Abstract
Aging causes various changes in body composition, which are critical implications for health and physical functioning in aging adults. The aim of this study was to explore the body composition outcomes of a qigong intervention among community-dwelling aging adults. This was a quasi-experimental study in which 90 participants were recruited. Forty-eight participants (experimental group) attended a 30-min qigong program 3 times per week for 12 weeks, whereas 42 participants (control group) continued performing their usual daily activities. The experimental group achieved a greater reduction in the fat mass percentage at the posttest, and exhibited increased fat-free mass, lean body mass percentage, and lean body mass to fat mass ratio compared with the controls. No difference between the two groups in body mass index, fat mass, and lean body mass was observed. These results indicated that the qigong intervention showed beneficial outcomes of body composition among community-dwelling aging adults.
Age-related changes in body composition (BC) have been widely reported, which are critical implications for health and physical functioning in aging adults (Bouchonville & Villareal, 2013; Brady & Straight, 2014; Carpenter et al., 2013; Ihász, Finn, Lepes, Halasi, & Szabó, 2015; Ranasinghe et al., 2013; Sakuma & Yamaguchi, 2013; Shihab et al., 2012; Silva et al., 2013). The majority of studies have found that the obesity and low muscle mass may coexist in aging adults (Gába & Přidalová, 2014; Kalyani, Corriere, & Ferrucci, 2014; N. Miljkovic, Lim, Miljkovic, & Frontera, 2015; Sakuma & Yamaguchi, 2013), and obesity and sarcopenia in the aging adults may potentiate each other, maximizing physical disability, morbidity, and mortality (Batsis, Mackenzie, Barre, Lopez-Jimenez, & Bartels, 2014; Benton, Whyte, & Dyal, 2011; Bouchonville & Villareal, 2013; Fragala, Kenny, & Kuchel, 2015; Mathus-Vliegen, 2012; Sakuma & Yamaguchi, 2013). However, physical activity (PA) is often recommended to improve physical function and potentially to prevent disability (Bann et al., 2014; Brady & Straight, 2014; King & King, 2010; Z. Miljkovic, Sporis, Vukic, Milanovic, & Pantelic, 2013).
Age-Related Body Composition
In normal aging, low muscle mass and obesity may coexist in the same person. Although body weight remains unchanged, aging is often accompanied by various changes in human BC with a substantial reduction in muscle mass, bone mineral density, and an increase in visceral fat (Amarya, Singh, & Sabharwal, 2015; Gába & Přidalová, 2014; Ihász et al., 2015; Kalyani et al., 2014; N. Miljkovic et al., 2015; Sakuma & Yamaguchi, 2013; Sillanpää et al., 2014). Between the age of 20 and 70 years, the aging progress redistributes the body proportion with an increase of fat mass (FM) and a loss of lean body mass (LBM); the losses in LBM thereby are considered one of the primary causes of progressive decline in fat-free mass (FFM; Amarya et al., 2015; Kalyani et al., 2014; Prado & Heymsfield, 2014; Sakuma & Yamaguchi, 2013; Sillanpää et al., 2014; Wells & Fewtrell, 2006). Therefore, BC changes associated with aging often occur in the absence of weight fluctuations (Kalyani et al., 2014; Sillanpää et al., 2014).
Body Composition Measurement
Accurate measurement of BC is a valuable evaluative/diagnostic tool to assess health-related biological processes, maturation, aging, and physical training. Thus, it is important to understand what exactly is BC (Sillanpää et al., 2014). To date, body mass index (BMI) is the best available anthropometric estimate of body fatness for public health purposes (Bhurosy & Jeewon, 2013; Nikolaidis, 2013). Nonetheless, BMI may not accurately measure specific shifts between lean and adipose tissues (Bhurosy & Jeewon, 2013; Franco-Villoria et al., 2016; Prado & Heymsfield, 2014).
The BC refers to the amounts/proportions of fat and lean tissues in the body, which is composed of two major types of mass: FM and FFM (Bouchonville & Villareal, 2013; Muralidhara, Ramesh Bhat, & Naveed Ahmed, 2009). FM is calculated by subtracting FFM from the total body weight (Birzniece, Khaw, Nelson, Meinhardt, & Ho, 2015). FFM primarily consists of LBM and bone mineral content (Bouchonville & Villareal, 2013; Fosson, 2012; Jiang et al., 2015; Khalil, Mohktar, & Ibrahim, 2014; Mialich, Sicchieri, & Junior, 2014; Muralidhara et al., 2009; Prado & Heymsfield, 2014).
Typically, evaluation of BC in health care includes an estimate of the FM and FFM and/or fat distributions (Amarya et al., 2015; Kalyani et al., 2014; Prado & Heymsfield, 2014; Sakuma & Yamaguchi, 2013; Sillanpää et al., 2014). Whereas, the FM distribution pattern in aging adults is characterized by the accumulation of fat, especially in the visceral fat and abdominal region (Franco-Villoria et al., 2016; Nikolic et al., 2014; Sakuma & Yamaguchi, 2013). Moreover, the changes in body mass in adults are subjective to retention of skeletal muscle, accumulation of fat storage, and alterations in the composition of bone and organ density (Ihász et al., 2015).
As described above, FFM and FM may be difficult to interpret individually. Furthermore, LBM/FM ratio as a parameter also considers the potential inter-relationship between these BC compartments rather than the absolute amount of each compartment (Prado, Wells, Smith, Stephan, & Siervo, 2012).
Aging and Physical Activity
Aging adults are the most sedentary segment of society, which is associated with poor health and physical function (Chastin et al., 2015; Chastin, Fitzpatrick, Andrews, & DiCroce, 2014). Many factors contributing to age-related loss of muscle mass and strength have been suggested, with physical inactivity probably being the most important. Regular PA has been consistently shown to be a feasible and effective intervention not only for counteracting muscle weakness and physical disability but also for improving muscle mass, strength, and physical functioning (Bouchonville & Villareal, 2013; Brady & Straight, 2014; Fragala et al., 2015; Leask, Harvey, Skelton, & Chastin, 2015; Zaccagni, Barbieri, & Gualdi-Russo, 2014). Furthermore, PA has also been shown to affect BC by promoting fat loss, maintaining, and/or increasing lean mass (Zanovec, Lakkakula, Johnson, & Tuuri, 2009). A systematic review of the literature also indicated that moderate to higher levels of activity are effective program to reduce risk of functional limitations and disability in older age (Paterson & Warburton, 2010). Moreover, numerous studies have reported that both traditional strength training and high-velocity training significantly improve muscle strength and muscle power in healthy community-dwelling adults (Henwood, Riek, & Taaffe, 2008; Lohne-Seiler, Torstveit, & Anderssen, 2013). Contrastingly, comparisons of traditional resistance training and high-velocity training in aging adults largely indicate that high-velocity training may be more effective for improving physical function. It is worth noting that moderate-intensity PA (e.g., normal walking or gardening) sustained for a moderate-to-high duration can reduce functional limitations by 50% in older adults (Paterson & Warburton, 2010), and resistance-training interventions can significantly improve muscle strength and muscle power in older adults (Brady & Straight, 2014). Specifically, the combination of progressive resistance training and aerobic exercise results in maximum benefits to weight loss, skeletal muscle mass, and strength gain (Davidson et al., 2009). Sedentary adults have lower bone mineral density than adults who are physically active. Moderate-intensity resistance training also shows beneficial for increasing bone mineral content (Yilmaz, 2014). However, statistics indicate that only 51.1% and 21.9% of older adults meet the aerobic and resistance-training guidelines, respectively (Brady & Straight, 2014). Overall, a majority of the PA or exercise examined in these studies required moderate to higher levels of physical fitness, yet older adults experienced difficulty in learning these exercises (Heydari, Freund, & Boutcher, 2012; Paterson & Warburton, 2010; Sakuma & Yamaguchi, 2013).
Master Sheng Yen of Dharma Drum Mountain developed a type of qigong eight-form moving meditation (EFMM; Figure 1; Dharma Drum Retreat Center, 2013) in which Chen-style Tai Chi Chuan is incorporated into a series of simple physical exercises. EFMM is a low-impact, low-intensity qigong practice that is easy to learn and can be practiced at almost any location and at any time. Therefore, EFMM is a highly suitable exercise for aging adults (M.-Y. Chang, 2015; M.-Y. Chang, Lin, et al., 2013; M.-Y. Chang, Yeh, Chu, Wu, & Huang, 2013).
Dharma Drum’s eight-form moving meditation.
Purpose
The purpose of this study was to explore the absolute body components (FFM, FM, LBM) and relative body components (FM%, LBM%, LBM/FM) changes in participants as the outcomes of a qigong intervention among community-dwelling aging adults.
Method
Design
A time-series (two-group pretest–posttest) quasi-experimental design was used, and potential participants who met the study criteria were informed of the research purposes, intervention benefits and risks, procedures, and instruments that would be used. Furthermore, the participants were assured that their identities and measurement data would remain confidential, and the participants were informed of their right to withdraw from the study at any time. The Institutional Review Board of the National Taipei University of Nursing and Health Sciences (No. S2011-06-0003) approved the study protocol. Before the study was conducted, a signed form of consent was obtained from all participants.
Participants
This study used a nonprobability sampling method and was conducted at a community center in Taipei City. Information about the research was distributed through flyers and brochures. Criteria for including participants were having intact cognitive ability, being able to walk, and having no neuromuscular disease. The exclusion criteria included cardiac arrhythmia and any type of thyroid dysfunction. Furthermore, participants with diseases such as severe arthritis or mental illness that might impede their participation were also excluded.
The Longpower method was used to calculate the longitudinal data for the generalized estimating equations (GEEs; Diggle, Heagerty, Liang, & Zeger, 2002). The largest sample size calculation, based on parameters of alpha = .05 (two-sided) and β = .20, yielded a sample size of 43 in each group. There was an estimated 15% dropout rate. The calculated sample size was 50 in each group. In the current study, 42 participants were in the intervention group and 48 in the control group. Group assignment was determined based on whether the participants were able to attend a 12-week EFMM program session. However, two participants from the control group dropped out because of conflicts with their work schedule. In the experimental group, eight participants had no motivation to complete the follow-up interventions, and the final sample comprised 42 experimental group participants and 48 control group participants. Figure 2 shows a consort flow diagram.
Consort flowchart of this study.
Intervention
EFMM is a simple physical exercise as well as a type of moving meditation. The following principles guided trainers’ breathing practice: relaxation of the mind, transfer of the mind to the body during the movement exercise, and awareness of breathing. The forms of EFMM include waist rotation with swinging arms, neck exercises, hip rotation, back stretching and bending, swinging and bending, upper body rotation, knee exercises, and stretching sideways (M.-Y. Chang, Lin, et al., 2013; Gába et al., 2009). Figure 1 shows the forms of EFMM.
The intervention was led and taught by a certified instructor of Dharma Drum Mountain. First, the participants in the EFMM group attended a 2-hr group class in a university stadium. Afterward, each participant was allocated time to practice under the guidance of the instructor to ensure the procedures of EFMM were properly applied. Finally, the participants of EFMM group were provided a standardized education booklet with the DVD, and practiced 3 times a week (sessions lasting more than 30 min) for up to 12 weeks in their homes. Moreover, exercise diaries were used to record data concerning the EFMM sessions. The researcher provided telephone access in case the participants in the experimental group had any inquiries or questions about EFMM practice to support the engagement of the participants in the home-based exercise program. The participants in the control group continued their routine daily activities and did not participate in any new exercise programs. During the intervention period of the longitudinal study, in the EFMM group, eight participants left the study: six because of conflicts with their work schedule and two because of moving out of the community. In the control group, two withdrew due to physical discomfort. In total, 84% of the intervention individuals and 96% of the control individuals completed the study.
Measurements
All measurements for the participants in both groups were conducted at baseline and after a 12-week intervention in a university laboratory maintained at 24°C. In addition, participants were asked not to consume caffeine, tea, or alcoholic beverages for 24 hr, and were instructed to rest quietly for 30 min before measurement (Shalileh, Shidfar, Haghani, Eghtesadi, & Heydari, 2010).
Body Mass Index
The BMI is one of the most commonly used measures for estimating the percentage of body fat as well as for indicating health status and predicting obesity risk, which is calculated as body weight divided by height squared (kg/m2)
Body Composition
Bioelectrical impedance analysis (BIA) is a widely used method for estimating BC, and which provides a valid and reliable measure of BC in clinical and research settings (Diniz Araújo, Coelho Cabral, Kruze Grande de Arruda, Siqueira Tavares Falcão, & Silva Diniz, 2012; Khalil et al., 2014; Saragat et al., 2014). BC consists of absolute (kg of the whole body mass) and relative (% of the whole body mass) amounts of muscle, bone and fat tissues, water, minerals, and other components of total body mass (Nikolic et al., 2014; Yilmaz, 2014).
The equations for calculating BC are expressed as follows (Esposito, Coutsoudis, Visser, & Kindra, 2008; Ryu, Jeong, & Ryu, 2010):
Data Analysis
Data were summarized as the mean and SD for continuous variables and as proportions for categorical variables. The Student’s t test and chi-square test were used to analyze group differences. Furthermore, to explore the BC outcomes of a qigong intervention among community-dwelling aging adults, we used a GEE model to estimate the differences in the BMI, FM, FFM, LBM, LBM/FM ratio, FM%, and FFM% values between the two groups at each time point as well as the time trend after intervention. The GEE approach was used because it is a crucial method for analyzing longitudinal data obtained from participants that were measured at different points in time. Both the GEE and the maximum likelihood approach are suitable for analyzing continuous and discrete outcome variables without making distribution assumptions regarding response variables (Oh, Carriere, & Park, 2008). A p value ≤ .05 indicated statistical significance. All statistical analyses were performed using SPSS 20.0 for Windows.
Results
Baseline Characteristics of the Participants
On completion of the participant-selection process, this study enrolled 90 participants. The experimental group comprised 42 participants (65.14 ± 6.16 years and 55.77 ± 7.56 Kg), and the control group comprised 48 participants (66.92 ± 7.39 years and 59.00 ± 9.60 Kg). No statistically significant differences between the two groups in age, body weight, and regular exercise habits were observed (Table 1). In addition, no significant differences in the BMI, FM, FFM, LBM, LBM/FM ratio, FM%, and FFM% were observed between the experimental and control groups at the baseline (Table 2).
Demographic Characteristics of the Participants (N = 90).
Comparisons of the Experimental Group and the Control Group in Body Composition Analysis (N = 90).
Note. BMI = Body Mass Index; FFM = Fat-Free Mass; Kg = Kilogram.
Analysis of the Effect of the Eight-Form Moving Meditation Program on Body Mass Index Parameters
The average pre-test and posttest BMI levels in the experimental group were 22.39 points and 24.09 points, respectively (Table 2). However, the GEE was used to evaluate the differences after we controlled for the potential effects of sex on the BMI. Table 3 shows that no statistically significant differences in the BMI existed between the two groups (β = 25.94, p = .275).
Generalized Estimating Equation Analysis of the Effect of Eight-Form Moving Meditation Program on Body Composition Analysis Parameters (N = 90).
Note. SE = standard error; BMI = Body Mass Index; EFMM = Eight-Form Moving Meditation; FFM = Fat-Free Mass; Kg = Kilogram.
Reference group: control group.
Reference group: time (pre-test).
Reference group: Group (control) × Time (pre-test).
Analysis of the Effect of the Eight-Form Moving Meditation Program on Fat-Free Mass, Lean Body Mass, Fat Mass, and the Ratio of Lean Body Mass-to-Fat Mass
The average FFM levels in the experimental group increased from 72.53 points at the pre-test to 72.89 points after intervention (Table 2). Table 3 shows the interaction effect (group difference and time), indicating that the participants in the experimental group achieved a significantly greater increase in FFM levels at the posttest than did the participants in the control group (β = 2.00, p = .009). Furthermore, the GEE was used to evaluate the effects of the EFMM program on FM and LBM, and no differences between the groups were noted at the pre-test and the posttest (β = −0.77, p = .221 and β = 0.09, p = .897, respectively).
Effect of the Eight-Form Moving Meditation Program on the Fat Mass Percentage, Lean Body Mass Percentage, and Ratio of Lean Body Mass to Fat Mass
The average FM% fell from 27.41 points to 27.20 points in the experimental group after the intervention (Table 2). The interactive effect indicated that the participants in the experimental group achieved a significantly greater reduction only in the FM% values at the posttest compared with the participants in the control group (β = −1.80, p = .015). After the intervention, the average LBM% of the experimental group increased from 68.54 points to 68.73 points, whereas the average LBM/FM ratio of the experimental group remained the same (2.68 points vs. 2.68 points; Table 2). However, compared with the control group, the interactive effects indicated that both the LBM% and LBM/FM ratio at the posttest increased significantly (β = 82.90, p = .046 and β = 5.23, p = .024, respectively; Table 3).
Discussion
After the 12-week EFMM training program, no statistically significant differences in the BMI were observed between the two groups. However, the participants in the experimental group achieved a greater reduction in FM% at the posttest than did those in the control group. Furthermore, the participants in the experimental group exhibited increased FFM and LBM% values and LBM/FM ratios compared with the control group.
Aging is generally associated with marked changes in BC, particularly substantial reductions in FFM and muscle mass and an increase in visceral fat, even if body weight remains unaltered (Bhurosy & Jeewon, 2013). Although the results of this study differ from those of some previous studies (Ferreira, da Silva Coqueiro, Barbosa, Pinheiro, & Fernandes, 2013), they are consistent with those of recent studies and suggest that the BMI alone is not an adequate index for all target populations because of age-related body fat redistribution, especially that in older adults (Bhurosy & Jeewon, 2013; S.-H. Chang, Beason, Hunleth, & Colditz, 2012; Gába & Přidalová, 2014). Therefore, it can be assumed that the BMI is not the most appropriate index for assessing visceral fat or predicting the effects of PA, especially in aging adults.
Reducing muscle mass is an important factor of frailty, disability, and loss of independence in aging adults. Therefore, age-related losses in muscle mass present an extremely important public health issue (Sakuma & Yamaguchi, 2013). The observation that the EFMM group exhibited a higher FFM level and LBM/FM ratio compared with the control group after the 12-week program was found. However, no statistically significant difference in FM or LBM was noted between the two groups.
LBM and bone mineral density generally decrease during the aging process (S.-H. Chang et al., 2012). Furthermore, FFM (lean mass and bone mineral mass) has been linked closely with the muscle strength and mortality rate of older adults (Zhang et al., 2013). The literature supports the findings of the present study: Resistance training and high-intensity intermittent exercise can improve muscular strength through increases in FFM (Moliner-Urdiales et al., 2010; Nikolic et al., 2014). Furthermore, several studies have documented that low muscle strength is a predictor of functional limitation and physical disability in older people (Moliner-Urdiales et al., 2010; Sakuma & Yamaguchi, 2013; Sternfeld, Ngo, Satariano, & Tager, 2002). A majority of the PAs examined in the aforementioned studies required moderate- to high-intensity muscle-strengthening exercises. In contrast with previous studies, EFMM is a type of qigong comprising a set of easy-to-learn and graceful exercises (M.-Y. Chang, Lin, et al., 2013). This study confirms that EFMM is an easy and effective intervention for increasing FFM. Therefore, EFMM can be implemented to improve muscular strength and promote physical health in community-dwelling aging adults. However, our data do not directly support the association between FFM and muscle strength and specific physical health; thus, this association must be addressed in future research.
The results regarding the LBM/FM ratio are consistent with those of previous studies, which indicated that this ratio is a reliable reference index for identifying the physical fitness and health competence of elderly people (Haight, Tager, Sternfeld, Satariano, & van der Laan, 2005; Prado et al., 2012). In other words, the LBM/FM ratio rather than the absolute FM and LBM of a person is the most relevant parameter to consider when the mechanical or physiological consequences of PAs are investigated. Several studies have indicated that the beneficial effects of PA are most likely mediated through an increase in LBM relative to FM (Auyeung, Lee, Leung, Kwok, & Woo, 2013; Haight et al., 2005; Tager, Haight, Sternfeld, Yu, & van Der Laan, 2004). These results provide further support for the hypothesis that regular qigong practice can increase the LBM/FM ratio. We hypothesize that the FFM and LBM/FM ratio are sensitive indexes of BC that are related to PA and exercise. However, BC varies according age, sex, weight, height, PA level, and general health status (Kyle et al., 2001); thus, caution is required when interpreting these results.
Research has recently focused on patterns of body fat distribution rather than amounts of fat (Zamboni et al., 1997). In the present study, the experimental group achieved a significant decrease in the FM% and a significant increase in the LBM% compared with the control group. These results are similar to those of previous studies, which reported that the FM% significantly decreased and the LBM% significantly increased after female participants partook in a 90-day conditioning program (Kumar & Mokha, 2005). In addition, a cross-sectional study indicated that an increased FM% and decreased FFM% are associated with greater functional disability in older men and women (Broadwin, Goodman-Gruen, & Slymen, 2001). These results may be attributed to the fact that some people are physically overweight but exhibit normal FM% values. By contrast, some people who are physically underweight can still exhibit an excessively high FM% because body fat distributions vary. Thus, these findings support that the relative amount of FM and LBM is a more favorable index than the absolute amounts of FM and LBM. In other words, the FM% and LBM% are favorable indicators of physical health and fitness, especially in older adults (Broadwin et al., 2001).
Overall, the results of this study yielded two major findings. First, the results indicated that the EFMM program is a suitable means for improving the BC in community-dwelling aging adults. Second, the results indicated that the FFM, FM%, LBM%, and LBM/FM ratio are more sensitive indexes than the BMI, FM, and LBM, which are suitable indicators of a healthy BC in aging adults.
The association between BC and PA and exercise can vary among population groups and is possibly mediated by exogenous characteristics. Furthermore, the measurements of body fat distribution deviate from study to study, and the various types, intensities, frequencies, and durations of exercise programs can engender diverse effects on BC indexes (Haight et al., 2005; Sakuma & Yamaguchi, 2013).
These data must be interpreted with caution because they can be influenced by the use of different BC measures, the levels and types of exercise, and biological differences in the characteristics of the participants (Haight et al., 2005; Sternfeld et al., 2002; Tager et al., 2004). Further research should be conducted to investigate validated and comparable measures and to make meaningful assumptions and comparisons with the results of other studies.
There are some limitations of the study that may provide further extension of the research. First, a nonprobability sampling method was used. Therefore, the results of this research should be interpreted with caution and cannot be generalized to the entire aging population. Thus, a large-scale longitudinal study examining the associations among the loss of muscle mass, strength, and PA in aging adults is required.
We also recommend that the measurements of body fat distribution deviate from study to study. In the result, the various types, intensities, frequencies, durations of PA, and exercise programs can engender diverse effects on BC indexes (Haight et al., 2005; Sakuma & Yamaguchi, 2013). Hence, further research should be conducted to investigate comparable measures and make meaningful assumptions to compare with the results of other studies. Finally, research is needed to establish the role of BC on determining clinical outcomes among aging adults and to provide evidence for qigong intervention aimed at preventing the onset of functional impairment and disability.
In conclusion, although these findings are based on preliminary study, they provide new insight into the positive effects of qigong (EFMM), an easy-to-accomplish training program, on BC in community-dwelling aging adults. The results of this study indicated that the relative indexes of BC, namely, the FM%, LBM%, LBM to FM ratio, and FFM, more accurately represent the various fat distributions of aging adults than does the BMI. Finally, we recommend that EFMM is a cost effectiveness of a community-based exercise program for aging adults.
Footnotes
Acknowledgements
We hereby thank all of the participants for their involvement and contribution in this study.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was partly funded by the Ministry of Education, Republic of China (Taiwan).