Sarcopenia, the age-associated loss of skeletal muscle mass, and increasing body fat mass are both hallmarks of the aging process. Sarcopenia has been cited as a major factor in strength decline (8), as well as functional impairment, disability, and loss of independence (26) with aging. In addition to loss of skeletal muscle mass, women experience bone mineral density (BMD) decreases (9) concomitant with increased central body fatness, which may promote a loss of fat-free mass during the menopausal transition. This adverse change in the ratio of fat-to-lean mass may be related to a decline in energy expenditure, loss of muscular strength, and a decline in physical activity (PA) (5,28,30). Preventing gain of fat mass and loss of skeletal muscle mass and function is preferable to trying to reverse these body composition changes in old age.
Current evidence suggests that maintaining PA over time is key to preventing these adverse age-related body composition changes associated with aging (14,20,25). Hankinson et al. (13) examined the relationship of habitual PA levels and changes in body mass index (BMI)) over a 20-yr period and observed that those individuals, particularly women, who reported high levels of PA through young adulthood experienced less weight gain and central adiposity through the transition to middle age. Andreoli et al. (2) examined the differences in BMD, body composition, and bone mineral content in women who had been elite athletes during their youth as compared with sedentary controls and observed that long-term PA significantly improved BMD and muscle mass, with a reduction in the adverse aging affects on body composition.
The Women’s Health Study reported that PA was associated with less weight gain only in women with BMI lower than 25 kg·m−2 (17). We recently reported a significant interaction of age and initial (baseline) PA in relation to weight changes over an 8-yr period in the large Women’s Health Initiative (WHI) clinical trial (CT) cohort (27). Among women age 50–59 yr at baseline, there was significantly less weight gain in those reporting moderate (>500 to 1200 MET·min·wk−1) and high (>1200 MET·min·wk−1) levels of PA compared with sedentary women (≤100 MET·min·wk−1), whereas among women age 70–79 yr, higher PA (>1200 MET·min·wk−1) was associated with significantly less weight loss, compared with those who reported sedentary, low, or moderate activity (27).
Only total weight changes were investigated in these earlier reports; however, healthy weight management should emphasize the prevention of fat mass gain and lean mass loss, both of which are believed to be favorably influenced by PA (11,31). Furthermore, prior analyses have focused on baseline PA, without taking into account changes in activity level during follow-up. The availability of dual-energy x-ray absorptiometry (DXA) data from a subgroup (the DXA cohort) of the large WHI cohort provided the opportunity to extend our investigation of the relationship of PA to weight changes to focus on changes in body composition over a 6-yr follow-up period, in relationship to changes in PA levels.
The WHI DXA cohort was drawn from three WHI clinical centers (Pittsburgh, PA; Birmingham, AL; and Tucson–Phoenix, AZ), among 40 US clinical centers that enrolled the large multiethnic cohort of 68,132 postmenopausal women into the WHI CT of diet modification (DM), hormone therapy (HT), and/or calcium plus vitamin D supplementation, as well as 93,676 women into the WHI observational study (OS) cohort, from October 1993 to December 1998. Details of recruitment, baseline data collection, and baseline characteristics of the CT and OS cohort have been published previously (15). All procedures and protocols were approved by the institutional review boards at each participating institution, and all participants provided written informed consent.
Body composition by DXA scans was assessed at baseline and after 1, 3, and 6 yr of follow-up in CT and OS participants who were randomly selected for DXA measurements at each of the three centers (total N = 11,941; OS N = 6365 and CT N = 4655). Diversity based on race/ethnicity was maximized at the WHI DXA sites. Participants who completed the baseline and at least one follow-up DXA scan postrandomization, with an accompanying PA questionnaire, were included in this analysis. The present analyses further excluded participants who had missing baseline information for variables used in statistical models, including PA, physical measures, dietary and alcohol intake, smoking status, menopausal HT use, education, and sleep information. These exclusions reduced the sample to a final analytic cohort of 8352 participants.
Body composition measurements.
Whole-body DXA (QDR2000, 2000+, or 4500W; Hologic Inc., Bedford, MA) scans were used to determine both regional and total body compositions. Measurements included bone mineral density (BMD), lean body mass (lean soft tissue mass), fat mass, and percentage of fat mass. As previously described (7), standard WHI protocols were used for the positioning and analysis of DXA scans by radiology technicians, trained and certified by Hologic and the WHI Bone Density Coordinating Center at the University of California, San Francisco.
Assessment of PA.
Recreational PA was assessed by questions on the frequency and duration of recreational activities, and MET scores (defined as the ratio of work metabolic rate to a standard resting metabolic rate, with one MET roughly equivalent to the resting metabolism while sitting quietly) were computed as the product of days per week, minutes per day, and MET value for each activity (1).
Information on walking and recreational PA was used to generate a summary variable in MET-minutes per week. Participants were asked how often they currently walked outside the home for more than 10 min without stopping and the usual duration and speed of their walks. Categories of frequency were rarely/never, one to three times per month, one time per week, two to three times per week, four to six times per week, and seven or more times per week. Duration categories were less than 20 min, 20 to 39 min, 40 to 59 min, and 1 h or more. Four speed categories were used: less than 2 mph (casual strolling or walking, 2.0 MET), 2–3 mph (average or normal walking, 3.0 MET), 3–4 mph (fairly fast walking, 4.0 MET), or more than 4 mph (very fast walking, 4.5 MET). The MET values were further calculated using the corrected MET equation (Harris–Benedict equation) to adjust the standard MET level for age, sex, height, and body weight as described in the Compendium of Physical Activities (2011).
On the basis of the questions asked, women were classified into four groups of PA levels at baseline and years 3 and 6: sedentary, i.e., reporting ≤100 MET·min·wk−1; low PA level, >100 to 500 MET·min·wk−1; moderate PA, >500 to 1200 MET·min·wk−1; and high PA, >1200 MET·min·wk−1. Achieving a minimum of 500 MET·min·wk−1 meets the current national guidelines to engage in at least 150 min·wk−1 of moderate-intensity PA, i.e., the minimum health-related dose of activity recommended by the 2008 US physical activity guidelines (32).
Assessment of other covariates.
Covariates including age, energy intake and other dietary variables, energy expenditure, ethnicity, smoking and alcohol habits, sleep duration, medications with a known effect on body composition (oral steroids, thyroid medications, and psychotropics/antidepressants), and prior HT were all assessed from baseline questionnaires. Waist/hip ratio and BMI were assessed at each clinic visit. Caloric intake was assessed using a validated food frequency questionnaire, based on instruments previously used in large-scale dietary intervention trials (6,23).
The primary outcomes were change in lean body mass and fat mass from baseline. The primary variable of interest was self-reported PA at baseline, year 3, and year 6. PA was incorporated in a time-varying fashion; for the difference in outcome at the year 1 clinical visit, baseline PA was used. Similarly, at the year 3 and year 6 visits, PA reported on year 3 and year 6 questionnaires, respectively, were used. Mixed effects linear regression techniques were used to describe the association between the primary outcomes (change in lean mass, fat mass, and BMI from baseline) and time-varying PA over the 6-yr study period. In particular, the main question of interest was whether the association between PA and change in body composition varied by age group. Thus, our main parameter of interest was an interaction between time varying in PA and age group. Our modeling approach accounted for the correlation of responses within a subject over time by including a subject-specific random intercept in the model. Estimates of the association were adjusted for the following potential confounders: years postrandomization, baseline measurement of the outcome, age group at study entry, ethnicity, education, smoking, prior and current HT usage, medications associated with body composition change (oral steroids, thyroid, and psychotropic/antidepressants), hours of sleep, total energy intake, protein intake, alcohol intake, fruit and vegetable servings per day, treatment assignment in the WHI DM trial, and scanner used for body composition measures. The hypothesis corresponding to presence of an interaction effect between time-varying MET and age group on each primary outcome was tested with a two-sided Wald test at the 0.05 level of significance. All analyses were performed using SAS 9.3 (SAS Institute Inc., Cary NC) and Stata 12 (StataCorp LP, College Station, TX).
Table 1 presents baseline sociodemographic and lifestyle characteristics of the analytic cohort by self-reported PA group, with 24.9% of participants categorized as sedentary, 29.5% as low PA level, 26.2% as moderate, and 19.5% as high. Less than half (45.6%) reported baseline PA levels that meet current recommended PA levels. Compared with the moderate and high PA groups, a greater proportion of women in the sedentary and low categories were obese, current smokers, and were distributed in the highest quartiles of waist/hip ratio.
At baseline, MET-hours per week were significantly different among the three age groups (P = 0.0004), with greater MET hours per week observed in the 70–79 yr. Fat mass, lean mass, and BMI were also significantly different across the age groups at baseline (P < 0.0001 for fat mass, lean mass, BMI) with all measures lower for older age groups (Table 2a).
Change in PA.
At year 3, 8,127 women reported their current PA (Table 2b). PA decreased by 0.06 MET·h·wk−1 from baseline levels on average (SD = 12.0). At year 6, 7457 women reported current PA with an average decrease of 0.53 MET·h·wk−1 from baseline levels (SD = 13.0). Difference in PA from baseline was significant at year 6 (P = 0.0004) but not at year 3 (P = 0.6385).
Relationships of time-varying PA on body composition
Table 3 presents results from fitting mixed effects linear regression models that adjusted for baseline MET category and other confounders mentioned previously to describe associations between time-varying PA and changes in body composition variables (lean mass, fat mass, and BMI) from baseline. For change in fat mass and BMI, the associations with time-varying PA varied by age group (P = 0.0006 and P = 0.0395, respectively). In contrast, the association between time-varying PA and change in lean mass did not vary significantly by age group (P = 0.1935). Furthermore, PA was not significantly associated with change in lean mass from baseline (P = 0.8147).
For women age 50–59, those in the sedentary MET category gained 1.11 kg of fat mass, whereas those in the most active MET category gained 0.23 kg on average over the 9 yr of follow-up. Women age 60–69 yr in the sedentary category did not gain or lose fat mass, but those in the most active category lost 0.56 kg. Women in the oldest age group (70–79 yr) all lost fat mass on average with the sedentary and most active category having a greater loss than the low and moderate activity categories. A similar pattern was observed for change in BMI from baseline on average over the 6-yr study period. Women in the 50- to 59-yr age group who reported high PA gained 0.10 kg·m−2; sedentary women in this age group gained 0.60 kg·m−2. A similar trend was observed for women age 60–69 yr; however, women age 70–79 yr all reported a loss in BMI that was similar across categories of PA. Women in all age groups lost similar amounts of lean mass across categories of PA (Fig. 1).
The current report demonstrates changes in body composition in postmenopausal women over a 6-yr period in association with time-varying PA, with higher PA levels associated with an attenuation in fat mass and BMI gain for women age 50–59 and 60–69 yr. Women in the oldest age group, however, lost fat mass and BMI at all levels of PA. Lean mass loss was not significantly associated with PA and invariant across the age groups.
Although it is generally stated that higher levels of PA attenuate fat mass gain and lean mass loss, most large studies rely on baseline measurements of PA and the projected trajectory of PA levels (3,10,12,15,22,29). The current study incorporates PA at baseline and 3 and 6 yr after follow-up; PA has decreased significantly by year 6 from baseline.
There is considerable discussion of the role of PA in preventing weight gain, in particular, the attenuation of fat mass gain, across the lifespan in the current literature on obesity (13,15,17,19,21,22,27,28,30). Although the maintenance of high levels of PA is believed to lessen weight gain, there are caveats to these data. First, it seems to be assumed that baseline activity levels persist in older adults over time (barring disease, chronic pain, or other illness), whereas the current study demonstrates that over a 6-yr period, postmenopausal women changed their habitual PA levels significantly. Furthermore, our results suggest that higher levels of PA reduce fat mass and BMI gain in women age 50–59 and 60–69 yr but not in the oldest age group, 70–79 yr. This in turn may suggest that efforts to encourage increased PA in postmenopausal women may be more effective at earlier ages.
Our data suggest that there should be greater emphasis on the maintenance of lean mass in postmenopausal women. First, the prevention of sarcopenia may attenuate risk of falls, loss of independence, and loss of physical function (8,9,12,14,16,26,33). Second, lean mass is more metabolically active and may therefore reduce the risk of cardiovascular and metabolic diseases (12,16,24,33). The current study demonstrates postmenopausal women in all age groups experience loss of lean mass as they age, invariant of PA levels. It is important to note that the PA reported in this study was primarily aerobic in nature. Especially as regards lean mass, the potential role of muscle-strengthening exercises deserves consideration. Peterson et al. (24) conducted a meta-analysis of resistance training studies among young and old adults. The evidence strongly indicated that resistance training elicits an approximate 1-kg increase in LBM among older adults. Although modest compared with the expected adaptation with healthy young adults, this increase is in contrast to the 0.18-kg annual decline that may occur through sedentary lifestyles, beyond 50 yr. Moreover, volume of training and age of participation are important determinants of effectiveness, suggesting that higher dosages result in greater adaptive response, and that aging individuals should consider starting a regimen of resistance exercise as early as possible, to optimize results. The lack of association between PA and lean mass in our cohort may be due to the majority of PA being aerobic in nature.
Lifetime PA plays a major role in the overall aging process. Booth et al. (4) describe the consequences of primary versus secondary aging. Secondary aging is defined as physiological changes that are not inevitable yet significantly alter quality of life and life expectancy. There is ample evidence that physical inactivity and, to a lesser degree, decreased PA, over the lifespan, plays a major role in “unsuccessful” aging (aging accompanied by decreased life expectancy, increased cardiometabolic risk factors, and decreased physical function with concomitant decreased skeletal muscle strength and function). Thus, the message of maintaining high and/or increasing overall aerobic and resistance training PA levels becomes fundamental in the notion of successful aging.
Strengths of this present study include the prospective design, the large size and diversity of the WHI DXA cohort, the detailed assessment of PA at multiple points during follow-up as well as sedentary behavior, long-term follow-up, and high retention rates (90.8% at 6 yr of follow-up).
Several limitations of the present analyses deserve mention. Although we controlled for a large number of potential confounding variables in our multivariable analyses, residual confounding by lifestyle-related factors cannot be excluded, and although the WHI PA questionnaire was shown to have good reliability and validity (6), self-reported PA is a limitation. The magnitude and consistency of the relations between PA and body composition across the variety of analytical approaches used here suggest that confounding by diet is not a likely explanation of the findings. An important limitation of these analyses is that adjusting for intensity and mode of exercise to demarcate resistance training from yoga-type and lower intensity aerobic exercise was not feasible due to the nature of the data collection.
In conclusion, PA levels throughout the postmenopausal years are associated with changes in BMI and fat mass, and this association differs by age group. PA was not associated with change in lean mass for all age groups. Moreover, our results reinforce the role of PA in minimizing the adverse effects of aging on body composition changes, which have been associated with improved health outcomes and successful aging.
The WHI program is funded by the National Heart, Lung, and Blood Institute; National Institutes of Health; and US Department of Health and Human Services through contracts HSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C.
The authors thank the WHI investigators and staff for their dedication and the study participants for making the program possible. A listing of WHI investigators can be found at https://cleo.whi.org/researchers/SitePAges/Write%20a%20Paper.aspx.
None of the authors of this manuscript declares any conflict of interests.
The results of the present study do not constitute endorsement by American College of Sports Medicine.
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