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Motives to practice exercise in old age and successful aging: A latent class analysis
Archives of Gerontology and Geriatrics 77 (2018) 44–50
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Motives to practice exercise in old age and successful aging: A latent class analysis
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Melchor Gutiérreza, , Pablo Calatayudb, José-Manuel Tomásb a b
Department of Educational and Developmental Psychology, Faculty of Psychology, University of Valencia, Av. Blasco Ibáñez, 21, 46010 Valencia, Spain Department of Methodology for the Behavioral Sciences, Faculty of Psychology, University of Valencia, Av. Blasco Ibáñez, 21, 46010 Valencia, Spain
A R T I C LE I N FO
A B S T R A C T
Keywords: Life satisfaction Perceived health Physical activity Spirituality Functional performance Gerotranscendence
Purpose: The aim was to classify motives for exercising trying to find sets of related cases that share common motivations, and to relate these latent classes to markers of successful aging. Methods: 725 old adult aged 55 to 97 years were sampled in several Spanish towns. Instruments: Successful Aging Inventory (SAI), International Physical Activity Questionnaire (IPAQ), Health Survey SF-8, Satisfaction with Life Scale (SWLS), and motives to practice exercise, were used. Latent Class Analyses (LCAs) were estimated. The classes obtained were compared on markers of successful aging. Results: Three latent classes were deemed optimal. Significant differences for several markers of successful aging were found. Conclusion: A main conclusion derived from the results is that not all old people do exercise for the same motives, and the class of motives you are in had an impact/relation on markers of successful aging. Motives related to internal rather than external pressures should be promoted in the old age.
1. Introduction As Barber, Forster, and Birch (2015) stated, life expectancy has increased dramatically over the last century, leading to changes in the world’s demography. It is predicted that by the year 2050, about 2 billion people, accounting for 20% of the global population, will be 60 years or older (OMS, 2015; United Nations, Department of Economic & Social Affairs, 2012). This has generated, among other things, a growing interest focused on successful aging factors for obtaining a healthy and happy life in old age and in an aging society (Paskulin, Vianna, & Molzahn, 2009; Pinto, Fontaine, & Neri, 2016). Many authors affirm that one of the most important non-pharmaceutical ways towards healthy aging is exercise (Müller, Ansari, Ebrahim, & Khoo, 2016; Södergren, 2013; Van Alphen, Hortobágyi, & van Heuvelen, 2016). There is evidence that high levels of physical functioning are fundamentally important to healthy aging, and participation in exercise is a strong predictor of aging well (Kolt, Driver, & Giles, 2004). Exercise can act as a health protective factor among older individuals. Regular participation in exercise can decrease the occurrence of diseases, falls, and disability as well as improve independence (Young & Dinan, 2005). Furthermore, regular exercise not only has many physical benefits but can also contribute to psychological wellbeing among older adults (Chung, Zhao, Liu, & Quach, 2017; Ferrand,
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Nasarre, Hautier, & Bonnefoy, 2012; Fox, Stathi, McKenna, & Davis, 2007; Kolt et al., 2004). Despite the physical and psychological health benefits of exercise, many old people do not exercise enough to gain health benefits (Patel, Schofield, Kolt, & Keogh, 2013; Schutzer & Graves, 2004). Therefore, knowing the motives why old people exercise, as well as barriers that limit them such practices, has become a target of interest for research (Biedenweg et al., 2014; Kolt, Chadha, Giles, & Driver, 2002; Patel et al., 2013; Stephan, Boiché, & Le Scanff, 2010; Stubbs et al., 2014; Victor et al., 2016). In the older population, barriers and motivators often intertwine, making it difficult to isolate factors specific to this cohort (Schutzer & Graves, 2004; Van Alphen et al., 2016). Kolt et al. (2004), investigating the motives for practicing exercise in a sample of Australian older adults, found that the predominant reasons reported related to health, fitness, enjoyment of the activity, and relaxation. In this study, women rated medical, social, and involvement reasons as significantly more important than did their male counterparts. More recently, Patel et al. (2013) carried out a study with the aim to identify perceived barriers, benefits, and motives for exercising in a sample of people 65 years old or older. They found that the main motives for participation in exercise were: being active for enjoyment reasons; being active for health and medical reasons; and engaged in exercise for the purpose of wanting to be physically active. The
Corresponding author. E-mail addresses: [email protected] (M. Gutiérrez), [email protected] (P. Calatayud), [email protected] (J.-M. Tomás).
https://doi.org/10.1016/j.archger.2018.04.003 Received 10 November 2016; Received in revised form 23 March 2018; Accepted 5 April 2018 Available online 12 April 2018 0167-4943/ © 2018 Published by Elsevier B.V.
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a) to elaborate a classification of motives for exercising trying to find sets of related cases (latent classes) that share common motivations using latent class analysis; b) to relate these latent classes to markers of successful aging. Specifically several hypotheses were raised:
benefits of exercise participation were: personal benefits (like selfconfidence), and physical benefits (like feeling fitter). As barriers to participation in exercise, they identified three factors: personal barriers (like lack of motivation); perceptual barriers (like feeling too old to be physically active); and time constraints (for example, family responsibilities). Cleland et al. (2015) explored the environmental factors that act as barriers or facilitators to exercise participation among rural adults, and found four key themes: functionality, diversity, spaces and places for all, and realistic expectations. In the study carried out by Patay, Patton and Parker (2015), four main categories emerged: (a) acknowledgment and knowledge of exercise, (b) environmental factors, (c) cultural aspects, and (d) social aspects of exercise. Many researchers agree that it is vital to ensure that the population ages healthily and that longevity is accompanied by better quality of life (Rennemark, Lindwall, Halling, & Berglund, 2009; Troutman, Nies, Small, & Bates, 2011). Reyna, Castruita, Zamarripa, Gurrola, and Valtier (2016) concluded that self-efficacy and perceived benefits of exercise were positively associated with the level of physical activity. What is successful aging? Rowe and Kahn (1987, 1998) defined successful aging as the avoidance of disease and disability, maintenance of physical and cognitive function, and engagement in social and productive activities. Later, Crowther, Parker, Achenbaum, Larimore, and Koenig (2002) added a fourth component, spirituality. The most commonly proposed definition of successful aging has been satisfaction with one’s life (Bowling & Dieppe, 2005). From an initial approach with a purely biomedical perspective, the focus has been changing towards a more holistic vision, attending to more subjective aspects of the aging process (Pruchno, Wilson-Genderson, & Cartwright, 2010). There are multidimensional theories of successful aging that propose components of both biomedical and psychosocial theories (Bowling & Dieppe, 2005). Psychosocial models emphasize aspects like life satisfaction, well-being, social engagement, or personal resources (Cosco, Prinq, Perales, Stephan, & Brayne, 2014). Troutman and Staples (2014) have studied the interpretation of successful aging from the viewpoint of older adults raising the question: What does successful aging mean to you? Eight broad themes emerged: active independence, relationships with people, relationship with God, comfort resources, health, beneficial contribution, positive perspective/coping, and freedom. Further, Troutman and Staples (2014) referred that, derived from the content analysis, the literature have supported six headings of successful aging: health; independence, the construct of active engagement; connectedness; attitude, adaptability, and coping; sense of purpose; and appropriate resources. A few years earlier, Troutman et al. (2011) created an instrument to measure successful aging, and they found four dimensions: functional performance mechanisms; intrapsychic factors, spirituality, and gerotranscendence. Lee, Lan and Yen (2011) proposed a model of successful aging composed by four factors: physical, psychological, social, and leisure. As literature has shown, in addition to exercise, other important variables have been related along the time to aging successfully, as perceived health and life satisfaction (Hilton, Gonzalez, Saleh, Maitoza, & Anngela-Cole, 2012; Troutman et al., 2011). Li et al. (2014) suggested that self-reported health measures may be the most appropriate measures for comparing cross-national differences in successful aging. They found that successfully aging old people had significantly more favorable health status than those who were not successful. Physical functioning is one aspect of health-related quality of life and it is often considered a component of successful aging (Cené et al., 2016). In the same vein, life satisfaction has been identified as an indicator of successful aging (Troutman et al., 2011). Rowe and Kahn (1998) stated that successful aging involves individuals’ physical health, psychological well-being, and social engagement with life. According to Feng, Son, and Zeng (2015), successful agers are those who are free from major illnesses and disabilities, having no depressive symptoms, participating in social or productive activities, and being satisfied with life. Based on the above mentioned, the aim of this research was twofold:
a) There will be, at least, three latent classes among the motives to practice exercise: medical or health reasons, fitness, and to socialize (having social relationships). b) Medical or health class will have lowers levels of successful aging as measured in the four dimensions of the Successful Aging InventorySAI (functional performance, intrapsychic factors, spirituality, and gerotranscendence) compared to the other two classes. c) Fitness class will have higher levels of exercise, given that fit is an intrinsic motivation d) Medical or health class will have lower levels of perceived health and life satisfaction. 2. Methods 2.1. Participants The sample under study consisted of 725 older adults aged 55 to 97 years (M = 68.28; SD = 8.62), 478 were women (66%) and 247 men (34%). The sample was collected in three areas: sport centers, day centers, and public areas of several Spanish towns. 2.2. Instruments (a) To measure successful aging, the Successful Aging Inventory (SAI; Troutman et al., 2011) was used. The scale is a 20-item instrument with four dimensions: Functional performance, Intrapsychic factors, Spirituality, and Gerotranscendence. Example items of each factor are: I have been able to cope with the changes that have occurred to my body as I have aged; I am in a positive, pleasant mood; I spend time in prayer or doing some kind of religious activity; I feel interest in/concern for the next generation. Internal consistencies for the four dimensions were respectively, 0.62, 0.87, 0.80 and 0.81. A 5point response scale was adopted, from (1) strongly disagree to (5) strongly agree. (b) The short form of the International Physical Activity Questionnaire (IPAQ; Craig et al., 2003) referred to the last 7 days. It is an indicator of time spent per week on different intensities of physical activity (vigorous, moderate, walking…). Physical activity was converted into metabolic equivalents (METs), according to the conversion factors applied in IPAQ. (c) To examine the health perception of old people, the SF-8 Health Survey (Ware, Kosinski, Dewey, & Gandek, 2001) was used. This scale has eight items that assess health related quality of life, as perceived within the last month. Examples of items are: How much energy have you had?, How many physical pains have you had?, or How much have you been bothered by emotional problems? Participants could answer in a Likert-type scale from (1) none or nothing to (5) much or many. Internal consistency estimate was 0.75. (d) Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985). This scale is composed of five items assessing global life satisfaction, ranging from (1) totally disagree to (5) totally agree. Example items are: In most ways my life is close to my ideal; If I could live my life over, I would change almost nothing. Reliability was 0.86. (e) The checklist of motives to practice exercise was developed ad hoc for the research purposes. Several scales and questionnaires existed to tap motives for exercising and related aspects such as barriers and benefits. Among them the Participation Motivation Questionnaire for Older Adults (PMQOA; Kirkby, Kolt, & Habel, 1998; Kirkby, Kolt, Habel, & Adams, 1999) with 31 items or the 45
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participants based on these classes were compared on several markers or indicators of successful aging. These comparisons were performed with Multivariate Analyses of Variance (MANOVA) and Analysis of Variance (ANOVA) tests. MANOVA was used to test the main effect of group on the four dimensions in the SAI questionnaire. MANOVA tests the differences in the centroid (vector) of means of the multiple dependents, for various categories of the independent or independents. Among the available multivariate criteria to test for effects, Pillai’s criterion was used because it is the most robust to violations of the underlying assumptions (Tabachnick & Fidell, 2007). If the overall Ftest showed the centroid (vector) of means of the dependent variables was not the same for all the groups formed by the categories of the independent variables, post-hoc univariate F-tests of group differences were used to determine which group means differ significantly from others. ANOVAs were used to test for mean differences among the three groups in amount of physical activity (IPAQ), perceived health and life satisfaction. Subsequently, pairwise multiple comparison tests tested each pair of groups to identify similarities and differences. Additionally to the tests of effects, effect sizes (partial eta-squares) were estimated, and Cohen’s guidelines to interpret the magnitude of the effects were employed: 0.02, 0.13 and 0.26 for small, medium, and large effects, respectively (Cohen, 1992). All these additional statistical analyses were performed in SPSS 22.
Exercise Motivation Inventory (EMI-2) by Kilpatrick, Hebert and Bartholomew (2005) with 51 items. Also Patel et al. (2013) studied the main motives to practice exercise in the old people and found four main motives. With all these scales in mind a checklist of main motives was summarized that included six of them: (a) medical advice (Kolt et al., 2004, Kirkby et al., 1999, Patel et al., 2013); (b) fun (Kolt et al., 2004, Patel et al., 2013); (c) weight loss (Kolt et al., 2004, Patel et al., 2013); (d) leisure (Kolt et al., 2004); keep fit (Kolt et al., 2004); (f) relations with other people (Kolt et al., 2004, Kirkby et al., 1999); (g) Others (to be specified). The checklist started with the statement “I practice exercise for…” and then the six motives were presented with a yes/no response format. Although being a very short and simple checklist, it was used because of a trade-off between the number of constructs the survey had to include and the limited time we had to interview the old people. Nevertheless, simple indicators of complex constructs have been shown to perform well in surveys with old people (among others: Maher et al., 2013; Zullig, Valois, Huebner & Drane, 2005). 2.3. Procedure The first step was to apply for the appropriate permissions to the municipalities of different Spanish towns and managers of the centers needed to conduct this investigation. Then, we contacted the instructors and staff in the sports facilities and day centers to coordinate the survey, explain the research and ask for assistance. For people interviewed on the street, only their permission and collaboration was needed. Finally, the survey was implemented. Given the nature of the research (a survey in centers and/or street with interviewers), it was crucial to keep the survey length at a minimum. Therefore, very short scales and indicators were chosen for all the constructs in the survey. The average time needed to answer the survey was about 10 min.
3. Results 3.1. Motives for exercising: a latent class analysis Descriptive statistics were calculated within the sample to determine current motives to exercise. These frequencies showed that 22% of the participants did exercise because of medical recommendation, 33.9% did exercise to have fun, 8.2% for weight loss, 81% to keep fit, and finally 40.5% of the old people did practice exercise in order to establish social relations. To determine the optimal number of classes, models evaluating the relative fit of 1–4 class solutions were run. Better solution was chosen based on a smaller Bayesian Information Criterion (BIC) value, a smaller sample size-adjusted BIC value, a smaller Akaike Information Criterion value, a higher entropy value, and significant Lo–Mendell–Rubin (LMR) and bootstrapped likelihood ratio (LR) tests. LMR and LR tests compare a solution with k classes vs. the solution with k-1 classes. Additionally, interpretability of the results was also considered. Statistical criteria and tests are shown in Table 1. In light of the results of statistical criteria, a three latent classes solution was deemed optimal. The three information criteria (BIC, ABIC and AIC) for this solution were lower than those in the other solutions. When LMR and LR test were conducted, the three latent classes solution was significantly better than the two latent classes solution, whereas the four latent class solution was not better than the three latent class solution. The only criterion in which the solution with three latent classes may be considered worse was the index of entropy. Therefore, we turned to interpretability and retained the three latent classes solution. The probabilities for most likely latent class membership were good for the three classes (class one = .84; class two = .81; class three = .95).
2.4. Statistical analyses Latent Class Analyses (LCAs) were estimated in Mplus 8 (Muthén & Muthén, 1998-2017Muthén & Muthén, 1998-2017). LCA is a person centered (cluster type) method that seeks for subgroups of observations with similar response patterns as regards the variables of interest in order to maximize the between-group heterogeneity and within-group homogeneity (Nylund, Asparouhov, & Muthén, 2007). LCA may be used to test a theory on a certain number and type of classes, or it can be used in an exploratory way, as it is the case in this research. The number of classes retained is based on several statistical criteria: Information criteria as the Bayesian Information Criteria (BIC), sample size—adjusted BIC (ABIC), and Akaike Information Criterion (AIC), with smaller values indicating better fit; entropy values (from 0 to 1 = perfect fit); and significant Lo–Mendell–Rubin (LMR) and bootstrapped likelihood ratio (LR) tests to compare one model against the model with one class less. Beyond the aforementioned statistical criteria, the selection of the number of classes is very subjective and requires theoretical and/or practical justifications. Therefore, interpretability of the results was also considered, as advised by Lukociené, Varriale, and Vermunt (2010). Once the number of latent classes was determined, the groups of Table 1 Fit indices of latent class analyses of motives to practice exercise. # classes
LR
AIC
BIC
ABIC
Entropy
LMR test
p
BLR test
p
1 2 3 4
228.81 126.12 81.56 65.11
2979.03 2890.34 2857.78 2857.33
3004.33 2945.15 2944.11 2971.18
2985.29 2903.89 2880.63 2885.48
1 0.87 0.65 0.77
NA 100.38 43.46 16.44
NA < .001 < .01 =.08
NA 102.69 44.56 16.44
NA < .001 < .001 =.07
Note: LR = Log-likelihood ratio; AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; ABIC = Adjusted BIC; LMR = Lo-Mendell-Rubin test; BLR = Bootstrapped Log-likelihood Ratio; NA = Non applicable. 46
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Fig. 1. Latent classes and their probabilities in the different categories.
Between subjects ANOVAs were also performed to test for mean differences in the amount of physical activity measured with the IPAQ, health perception and life satisfaction. Means and standard deviations for these three variables, in the three groups, are presented in Table 2. The first ANOVA found no statistically significant differences among the means of the three latent classes in amount of physical activity (F (2498) = 2.127; p = .12; η2 = .008). The ANOVA testing for differences in perceived health was statistically significant (F (2498) = 28.047; p < .001; η2 = .101). The post-hoc tests found that perceived health was higher for those exercising as a leisure activity or to keep fit versus those practicing exercise because of medical advice. Finally, in the third ANOVA on life satisfaction, there also were statistically significant differences among the three groups (F (2498) = 8.243; p < .001; η2 = .032). Pairwise comparisons found that people who exercise for leisure were more satisfied than those that exercise to keep fit or for medical advice.
A look at Fig. 1 aids to interpret the three classes solution. Class one grouped the participants with high probabilities to exercise due to fit reasons but also for socializing and to have fun. We labeled this class as leisure/sports. Class two was formed by participants only interested in keeping physical fit. Finally, class three comprised those that exercise following medical advice, and with also some probability to do it for weight loss. 43.6% of the subjects were classified in latent class one, 47.2% in class two and a 9.2% in class 3.
3.2. Relationships among motives for exercising and markers of successful ageing Group (or latent class) membership according to the results in the LCA analysis, was used to test for mean differences in some important markers of successful aging. Among them, the four dimensions in the SAI. A MANOVA was performed to test for mean differences in the linear combination of the four dimensions of successful aging, and mean differences were statistically significant (F (8, 992) = 4.376; p < .001; η2 = .034). In order to separately test for differences in the means of the four dimensions, follow-up ANOVAs were performed. These ANOVAS found significant differences for functional performance (F (2, 498) = 7.150; p = .001; η2 = .028), intrapsychic mechanism (F (2, 498) = 8.874; p < .001; η2 = .034), and gerotranscendence (F (2, 498) = 10.805; p < .001; η2 = .042), but non-significant differences for spirituality (F (2, 498) = .252; p = .777; η2 = .001). Means and standard deviations for the three latent classes in the four dimensions are shown in Table 2. Pairwise tests showed that those who practice for leisure or to keep fit had more functional performance than those who exercise for medical advice. Mean differences tests in intrapsychic mechanism also found larger means for those who exercise for leisure compared to those who want to be fit and the lowest mean was the one of those exercising for medical recommendation, and that pattern also hold for the dimension of gerotranscendence.
4. Discussion This study is grounded on the basis of the progressive aging of world’s population in the last century, and that many of this old people do not practice enough exercise for having a healthy aging. The aim of this study was to elaborate a classification of motives for exercising trying to find sets of related cases that share common motivations using latent class analysis, and to relate these latent classes to several markers of successful aging. It was hypothesized that there would be, at least, three latent classes among the motives to practice exercise. According to results shown in Table 1 and Fig. 1, three latent classes were obtained: class one that grouped the participants to exercise for leisure/sports, class two formed by participants who exercise to keep fit, and class three comprised by those who practice exercise for medical advice. These results partially satisfy the compliance with the first hypothesis and are in line with
Table 2 Means and standard deviations (SD) by latent class. Class 2 Keep fit
Class 1 Leisure/sports Markers of successful aging Functional performance Intrapsychic mechanism Gerotranscendence Spirituality Physical activity Perceived health Life satisfaction
Mean 4.58 4.27 4.30 3.35 2218.4 4.23 4.22
SD 0.46 0.45 0.50 1.15 1309.1 0.56 0.84
Mean 4.52 4.13 4.14 3.33 1967.1 4.18 3.94
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Class 3 Medical advice SD 0.47 0.47 0.41 1.53 1287.1 0.46 0.75
Mean 4.29 4.14 4.05 3.48 2241.0 3.59 3.92
SD 0.50 0.41 0.37 0.78 2104.9 0.73 0.68
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lower life satisfaction than the group that exercise for leisure/sports. It seems that to practice exercise for keeping fit (be healthy) or medical advice, may be associated to health problems or health risks, which may, in turn be associated to lower levels of life satisfaction. Apparently, those who practice exercise for fun/leisure are more likely to be free from physical and health problems and therefore feel more satisfied with life. These results are consistent with the works carried out by Kolt et al. (2004), Ferrand et al. (2012), and Li et al. (2014). In general, our results are pretty much in line with those of previous studies about successful aging (Cené et al., 2016; Dahany et al., 2014; Kobayashi, Wardle, Wolf, & von Wagner, 2016), motives to exercise (Biedenweg et al., 2014; Cleland et al., 2015; Schutzer & Graves, 2004; Patay et al., 2015), perceived health (Li et al., 2014; Meng & D’Arcy, 2013), physical activity (Enríquez-Reyna et al., 2016; Ferrand et al., 2013; Patel et al., 2013; Troutman & Staples, 2014), and well-being (Ferrand et al., 2013: Fox et al., 2007).
those obtained by authors like Kolt et al. (2004) and Patel et al. (2013) that have investigated the motives to practice exercise in Australian older adults samples. Kolt et al. (2004) found four main motivations for exercising: health, fitness, enjoyment of the activity, and relaxation. These four motives resemble our classes, as they were medical/health reasons, leisure (which includes the enjoyment and relaxation motives) and fit. Also very similar to current classes were the main motives found by Patel et al. (2013): enjoyment; health and medical reasons; and wanting to be physically active. In a qualitative study, Costello, Kafchinski, Vrazel and Sullivan (2011) with American older adults found that active people listed a number of motivators for exercising that could be grouped into categories. Specifically, the categories they made were health concerns, socialization, staff and programming, accessibility, facilities and physician encouragement. Health concerns and physician encouragement would group into the class of medical advice/ health, whereas socialization would integrate the leisure/sport class. Also with an American sample of 645 old people, Dacey, Baltzell and Zaichkowsky (2008) studied how motivators for exercising grouped together with an Exploratory Factor Analysis (EFA) of the EMI-2 scale. They found a solution of six factors: health and fitness; social/emotional benefits; weight management, stress management, enjoyment and appearance. Some of the factors found by Dacey et al. (2008) agree with the latent classes, even though they come from a very different type of statistical analyses, EFA that groups variables, whereas our results come from a LCA that groups peoples. Health, weight management may go under the latent class medical recommendation, social and emotional benefits are clearly similar to our leisure class, while appearance and fitness would agree with fit class. The second hypothesis was that the medical advice class would have lowers levels of successful aging as measured in the four dimensions of the SAI compared to the other two classes. Results showed that three of the four dimensions of successful aging (functional performance, intrapsychic factors, and gerotranscendence) performed in the expected direction. Spirituality was the exception in this hypothesis because the group who is motivated to exercise for medical advice has obtained higher values in spirituality than the other groups (leisure/sports, and keep fit). These results are in line with those by Troutman and Staples (2014), and Li et al. (2014). As Dahany et al. (2014) stated, spirituality is particularly important for older subjects of all cultures, and are frequently associated with improved psychological and mental well-being, and it may act as a protector against poor health. The three significant results obviously do not mean that the medical and health motives are per se the causes of lower functional performance, or worse intrapsychic factors and gerotranscendence. Probably, on the contrary, those with medical problems have poorer health and accordingly evaluate their functional performance, their mood (intrapsychic mechanism) and even their concerns about next generation (gerotranscendence) worse than those in healthier conditions. The third hypothesis stated that fitness class would have higher levels of physical activity, given that fit is an intrinsic motivation. This hypothesis has not been supported by our data, the group practicing activity for leisure/sports has obtained equal results that the group that exercise because of medical advice. The group that has obtained minor values in physical activity was the group that exercised for fitness. This result seems was not expected, especially if we consider that the practice of exercise on medical advice has been considered as both a motive and a barrier for exercising in older adults (Mathews et al., 2010). Medical and health reasons are extrinsic motivations, but apparently were strong motives to keep the old people active. The fourth hypothesis was that medical or health class would have lower levels of perceived health and life satisfaction. Indeed, the group who exercised for medical advice has had lower levels of perceived health than the other two groups (leisure/sports and keep fit). Nevertheless, in relation with life satisfaction, there were not differences between the group that exercised for medical advice and the group that exercised to be fit. These two groups showed a significantly
4.1. Practical implications From an applied perspective, the results of this study highlight the importance of motivating older people to practice exercise before having the need to do so by medical prescription. If people would practice exercise for fun throughout their lives, they would reach their old age in better physical and psychological conditions. This is important because, as Biedenweg et al. (2014) stated, the most frequently cited personal factors motivating program participation were enjoying being with others while exercising and desiring a routine that promoted accountability, and the most common barriers to participation were already getting enough exercise, not being motivated or ready, and having poor health. As Södergren (2013) stated, the major challenge with aging populations is to maintain physical and cognitive functions, quality of life and independence. 4.2. Limitations, strengths and future directions Current research has several limitations. The study sample was large, however it was not a random sample and generalization of these results is therefore limited. Additionally, our sample was also mainly female, likely due to a greater tendency for females to participate in group exercise classes, as in studies by Bopp, Peterson and Webb (2012), and Biedenweg et al. (2014). Another limitation is that the cross-sectional design does not allow for strong causal interpretation, and future longitudinal studies should seed light on potential causes and effects. Another is the relatively good health of the sample we recruited. As such, our findings may not generalize to persons in poorer health. Last, but not least, the nature of the survey research, together with the relative large number of constructs to be measured made us use a very short checklist of motives. Despite the fact that these motives were among the mostly communicated by old people to practice exercise, and the fact that our results are extremely similar to those found by other authors, it would be very interesting to replicate this type of analysis with larger scales that consider more motives as well as barriers and benefits of exercising. Among the strengths, the variety of dimensions of successful aging measured and the fact that they not only consider the biomedical perspective but also the social and psychological one. Additionally, the use of latent class analysis is relatively new to the study of motives to exercise, and this technique is a powerful person-oriented statistical technique that overcomes the limitations of purely descriptive statistics or cluster analysis. In this research, we asked the older adults for their reasons or motives to practice exercise in an open way. Future research, could investigate the older people’s motives for exercising in the framework of the self-determined motivation theory. In this sense, Dacey et al. (2008) stated that motivation can differentiate activity levels, and that an increase of intrinsic and self-determined motives is positively 48
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associated with more exercise in older adults. Knowing how the motives vary by gender and age could contribute to effective interventions for increasing older adults’ activity levels. A bulk of research on physical activity suggests that when people are autonomously motivated to exercise, they are most likely to do so. Nevertheless, further research is needed to provide a better understanding of motivational processes in older adults to maintain an active lifestyle (Ferrand et al., 2012).
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Cultural factors in exercise participation of older adults. Perceptual and Motor Skills, 87, 890. Kirkby, R. J., Kolt, G. S., Habel, K., & Adams, J. (1999). Exercise in older women: Motives for participation. Australian Psychologist, 34, 122–127. Kobayashi, L. C., Wardle, J., Wolf, M. S., & von Wagner, C. (2016). Aging and functional health literacy: A systematic review and meta-analysis. Journals of Gerontology Series B-Psychological Sciences and Social Sciences, 71(3), 445–457. Kolt, G. S., Chadha, N. K., Giles, L. C., & Driver, R. (2002). Exercise participation motives in older Asian Indians. Psychological Studies, 47, 47–55. Kolt, G. S., Driver, K. R., & Giles, L. C. (2004). Why older Australians participate in exercise and sport. Journal of Aging and Physical Activity, 12(2), 185–198. Lee, P. L., Lan, W., & Yen, T. W. (2011). Aging successfully: A four-factor model. Educational Gerontology, 37(3), 210–227. Li, C. I., Lin, C. H., Lin, W. I., Liu, C. S., Chang, C. K., Meng, N. H., ... Lin, C. C. (2014). Successful aging defined by health-related quality of life and its determinants in community dwelling elders. BMC Public Health, 14(1013), 1–8. Lukociené, O., Varriale, R., & Vermunt, J. K. (2010). The simultaneous decision(s) about the number of lower- and higher-level classes in multilevel latent class analysis. Sociological Methodology, 40, 247–284. Müller, A. M., Ansari, P., Ebrahim, N. A., & Khoo, S. (2016). Physical activity and aging research: A bibliometric analysis. Journal of Aging and Physical Activity, 24, 476–483. Maher, J. P., Doerksen, S. E., Elavsky, S., Hyde, A. L., Pincus, A. L., Ram, N., ... Conroy, D. E. (2013). A daily analysis of physical activity and satisfaction with life in emerging adults. Health Psychology, 32(6), 647–656. Mathews, A. E., Laditka, S. B., Laditka, J. N., Wilcox, S., Crowin, S. J., Liu, R., ... Logsdon, R. G. (2010). Older adults’ perceived physical activity enablers and barriers: A multicultural perspective. Journal of Aging and Physical Activity, 18(2), 119–140. Meng, X., & D’Arcy, C. (2013). Successful aging in Canada: Prevalence and predictors from a population-based sample of older adults. Gerontology, 60, 65–72. Muthén, L. K., & Muthén, B. O. (1998-2017). Mplus user’s guide (8th ed.). Los Angeles, CA: Muthén & Muthén. Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A monte carlo simulation study. Structural Equation Modeling, 14, 535–569. Organización Mundial de la Salud (2015). Informe mundial sobre el envejecimiento y la salud. http://apps.who.int/iris/bitstream/10665/186466/1/9789240694873_spa. pdf?ua=1. Paskulin, L., Vianna, L., & Molzahn, A. E. (2009). Factors associated with quality of life of Brazilian older adults. International Nursing Review, 56, 109–115. Patay, M. E., Patton, K., & Parker, M. (2015). Understanding motivators and barriers to physical activity. The Physical Educator, 72(3), 496–517. Patel, A., Schofield, G. M., Kolt, G. S., & Keogh, W. L. (2013). Perceived barriers, benefits: And motives for physical activity: Two primary-care physical activity prescription programs. Journal of Aging and Physical Activity, 21, 85–99. Pinto, J. M., Fontaine, A. M., & Neri, A. L. (2016). The influence of physical and mental health on life satisfaction is mediated by self-rated health: A study with Brazilian elderly. Archives of Gerontology and Geriatrics, 65, 104–110. Pruchno, R. A., Wilson-Genderson, M., & Cartwright, F. (2010). A two-factor model of successful aging. Journal of Gerontolology Series B: Psychological Sciences and Social Sciences, 65, 671–679. Rennemark, M., Lindwall, M., Halling, A., & Berglund, J. (2009). Relationships between physical activity and perceived qualities of life in old age. Results of the SNAC study. Aging & Mental Health, 13(1), 1–8. Rowe, J. W., & Kahn, R. L. (1987). Human aging: Usual and successful. Science, 237, 143–149. Rowe, J. W., & Kahn, R. L. (1998). Successful aging. New York: Pantheon. Södergren, M. (2013). Lifestyle predictors of healthy ageing in men. Maturitas, 75, 113–117. Schutzer, K. A., & Graves, B. S. (2004). Barriers and motivations to exercise in older adults. Preventive Medicine, 39, 1056–1061. Stephan, Y., Boiché, J., & Le Scanff, C. (2010). Motivation and physical activity behaviors among older women: A self-determination perspective. Psychology of Women Quarterly, 34, 339–348. Stubbs, B., Eggermont, L., Soundy, A., Probst, M., Vandenbulcke, M., & Vancampfort, D. (2014). What are the factors associated with physical activity (PA) participation in community dwelling adults with dementia? A systematic review of PA correlates. Archives of Gerontology and Geriatrics, 59, 195–203. Tabachnick, B., & Fidell, L. (2007). Using multivariate statistics. New York: Harper Collins. Troutman, M., & Staples, J. (2014). Successful aging from the viewpoint of older adults. Research and Theory for Nursing Practice: An International Journal, 28(1), 87–104. Troutman, M., Nies, M., Small, S., & Bates, A. (2011). The development and testing of an instrument to measure successful aging. Research in Gerontological Nursing, 4(3), 221–232.
4.3. Main conclusion A main conclusion derived from the results is that not all old people do exercise for the same motives, and the type of motives you are in may have an impact/relation on markers of successful aging. Motives related to internal conviction (fitness, socializing, having fun…) rather than external pressures (medical advice, need to lose weight…) should be promoted in the old age. Funding This research was funded by the Spanish Ministery of Education grant PSI 2014-53280-R. Conflict of interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. References Barber, S. E., Forster, A., & Birch, K. M. (2015). Levels and patterns of daily physical activity and sedentary behavior. Measured objectively in older care home residents in the United Kingdom. Journal of Aging and Physical Activity, 23, 133–143. Biedenweg, K., Meischke, H., Bohl, A., Hammerback, K., Williams, B., Poe, P., ... Phelan, E. A. (2014). Understanding older adults’ motivators and barriers to participating in organized programs supporting exercise behaviors. The Journal of Primary Prevention, 35, 1–11. Bopp, M., Peterson, J. A., & Webb, B. L. (2012). A comprehensive review of faith-based physical activity interventions. American Journal of Lifestyle Medicine, 6(6), 460–478. Bowling, A., & Dieppe, P. (2005). What is successful ageing and who should define it? British Medical Journal, 331, 1548–1551. Cené, C. W., Dilworth-Anderson, P., Leng, I., Garcia, L., Benavente, V., Rosal, M., ... Cochrane, B. (2016). Correlates of successful aging in racial and ethnic minority women age 80 years and older: Findings from the Womenés Health Initiative. Journals of Gerontology, S87–S99. Chung, P. K., Zhao, Y., Liu, J. D., & Quach, B. (2017). A canonical correlation analysis on the relationship between functional fitness and health-related quality of life in older adults. Archives of Gerontology and Geriatrics, 68, 44–48. Cleland, V., Hughes, C., Thornton, L., Squibb, K., Venn, A., & Ball, K. (2015). Environmental barriers and enablers to physical activity participation among rural adults: A qualitative study. Health Promotion Journal of Australia, 26, 99–104. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159. Cosco, T. D., Prinq, A. M., Perales, J., Stephan, B. C. M., & Brayne, C. (2014). Operational definitions of successful aging: A systematic review. International Psychogeriatrics, 26(3), 373–381. Costello, E., Kafchinski, M., Vrazel, J., & Sullivan, P. (2011). Motivators, barriers, and beliefs regarding physical activity in an older adult population. Journal of Geriatric Physical Therapy, 34(3), 138–147. Craig, C. L., Marshall, A. L., Sjöström, M., Bauman, A. E., Booth, M. L., Ainsworth, B. E., ... Oja, P. (2003). International physical activity questionnaire: 12-country reliability and validity. Medicine and Science in Sports and Exercise, 35(8), 1381–1395. Crowther, M. R., Parker, M. W., Achenbaum, W. A., Larimore, W. L., & Koenig, H. G. (2002). Rowe and Kahn’s model of successful aging revisited: Positive spirituality. The forgotten factor. The Gerontologist, 42(5), 613–620. Dacey, M., Baltzell, A., & Zaichkowsky, L. (2008). Older adults' intrinsic and extrinsic motivation toward physical activity. American Journal of Health Behavior, 32(6), 570–582. Dahany, M. M., Dramé, M., Mahmoudi, R., Novella, J. L., Ciocan, D., Kanagaratnam, L., ... Jolly, D. (2014). Factors associated with successful aging in persons aged 65 to 75 years. European Geriatric Medicine, 5, 365–370. Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49, 71–75. Enríquez-Reyna, M. C., Castruita, R. M., Zamarripa, J., Gurrola, O., & Valtier, M. C. (2016). Physical activity level, exercise self-efficacy, benefits and perceived barriers of independent Mexican older women? Hispanic Health Care International, 14(1), 26–36. Feng, Q., Son, J., & Zeng, Y. (2015). Prevalence and correlates of successful ageing: A comparative study between China and South Korea. European Journal of Ageing, 12,
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United Nations, Department of Economic and Social Affairs (2012). Population ageing and development 2012 (wall chart). New York: United Nations Publications. Van Alphen, H. J. M., Hortobágyi, T., & van Heuvelen, J. G. (2016). Barriers, motivators, and facilitators of physical activity in dementia patients: A systematic review. Archives of Gerontology and Geriatrics, 66, 109–118. Victor, C. R., Rogers, A., Woodcock, A., Beighton, C., Cook, D. G., Kerry, S. M., & Harris, T. J. (2016). What factors support older people to increase their physical activity levels? An exploratory analysis of the experiences of PACE-Lift trial participants. Archives of Gerontology and Geriatrics, 67, 1–6. Ware, J. E., Kosinski, M., Dewey, J. E., & Gandek, M. S. (2001). How to score and interpret single-item health status measures: A manual for users of the SF-8 Health Survey. Lincoln, RI: Quality Metric. Inc. Young, A., & Dinan, S. (2005). Activity in later life. British Medical Journal, 330, 189–191. Zullig, K. J., Valois, R. F., Huebner, E. S., & Drane, J. W. (2005). Adolescent health-related quality of life and perceived satisfaction with life. Quality of Life Research, 14, 1573–1584.
Dr. Melchor Gutiérrez is full professor of Motor Control and Learning at the Department of Educational and Developmental Psychology (University of Valencia, Spain). His main research topics are adolescents’ socialization through sports, and quality of life in older people. Dr. Pablo Calatayud is MD at the Department of Methodology for the Behavioral Sciences (Faculty of Psychology, University of Valencia, Spain). His main research topic is the influence of physical activity and exercise on successful aging. Dr. José-Manuel Tomás is full professor of Statistics at the Department of Methodology for the Behavioral Sciences. He is an expert in structural equation modeling and measurement, and has extensively published in indexed international journals on quality of life, health at work, and ageing.
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Contents lists available at ScienceDirect
Archives of Gerontology and Geriatrics journal homepage: www.elsevier.com/locate/archger
Motives to practice exercise in old age and successful aging: A latent class analysis
T
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Melchor Gutiérreza, , Pablo Calatayudb, José-Manuel Tomásb a b
Department of Educational and Developmental Psychology, Faculty of Psychology, University of Valencia, Av. Blasco Ibáñez, 21, 46010 Valencia, Spain Department of Methodology for the Behavioral Sciences, Faculty of Psychology, University of Valencia, Av. Blasco Ibáñez, 21, 46010 Valencia, Spain
A R T I C LE I N FO
A B S T R A C T
Keywords: Life satisfaction Perceived health Physical activity Spirituality Functional performance Gerotranscendence
Purpose: The aim was to classify motives for exercising trying to find sets of related cases that share common motivations, and to relate these latent classes to markers of successful aging. Methods: 725 old adult aged 55 to 97 years were sampled in several Spanish towns. Instruments: Successful Aging Inventory (SAI), International Physical Activity Questionnaire (IPAQ), Health Survey SF-8, Satisfaction with Life Scale (SWLS), and motives to practice exercise, were used. Latent Class Analyses (LCAs) were estimated. The classes obtained were compared on markers of successful aging. Results: Three latent classes were deemed optimal. Significant differences for several markers of successful aging were found. Conclusion: A main conclusion derived from the results is that not all old people do exercise for the same motives, and the class of motives you are in had an impact/relation on markers of successful aging. Motives related to internal rather than external pressures should be promoted in the old age.
1. Introduction As Barber, Forster, and Birch (2015) stated, life expectancy has increased dramatically over the last century, leading to changes in the world’s demography. It is predicted that by the year 2050, about 2 billion people, accounting for 20% of the global population, will be 60 years or older (OMS, 2015; United Nations, Department of Economic & Social Affairs, 2012). This has generated, among other things, a growing interest focused on successful aging factors for obtaining a healthy and happy life in old age and in an aging society (Paskulin, Vianna, & Molzahn, 2009; Pinto, Fontaine, & Neri, 2016). Many authors affirm that one of the most important non-pharmaceutical ways towards healthy aging is exercise (Müller, Ansari, Ebrahim, & Khoo, 2016; Södergren, 2013; Van Alphen, Hortobágyi, & van Heuvelen, 2016). There is evidence that high levels of physical functioning are fundamentally important to healthy aging, and participation in exercise is a strong predictor of aging well (Kolt, Driver, & Giles, 2004). Exercise can act as a health protective factor among older individuals. Regular participation in exercise can decrease the occurrence of diseases, falls, and disability as well as improve independence (Young & Dinan, 2005). Furthermore, regular exercise not only has many physical benefits but can also contribute to psychological wellbeing among older adults (Chung, Zhao, Liu, & Quach, 2017; Ferrand,
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Nasarre, Hautier, & Bonnefoy, 2012; Fox, Stathi, McKenna, & Davis, 2007; Kolt et al., 2004). Despite the physical and psychological health benefits of exercise, many old people do not exercise enough to gain health benefits (Patel, Schofield, Kolt, & Keogh, 2013; Schutzer & Graves, 2004). Therefore, knowing the motives why old people exercise, as well as barriers that limit them such practices, has become a target of interest for research (Biedenweg et al., 2014; Kolt, Chadha, Giles, & Driver, 2002; Patel et al., 2013; Stephan, Boiché, & Le Scanff, 2010; Stubbs et al., 2014; Victor et al., 2016). In the older population, barriers and motivators often intertwine, making it difficult to isolate factors specific to this cohort (Schutzer & Graves, 2004; Van Alphen et al., 2016). Kolt et al. (2004), investigating the motives for practicing exercise in a sample of Australian older adults, found that the predominant reasons reported related to health, fitness, enjoyment of the activity, and relaxation. In this study, women rated medical, social, and involvement reasons as significantly more important than did their male counterparts. More recently, Patel et al. (2013) carried out a study with the aim to identify perceived barriers, benefits, and motives for exercising in a sample of people 65 years old or older. They found that the main motives for participation in exercise were: being active for enjoyment reasons; being active for health and medical reasons; and engaged in exercise for the purpose of wanting to be physically active. The
Corresponding author. E-mail addresses: [email protected] (M. Gutiérrez), [email protected] (P. Calatayud), [email protected] (J.-M. Tomás).
https://doi.org/10.1016/j.archger.2018.04.003 Received 10 November 2016; Received in revised form 23 March 2018; Accepted 5 April 2018 Available online 12 April 2018 0167-4943/ © 2018 Published by Elsevier B.V.
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a) to elaborate a classification of motives for exercising trying to find sets of related cases (latent classes) that share common motivations using latent class analysis; b) to relate these latent classes to markers of successful aging. Specifically several hypotheses were raised:
benefits of exercise participation were: personal benefits (like selfconfidence), and physical benefits (like feeling fitter). As barriers to participation in exercise, they identified three factors: personal barriers (like lack of motivation); perceptual barriers (like feeling too old to be physically active); and time constraints (for example, family responsibilities). Cleland et al. (2015) explored the environmental factors that act as barriers or facilitators to exercise participation among rural adults, and found four key themes: functionality, diversity, spaces and places for all, and realistic expectations. In the study carried out by Patay, Patton and Parker (2015), four main categories emerged: (a) acknowledgment and knowledge of exercise, (b) environmental factors, (c) cultural aspects, and (d) social aspects of exercise. Many researchers agree that it is vital to ensure that the population ages healthily and that longevity is accompanied by better quality of life (Rennemark, Lindwall, Halling, & Berglund, 2009; Troutman, Nies, Small, & Bates, 2011). Reyna, Castruita, Zamarripa, Gurrola, and Valtier (2016) concluded that self-efficacy and perceived benefits of exercise were positively associated with the level of physical activity. What is successful aging? Rowe and Kahn (1987, 1998) defined successful aging as the avoidance of disease and disability, maintenance of physical and cognitive function, and engagement in social and productive activities. Later, Crowther, Parker, Achenbaum, Larimore, and Koenig (2002) added a fourth component, spirituality. The most commonly proposed definition of successful aging has been satisfaction with one’s life (Bowling & Dieppe, 2005). From an initial approach with a purely biomedical perspective, the focus has been changing towards a more holistic vision, attending to more subjective aspects of the aging process (Pruchno, Wilson-Genderson, & Cartwright, 2010). There are multidimensional theories of successful aging that propose components of both biomedical and psychosocial theories (Bowling & Dieppe, 2005). Psychosocial models emphasize aspects like life satisfaction, well-being, social engagement, or personal resources (Cosco, Prinq, Perales, Stephan, & Brayne, 2014). Troutman and Staples (2014) have studied the interpretation of successful aging from the viewpoint of older adults raising the question: What does successful aging mean to you? Eight broad themes emerged: active independence, relationships with people, relationship with God, comfort resources, health, beneficial contribution, positive perspective/coping, and freedom. Further, Troutman and Staples (2014) referred that, derived from the content analysis, the literature have supported six headings of successful aging: health; independence, the construct of active engagement; connectedness; attitude, adaptability, and coping; sense of purpose; and appropriate resources. A few years earlier, Troutman et al. (2011) created an instrument to measure successful aging, and they found four dimensions: functional performance mechanisms; intrapsychic factors, spirituality, and gerotranscendence. Lee, Lan and Yen (2011) proposed a model of successful aging composed by four factors: physical, psychological, social, and leisure. As literature has shown, in addition to exercise, other important variables have been related along the time to aging successfully, as perceived health and life satisfaction (Hilton, Gonzalez, Saleh, Maitoza, & Anngela-Cole, 2012; Troutman et al., 2011). Li et al. (2014) suggested that self-reported health measures may be the most appropriate measures for comparing cross-national differences in successful aging. They found that successfully aging old people had significantly more favorable health status than those who were not successful. Physical functioning is one aspect of health-related quality of life and it is often considered a component of successful aging (Cené et al., 2016). In the same vein, life satisfaction has been identified as an indicator of successful aging (Troutman et al., 2011). Rowe and Kahn (1998) stated that successful aging involves individuals’ physical health, psychological well-being, and social engagement with life. According to Feng, Son, and Zeng (2015), successful agers are those who are free from major illnesses and disabilities, having no depressive symptoms, participating in social or productive activities, and being satisfied with life. Based on the above mentioned, the aim of this research was twofold:
a) There will be, at least, three latent classes among the motives to practice exercise: medical or health reasons, fitness, and to socialize (having social relationships). b) Medical or health class will have lowers levels of successful aging as measured in the four dimensions of the Successful Aging InventorySAI (functional performance, intrapsychic factors, spirituality, and gerotranscendence) compared to the other two classes. c) Fitness class will have higher levels of exercise, given that fit is an intrinsic motivation d) Medical or health class will have lower levels of perceived health and life satisfaction. 2. Methods 2.1. Participants The sample under study consisted of 725 older adults aged 55 to 97 years (M = 68.28; SD = 8.62), 478 were women (66%) and 247 men (34%). The sample was collected in three areas: sport centers, day centers, and public areas of several Spanish towns. 2.2. Instruments (a) To measure successful aging, the Successful Aging Inventory (SAI; Troutman et al., 2011) was used. The scale is a 20-item instrument with four dimensions: Functional performance, Intrapsychic factors, Spirituality, and Gerotranscendence. Example items of each factor are: I have been able to cope with the changes that have occurred to my body as I have aged; I am in a positive, pleasant mood; I spend time in prayer or doing some kind of religious activity; I feel interest in/concern for the next generation. Internal consistencies for the four dimensions were respectively, 0.62, 0.87, 0.80 and 0.81. A 5point response scale was adopted, from (1) strongly disagree to (5) strongly agree. (b) The short form of the International Physical Activity Questionnaire (IPAQ; Craig et al., 2003) referred to the last 7 days. It is an indicator of time spent per week on different intensities of physical activity (vigorous, moderate, walking…). Physical activity was converted into metabolic equivalents (METs), according to the conversion factors applied in IPAQ. (c) To examine the health perception of old people, the SF-8 Health Survey (Ware, Kosinski, Dewey, & Gandek, 2001) was used. This scale has eight items that assess health related quality of life, as perceived within the last month. Examples of items are: How much energy have you had?, How many physical pains have you had?, or How much have you been bothered by emotional problems? Participants could answer in a Likert-type scale from (1) none or nothing to (5) much or many. Internal consistency estimate was 0.75. (d) Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985). This scale is composed of five items assessing global life satisfaction, ranging from (1) totally disagree to (5) totally agree. Example items are: In most ways my life is close to my ideal; If I could live my life over, I would change almost nothing. Reliability was 0.86. (e) The checklist of motives to practice exercise was developed ad hoc for the research purposes. Several scales and questionnaires existed to tap motives for exercising and related aspects such as barriers and benefits. Among them the Participation Motivation Questionnaire for Older Adults (PMQOA; Kirkby, Kolt, & Habel, 1998; Kirkby, Kolt, Habel, & Adams, 1999) with 31 items or the 45
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participants based on these classes were compared on several markers or indicators of successful aging. These comparisons were performed with Multivariate Analyses of Variance (MANOVA) and Analysis of Variance (ANOVA) tests. MANOVA was used to test the main effect of group on the four dimensions in the SAI questionnaire. MANOVA tests the differences in the centroid (vector) of means of the multiple dependents, for various categories of the independent or independents. Among the available multivariate criteria to test for effects, Pillai’s criterion was used because it is the most robust to violations of the underlying assumptions (Tabachnick & Fidell, 2007). If the overall Ftest showed the centroid (vector) of means of the dependent variables was not the same for all the groups formed by the categories of the independent variables, post-hoc univariate F-tests of group differences were used to determine which group means differ significantly from others. ANOVAs were used to test for mean differences among the three groups in amount of physical activity (IPAQ), perceived health and life satisfaction. Subsequently, pairwise multiple comparison tests tested each pair of groups to identify similarities and differences. Additionally to the tests of effects, effect sizes (partial eta-squares) were estimated, and Cohen’s guidelines to interpret the magnitude of the effects were employed: 0.02, 0.13 and 0.26 for small, medium, and large effects, respectively (Cohen, 1992). All these additional statistical analyses were performed in SPSS 22.
Exercise Motivation Inventory (EMI-2) by Kilpatrick, Hebert and Bartholomew (2005) with 51 items. Also Patel et al. (2013) studied the main motives to practice exercise in the old people and found four main motives. With all these scales in mind a checklist of main motives was summarized that included six of them: (a) medical advice (Kolt et al., 2004, Kirkby et al., 1999, Patel et al., 2013); (b) fun (Kolt et al., 2004, Patel et al., 2013); (c) weight loss (Kolt et al., 2004, Patel et al., 2013); (d) leisure (Kolt et al., 2004); keep fit (Kolt et al., 2004); (f) relations with other people (Kolt et al., 2004, Kirkby et al., 1999); (g) Others (to be specified). The checklist started with the statement “I practice exercise for…” and then the six motives were presented with a yes/no response format. Although being a very short and simple checklist, it was used because of a trade-off between the number of constructs the survey had to include and the limited time we had to interview the old people. Nevertheless, simple indicators of complex constructs have been shown to perform well in surveys with old people (among others: Maher et al., 2013; Zullig, Valois, Huebner & Drane, 2005). 2.3. Procedure The first step was to apply for the appropriate permissions to the municipalities of different Spanish towns and managers of the centers needed to conduct this investigation. Then, we contacted the instructors and staff in the sports facilities and day centers to coordinate the survey, explain the research and ask for assistance. For people interviewed on the street, only their permission and collaboration was needed. Finally, the survey was implemented. Given the nature of the research (a survey in centers and/or street with interviewers), it was crucial to keep the survey length at a minimum. Therefore, very short scales and indicators were chosen for all the constructs in the survey. The average time needed to answer the survey was about 10 min.
3. Results 3.1. Motives for exercising: a latent class analysis Descriptive statistics were calculated within the sample to determine current motives to exercise. These frequencies showed that 22% of the participants did exercise because of medical recommendation, 33.9% did exercise to have fun, 8.2% for weight loss, 81% to keep fit, and finally 40.5% of the old people did practice exercise in order to establish social relations. To determine the optimal number of classes, models evaluating the relative fit of 1–4 class solutions were run. Better solution was chosen based on a smaller Bayesian Information Criterion (BIC) value, a smaller sample size-adjusted BIC value, a smaller Akaike Information Criterion value, a higher entropy value, and significant Lo–Mendell–Rubin (LMR) and bootstrapped likelihood ratio (LR) tests. LMR and LR tests compare a solution with k classes vs. the solution with k-1 classes. Additionally, interpretability of the results was also considered. Statistical criteria and tests are shown in Table 1. In light of the results of statistical criteria, a three latent classes solution was deemed optimal. The three information criteria (BIC, ABIC and AIC) for this solution were lower than those in the other solutions. When LMR and LR test were conducted, the three latent classes solution was significantly better than the two latent classes solution, whereas the four latent class solution was not better than the three latent class solution. The only criterion in which the solution with three latent classes may be considered worse was the index of entropy. Therefore, we turned to interpretability and retained the three latent classes solution. The probabilities for most likely latent class membership were good for the three classes (class one = .84; class two = .81; class three = .95).
2.4. Statistical analyses Latent Class Analyses (LCAs) were estimated in Mplus 8 (Muthén & Muthén, 1998-2017Muthén & Muthén, 1998-2017). LCA is a person centered (cluster type) method that seeks for subgroups of observations with similar response patterns as regards the variables of interest in order to maximize the between-group heterogeneity and within-group homogeneity (Nylund, Asparouhov, & Muthén, 2007). LCA may be used to test a theory on a certain number and type of classes, or it can be used in an exploratory way, as it is the case in this research. The number of classes retained is based on several statistical criteria: Information criteria as the Bayesian Information Criteria (BIC), sample size—adjusted BIC (ABIC), and Akaike Information Criterion (AIC), with smaller values indicating better fit; entropy values (from 0 to 1 = perfect fit); and significant Lo–Mendell–Rubin (LMR) and bootstrapped likelihood ratio (LR) tests to compare one model against the model with one class less. Beyond the aforementioned statistical criteria, the selection of the number of classes is very subjective and requires theoretical and/or practical justifications. Therefore, interpretability of the results was also considered, as advised by Lukociené, Varriale, and Vermunt (2010). Once the number of latent classes was determined, the groups of Table 1 Fit indices of latent class analyses of motives to practice exercise. # classes
LR
AIC
BIC
ABIC
Entropy
LMR test
p
BLR test
p
1 2 3 4
228.81 126.12 81.56 65.11
2979.03 2890.34 2857.78 2857.33
3004.33 2945.15 2944.11 2971.18
2985.29 2903.89 2880.63 2885.48
1 0.87 0.65 0.77
NA 100.38 43.46 16.44
NA < .001 < .01 =.08
NA 102.69 44.56 16.44
NA < .001 < .001 =.07
Note: LR = Log-likelihood ratio; AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion; ABIC = Adjusted BIC; LMR = Lo-Mendell-Rubin test; BLR = Bootstrapped Log-likelihood Ratio; NA = Non applicable. 46
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Fig. 1. Latent classes and their probabilities in the different categories.
Between subjects ANOVAs were also performed to test for mean differences in the amount of physical activity measured with the IPAQ, health perception and life satisfaction. Means and standard deviations for these three variables, in the three groups, are presented in Table 2. The first ANOVA found no statistically significant differences among the means of the three latent classes in amount of physical activity (F (2498) = 2.127; p = .12; η2 = .008). The ANOVA testing for differences in perceived health was statistically significant (F (2498) = 28.047; p < .001; η2 = .101). The post-hoc tests found that perceived health was higher for those exercising as a leisure activity or to keep fit versus those practicing exercise because of medical advice. Finally, in the third ANOVA on life satisfaction, there also were statistically significant differences among the three groups (F (2498) = 8.243; p < .001; η2 = .032). Pairwise comparisons found that people who exercise for leisure were more satisfied than those that exercise to keep fit or for medical advice.
A look at Fig. 1 aids to interpret the three classes solution. Class one grouped the participants with high probabilities to exercise due to fit reasons but also for socializing and to have fun. We labeled this class as leisure/sports. Class two was formed by participants only interested in keeping physical fit. Finally, class three comprised those that exercise following medical advice, and with also some probability to do it for weight loss. 43.6% of the subjects were classified in latent class one, 47.2% in class two and a 9.2% in class 3.
3.2. Relationships among motives for exercising and markers of successful ageing Group (or latent class) membership according to the results in the LCA analysis, was used to test for mean differences in some important markers of successful aging. Among them, the four dimensions in the SAI. A MANOVA was performed to test for mean differences in the linear combination of the four dimensions of successful aging, and mean differences were statistically significant (F (8, 992) = 4.376; p < .001; η2 = .034). In order to separately test for differences in the means of the four dimensions, follow-up ANOVAs were performed. These ANOVAS found significant differences for functional performance (F (2, 498) = 7.150; p = .001; η2 = .028), intrapsychic mechanism (F (2, 498) = 8.874; p < .001; η2 = .034), and gerotranscendence (F (2, 498) = 10.805; p < .001; η2 = .042), but non-significant differences for spirituality (F (2, 498) = .252; p = .777; η2 = .001). Means and standard deviations for the three latent classes in the four dimensions are shown in Table 2. Pairwise tests showed that those who practice for leisure or to keep fit had more functional performance than those who exercise for medical advice. Mean differences tests in intrapsychic mechanism also found larger means for those who exercise for leisure compared to those who want to be fit and the lowest mean was the one of those exercising for medical recommendation, and that pattern also hold for the dimension of gerotranscendence.
4. Discussion This study is grounded on the basis of the progressive aging of world’s population in the last century, and that many of this old people do not practice enough exercise for having a healthy aging. The aim of this study was to elaborate a classification of motives for exercising trying to find sets of related cases that share common motivations using latent class analysis, and to relate these latent classes to several markers of successful aging. It was hypothesized that there would be, at least, three latent classes among the motives to practice exercise. According to results shown in Table 1 and Fig. 1, three latent classes were obtained: class one that grouped the participants to exercise for leisure/sports, class two formed by participants who exercise to keep fit, and class three comprised by those who practice exercise for medical advice. These results partially satisfy the compliance with the first hypothesis and are in line with
Table 2 Means and standard deviations (SD) by latent class. Class 2 Keep fit
Class 1 Leisure/sports Markers of successful aging Functional performance Intrapsychic mechanism Gerotranscendence Spirituality Physical activity Perceived health Life satisfaction
Mean 4.58 4.27 4.30 3.35 2218.4 4.23 4.22
SD 0.46 0.45 0.50 1.15 1309.1 0.56 0.84
Mean 4.52 4.13 4.14 3.33 1967.1 4.18 3.94
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Class 3 Medical advice SD 0.47 0.47 0.41 1.53 1287.1 0.46 0.75
Mean 4.29 4.14 4.05 3.48 2241.0 3.59 3.92
SD 0.50 0.41 0.37 0.78 2104.9 0.73 0.68
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lower life satisfaction than the group that exercise for leisure/sports. It seems that to practice exercise for keeping fit (be healthy) or medical advice, may be associated to health problems or health risks, which may, in turn be associated to lower levels of life satisfaction. Apparently, those who practice exercise for fun/leisure are more likely to be free from physical and health problems and therefore feel more satisfied with life. These results are consistent with the works carried out by Kolt et al. (2004), Ferrand et al. (2012), and Li et al. (2014). In general, our results are pretty much in line with those of previous studies about successful aging (Cené et al., 2016; Dahany et al., 2014; Kobayashi, Wardle, Wolf, & von Wagner, 2016), motives to exercise (Biedenweg et al., 2014; Cleland et al., 2015; Schutzer & Graves, 2004; Patay et al., 2015), perceived health (Li et al., 2014; Meng & D’Arcy, 2013), physical activity (Enríquez-Reyna et al., 2016; Ferrand et al., 2013; Patel et al., 2013; Troutman & Staples, 2014), and well-being (Ferrand et al., 2013: Fox et al., 2007).
those obtained by authors like Kolt et al. (2004) and Patel et al. (2013) that have investigated the motives to practice exercise in Australian older adults samples. Kolt et al. (2004) found four main motivations for exercising: health, fitness, enjoyment of the activity, and relaxation. These four motives resemble our classes, as they were medical/health reasons, leisure (which includes the enjoyment and relaxation motives) and fit. Also very similar to current classes were the main motives found by Patel et al. (2013): enjoyment; health and medical reasons; and wanting to be physically active. In a qualitative study, Costello, Kafchinski, Vrazel and Sullivan (2011) with American older adults found that active people listed a number of motivators for exercising that could be grouped into categories. Specifically, the categories they made were health concerns, socialization, staff and programming, accessibility, facilities and physician encouragement. Health concerns and physician encouragement would group into the class of medical advice/ health, whereas socialization would integrate the leisure/sport class. Also with an American sample of 645 old people, Dacey, Baltzell and Zaichkowsky (2008) studied how motivators for exercising grouped together with an Exploratory Factor Analysis (EFA) of the EMI-2 scale. They found a solution of six factors: health and fitness; social/emotional benefits; weight management, stress management, enjoyment and appearance. Some of the factors found by Dacey et al. (2008) agree with the latent classes, even though they come from a very different type of statistical analyses, EFA that groups variables, whereas our results come from a LCA that groups peoples. Health, weight management may go under the latent class medical recommendation, social and emotional benefits are clearly similar to our leisure class, while appearance and fitness would agree with fit class. The second hypothesis was that the medical advice class would have lowers levels of successful aging as measured in the four dimensions of the SAI compared to the other two classes. Results showed that three of the four dimensions of successful aging (functional performance, intrapsychic factors, and gerotranscendence) performed in the expected direction. Spirituality was the exception in this hypothesis because the group who is motivated to exercise for medical advice has obtained higher values in spirituality than the other groups (leisure/sports, and keep fit). These results are in line with those by Troutman and Staples (2014), and Li et al. (2014). As Dahany et al. (2014) stated, spirituality is particularly important for older subjects of all cultures, and are frequently associated with improved psychological and mental well-being, and it may act as a protector against poor health. The three significant results obviously do not mean that the medical and health motives are per se the causes of lower functional performance, or worse intrapsychic factors and gerotranscendence. Probably, on the contrary, those with medical problems have poorer health and accordingly evaluate their functional performance, their mood (intrapsychic mechanism) and even their concerns about next generation (gerotranscendence) worse than those in healthier conditions. The third hypothesis stated that fitness class would have higher levels of physical activity, given that fit is an intrinsic motivation. This hypothesis has not been supported by our data, the group practicing activity for leisure/sports has obtained equal results that the group that exercise because of medical advice. The group that has obtained minor values in physical activity was the group that exercised for fitness. This result seems was not expected, especially if we consider that the practice of exercise on medical advice has been considered as both a motive and a barrier for exercising in older adults (Mathews et al., 2010). Medical and health reasons are extrinsic motivations, but apparently were strong motives to keep the old people active. The fourth hypothesis was that medical or health class would have lower levels of perceived health and life satisfaction. Indeed, the group who exercised for medical advice has had lower levels of perceived health than the other two groups (leisure/sports and keep fit). Nevertheless, in relation with life satisfaction, there were not differences between the group that exercised for medical advice and the group that exercised to be fit. These two groups showed a significantly
4.1. Practical implications From an applied perspective, the results of this study highlight the importance of motivating older people to practice exercise before having the need to do so by medical prescription. If people would practice exercise for fun throughout their lives, they would reach their old age in better physical and psychological conditions. This is important because, as Biedenweg et al. (2014) stated, the most frequently cited personal factors motivating program participation were enjoying being with others while exercising and desiring a routine that promoted accountability, and the most common barriers to participation were already getting enough exercise, not being motivated or ready, and having poor health. As Södergren (2013) stated, the major challenge with aging populations is to maintain physical and cognitive functions, quality of life and independence. 4.2. Limitations, strengths and future directions Current research has several limitations. The study sample was large, however it was not a random sample and generalization of these results is therefore limited. Additionally, our sample was also mainly female, likely due to a greater tendency for females to participate in group exercise classes, as in studies by Bopp, Peterson and Webb (2012), and Biedenweg et al. (2014). Another limitation is that the cross-sectional design does not allow for strong causal interpretation, and future longitudinal studies should seed light on potential causes and effects. Another is the relatively good health of the sample we recruited. As such, our findings may not generalize to persons in poorer health. Last, but not least, the nature of the survey research, together with the relative large number of constructs to be measured made us use a very short checklist of motives. Despite the fact that these motives were among the mostly communicated by old people to practice exercise, and the fact that our results are extremely similar to those found by other authors, it would be very interesting to replicate this type of analysis with larger scales that consider more motives as well as barriers and benefits of exercising. Among the strengths, the variety of dimensions of successful aging measured and the fact that they not only consider the biomedical perspective but also the social and psychological one. Additionally, the use of latent class analysis is relatively new to the study of motives to exercise, and this technique is a powerful person-oriented statistical technique that overcomes the limitations of purely descriptive statistics or cluster analysis. In this research, we asked the older adults for their reasons or motives to practice exercise in an open way. Future research, could investigate the older people’s motives for exercising in the framework of the self-determined motivation theory. In this sense, Dacey et al. (2008) stated that motivation can differentiate activity levels, and that an increase of intrinsic and self-determined motives is positively 48
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associated with more exercise in older adults. Knowing how the motives vary by gender and age could contribute to effective interventions for increasing older adults’ activity levels. A bulk of research on physical activity suggests that when people are autonomously motivated to exercise, they are most likely to do so. Nevertheless, further research is needed to provide a better understanding of motivational processes in older adults to maintain an active lifestyle (Ferrand et al., 2012).
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Dr. Melchor Gutiérrez is full professor of Motor Control and Learning at the Department of Educational and Developmental Psychology (University of Valencia, Spain). His main research topics are adolescents’ socialization through sports, and quality of life in older people. Dr. Pablo Calatayud is MD at the Department of Methodology for the Behavioral Sciences (Faculty of Psychology, University of Valencia, Spain). His main research topic is the influence of physical activity and exercise on successful aging. Dr. José-Manuel Tomás is full professor of Statistics at the Department of Methodology for the Behavioral Sciences. He is an expert in structural equation modeling and measurement, and has extensively published in indexed international journals on quality of life, health at work, and ageing.
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