These findings represent the first study to examine whether metabolic adaptation, at the level of Resting Metabolic Rate RMR , is associated with time to reach weight-loss goals.

A total of 65 white and Black premenopausal women ages 21 to 41 years old with overweight were selected for the study. All participants were non-smokers and reported a regular menstrual cycle. Participants included in the retrospective analysis came from two different studies — ROMEO and JULIET performed in the UAB Department of Nutrition Sciences with the same sequence of events and methodologies and both aiming to identify metabolic predictors of weight regain.

In the ROMEO study, all participants achieved weight loss with diet alone, while in the JULIET study, participants were randomly assigned to one of three groups: weight loss with aerobic exercise training three times a week, weight loss with resistance exercise training three times a week and weight loss with diet alone same diet as in ROMEO.

For the present study, researchers included all participants from the ROMEO study and the participants randomized to diet only from the JULIET study.

Martins says the most important determinant of success in dietary interventions is undoubtedly diet adherence; however, metabolic adaptation also plays a significant role. So, for those who struggle to lose the last pounds, despite adherence to the energy-restricted diet, there is good news.

Despite relative preservation of FFM, exercise did not prevent dramatic slowing of resting metabolism out of proportion to weight loss. This metabolic adaptation may persist during weight maintenance and predispose to weight regain unless high levels of physical activity or caloric restriction are maintained.

The prevalence of severe obesity [ i. Bariatric surgery is becoming an increasingly accepted treatment for severe obesity 3 because it results in massive weight loss and improved health and disease outcomes 4.

However, these procedures typically cause an undesirable loss of fat-free mass FFM 5 , which comprises the metabolically active tissues of the body 6 , 7.

Because FFM is the primary determinant of resting metabolic rate RMR 8 , 9 , a large reduction in FFM is expected to slow the metabolic rate.

Furthermore, a suppression of RMR out of proportion to the loss in body weight and FFM may occur through a phenomenon known as adaptive thermogenesis or metabolic adaptation 10 — Together the loss of FFM along with metabolic adaptation may profoundly decrease resting energy expenditure, slow the rate of weight loss, and may predispose to weight regain.

Adding exercise to a weight-loss program, particularly resistance training, is thought to preserve FFM and attenuate the drop in RMR during weight loss 18 — Theoretically any strategy that can lessen the decrease in RMR after weight loss could increase the chances for long-term weight loss success In the present study, we measured body composition and energy expenditure in a unique group of severely obese individuals undergoing massive weight loss through a wk competitive program of diet restriction and vigorous exercise.

The objective of this observational study was to determine whether participation in this intensive program helped to preserve FFM and thereby attenuate the metabolic slowing due to weight loss.

This study involved measures of body composition and energy expenditure in individuals competing in a nationally televised weight loss competition.

To participate in the competition, subjects could not be pregnant or lactating, have orthopedic conditions that interfered with walking, or have had previous bariatric surgery.

All subjects obtained medical clearance before competition. The study was approved by the Institutional Review Boards of Cedars Sinai Medical Center no. PBRC , and participants provided written informed consent before participating. Once in the competition, participants were housed together at an isolated ranch outside Los Angeles.

Every 7—10 d, a participant was voted out of the competition and returned home to continue their exercise and diet program unsupervised at home. Four participants remained at the ranch by wk 13, at which time they all returned home.

At wk 30 7 months , all the participants returned to Los Angeles for testing, coincident with the live television broadcast. Body composition was determined by dual-energy x-ray absorptiometry GE Lunar, Madison, WI , and FFM and fat mass FM were calculated from weight and whole-body percent fat using the thick scan mode.

The supine body width exceeded the dimensions of the scan window for all participants; therefore, scans were analyzed using the dual-energy x-ray absorptiometry MirrorImage application, which automatically calculates total body results by doubling the half-body values.

Previous research has shown that this method provides an accurate estimate of total body results The RMR was measured by indirect calorimetry Max II metabolic cart; AEI Technologies, Naperville, FL after a h overnight fast. Participants rested supine in a quiet, darkened room for 30 min at thermoneutrality before testing, followed by the measurement of the O 2 consumption and CO 2 production for 20 min, with the last 15 min used to determine the RMR.

Blood samples were collected after a h overnight fast at only the baseline and wk 30 time points. A chemistry panel was measured on a Beckman Synchron CX5CE or CX9PRO GMI, Inc. Insulin, adiponectin, and leptin were determined by RIA, and a thyroid panel T 3 , T 4 , TSH was run by immunoassay with chemiluminescent detection Millipore Corp.

Insulin resistance was calculated using the homeostasis model assessment of insulin resistance HOMA-IR using fasting measurements of glucose and insulin Predicted RMR values were calculated at wk 6 and 30 using measured FFM and FM at those time points.

Differences between measured and predicted RMR i. RMR residual were calculated and analyzed by ANOVA. A metabolic adaptation was considered present if the RMR residuals were negative and different from zero.

To graphically illustrate the dependence of RMR on FFM, we plotted the RMR adjusted for age, sex, and FM vs. Associations between physiological factors were examined using Pearson or Spearman rank correlation coefficients as appropriate, depending on normality of the data.

Tukey-Kramer adjustment was used to control for multiple comparisons. Seven males and nine females participated in the study and ranged in age from 20 to 56 yr 33 ± 10 yr. Participants were severely obese at baseline with a BMI of Mean fasting glucose and insulin were within normal limits; however, calculated HOMA-IR values suggested insulin resistance Table 2.

Other laboratory values, including triacylglycerol TAG and total cholesterol, were within normal limits Table 2.

Data were mean sd. Metabolic adaptation refers to the change in energy expenditure not explained by changes in FFM and FM, i.

the difference between actual and predicted values. Predicted values were calculated on the basis of the equation for RMR generated at baseline. ns, Not significant. Data are mean ± sd. LDL, Low-density lipoprotein; HDL, high-density lipoprotein.

At wk 6, the 11 participants who were at the ranch had lost Accordingly, FM decreased significantly between baseline and wk 6, without a significant change in FFM Table 1. By wk 30, in the entire sample of 16, participants lost The classification of BMI changed from being in the severely obese category to just over the threshold for obesity Table 1.

The proportion of weight loss coming from fat vs. FFM remained consistent from wk 6 percentages Table 1 and Fig. Figure 1 b shows the progression of body weight loss over 30 wk. B, The progression of weight loss over the wk competition.

The numbers below each data point indicate the number of participants who had their body weight measured at that time and comprise the measurement.

At week Although simple division of the RMR by FFM is commonly used to correct for metabolic mass, this procedure is known to artificially increase the normalized RMR as the FFM decreases Thus, the RMR per kilogram of FFM is expected to increase with weight loss in the absence of metabolic adaptation.

Figure 2 shows the relationship between RMR adjusted for FM, age, and sex and FFM at baseline and wk 30 in comparison with the regression line derived from the RMR and FFM at baseline. Although the baseline RMR data Fig.

Together the residuals in the RMR actual minus predicted value plus the deviation from the regression line demonstrate that despite a relative preservation of FFM, a large metabolic adaptation to weight loss occurred.

The regression line was derived from RMR measurements at baseline in all 16 participants. The deviation from the regression line at wk 30 suggests that RMR per kilogram of FFM was reduced, indicative of metabolic adaptation. At wk 30, TEE was similar to baseline levels; however, the similar TEE despite massive weight loss suggests maintenance of a high level of physical activity Table 1.

Absolute NREE was not different between baseline and wk 30 ± vs. The subjects were relatively sedentary at baseline with a physical activity expenditure of 5. However, physical activity expenditure substantially increased by A, TEE partitioned into resting RMR and nonresting NREE components.

The NREE includes the energy expended in physical movement and diet-induced thermogenesis. B, The increase in estimated physical activity from baseline was As a consequence, HOMA-IR fell to within normal range, indicating improved insulin sensitivity.

The lipid profile showed that TAG decreased significantly; however, cholesterol tended to increase and consisted of increases in both low-density lipoprotein and high-density lipoprotein components. No associations were detected between weight loss, changes in energy expenditure, and changes in leptin concentration.

An important objective during weight loss is to maximize the loss of body fat while minimizing the loss of metabolically active fat free mass. Limited studies of modest weight loss suggest that adding exercise to a weight loss program may help spare FFM 19 — We suspect that the relative preservation of FFM was due to the maintenance or possible increase of skeletal muscle tissue during the vigorous exercise program Thus, we showed that a substantial loss of FFM is not an obligatory consequence of massive weight loss.

This metabolic adaptation to the weight loss intervention was also significant at wk 6 but doubled by the end of the competition. Therefore, we showed that a drop in resting metabolism during active weight loss of this magnitude probably cannot be avoided by the addition of an exercise program.

This amount of vigorous physical activity, with both aerobic and resistance training, resulted in a substantial increase in total daily energy expenditure in the 11 participants who were tested at wk 6. This large increase in TEE, in the face of a metabolic adaptation in resting metabolism, confirms the high physical activity levels in these subjects.

Our data show that physical activity dropped slightly but nonsignificantly between wk 6 and 30, suggesting that the high levels of physical activity were largely maintained, even after the participants were sent home.

Furthermore, FFM continued to be markedly conserved compared with the loss of fat. The causes for the metabolic adaptation to weight loss are still unclear.

Although metabolic adaptation acts to decrease the rate of weight loss, it was the subjects with the greatest weight loss who had the greatest metabolic adaptation.

This suggests that the magnitude of the intervention plays a role in determining both the degree of weight loss as well as the metabolic response acting to counter weight loss. Mechanistically, the decline in circulating leptin and thyroid hormones may contribute to the metabolic adaptation, with a consequent blunting of sympathetic nervous activity 14 , 16 , 32 , Whereas we found that leptin decreased dramatically with weight loss, neither the degree of weight loss nor metabolic adaptation was directly associated with the change in leptin concentration.

Because TSH and T 3 were both associated with greater weight loss, this supports the role of thyroid suppression in metabolic adaptation. On average, T 3 levels decreased, while TSH and T 4 levels were not significantly changed after weight loss.

The subjects who had the largest increase in TSH had the least reduction of T 3 , suggesting that the thyroid axis was acting to counter alterations in peripheral thyroid metabolism, but this response was insufficient to preserve T 3 levels. Surprisingly, the magnitude of metabolic adaptation was not significantly correlated with circulating T 3 changes but was associated with the change in TSH such that those with the greatest increase in TSH had the least metabolic adaptation.

These results suggest that metabolic adaptation may be centrally mediated with a parallel action on the hypothalamic-pituitary-thyroid axis. It is also possible that a disproportionate mass reduction of high metabolic rate organs may have contributed to the observed metabolic adaptation.

Given that the total mass of these tissues brain, liver, heart, kidneys is approximately 4 kg, this would represent an unrealistically large relative decrease in the mass of high metabolic rate tissues.

Thus, a disproportionate loss of metabolically active tissues is unlikely to fully explain the observed metabolic adaptation. Adiponectin is known to reduce hepatic glucose output, increase fatty acid oxidation, and activate cellular energy sensing pathways via AMP-activated protein kinase, leading to improved insulin sensitivity Intracerebroventricular administration of adiponectin also decreases body weight and fat mass through increased energy expenditure 36 , possibly through the activation of AMP-activated protein kinase Adiponectin increased 2-fold in our study and was associated with weight and fat mass loss but also with lowered resting metabolism.

It is impossible to know from this study whether the changes in adiponectin had an independent effect on weight loss or RMR or was merely a reflection of weight loss magnitude. Limitations of this study include the lack of experimental control group throughout the competition. We can assume that the degree of energy deficit was different among subjects as was the amount and type of exercise and calorie restriction.

Your metabolism will drop as a result. Foods that are high in protein are usually low in fat and calories. This is especially true of plant-based proteins like quinoa, black beans, tofu, and tempeh.

When you increase your protein intake, your body needs to expel more energy to burn them than it would for fats and carbohydrates. This increased energy causes your RMR to increase. Your body needs to expel more energy in order to maintain them because they are constantly in use.

So, add some weight lifting to your weekly gym routine. For example, you should eat a piece of fruit or small amount of bread within 10 minutes of completing an intense exercise. Interval training doing short spurts of different activities in a sequence is another great way to increase your RMR.

When you do one activity for a long period of time like running or biking your body gets used to the motion and eventually burns less energy during the activity than when you first started.

For instance, you can jump rope for three minutes, do two minutes of squats, do 15 push-ups, and then do a one-minute plank. Then, start the process over. This method can increase your RMR for up to hours after your workout.

You can count every calorie and risk the weight returning shortly after you lose it, or you can focus on increasing your Resting Metabolic Rate and experience sustainable, healthy weight loss. The choice seems pretty easy to me. Clyde Wilson , nutritionist at our practice can answer your question about metabolism and help you with weight management.