20.9 13.9
Playing board/card games
65 Age , 75 69.2 18.4 8.4 3.8
75 Age , 85 81.5 10.0 7.6 0.7
Age 85 86.0 2.3 11.6 0
Doing crafts
65 Age , 75 43.0 20.0 29.4 8.4
75 Age
, 85 39.2 21.5 30.0 9.2
Age 85 55.8 16.2 27.9 0
Performing in a chorus/singing karaoke
65 Age , 75 79.2 3.8 14.6 2.3
75 Age , 85 77.6 5.4 13.8 3.0
Age 85 81.4 2.3 13.9 2.3
Writing haiku/senryu
65 Age , 75 92.3 2.3 5.3 0
75 Age , 85 86.9 3.8 7.6 1.5
Age 85 90.7 2.3 6.9 0
Traveling
65 Age , 75 20.7 72.3 6.1 0.7
75 Age , 85 36.9 59.2 3.8 0
Age 85 60.4 39.5 0 0
Attending classes
65 Age , 75 63.0 23.0 13.8 0
75 Age , 85 72.3 15.3 11.5 0.7
Age 85 72.0 18.6 9.3 0
Nonphysical Activity Index, Mean (SD)*
65 Age , 75 26.9 (7.8) p value on the difference (compared with the youngest)
y
75 Age , 85 25.7 (7.9) p ¼ .19
Age 85 21.8 (7.9) p , .001
Physical activities
Playing Gate Ball
z
65 Age , 75 74.6 4.6 20.0 0.7
75 Age , 85 67.6 6.1 24.6 1.5
Age 85 79.0 4.6 11.6 4.6
Hiking
65 Age , 75 84.6 12.3 3.0 0
75 Age , 85 93.0 6.9 0 0
Age 85 100.0 0 0 0
1196 DODGE ET AL.
Page 4
Table 2. Frequently Engaged Activities (N ¼ 303) (Continued)
Activities
Not at
all %
Once per
Year or More %
Once per Month
or More % Almost Every Day %
Swimming
65 Age , 75 84.6 3.8 6.1 1.5
75 Age , 85 98.4 0 0.7 0.7
Age 85 97.6 2.3 0 0
Stretching
65 Age , 75 65.3 9.2 10.7 14.6
75 Age , 85 70.0 3.8 13.0 13.0
Age 85 60.4 0 11.6 27.9
Walking
65 Age , 75 66.9 3.0 16.1 13.8
75 Age , 85 58.4 0.7 14.6 26.1
Age 85 67.4 0 9.3 23.2
Fast Walking (sport)
65 Age , 75 75.3 3.8 11.5 9.2
75 Age , 85 90.7 0.7 4.6 3.8
Age 85 100.0 0 0 0
Bicycling
65 Age , 75 92.3 0 3.8 3.8
75 Age , 85 87.6 0 3.0 9.2
Age 85 95.3 0 0 4.6
Gardening
65 Age , 75 10.0 7.6 34.6 47.6
75 Age , 85 10.7 6.1 32.3 50.7
Age 85 25.5 9.3 27.9 37.2
Physical Activity Index, Mean (SD)
§
65 Age , 75 6.0 (4.6) p value on the difference (compared with the youngest)
k
75 Age , 85 5.4 (4.3) p ¼ .45
Age 85 4.3 (4.2) p ¼ .04
Social activities
Talk with younger generation
65 Age , 75 5.3 8.4 35.5 50.7
75 Age , 85 5.3 12.3 33.8 48.4
Age 85 6.9 18.6 27.9 46.5
Talk with neighbors
65 Age , 75 3.8 3.0 50.7 42.3
75 Age , 85 3.8 4.6 46.9 44.6
Age 85 18.6 4.6 48.8 27.9
Visit/call friends and relatives
65 Age , 75 9.2 13.8 66.9 10.0
75 Age , 85 13.0 16.9 59.2 10.7
Age 85 30.2 9.3 53.4 6.9
Volunteering
65 Age , 75 38.4 33.8 26.1 1.5
75 Age , 85 28.4 46.9 24.6 0
Age 85 53.4 41.8 4.6 0
Social Activity Index Mean (SD)
65 Age , 75 11.0 (2.6) p value on the difference (compared with the youngest)
y
75 Age , 85 10.6 (2.7) p ¼ .22
Age 85 9.2 (3.6) p , .001
Notes: *Activities not listed in this table, but included in the calculation of the index (i.e., reported by ,15 participants): pachinko (an arcade game similar to
pinball) (n ¼ 3), computer games (n ¼ 9), writing in diaries/novels (n ¼8), and listening to music (n ¼ 8).
y
Based on the t test.
z
Gate Ball: A type of miniature golf where teams score a point for each ball to hit through a gate.
§
Activities not listed in this table, but included in the calculation of the index (i.e., reported by ,15 participants): jogging (n ¼6), golf (n ¼8), tennis/bowling/
ping-pong (n ¼ 3), dancing/Japanese dancing (n ¼ 4), martial arts/Kikou (Qigong) (n ¼4), and fishing (n ¼ 11).
k
Based on the Wilcoxon rank sum nonparametric test.
SD ¼standard deviation.
1197LEISURE ACTIVITIES AMONG THE OLDEST OLD
Page 5
separately in the model, the coefficient of 85 years old or
older became insignificant (not in table). In the full model,
higher levels of nonphysical hobby activities were associ-
ated with female gender, more education, higher mobility
(TUG), and fewer depressive symptoms (J-GDS). The
J-MMSE, which was significant in the model containing
only this variable and demographic variable, became in-
significant in the full model, suggesting that the effect of
general cognition on the levels of nonphysical hobbies
was not independent of morbidity burden.
Social Activity Index
The reduced levels of social interaction among the oldest
old became insignificant when we added the block of
physical function variables. In the full model, higher levels
of social interaction were associated with female gender, no
vision or hearing impairment, higher mobility function, and
fewer depressive symptoms.
Physical Hobby Index
The reduced level of engagement in physical hobbies
among the oldest old was explained only by mobility. No
other variables were significant in the full model.
Associations Between Domain-Specific Cognitive
Functions and Activity Indexes
Physical hobby and social activity indexes were not
associated with any specific cognitive domains, whereas
the nonphysical hobby index was associated with all of the
cognitive domains (not in table). Among the cognitive
domains, visuospatial (p ¼ .0002) and language abilities
(p , .0001) were strongly associated with nonphysical
hobby index even with the p value adjusted under multiple
comparisons (p , .0024).
We conducted three post hoc analyses. First, the strong
association between mobility function and nonphysical
and social activities could have been because of the inability
of participants with limited mobility to use public trans-
portation, for example, for attending classes and visiting
friends. To test this hypothesis, we refit the model after
deleting 22 participants (17 women and 5 men) with dis-
ability in using public transportation. The results reported in
Table 3 were virtually unchanged.
Second, we replaced the prescription medications variable
with self-reported information on specific current diseases to
determine whether specific disorders might have indepen-
dent effects on activity index. We created the following
seven disease categories for the presence of cerebrovascular
disease, cardiovascular disease, hypertension, hypercholes-
terolemia, musculoskeletal diseases, diabetes, and others.
None of these disease variables were significant, and the
results did not change.
Third, we separately examined the associations of domain-
specific cognitive functions with frequencies of engagement
in each of 11 nonphysical activities. Significant associations
with z-standardized scores at p , .0045 (significance level
adjusted for multiple comparisons) were found for the
following activities: reading books, with digit span forward
and backward (attention and working memory) (p ¼ .003)
and block design (visuospatial ability) (p¼.0007); traveling,
Table 3. Factors Explaining Age Differences in Leisure Activity Frequencies
Nonphysical Activity Index* Social Activity Index* Physical Activity Index
y
Demographic
Variables Only Full Model
Demographic
Variables Only Full Model
Demographic
Variables Only Full Model
Covariates Coefficient (SD) Coefficient (SD) Coefficient (SD) Coefficient (SD) OR (95% CI) OR (95% CI)
Demographic variables
Age 75–84 NS NS NS NS NS NS
Age 85þ0.30
z
0.15 NS 0.77
§
0.20 NS NS 5.10
z
(1.33, 19.58)
NS
Female 0.35
§
0.09 0.29
§
0.09 0.48
§
0.13 0.42
§
0.12 NS NS
Years of education 0.15
§
0.02 0.11
§
0.02 NS NS NS NS
Living alone NS NS NS NS NS NS NS
Physical Function
Visual or hearing impairment NS 0.48
z
0.24 NS
Gait speed/Lower extremity
function (TUG test)
0.02
z
0.01 0.03
§
0.01 1.16
§
(1.05, 1.27)
Morbidity Burden
J-GDS 0.07
§
0.01 0.09
§
0.02 NS
Total No. of prescription
medications 0.02
z
0.01 NS NS
General cognitive function
J-MMSE NS NS NS
Notes: *Based on ordinal linear regression models.
y
Based on logistic regression; outcome is persons with the lowest 25th percentile in physical activity index (vs others).
z
p , .05.
§
p , .01.
SD ¼standard deviation; CI ¼confidence interval; TUG ¼Timed Up and Go; J-GDS ¼Japanese Geriatric Depression Scale; J-MMSE ¼Japanese version of the
Mini-Mental State Examination; NS ¼ not significant.
1198 DODGE ET AL.
Page 6
with word list immediate recall (learning/acquisition) (p ¼
.003), and word fluency (language) (p ¼.0005).
D
ISCUSSION
The news media frequently carry human interest stories
about very old individuals who maintain very high activity
levels, implying that these are exceptional people. In fact,
little is known regarding the normative levels of leisure
activities and social engagement among the oldest old and
the factors that explain the apparently typical age-associated
decline among normal elderly persons. Overall, in this
community-dwelling, relatively healthy, cognitively un-
impaired, elderly Japanese sample, we found significant
declines in activity scores among the oldest old (85 years
old or older) compared with the youngest old (65–74 years)
in all three types of leisure activities (physical and
nonphysical hobbies and social activities).
Gait speed consistently explained the age-associated reduc-
tion in levels of activities. Previous studies of older adults
have reported that average gait speed/velocity predicted dis-
abilities and health outcomes including disability incidence,
nursing home admission, new falls, mortality (22–24), and
cognitive decline (25,26). Abnormal gait also predicts non-
Alzheimer’s disease dementia (27) and cognitive decline (28).
Gait is not a simple motor activity, but a cognitively complex
task (29). Various leisure activities have been found to be
associated with reduced risk of dementia and rate of cognitive
decline (2–7). Greater cognitive challenge might stimulate
and increase cognitive reserve (8), or, alternatively, persons
with greater cognitive reserve might be capable of rising
to greater cognitive challenges than could persons with less
reserve. Our finding suggests that mobility could play a role
in the relationship between leisure activities and dementia
risk: slowing gait speed leading to reduced engagement in
various hobby activities, in turn associated with lesser
cognitive reserve and increased likelihood of manifesting
dementia. In addition, subclinical cerebrovascular or other
brain pathology, reducing gait speed (30–33), could also
contribute to the development of dementia. Regardless of
mechanism, gait speed could add a dimension to the study of
potential mechanisms underlying the apparently protective
effect of leisure activity against cognitive decline. Further,
the elderly population may benefit from opportunities to
strengthen lower extremity functions, improving gait and
mobility so as to maintain optimal activity levels and
potentially benefit their cognitive functioning as well.
Contrary to our hypothesis, vision or hearing impairment
did not explain the decreased levels of engagement except in
social activities. Our finding suggests that relatively healthy
elderly persons might be able to retain their levels of
physical and nonphysical leisure activities, if they avoid
depressive symptoms and reduced mobility.
Interestingly, age-associated decline in the levels of en-
gagement in physical activities was not explained by morbid-
ity burden, as was also found in the Study of Osteoporotic
Fractures (34). That study found that self-reported arthritis
was not independently associated with taking walks, the most
popular physical exercise among their study participants. It
has been suggested that deteriorating health or disease can
work either as a motivator for increasing physical activity or
as a factor reducing the activity (35). Possibly because of this
bidirectional effect of morbidity on physical activity, neither
the total numbers of prescription medications taken nor
specific disease variables were significantly associated with
physical activity among our sample of relatively healthy
community-dwelling participants. Furthermore, because our
study selection criteria included absence of ADL limitations
with minimal IADL disabilities, our participants’ illnesses
may have been too mild to interfere substantially with their
physical activities. Additionally, physical hobby activities
could be associated with factors not examined in this study
such as proximity to the park or walking path, easy access to
public transportation, climate, or life course factors such as
exposure to exercise during adolescence (35).
We found that the frequency of engagement in non-
physical hobbies was significantly associated with all of the
cognitive domains examined here. Reading a book and
traveling were found to be especially cognitively demanding
activities; reading a book was associated with attention,
working memory, and visuospatial ability, and traveling with
learning or acquisition and fluency. These activities could be
encouraged among the elderly population even though their
longitudinal effect on cognition has yet to be confirmed.
Our study had some limitations. Results from a particular
area in Japan have limited generalizability to other regions.
Categorization of each activity into the three indices used in
this study is somewhat arbitrary because there is much
potential for overlap among them. Factor analysis is often
used for categorizing psychometric measurements or func-
tional abilities, but it is not appropriate here as hobbies are
based on personal choices. We did not measure socioeco-
nomic status or daily pain, which can influence the level of
leisure activities, or health-related quality of life, which is
reportedly improved by cognitively demanding activities
such as cognitive training (36). The study participation rate
of 40% is quite low, and our sample may have been biased
toward persons who tend to volunteer and be socially active.
The cross-sectional nature of this study limits the ability to
infer causal directions.
Japan and also the United States are projected to
experience a large increase of the oldest old population
(37). Preserved cognitive function is a central component of
healthy aging and associated with reduced risk of disabilities
and mortality (38–42). Because even the oldest old with
superior health are at high risk of developing dementia (43),
it is urgent to find preventive strategies against cognitive
decline (44). If increased opportunities to conduct appro-
priate leisure and social activities could sustain and prolong
their physical and cognitive health, they would have
important public health implications. Further research on
factors explaining age-associated decline among healthy
elderly persons is warranted.
ACKNOWLEDGMENT
This study was supported by grants from the Japanese Ministry of
Education, Culture, Sports, Science and Technology (17390186, 16659159)
and by the National Institute on Aging (K01AG023014).
We thank Keiko Aotani, Noriko Fujisawa, Toshie Sugihara, and Fusako
Katsurada for data collection. We greatly appreciate the time and effort
devoted by our study participants in this study. We also thank Dr. Bradley
Willcox for his helpful suggestions.
1199LEISURE ACTIVITIES AMONG THE OLDEST OLD
Page 7
CORRESPONDENCE
Address correspondence to Hiroko Dodge, PhD, 260 Waldo Hall,
Department of Public Health, Oregon State University, Corvallis, OR
97401. E-mail: dodge@ohsu.edu
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Received October 6, 2007
Accepted March 5, 2008
Decision Editor: Luigi Ferrucci, MD, PhD
1200 DODGE ET AL.
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  • Source
    • "The perceived importance of reading does not change with the vision loss (Ryan et al., 2003). Reading is a popular leisure activity among senior adults without visual impairments as well (Dodge et al., 2008; Williamson, 1998). Health and finance as topics of interest were identified in the research of information seeking behaviour of visually impaired citizens by Williamson, Shauder and Bow (2000). "
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    • "Based on the benefits of leisure participation in the lives of older adults, some researchers have explored how different leisure activities have influenced the health of older adults (Chen & Fu, 2011; Dodge et al., 2008; Everard, Lack, Fisher, & Baum, 2000). Everard and his colleagues discovered that in later life, physical leisure activities such as gardening, walking, and exercising, were associated with increased physical health, while less physical activities such as social or telephone conversations were associated with improved mental health. "
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