Volume 4, Issue 2 (December 2018)                   Elderly Health Journal 2018, 4(2): 75-80 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Ahmadi B, AminiSanii N, Bani F, Bakhtari F. Predictors of Physical Activity in Older Adults in Northwest of Iran. Elderly Health Journal. 2018; 4 (2) :75-80
URL: http://ehj.ssu.ac.ir/article-1-119-en.html
Department of Health Education and Promotion, School of Health, Tabriz University of Medical Sciences, Tabriz, Iran , fatemeh.bakhtari@gmail.com
Full-Text [PDF 586 kb]   (47 Downloads)     |   Abstract (HTML)  (57 Views)
Full-Text:   (46 Views)
Predictors of Physical Activity in Older Adults in Northwest of Iran
 
Batool Ahmadi 1, Nayyereh Amini Sanii 2, Fahim Bani 3, Fatemeh Bakhtari 1*
 
1. Department of Health Education and Promotion, School of Health, Tabriz University of Medical Sciences, Tabriz, Iran
2. Department of Statistics and Epidemiology, School of Health, Tabriz University of Medical Sciences, Tabriz, Iran
3. Health Affaire of Urmia University of Medical Sciences, Urmia University of Medical Sciences, Urmia, Iran

Article history

Received 17 Jun 2018
Accepted 18 Dec 2018

A B S T R A C T

 
Introduction: There are strong evidences to support the relation between Physical Activity (PA) and improved health in older adults. So this study aimed to determine the predictors of PA among a group of older adults in northwest of Iran.
 
Methods: In 2016, a randomly sample size of 340 older people in urban regions of Maku, West Azerbaijan, Iran, was recruited to complete Physical Activity Scale for the Elderly (PASE) and individual factors questionnaires.
 
Results: The mean score of PA was 94.02 ± 3.41. Logistic regression analysis showed that age was the strongest predictor of PA; among younger elderly with higher level education, who had less comorbidity were significantly more active than their counterparts. (β = -2.72, SE = 0.47, P- value = 0.001)
 
Conclusion: In this study the level of PA among the older adults was low and interventions to promote PA in this population is recommended.
 
Keywords: Physical Activity, Aged, Individual Factors
 
Introduction
    Aging is a complex process of physiological and social change that results in diseases, disabilities, reduced levels of happiness (1), gradual decline in performance, and individual changes (2). One of the key strategies in the healthy ageing process is a physical activity (PA) (1), which results in the lack of dependence, physical ability, and the improvement of the quality of life and the reduction of the risk of disease (2, 3). Regular PA has unexpected changes in physiological factors and increases life expectancy by limiting the growth and progression of chronic diseases, disability in the elderly (4). Despite such health benefits (1, 5-7), insufficient PA is very common in older adults ranging from 50 % to 88 % (5, 8-11). Studies showed that different factors are associated with participating in PA in older adults including social, cultural and climatic conditions (2), and individual and social factors such as age, gender, marital status, education level, income and health status (10).
    Iran’s population is ageing, according to 2011 census, 8.2 % of the total population was made up by the elderly (12), which increased to 10 % by 2025 and 21-25 % by 2050 because of the advancements in health care and social factors toward medical and therapeutic care (1).
    Iranian studies have also shown a high degree of insufficient PA varied between 30 % and up to 85 % (8, 13-15). Findings from studies, the means Physical Activity Scale for the Elderly (PASE) score in the older people were 124.79 in Tehran (15), 222 in Illam (16), and the elderly living in the Canadian Senior Health Center 112.6 (10, 17). Level of PA based on PASE score in the northwest of Iran, with special culture, no study has done on PA level of the elderly. Therefore assessment of PA in this age group can helpful to design healthy programs.
    Maku is located in the northwest of Iran with a population about 49500, it has shared a border with Turkey, and people in this area have Azari-Turkish background with sociocultural differences that affect their lifestyle, based on SIB (an abbreviation for the Persian equivalent of ‘integrated health system’) the percentage of people aged 65 and older is about 7 % in this city (12). Obesity, diabetes, hypertension which are strongly related to the lifestyle factors such as insufficient PA are common in this city and the number of studies targeting the health of older people is scarce. Therefore, this study aimed to assess the level of the PA, and its correlates among older adults in this area to introduce proper health promotion for older adults (18, 19).
 
Methods
Study design
    This cross-sectional study was conducted in 2016 in Maku located in the north-west of Iran. Subject selection: A total of 340 randomly selected individuals aged 60 years and older were included in this study. Inclusion criteria were: aged 60 and above, standing and walking ability, no severe mental history, limiting musculoskeletal disorders, neurological defects, Parkinson's disease, acute heart failure, severe hearing impairment and visual impairment and congenital physical defects.
Data collection
    Eligible individuals received a phone call informing the study aim and procedure, and if they provided a verbal consent, then the interviewer invited them to attend the health center for conduction an interview. In some circumstances where the study participants were not able to visit the health center, a home visit was arranged.
Instrumentation
    Study information was collected through a questionnaire which consisted of two parts. 1 socio-demographic data (age, sex, level of education, occupation, monthly income, marital status), smoking, weight, height, the presence of the chronic disease (diabetes, hypertension, heart disease, cancer, depression, arthritis, cholesterol, prostate, asthma, thyroid and co-morbidity) (2). We applied the PA Scale for the Elderly (PASE) to measure the level of PA among the participants. The PASE, as a brief and specific instrument was designed for the elderly to measure the PA recalled over a period of one week (20). In this scale, participants are asked to report how often (i.e, never, seldom, 1–2 days; sometimes, 3–4 days; or often, 5–7days) they were engaged in a variety of activities during the previous week. The activities included light (e.g., stretching), moderate (e.g., pairs tennis), or strenuous intensity activities (e.g., jogging) as well as muscle-conditioning activities. Time spent on these activities was categorized into four classes of less than 1 hour, 1–2 hrs, 2–4 hrs, or more than 4 hrs/day. Moreover, time spent in paid or volunteer work involving at least some standing or walking was recorded in total hours per week. Furthermore, household activities such as light house-work, yard work, and caring for others were also recorded and was categorized as yes or no. To generate the final PASE score for the week, various activities were multiplied by established item weights (20). PA levels were categorized based on PASE score to 4 levels. level 1 including PASE ≤ 93, level 2: PASE = 94-146, level 3: PASE = 147-206 and level 4: PASE ≥ 206(21).
    The validity and reliability of PASE have been used to measure the PA of the elderly in various studies (20, 22). The content validity and reliability of the questionnaire in Iran were also evaluated by Ishani et al. And the Cronbach's alpha coefficient was 0.97 (23).
Ethical considerations
    All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Ethical approval was provided by a research committee in an Iranian medical university with number IR.TBZMED.REC.1395.767.
Data analysis
    Data were summarized using means (± SD) for continuous variables and counts and percentages for categorical variables. Distribution of PA as PASE score across different variables was also described as means (± SD). Kruskal Wallis test was used to assess the bivariate differences of PA level across different variables, respectively because the PASE score was not distributed normally. Multiple linear regression was used to identify the association between PASE score and selected variables in this study such as age, sex, BMI, education, job, number of comorbidities, and smoking. The β coefficient, the standard error and the p-value were reported with the multiple regression models. All statistical assumptions were checked and fulfilled before using the regression running the model. The analysis was performed using the STATA software.
 
Results
    A total of 340 people aged 60 years and above were included in this study. The average age of participants was 69.2 ± 7.3, 193 (56.8 %) were women, 176 (51.8 %) were illiterate/reading and writing ability, the majority were married and currently lived with their spouses and 28.2 % were smokers. (Table 1)
    Mean scores for PA were low (94.2) and 54 % of participants were inactive. (Table2)
    A linear regression was conducted to test a predictive model for PA (PASE score) with predictor variables (age, gender, education, smoking, job, number of comorbidities, and BMI). The overall model was significant (R2 = 0.28, F (12, 327) = 12.21, p < 0.001. Age strongly predicted PA (β = -2.72, p < 0.001), implies that PASE score was lower among older participants. PASE score was higher among with highest level of education (β = 31.49, p = 0.01). Being currently working predicted the PA level among study population (β = 63.75, p = 0.001). A number of comorbidities was also the strong predictor of the PASE score, (β = -22.15, p < 0.001), implies those with more comorbidities had a lower score of PASE. (Table 3)
    There was a sex difference between the score of PA that was higher among women than men (104.0 vs 65.7, p = 0.0002). PA scores was significantly higher among those younger (p < 0.001) and had high level of education (p = 0.006) in both men and women (p < 0.001). Also PA scores was significantly lower among those had one or two chronic diseases. (Table 4)
 
Table 1. Demographic characteristics among older people
% N Variable
59.1 201 60-69 Age group
30.3 103 70-79
10.6 36 80+
56.8 193 Women Sex
43.2 147 Men
51.8 176 Illiterate Education
23.2 79 Primary/Literacy
25.0 85 Diplomat+
45.9 156 Housewife Job status
41.2 140 Retired
7.9 27 In-paid work
5 17 Workless
47.6 162 No-income Income
43.8 149 Retired
8.5 29 Working
71.8 244 Non-smoking Smoking
28.2 96 Smoker
28.5 97 Less than 25 BMI
45.0 153 25-29.9
26.5 90 30+
72.1 245 Married Marital status
27.9 95 Single/divorce/widow
 
Table2. Frequency, percentage, mean, SD and Confidence Interval PA among older people
% N Level of PASE
54 184 Level 1 PASE ≤ 93
29 99 Level 2 PASE 93.1-146
11 38 Level 3 PASE 146.1-206
5 19 Level 4 PASE ≥ 206
95 % (CI) SD Mean PASE
87.30-100.73 3.41 94.02
 

Table 3. Predictors of the PA among older people
Variables β SE P- value
Age -2.72 0.47 0.001
Sex 22.54 11.00 0.04
Education level 30.49 4.16 0.01
Smoking -4.33 9.19 0.63
Job status 63.75 5.23 0.001
Comorbidity -22.15 3.88 0.001
BMI -1.44 0.76 0.85


Table 4. The mean score of PASE according to different factors by sex in elderly
Age group Overall Men Women
60-69 123.65 (72.70) 120.42 (95.90) 125.49 (55.66)
70-79 81.37 (72.13) 84.48 (94.37) 78.19 (38.85)
80 44.77 (48.03) 36.99 (48.01) 57.01 (47.15)
P-value 0.0001 0.0001 0.0001
Education
Illiterate 93.29 (66.28) 77.51 (96.62) 98.39 (52.41)
Primary/intermediate 98.91 (83.15) 89.78 (92.02) 117.53 (58.50)
Diploma& higher 124.85 (81.48) 115.80 (91.95) 138.43 (61.42)
P-value 0.006 0.016 0.0003
Occupation
Housewife 97.58 (48.13) - 97.58 (48.13)
Retired 95.09 (84.11) 82.44 (85.71) 138.68 (61.62)
Working 174.13 (106.77) 164.12 (108.45) 231.70 (85.74)
P-value 0.0006 0.0007 0.0001
BMI
Normal 92.33 (78.70) 97.81 (93.75) 83.45 (44.49).
Overweight 104.98 (76.55) 94.33 (94.37) 112.8 (59.49)
Obese 109.20 (69. 02) 90.76 (98.15) 115.17 (56.22)
P-value 0.076 0.922 0.006
Smoking*
Yes 94.96 (91.33) 90.28 (72.01) 202.73 (109.78)
No 105.45 (68.02) 103.48 (103.45) 106.02 (53.89)
P-value 0.009 0.536 0.073
Comorbidity number
0 144.98 (91.31) 147.02 (103.34) 142.13 (72.20)
1 93.22 (59.02) 64.87 (61.91) 114.21 (47.28)
2 78.89 (58.65) 56.83 (73.95) 89.81 (46.03)
P-value 0.0001 0.0001 0.0001
*only four women were smokers
 
Discussion
    The results showed that the PA of the elderly was 94.02 ± 3.41 indicating low level of activity. Several studies have shown that elderly people have sufficient PA to achieve health benefits (24, 25). In this study 54 % of older people  had sedentary lifestyle which is consistent with the findings of those studies that reported more than half of the elderly do not do PA of moderate to vigorous (10, 24). Many studies have reported that PA in the elderly is low (2, 10, 11, 13, 14, 24, 26, 27). In this study among demographic factors, age was the most predictive for PA, so that with the increase in age, PA decreased in individuals. The results were consistent with other studies (3, 10, 11, 13, 14, 24, 25, 27-30). But it did not match the results of studies conducted by Sadrollahi in Kashan and Muni in New York (2, 31) in older people, The reason for this contradiction could be attributed to differences in cultural background, In west Azerbaijan, older people are generally sitting and others respect him/her and do his/her jobs.
    Multivariate analysis showed that female elderly were more active than men in our study, which was consistent with the results of some studies (10, 15). Research conducted in rural Thailand population showed that women were 3.64 times more active than men, while in Thai families, most men were family leaders who were less likely to be active in their families, but women were doing housework, gardening, and agriculture, so the lifestyle can explain sex difference in Thailand population study (10). Therefore in the present study women were high active than men, which is inconsistent with the findings of those studies that reported reverse results inside (2, 13, 24) and outside the country (2, 3, 11, 13, 24, 25, 30, 32, 33). Several studies in Ireland have shown that gender is more important than age and employment, which has a stronger effect on the PA of the elderly (32, 33). The reasons for these differences may be explained by cultural, social, economic and living arrangement (2, 10, 24). A surprising finding was that people with a BMI over 25 were more active than those with normal BMI. While in some studies it was found no significant correlation between BMI and PA (24, 34) some researchers have proven that high body mass index reduces PA in the elderly (11, 15, 35, 36), which did not match our study outcomes. In this study, some chronic diseases reduced PA. Most studies have shown the negative impact of chronic illnesses or poor health on reducing PA (15, 24, 25, 31, 32, 34, 37). Due to the fact that having serious illnesses such as joint pain, hypertension and diabetes, it is difficult for a person to have mobility (24). Sadrollahi and co-authors showed that in Kashan older people with chronic diseases had a higher level of PA that contradicted our study results (2), They believed that diseases altered individuals' attitudes toward health issues, and when people were diagnosed with illness, sufferers tend to change their lifestyle which may increase the level of PA in the elderly (2). Also, in this study, people with higher education had more PA, which was in line with other studies that reported the high level of PA among educated people (2, 11, 24, 25, 31), the level of education can have a positive impact on PA as well as personal hobbies (2). However some studies reported the opposite results; people with higher education had less activity than those with lower education levels (14, 29, 34), this indicates that the problem is not lack of knowledge but lack of the motivation is more impressive (14). In some studies, there was no significant relationship between the level of education and PA (13, 15, 32), that may be due to the difference in type and level of activity (13, 15). Additionally, public awareness of the effect of PA seems more important than education level (15), another reason for this controversy in the results of studies might be because  of sampling  which allowed to recruit less educated individuals (13).
    Overall, it seems that PA in the elderly has  a multi-factorial nature, and a range of socio-demographic factors is involved in determining the level of individual activities (24). Studies in different parts of the world identified several factors as significant determinants and from a global perspective of behaviors of elderly individuals is relatively unpredictable (24).
 
Conclusion
    PA level in the present study was very low and the majority of participants were sedentary. The predictors of PA among urban older people in the present study were age, sex, and education level and comorbid diseases. Compared with all the variables investigated in the present study, age was more influential in predicting the PA. Therefore, interventions to increase physical activity in the elderly are necessary.
 
Study limitations
    This study had strengths as well as certain restrictions. As strengths, the samples were recruited from the SIB so, the sample may be considered as a representative of the older people in the city, also a right level of coverage for all the elder from the high- and medium-class groups in Maku was ensured. As a limitation of the study, monthly income as a significant indicator for the economic status of the participants was not investigated.
 
Conflict of interest
    The authors declare that they have no conflict of interest.
 
Acknowledgment
    The authors are most grateful for the collaboration by the participants and staffs of health care centers in Maku, Iran.
 
Author's contributions
    FB (corresponding author) was involved in the conception of the study, interpreted the results from the analyses. BA and NA performed data collection and the analyses and drafted the manuscript. FB was involved in the conception of the study, interpreted the results from the analyses, performed significant revisions, assisted in the revision of the manuscript and approved the final version of the manuscript. FB assisted in statistical analysis and interpretation and revision of the article
 
References
1.Khazaee-Pool M, Sadeghi R, Majlessi F, Rahimi Foroushani A. Effects of physical exercise programme on happiness among older people. Journal of psychiatric and mental health nursing. 2015; 22(1): 47-57.
2. Sadrollahi A, Hosseinian M, Alavi NM, Khalili Z, Esalatmanesh S. Physical activity patterns in the elderly kashan population. Iranian Red Crescent Medical Journal. 2016; 18(6): 1-8.
3. Sun F, Norman IJ, While AE. Physical activity in older people: a systematic review. BioMed Central Public Health. 2013; 13(449): 1-17.
4. Chodzko-Zajko WJ, Proctor DN, Singh MAF, Minson CT, Nigg CR, Salem GJ, et al. Exercise and physical activity for older adults. Medicine & Science in Sports & Exercise. 2009; 41(7): 1510-30.
5. Moran M, Van Cauwenberg J, Hercky-Linnewiel R, Cerin E, Deforche B, Plaut P. Understanding the relationships between the physical environment and physical activity in older adults: a systematic review of qualitative studies. International Journal of Behavioral Nutrition and Physical Activity. 2014; 11(79): 1-12.
6. Pan SY, Cameron C, DesMeules M, Morrison H, Craig CL, Jiang X. Individual, social, environmental, and physical environmental correlates with physical activity among Canadians: a cross-sectional study. BioMed Central Public Health. 2009; 9(21): 1-12.
7.Yi X, Pope Z, Gao Z, Wang S, Pan F, Yan J, et al. Associations between individual and environmental factors and habitual physical activity among older Chinese adults: A social–ecological perspective. Journal of Sport and Health Science. 2016; 5(3): 315-21.
8.  Ishii K, Shibata A, Oka K. Environmental, psychological, and social influences on physical activity among Japanese adults: structural equation modeling analysis. International Journal of Behavioral Nutrition and Physical Activity. 2010; 7(61): 1-8.
9. Gellert P, Witham MD, Crombie IK, Donnan PT, McMurdo ME, Sniehotta FF. The role of perceived barriers and objectively measured physical activity in adults aged 65–100. Age and Ageing. 2015;44(3):384-90.
10.Ethisan P, Somrongthong R, Ahmed J, Kumar R, Chapman RS. Factors related to physical activity among the elderly population in rural thailand. Journal Prim Care Community Health. 2017; 8(2): 71-6.
11.Florindo AA, Hallal PC, Moura ECd, Malta DC. Practice of physical activities and associated factors in adults, Brazil, 2006. Revista de Saude Publica. 2009; 43: 65-73.
12.Statistical Center of Iran. Selection of the results of the Population and Housing Census [Internet]. Iran: Statistical Center of Iran: 2012. Available from: http://www.amar.org.ir/
13.Eshaghi SR, Shahsanai A, Ardakani MM. Assessment of the Physical Activity of Elderly Population of Isfahan, Iran. Journal of Isfahan Medical School. 2011; 29(147): 939-46. [Persian]
14.Motefaker M, Sadrbafghi MS, Rafiee M, Bahadorzadeh L, Namayandeh SM, Karimi M, et al. Suicepidemiology of physical activity: a population based study in Yazd cityide attempt and its relation to stressors and supportive systems: a study in Karaj city. Tehran University Medical Journal. 2007; 65(4): 77-81. [Persian]
15.Salehi L, Tagdisi MH, Gasemi H, Shekarvash B. To identify the facilitator and barrier factors of physical activity among elderly people in Tehran. Iranian Journal of Epidemiology. 2010; 6(2): 7-15. [Persian]
16.Borji M, Motaghi M. The relationship between physical activity, social support and Fatigue Severity of elderly Ilam in 2016. Iran Journal Rehabilitation Research in Nursing. 2017; 3(4): 50-7. [Persian]
17. Fisher KL, Harrison EL, Bruner BG, Lawson JA, Reeder BA, Ashworth NL, et al. Predictors of physical activity levels in community-dwelling older adults: a multivariate approach based on a socio-ecological framework. Journal of Aging and Physical Activity. 2018; 26(1): 114-20.
18.Bakhtri Aghdam F, Baghiani Moghaddam MH, Asghari Jafarabadi M, Allahverdipour H, Dabagh Nikookheslat S, Noorizadeh R. Explaining the role of personal, social and physical environment factors on employed women's physical activity: a structural equation analysis. Global Journal of Health Science. 2013; 5(4): 189-99.
19.Bakhtari Aghdam F, Sahranavard H, Jahangiry L, Asghari M. The effect of a physical activity intervention on sedentary behavior in female teachers: a randomized, controlled trial. Health Scope. 2016; 7(1): 1-8.
20.Washburn RA, Smith KW, Jette AM, Janney CA. The physical activity scale for the elderly (PASE): development and evaluation. Journal of Clinical Epidemiology. 1993; 46(2): 153-62.
21. Dunlop DD, Song J, Semanik PA, Sharma L, Chang RW. Physical activity levels and functional performance in the osteoarthritis initiative: a graded relationship. Arthritis & Rheumatism. 2011; 63(1): 127-36.
22. Alqarni AM, Vennu V, Alshammari SA, Bindawas SM. cross-cultural adaptation and validation of the arabic version of the physical activity scale for the elderly among community-dwelling older adults in saudi Arabia. Clinical Interventions in Aging. 2018; 13: 419-27.
23.Ishaghi R, Mahmoudian SA, Asgarian R, Sohrabi A. Effect of faith-based education on physical activity on the elderly. Iranian Journal of Medical Education. 2011; 10(5): 1281-8. [Persian]
24.Shiraly R, Shayan Z, Keshtkar V, Hamed M. Self-reported factors associated with engagement in moderate to vigorous physical activity among elderly people: a population-based study. International Journal of Preventive Medicine. 2017; 8(26).
25.Souza AM, Fillenbaum GG, Blay SL. Prevalence and correlates of physical inactivity among older adults in Rio grande do Sul, Brazil. PloS One. 2015; 10(2).
26. Imani A, Dastgiri  S, Azizi A. Population aging and burden of diseases ( review study). Health Image. 2015; 6(2): 54-61. [Persian]
27.Momenan A, Delshad M, Mirmiran P, Ghanbarian A, Safarkhani M, Azizi F. Physical inactivity and related factors in an adult Tehranian population (Tehran lipid and glucose study). Iranian Journal of Endocrinology and Metabolism. 2012; 13(5): 493-503. [Persian]
28. Layne AS, Hsu F-C, Blair SN, Chen S-H, Dungan J, Fielding RA, et al. Predictors of change in physical function in older adults in response to long-term, structured physical activity: the life study. Archives of physical medicine and rehabilitation. 2017;98(1):11-24.
29.Mourao AR, Novais FV, Andreoni S, Ramos LR. Physical activity in the older adults related to commuting and leisure, Maceió, Brazil. Revista de Saude Publica. 2013; 47(6): 1112-22.
30. Vagetti GC, Barbosa Filho VC, Moreira NB, de Oliveira V, Mazzardo O, de Campos W. The prevalence and correlates of meeting the current physical activity for health guidelines in older people: a cross-sectional study in Brazilian women. Archives of Gerontology and Geriatrics. 2013; 56(3): 492-500.
31.Mooney SJ, Joshi S, Cerdá M, Quinn JW, Beard JR, Kennedy GJ, et al. Patterns of physical activity among older adults in New York City: a latent class approach. American Journal of Preventive Medicine. 2015; 49(3): 13-22.
32. Murtagh EM, Murphy MH, Murphy NM, Woods C, Nevill AM, Lane A. Prevalence and correlates of physical inactivity in community-dwelling older adults in Ireland. PloS One. 2015; 10(2): e0118293.
32. McKee G, Kearney PM, Kenny RA. The factors associated with self-reported physical activity in older adults living in the community. Age and Ageing. 2015; 44(4): 586-92.
33.  McKee G, Kearney PM, Kenny RA. The factors associated with self-reported physical activity in older adults living in the community. Age and Ageing. 2015; 44(4): 586-92.
34.Shaw BA, Spokane LS. Examining the association between education level and physical activity changes during early old age. Journal of Aging and Health. 2008; 20(7): 767-87.
35.Jenkins KR, Fultz NH. The relationship of older adults' activities and body mass index. Journal of Aging and Health. 2008; 20(2): 217-34.
36.Nicklas BJ, Beavers DP, Mihalko SL, Miller GD, Loeser RF, Messier SP. Relationship of objectively-measured habitual physical activity to chronic inflammation and fatigue in middle-aged and older adults. The Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences. 2016; 71(11): 1437-43.
37.  Moschny A, Platen P, Klaassen-Mielke R, Trampisch U, Hinrichs T. Barriers to physical activity in older adults in Germany: a cross-sectional study. The International Journal of Behavioral Nutrition and Physical Activity. 2011; 8(1): 121.
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
Type of Study: Research | Subject: General
Received: 2018/06/17 | Accepted: 2018/12/18 | Published: 2018/12/29

References
1. Khazaee-Pool M, Sadeghi R, Majlessi F, Rahimi Foroushani A. Effects of physical exercise programme on happiness among older people. Journal of psychiatric and mental health nursing. 2015; 22(1): 47-57.
2. Sadrollahi A, Hosseinian M, Alavi NM, Khalili Z, Esalatmanesh S. Physical activity patterns in the elderly kashan population. Iranian Red Crescent Medical Journal. 2016; 18(6): 1-8.
3. Sun F, Norman IJ, While AE. Physical activity in older people: a systematic review. BioMed Central Public Health. 2013; 13(449): 1-17.
4. Chodzko-Zajko WJ, Proctor DN, Singh MAF, Minson CT, Nigg CR, Salem GJ, et al. Exercise and physical activity for older adults. Medicine & Science in Sports & Exercise. 2009; 41(7): 1510-30.
5. Moran M, Van Cauwenberg J, Hercky-Linnewiel R, Cerin E, Deforche B, Plaut P. Understanding the relationships between the physical environment and physical activity in older adults: a systematic review of qualitative studies. International Journal of Behavioral Nutrition and Physical Activity. 2014; 11(79): 1-12.
6. Pan SY, Cameron C, DesMeules M, Morrison H, Craig CL, Jiang X. Individual, social, environmental, and physical environmental correlates with physical activity among Canadians: a cross-sectional study. BioMed Central Public Health. 2009; 9(21): 1-12.
7. Yi X, Pope Z, Gao Z, Wang S, Pan F, Yan J, et al. Associations between individual and environmental factors and habitual physical activity among older Chinese adults: A social–ecological perspective. Journal of Sport and Health Science. 2016; 5(3): 315-21.
8. Ishii K, Shibata A, Oka K. Environmental, psychological, and social influences on physical activity among Japanese adults: structural equation modeling analysis. International Journal of Behavioral Nutrition and Physical Activity. 2010; 7(61): 1-8.
9. Gellert P, Witham MD, Crombie IK, Donnan PT, McMurdo ME, Sniehotta FF. The role of perceived barriers and objectively measured physical activity in adults aged 65–100. Age and Ageing. 2015;44(3):384-90.
10. Ethisan P, Somrongthong R, Ahmed J, Kumar R, Chapman RS. Factors related to physical activity among the elderly population in rural thailand. Journal Prim Care Community Health. 2017; 8(2): 71-6.
11. Florindo AA, Hallal PC, Moura ECd, Malta DC. Practice of physical activities and associated factors in adults, Brazil, 2006. Revista de Saude Publica. 2009; 43: 65-73.
12. Statistical Center of Iran. Selection of the results of the Population and Housing Census [Internet]. Iran: Statistical Center of Iran: 2012. Available from: http://www.amar.org.ir/
13. Eshaghi SR, Shahsanai A, Ardakani MM. Assessment of the Physical Activity of Elderly Population of Isfahan, Iran. Journal of Isfahan Medical School. 2011; 29(147): 939-46. [Persian]
14. Motefaker M, Sadrbafghi MS, Rafiee M, Bahadorzadeh L, Namayandeh SM, Karimi M, et al. Suicepidemiology of physical activity: a population based study in Yazd cityide attempt and its relation to stressors and supportive systems: a study in Karaj city. Tehran University Medical Journal. 2007; 65(4): 77-81. [Persian]
15. Salehi L, Tagdisi MH, Gasemi H, Shekarvash B. To identify the facilitator and barrier factors of physical activity among elderly people in Tehran. Iranian Journal of Epidemiology. 2010; 6(2): 7-15. [Persian]
16. Borji M, Motaghi M. The relationship between physical activity, social support and Fatigue Severity of elderly Ilam in 2016. Iran Journal Rehabilitation Research in Nursing. 2017; 3(4): 50-7. [Persian]
17. Fisher KL, Harrison EL, Bruner BG, Lawson JA, Reeder BA, Ashworth NL, et al. Predictors of physical activity levels in community-dwelling older adults: a multivariate approach based on a socio-ecological framework. Journal of Aging and Physical Activity. 2018; 26(1): 114-20.
18. Bakhtri Aghdam F, Baghiani Moghaddam MH, Asghari Jafarabadi M, Allahverdipour H, Dabagh Nikookheslat S, Noorizadeh R. Explaining the role of personal, social and physical environment factors on employed women's physical activity: a structural equation analysis. Global Journal of Health Science. 2013; 5(4): 189-99.
19. Bakhtari Aghdam F, Sahranavard H, Jahangiry L, Asghari M. The effect of a physical activity intervention on sedentary behavior in female teachers: a randomized, controlled trial. Health Scope. 2016; 7(1): 1-8.
20. Washburn RA, Smith KW, Jette AM, Janney CA. The physical activity scale for the elderly (PASE): development and evaluation. Journal of Clinical Epidemiology. 1993; 46(2): 153-62.
21. Dunlop DD, Song J, Semanik PA, Sharma L, Chang RW. Physical activity levels and functional performance in the osteoarthritis initiative: a graded relationship. Arthritis & Rheumatism. 2011; 63(1): 127-36.
22. Alqarni AM, Vennu V, Alshammari SA, Bindawas SM. cross-cultural adaptation and validation of the arabic version of the physical activity scale for the elderly among community-dwelling older adults in saudi Arabia. Clinical Interventions in Aging. 2018; 13: 419-27.
23. Ishaghi R, Mahmoudian SA, Asgarian R, Sohrabi A. Effect of faith-based education on physical activity on the elderly. Iranian Journal of Medical Education. 2011; 10(5): 1281-8. [Persian]
24. Shiraly R, Shayan Z, Keshtkar V, Hamed M. Self-reported factors associated with engagement in moderate to vigorous physical activity among elderly people: a population-based study. International Journal of Preventive Medicine. 2017; 8(26).
25. Souza AM, Fillenbaum GG, Blay SL. Prevalence and correlates of physical inactivity among older adults in Rio grande do Sul, Brazil. PloS One. 2015; 10(2).
26. Imani A, Dastgiri S, Azizi A. Population aging and burden of diseases ( review study). Health Image. 2015; 6(2): 54-61. [Persian]
27. Momenan A, Delshad M, Mirmiran P, Ghanbarian A, Safarkhani M, Azizi F. Physical inactivity and related factors in an adult Tehranian population (Tehran lipid and glucose study). Iranian Journal of Endocrinology and Metabolism. 2012; 13(5): 493-503. [Persian]
28. Layne AS, Hsu F-C, Blair SN, Chen S-H, Dungan J, Fielding RA, et al. Predictors of change in physical function in older adults in response to long-term, structured physical activity: the life study. Archives of physical medicine and rehabilitation. 2017;98(1):11-24.
29. 29. Mourao AR, Novais FV, Andreoni S, Ramos LR. Physical activity in the older adults related to commuting and leisure, Maceió, Brazil. Revista de Saude Publica. 2013; 47(6): 1112-22.
30. 30. Vagetti GC, Barbosa Filho VC, Moreira NB, de Oliveira V, Mazzardo O, de Campos W. The prevalence and correlates of meeting the current physical activity for health guidelines in older people: a cross-sectional study in Brazilian women. Archives of Gerontology and Geriatrics. 2013; 56(3): 492-500.
31. 31. Mooney SJ, Joshi S, Cerdá M, Quinn JW, Beard JR, Kennedy GJ, et al. Patterns of physical activity among older adults in New York City: a latent class approach. American Journal of Preventive Medicine. 2015; 49(3): 13-22.
32. Murtagh EM, Murphy MH, Murphy NM, Woods C, Nevill AM, Lane A. Prevalence and correlates of physical inactivity in community-dwelling older adults in Ireland. PloS One. 2015; 10(2): e0118293.
33. McKee G, Kearney PM, Kenny RA. The factors associated with self-reported physical activity in older adults living in the community. Age and Ageing. 2015; 44(4): 586-92.
34. Shaw BA, Spokane LS. Examining the association between education level and physical activity changes during early old age. Journal of Aging and Health. 2008; 20(7): 767-87.
35. Jenkins KR, Fultz NH. The relationship of older adults' activities and body mass index. Journal of Aging and Health. 2008; 20(2): 217-34.
36. Nicklas BJ, Beavers DP, Mihalko SL, Miller GD, Loeser RF, Messier SP. Relationship of objectively-measured habitual physical activity to chronic inflammation and fatigue in middle-aged and older adults. The Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences. 2016; 71(11): 1437-43.
37. Moschny A, Platen P, Klaassen-Mielke R, Trampisch U, Hinrichs T. Barriers to physical activity in older adults in Germany: a cross-sectional study. The International Journal of Behavioral Nutrition and Physical Activity. 2011; 8(1): 121.

Add your comments about this article : Your username or Email:
CAPTCHA code

Send email to the article author


© 2019 All Rights Reserved | Elderly Health Journal

Designed & Developed by : Yektaweb