Effects of different amounts of exercise on preventing ...

For peer review only

Impacts of different exercise models on depressive symptoms in community-dwelling older adults: a

longitudinal cohort study

Journal: BMJ Open

Manuscript ID bmjopen-2016-014256

Article Type: Research

Date Submitted by the Author: 13-Sep-2016

Complete List of Authors: Chang, Yu-Chen ; Ditmanson Medical Foundation Chia-Yi Christian Hospital, Community Health Lu, Mei-Chun ; Kuang Tien General Hospital, Medical Research

Hu, I-Han; National Cheng Kung University College of Medicine, Institute of Gerontology Wu, Wan-Chi; National Cheng Kung University College of Medicine, Public Health Hu, Susan; National Cheng Kung University College of Medicine, Public Health

<b>Primary Subject Heading</b>:

Mental health

Secondary Subject Heading: Geriatric medicine, Epidemiology, Sports and exercise medicine

Keywords: EPIDEMIOLOGY, MENTAL HEALTH, Depression & mood disorders < PSYCHIATRY, SPORTS MEDICINE

For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml

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Impacts of different exercise models on depressive symptoms in

community-dwelling older adults: a longitudinal cohort study

Yu-Chen Chang1, Mei-Chun Lu

2, I-Han Hu

3, Wan-Chi Ida Wu

4, Susan C. Hu

5*

1. Yu-Chen Chang, MD, PhD, Department of Community Health, Chia-Yi Christian

Hospital, Chia-Yi, Taiwan. [email protected]

2. Mei-Chun Lu, MS, Department of Medical Research, Kuang Tien General Hospital,

Taichung, Taiwan. [email protected]

3. I-Han Hu, MS, Institute of Gerontology, College of Medicine, National Cheng Kung

University. [email protected]

4. Wan-Chi Ida Wu, PhD, Department of Public Health, College of Medicine, National

Cheng Kung University, Tainan, Taiwan. [email protected]

5. Susan C. Hu, PhD, Department of Public Health, College of Medicine, National Cheng

Kung University, Tainan, Taiwan. [email protected]

*Corresponding author: Susan C. Hu, PhD

Dept. of Public Health, College of Medicine, National Cheng Kung University,

No.1, University Rd, Tainan, Taiwan, 70101

E-mail: [email protected]

Tel: +886-972-967800, Fax: +886-6-2359033

Running title: Exercise on depression

World count: Abstract 252, Text 3010

Number of figures: 1

Number of tables: 4

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ABSTRACT

Objectives: to examine the impacts of four different exercise models on depressive

symptoms in community-dwelling older adults.

Design: prospective cohort study.

Setting: a nationally representative sample, Taiwan.

Participants: Four waves of the survey “Taiwan Longitudinal Study on Aging (TLSA)” from

1996 to 2007 were used. A total of 2,673 older adults aged 65 and over were recruited.

Primary and secondary outcome measures: Depressive symptoms were measured using

the Center for Epidemiologic Studies Depression scale (CESD). Four different exercise

models were examined, including (1) 3 times/week, 15 min/time; (2) 3 times/week, 30

min/time; (3) 6 times/week, 15 min/time; and (4) 6 times/week, 30 min/time. All exercise

models were required to have at least moderate intensity. The impacts of different exercise

models on depressive symptoms were analyzed using generalized linear mixed models.

Results: More than one fifth of the elderly had depressive symptoms (CESD ≥10). About

38.6% of older adults met the lowest criteria of exercise model 1, and fewer (28.0%) met the

highest criteria of model 4. Only exercise model 4 in the current survey was initially related

to lower depressive symptoms (OR=0.8, 95%CI=0.66-0.95). However, after considering the

interaction between time and changes in the exercise patterns, we found that all persistent

exercise models, even if very low amount (3 times/week, 15 min/week), had significantly

preventive effects on depressive symptoms (OR=0.56~0.67).

Conclusion: A consistent exercise with 15-min moderate intensity and a frequency of no less

than 3 times a week is significantly associated with lower risk of depressive symptoms. This

exercise model may be easier to promote at the community and population level.

Trial registration: registry number 104040 of the Institutional Ethics Committee of Chia-Yi

Christian Hospital.

Keywords:

Exercise, depression, mental health, elderly, generalized linear mixed models, cohort study.

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Strengths and limitations of this study

� This is the first report to examine the impacts of four different exercise models on

depressive symptoms in the elderly.

� A low volume of persistent exercise (≥15 min, 3 times per week of moderate intensity

exercise) can provide preventive effects on depressive symptoms for

community-dwelling older adults.

� The effects of different variables for depression may be altered for different cohorts

because of changes in medicine, nutrition or in the environment.

� The outcome event was performed the same time as the second visit to develop the

transitional patterns of exercise, which may reduce the interpretation of a causal

relationship.

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INTRODUCTION

Late life depression is an important health issue in different ethnic groups, affecting

13.7% of the population in the US and 20% of Chinese older adults in Taiwan.1-2

Depressive

disorder has been indicated as the top ten causes of years lived with disability among 188

countries based on the Global Burden of Disease Study, 2013.3 It has also been closely linked

to quality of life among community-dwelling older adults in many studies.4-6

Several relevant interventions have been suggested for preventing or treating depression

besides medicine. For instance, having a marital partner or having good social support will

significantly reduce the impacts of disability from depression.7 Psychological intervention,

especially group-based, has been shown to have benefits in regard to both prevention and

economic effects.8-10

Six weeks of healthy dietary practice has also been helpful in reducing

depressive symptoms, and the benefits may be sustained for 2 years.11

However, as early as in ancient Greece, Hippocrates suggested his patients exercise to

treat the disease of consumption, and Galen further instructed patients to exercise to reduce

troublesome depression.12

Many mechanisms of anti-depressive effects of exercise were

summarized in Rethorst, Wipfli, and Landers’s study.13

For example, four mechanisms in

hippocampal neurogenesis can be potentially facilitated by exercise: increases in

B-endorphins, vascular endothelial growth factor, brain-derived neurotrophic factor and

serotonin. Thus, exercise is potentially an effective approach to treating or preventing

depression.

Little research has focused on the relationship between exercise and depressive

symptoms in the elderly. Among the limited number of studies, exercise seems to have

similar effects to some pharmacological treatments14

but some meta-analysis studies have

yielded inconsistent results.15-17

Also, exercise did not always show benefits related to

preventing or treating depression because many of the studies did not control for previous

levels of depressive symptoms, and only a few included a follow-up period of more than 2

years. Furthermore, since exercise status will change as people age, how the transitional

patterns of exercise in older adults affect depressive symptoms has yet to be studied.

In addition, for older adults, exercise programs need to consider the intensity and

duration. The general recommendation for exercise by the American College of Sports

Medicine is moderate intensity; exercise is engaged in at least 30 minutes per day at least 5

days a week to accumulate a total of 150-300 minutes per week, or vigorous intensity of at

least 20 minutes per day for 3-5 days per week to a total of 75-100 minutes/week.18

However,

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a recent study by Wen et al. have indicated that a low amount of exercise, which refers to 15

minutes per day or 90 minutes per week at moderate intensity, has been proven beneficial in

reducing all-cause and all-cancer mortality.19

This result provides a more age-friendly

exercise model, which could be further explored in regard to its effects on depressive

symptoms in older adults.

Therefore, in this study, we use an 11-year cohort data from a population-based survey

to examine how different exercise models affect depressive symptoms in

community-dwelling older adults. The purposes of the study were: (1) to examine the impacts

of four different exercise models on preventing depressive symptoms in older adults, using

Taiwan as an example; and (2) to test the effects of changes in exercise status during a period

of time on depressive symptoms in the elderly.

METHODS

Study design and participants

This is a longitudinal cohort study, using nationally representative data from the survey

“Taiwan Longitudinal Study on Aging, TLSA”. The TLSA survey was undertaken by a

collaborative project from the University of Michigan, USA and the Health Promotion

Administration, Ministry of Health and Welfare, Taiwan. There were six waves of surveys for

those aged 60 and over in 1989, 1993, 1996, 1999, 2003 and 2007. Supplemental cases who

were aged 50 and older were added to the cohort in 1996 and 2003. A three-stage

proportional-to-size probability sampling technique was used in the survey, and face-to-face

interviews were performed for each individual. The response rates in each wave were high,

ranging from 81.2% to 91.4%.

Since detailed exercise questionnaires were launched in 1996, we combined two cohorts

(cohort I aged 67+ and cohort II aged 50-66) in 1996 together as our study cohort. The

inclusion criteria was aged 65 and older; the exclusion criteria was those who did not

complete the relevant questionnaires, lived in institutions or answered by proxy. We used the

1999 survey as the baseline and followed them up to 2007. A total of 2,673 valid participants

was selected as the baseline. The flow chart of the valid sample size is shown in Figure 1.

Due to the significant effects of previous depressive symptoms and changes in exercise

behavior on depression, we thus added more related data from the 1996 survey. Thus, the

total number of observations in the four survey waves was 8,397. This study was approved by

the Institutional Ethics Committee of Chia-Yi Christian Hospital (registry number 104040).

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Measurements

Dependent Variable: Depressive Symptoms

Depressive symptoms were measured with the Center for Epidemiologic Studies

Depression Scale (CESD). This 20-item scale assessment20

was modified to a 10-item scale,21

which was used in the TLSA survey. Each item was scored from 0 to 3, making the total

score range from 0 to 30. The measure, with a cutoff score of 10, has been recommended as a

good tool to assess depressive symptom severity in a community.22

Because the levels of

depressive symptoms are associated with future depression and quality of life,23-24

we

categorized the levels of depressive symptoms as No Depressive Symptom (NDS), which

means CESD=0; Lower Level of Depressive Symptoms (LLDS), 0<CESD≤9; and Higher

Level of Depressive Symptoms (HLDS), CESD≥10.

Independent Variables: Exercise Models and Transitional Patterns

The degree of exercise was quantified by asking about the frequency (0, ≤2, 3-5, ≥6

times per week), duration (<15 min, 15-30 min, >30 min), and intensity by sweating level

(none, a little, a lot, none of the above) and panting level (none, a little, a lot, none of the

above) after exercise.

Four exercise models (EMs) were classified in this study. Exercise model 1 means that

exercise of at least moderate intensity was performed ≥3 times/week, ≥15 min/time

(EM3_15); Exercise model 2 means ≥3 times/week, >30 min/time (EM3_30); Exercise model

3 means ≥6 times/week, ≥15 min/time (EM6_15); Exercise model 4 means ≥6 times/week,

>30 min/time (EM6_30). The moderate intensity was defined as experiencing a little

sweating and panting after exercise.18

The pattern of exercise transition refers to changes in practices of respective exercise

models between two waves, which was classified as (a) Low pattern (pattern NN): the

respective exercise model was not practiced in the previous or in the current surveys; (b)

Declining pattern (pattern YN): the respective exercise model was practiced in the previous

but not in the current surveys; (c) Increasing pattern (pattern NY): the respective exercise

model was practiced in the current but not in the previous surveys; and (d) Persistent pattern

(pattern YY): the respective exercise model was practiced in both the previous and in the

current surveys.

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Control Variables

Sociodemographic variables included gender, age, marital status (married or living with

a partner was coded as 1, otherwise 0), level of education (none, elementary, junior high

school, senior high school, and college and above), economic satisfaction (dissatisfied,

satisfied) and employment status (yes/no).

Physical function involved reversing the score from a 4-point measurement inquiring

about level of difficulty of seven mobility tasks, including standing for 15 min, squatting,

raising both arms up, grasping with fingers, lifting an 11 kg weight, running 20-30 m,

climbing up two to three floors. The sum of the physical battery ranged from 0-21. A higher

score indicated a better physical battery. These measurements have been reported as

hierarchically associated with instrumental and basic activities of daily living.25

Social participation refers to participation in any of the following groups: volunteers,

community groups, religious groups, occupational associations, political parties or groups,

social service groups, clan associations, seniors’ groups or schools. Social participation was

coded as a binary variable (yes/no).

Emotional support was the summed scores of seven items, which were coded from 0 to 3,

including (1) family/relatives/friends care about you, (2) family/relatives/friends listen to you,

(3) you can count on family/relatives/friends when you are ill, (4) you are satisfied with the

support from your family/relatives/friends, (5) How often do your family or friends come to

you for opinions, (6) In what ways do you feel that you are helpful to your family or friends,

and (7) How often do you feel rejected by your family/relatives/friends. The last item was

scored reversely.

Health-related variables included self-rated health (poor, fair and good) and other binary

variables such as current smoking and 10 chronic conditions including cancer, chronic

respiratory disease, gastrointestinal disease, hypertension, diabetes mellitus, heart disease,

stroke, arthritis, hepatobiliary disease and renal disease.

Statistical analysis

The descriptive analysis of depressive symptoms and covariates were presented as a

mean ± standard deviation (SD) or as n (%) for continuous or categorical data, respectively.

We applied generalized linear mixed models (GLMMs) via PROC GLIMMIX to estimate the

effects of different transitional patterns of exercise on depressive symptoms with HLDS as

the event, after adjusting for previous CESD score, age, gender, level of education, marital

status, smoking, physical function, emotional support, social participation, self-rated health,

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economic satisfaction, employment and 10 chronic conditions. The interaction of time and

transitional patterns of exercise was also included in the above analysis. A two-sided p-value

<0.05 was considered statistically significant. All data was merged and analyzed using SAS

9.2 (SAS Institute, Cary, NC).

RESULTS

There were 2,673 valid subjects selected from the survey conducted in 1999, and a total

of 8,397 observations in four waves of survey. Table 1 shows the distribution of

characteristics for the subjects from 1999 (baseline) to 2007. At baseline, the average age was

74.2 ± 5.7 years old, of which 54.5% were male. The prevalence of LLDS and HLDS was

20~24% over time. About 38.6% of participants met the lowest criteria of EM3_15, and

fewer (28.0%) met the highest criteria of EM6_30. Noticeably, in any survey, exercise

models EM3_15 and EM6_15 have a higher proportion than EM3_30 and EM6_30. This may

imply the difficulty of engaging in long exercise in older adults.

Table 2 illustrates the odd ratios (OR) of HLDS according to the current practices of

exercise models and other determining factors. Only exercise model 4 (EM6_30) had a

significant reducing effect on HLDS (OR=0.80, 95% CI=0.66-0.95). Also, the previous level

of depressive symptoms, physical function, emotional support, self-rated health and

economic satisfaction were all positively predictive of HLDS.

Table 3 shows the predictive effects of previous exercise models for HLDS. However,

none of the four exercise models in the previous survey could predict the present HLDS.

Namely, previous exercise behavior appeared to have no benefits on reducing depression,

regardless of amount or type of exercise. This may suggest that the effects of exercise on

depressive symptoms are only concurrent and short-term.

Thus, we conducted another test to examine the effect of changes in different exercise

models on depressive symptoms, as shown in Table 4. After controlling for other determining

factors and considering the interaction of time and transitional patterns of exercise, the results

indicated that only persistent patterns of exercise transitions (pattern YY) reveal a significant

protective effect from HLDS, regardless of exercise model (OR=0.58, 0.56, 0.67, 0.62,

respectively, all p<0.05). Namely, even the lower amount of exercise (EM3_15) may have

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protective effects on depression as long as the older adults continuously reach moderate

intensity at least 15 minutes with a frequency of no less than three times a week.

DISCUSSION

Very limited research has been conducted to determine the long-term effects of different

exercise models on depressive symptoms in the elderly. This study shows that different

transitional patterns of exercise are significantly associated with HLDS outcomes. The

persistent patterns of exercise transitions (pattern YY) revealed a significant protective effect

from HLDS, regardless of the exercise model. The concordant associations between

transitional patterns of respective exercise models and depressive symptoms may suggest a

changing influence of exercise on depression over time.

Furthermore, this study shows that persistent low-volume exercise, i.e. ≥15 min of

moderate intensity exercise (EM3_15 and EM6_15), can provide preventive effects on

depressive symptoms, similar to the benefits of high-volume exercise, i.e. ≥30 min of

moderate intensity exercise (EM3_30 and EM6_30), for older adults. These findings suggest

a shorter, age-friendly exercise model may benefit older adults physically and

psychologically.

One study suggested that frequency of exercise may be important for depressive

symptoms.26

Our study revealed that consistency may be the key factor when the frequencies

of exercise with moderate intensity are different. Both exercise frequencies of ≥3 times/week

or ≥6 times/week with respective durations each time showed significantly negative

association for HLDS in this study. These results indicate the importance of the consistency

of exercise.

Another study using the Taiwanese national survey suggested promoting high intensity,

rather than frequent or long duration exercise, to improve mental well-being in older adults,27

which seems to be not completely compatible with our findings. However, the nature of the

cross-sectional study design of that study may have caused it to have a higher possibility of

over-interpreting the results. Less depressed people may be more likely to engage in higher

intensity exercise as compared to more depressed people. Our longitudinal study suggests

that a low amount of exercise also has benefits related to preventing depressive symptoms.

Furthermore, transitional patterns of exercise may be more important than the current

exercise models that people are practicing.

Physical inactivity was found to be among the top 10 leading risk factors for global

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disease burden in 2010.28

It is important to promote exercise especially among older adults,

who are more vulnerable to physical and psychological dysfunction. The general

recommendation for older adults is moderate intensity exercise accumulated at least 30 min

each day for at least 5 days a week to total 150-300 min/week, or vigorous intensity exercise

at least 20-30 min per day for 3-5 days per week to total 75-100 min/week.18

However, East

Asians usually engage in fewer physical activities at lower intensity than people in western

countries.29-30

In consideration of physical conditions, it would be helpful to find out the

minimal volume of exercise for older adults required to improve their health.

This study showed that the percentage of participants who engaged in exercise model

EM6_15 was higher than that of EM3_30 and EM6_30, which indicates that lower intensity,

higher frequency exercise may be more acceptable to older people than higher intensity

exercise with a lower frequency. Furthermore, the low-volume exercise model has been

shown to have the benefits related to reducing all-cause mortality and all-cancer mortality.19,

31 Therefore, with the findings of our study, we are confident to conclude that persistent

low-amount exercise with the same moderate intensity (at least ≥15 min/ 6 times/ week) may

also benefit older adults both physically and psychologically.

Because of the social stigma of depressive symptoms, many people with this condition

tend to remain under-treated. When unable to appropriately address the causes or when there

is no access to adequate non-medical or community services to treat depression, patients may

become further burdened due to a lack of solutions for specific conditions.32

Our study

provides a practical and non-medical option to prevent people from HLDS. Most importantly,

it will help reduce the unnecessary use of medication, which sometimes causes adverse drug

reactions in older adults, and it may also help people when they lack awareness of their

disorder or are reluctant to be treated.

Still, there are several other factors affecting depressive symptoms. Depression is

significantly associated with chronic medical conditions, problems with ADLs, poor social

support, and previous depressive conditions.7, 33-34

Functional limitation and arthritis are the

strong risk factors in chronic conditions for depression.35

In our study, physical function,

emotional support, self-rated health, and economic satisfaction have always been shown to

significantly influence HLDS in all analyses. However, among the above-mentioned factors,

exercise is the more changeable variable, which could also benefit physical function and

self-rated health.

The advantages of this study include the fact that it had a nationally representative

sample, a longitudinal cohort design, a test of different exercise models, an examination of

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the changes in exercise status over time, and a proper consideration of statistical analysis

methods. Nonetheless, the study has some limitations. Firstly, the observation for the

outcome event was performed the same time as the second visit to develop the variables for

transitional patterns of exercise, which may have reduced the interpretation of a causal

relationship if the association between current exercise and the outcome event is too strong.

However, if the assumption is true, the bias will support the null hypothesis. The results

indicate that the significantly protective effects of a persistent pattern of exercise transitions

are consistent across all of the exercise models. The increasing exercise model did not have

the same finding although both models indicated that the subjects had practiced the respective

exercises on their second visit. We are therefore comfortable to infer that a persistent pattern

of exercise transitions has more influence than increasing and other transitional patterns of

exercise. Secondly, the effects of different variables for HLDS may be altered for different

cohorts because of changes in medicine, nutrition or in the environment. This may limit the

application of the findings of this study. Lastly, activities of daily living (ADL) was not

included in the analysis, which may include those who cannot perform exercise. We used

physical function ability, which has shown to be hierarchically associated with instrumental

and basic ADL25

to control the differences related to mobility limitation.

CONCLUSION

A consistent exercise with 15-min moderate intensity and a frequency of no less than 3

times a week is significantly associated with lower risk of depressive symptoms. Increasing

the frequency to more than 5 times per week will benefit older adults both physically and

psychologically. We recommend taking this low amount of exercise model into core

consideration when designing exercise programs related to older adults.

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Acknowledgements

We would like to thank the Health Promotion Administration, Ministry of Health and

Welfare of Taiwan for providing the dataset for analysis.

Contributors

Y-CC and M-CL designed and conducted the study, and wrote the daft; I-HH analyzed

the data and interpreted the tables; W-CW involved literature review and revised the draft;

SCH advised the whole study and completed the manuscript. All authors contributed to the

interpretation of results, critically reviewed the draft, and approved the final manuscript.

Funding

This study was supported by Research Center for Humanities and Social Sciences,

National Cheng Kung University, (H10-A304, FD101037).

Competing interests

None declared.

Ethical approval

This study was approved by the Institutional Ethics Committee of Chia-Yi Christian

Hospital (registry number 104040).

Provenance and peer review

Not commissioned; externally peer reviewed.

Data sharing statement

No additional data are available.

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15. Cooney GM, Dwan K, Greig CA, et al. Exercise for depression. Cochrane Database

Syst Rev 2013;9:CD004366.

16. Walker JG, Mackinnon AJ, Batterham P, et al. Mental health literacy, folic acid and

vitamin B12, and physical activity for the prevention of depression in older adults:

randomised controlled trial. Br J Psychiatry 2010;197:45-54.

17. Rhyner KT, Watts A. Exercise and Depressive Symptoms in Older Adults: A Systematic

Meta-Analytic Review. J Aging Phys Act 2016;24:234-246.

18. Pescatello LS. ACSM's Guidelines for Exercise Testing and Prescription. 9th Edition,

edited by American College of Sports Medicine; 2013.

19. Wen CP, Wai JP, Tsai MK, et al. Minimum amount of physical activity for reduced

mortality and extended life expectancy: a prospective cohort study. Lancet

2011;378:1244-53.

20. Radloff LS. The CES-D scale: a self-reported depression scale for research in the

general population. Appl Psychol Meas 1977;I:385-401.

21. Kohout FJ, Berkman LF, Evans DA,et al. Two shorter forms of the CES-D (Center for

Epidemiological Studies Depression) depression symptoms index. J Aging Health

1993;5:179-93.

22. Bjorgvinsson T, Kertz SJ, Bigda-Peyton JS,et al. Psychometric properties of the

CES-D-10 in a psychiatric sample. Assessment 2013;20:429-36.

23. Lyness JM, Chapman BP, McGriff J,et al. One-year outcomes of minor and

subsyndromal depression in older primary care patients. Int Psychogeriatr 2009;21:60-8.

24. Chang YC, Ouyang WC, Lu MC,et al. Levels of depressive symptoms may modify the

relationship between the WHOQOL-BREF and its determining factors in

community-dwelling older adults. Int Psychogeriatr 2016;28:591-601.

25. Chen HY, Wang CY, Lee MY,et al. A hierarchical categorisation of tasks in mobility

disability. Disabil Rehabil 2010;32:1586-93.

26. Ku PW, Fox KR, Chen LJ, et al. Physical activity and depressive symptoms in older

adults: 11-year follow-up. Am J Prev Med 2012;42:355-62.

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27. Chen LJ, Stevinson C, Ku PW, et al. Relationships of leisure-time and non-leisure-time

physical activity with depressive symptoms: a population-based study of Taiwanese

older adults. Int J Behav Nutr Phys Act 2012;9:28.

28. Lim SS, Vos T, Flaxman AD, et al. A comparative risk assessment of burden of disease

and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010:

a systematic analysis for the Global Burden of Disease Study 2010. Lancet

2012;380:2224-60.

29. Ku PW, Fox KR, McKenna J, et al. Prevalence of leisure-time physical activity in

Taiwanese adults: results of four national surveys, 2000-2004. Prev Med 2006;43:454-7.

30. Wai JP, Wen CP, Chan HT, et al. Assessing physical activity in an Asian country: low

energy expenditure and exercise frequency among adults in Taiwan. Asia Pac J Clin

Nutr 2008;17:297-308.

31. Hubbard RE, Fallah N, Searle SD, et al. Impact of exercise in community-dwelling older

adults. PLoS One 2009;4:e6174.

32. Bird MJ, Parslow RA. Potential for community programs to prevent depression in older

people. Med J Aust 2002;177 Suppl:S107-10.

33. Schoevers RA, Geerlings MI, Beekman AT, et al. Association of depression and gender

with mortality in old age. Results from the Amsterdam Study of the Elderly (AMSTEL).

Br J Psychiatry 2000;177:336-42.

34. Roberts RE, Kaplan GA, Shema SJ, et al. Does growing old increase the risk for

depression? Am J Psychiatry 1997;154:1384-90.

35. Dunlop DD, Lyons JS, Manheim LM, et al. Arthritis and heart disease as risk factors for

major depression: the role of functional limitation. Med Care 2004;42:502-11.

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Table 1 Characteristics of the participants from 1999 to 2007

Variables

1999 2003 2007

N=2673 N=1889 N=1361

n (%) n (%) n (%)

Age 74.2 ± 5.7 77.1 ± 5.1 80.2 ± 4.7

Male 1456 (54.5) 1019 (53.9) 703 (51.7)

Level of depressive symptoms

NDS 1401 (52.5) 1049 (55.5) 708 (52.0)

LLDS 646 (24.2) 388 (20.5) 321 (23.6)

HLDS 624 (23.4) 452 (23.9) 332 (24.4)

M±SD 6.1 ± 6.4 5.7 ± 5.9 5.8 ± 6.1

Exercise models*

EM3_15 1032 (38.6) 810 (42.9) 562 (41.3)

EM3_30 859 (32.1) 671 (35.5) 450 (33.1)

EM6_15 922 (34.5) 742 (39.3) 498 (36.6)

EM6_30 749 (28.0) 603 (31.9) 386 (28.4)

Education

No 1111 (41.6) 733 (38.8) 507 (37.3)

Elementary 983 (36.8) 723 (38.3) 515 (37.8)

Junior high school 273 (10.2) 200 (10.6) 155 (11.4)

Senior high school 162 (6.1) 124 (6.6) 96 (7.1)

College and above 143 (5.4) 109 (5.8) 88 (6.5)

Married 1630 (61.0) 1096 (58.0) 727 (53.4)

Employment 322 (12.1) 142 (7.5) 84 (6.2)

Current smoking 595 (22.3) 344 (18.2) 189 (13.9)

Physical function 17.2 ± 4.8 16.2 ± 5.0 16.0 ± 5.1

Emotional support 18.1 ± 3.0 18.0 ± 2.9 18.4 ± 2.7

Social participation 1369 (51.2) 842 (44.6) 576 (42.3)

Self-rated health

Poor 934 (34.9) 707 (37.4) 481 (35.3)

Fair 927 (34.7) 583 (30.9) 531 (39.0)

Good 812 (30.4) 599 (31.7) 349 (25.6)

Economic satisfaction

Dissatisfied 544 (20.4) 407 (21.6) 271 (19.9)

Fair 1144 (42.9) 653 (34.6) 486 (35.7)

Satisfied 978 (36.7) 828 (43.9) 604 (44.4)

Chronic conditions

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Cancer 71 (2.7) 61 (3.2) 54 (4.0)

Chronic respiratory disease 370 (13.8) 256 (13.6) 179 (13.2)

Gastrointestinal 543 (20.3) 402 (21.3) 301 (22.1)

Hypertension 1002 (37.5) 829 (43.9) 672 (49.4)

Diabetes mellitus 408 (15.3) 319 (16.9) 235 (17.3)

Heart disease 576 (21.6) 469 (24.8) 373 (27.4)

Stroke 144 (5.4) 126 (6.7) 83 (6.1)

Arthritis 594 (22.2) 465 (24.6) 322 (23.7)

Hepatobiliary disease 191 (7.2) 158 (8.4) 116 (8.5)

Renal disease 217 (8.1) 192 (10.2) 139 (10.2)

Data were presented as mean ± SD or n (%).

NDS: No Depressive Symptom (CESD=0);

LLDS: Lower Level of Depressive Symptoms (0<CESD≦9);

HLDS: Higher Level of Depressive Symptoms (CESD≧10);

CESD: Center for Epidemiologic Studies of Depression;

*EM3_15: Exercise ≧moderate intensity, ≧3 times/week, ≧15 min/time;

EM3_30: Exercise ≧moderate intensity, ≧3 times/week, ≧30 min/time;


EM6_30: Exercise ≧moderate intensity, ≧6 times/week, ≧30 min/time.

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Table 2 Odds ratios of HLDS according to the current exercise models estimated by

GLMM ‡

Variables HLDS

OR (95% CI) p-value

Exercise models

EM3_15 1.14 (0.92-1.42) 0.24

EM3_30 0.86 (0.59-1.25) 0.42

EM6_15 0.86 (0.65-1.13) 0.27

EM6_30 0.80 (0.66-0.95) 0.01

Previous level of depressive symptoms

NDS ref

LLDS 1.83 (1.48-2.28) <0.001

HLDS 3.04 (2.39-3.85) <0.001

Physical function 0.92 (0.90-0.93) <0.001

Emotional support 0.86 (0.84-0.88) <0.001

Self-rated health

Poor ref

Fair 0.52 (0.44-0.61) <0.001

Good 0.29 (0.23-0.36) <0.001


Dissatisfied ref

Fair 0.51 (0.43-0.60) <0.001

Satisfied 0.33 (0.27-0.40) <0.001

OR: odds ratio; CI: confidence interval.


GLMM: generalized linear mixed models





‡All the analysis models were adjusted by the present age, gender, education, marital status, smoking,

social participation, and chronic conditions including cancer, chronic respiratory disease,

gastrointestinal, hypertension, diabetes mellitus, heart disease, stroke, arthritis, hepatobiliary disease

and renal disease.

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Table 3 Odds ratios of HLDS according to the previous exercise models estimated by

GLMM‡

Variables HLDS

OR (95% CI) p-value

Previous Exercise models

EM3_15 0.88 (0.72-1.06) 0.17

EM3_30 1.05 (0.76-1.46) 0.77

EM6_15 0.98 (0.79-1.23) 0.89

EM6_30 0.68 (0.44-1.07) 0.10


NDS ref

LLDS 1.86 (1.50-2.31) <0.001

HLDS 3.12 (2.46-3.96) <0.001



Self-rated health

Poor ref

Fair 0.52 (0.44-0.60) <0.001

Good 0.28 (0.23-0.35) <0.001


Dissatisfied ref

Fair 0.51 (0.43-0.60) <0.001

Satisfied 0.33 (0.27-0.40) <0.001




EM3_15: Exercise ≧moderate intensity, ≧3 times/week, ≧15min/time;



EM6_30: Exercise ≧moderate intensity, ≧6 times/week, ≧30min/time.

‡All the analysis models were adjusted by the present age, gender, education, marital status, smoking, social participation, and chronic conditions including cancer, chronic respiratory disease,


and renal disease.

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Table 4 Odds ratios of HLDS under the consideration of the interaction of time and exercise transition‡

Variables

Model 1

(EM3_15)

Model 2

(EM3_30)

Model 3

(EM6_15)

Model 4

(EM6_30)

OR (95% CI) P OR (95% CI) P OR (95% CI) P OR (95% CI) P

Exercise transitions

NN ref ref ref ref

YN 0.77 (0.54-1.11) 0.16 0.86 (0.60-1.25) 0.43 0.76 (0.53-1.09) 0.14 0.92 (0.64-1.34) 0.68

NY 0.79 (0.54-1.16) 0.24 0.78 (0.52-1.17) 0.23 0.68 (0.45-1.01) 0.06 0.71 (0.46-1.10) 0.12

YY 0.58 (0.40-0.85) 0.01 0.56 (0.36-0.88) 0.01 0.67 (0.45-1.00) 0.048 0.62 (0.38-0.99) 0.047

Previous CESD

NDS ref ref ref ref

LLDS 1.82 (1.43-2.33) <0.001 1.81 (1.42-2.31) <0.001 1.82 (1.42-2.32) <0.001 1.81 (1.42-2.31) <0.001

HLDS 3.23 (2.47-4.23) <0.001 3.20 (2.45-4.18) <0.001 3.23 (2.47-4.22) <0.001 3.20 (2.45-4.19) <0.001

Time slope 0.95 (0.92-0.99) 0.01 0.97 (0.94-1.00) 0.08 0.96 (0.92-0.99) 0.01 0.98 (0.94-1.01) 0.14

Time x exercise transitions

NN ref ref ref ref

YN 1.12 (1.05-1.20) <0.01 1.07 (1.00-1.15) 0.04 1.12 (1.05-1.20) <0.01 1.06 (0.99-1.14) 0.07

NY 1.01 (0.93-1.09) 0.79 0.99 (0.91-1.08) 0.84 1.02 (0.94-1.10) 0.69 0.98 (0.90-1.07) 0.68

YY 1.11 (1.03-1.18) <0.01 1.09 (1.01-1.17) 0.04 1.09 (1.01-1.17) 0.02 1.07 (0.99-1.17) 0.10







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NN: Low pattern of exercise transition, indicating the respective exercise model was not practiced in both previous and current surveys.

YN: Declining pattern of exercise transition, indicating the respective exercise model was practiced in the previous but not current survey. NY: Increasing pattern of exercise transition, indicating the respective exercise model was practiced in the current but not previous survey.

YY: Persistent pattern of exercise transition, indicating the respective exercise model was practiced in both previous and current surveys.

‡All the analysis models were adjusted by present age, gender, education, marital status, smoking, physical function, emotional support, social participation, self-rated health, economic satisfaction, employment and chronic conditions including cancer, chronic respiratory disease, gastrointestinal, hypertension,

diabetes mellitus, heart disease, stroke, arthritis, hepatobiliary disease and renal disease.

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210x297mm (300 x 300 DPI)

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STROBE Statement—checklist of items that should be included in reports of observational studies

Item

No Recommendation

Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the title or the abstract

(b) Provide in the abstract an informative and balanced summary of what was done

and what was found

Introduction

Background/rationale 2 Explain the scientific background and rationale for the investigation being reported

Objectives 3 State specific objectives, including any prespecified hypotheses

Methods

Study design 4 Present key elements of study design early in the paper

Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment,

exposure, follow-up, and data collection

Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and methods of

selection of participants. Describe methods of follow-up

Case-control study—Give the eligibility criteria, and the sources and methods of

case ascertainment and control selection. Give the rationale for the choice of cases

and controls

Cross-sectional study—Give the eligibility criteria, and the sources and methods of

selection of participants

(b) Cohort study—For matched studies, give matching criteria and number of

exposed and unexposed

Case-control study—For matched studies, give matching criteria and the number of

controls per case

Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect

modifiers. Give diagnostic criteria, if applicable

Data sources/

measurement

8* For each variable of interest, give sources of data and details of methods of

assessment (measurement). Describe comparability of assessment methods if there

is more than one group

Bias 9 Describe any efforts to address potential sources of bias

Study size 10 Explain how the study size was arrived at

Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If applicable,

describe which groupings were chosen and why

Statistical methods 12 (a) Describe all statistical methods, including those used to control for confounding

(b) Describe any methods used to examine subgroups and interactions

(c) Explain how missing data were addressed

(d) Cohort study—If applicable, explain how loss to follow-up was addressed

Case-control study—If applicable, explain how matching of cases and controls was

addressed

Cross-sectional study—If applicable, describe analytical methods taking account of

sampling strategy

(e) Describe any sensitivity analyses

Continued on next page

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Results

Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially eligible,

examined for eligibility, confirmed eligible, included in the study, completing follow-up, and

analysed

(b) Give reasons for non-participation at each stage

(c) Consider use of a flow diagram

Descriptive

data

14* (a) Give characteristics of study participants (eg demographic, clinical, social) and information

on exposures and potential confounders

(b) Indicate number of participants with missing data for each variable of interest

(c) Cohort study—Summarise follow-up time (eg, average and total amount)

Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over time

Case-control study—Report numbers in each exposure category, or summary measures of

exposure

Cross-sectional study—Report numbers of outcome events or summary measures

Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their

precision (eg, 95% confidence interval). Make clear which confounders were adjusted for and

why they were included

(b) Report category boundaries when continuous variables were categorized

(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful

time period

Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and sensitivity

analyses

Discussion

Key results 18 Summarise key results with reference to study objectives

Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or imprecision.

Discuss both direction and magnitude of any potential bias

Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations, multiplicity

of analyses, results from similar studies, and other relevant evidence

Generalisability 21 Discuss the generalisability (external validity) of the study results

Other information

Funding 22 Give the source of funding and the role of the funders for the present study and, if applicable,

for the original study on which the present article is based

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and

unexposed groups in cohort and cross-sectional studies.

Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and

published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely

available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at

http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is

available at www.strobe-statement.org.

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Impacts of different amount of exercise on depressive symptoms in community-dwelling older adults: a

longitudinal cohort study

Journal: BMJ Open

Manuscript ID bmjopen-2016-014256.R1


Date Submitted by the Author: 09-Dec-2016




Mental health




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Impacts of different amount of exercise on depressive symptoms in

community-dwelling older adults: a longitudinal cohort study


2, I-Han Hu

3, Wan-Chi Ida Wu

4, Susan C. Hu

5*

1. Yu-Chen Chang, MD, PhD, Department of Community Health, Chia-Yi Christian

Hospital, Chia-Yi, Taiwan. [email protected]

2. Mei-Chun Lu, MS, Department of Medical Research, Kuang Tien General Hospital,

Taichung, Taiwan. [email protected]

3. I-Han Hu, MS, Institute of Gerontology, College of Medicine, National Cheng Kung

University. [email protected]

4. Wan-Chi Ida Wu, PhD, Department of Public Health, College of Medicine, National

Cheng Kung University, Tainan, Taiwan. [email protected]

5. Susan C. Hu, PhD, Department of Public Health, College of Medicine, National Cheng

Kung University, Tainan, Taiwan. [email protected]

*Corresponding author: Susan C. Hu, PhD

Dept. of Public Health, College of Medicine, National Cheng Kung University,

No.1, University Rd, Tainan, Taiwan, 70101

E-mail: [email protected]

Tel: +886-972-967800, Fax: +886-6-2359033

Running title: Exercise on depression

World count: Abstract 252, Text 3010

Number of figures: 1

Number of tables: 4

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ABSTRACT

Objectives: to examine the impacts of four different types of exercise on depressive

symptoms in community-dwelling older adults.

Design: prospective cohort study.

Setting: a nationally representative sample, Taiwan.

Participants: Four waves of the survey “Taiwan Longitudinal Study on Aging (TLSA)” from

1996 to 2007 were used. A total of 2,673 older adults aged 65 and over were recruited.

Primary and secondary outcome measures: Depressive symptoms were measured using

the Center for Epidemiologic Studies Depression scale (CESD). Four different types of

exercise were examined, including (1) 3 times/week, 15 min/time; (2) 3 times/week, 30

min/time; (3) 6 times/week, 15 min/time; and (4) 6 times/week, 30 min/time. All exercise

types were required to have at least moderate intensity. The impacts of different types of

exercise on depressive symptoms were analyzed using generalized linear mixed models.

Results: More than one fifth of the elderly had depressive symptoms (CESD ≥10). About

38.6% of older adults met the lowest criteria of exercise type 1, and fewer (28.0%) met the

highest criteria of type 4. Only exercise type 4 in the current survey was initially related to

lower depressive symptoms (OR=0.8, 95%CI=0.66-0.95). However, after considering the

interaction between time and changes in the exercise patterns, we found that all persistent

exercise models, even if very low amount (3 times/week, 15 min/week), had significantly

preventive effects on depressive symptoms (OR=0.56~0.67).

Conclusion: A consistent exercise with 15-min moderate intensity and a frequency of no less

than 3 times a week is significantly associated with lower risk of depressive symptoms. This

exercise type may be easier to promote at the community and population level.

Trial registration: registry number 104040 of the Institutional Ethics Committee of Chia-Yi

Christian Hospital.

Keywords:

Exercise, depression, mental health, elderly, generalized linear mixed models, cohort study.

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Strengths and limitations of this study

� This is the first report to examine the impacts of four different types of exercise, on

depressive symptoms in the elderly, according to different criteria.

� The strengths of this study include a nationally representative sample, a longitudinal

cohort design, an examination of the changes in exercise status over time, and a proper

consideration of statistical analysis methods.

� However, the effects of different variables for depression may be altered for different

cohorts because of changes in medicine, nutrition or in the environment.

� The outcome event was performed the same time as the second visit to develop the

change patterns of exercise, which may reduce the interpretation of a causal relationship.

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INTRODUCTION

Late life depression is an important health issue in different ethnic groups, affecting

13.7% of the population in the US and 20% of Chinese older adults in Taiwan.1-2

Depressive

disorder has been indicated as the top ten causes of years lived with disability among 188

countries based on the Global Burden of Disease Study, 2013.3 It has also been closely linked

to quality of life among community-dwelling older adults in many studies.4-6

Several relevant interventions have been suggested for preventing or treating depression

besides medicine. For instance, having a marital partner or having good social support will

significantly reduce the impacts of disability from depression.7 Psychological intervention,

especially group-based, has been shown to have benefits in regard to both prevention and

economic effects.8-10

Six weeks of healthy dietary practice has also been helpful in reducing

depressive symptoms, and the benefits may be sustained for 2 years.11

However, as early as in ancient Greece, Hippocrates suggested his patients exercise to

treat the disease of consumption, and Galen further instructed patients to exercise to reduce

troublesome depression.12

Many mechanisms of anti-depressive effects of exercise were

summarized in Rethorst, Wipfli, and Landers’s study.13

For example, four mechanisms in

hippocampal neurogenesis can be potentially facilitated by exercise: increases in

B-endorphins, vascular endothelial growth factor, brain-derived neurotrophic factor and

serotonin. Thus, exercise is potentially an effective approach to treating or preventing

depression.

Little research has focused on the relationship between exercise and depressive

symptoms in the elderly. Among the limited number of studies, exercise seems to have

similar effects to some pharmacological treatments14

but some meta-analysis studies have

yielded inconsistent results.15-17

Also, exercise did not always show benefits related to

preventing or treating depression because many of the studies did not control for previous

levels of depressive symptoms, and only a few included a follow-up period of more than 2

years. Furthermore, since exercise status will change as people age, how the transitional

patterns of exercise in older adults affect depressive symptoms has yet to be studied.

In addition, for older adults, exercise programs need to consider the intensity and

duration. The general recommendation for exercise by the American College of Sports

Medicine is moderate intensity; exercise is engaged in at least 30 minutes per day at least 5

days a week to accumulate a total of 150-300 minutes per week, or vigorous intensity of at


However,

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a recent study by Wen et al. have indicated that a low amount of exercise, which refers to 15

minutes per day or 90 minutes per week at moderate intensity, has been proven beneficial in


This result provides a more age-friendly

exercise model, which could be further explored in regard to its effects on depressive

symptoms in older adults.

Therefore, in this study, we use an 11-year cohort data from a population-based survey

to examine how different amount of exercise affect depressive symptoms in older adults. The

purposes of the study were: (1) to examine the impacts of four different types of exercise on

preventing depressive symptoms in older adults, using Taiwan as an example; and (2) to test

the effects of changes in exercise status during a period of time on depressive symptoms in

the elderly.

METHODS

Study design and participants

This is a longitudinal cohort study, using nationally representative data from the survey

“Taiwan Longitudinal Study on Aging, TLSA”. The TLSA survey was undertaken by a

collaborative project from the University of Michigan, USA and the Health Promotion

Administration, Ministry of Health and Welfare, Taiwan. There were six waves of surveys for

those aged 60 and over in 1989, 1993, 1996, 1999, 2003 and 2007. Supplemental cases who

were aged 50 and older were added to the cohort in 1996 and 2003. A three-stage

proportional-to-size probability sampling technique was used in the survey, and face-to-face

interviews were performed for each individual. The response rates in each wave were high,

ranging from 81.2% to 91.4%.

Since detailed exercise questionnaires were launched in 1996, we combined two cohorts

(cohort B aged 67+ and cohort A aged 50-66) in 1996 together as our study cohort. The

inclusion criteria was aged 65 and older; the exclusion criteria was those who did not

complete the relevant questionnaires, lived in institutions or answered by proxy. We used the

1999 survey as the baseline and followed them up to 2007. A total of 2,673 valid participants

was selected as the baseline and 5923 observations were counted.

Due to the significant effects of previous depressive symptoms and changes in exercise

behavior on depression, we thus put more retrospective data as control variables from the

1996 survey when analyzing the effects in 1999. Thus, the total number of observations in the

four-wave surveys was added up to 8,397. The flow chart of the valid sample size is shown in

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Figure 1. This study was approved by the Institutional Ethics Committee of Chia-Yi Christian


Fig. 1: No. of participants in the four-wave surveys

Measurements

Dependent Variable: Depressive Symptoms

Depressive symptoms were measured with the Center for Epidemiologic Studies


was modified to a 10-item scale,21

which was used in the TLSA survey. Each item was scored from 0 to 3, making the total

score range from 0 to 30. The measure, with a cutoff score of 10, has been recommended as a

good tool to assess depressive symptom severity in a community.22

Because the levels of

depressive symptoms are associated with future depression and quality of life,23-24

we

categorized the levels of depressive symptoms as No Depressive Symptom (NDS), which

means CESD=0; Lower Level of Depressive Symptoms (LLDS), 0<CESD≤9; and Higher

Level of Depressive Symptoms (HLDS), CESD≥10.

Independent Variables: Types of exercise and Changing patterns

The degree of exercise was quantified by asking about the frequency (0, ≤2, 3-5, ≥6

times per week), duration (<15 min, 15-30 min, >30 min), and intensity by sweating level

(none, a little, a lot, none of the above) and panting level (none, a little, a lot, none of the

above) after exercise.

Four types of exercise were classified in this study. Exercise type 1 means that exercise

of at least moderate intensity was performed ≥3 times/week, ≥15 min/time (T3_15); Exercise

type 2 means ≥3 times/week, >30 min/time (T3_30); Exercise type 3 means ≥6 times/week,

≥15 min/time (T6_15); Exercise type 4 means ≥6 times/week, >30 min/time (T6_30). The

moderate intensity was defined as experiencing a little sweating and panting after exercise.18

The patterns of exercise consistency refers to changes in practices of respective exercise

types between two waves, which was classified as (a) Low pattern (pattern NN): the

respective exercise type was not practiced in the previous or in the current surveys; (b)

Declining pattern (pattern YN): the respective exercise type was practiced in the previous but

not in the current surveys; (c) Increasing pattern (pattern NY): the respective exercise type

was practiced in the current but not in the previous surveys; and (d) Persistent pattern (pattern

YY): the respective exercise type was practiced in both the previous and in the current

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surveys. In the analysis, all models were based on paired observations between two waves,

for example, 1996-1999, 1999-2003, 2003-2007. Therefore, when someone exercised in 2003

and 2007 but not 1999, he/she will be counted twice as “increasing pattern” in 1999-2003 and

as “persistent pattern” in 2003-2007.

Control Variables

Sociodemographic variables included gender, age, marital status (married or living with

a partner was coded as 1, otherwise 0), level of education (none, elementary, junior high

school, senior high school, and college and above), economic satisfaction (dissatisfied,

satisfied) and employment status (yes/no).

Physical function involved reversing the score from a 4-point measurement inquiring

about level of difficulty of seven mobility tasks, including standing for 15 min, squatting,

raising both arms up, grasping with fingers, lifting an 11 kg weight, running 20-30 m,

climbing up two to three floors. The sum of the physical battery ranged from 0-21. A higher

score indicated a better physical battery. These measurements have been reported as

hierarchically associated with instrumental and basic activities of daily living.25

Social participation refers to participation in any of the following groups: volunteers,

community groups, religious groups, occupational associations, political parties or groups,

social service groups, clan associations, seniors’ groups or schools. Social participation was

coded as a binary variable (yes/no).

Emotional support was the summed scores of seven items, which were coded from 0 to 3,

including (1) family/relatives/friends care about you, (2) family/relatives/friends listen to you,

(3) you can count on family/relatives/friends when you are ill, (4) you are satisfied with the

support from your family/relatives/friends, (5) How often do your family or friends come to

you for opinions, (6) In what ways do you feel that you are helpful to your family or friends,

and (7) How often do you feel rejected by your family/relatives/friends. The last item was

scored reversely.

Health-related variables included self-rated health (poor, fair and good) and other binary

variables such as current smoking and 10 chronic conditions including cancer, chronic

respiratory disease, gastrointestinal disease, hypertension, diabetes mellitus, heart disease,

stroke, arthritis, hepatobiliary disease and renal disease.

Statistical analysis

The descriptive analysis of depressive symptoms and covariates were presented as a

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mean ± standard deviation (SD) or as n (%) for continuous or categorical data, respectively.

We applied generalized linear mixed models (GLMMs) via PROC GLIMMIX to estimate the

effects of different transitional patterns of exercise on depressive symptoms with HLDS as

the event, after adjusting for previous CESD score, age, gender, level of education, marital

status, smoking, physical function, emotional support, social participation, self-rated health,

economic satisfaction, employment and 10 chronic conditions. The interaction of time and

transitional patterns of exercise was also included in the above analysis. A two-sided p-value

<0.05 was considered statistically significant. All data was merged and analyzed using SAS

9.2 (SAS Institute, Cary, NC).

RESULTS

There were 2,673 valid subjects selected from the survey conducted in 1999, and a total

of 8,397 observations in four waves of survey. Table 1 shows the distribution of

characteristics for the subjects from 1999 (baseline) to 2007. At baseline, the average age was

74.2 ± 5.7 years old, of which 54.5% were male. The prevalence of LLDS and HLDS was

20~24% over time. About 38.6% of participants met the lowest criteria of T3_15, and fewer

(28.0%) met the highest criteria of T6_30. Noticeably, in any survey, exercise models T3_15

and T6_15 have a higher proportion than T3_30 and T6_30. This may imply the difficulty of

engaging in long exercise in older adults.

Table 2 illustrates the odd ratios (OR) of HLDS according to the current practices of

exercise models and other determining factors. Only exercise type 4 (T6_30) had a significant

reducing effect on HLDS (OR=0.80, 95% CI=0.66-0.95). Also, the previous level of

depressive symptoms, physical function, emotional support, self-rated health and economic

satisfaction were all positively predictive of HLDS.

Table 3 shows the predictive effects of previous exercise models for HLDS. However,

none of the four exercise models in the previous survey could predict the present HLDS.

Namely, previous exercise behavior appeared to have no benefits on reducing depression,

regardless of amount or type of exercise. This may suggest that the effects of exercise on

depressive symptoms are only concurrent and short-term.

Thus, we conducted another test to examine the effect of changes in different exercise

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models on depressive symptoms, as shown in Table 4. After controlling for other determining

factors and considering the interaction of time and patterns of exercise, the results indicated

that only persistent patterns (pattern YY) reveal a significant protective effect from HLDS,

regardless of exercise type (OR=0.58, 0.56, 0.67, 0.62, respectively, all p<0.05). Namely,

even the lower amount of exercise (T3_15) may have protective effects on depression as long

as the older adults continuously reach moderate intensity at least 15 minutes with a frequency

of no less than three times a week.

DISCUSSION

Very limited research has been conducted to determine the long-term effects of different

exercise models on depressive symptoms in the elderly. The purpose of the study was to

examine the impacts of four different types of exercise on depressive symptoms in

community-dwelling older adults. We found that only current exercise type 4 (T6_30) was

significantly associated with lower depressive symptoms, whereas previous exercise

behaviors seemed to have no benefits on reducing depression. However, when considering

the changes in exercise behaviors between two waves, this study shows that different patterns

of exercise are significantly associated with HLDS outcomes. Only the persistent patterns of

exercise (pattern YY) revealed a significant protective effect from HLDS.

Furthermore, this study shows that persistent low-volume exercise, i.e. ≥15 min of

moderate intensity exercise (T3_15 and T6_15), can provide preventive effects on depressive

symptoms, similar to the benefits of high-volume exercise, i.e. ≥30 min of moderate intensity

exercise (T3_30 and T6_30), for older adults. These findings suggest a shorter, age-friendly

exercise type may benefit older adults physically and psychologically.

Comparing with the similar studies from Ku et al., Ku et al suggested that frequency of

exercise may be important for depressive symptoms26

and the changing pattern of low-low

group had a high risk to developing depressive symtoms.27

Our study revealed that

consistency may be the key factor, regardless the frequency or duration of exercise, as long as

the exercise with moderate intensity. Namely, both exercise frequencies of ≥3 times/week or

≥6 times/week with at least 15- or 30- minutes each time showed significantly negative

association for HLDS in this study. These results indicate the importance of the consistency

of exercise.

Noticeably, Ku et al study analyzed only traditional type of physical activity by using its

frequency, while, in this study, we compared 4 types of physical activity and measured

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physical activity simultaneously by using three dimensions including frequency, duration and

intensity. Besides, we considered the important covariates related depressive symptoms, such

as social participation, emotional support, mobility, and self-rated health etc. Therefore, we

believe our results can substantially contribute to the existing knowledge of physical activity

and depressive symptoms.

Another study using the Taiwanese national survey suggested promoting high intensity,


which seems to be not completely compatible with our findings. However, the nature of the

cross-sectional study design of that study may have caused it to have a higher possibility of

over-interpreting the results. Less depressed people may be more likely to engage in higher

intensity exercise as compared to more depressed people. Our longitudinal study suggests

that a low amount of exercise also has benefits related to preventing depressive symptoms.

Furthermore, transitional patterns of exercise may be more important than the current

exercise models that people are practicing.

Physical inactivity was found to be among the top 10 leading risk factors for global


It is important to promote exercise especially among older adults,

who are more vulnerable to physical and psychological dysfunction. The general

recommendation for older adults is moderate intensity exercise accumulated at least 30 min

each day for at least 5 days a week to total 150-300 min/week, or vigorous intensity exercise

at least 20-30 min per day for 3-5 days per week to total 75-100 min/week.18

However, East

Asians usually engage in fewer physical activities at lower intensity than people in western

countries.30-31

In consideration of physical conditions, it would be helpful to find out the

minimal volume of exercise for older adults required to improve their health.

This study showed that the percentage of participants who engaged in exercise type

T6_15 was higher than that of T3_30 and T6_30, which indicates that lower intensity, higher

frequency exercise may be more acceptable to older people than higher intensity exercise

with a lower frequency. Furthermore, the low-volume exercise type has been shown to have

the benefits related to reducing all-cause mortality and all-cancer mortality.19, 32

Therefore,

with the findings of our study, we are confident to conclude that persistent low-amount

exercise with the same moderate intensity (at least ≥15 min/ 6 times/ week) may also benefit

older adults both physically and psychologically.

Because of the social stigma of depressive symptoms, many people with this condition

tend to remain under-treated. When unable to appropriately address the causes or when there

is no access to adequate non-medical or community services to treat depression, patients may

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Our study

provides a practical and non-medical option to prevent people from HLDS. Most importantly,

it will help reduce the unnecessary use of medication, which sometimes causes adverse drug

reactions in older adults, and it may also help people when they lack awareness of their

disorder or are reluctant to be treated.

Still, there are several other factors affecting depressive symptoms. Depression is

significantly associated with chronic medical conditions, problems with ADLs, poor social


Functional limitation and arthritis are the

strong risk factors in chronic conditions for depression.36

In our study, physical function,

emotional support, self-rated health, and economic satisfaction have always been shown to

significantly influence HLDS in all analyses. However, among the above-mentioned factors,

exercise is the more changeable variable, which could also benefit physical function and

self-rated health.

This is the first report to examine the impacts of four different types of exercise, on

depressive symptoms in the elderly, according to different expert’s recommendations.18-19

However, there are previous studies that have examined the relationship between physical

activity and depressive symptoms in the elderly with different definitions of exercise groups

from different places (city/rural).37-38

Thus, to compare the results with each other, it should

be careful for the compatibility of participants, the measurement of exercise, and the

categories of exercise groups. The advantages of this study include the fact that it had a

nationally representative sample, a longitudinal cohort design, a test of different amount of

exercise, an examination of the changes in exercise status over time, and a proper

consideration of statistical analysis methods.

Nonetheless, the study has some limitations. Firstly, the observation for the outcome

event was performed the same time as the second visit to develop the variables for

transitional patterns of exercise, which may have reduced the interpretation of a causal

relationship if the association between current exercise and the outcome event is too strong.

However, if the assumption is true, the bias will support the null hypothesis. The results

indicate that the significantly protective effects of a persistent pattern of exercise are

consistent across all of the types of exercise. The increasing exercise pattern did not have the

same finding although both patterns indicated that the subjects had practiced the respective

exercises on their second visit. We are therefore comfortable to infer that a persistent pattern

of exercise has more influence than increasing and other transitional patterns of exercise.

Secondly, the effects of different variables for HLDS may be altered for different cohorts

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because of changes in medicine, antidepressants, nutrition or in the environment. This may

limit the application of the findings of this study. Lastly, activities of daily living (ADL) was

not included in the analysis, which may include those who cannot perform exercise. We used

physical function ability, which has shown to be hierarchically associated with instrumental

and basic ADL25

to control the differences related to mobility limitation.

CONCLUSION

A consistent exercise with 15-min moderate intensity and a frequency of no less than 3

times a week is significantly associated with lower risk of depressive symptoms. Increasing

the frequency to more than 5 times per week will benefit older adults both physically and

psychologically. We recommend taking this low amount of exercise into core consideration

when designing exercise programs related to older adults.

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Acknowledgements

We would like to thank the Health Promotion Administration, Ministry of Health and

Welfare of Taiwan for providing the dataset for analysis.

Contributors

Y-CC and M-CL designed and conducted the study, and wrote the daft; I-HH analyzed

the data and interpreted the tables; W-CW involved literature review and revised the draft;

SCH advised the whole study and completed the manuscript. All authors contributed to the

interpretation of results, critically reviewed the draft, and approved the final manuscript.

Funding

This study was supported by Research Center for Humanities and Social Sciences,

National Cheng Kung University, (H10-A304, FD101037).

Competing interests

None declared.

Ethical approval

This study was approved by the Institutional Ethics Committee of Chia-Yi Christian


Provenance and peer review

Not commissioned; externally peer reviewed.

Data sharing statement

No additional data are available.

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Table 1 Characteristics of the participants from 1999 to 2007

Variables

1999 2003 2007

N=2673 N=1889 N=1361

n (%) n (%) n (%)

Age 74.2 ± 5.7 77.1 ± 5.1 80.2 ± 4.7

Male 1456 (54.5) 1019 (53.9) 703 (51.7)


NDS 1401 (52.5) 1049 (55.5) 708 (52.0)

LLDS 646 (24.2) 388 (20.5) 321 (23.6)

HLDS 624 (23.4) 452 (23.9) 332 (24.4)

M±SD 6.1 ± 6.4 5.7 ± 5.9 5.8 ± 6.1

Types of exercise*

T3_15 1032 (38.6) 810 (42.9) 562 (41.3)

T3_30 859 (32.1) 671 (35.5) 450 (33.1)

T6_15 922 (34.5) 742 (39.3) 498 (36.6)

T6_30 749 (28.0) 603 (31.9) 386 (28.4)

Education

No 1111 (41.6) 733 (38.8) 507 (37.3)

Elementary 983 (36.8) 723 (38.3) 515 (37.8)




Married 1630 (61.0) 1096 (58.0) 727 (53.4)

Employment 322 (12.1) 142 (7.5) 84 (6.2)

Current smoking 595 (22.3) 344 (18.2) 189 (13.9)




Self-rated health

Poor 934 (34.9) 707 (37.4) 481 (35.3)

Fair 927 (34.7) 583 (30.9) 531 (39.0)

Good 812 (30.4) 599 (31.7) 349 (25.6)


Dissatisfied 544 (20.4) 407 (21.6) 271 (19.9)

Fair 1144 (42.9) 653 (34.6) 486 (35.7)

Satisfied 978 (36.7) 828 (43.9) 604 (44.4)

Chronic conditions

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Cancer 71 (2.7) 61 (3.2) 54 (4.0)



Hypertension 1002 (37.5) 829 (43.9) 672 (49.4)


Heart disease 576 (21.6) 469 (24.8) 373 (27.4)

Stroke 144 (5.4) 126 (6.7) 83 (6.1)

Arthritis 594 (22.2) 465 (24.6) 322 (23.7)


Renal disease 217 (8.1) 192 (10.2) 139 (10.2)

Data were presented as mean ± SD or n (%).

NDS: No Depressive Symptom (CESD=0);

LLDS: Lower Level of Depressive Symptoms (0<CESD≦9);


CESD: Center for Epidemiologic Studies of Depression;

*T3_15: Exercise ≧moderate intensity, ≧3 times/week, ≧15 min/time;

T3_30: Exercise ≧moderate intensity, ≧3 times/week, ≧30 min/time;


T6_30: Exercise ≧moderate intensity, ≧6 times/week, ≧30 min/time.

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Table 2 Odds ratios of HLDS according to the current exercise behaviors estimated

by GLMM ‡

Variables HLDS

OR (95% CI) p-value

Types of exercise

T3_15 1.14 (0.92-1.42) 0.24

T3_30 0.86 (0.59-1.25) 0.42

T6_15 0.86 (0.65-1.13) 0.27

T6_30 0.80 (0.66-0.95) 0.01


NDS ref

LLDS 1.83 (1.48-2.28) <0.001

HLDS 3.04 (2.39-3.85) <0.001



Self-rated health

Poor ref

Fair 0.52 (0.44-0.61) <0.001

Good 0.29 (0.23-0.36) <0.001


Dissatisfied ref

Fair 0.51 (0.43-0.60) <0.001

Satisfied 0.33 (0.27-0.40) <0.001








‡All the analysis models were adjusted by the present age, gender, education, marital status, smoking,

social participation, and chronic conditions including cancer, chronic respiratory disease,


and renal disease.

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Table 3 Odds ratios of HLDS according to the previous exercise behaviors estimated

by GLMM‡

Variables HLDS

OR (95% CI) p-value

Previous exercise types

T3_15 0.88 (0.72-1.06) 0.17

T3_30 1.05 (0.76-1.46) 0.77

T6_15 0.98 (0.79-1.23) 0.89

T6_30 0.68 (0.44-1.07) 0.10


NDS ref

LLDS 1.86 (1.50-2.31) <0.001

HLDS 3.12 (2.46-3.96) <0.001



Self-rated health

Poor ref

Fair 0.52 (0.44-0.60) <0.001

Good 0.28 (0.23-0.35) <0.001


Dissatisfied ref

Fair 0.51 (0.43-0.60) <0.001

Satisfied 0.33 (0.27-0.40) <0.001




T3_15: Exercise ≧moderate intensity, ≧3 times/week, ≧15min/time;



T6_30: Exercise ≧moderate intensity, ≧6 times/week, ≧30min/time.

‡All the analysis models were adjusted by the present age, gender, education, marital status, smoking, social participation, and chronic conditions including cancer, chronic respiratory disease,


and renal disease.

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Table 4 Odds ratios of HLDS under the consideration of the interaction of time and exercise consistency‡

Variables

Model 1

(T3_15)

Model 2

(T3_30)

Model 3

(T6_15)

Model 4

(T6_30)


Patterns of consistency

NN ref ref ref ref

YN 0.77 (0.54-1.11) 0.16 0.86 (0.60-1.25) 0.43 0.76 (0.53-1.09) 0.14 0.92 (0.64-1.34) 0.68

NY 0.79 (0.54-1.16) 0.24 0.78 (0.52-1.17) 0.23 0.68 (0.45-1.01) 0.06 0.71 (0.46-1.10) 0.12

YY 0.58 (0.40-0.85) 0.01 0.56 (0.36-0.88) 0.01 0.67 (0.45-1.00) 0.048 0.62 (0.38-0.99) 0.047

Previous CESD

NDS ref ref ref ref

LLDS 1.82 (1.43-2.33) <0.001 1.81 (1.42-2.31) <0.001 1.82 (1.42-2.32) <0.001 1.81 (1.42-2.31) <0.001

HLDS 3.23 (2.47-4.23) <0.001 3.20 (2.45-4.18) <0.001 3.23 (2.47-4.22) <0.001 3.20 (2.45-4.19) <0.001

Time slope 0.95 (0.92-0.99) 0.01 0.97 (0.94-1.00) 0.08 0.96 (0.92-0.99) 0.01 0.98 (0.94-1.01) 0.14

Time x Exercise consistency

NN ref ref ref ref

YN 1.12 (1.05-1.20) <0.01 1.07 (1.00-1.15) 0.04 1.12 (1.05-1.20) <0.01 1.06 (0.99-1.14) 0.07

NY 1.01 (0.93-1.09) 0.79 0.99 (0.91-1.08) 0.84 1.02 (0.94-1.10) 0.69 0.98 (0.90-1.07) 0.68

YY 1.11 (1.03-1.18) <0.01 1.09 (1.01-1.17) 0.04 1.09 (1.01-1.17) 0.02 1.07 (0.99-1.17) 0.10







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NN: Low pattern of exercise transition, indicating the respective exercise type was not practiced in both previous and current surveys.

YN: Declining pattern of exercise transition, indicating the respective exercise type was practiced in the previous but not current survey. NY: Increasing pattern of exercise transition, indicating the respective exercise type was practiced in the current but not previous survey.

YY: Persistent pattern of exercise transition, indicating the respective exercise type was practiced in both previous and current surveys.

‡All the analysis models were adjusted by present age, gender, education, marital status, smoking, physical function, emotional support, social participation, self-rated health, economic satisfaction, employment and chronic conditions including cancer, chronic respiratory disease, gastrointestinal, hypertension,

diabetes mellitus, heart disease, stroke, arthritis, hepatobiliary disease and renal disease.

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179x129mm (300 x 300 DPI)

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Item No Page Recommendation

Title and abstract 1 0-1 (a) Indicate the study’s design with a commonly used term in the title

or the abstract

(b) Provide in the abstract an informative and balanced summary of

what was done and what was found

Introduction

Background/rationale 2 3-4 Explain the scientific background and rationale for the investigation

being reported

Objectives 3 4 State specific objectives, including any prespecified hypotheses

Methods

Study design 4 4 Present key elements of study design early in the paper

Setting 5 4 Describe the setting, locations, and relevant dates, including periods of

recruitment, exposure, follow-up, and data collection

Participants 6 4 (a) Cohort study—Give the eligibility criteria, and the sources and

methods of selection of participants. Describe methods of follow-up

Case-control study—Give the eligibility criteria, and the sources and

methods of case ascertainment and control selection. Give the rationale

for the choice of cases and controls

Cross-sectional study—Give the eligibility criteria, and the sources

and methods of selection of participants

(b) Cohort study—For matched studies, give matching criteria and

number of exposed and unexposed

Case-control study—For matched studies, give matching criteria and

the number of controls per case

Variables 7 5-6 Clearly define all outcomes, exposures, predictors, potential

confounders, and effect modifiers. Give diagnostic criteria, if

applicable

Data sources/

measurement

8* 5-6 For each variable of interest, give sources of data and details of

methods of assessment (measurement). Describe comparability of

assessment methods if there is more than one group

Bias 9 4-5 Describe any efforts to address potential sources of bias

Study size 10 4 Explain how the study size was arrived at

Quantitative

variables

11 5-6 Explain how quantitative variables were handled in the analyses. If

applicable, describe which groupings were chosen and why

Statistical methods 12 6-7 (a) Describe all statistical methods, including those used to control for

confounding

(b) Describe any methods used to examine subgroups and interactions


(d) Cohort study—If applicable, explain how loss to follow-up was

addressed

Case-control study—If applicable, explain how matching of cases and

controls was addressed

Cross-sectional study—If applicable, describe analytical methods

taking account of sampling strategy


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(Continue)

Item No Page Results

Participants 13* 7 (a) Report numbers of individuals at each stage of study—eg numbers

potentially eligible, examined for eligibility, confirmed eligible,

included in the study, completing follow-up, and analysed



Descriptive

data

14* 7 (a) Give characteristics of study participants (eg demographic, clinical,

social) and information on exposures and potential confounders

(b) Indicate number of participants with missing data for each variable

of interest

(c) Cohort study—Summarise follow-up time (eg, average and total

amount)

Outcome data 15* 7-8 Cohort study—Report numbers of outcome events or summary

measures over time

Case-control study—Report numbers in each exposure category, or

summary measures of exposure

Cross-sectional study—Report numbers of outcome events or

summary measures

Main results 16 7-8 (a) Give unadjusted estimates and, if applicable, confounder-adjusted

estimates and their precision (eg, 95% confidence interval). Make

clear which confounders were adjusted for and why they were

included

(b) Report category boundaries when continuous variables were

categorized

(c) If relevant, consider translating estimates of relative risk into

absolute risk for a meaningful time period

Other analyses 17 7-8 Report other analyses done—eg analyses of subgroups and

interactions, and sensitivity analyses

Discussion

Key results 18 8 Summarise key results with reference to study objectives

Limitations 19 10 Discuss limitations of the study, taking into account sources of

potential bias or imprecision. Discuss both direction and magnitude of

any potential bias

Interpretation 20 8-10 Give a cautious overall interpretation of results considering objectives,

limitations, multiplicity of analyses, results from similar studies, and

other relevant evidence

Generalisability 21 10 Discuss the generalisability (external validity) of the study results

Other information

Funding 22 12 Give the source of funding and the role of the funders for the present

study and, if applicable, for the original study on which the present

article is based

*Give information separately for cases and controls in case-control studies and, if applicable, for exposed

and unexposed groups in cohort and cross-sectional studies.

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Note: An Explanation and Elaboration article discusses each checklist item and gives methodological

background and published examples of transparent reporting. The STROBE checklist is best used in

conjunction with this article (freely available on the Web sites of PLoS Medicine at

http://www.plosmedicine.org/, Annals of Internal Medicine at http://www.annals.org/, and Epidemiology at

http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.

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Comparisons of four different amounts of exercise for preventing depressive symptoms in community-dwelling

older adults: an 11-year follow-up study in Taiwan

Journal: BMJ Open



Date Submitted by the Author: 29-Jan-2017




Mental health




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Comparisons of four different amounts of exercise for preventing 1

depressive symptoms in community-dwelling older adults: an 11-year 2

follow-up study in Taiwan 3

4


2, I-Han Hu

3, Wan-Chi Ida Wu

4, Susan C. Hu

5* 5

6

7

1. Yu-Chen Chang, MD, PhD, Department of Community Health, Chia-Yi Christian 8

Hospital, Chia-Yi, Taiwan. [email protected] 9

2. Mei-Chun Lu, MS, Department of Medical Research, Kuang Tien General Hospital, 10

Taichung, Taiwan. [email protected] 11

3. I-Han Hu, MS, Institute of Gerontology, College of Medicine, National Cheng Kung 12

University. [email protected] 13

4. Wan-Chi Ida Wu, PhD, Department of Public Health, College of Medicine, National 14

Cheng Kung University, Tainan, Taiwan. [email protected] 15

5. Susan C. Hu, PhD, Department of Public Health, College of Medicine, National Cheng 16

Kung University, Tainan, Taiwan. [email protected] 17

18

19

*Corresponding author: Susan C. Hu, PhD 20

Dept. of Public Health, College of Medicine, National Cheng Kung University, 21

No.1, University Rd, Tainan, Taiwan, 70101 22

E-mail: [email protected] 23

Tel: +886-972-967800, Fax: +886-6-2359033 24

25

Running title: Exercise on depression 26

World count: Abstract 272, Text 3389 27

Number of figures: 1 28

Number of tables: 429

30

31

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ABSTRACT 1

Objectives: to compare the effects of four different amounts of exercise for preventing 2

depressive symptoms in community-dwelling older adults. 3

Design: prospective cohort study. 4

Setting: a nationally representative sample in Taiwan. 5

Participants: Four waves of the survey “Taiwan Longitudinal Study on Aging (TLSA)” from 6

1996 to 2007 were analyzed. A total of 2,673 older adults aged 65 and over were recruited. 7

Primary and secondary outcome measures: Depressive symptoms were measured using 8

the Center for Epidemiologic Studies Depression scale (CESD). Four different types/amounts 9

of exercise were examined, including (1) 3 times/week, 15 min/time; (2) 3 times/week, 30 10

min/time; (3) 6 times/week, 15 min/time; and (4) 6 times/week, 30 min/time. All exercise 11

types were required to have at least moderate intensity. The impacts of different amounts of 12

exercise on depressive symptoms were analyzed using generalized linear mixed models. 13

Results: More than one fifth of the elder individuals under consideration had depressive 14

symptoms (CESD ≥10). About 38.6% of older adults met the lowest criteria for exercise type 15

1, and fewer (28.0%) met the highest criteria for type 4. Only exercise type 4 in the current 16

survey was initially related to lower depressive symptoms (OR=0.8, 95%CI=0.66-0.95). 17

However, after considering the interaction between time and changes in exercise patterns, the 18

results showed that all persistent exercise models, even if a very low amount (3 times/week, 19

15 min/time), had significantly preventive effects on depressive symptoms (OR=0.56~0.67). 20

Conclusion: Consistent exercise with at least 15-min per time, 3 times a week of moderate 21

intensity is significantly associated with lower risk of depressive symptoms. This low amount 22

of exercise may be easier to promote at the community and population level than other 23

alternatives. 24

Trial registration: registry number 104040 of the Institutional Ethics Committee of Chia-Yi 25

Christian Hospital. 26

27

Keywords: 28

Exercise, depression, mental health, elderly, generalized linear mixed models, cohort study. 29

30

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Strengths and limitations of this study 1

� This is the first report to compare the effects of four different amounts of exercise on 2

preventing depressive symptoms in older adults. 3

� The strengths of this study include the fact that it is a nationally representative sample, a 4

longitudinal cohort design, an examination of the changes in exercise status over time, 5

and a proper consideration of statistical analysis methods. 6

� However, the effects of different variables for depression may be altered for different 7

cohorts because of changes in medicine, nutrition, or in the environment. 8

� The outcome event was performed the same time as the second visit to develop the 9

changes in exercise patterns, which may reduce the interpretation of a causal 10

relationship. 11

12

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INTRODUCTION 1

Late life depression is an important health issue among different ethnic groups, affecting 2

13.7% of the population in the US and 20% of older Chinese adults in Taiwan.1-2

Depressive 3

disorder has been indicated as one of the top ten causes of years lived with disability among 4

188 countries based on the Global Burden of Disease Study, 2013.3 It has also been closely 5

linked to quality of life among community-dwelling older adults in many studies.4-6

6

Several relevant interventions have been suggested for preventing or treating depression 7

in addition to medicine. For instance, having a marital partner or having good social support 8

will significantly reduce the impacts of disability from depression.7 Psychological 9

intervention, especially group-based, has been shown to have benefits in regard to both 10

prevention and economic effects.8-10

Six weeks of healthy dietary practice has also been 11

helpful in reducing depressive symptoms, and the benefits may be sustained for as long as 2 12

years.11

13

However, even in ancient Greece, Hippocrates suggested that his patients exercise to 14

treat the behaviors of overconsumption, and Galen further instructed patients to exercise to 15

reduce troublesome depression.12

Many mechanisms of anti-depressive effects of exercise 16

were summarized in Rethorst, Wipfli, and Landers’s study.13

For example, four mechanisms 17

in hippocampal neurogenesis can be potentially facilitated by exercise: increases in 18

B-endorphins, vascular endothelial growth factor, brain-derived neurotrophic factor, and 19

serotonin. Thus, exercise is potentially an effective approach to treating or preventing 20

depression. 21

Little research has focused on the relationship between exercise and depressive 22

symptoms in the elderly. Among the limited number of studies, exercise seems to have 23

similar effects to those of some pharmacological treatments14

, but some meta-analysis studies 24

have yielded inconsistent results.15-17

Also, exercise did not always show benefits related to 25

preventing or treating depression because many of the studies did not control for previous 26

levels of depressive symptoms, and only a few included a follow-up period of more than 2 27

years. Furthermore, since exercise status changes as people age, how the transitional patterns 28

of exercise in older adults affect depressive symptoms has yet to be studied. 29

In addition, in the case of older adults, exercise programs must consider both intensity 30

and duration. The general recommendation for exercise by the American College of Sports 31

Medicine is moderate intensity; exercise is engaged in at least 30 minutes per day at least 5 32

days a week to accumulate a total of 150-300 minutes per week, or vigorous intensity of at 33

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However, 1

a recent study by Wen et al. indicated that a low amount of exercise, which is defined as 15 2

minutes per day or 90 minutes per week at moderate intensity, has proven beneficial in 3


This result provides a more age-friendly 4

exercise model, which could be further explored in regard to its effects on depressive 5

symptoms in older adults. 6

Therefore, in this study, we use an 11-year cohort data from a population-based survey 7

to examine how different amounts of exercise affect depressive symptoms in older adults. 8

The purposes of the study were: (1) to examine the impacts of four different types of exercise 9

on preventing depressive symptoms in older adults using Taiwan as an example and (2) to test 10

the effects of changes in exercise status during a specific period of time on depressive 11

symptoms in the elderly. 12

13

METHODS 14

Study design and participants 15

This is a longitudinal cohort study, using nationally representative data from the survey 16

“Taiwan Longitudinal Study on Aging, TLSA.” The TLSA survey was undertaken as a 17

collaborative project between the University of Michigan, USA and the Health Promotion 18

Administration, Ministry of Health and Welfare, Taiwan. There were six waves of surveys for 19

those aged 60 and over in 1989, 1993, 1996, 1999, 2003 and 2007. Supplemental cases aged 20

50 and older were added to the cohort in 1996 and 2003. A three-stage proportional-to-size 21

probability sampling technique was used in the survey, and face-to-face interviews were 22

conducted with each individual. The response rates in each wave were high, ranging from 23

81.2% to 91.4%. 24

Since detailed exercise questionnaires were launched in 1996, we combined two cohorts 25

(cohort B aged 67+ and cohort A aged 50-66) in 1996 as our study cohort. The inclusion 26

criterion was aged 65 and older; the exclusion criteria included those who did not complete 27

the relevant questionnaires, lived in institutions, or answered by proxy. We used the 1999 28

survey as the baseline and followed subjects up to 2007. A total of 2,673 valid participants 29

was selected as the baseline, and 5923 observations were counted. 30

Due to the significant effects of previous depressive symptoms and changes in exercise 31

behavior on depression, we used more retrospective data as control variables from the 1996 32

survey when analyzing the effects in 1999. Thus, the total number of observations in the 33

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four-wave surveys was 8,397. The flow chart of the valid sample size is shown in Figure 1. 1

This study was approved by the Institutional Ethics Committee of Chia-Yi Christian Hospital 2

(registry number 104040). 3

4

Fig. 1: No. of participants in the four-wave surveys 5

6

Measurements 7

Dependent Variable: Depressive Symptoms 8

Depressive symptoms were measured with the Center for Epidemiologic Studies 9


was modified to a 10-item scale21

, 10

which was used in the TLSA survey. Each item was scored from 0 to 3, making the total 11

score range from 0 to 30. The measure, with a cutoff score of 10, has been recommended as a 12

good tool to assess depressive symptom severity at the community level.22

Because level of 13

depressive symptoms is associated with future depression and quality of life23-24

, we 14

categorized the level of depressive symptoms into No Depressive Symptom (NDS), defined 15

as CESD=0; Lower Level of Depressive Symptoms (LLDS), 0<CESD≤9; and Higher Level 16

of Depressive Symptoms (HLDS), CESD≥10. 17

18

Independent Variables: Types/amount of exercise and Changing patterns 19

The degree of exercise was quantified by asking about the frequency (0, ≤2, 3-5, ≥6 20

times per week), duration (<15 min, 15-30 min, >30 min), and intensity based on sweating 21

level (none, a little, a lot, none of the above) and panting level (none, a little, a lot, none of 22

the above) after exercise. 23

Four types/amount of exercise were classified in this study. Exercise type 1 means that 24

exercise of at least moderate intensity was performed ≥3 times/week, ≥15 min/time (T3_15); 25

Exercise type 2 means ≥3 times/week, >30 min/time (T3_30); Exercise type 3 means ≥6 26

times/week, ≥15 min/time (T6_15); Exercise type 4 means ≥6 times/week, >30 min/time 27

(T6_30). Moderate intensity was defined as experiencing some sweating and panting after 28

exercise.18

29

Patterns of exercise consistency refers to changes in the practice of respective exercise 30

types between two waves, which was classified as (a) Low pattern (pattern NN): the 31

respective exercise type was not practiced in the previous or in the current surveys; (b) 32

Declining pattern (pattern YN): the respective exercise type was practiced in the previous but 33

not in the current surveys; (c) Increasing pattern (pattern NY): the respective exercise type 34

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was practiced in the current but not in the previous surveys; and (d) Persistent pattern (pattern 1

YY): the respective exercise type was practiced in both the previous and in the current 2

surveys. In the analysis, all models were based on paired observations between two waves, 3

for example, 1996-1999, 1999-2003, 2003-2007. Therefore, when someone exercised in 2003 4

and 2007 but not 1999, he/she was counted twice, as “increasing pattern” in 1999-2003 and 5

as “persistent pattern” in 2003-2007. 6

7

Control Variables 8

Sociodemographic variables included gender, age, marital status (married or living with 9

a partner was coded as 1, otherwise 0), level of education (none, elementary, junior high 10

school, senior high school, and college and above), economic satisfaction (dissatisfied, 11

satisfied) and employment status (yes/no). 12

Physical function involved reversing the scale of a 4-point measurement inquiring the 13

level of difficulty of seven mobility tasks, including standing for 15 min, squatting, raising 14

both arms up, grasping with fingers, lifting an 11 kg weight, running 20-30 m, and climbing 15

up two to three floors. The sum of the physical battery ranged from 0-21. A higher score 16

indicated a better physical battery. These measurements have been reported as hierarchically 17

associated with instrumental and basic activities of daily living.25

18

Social participation refers to participation in any of the following groups: volunteers, 19

community groups, religious groups, occupational associations, political parties or groups, 20

social service groups, clan associations, senior groups, or schools. Social participation was 21

coded as a binary variable (yes/no). 22

Emotional support was the summed scores of seven items, which were coded from 0 to 3, 23

including (1) family/relatives/friends care about you; (2) family/relatives/friends listen to you; 24

(3) you can count on family/relatives/friends when you are ill; (4) you are satisfied with the 25

support from your family/relatives/friends. (5) How often do your family or friends come to 26

you for opinions? (6) In what ways do you feel that you are helpful to your family or friends? 27

(7) How often do you feel rejected by your family/relatives/friends? The last item was scored 28

reversely. 29

Health-related variables included self-rated health (poor, fair and good) and other binary 30

variables such as current smoking and 10 chronic conditions including cancer, chronic 31

respiratory disease, gastrointestinal disease, hypertension, diabetes mellitus, heart disease, 32

stroke, arthritis, hepatobiliary disease and renal disease. 33

34

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Statistical analysis 1

The descriptive analysis of depressive symptoms and covariates were presented as a 2

mean ± standard deviation (SD) or as n (%) for continuous or categorical data, respectively. 3

We applied generalized linear mixed models (GLMMs) via PROC GLIMMIX to estimate the 4

effects of different transitional patterns of exercise on depressive symptoms with HLDS as 5

the event, after adjusting for the previous CESD score, age, gender, level of education, 6

marital status, smoking, physical function, emotional support, social participation, self-rated 7

health, economic satisfaction, employment, and 10 chronic conditions. The interaction of 8

time and transitional patterns of exercise was also included in the above analysis. A two-sided 9

p-value <0.05 was considered statistically significant. All data was merged and analyzed 10

using SAS 9.2 (SAS Institute, Cary, NC). 11

12

RESULTS 13

There were 2,673 valid subjects selected from the survey conducted in 1999, and a total 14

of 8,397 observations in four survey waves. Table 1 shows the distribution of characteristics 15

for the subjects from 1999 (baseline) to 2007. At baseline, the average age was 74.2 ± 5.7 16

years old, of which 54.5% were male. The prevalence of LLDS and HLDS was 20~24% over 17

time. About 38.6% of participants met the lowest criteria of T3_15, and fewer (28.0%) met 18

the highest criteria of T6_30. Noticeably, in any survey, exercise models T3_15 and T6_15 19

have a higher proportion than T3_30 and T6_30. This may imply the difficulty for older 20

adults to engage in long periods of exercise. 21

Table 2 illustrates the odd ratios (OR) of HLDS according to the current practices of 22

exercise models and other determining factors. Only exercise type 4 (T6_30) had a significant 23

reducing effect on HLDS (OR=0.80, 95% CI=0.66-0.95). Also, the previous level of 24

depressive symptoms, physical function, emotional support, self-rated health and economic 25

satisfaction were all positively predictive of HLDS. 26

Table 3 shows the predictive effects of previous exercise models for higher levels of 27

depressive symptoms. However, none of the four exercise models in the previous survey 28

could predict the presence of higher levels of depressive symptoms. Namely, previous 29

exercise behavior appeared to have no benefits on reducing depression, regardless of the 30

amount or type of exercise. This may suggest that the effects of exercise on depressive 31

symptoms are only concurrent and short-term. 32

Thus, we conducted another test to examine the effect of changes in different exercise 33

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models on depressive symptoms, as shown in Table 4. After controlling for other determining 1

factors and considering the interaction of time and patterns of exercise, the results indicated 2

that only persistent patterns (pattern YY) reveal a significant protective effect from higher 3

levels of depressive symptoms, regardless of exercise type (OR=0.58, 0.56, 0.67, 0.62, 4

respectively, all p<0.05). Namely, even the lower amount of exercise (T3_15) may have 5

protective effects on depression as long as older adults continuously reach moderate intensity 6

for at least 15 minutes with a frequency of no less than three times a week. 7

8

DISCUSSION 9

Very limited research has been conducted to determine the long-term effects of different 10

exercise models on depressive symptoms in the elderly. The purpose of the current study was 11

to examine the impacts of four different types of exercise on depressive symptoms in 12

community-dwelling older adults. We found that only current exercise type 4 (T6_30) was 13

significantly associated with lower depressive symptoms, whereas previous exercise behavior 14

seemed to have no benefits with regard to reducing depression. However, when considering 15

the changes in exercise behavior between two waves, this study shows that different patterns 16

of exercise are significantly associated with HLDS outcomes. Only the persistent patterns of 17

exercise (pattern YY) revealed a significant protective effect from higher levels of depressive 18

symptoms. 19

Furthermore, this study shows that persistent low-volume exercise, i.e. ≥15 min of 20

moderate intensity exercise (T3_15 and T6_15), can provide preventive effects on depressive 21

symptoms, similar to the benefits of high-volume exercise, i.e. ≥30 min of moderate intensity 22

exercise (T3_30 and T6_30), in older adults. These findings suggest that short, age-friendly 23

exercise types may benefit older adults both physically and psychologically. 24

Comparing similar studies from Ku et al., where they suggested that exercise frequency 25

may be important for depressive symptoms26

and where the changing pattern of the low-low 26

group led to a high risk of developing depressive symtoms27

, our study revealed that 27

consistency may be the key factor, regardless the frequency or duration of exercise, as long as 28

the exercise is of moderate intensity. Namely, both exercise frequencies of ≥3 times/week or 29

≥6 times/week with at least 15- or 30- minutes each time showed significantly negative 30

association with higher levels of depressive symptoms in this study. These results indicate the 31

importance of the consistency of exercise. 32

Noticeably, the study by Ku et al. analyzed only traditional types of physical activity 33

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according to frequency, while in this study, we compared four types of physical activity and 1

measured physical activity simultaneously by using three dimensions, including frequency, 2

duration and intensity. In addition, we considered important covariates related to depressive 3

symptoms, such as social participation, emotional support, mobility, and self-rated health, 4

among others. Therefore, we believe our results can substantially contribute to the existing 5

knowledge of the relationship between physical activity and depressive symptoms. 6

Another study using a Taiwanese national survey suggested promoting high intensity, 7


8

the results of which are not completely compatible with our findings. However, the nature of 9

the cross-sectional study design used in that study may have caused it to have a higher 10

possibility of over-interpretation of the results. Less depressed people may be more likely to 11

engage in higher intensity exercise as compared to more depressed people. Our longitudinal 12

study suggests that a low amount of exercise also has benefits related to preventing 13

depressive symptoms. Furthermore, transitional patterns of exercise may be more important 14

than the current exercise models that people are practicing. 15

Physical inactivity was found to be among the top 10 leading risk factors for the global 16


It is important to promote exercise, especially among older adults, 17

who are more vulnerable to physical and psychological dysfunction. The general 18

recommendation for older adults is moderate intensity exercise accumulated to at least 30 19

min each day for at least 5 days a week to total 150-300 min/week, or vigorous intensity 20

exercise at least 20-30 min per day for 3-5 days per week to total 75-100 min/week.18

21

However, East Asians usually engage in fewer physical activities at lower intensity than 22

people in western countries.30-31

In consideration of physical conditions, it would be helpful 23

to determine the minimal volume of exercise for older adults required to improve their health. 24

This study showed that the percentage of participants who engaged in exercise type 25

T6_15 was higher than that of T3_30 and T6_30, which indicates that lower intensity, higher 26

frequency exercise may be more acceptable to older people than higher intensity exercise at a 27

lower frequency. Furthermore, the low-volume exercise type has been shown to have benefits 28

related to reducing all-cause mortality and all-cancer mortality.19, 32

Therefore, based on the 29

findings of our study, we feel confident about concluding that persistent low-amount exercise 30

with the same moderate intensity (at least ≥15 min/ 6 times/ week) may also benefit older 31

adults both physically and psychologically. 32

Because of the social stigma of depressive symptoms, many people with this condition 33

tend to remain under-treated. When unable to appropriately address the causes or when there 34

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is no access to adequate non-medical or community services to treat depression, patients may 1


Our study 2

provides a practical and non-medical option to prevent higher levels of depressive symptoms. 3

Most importantly, it will help reduce the unnecessary use of medication, which sometimes 4

causes adverse drug reactions in older adults, and it may also help people when they lack 5

awareness of their disorder or are reluctant to be treated. 6

Still, there are several other factors affecting depressive symptoms. Depression is 7

significantly associated with chronic medical conditions, problems with ADLs, poor social 8


Functional limitations and arthritis are 9

among the strong risk factors in chronic conditions for depression.36

Physical function, 10

emotional support, self-rated health, and economic satisfaction were consistently shown to 11

significantly influence HLDS in all analyses in our study. However, among the 12

above-mentioned factors, exercise is the more changeable variable, which could also benefit 13

physical function and self-rated health. 14

This is the first report to examine the impacts of four different types of exercise on 15

depressive symptoms in the elderly according to the recommendations of different 16

experts.18-19

However, there have been previous studies that have examined the relationship 17

between physical activity and depressive symptoms in the elderly with different definitions of 18

exercise groups in different areas (city/rural).37-38

Thus, to compare the results, the 19

compatibility of participants, the exercise measurement, and the categories of the exercise 20

groups should be carefully considered. The advantages of this study include the fact that it 21

included a nationally representative sample, a longitudinal cohort design, a test of different 22

amount of exercise, an examination of the changes in exercise status over time, and a proper 23

consideration of statistical analysis methods. 24

Nonetheless, the study has some limitations. Firstly, the observation for the outcome 25

event was performed the same time as the second visit to develop the variables for 26

transitional patterns of exercise, which may have reduced the interpretation of a causal 27

relationship if the association between current exercise and the outcome event is too strong. 28

However, if the assumption is true, the bias will support the null hypothesis. The results 29

indicate that the significantly protective effects of a persistent pattern of exercise are 30

consistent across all types of exercise considered in this study. The increasing exercise 31

pattern did not result in the same finding although both patterns indicated that the subjects 32

had practiced the respective exercises on their second visit. We are therefore comfortable 33

with inferring that a persistent pattern of exercise has more influence than increasing and 34

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other transitional patterns of exercise. Secondly, the effects of different variables for HLDS 1

may be altered for different cohorts because of changes in medicine, antidepressants, 2

nutrition or in the environment. This may limit the application of the findings of this study. 3

Thirdly, the measurement for physical activity did not include a timeframe but only asked 4

participants “Do you usually engage in exercise?” This may reduce the reliability of the 5

measurement of exercise. However, most of the time, when a questionnaire does not mention 6

a timeframe, it implies “in the past year.” Lastly, activities of daily living (ADL) was not 7

included in the analysis because it may include those who cannot perform exercise. We used 8

physical function ability, which has shown to be hierarchically associated with instrumental 9

and basic ADL25

to control for any differences related to limitations in mobility. 10

11

CONCLUSION 12

Consistent exercise comprised of at least 15-min per time, 3 times a week of moderate 13

intensity is significantly associated with lower risk of depressive symptoms. Increasing the 14

frequency to more than 5 times per week will benefit older adults both physically and 15

psychologically. We recommend taking this low amount of exercise into serious consideration 16

when designing exercise programs related to older adults. 17

18

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Acknowledgements 1

We would like to thank the Health Promotion Administration, Ministry of Health and 2

Welfare of Taiwan for providing the dataset for analysis. 3

Contributors 4

Y-CC and M-CL designed and conducted the study and wrote the daft; I-HH analyzed 5

the data and interpreted the tables; W-CW conducted the literature review and revised the 6

draft; SCH advised the whole study and completed the manuscript. All authors contributed to 7

the interpretation of results, critically reviewed the draft, and approved the final manuscript. 8

Funding 9

This study was supported by Research Center for Humanities and Social Sciences, 10

National Cheng Kung University, (H10-A304, FD101037). 11

Competing interests 12

None declared. 13

Ethical approval 14

This study was approved by the Institutional Ethics Committee of Chia-Yi Christian 15

Hospital (registry number 104040). 16

Provenance and peer review 17

Not commissioned; externally peer reviewed. 18

Data sharing statement 19

No additional data are available. 20

21

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1

Table 1 Characteristics of the participants from 1999 to 2007 2

Variables

1999 2003 2007

N=2673 N=1889 N=1361

n (%) n (%) n (%)

Age 74.2 ± 5.7 77.1 ± 5.1 80.2 ± 4.7

Male 1456 (54.5) 1019 (53.9) 703 (51.7)


NDS 1401 (52.5) 1049 (55.5) 708 (52.0)

LLDS 646 (24.2) 388 (20.5) 321 (23.6)

HLDS 624 (23.4) 452 (23.9) 332 (24.4)

M±SD 6.1 ± 6.4 5.7 ± 5.9 5.8 ± 6.1

Types/amount of exercise*

T3_15 1032 (38.6) 810 (42.9) 562 (41.3)

T3_30 859 (32.1) 671 (35.5) 450 (33.1)

T6_15 922 (34.5) 742 (39.3) 498 (36.6)

T6_30 749 (28.0) 603 (31.9) 386 (28.4)

Education

No 1111 (41.6) 733 (38.8) 507 (37.3)

Elementary 983 (36.8) 723 (38.3) 515 (37.8)




Married 1630 (61.0) 1096 (58.0) 727 (53.4)

Employment 322 (12.1) 142 (7.5) 84 (6.2)

Current smoking 595 (22.3) 344 (18.2) 189 (13.9)




Self-rated health

Poor 934 (34.9) 707 (37.4) 481 (35.3)

Fair 927 (34.7) 583 (30.9) 531 (39.0)

Good 812 (30.4) 599 (31.7) 349 (25.6)


Dissatisfied 544 (20.4) 407 (21.6) 271 (19.9)

Fair 1144 (42.9) 653 (34.6) 486 (35.7)

Satisfied 978 (36.7) 828 (43.9) 604 (44.4)

Chronic conditions

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Cancer 71 (2.7) 61 (3.2) 54 (4.0)



Hypertension 1002 (37.5) 829 (43.9) 672 (49.4)


Heart disease 576 (21.6) 469 (24.8) 373 (27.4)

Stroke 144 (5.4) 126 (6.7) 83 (6.1)

Arthritis 594 (22.2) 465 (24.6) 322 (23.7)


Renal disease 217 (8.1) 192 (10.2) 139 (10.2)

Data were presented as mean ± SD or n (%). 1

NDS: No Depressive Symptom (CESD=0); 2

LLDS: Lower Level of Depressive Symptoms (0<CESD≦9); 3

HLDS: Higher Level of Depressive Symptoms (CESD≧10); 4

CESD: Center for Epidemiologic Studies of Depression; 5

*T3_15: Exercise ≧moderate intensity, ≧3 times/week, ≧15 min/time; 6

T3_30: Exercise ≧moderate intensity, ≧3 times/week, ≧30 min/time; 7


T6_30: Exercise ≧moderate intensity, ≧6 times/week, ≧30 min/time. 9

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Table 2 Odds ratios of HLDS according to the current exercise behavior as estimated 11

using GLMM ‡ 12

Variables HLDS

OR (95% CI) p-value

Types/amount of exercise

T3_15 1.14 (0.92-1.42) 0.24

T3_30 0.86 (0.59-1.25) 0.42

T6_15 0.86 (0.65-1.13) 0.27

T6_30 0.80 (0.66-0.95) 0.01


NDS ref

LLDS 1.83 (1.48-2.28) <0.001

HLDS 3.04 (2.39-3.85) <0.001



Self-rated health

Poor ref

Fair 0.52 (0.44-0.61) <0.001

Good 0.29 (0.23-0.36) <0.001


Dissatisfied ref

Fair 0.51 (0.43-0.60) <0.001

Satisfied 0.33 (0.27-0.40) <0.001

OR: odds ratio; CI: confidence interval. 13


GLMM: generalized linear mixed models 15





‡All of the analysis models were adjusted according to present age, gender, education, marital status, 20

smoking, social participation, and chronic conditions including cancer, chronic respiratory disease, 21

gastrointestinal, hypertension, diabetes mellitus, heart disease, stroke, arthritis, hepatobiliary disease 22

and renal disease. 23

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Table 3 Odds ratios of HLDS according to the previous exercise behavior as 25

estimated by GLMM‡ 26

Variables HLDS

OR (95% CI) p-value

Previous exercise types/amount

T3_15 0.88 (0.72-1.06) 0.17

T3_30 1.05 (0.76-1.46) 0.77

T6_15 0.98 (0.79-1.23) 0.89

T6_30 0.68 (0.44-1.07) 0.10


NDS ref

LLDS 1.86 (1.50-2.31) <0.001

HLDS 3.12 (2.46-3.96) <0.001



Self-rated health

Poor ref

Fair 0.52 (0.44-0.60) <0.001

Good 0.28 (0.23-0.35) <0.001


Dissatisfied ref

Fair 0.51 (0.43-0.60) <0.001

Satisfied 0.33 (0.27-0.40) <0.001




T3_15: Exercise ≧moderate intensity, ≧3 times/week, ≧15min/time; 30



T6_30: Exercise ≧moderate intensity, ≧6 times/week, ≧30min/time. 33





38

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Table 4 Odds ratios of HLDS taking interaction of time and exercise consistency into consideration ‡ 40

Variables

Model 1

(T3_15)

Model 2

(T3_30)

Model 3

(T6_15)

Model 4

(T6_30)



NN ref ref ref ref

YN 0.77 (0.54-1.11) 0.16 0.86 (0.60-1.25) 0.43 0.76 (0.53-1.09) 0.14 0.92 (0.64-1.34) 0.68

NY 0.79 (0.54-1.16) 0.24 0.78 (0.52-1.17) 0.23 0.68 (0.45-1.01) 0.06 0.71 (0.46-1.10) 0.12

YY 0.58 (0.40-0.85) 0.01 0.56 (0.36-0.88) 0.01 0.67 (0.45-1.00) 0.048 0.62 (0.38-0.99) 0.047

Previous CESD

NDS ref ref ref ref

LLDS 1.82 (1.43-2.33) <0.001 1.81 (1.42-2.31) <0.001 1.82 (1.42-2.32) <0.001 1.81 (1.42-2.31) <0.001

HLDS 3.23 (2.47-4.23) <0.001 3.20 (2.45-4.18) <0.001 3.23 (2.47-4.22) <0.001 3.20 (2.45-4.19) <0.001

Time slope 0.95 (0.92-0.99) 0.01 0.97 (0.94-1.00) 0.08 0.96 (0.92-0.99) 0.01 0.98 (0.94-1.01) 0.14


NN ref ref ref ref

YN 1.12 (1.05-1.20) <0.01 1.07 (1.00-1.15) 0.04 1.12 (1.05-1.20) <0.01 1.06 (0.99-1.14) 0.07

NY 1.01 (0.93-1.09) 0.79 0.99 (0.91-1.08) 0.84 1.02 (0.94-1.10) 0.69 0.98 (0.90-1.07) 0.68

YY 1.11 (1.03-1.18) <0.01 1.09 (1.01-1.17) 0.04 1.09 (1.01-1.17) 0.02 1.07 (0.99-1.17) 0.10







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NN: Low pattern of exercise transition, indicating the respective exercise type was not practiced in either the previous or current survey. 48

YN: Declining pattern of exercise transition, indicating the respective exercise type was practiced in the previous but not in the current survey. 49

NY: Increasing pattern of exercise transition, indicating the respective exercise type was practiced in the current but not in the previous survey. 50

YY: Persistent pattern of exercise transition, indicating the respective exercise type was practiced in both the previous and current surveys. 51

‡All the analysis models were adjusted according to present age, gender, education, marital status, smoking, physical function, emotional support, social 52

participation, self-rated health, economic satisfaction, employment and chronic conditions including cancer, chronic respiratory disease, gastrointestinal, 53

hypertension, diabetes mellitus, heart disease, stroke, arthritis, hepatobiliary disease and renal disease. 54

55

56

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179x129mm (300 x 300 DPI)

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Item No Page/Line Recommendation

Title and abstract 1 0/1-3 (a) Indicate the study’s design with a commonly used term in the

title or the abstract

1/1-24 (b) Provide in the abstract an informative and balanced summary of


Introduction

Background/rationale 2 3/1-33 Explain the scientific background and rationale for the investigation

being reported

Objectives 3 4/4-9 State specific objectives, including any pre-specified hypotheses

Methods

Study design 4 4/12-21 Present key elements of study design early in the paper

Setting 5 4/22-31 Describe the setting, locations, and relevant dates, including

periods of recruitment, exposure, follow-up, and data collection

Participants 6 4/12-31 (a) Cohort study—Give the eligibility criteria, and the sources and

methods of selection of participants. Describe methods of follow-

up

Case-control study—Give the eligibility criteria, and the sources

and methods of case ascertainment and control selection. Give the

rationale for the choice of cases and controls





Case-control study—For matched studies, give matching criteria

and the number of controls per case

Variables 7 5/4-33 Clearly define all outcomes, exposures, predictors, potential


applicable

Data sources/

measurement

8* 5/4-33

6/1-30

For each variable of interest, give sources of data and details of



Bias 9 4/18-21 Describe any efforts to address potential sources of bias

Study size 10 4/22-31 Explain how the study size was arrived at

Quantitative

variables

11 5/4-33

6/1-30

Explain how quantitative variables were handled in the analyses. If


Statistical methods 12 6/33-34 (a) Describe all statistical methods, including those used to control

for confounding

7/1-8 (b) Describe any methods used to examine subgroups and

interactions



addressed

Case-control study—If applicable, explain how matching of cases

and controls was addressed


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(Continue)

Item No Page/Line Results

Participants 13* 7/11-13 (a) Report numbers of individuals at each stage of study—eg

numbers potentially eligible, examined for eligibility, confirmed

eligible, included in the study, completing follow-up, and analysed



Descriptive

data

14* 7/13-18 (a) Give characteristics of study participants (eg demographic,

clinical, social) and information on exposures and potential

confounders

(b) Indicate number of participants with missing data for each

variable of interest


amount)

Outcome data 15* 7/19-23 Cohort study—Report numbers of outcome events or summary

measures over time




summary measures

Main results 16 7/24-33

8/1-4

(a) Give unadjusted estimates and, if applicable, confounder-adjusted



included


categorized



Other analyses 17 8/1-4 Report other analyses done—eg analyses of subgroups and


Discussion

Key results 18 8/7-21 Summarise key results with reference to study objectives

Limitations 19 10/22-34

11/1-7

Discuss limitations of the study, taking into account sources of

potential bias or imprecision. Discuss both direction and magnitude

of any potential bias

Interpretation 20 8/22-33

9/1-34

Give a cautious overall interpretation of results considering

objectives, limitations, multiplicity of analyses, results from similar

studies, and other relevant evidence

Generalisability 21 10/4-21 Discuss the generalisability (external validity) of the study results

Other information

Funding 22 12/9-11 Give the source of funding and the role of the funders for the present


article is based

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Effects of different amounts of exercise on preventing depressive symptoms in community-dwelling older adults: a

prospective cohort study in Taiwan

Journal: BMJ Open



Date Submitted by the Author: 26-Feb-2017




Mental health




BMJ Open on M


http://bmjopen.bm

j.com/

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Effects of different amounts of exercise on preventing depressive symptoms 1

in community-dwelling older adults: a prospective cohort study in Taiwan 2

3


2, I-Han Hu

3, Wan-Chi Ida Wu

4, Susan C. Hu

5* 4

5

6

1. Yu-Chen Chang, MD, PhD, Department of Community Health, Chia-Yi Christian 7

Hospital, Chia-Yi, Taiwan. [email protected] 8

2. Mei-Chun Lu, MS, Department of Medical Research, Kuang Tien General Hospital, 9

Taichung, Taiwan. [email protected] 10

3. I-Han Hu, MS, Institute of Gerontology, College of Medicine, National Cheng Kung 11

University. [email protected] 12

4. Wan-Chi Ida Wu, PhD, Department of Public Health, College of Medicine, National 13

Cheng Kung University, Tainan, Taiwan. [email protected] 14

5. Susan C. Hu, PhD, Department of Public Health, College of Medicine, National Cheng 15

Kung University, Tainan, Taiwan. [email protected] 16

17

18

*Corresponding author: Susan C. Hu, PhD 19

Dept. of Public Health, College of Medicine, National Cheng Kung University, 20

No.1, University Rd, Tainan, Taiwan, 70101 21

E-mail: [email protected] 22

Tel: +886-972-967800, Fax: +886-6-2359033 23

24

Running title: Exercise on depression 25

World count: Abstract 272, Text 3389 26

Number of figures: 1 27

Number of tables: 428

29

30

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