Abstract
Objective
To assess the association of different components of physical fitness with HRQoL in early postmenopause and to test which physical fitness components are independently associated with the physical and mental components of HRQoL.
Methods
The final sample comprised 67 early postmenopausal women. Physical fitness was assessed with the Senior Fitness Test battery (additionally including handgrip strength test), and HRQoL was evaluated with the Short-Form Health Survey-36 (SF-36). We also analyzed plasma gonadotropic hormones and estradiol.
Results
Overall, most of the fitness components were positively associated with HRQoL. Lower-body flexibility, upper-body muscle strength and cardiorespiratory fitness were the fitness components more strongly associated with HRQoL (r range from 0.28 to 0.56). Static balance was especially associated with mental health (r = −0.46, P < 0.001). Lower-body flexibility (assessed with the chair sit-and-reach test) and upper-body muscle strength (assessed with handgrip dynamometry) were independently associated with the SF-36 Physical Component Summary (both, P < 0.001). Upper-body muscle strength (P < 0.01) and cardiorespiratory fitness (assessed with the 6-min walk test, P < 0.05) were independently associated with the SF-36 Mental Component Summary.
Conclusions
Higher physical fitness is associated with better HRQoL in early postmenopause. Lower-body flexibility and upper-body muscle strength were the most important independent fitness indicators, explaining ~30 % of HRQoL.
Keywords: Functional capacity, Fitness testing, Physical health, Mental health, Flexibility, Strength, Women
Introduction
The physiological impact of menopause on women’s health has been deeply explored. Menopause increases cardiometabolic risk factors due to the significant decline in the estrogen levels and the testosterone predominance [1]. Consequently, postmenopause appears to be associated with higher incidence of metabolic syndrome and cardiovascular diseases [2–4]. These hormonal changes occurring in women during and after menopause transition may also have a relevant impact on health-related quality of life (HRQoL) [5, 6], especially at the psychological, physical and sexual spheres [7, 8]. Indeed, the postmenopausal period is also characterized by higher incidence of depressive symptoms [9]. Furthermore, early postmenopause is a relevant period in women’s life that is characterized by even a greater prevalence of vasomotor menopausal symptoms such as hot flushes, which negatively impact their HRQoL in comparison with pre-menopausal women [6].
Higher levels of physical activity are closely related to higher physical fitness [10, 11], a more favorable cardiometabolic profile [12, 13], lower levels of depression [14], lower frequency of hot flushes [15] and better HRQoL [16–18] in postmenopausal women. However, the association of different components of physical fitness with HRQoL in early postmenopause is not well documented. Since physical fitness is a multicomponent modifiable factor strongly related to health and disease in different populations [19, 20], and early postmenopause is a rather critical period in women’s health, it is important to comprehensively characterize the association of different fitness components with HRQoL in this specific population. In addition, it is also of clinical interest to address the extent to which different components of fitness (cardiorespiratory fitness, muscle strength, flexibility and balance/motor agility) are independently related to mental and physical HRQoL, which might have important implications for the development and implementation of future exercise-based intervention programs in early postmenopausal women.
The aims of the present study were: (1) to assess the association of different components of physical fitness with HRQoL in early postmenopausal women and (2) to examine which fitness components are independently related to HRQoL in this specific population.
Methods
Participants and study design
A descriptive, cross-sectional study using a convenience sample was conducted. The recruitment of participants was performed by researchers and staff from primary care centers from Granada, southeast Spain, via information panels, lectures, e-mails, letters or telephone. We recruited 198 women. All participants were informed about the aims and study procedures and signed written informed consent before taking part in the study. The general inclusion criteria were: (1) to be between 40 and 65 years old; (2) not to have acute or terminal illness or severe cognitive impairment (a score <10 in the Mini-Mental State Evaluation [MMSE] [21]); (3) lack of neuromuscular disease or drugs affecting neuromuscular function; (4) to be able to ambulate without assistance; (5) not to have suffered major cardiovascular event in the past (i.e., myocardial infarction, angina or ictus). The study was reviewed and approved by the Ethics Committee of the “Hospital Virgen de las Nieves” (Granada, Spain).
Procedures
Measurements were performed on two alternate days (e.g., Monday and Wednesday) by the same trained group of researchers. On day 1, the MMSE was performed by personal interview in a private room. Thereafter, socio-demographic (self-reported questionnaire including age, educational status and current occupational status) and clinical data were obtained. Subsequently, biochemical analysis and anthropometric and body composition parameters were assessed. Participants then received the Short-Form Health Survey-36 (SF-36) [22] to be filled at home (middle day). On day 2, the research team verified that the questionnaire was completely and correctly filled, and physical fitness was assessed.
Anthropometry and body composition
A portable eight-polar tactile-electrode bioimpedance device (InBody R20, Biospace, Seoul, Korea) was used to measure body fat percentage and muscle mass. Height (cm) was measured using a stadiometer (Seca 22, Hamburg, Germany). Body mass index (BMI) was calculated (weight[Kg]/height[m2]).
Hormonal assessments
Venous blood samples after all night fasting were collected. Immediately after the blood collections, the samples were brought to the hospital biochemical analysis laboratory, where they were centrifuged, and pipetted. Plasma luteinizing hormone (LH), follicle-stimulating hormone (FSH) and estradiol hormone concentrations were estimated using an autoanalyzer (Hitachi-Roche p800, F. Hoffmann-La Roche Ltd. Switzerland).
Health-related quality of life
We assessed HRQoL with the SF-36 [22]. The SF-36 contains 36 items grouped into 8 dimensions: physical functioning, physical role, bodily pain, general health, vitality, social functioning, emotional role and mental health. The scores range from 0 to 100 in every dimension, where higher scores indicate better health. The physical component summary (range 0–100) and the mental component summary (range 0–100) were also calculated.
Physical fitness
Physical fitness was assessed with the Senior Fitness Test battery [23] (6-min walk, chair-stand, chair sit-and-reach, back scratch and 8-foot up-and-go tests), additionally including the handgrip strength test [24] and the blind flamingo test [25].
Statistical analysis
Bivariate partial correlation (adjusted for age, BMI, educational and occupational status) was used to assess the association of the different components of physical fitness with the eight dimensions of HRQoL, as well as with the physical and mental component summary of the SF-36 (objective 1). To test which fitness component were independently associated with HRQoL (objective 2), a forward stepwise regression analysis was carried out including the physical component summary and the mental component summary of the SF-36 as dependent variables in separate models. For each of the two models, age, educational and occupational status were included and kept fixed into the model (so that potential confounding was controlled). Thereafter, the eight fitness tests were simultaneously introduced into the model using a stepwise procedure. This procedure introduces the fitness tests step-by-step into the model (when P < 0.05) according to the strength of their association with the outcome. The model is reassessed with the addition of every new fitness test and variables are left out of the model if P > 0.10.
The statistical analysis was performed with SPSS (IBM SPSS Statistics for Windows, version 20.0; Armonk, NY, USA), and the statistical significance was set at α = 0.05.
Results
One women was >65 years old, 36 did not complete or had valid data in all the physical fitness assessments, and 94 women did not met the criteria to be considered postmenopausal women (at least one year with amenorrhea and FSH > 20 mg/dL with a LH/FSH index < 0.7 or estradiol levels < 40 pg/mL). Therefore, the final study sample comprised 67 early postmenopausal women whose socio-demographic and clinical characteristics are given in Table 1.
Table 1.
Descriptive characteristics of the early postmenopausal participants (n = 67)
| Variables | Mean ± SD |
|---|---|
| Age (years) | 55.6 ± 5.0 |
| Weight (kg) | 70.3 ± 11.0 |
| Height (cm) | 155.1 ± 6.0 |
| Body mass index (kg/m2) | 30.1 ± 5.8 |
| Body fat (%) | 40.0 ± 7.0 |
| Gonadotropic hormonal profile | |
| LH (mg/dL) | 29.3 ± 12.7 |
| FSH (mg/dL) | 69.6 ± 25.8 |
| LH/FSH | 0.42 ± 0.13 |
| Estradiol (mg/dL) | 15.9 ± 15.5 |
| Physical fitness | |
| Cardiorespiratory fitness | |
| 6-min walk (m) | 501.1 ± 55.6 |
| Muscle strength | |
| Upper body | 22.7 ± 5.4 |
| Handgrip strength (kg) | |
| Lower body | 13.1 ± 3.3 |
| 30-s chair-stand (rep) | |
| Flexibility | |
| Upper body | |
| Back scratch (cm) | −6.3 ± 9.7 |
| Lower body | |
| Chair sit-and-reach (cm) | −0.5 ± 13.5 |
| Balance | |
| Dynamic/agility | |
| 8-feet up-and-go (s)# | 6.1 ± 1.2 |
| Static | |
| Blind flamingo (fails)# | 7.4 ± 4.2 |
| Health-related quality of life (SF-36) | |
| Physical functioning | 72.6 ± 30.9 |
| Emotional role | 76.2 ± 39.8 |
| Physical role | 60.4 ± 43.4 |
| Vitality | 55.5 ± 24.5 |
| Mental health | 62.7 ± 25.7 |
| Social functioning | 81.5 ± 25.4 |
| Bodily pain* | 54.8 ± 28.4 |
| General health | 56.9 ± 26.8 |
| SF-36 physical component summary | 60.8 ± 26.0 |
| SF-36 mental component summary | 69.0 ± 23.4 |
| Educational status | n (%) |
| No studies | 9 (13.4) |
| Primary school | 45 (67.2) |
| Secondary school/professional training | 6 (9.0) |
| University degree | 7 (10.4) |
| Occupational status | |
| Home worker | 26 (38.8) |
| Unemployed/retired | 28 (41.8) |
| Partial or full employed | 13 (19.4) |
SD standard deviation, BMI body mass index, LH luteinizing hormone, FSH follicle-stimulating hormone, SF-36 short-form-36 health survey
* Higher values indicate less pain
# Lower scores indicate better performance
Partial correlations after adjustment for age, BMI, educational and occupational status between physical fitness components and HRQoL (as assessed through the different SF-36 dimensions and standardized components; objective 1) are given in Table 2. Overall, higher levels of physical fitness were significantly associated with better HRQoL. Lower-body flexibility (r range from 0.31 to 0.56), upper-body muscle strength (r range from 0.28 to 0.48) and cardiorespiratory fitness (r range from 0.28 to 0.32) were the fitness components more strongly associated with HRQoL. Static balance showed a moderate association with the mental health subscale of the SF-36 (r = −0.46, P < 0.001). Physical fitness was particularly associated with the vitality and bodily pain dimensions of the SF-36 (r range from 0.28 to 0.56).
Table 2.
Partial correlations of health-related quality of life with physical fitness in early postmenopausal women (n = 67)
| SF-36 dimensions | Muscle FITNESS | Flexibility | Balance | Cardiorespiratory fitness | |||
|---|---|---|---|---|---|---|---|
| Upper body | Lower body | Upper body | Lower body | Static | Dynamic | ||
| Handgrip strength | Chair-stand | Back scratch | Chair sit-and-reach | Blind flamingo# | 8-feet up-and-go# | 6-min walk | |
| Physical functioning | 0.289* | −.019 | 0.079 | 0.178 | −.198 | −.165 | 0.127 |
| Emotional role | 0.279* | 0.049 | 0.207 | 0.307* | −.128 | −.023 | 0.299* |
| Physical role | 0.390** | 0.235 | 0.298* | 0.524*** | −.130 | −.161 | 0.190 |
| Vitality | 0.406** | 0.222 | 0.156 | 0.476*** | −.243 | −.276* | 0.313* |
| Mental health | 0.155 | 0.056 | 0.104 | 0.239 | −.459*** | −.082 | 0.124 |
| Social functioning | 0.438** | 0.103 | 0.047 | 0.213 | −.102 | −.083 | 0.214 |
| Bodily painΨ | 0.481*** | 0.205 | 0.324* | 0.557*** | −.217 | −.217 | 0.315* |
| General health | 0.371** | 0.290* | 0.114 | 0.356** | −.164 | −.191 | 0.135 |
| Physical component summary | 0.475*** | 0.217 | 0.266 | 0.510*** | −.218 | −.224 | 0.233 |
| Mental component summary | 0.401** | 0.108 | 0.185 | 0.385** | −.271 | −.132 | 0.283* |
The models were adjusted for age, body mass index, educational status and employment status
SF-36 Short-Form Health Survey-36
* P < 0.05; ** P < 0.01; *** P < 0.001
ΨHigher values indicate less pain
#Lower scores in that test indicate better performance
The independent association of different fitness components with HRQoL (physical and mental component summary of the SF-36, objective 2) is presented in Table 3. Lower-body flexibility (assessed with the chair sit-and-reach test) and upper-body muscle strength (measured with handgrip dynamometry) were independently associated with the SF-36 physical component summary (both, P < 0.001). The final model explained 35 % of the variability of the physical component (P < 0.001). Upper-body muscle strength (P < 0.01) and cardiorespiratory fitness (assessed with the 6-min walk test, P < 0.05) were independently associated with the SF-36 mental component summary. The final model explained 27 % of the variability in mental health (P < 0.01).
Table 3.
Stepwise regression analysis assessing which fitness components were independently associated with health-related quality of life in early postmenopausal women
| β | B | SE | P | R 2 | R 2 change | P | |
|---|---|---|---|---|---|---|---|
| SF-36 physical component summary | |||||||
| Step 1 | 0.032 | 0.573 | |||||
| Age | 0.145 | 0.742 | 0.649 | 0.258 | |||
| Educational status | 0.126 | 3.040 | 3.200 | 0.345 | |||
| Occupational status | −0.038 | −0.909 | 3.129 | 0.773 | |||
| Step 2 | 0.290 | 0.258 | <0.001 | ||||
| Age | 0.152 | 0.777 | 0.561 | 0.172 | |||
| Educational status | −0.064 | −0.002 | 2.838 | 0.982 | |||
| Occupational status | 0.004 | 0.096 | 2.711 | 0.972 | |||
| Chair sit-and-reach | 0.523 | 0.988 | 0.212 | <0.001 | |||
| Step 3 | 0.349 | 0.059 | <0.001 | ||||
| Age | 0.151 | 0.773 | 0.542 | 0.159 | |||
| Educational status | 0.001 | 0.027 | 2.741 | 0.992 | |||
| Occupational status | −0.020 | −0.474 | 2.630 | 0.858 | |||
| Chair sit-and-reach | 0.377 | 0.713 | 0.236 | 0.004 | |||
| Handgrip strength | 0.283 | −13.313 | 0.598 | 0.025 | |||
| SF-36 mental component summary | |||||||
| Step 1 | 0.275 | 0.643 | |||||
| Age | 0.108 | 0.480 | 0.480 | 0.401 | |||
| Educational status | 0.129 | 2.704 | 2.794 | 0.337 | |||
| Occupational status | −0.091 | 2.737 | −1.885 | 0.493 | |||
| Step 2 | 0.194 | 0.167 | 0.011 | ||||
| Age | 0.109 | 0.488 | 0.522 | 0.350 | |||
| Educational status | 0.082 | 1.724 | 2.580 | 0.507 | |||
| Occupational status | −0.109 | −2.254 | 2.514 | 0.374 | |||
| Handgrip strength | 0.412 | 1.750 | 0.497 | 0.001 | |||
| Step 3 | 0.266 | 0.072 | 0.002 | ||||
| Age | 0.165 | 0.739 | 0.513 | 0.155 | |||
| Educational status | −0.034 | −0.719 | 2.685 | 0.790 | |||
| Occupational status | −0.059 | −1.216 | 2.459 | 0.623 | |||
| Handgrip strength | 0.361 | 1.533 | 0.487 | 0.003 | |||
| 6-min walk | 0.304 | 0.125 | 0.052 | 0.020 | |||
SF-36 Short-Form Health Survey-36, SE standard error, CI confidence interval, β standardized regression coefficient, B nonstandardized regression coefficient, R 2 adjusted coefficient of determination, expressing the percent variability of the dependent variable explained by each model, R 2 change, additional percent variability explained by the model due to the inclusion of the new term
Discussion
The main findings of the present study indicate that higher physical fitness is consistently associated with better HRQoL in early postmenopausal women, regardless of the fitness component evaluated. Lower-body flexibility (assessed with the chair sit-and-reach test), followed by upper-body muscle strength (measured with handgrip dynamometry), were the fitness components more strongly associated with HRQoL. Lower-body flexibility and upper-body muscle strength were independently associated with the SF-36 physical component summary and both explained 35 % of the variability in physical HRQoL. Upper-body muscle strength and cardiorespiratory fitness (assessed with the 6-min walk test) were independently associated with the SF-36 mental component summary and both explained 27 % of the variability in mental HRQoL.
Our data support previous findings reporting that physical fitness is positively associated with HRQoL in postmenopausal women [23, 26–29] and extends current knowledge on the association of different fitness components with specific dimensions of HRQoL in this specific population. We observed a noticeable association of lower-body flexibility (as measured with the chair sit-and-reach test) with most of the SF-36 dimensions. Moreover, the score obtained in this test was an independent indicator of the physical component of HRQoL. On the other hand, upper-body flexibility only correlated with SF-36-bodily pain. A potential explanatory hypothesis for the great associations found between lower-body flexibility and HRQoL is that lower-body flexibility is clearly associated with bodily functionality, a key factor for better reliance, assertiveness, esteem, independence, confidence feelings and, consequently, better HRQoL [30].
Another major finding of the present study was the relatively strong relationships of upper-body muscle strength (measured with the handgrip strength test) with almost all physical and mental dimensions of HRQoL. Although muscle strength has been widely linked to better physical health and longevity [31], its relationship with HRQoL has not been studied in detail. Although not consistent [32], previous studies have shown concomitant improvements in muscle strength and HRQoL following an exercise-based intervention program [33] and our results supports a potential important role for upper-body muscle strength on HRQoL in this period of women’s life.
We also found a positive and independent relationship between cardiorespiratory fitness (assessed with the 6-min walk test) and the mental component summary of the SF-36. Previous studies have demonstrated the important cardioprotective effect of cardiorespiratory fitness in midlife women [31, 34]. Notwithstanding, no prior study has analyzed the relationship of this test with mental health components of HRQoL in postmenopause, which warrants further research.
Postmenopausal women usually experience higher anxiety and depressive symptoms [9, 35], so it is important to highlight that static balance showed a marked association with the SF-36-mental health dimension and with the SF-36 mental component summary. Balance requires concentration as well as mental equilibrium, which could partially explain this strong relationship. Moreover, the early postmenopausal period is also characterized by decreases in attention/working memory, verbal learning, verbal memory and fine motor speed [36]. Indeed, not only cardiorespiratory fitness and muscle strength but also motor fitness including movement speed, balance, motor coordination and flexibility is associated with cognitive functioning and brain activation patterns [37]. Hence, these data may suggest that exercise programs focused on enhancing flexibility, motor agility and balance in early postmenopause are mandatory in order to concurrently improve the physical and mental components of HRQoL. Indeed, exercise modalities such as yoga or Tai-Chi, where flexibility and balance activities are performed simultaneously, have shown beneficial effects on HRQoL [38–41].
This study has limitations. The sample size was relatively small and the cross-sectional design does not allow establishing causal relationships. However, physical fitness has been consistently associated with health-related benefits in different populations and it is likely that enhancing fitness might induce improvements in HRQoL. On the other hand, we contrasted the postmenopausal status through hormonal assessments, and we focused on the early stage of postmenopause, which constitutes a complicated physical and psychological period of women’s life [6]. Therefore, our results might have implications for the development of exercise-based intervention studies in postmenopausal women, with special focus on enhancing specific fitness components.
Conclusions
The findings of the present study indicate that physical fitness is directly and consistently associated with mental and physical dimensions of HRQoL in early postmenopausal women. Lower-body flexibility and upper-body muscle strength were independently associated with the SF-36 physical component summary and both explained ~35 % of the variability in physical HRQoL. Upper-body muscle strength and cardiorespiratory fitness were independently associated with the SF-36 mental component summary and both explained ~27 % of the variability in mental HRQoL. The results from the present study could facilitate the improvement of exercise-based preventive and treatment strategies to improve HRQoL in the early stage following the menopause transition.
Acknowledgments
This study was funded by the Ministry of Health of the Andalusian Junta, Spain (PI-0339/2008). Dr. Virginia A. Aparicio was supported by the Andalucía Talent Hub Program launched by the Andalusian Knowledge Agency, co-funded by the European Union’s Seventh Framework Program, Marie Skłodowska-Curie actions (COFUND–Grant Agreement Number 291780), and the Ministry of Economy, Innovation, Science and Employment of the Junta de Andalucía, Spain. Dr. Alberto Soriano-Maldonado was supported by the Spanish Ministry of Education, Culture and Sport (Grant Number: FPU12/00963).
Compliance with ethical standards
Conflicts of interest
The authors declare that they have no conflict of interests.
Ethical approval
All procedures performed in this study were reviewed and approved by the Ethics Committee of the “Hospital Virgen de las Nieves” (Granada, Spain) and were done in accordance with the 1964 Helsinki Declaration and its later amendments.
References
- 1.Ramezani Tehrani F, Behboudi-Gandevani S, Ghanbarian A, Azizi F. Effect of menopause on cardiovascular disease and its risk factors: A 9-year follow-up study. Climacteric. 2014;17(2):164–172. doi: 10.3109/13697137.2013.828197. [DOI] [PubMed] [Google Scholar]
- 2.Figueroa-Vega N, Moreno-Frias C, Malacara JM. Alterations in adhesion molecules, pro-inflammatory cytokines and cell-derived microparticles contribute to intima-media thickness and symptoms in postmenopausal women. PLoS One. 2015;10(5):e0120990. doi: 10.1371/journal.pone.0120990. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Cagnacci A, Cannoletta M, Palma F, Bellafronte M, Romani C, Palmieri B. Relation between oxidative stress and climacteric symptoms in early postmenopausal women. Climacteric. 2015;18:631–636. doi: 10.3109/13697137.2014.999659. [DOI] [PubMed] [Google Scholar]
- 4.Janssen I, Powell LH, Crawford S, Lasley B, Sutton-Tyrrell K. Menopause and the metabolic syndrome: The Study of Women’s Health Across the Nation. Archives of Internal Medicine. 2008;168(14):1568–1575. doi: 10.1001/archinte.168.14.1568. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Blumel JE, Castelo-Branco C, Binfa L, Gramegna G, Tacla X, Aracena B, Cumsille MA, Sanjuan A. Quality of life after the menopause: A population study. Maturitas. 2000;34(1):17–23. doi: 10.1016/S0378-5122(99)00081-X. [DOI] [PubMed] [Google Scholar]
- 6.Mohammadalizadeh Charandabi S, Rezaei N, Hakimi S, Montazeri A, Taheri S, Taghinejad H, Sayehmiri K. Quality of life of postmenopausal women and their spouses: A community-based study. Iranian Red Crescent Medical Journal. 2015;17(3):e21599. doi: 10.5812/ircmj.21599. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Taavoni S, Ekbatani NN, Haghani H. Postmenopausal Women’s Quality of Sleep and its Related Factors. Journal of Midlife Health. 2015;6(1):21–25. doi: 10.4103/0976-7800.153611. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Barton DL, Ganz PA. Symptoms: Menopause, infertility, and sexual health. Advances in Experimental Medicine and Biology. 2015;862:115–141. doi: 10.1007/978-3-319-16366-6_9. [DOI] [PubMed] [Google Scholar]
- 9.Tsiligianni IG, Tyrovolas S, Bountziouka V, Zeimbekis A, Gotsis E, Metallinos G, Tyrovola D, Polychronopoulos E, Lionis C, Panagiotakos D. Depressive symptoms in postmenopausal women: results from the MEDIS Study. Women and Health. 2014;54(5):389–401. doi: 10.1080/03630242.2014.897678. [DOI] [PubMed] [Google Scholar]
- 10.Teoman N, Ozcan A, Acar B. The effect of exercise on physical fitness and quality of life in postmenopausal women. Maturitas. 2004;47(1):71–77. doi: 10.1016/S0378-5122(03)00241-X. [DOI] [PubMed] [Google Scholar]
- 11.Ward-Ritacco CL, Adrian AL, Johnson MA, Rogers LQ, Evans EM. Adiposity, physical activity, and muscle quality are independently related to physical function performance in middle-aged postmenopausal women. Menopause. 2014;21(10):1114–1121. doi: 10.1097/GME.0000000000000225. [DOI] [PubMed] [Google Scholar]
- 12.Gudmundsdottir SL, Flanders WD, Augestad LB. Physical activity and cardiovascular risk factors at menopause: The Nord-Trondelag health study. Climacteric. 2013;16(4):438–446. doi: 10.3109/13697137.2013.768231. [DOI] [PubMed] [Google Scholar]
- 13.Barnett F. Do physical activity levels influence the cardiovascular-related physiological characteristics of postmenopausal women? Australasian Journal of Ageing. 2009;28(4):216–218. doi: 10.1111/j.1741-6612.2009.00389.x. [DOI] [PubMed] [Google Scholar]
- 14.Bernard P, Ninot G, Bernard PL, Picot MC, Jaussent A, Tallon G, Blain H. Effects of a six-month walking intervention on depression in inactive post-menopausal women: A randomized controlled trial. Aging and Mental Health. 2014;19:485–492. doi: 10.1080/13607863.2014.948806. [DOI] [PubMed] [Google Scholar]
- 15.Luoto R, Moilanen J, Heinonen R, Mikkola T, Raitanen J, Tomas E, Ojala K, Mansikkamaki K, Nygard CH. Effect of aerobic training on hot flushes and quality of life—a randomized controlled trial. Annals of Medicine. 2012;44(6):616–626. doi: 10.3109/07853890.2011.583674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Moilanen JM, Aalto AM, Raitanen J, Hemminki E, Aro AR, Luoto R. Physical activity and change in quality of life during menopause—an 8-year follow-up study. Health Qual Life Outcomes. 2012;10(8):1–7. doi: 10.1186/1477-7525-10-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Sanchez-Villegas A, Ara I, Dierssen T, de la Fuente C, Ruano C, Martinez-Gonzalez MA. Physical activity during leisure time and quality of life in a Spanish cohort: SUN (Seguimiento Universidad de Navarra) project. British Journal of Sports Medicine. 2012;46(6):443–448. doi: 10.1136/bjsm.2010.081836. [DOI] [PubMed] [Google Scholar]
- 18.Vuillemin A, Boini S, Bertrais S, Tessier S, Oppert JM, Hercberg S, Guillemin F, Briancon S. Leisure time physical activity and health-related quality of life. Preventive Medicine. 2005;41(2):562–569. doi: 10.1016/j.ypmed.2005.01.006. [DOI] [PubMed] [Google Scholar]
- 19.Barry VW, Baruth M, Beets MW, Durstine JL, Liu J, Blair SN. Fitness versus fatness on all-cause mortality: A meta-analysis. Progress in Cardiovascular Diseases. 2014;56(4):382–390. doi: 10.1016/j.pcad.2013.09.002. [DOI] [PubMed] [Google Scholar]
- 20.Sui X, Li H, Zhang J, Chen L, Zhu L, Blair SN. Percentage of deaths attributable to poor cardiovascular health lifestyle factors: Findings from the Aerobics Center Longitudinal Study. Epidemiology Research International. 2013;2013:437465. doi: 10.1155/2013/437465. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research. 1975;12(3):189–198. doi: 10.1016/0022-3956(75)90026-6. [DOI] [PubMed] [Google Scholar]
- 22.Alonso J, Prieto L, Anto JM. The Spanish version of the SF-36 Health Survey (the SF-36 health questionnaire): an instrument for measuring clinical results. Medicina Clínica (Barc) 1995;104(20):771–776. [PubMed] [Google Scholar]
- 23.Rikli RE, Jones CJ. Development and validation of a functional fitness test for community-residing older adults. Journal of Aging and Physical Activity. 1999;7:129–161. doi: 10.1123/japa.7.2.129. [DOI] [Google Scholar]
- 24.Ruiz-Ruiz J, Mesa JL, Gutiérrez A, Castillo MJ. Hand size influences optimal grip span in women but not in men. The Journal of Hand Surgery. 2002;27(5):897–901. doi: 10.1053/jhsu.2002.34315. [DOI] [PubMed] [Google Scholar]
- 25.Rodriguez FA, Gusi N, Valenzuela A, Nacher S, Nogues J, Marina M. Evaluation of health-related fitness in adults (I): Background and protocols of the AFISAL-INEFC Battery [in Spanish] Apunts Educacion Fisica y Deportes. 1998;52:54–76. [Google Scholar]
- 26.Hsu WH, Chen CL, Kuo LT, Fan CH, Lee MS, Hsu RW. The relationship between health-related fitness and quality of life in postmenopausal women from Southern Taiwan. Clinical Interventions in Aging. 2014;9:1573–1579. doi: 10.2147/CIA.S66310. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Karelis AD, Fontaine J, Messier V, Messier L, Blanchard C, Rabasa-Lhoret R, Strychar I. Psychosocial correlates of cardiorespiratory fitness and muscle strength in overweight and obese post-menopausal women: A MONET study. Journal of Sports Sciences. 2008;26(9):935–940. doi: 10.1080/02640410801885958. [DOI] [PubMed] [Google Scholar]
- 28.Chan OY, van Houwelingen AH, Gussekloo J, Blom JW, den Elzen WP. Comparison of quadriceps strength and handgrip strength in their association with health outcomes in older adults in primary care. Age (Dordrecht) 2014;36(5):9714. doi: 10.1007/s11357-014-9714-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Olivares PR, Gusi N, Prieto J, Hernandez-Mocholi MA. Fitness and health-related quality of life dimensions in community-dwelling middle aged and older adults. Health and Quality of Life Outcomes. 2011;9:117. doi: 10.1186/1477-7525-9-117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Frank AM, McConnell TR, Rawson ES, Fradkin A. Clinical and functional predictors of health-related quality of life during cardiac rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention. 2011;31(4):223–229. doi: 10.1097/HCR.0b013e31820333b3. [DOI] [PubMed] [Google Scholar]
- 31.Kishimoto H, Hata J, Ninomiya T, Nemeth H, Hirakawa Y, Yoshida D, Kumagai S, Kitazono T, Kiyohara Y. Midlife and late-life handgrip strength and risk of cause-specific death in a general Japanese population: the Hisayama Study. Journal of Epidemiology and Community Health. 2014;68(7):663–668. doi: 10.1136/jech-2013-203611. [DOI] [PubMed] [Google Scholar]
- 32.Bonganha V, Modeneze DM, Madruga VA, Vilarta R. Effects of resistance training (RT) on body composition, muscle strength and quality of life (QoL) in postmenopausal life. Archives of Gerontology and Geriatrics. 2012;54(2):361–365. doi: 10.1016/j.archger.2011.04.006. [DOI] [PubMed] [Google Scholar]
- 33.Agil A, Abike F, Daskapan A, Alaca R, Tuzun H. Short-term exercise approaches on menopausal symptoms, psychological health, and quality of life in postmenopausal women. Obstetrics and Gynecology International. 2010;2010:274261. doi: 10.1155/2010/274261. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Aparicio VA, Carbonell-Baeza A, Senhaji M, Martin S, Camiletti-Moiron D, Aranda P. Usefulness of fitness testing to establish metabolic syndrome in perimenopausal Moroccan women. European Journal of Cardiovascular Nursing. 2013;13(6):524–531. doi: 10.1177/1474515113516395. [DOI] [PubMed] [Google Scholar]
- 35.Ibrahim ZM, Sayed Ahmed WA, El-Hamid SA. Prevalence of menopausal related symptoms and their impact on quality of life among Egyptian women. Clinical and Experimental Obstetrics and Gynecology. 2015;42(2):161–167. [PubMed] [Google Scholar]
- 36.Weber MT, Rubin LH, Maki PM. Cognition in perimenopause: The effect of transition stage. Menopause. 2013;20(5):511–517. doi: 10.1097/GME.0b013e31827655e5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Voelcker-Rehage C, Godde B, Staudinger UM. Physical and motor fitness are both related to cognition in old age. European Journal of Neuroscience. 2010;31(1):167–176. doi: 10.1111/j.1460-9568.2009.07014.x. [DOI] [PubMed] [Google Scholar]
- 38.Tuzun S, Aktas I, Akarirmak U, Sipahi S, Tuzun F. Yoga might be an alternative training for the quality of life and balance in postmenopausal osteoporosis. European Journal of Physical and Rehabilitation Medicine. 2010;46(1):69–72. [PubMed] [Google Scholar]
- 39.Kinser PA, Elswick RK, Kornstein S. Potential long-term effects of a mind-body intervention for women with major depressive disorder: sustained mental health improvements with a pilot yoga intervention. Archives of Psychiatric Nursing. 2014;28(6):377–383. doi: 10.1016/j.apnu.2014.08.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Kim H, Kim YL, Lee SM. Effects of therapeutic Tai Chi on balance, gait, and quality of life in chronic stroke patients. International Journal of Rehabilitation Research. 2015;38(2):156–161. doi: 10.1097/MRR.0000000000000103. [DOI] [PubMed] [Google Scholar]
- 41.Kelley GA, Kelley KS. Meditative movement therapies and health-related quality-of-life in adults: A systematic review of meta-analyses. PLoS One. 2015;10(6):e0129181. doi: 10.1371/journal.pone.0129181. [DOI] [PMC free article] [PubMed] [Google Scholar]