Persistent metabolic adaptation 6 years after “The Biggest Loser” competition

Body weight and composition

For 2 weeks before being admitted to the NIH Clinical Center for the follow-up measurements, body weights were monitored daily via a scale (model UC-352BLE, A&D Medical, San Jose, CA) connected via Bluetooth to an iPad mini (Apple Inc., Cupertino, CA) that transmitted the data back to the study team using a remote patient monitoring system (Tactio RPM Platform, Tactio Health Group, Montreal, Canada). Subjects were then admitted to the NIH Clinical Center for a 3-day inpatient stay to conduct the RMR and body composition measurements. Body composition was determined by dual-energy X-ray absorptiometry using the same model of scanner used to make the original measurements during the weight loss competition (iDXA; GE Lunar, Madison, WI). Body FFM and FM were calculated from weight and whole-body percent fat using the thick scan mode. All participants whose supine body width exceeded the dimensions of the scan window were analyzed using the iDXA MirrorImage™ application [5].

Resting metabolic rate

The RMR measurements were performed using indirect calorimetry (TrueOne metabolic cart, ParvoMedics, Sandy, UT) following a 12-h overnight fast. Participants rested supine in a quiet, darkened room for 30 min before making measurements of VO₂ and VCO₂ for 20 min with the last 15 min used to determine RMR according to:

RMR(kcal)=3.85×VO2(L)+1.07×VCO2(L)

which assumes that protein oxidation contributes 15% to the energy expenditure [6].

Total energy expenditure

After returning home from the NIH Clinical Center, subjects drank from a stock solution of 10% ¹⁸O enriched H₂O and 99% enriched ²H₂O at a dose of 1.5 g/kg body weight followed by 100 to 200 mL tap water to rinse the dose container. Spot urine samples were collected at 1.5, 3, 4.5, and 6 h after administration and once daily over the next 13 days when the subjects were instructed not to change their usual routine. Isotopic enrichments of urine samples were measured by dual inlet chromium reduction and continuous flow CO₂ equilibration isotope ratio mass spectrometry. An aliquot of the stock solution was saved for dilution to be analyzed along with each set of urine samples. The average CO₂ production rate (rCO₂) over the 14-day period was estimated from the rate constants describing the exponential disappearance of the labeled ¹⁸O and D water isotopes (k_O and k_D) in repeated spot urine samples collected over several days. We used the parameters of Racette et al. [7] with the pool size, N, determined as 73% of the FFM:

rCO2=(N/2.078)(1.007kO−1.007RdilkD)−0.0246rGFrGF=1.05(1.007kO−1.007RdilkD)Rdil=1.034

The average total energy expenditure (TEE) from the doubly labeled water measurement of rCO₂ was calculated as:

TEE(kcal)=[3.85RQ+1.07]×rCO2(L)

where the respiratory quotient, RQ, was assumed to be 0.86 representative of the food quotient of a typical diet.

Physical activity energy expenditure

Physical activity energy expenditure was calculated as the nonresting energy expenditure (TEE-RMR) minus the estimated thermic effect of food which was assumed to be 10% of energy intake and was calculated as 0.1 × TEE at baseline and 6 years. At the end of the 30-week competition we assumed the thermic effect of food was 0.1 × TEE_baseline − 180 kcal/day since energy intake was estimated to have decreased by ∼1,800 kcal/day compared with baseline at the end of the competition [8]. Since most physical activities involve locomotion and therefore have an energy cost that is proportional to body weight for a given intensity and duration [9], we normalized the physical activity energy expenditure by dividing by body weight.

Biochemical assays

Blood samples from overnight fasted participants were analyzed by a commercial laboratory (West Coast Clinical Laboratories, Van Nuys, CA). The chemistry panel was measured on a Beckman Synchron CX5CE or CX9PRO. Insulin was determined by radioimmunoassay, and leptin and adiponectin concentrations were measured using a commercially available kit (Millipore, St. Charles, MO). Triglycerides (TG) and total, high-density lipoprotein, and low-density lipoprotein cholesterol were assayed with ACE reagents and instrumentation (Alfa Wassermann, Caldwell, NJ). Insulin resistance was calculated using the homeostasis model assessment of insulin resistance using fasting measurements of glucose and insulin [10]. Thyroid panel [T3, T4, thyroid stimulating hormone] was measured by immunoassay with chemiluminescent detection (Millipore Corporation, Billerica, MA).

Statistical analysis

The prespecified primary aim of the study was to measure body composition and RMR several years after the end of “The Biggest Loser” competition and the study was powered to detect a metabolic adaptation ≥220 kcal/day in 12 subjects using an endpoint analysis with probability (power) 0.8 assuming a 250 kcal/day standard deviation and a two-sided test with type I error probability of 0.05. We chose to power the study for 12 subjects since we did not expect to recruit the entire 16-subject original cohort and the 220 kcal/day effect size was considered to be physiologically significant.

Baseline data from all 16 subjects were used to generate a least squares best-fit linear regression equation for RMR as a function of FFM, FM, age, and sex (R² = 0.84):

RMR(kcal/d)=1,001+21.2×FFM(kg)+1.4×FM(kg)−7.1×Age(yr)+276×Sex(F = 0, M =  1)

We calculated the predicted RMR using this equation along with the corresponding FFM, FM, and age at each time point for every individual. Differences between the measured and predicted RMR defined the magnitude of metabolic adaptation which was considered to be present if the RMR residuals were significantly different from zero [3].

Despite all our subjects having class III obesity at baseline, the coefficients of the best-fit RMR regression equation above were similar to those previously published using data from subjects with less severe obesity [11-13]. Furthermore, the baseline RMR measurements in our subjects were not significantly different (P = 0.34) from those predicted using a standard equation as a function of height, weight, age, and sex [12].

Statistical analyses were performed using SAS version 9.3 (SAS Institute Inc., Cary, NC). Data are expressed as mean ± SD and were analyzed by analysis of variance (PROC GLM, SAS) with each subject as a fixed block effect. Associations were examined using Pearson correlation (PROC CORR, SAS). Significance was declared at P < 0.05.

Body weight and composition

Of the original 16 “Biggest Loser” competitors, six men and eight women agreed to participate in the follow-up study. These 14 subjects weighed (mean ± SD) 148.9 ± 40.5 kg at baseline and lost 58.3 ±24.9 kg at the end of the 30-week competition (Table 1). Body weight was relatively stable in the weeks before the follow-up measurements (Figure 1) with a mean rate of weight change of −37.3 ± 84.6 g/day that was not significantly different from zero (P = 0.1). Figure 2 and Table 1 show the changes in body weight, FM, and FFM at the end of the 30-week competition and at the 6-year follow-up compared with baseline.

After 6 years, most subjects regained a significant amount of the weight lost during the competition, but there was a wide degree of individual variation and a mean weight loss of 11.9 ± 16.8% (P = 0.02) compared with baseline. All but one subject regained some of the weight lost during the competition and five subjects were within 1% of their baseline weight or above. Mean FM and FFM significantly increased in the 6 years since the competition but remained significantly below baseline.

Figure 3 illustrates the relationship between body weight and FM changes and shows that ∼80% of the weight changes at both 30 weeks and 6 years were attributable to FM. Since the data points all fell on the same curve, there was no evidence for a disproportionate regain of FM.

TEE and physical activity

TEE decreased at the end of the 30-week competition despite a significant increase in physical activity expenditure (Table 1). After 6 years, TEE increased but remained below baseline while physical activity was not significantly changed since the end of the competition.

Fasting plasma hormones and metabolites

Table 2 presents the fasting hormone and metabolite data at baseline, the end of the 30-week competition, and 6 years later. After 6 years, plasma leptin, thyroxin (T4), and TG remained lower than baseline while high-density lipoprotein and adiponectin were increased. Interestingly, insulin sensitivity was not significantly improved 6 years after the competition compared with baseline despite significant sustained weight loss.

RMR and metabolic adaptation

Table 1 shows that the RMR at baseline was 2,607 ± 649 kcal/day which fell to 1,996 ± 358 kcal/day at the end of the 30-week competition (P = 0.0004). Despite a significant amount of weight regain 6 years later, the mean RMR was 1,903 ± 466 kcal/day, which was not significantly different from the end of the competition (P = 0.35). Figure 4A shows that RMR was decreased by 610 ± 483 kcal/day at the end of the competition (P = 0.0004) and was 704 ± 427 kcal/day below baseline 6 years later (P < 0.0001), which was not significantly different from the end of the competition (P = 0.35).

We previously showed in the full 16-subject cohort that the magnitude of metabolic adaptation at the end of the competition was significantly correlated with the amount of weight lost [3], and this trend continued with the 14 subjects of this study but did not reach statistical significance (r = 0.48, P = 0.08). Figure 4B shows that at the end of the 30-week competition there was a significant metabolic adaptation of −275 ± 207 kcal/day (P = 0.00025) that increased in magnitude to −499 ± 207 kcal/day after 6 years (P < 0.0001). Metabolic adaptation at 6 years was not significantly correlated with metabolic adaptation at the end of the competition (r = 0.18, P = 0.54).

Figure 5A, B show that metabolic adaptation measured at the end of the 30-week competition was not significantly related to weight regained (r = −0.1, P = 0.75) or the percent weight change (r = 0.31, P = 0.28) at the 6-year follow-up. However, metabolic adaptation at follow-up was significantly related to both weight regain (r = 0.59, P = 0.025) and the percent weight change (r = 0.54, P = 0.045) such that those with greater weight loss at 6 years continued to experience greater metabolic slowing. Metabolic adaptation at 6 years was not significantly correlated with changes in fasting plasma leptin (r = 0.204, P = 0.48), triiodothyronine (T3) (r = 0.34, P = 0.23), thyroid stimulating hormone (r = 0.42, P = 0.88), or T4 (r = 0.044, P = 0.88).

Assessing metabolic cart bias

Different metabolic carts were used to make the RMR measurements at the 6-year follow-up compared with the cart used at both baseline and 30 weeks. To investigate the potential bias of using different instruments, we tested the original Max II cart in comparison with the Parvo cart used to make the 6-year follow-up measurements as described in the Supporting Information. Supporting Information Figure 1A illustrates that the Max II cart was more variable. We found that the Max II cart had no significant energy expenditure bias compared with the Parvo cart (1.96 ± 8.45%, P = 0.82) and Supporting Information Figure 1B demonstrates that there was no significant trend compared with the Parvo cart as a function of energy expenditure (r = 0.45, P = 0.32). We cannot rule out the possibility that the original Max II cart became more accurate at the time of testing compared with 6 years earlier, but this seems unlikely.

We also performed a sensitivity analysis to investigate how the metabolic adaptation measurements varied in response to an assumed % bias of the RMR measurements during the competition versus at the 6-year follow-up. Supporting Information Figure 2 illustrates that a metabolic cart bias >16% would be required to eliminate the statistical significance of the measured metabolic adaptation at the 6-year follow-up. A bias ≥4% would be required to nullify the statistical significance of the measured increase in metabolic adaptation observed at the 6-year follow-up compared with the end of the 30-week competition. Therefore, we found no evidence that the use of different metabolic carts could explain our observations in the absence of a real effect on RMR.