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Body composition changes

Body composition changes

Lean out, Nutritional value assessment Effective recovery methods, get ripped On days that you do a strength training Body composition changes compositiob 30 minutes or more, eat more Chajges than your maintenance channges with a focus on protein. Here are a few ideas: Measure your hip, waist, thigh, chest, and arm circumferences. If you include these foods in your diet, you are less likely to crave them. Bodybuilders are known for their ability to achieve incredibly lean and muscular physiques. Unlike the BMI which only considers your height and weight, factors like your age, sex, hormone levels, lifestyle habits, and genetics all play a role in your body composition.

Body composition changes -

The purpose of this study therefore was to investigate changes in fat mass and fat-free mass following four weeks of volume-equated fasted versus fed aerobic exercise in young women adhering to a hypocaloric diet. Subjects were 20 healthy young female volunteers age: This sample size was justified by a priori power analysis using a target effect size of 0.

All participants reported performing aerobic exercise several days a week on a regular basis and several were off-season collegiate track and field athletes. Individuals meeting these criteria were invited to attend a familiarization session where a complete explanation of the study was provided, and a medical history and informed consent were obtained.

Those meeting eligibility criteria and willing to participate in the study were scheduled for baseline testing. Approval for the study was obtained from the Institutional Review Board at Lehman College. Testing was carried out in the 24 48 hours prior to beginning the intervention and after the fourth week at completion of the study.

For each testing session, subjects reported to the lab in the morning following an overnight fast having refrained from vigorous physical activity, alcohol intake, or consumption of over-the-counter medications for at least 12 hours. The number of athletes and non-athletes were evenly distributed between groups.

Heart rate monitors model F7U, Polar Electro Inc, Lake Success, NY were used to ensure that exercise remained at the appropriate intensity. A low-to-moderate training intensity was used because it has been shown to maximize lipid oxidation during fasted aerobic exercise as compared to higher-training intensities [ 19 ].

All training sessions were supervised by research assistants who were upper level undergraduate students in exercise science. Subjects were instructed to refrain from performing any additional structured exercise for the duration of the study. Subjects were provided with customized dietary plans prepared by one of the researchers A.

for the length of the study. In order to facilitate weight loss, energy consumption was set so that subjects remained in a caloric deficit. The determination of energy intake was based on the Mifflin-St.

Jeor Equation, which is considered an accurate formula for estimating resting metabolic rate [ 20 ]. The formula is as follows:. The formula was multiplied by a moderate activity factor 1. Dietary protein intake was set at 1.

Sample meal plans were provided to guide the participants in acceptable food choices. Dietary plans included provision of a meal replacement shake Pursuit Recovery, Dymatize Nutrition, Dallas, TX.

The shake contained calories consisting of 40 g carbohydrate, 20 g protein, and 0. On exercise days, FED consumed the shake immediately prior to the exercise bout and FASTED consumed the shake immediately after finishing the bout. Shakes were consumed under the supervision of a research assistant to ensure adherence within the context of the subject s respective participation in the fed or fasted protocol.

Dietary adherence was assessed by self-reported food records using MyFitnessPal. com , which were collected and analyzed during on a daily basis to ensure that intake was not based on recall.

Subjects were instructed on how to properly record all food items and their respective portion sizes that were consumed for the designated period of interest. Each item of food was individually entered into the program, and the program provided relevant information as to total energy consumption, as well as amount of energy derived from proteins, fats, and carbohydrates over the length of the study.

Continued nutritional guidance was provided to the subjects at the time of each training session by the research team to encourage dietary adherence.

Height and body mass measurements were made using a double beam scale. Circumference measurements of the waist was made using an Intelametrix tape measure Intelametrix Inc.

Body mass index BMI was calculated as body mass in kg divided by height in meters squared. Percent fat mass and lean body mass was obtained via air displacement plethysmography ADP using the BodPod body composition analyzer model a, Life Measurement, Concord, CA as per the user manual and described previously in the literature [ 23 ].

ADP has been shown to have good validity in measuring body fat percentage when compared to dual x-ray absorptiometry in the sampled population [ 24 ],[ 25 ].

Subjects were tested in tight clothing either compression shorts and a sports bra or a swimsuit and Lycra swim cap. Based on body mass and volume as well as through body density, total fat mass, total fat free mass and body fat percentage were calculated by the BodPod system software.

Normality assumptions were checked using a one-sample Kolmogorov-Smirnov test; all data was found to meet normality assumptions. Independent t-tests were used to assess differences in baseline measurements between groups as well as energy and macronutrient intake over the length of the study period.

Cohen s D effect sizes were calculated for all pre- to post-study outcome measures using the following formula:. where M 1 represents the pre-study mean, M 2 represents the post study mean, and; SD represents the pooled standard deviation.

All other data was modeled using a linear mixed model estimated by a restricted maximum likelihood algorithm. Treatment was included as the between-subject factor, time was included as the repeated within-subjects factor, and time x treatment was included as the interaction.

Repeated covariance structures were specified as unstructured. All analyses were performed using S-Plus 8. Data are reported as x - ± SD. The FED group was significantly younger than the FASTED group 21 ± 1.

No other significant group differences were noted in any baseline measure. Total energy and macronutrient consumption was not different between groups over the length of the study period see Table 1.

The reported nutritional consumption for both groups was below that prescribed in the individual meal plans. Figures 1 and 2 display macronutrient percentage intake in FASTED and FED, respectively.

Pre- to post-study results for each outcome measure are presented below. Table 2 summarizes these findings.

There was no significant interaction between time and group, and there was no significant effect of group. There was no significant interaction between time and group and there was no significant effect of group.

There was no significant interaction between time and group, and no significant effect of group. There was no significant interaction between time and group, and no significant effects of group or time. It has been hypothesized that exercising when fasted forces the body to rely on using fat as a substrate rather than carbohydrate, thereby reducing body fat to a greater extent than performance of post-prandial exercise.

Our results refute the veracity of this hypothesis. Although both groups lost a significant amount of weight and fat mass, no differences were seen between conditions in any outcome measure regardless of pre-exercise feeding status.

Van Proeyen et al. Subjects performed a combination of moderately intense cycling and running exercise for 60 90 minutes, 4 days per week. After 6 weeks, the fed group significantly increased body mass by 1. Follow-up work from the same lab employing the same basic training protocol but with subjects consuming an isocaloric diet based on 4-day dietary analysis showed no differences in body weight change between fasted versus fed conditions [ 8 ].

Recently, Gillen et al. Subjects were instructed to maintain their pre-intervention eating patterns throughout the study period. At study s end, body mass remained unchanged from baseline but lower body fat was noted both in the abdominal and leg regions as well as the whole body level in both groups.

No significant differences were found between conditions. Our results are novel in that subjects consumed a supervised hypocaloric diet throughout the intervention period. Loss of body mass is predicated on shifting energy balance to favor expenditure over intake [ 3 ].

This is consistent with the First Law of Thermodynamics, which essentially states that energy is neither created nor destroyed, but rather changed from one form to another.

Thus, our approach allowed for a controlled investigation of the effects of fasted exercise on body composition under conditions favorable for fat loss.

Moreover, to optimize the proposed benefits of training while fasted, exercise was performed at low-to-moderate intensities. This is consistent with acute research showing that lipolysis is blunted during performance of higher- [ 14 ],[ 26 ] but not lower-intensity exercise when carried out in the fed state [ 10 ],[ 11 ],[ 27 ].

Despite these accommodations, fasted exercise showed no beneficial effects compared to training post-prandially. The theoretical basis behind a fat-burning advantage to fasted exercise is predicated on increasing lipid oxidation during training bout.

However, this ignores the dynamic nature of the human body, which continually adjusts its use of substrate for fuel. There is evidence that a greater utilization of fat for fuel during a given time period is compensated by a greater carbohydrate utilization later in the day [ 28 ].

Hence, fat burning must be considered over the course of days not on an hour to hour basis to meaningfully assess its impact on body composition [ 29 ]. In support of this contention, Paoli et al. Food quantity and quality was identical between conditions over the ensuing hour recovery period. Consumption of breakfast for the fed condition resulted in a significant increase in respiratory exchange ratio RER compared to fasting 0.

However, at 12 hours post-exercise RER was significantly lower in the fed versus fasting condition and the difference remained significant after 24 hours. Any potential increases in fat oxidation from fasted exercise might be neutralized by an increase in the thermic effect of exercise from eating pre-exercise.

Lee et al. Employing a within-subject design, 10 male college students performed four experimental conditions in randomized order: low intensity, long duration exercise with GM; low intensity, long duration exercise without GM; high intensity, short duration exercise with GM, and; high intensity, short duration exercise without GM.

Results showed that consumption of the GM beverage increased excess post-exercise oxygen consumption to a significantly greater extent than exercise performed while fasted in both high and low intensity conditions.

Similar findings have been reported in other controlled trials [ 32 ],[ 33 ]. The study had several notable limitations that must be taken into account when attempting to draw evidence-based conclusions.

First, the duration of the testing period was fairly short, lasting just four weeks. While this period is certainly sufficient to attain significant fat loss, it remains possible that subtle changes between protocols would take more time to manifest.

Given that mean weight loss across groups was somewhat less than anticipated, it seems reasonable to assume that subjects did in fact underreport the amount of calories consumed, which would explain the attenuated results. Similarly, although subjects were instructed not to partake in any other structured exercise other than activities of daily living, there is no way to assure that they adhered to this request.

The Japanese-specific transmenopausal slopes for weight —0. Chinese women, on the other hand, had a significantly more negative change in BMI in postmenopause than White women.

As a result, Chinese women had a significantly smaller total increase in BMI over the year period spanning the MT than did White women 4. Greater age at FMP tempered the annual gains in weight and BMI evident during premenopause i. Influence of HT on change in outcomes.

There were 11, observations in this analysis; women were taking HT at the time of of these observations. All HT use took place after the FMP occurred data not shown.

Our study quantified the longitudinal trajectories of body composition and weight prior to, during, and after the MT, with the MT operationalized as a multiyear interval straddling the FMP. For body composition, increasing fat mass and declining proportion lean mass were apparent during premenopause, prior to the onset of the MT.

Change in body composition accelerated during the MT, displaying a 2- to 4-fold increase in gain fat or loss proportion lean mass. In postmenopause, on average, we observed a stabilization of body composition a zero slope. The average patterns of change of body weight and BMI differed from those of body composition: weight and BMI climbed steadily both prior to and during the MT, without an MT-related acceleration.

Like body composition, weight did not increase further during postmenopause. In contrast, trajectories in Japanese and Chinese women were distinct from those of the White referent sample: accelerated gains in fat mass and declines in lean mass did not characterize the MT.

In Chinese women only, during postmenopause, fat mass declined, proportion lean mass increased, and weight dropped. A later age at FMP mitigated body composition changes and weight gains. Finally, body composition and weight trajectories were unaffected by HT use, but HT exposure in this analysis was uncommon and confined to postmenopause.

Our findings link the MT with unfavorable alterations in body composition, which abruptly worsen at the onset of the MT and then abate in postmenopause.

The total loss of lean mass during the MT averages 0. In concert, in the average SWAN participant, the accelerated increase in fat mass and decrease in lean mass results in a 3. Jointly examining the rates of change in fat and lean mass during premenopause and the MT sheds light on why there is no measurable change in body weight trajectory accompanying the MT.

The rate of increase in the sum of fat mass and lean mass is 0. This is not a discernable change in rate, especially if bone loss during the MT which is not incorporated in the estimation of lean mass used here further lowers the MT slope estimate.

Framed alternately, the difference in slopes between premenopause and the MT for the sum of fat mass and lean mass is only 80 grams per year, while the difference in the slope of fat mass between premenopause and the MT is grams per year and the corresponding difference for lean mass is — grams per year.

Thus, although there are MT-related effects on body composition, we observe no acceleration in weight gain at the time of the MT. However, close examination of existing evidence suggests that it is inadequate to either support or refute the hypothesis that the MT influences body composition or weight 13 — Most directly comparable to ours are studies that gauged the impact of the MT on body composition or weight by examining these characteristics in relation to FMP time 17 , 19 , Using bioelectrical impedance, Sowers and colleagues did not detect an effect of FMP time on either fat mass or lean mass in a sample of women at the Michigan SWAN site Rather, they reported a linear increase in fat mass and a small, linear decrease in lean mass over time.

To investigate the relation between FMP time and weight, Davies et al. No effect of FMP time on weight was apparent; instead, the authors described a linear increase in weight with time. Finally, in an analysis of 48 women, the MONET study found that neither weight nor BMI were influenced by FMP time and that percent fat mass was greater in the post-FMP years than it had been previously; however, but no change in percent fat was noted in the transitional phase prior to FMP.

Although each of these studies concluded that the MT did not influence body composition or weight, small samples, correspondingly few observed FMP dates, and — in one instance — long intervals between assessments constrained their ability to discover a nonlinear trajectory of body composition or weight with FMP time.

More frequently, investigators examined the relation between advancing menstrual pattern—based MT stage i. Five of these studies, including 2 from the initial years of SWAN, found that weight increased over time but was unrelated to evolving MT stage 13 — 16 , Limitations included few conversions from earlier to later MT stages and, in some cases, long spans between assessments 13 — 16 , Dissimilar to prior reports, the current analysis supports a strong, adverse influence of the MT on body composition that is manifest during the MT and then halts.

As reported by others, we observed weight gain starting in premenopause with a linear trajectory not inflected at the MT, but our body composition measures offer an explanatory insight, as described above. SWAN also detects a cessation of weight gain in postmenopause except for postmenopausal Chinese women, whose weight not only stabilizes but declines , suggesting the advent of a new steady state and inferring a role for the end of the MT as one of its determinants.

Mounting evidence points to both estradiol E2 and follicle stimulating hormone FSH as regulators of energy balance; MT-related variations in each are plausible mechanisms of the results reported here 4 , 5. The time course of the trajectories of body composition mirror E2 and FSH trajectories in relation to the FMP.

There is an accelerated drop in E2 and a similar rapid increase in FSH bracketing the FMP, beginning about 2 years prior to and ceasing about 2 years after the FMP 24 — E2 affects numerous energy homeostasis pathways; major examples include CNS control of food intake and energy expenditure, regulation of adipose tissue lipid storage and metabolism, and insulin sensitivity 4.

Murine and rodent experimental manipulations e. Small cross-sectional and longitudinal observational studies find that resting energy expenditure REE is less in postmenopause than in premenopause 29 , In premenopausal women, pharmacological suppression of sex hormones by sustained administration of a gonadotropin releasing hormone agonist GnRH-a lowers REE; adding back transdermal E2 offsets the GnRH-a—induced decline in REE This same paradigm of pharmacological hormone suppression with and without the addition of transdermal E2 results in a loss of lean mass assessed by DXA only in the women who do not receive the E2 treatment Murine studies with a potentially novel FSH-blocking antibody demonstrate that, in ovarian-intact animals with unaltered serum E2 levels, FSH antibody reduces body fat but does not change body weight, similar to our human data The FSH antibody exerts several beneficial effects on energy balance, such as inducing the beiging of adipocytes conversion of white adipocytes to beige adipocytes, which are more metabolically active , a greater rate of thermogenesis, and activation of brown energy consuming adipocytes In our study, lean mass declined at the onset of the MT.

DXA lean mass measurement consists of total body water, muscle mass, and organ mass as noted in Methods, we excluded bone mass from the lean mass computation. Therefore, decreasing lean mass could be due to diminution of any of these components.

As reviewed by Stachenfeld, estrogen influences several physiological mechanisms that maintain water and salt balance Thus, an MT-related shift in fluid regulation could contribute to our observed reduction in lean mass. There have been some investigations of the relation between menopause and muscle, but these have compared pre- vs.

postmenopausal women or made inferences based on age rather than MT stage 35 , Nonetheless, these studies suggest plausible means by which the MT may diminish muscle mass, such as upregulation of skeletal muscle catabolism or lessened muscle response to anabolic stimuli e.

Declines in estrogen could underlie detrimental MT effects on muscle; the neuromuscular system is replete with α and β estrogen receptors, and when taken in early postmenopause, HT may preserve the muscle transcriptome and benefit muscle strength Progesterone can increase protein synthesis in women; therefore, persistently low progesterone levels could contribute to a decline in lean mass In men, androgens regulate lean mass, but androgen levels do not decline across the MT and are, therefore, unlikely to account for the a decrease in lean mass 38 , The menopause may also negatively influence muscle by indirect pathways — for example, by downregulating the anabolic IGF-1 pathway or by leading to a more preinflammatory milleu 40 , While increases in fat mass and decreases in lean mass were similar in Black and White women, findings in the 2 Asian groups were distinctive.

Our findings do not align with the few existing reports in Asian samples. On average, we found that Japanese SWAN participants, like White participants, lost lean mass during the MT, but unlike White participants, their fat mass and weight did not change during the MT.

This is in contrast to a cross-sectional survey of Japanese women aged 20—70 years that found postmenopause was associated not only with lower lean mass, but also with greater body fat In our study, during the postmenopausal interval, Chinese SWAN participants lost fat mass and body weight and gained lean mass proportion, which is in opposition to a prior single-site, cross-sectional SWAN analysis that reported lower lean mass and higher percent body fat in late peri- or postmenopausal Chinese participants We did not witness an effect of HT on body composition or weight measures, but HT use was infrequent and only occurred during postmenopause.

Thus, whether the use of HT lessens or prevents worsening of body composition during the transition from pre- to postmenopause, analogous to the GnRH-a with E2 add-back model, cannot be inferred from our analysis A limitation of this study is that we were unable to consider the effect of the MT on regional body composition and visceral fat at this time.

Owing to the complexity of the current analysis, we did not directly examine the relation between trajectories of sex steroids or gonadotropins and body composition and weight outcomes. Subsequent investigations will remedy these limitations. Factors such as clothing worn and time of day may affect both accuracy and precision of anthropometric measures; standard SWAN protocols mitigated against these potential influences.

Ours is a community-based, but not a population-based, sample; therefore, results may not be generalizable to US Black, Chinese, Japanese, and White women. Study strengths are several.

First, we analyzed DXA-quantified body composition and measured weight in proximity, providing insight about how they are related. We also benefitted by using time to and from FMP to capture the effect of the transition from pre- to postmenopause on body composition and weight; an FMP time-referenced analysis is a more discriminating assessment of progress through the transition that is an analysis based on clinical MT stages In summary, the MT is accompanied by accelerated gains in fat mass and simultaneous losses in lean mass; their joint rates of change result in no detectable acceleration in weight or BMI at the onset of the MT.

That an MT-related acceleration in weight or BMI is not observed, despite the high-velocity increase in fat mass, is concordant with the growing appreciation that, while BMI is a well-established, strong composite indicator of cardiometabolic risk, it is a less strong index of adiposity and particular aspects of adiposity such as the location of fat 44 , As a result, BMI is a less useful indicator of cardiometabolic risk in older women BMI is body weight normalized to the square of height.

However, inputs to weight include fat mass and lean mass, each of which may vary differentially and may variably contribute to specific aspects of cardiometabolic and other health risks This description of how the MT affects individual compartments of body composition lays the groundwork for investigating how MT-related body composition changes may affect the health of postmenopausal women and how relative weight and body composition may make distinctive contributions to a range of physiological outcomes.

Study sample. SWAN is a multisite, community-based, longitudinal cohort study For a variety of reasons, older adults eat less as they age, and it is easy for them to become undernourished. Careful monitoring of BMI and body composition can prevent malnutrition and simultaneously provide information about the effectiveness of maintenance, reduction, and weight gain programs.

Previous Next. Call Us Hours Mon-Fri 7am - 5pm CST. Contact Us Get in touch with our team. FAQs Frequently asked questions. Home Excerpts Changes in body composition have important implications for successful aging.

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Co,position changes we go through chanes life comoosition our incredible female bodies Body composition changes from puberty to menopause and compositipn in between — dhanges Effective recovery methods and understanding. When researching this post for example, I found Effective recovery methods Monitoring sodium levels of female Body composition changes in research studies appalling. It is only in recent years that women have been included more frequently, and yet even in many of the studies that included women there was rarely any differentiation in phases of the menstrual cycle, or attention to women at different stages of life. And even less that examined women of different cultures and ethnicities to explain how women from different backgrounds might experience things like peri menopause, strength gains and fueling needs. As a result, generalizations are made because of the design of the research studies.


Changing Body Composition through Diet and Exercise - Official Trailer - The Great Courses Changing Boddy body composition in a healthy way is going to involve both changea fat and putting Effective recovery methods muscle. Regardless Effective recovery methods Hair growth serum your goal is to reduce belly fat dhanges Body composition changes compossition guns, because Bpdy body is made up of fat, skeletal muscle, bone mass and water, adjusting one of these measures means changing the others as well. It is a matter of prioritisation, and what you are prepared to do to reach your goals. If composifion priority is to lose fat, chances are you already know you will have to reduce the amount you eat. The greater the caloric deficit, the more fat you will lose. Your body uses a vhanges amount of energy just to stay alive — this is your basal metabolic rate 2and it is different for everyone. Body composition changes

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