The Effect of Baseline Thyroid Function on Weight Loss Outcomes in Euthyroid Individuals Undergoing Full Meal Replacement Therapy

doi:10.21203/rs.3.rs-4618399/v1

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The Effect of Baseline Thyroid Function on Weight Loss Outcomes in Euthyroid Individuals Undergoing Full Meal Replacement Therapy

https://doi.org/10.21203/rs.3.rs-4618399/v1

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Background

Thyroid function plays a key role in regulating energy metabolism and thermogenesis, with thyroid dysfunction closely linked to alterations in body weight and composition. However, there is a lack of data on the effect of baseline thyroid function on weight loss outcomes in euthyroid individuals.

Methods

This study constitutes a secondary analysis utilizing prospectively collected data from a cohort study comprising individuals living with obesity (BMI > 30kg/m² or ≥ 27 kg/m² with comorbidities) and normal thyroid function participating in a weight management program, which incorporates full meal replacement therapy (FMR). The primary objective was to examine the association between baseline thyroid function and weight loss (WL) outcomes 6-week post-FMR initiation.

Results

A total of 1078 participants were included in the study: 67% female, aged 45.4±10.9 years, 64% had type 2 diabetes with an initial BMI of 45.0±7.6 kg/m², and a baseline TSH and fT3 levels of 2.0±0.8 mIU/L and 4.5±2.6 pmol/L respectively. 6-week post-FMR initiation, there was significant correlation between the amount of WL and TSH levels (β:-0.473 IC₉₅[-0.796; -0.150]). The percentage of WL between extreme TSH quantiles (Q1-Q5) were 8.1±1.8% vs 7.3±1.6% (p < 0.001). No correlation was found between WL and TSH levels at 12 weeks and fT3 levels at 6 and 12 weeks.

Conclusion

Within a cohort of euthyroid individuals living with obesity undergoing FMR, lower baseline TSH levels, not fT3 levels, were predictive of greater weight loss at 6-week. These findings suggest that this parameter might be an important weight loss outcomes predictive factor for euthyroid individuals with obesity.

Health sciences/Endocrinology/Endocrine system and metabolic diseases/Obesity

Health sciences/Health care/Weight management

Thyroid

Full Meal Replacement Therapy

Obesity

Weight Loss

Prediction

Obesity is a chronic disease that is on the rise worldwide (1). One of the pillars of weight management involves the implementation of multicomponent behavior modification such as medical nutrition therapy. As part of a comprehensive approach to patient care, a key element of this therapy relies on setting realistic expectations of achievable weight loss with a nutritional program (2). To help clinicians provide individualized care to their patients, two weight prediction models were developed and are widely used to predict weight loss outcomes, namely, the National Institute of Health Body Weight Planner (NIH-BWP) and the Pennington Biomedical Research Center Weight Loss Predictor (PBRC-WLP) (3, 4). These two models use covariates such as an individual’s age, sex, baseline weight and height as well as daily caloric intake to predict the weight loss over time. However, the NIH-BWP and PBRC-WLP models present some limitations. As a matter of fact, studies suggest high variability between predicted weight and observed weight, with a mean difference up to 8.4 lbs (3.8 kg) (5). In a validation study with over 3700 individuals, Dent et al. reported that the NIH-BWP was significantly more accurate than PBRC-WLP. However, notable variation between observed and expected body weights remains, with a relative difference ranging between − 6.3% and + 2.8% for 90% of people (6). Therefore, there is a need to identify more predictive factors that will help guide patients regarding weight loss expectations in the clinical setting.

Obesity has long been recognized as a multifactorial disease that originates from a complex relationship between biopsychosocial factors. Therefore, the use of only four covariates to predict weight loss outcomes is likely suboptimal to capture all the complexity of inter-individual variabilities. For instance, genetic predisposition, weight-promoting pharmacotherapy, and behavioral factors all play a key role in an individual’s weight loss trajectory (7). In recent years, there has been an increasing interest in the impact of endocrine function on weight. Precisely, a growing body of evidence has demonstrated that thyroid abnormalities are linked to obesity (8).

Thyroid function plays a pivotal role in baseline energy metabolism and thermogenesis by influencing glucose and lipid metabolism, food intake, and fatty acid oxidation (9, 10). Consequently, thyroid dysfunction is closely associated with changes in body weight and composition (11). A cross-sectional, population-based study involving 27 097 individuals revealed a correlation between overt hypothyroidism and a higher prevalence of obesity (12). In their study, Knudsen et al. suggest that even small variations in thyroid function were associated with significant alterations in resting energy expenditure (13). Interestingly, Yavuz et al. showed that this positive correlation between thyroid hormones and weight is present even when thyroid- stimulating hormone (TSH) levels were within the normal range (14). Therefore, baseline thyroid function in euthyroid individuals may play an important role in weight trajectory and its prediction.

Studies on the impact of baseline thyroid function and expected weight loss outcomes in euthyroid individuals living with obesity remains scarce. In a secondary analysis of the POUNDS LOST study, Liu et al. showed that higher baseline free triiodothyronine (fT3) and free thyroxine (fT4), but not TSH, predicted more weight loss in a diet-induced weight-loss setting in adults living with obesity with normal thyroid function (15). In addition, Neves et al. demonstrated that high fT3 levels was associated to greater weight loss after bariatric surgery. However, these results were not confirmed by subsequent studies (16). Therefore, there is knowledge gap about the impact of baseline thyroid function on weight loss outcomes, particularly for individuals undergoing very low energy diets (VLED). Our study aims to investigate the impact of an individual’s baseline thyroid function level on their weight loss trajectory within a weight management program.

Study design and population

This is a secondary analysis of prospectively collected data from a cohort study. The initial cohort is composed of 5057 participants who enrolled in a weight management program at the Ottawa Bariatric Center between 1992 (the year that the program started) and 2015 (the final year of data collection prior to creating the research database) (17). The program is an intensive 26-week weight management skill-building program consisting of weekly 3-hour group sessions facilitated by registered dietitians, social workers, behaviorists, and exercise specialists. Patients paid for the program up to 2010, after which it was funded by the Ontario Ministry of Health. The program’s first intervention (week 0) was a 1200 kcal/day diet for which participants were given detailed instructions. From weeks 1 to 13, participants exclusively consumed a program-provided 900 kcal/day meal replacement program (Optifast^® 900 from Nestle Health Science), paid for by the participants. Data were collected prospectively at the Ottawa Hospital Bariatric Center and recorded in a database.

Eligible participants for the derivation cohort were adults (≥ 18 years old) with a BMI of ≥ 30 kg/m² or ≥ 27 kg/m² with comorbidities and normal thyroid function (TSH < 0.7 or > 4.2 mIU/L). Exclusion criteria included one or more of the following: a known thyroid disease, a history of bariatric surgery, treatment with thyroid supplements, corticosteroids, beta-blocker, or weight loss medication before or during the program, suboptimal adherence to the prescribed diet (meal replacement usage < 80% or > 100% during the program), > 5% weight loss between the initial assessment visit and the program start, and missing weight data at week 6 of the program.

This research was approved by the Ottawa Health Science Network Research Ethics Board (OHSN-REB). All data collection and analysis were performed in accordance with OHSN-REB regulations. Data used in this analysis were solely from patients who provided informed consent to permit its use.

Data collection

Baseline weights were calculated as the mean of weights taken at program intake (week − 1) and program initiation prior to any dietary intervention (week 0). Participant’s baseline demographic data, medical history, and TSH and fT3 levels were measured at the beginning of program intake. All TSH and fT3 levels were measured at The Ottawa Hospital laboratory. Participants’ weights were measured at the end of each week on the same scale at each weekly program meeting.

Study outcomes

The primary outcome was the percentage of weight loss between baseline TSH quantiles at week 6. Secondary outcomes included the percentage of weight loss between baseline TSH quantiles at week 12, the percentage of weight loss between baseline fT3 quantiles at week 6 and week 12, the absolute amount of weight loss (in lbs) between baseline TSH and fT3 quantiles at week 6 and week 12, and the correlation between baseline TSH and fT3 levels and absolute weight loss at week 6 and week 12.

Statistical analysis

Descriptive statistics for participant’s baseline characteristics are reported as means and standard deviations (SD) for continuous variables, and as counts and percentage for categorical variables. Percentages of and absolute weight loss between TSH and fT3 quantiles were analyzed using a non-parametric Kruskal-Wallis test and Dunn’s test. To evaluate the correlation between TSH, fT3, and absolute weight loss, a multiple linear regression adjusted for sex, age, initial weight, and diabetes statuses was conducted. All statistical analysis was performed using R version 4.2.2. A two-sided 5% significance threshold was used to declare statistical significance.

A total of 1078 participants were included in this study. 3979 participants were excluded in a step-wise manner: 3074 (60.8%) for suboptimal adherence to the prescribed diet, 34 (0.7%) for known thyroid disease, 260 (5.1%) for taking thyroid supplements, 135 (2.6%) for abnormal thyroid function, 157 (3.1%) for taking a beta-blockers, 199 (3.9%) for taking corticosteroids, 52 (4.8%) for taking weight loss medication, 24 (0.5%) for > 5% weight loss prior to the program start, 35 (0.7%) for missing weight data at week-6 (Fig. 1). Out of the participants, 837 individuals had a baseline fT3 level for analysis.

Participant’s characteristics were 67% female, 45.4 ± 10.9 years old, initial BMI of 45.0 ± 7.6 kg/m², initial weight of 277.2 ± 59.1 lbs, 64% with type 2 diabetes, fasting blood glucose of 5.9 ± 2.00 mmol/L, TSH level of 2.0 ± 0.8 mUI/L, and a fT3 levels of 4.5 ± 2.6 pmol/L. Apart from thyroid functions, all baseline characteristics were comparable between TSH and fT3 extreme quantiles (Table 1).

After 6 weeks in the weight management program, the percentage of weight loss was 8.1 ± 1.8% vs 7.7 ± 1.7% vs 7.5 ± 1.6% vs. 7.4 ± 1.9% vs 7.3 ± 1.7% for baseline TSH quantiles (Q) 1 to 5 (p < 0.001). This translates into an absolute weight loss of 22.4 ± 7.8lbs vs 21.6 ± 7.6lbs vs 20.6 ± 6.3lbs vs 20.8 ± 7.5lbs vs 21.1 ± 7.8lbs (p = 0.112), respectively. The difference in the percentage of weight loss between extreme TSH quantiles was statistically significant (p < 0.001). Similar results were noted at the 12 weeks follow-up with percentage of weight loss in extreme TSH quantiles of 15.7%±3.1% (Q1) vs 14.8%±14.6% (Q5) (p = 0.001). The absolute weight loss between TSH quantiles remained non-significant at 12 weeks (p = 0.493).

At week 6, no statistical differences were noted for the percentage of weight loss between baseline fT3 quantiles (p = 0.060). There was a significant difference in absolute weight loss between baseline fT3 levels quantiles (p = 0.021), but there was no clear trend of progressive increase in weight loss with higher fT3 levels. The observed weight loss between extreme fT3 quantiles were 21.1 ± 6.2 lbs (Q1) vs 22.3 ± 8.1 lbs (Q5) (p = 0.959). At week 12, there was a significant difference for the percentage of weight loss (p-value = 0.003) and the absolute weight loss (p-value = 0.006) between baseline fT3 quantiles. However, there was no clear trend of progressive increase in weight loss with higher fT3 levels with no significant difference between extreme fT3 quantiles (p-value = 0.959, p-value = 0.704, respectively) (Table 2).

When adjusted for age, sex, initial weight, and diabetes status, there was a significant negative correlation between baseline TSH levels and absolute weight loss at week 6 (β:-0.4733 IC₉₅[-0.796; -0.150]). There was no significant correlation between baseline TSH levels and absolute weight loss at week 12. No significant correlation was noted between baseline fT3 levels and absolute weight loss at week 6 and week 12 (Table 3).

There is a growing need to identify predictive factors to forecast weight loss outcomes for individuals living with obesity undergoing medical nutrition therapy. Although the effect of thyroid function on weight has been well described in the literature, its impact on weight loss trajectory for this population of patients remains uncertain (8–14). Our study suggest that baseline thyroid function plays a significant role on weight loss outcomes, with a negative correlation between baseline TSH levels and the amount of weight loss after 6 weeks. No correlation was noted between fT3 levels and the amount weight loss. Therefore, baseline TSH could serve as a predictive variable and merit incorporation into future prediction models.

Precisely, our data shows a negative correlation at week 6 between baseline TSH levels and absolute weight loss, with a β-coefficient of -0.473 (Table 3). In other words, for every decrease of 1 mIU/L of TSH, there is an additional 0.473 lbs of weight loss after 6 weeks of VLED. This translates to a significant mean weight loss difference of 1.3 lbs or 0.8% of total body weight loss (TBWL) between extreme TSH quantiles. This weight loss difference persisted at week 12 (Table 2). Studies have shown that individuals using a VLED achieve weight loss of 3 lbs per week on average (18). Therefore, the additional weight loss by unit of TSH decrease represents close to 4% of an individuals’ total weight loss after 6 weeks, which is clinically relevant.

Although the % of TBWL remained statistically significant between extreme TSH quantiles, there was no clear correlation between baseline TSH levels and absolute weight loss at week 12. These findings reflect the anticipated weight loss rate within VLED programs. Indeed, studies on VLED suggest that the rate of weight loss is higher in the first 6 weeks following the initiation of the diet (19). Therefore, the effect of baseline TSH levels on weight loss is expected to be more pronounced within this treatment period. Additionally, the levels of fT4 and fT3 are expected to fluctuate with weight loss due to associated changes in deiodinase activity (20). fT4 has a half-life of 7 days, which will reflect a change in TSH levels in 4–6 weeks (21). Hence, baseline TSH levels could better represent an individual’s baseline thyroid function within the initial 6 weeks of VLED.

When expressed in terms of absolute amount of weight loss, our study did not demonstrate a statistically significant difference between baseline TSH quantiles at week 6 and week 12. A possible explanation could be the variance in the mean initial weight between the groups. In fact, the participant’s mean weight in the lower TSH quantile was 276.16 ± 52.67lbs compared to 282.74 ± 63.70 lbs in the highest TSH quantile (Table 1). It has been well established that initial weight impacts weight loss outcomes (22). Therefore, the mean weight difference between the TSH quantiles could potentially skew our results. Nevertheless, studies have suggested that the percentage of weight loss might be a more sensitive predictor of weight loss outcomes than absolute weight, as it is the least influenced by initial weight, as found in our study (23). Accordingly, the % of TWBL is the most often used metric in clinic and research settings.

Contrary to previous findings, our study did not demonstrate a correlation between baseline fT3 levels and weight loss outcomes. Although there was a statistically significant difference in absolute weight loss at week 6 and week 12 between fT3 quantiles, there was no clear trend of progressive increase in weight loss with higher fT3 levels. As such, no significant difference was noted between extreme fT3 quantiles. Additionally, there was not significant difference in the % of TBWL between fT3 quantiles. The inconsistency of this finding is expected due to the potential variability in fT3 levels within individuals. For instance, serum fT3 follows a circadian rhythm with approximately 10% higher concentrations in the morning (24). Furthermore, the immunoassays frequently used by laboratories are highly susceptible to interference by various factors (e.g., heterophil antibodies, medications), rendering them to be an unreliable tool in clinical settings (25). Consequently, the American Thyroid Association does not recommend the use of fT3 levels as a therapeutic target for individuals with thyroid disorders (26). Although fT3 could potentially play a role in weight loss at the cellular level, its dosage is variable and should not be used as a predictor for weight loss outcomes in this population.

The mechanism underlying our findings remains unclear. It has been described that thyroid hormones regulate resting energy expenditure by acting both in peripheral tissues and the central nervous system. For instance, thyroid hormones play a role in ATP-dependent metabolic cycles such as lipid and glucose homeostasis in the liver, promote adipocyte proliferation, and regulate feeding behaviors in the hypothalamus (27, 28). We hypothesize that euthyroid individuals with lower baseline TSH levels have a higher circulating fT4 and fT3, and thus, a higher resting metabolic rate. These individuals might therefore be more responsive to lower energy diets and experience greater weight loss. This finding aligns with the results found by Tagliaferri et al. who also observed that higher TSH levels affects energy expenditure in patients with obesity and subclinical hypothyroidism (29). However, further research is needed to understand how normal thyroid function regulates weight changes in this population of patients.

To our knowledge, this study boasts the largest sample size investigating the impact of baseline thyroid function on weight loss outcomes in euthyroid individuals living with obesity. Nevertheless, some limits merit mention. Firstly, obesity is a complex multifactorial disease, making it impossible to control for all potential confounding factors (e.g., sleep apnea status, diabetes pharmacotherapy, etc.). Secondly, the participants in this study were individuals enrolled in a weight management program with weekly visits who adhered to the recommended diet. The negative correlation between baseline TSH and weight loss outcomes might be attenuated in a clinic setting. Thirdly, most participants in our study presented with a baseline TSH level within the lower half of the normal range for the laboratory, which might indicate a potential selection bias as higher TSH levels are typically expected with increased BMI. This could have skewed the results. Lastly, fT4 levels were not collected in the cohort used for this study. Some participants could present with undiagnosed subclinical hypothyroid. fT4 levels is also more stable than fT3 levels and could potentially better represent thyroid function than TSH.

In conclusion, our study demonstrated that a lower baseline TSH level is associated with greater weight loss at both 6 and 12 weeks following a medical weight management program utilizing VLED therapy, with a significant negative correlation observed week 6. Conversely, a higher baseline fT3 level was not associated with increased weight loss. Therefore, baseline TSH could serve as a predictive variable that merits incorporation into future prediction models. Moreover, our findings prompt a crucial clinical inquiry into whether supplementing euthyroid individuals with elevated baseline TSH could improve their weight loss outcomes. Further research is essential to address this pertinent clinical question.

Personal Thanks

We thank all the participants in our clinical trials for their valuable time and the clinical staff at The Ottawa Hospital Bariatric Center for their invaluable work.

Competing Interests

All other authors have no relationships or activities that might bias or be perceived to biais this work.

Authors Contributions and Guarantor Statement

RC, AB, JS, RRMD designed the study. RC and RRMD conducted data collection. RC conducted data analysis. RC, AB, BE, JS, RRMD helped in data interpretation. RC drafted the manuscript, which was critically revised by RC, AB, BE, JS, RRMD. All authors revised the final draft and approved its contents. RRMD is the guarantor of this work, and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Data Availability Statement

The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

Burki T. (2021). European Commission classifies obesity as a chronic disease. The lancet. Diabetes & endocrinology, 9(7), 418.
Wharton, S., Lau, D. C. W., Vallis, M., Sharma, A. M., Biertho, L., Campbell-Scherer, D., Adamo, K., Alberga, A., Bell, R., Boulé, N., Boyling, E., Brown, J., Calam, B., Clarke, C., Crowshoe, L., Divalentino, D., Forhan, M., Freedhoff, Y., Gagner, M., Glazer, S., … Wicklum, S. (2020). Obesity in adults: a clinical practice guideline. CMAJ: Canadian Medical Association journal = journal de l'Association medicale canadienne, 192(31), E875–E891.
Hall, K. D., Sacks, G., Chandramohan, D., Chow, C. C., Wang, Y. C., Gortmaker, S. L., & Swinburn, B. A. (2011). Quantification of the effect of energy imbalance on bodyweight. Lancet (London, England), 378(9793), 826–837.
Thomas, D. M., Martin, C. K., Heymsfield, S., Redman, L. M., Schoeller, D. A., & Levine, J. A. (2011). A Simple Model Predicting Individual Weight Change in Humans. Journal of biological dynamics, 5(6), 579–599.
Ravussin, E., Redman, L. M., Rochon, J., Das, S. K., Fontana, L., Kraus, W. E., Romashkan, S., Williamson, D. A., Meydani, S. N., Villareal, D. T., Smith, S. R., Stein, R. I., Scott, T. M., Stewart, T. M., Saltzman, E., Klein, S., Bhapkar, M., Martin, C. K., Gilhooly, C. H., Holloszy, J. O., … CALERIE Study Group (2015). A 2-Year Randomized Controlled Trial of Human Caloric Restriction: Feasibility and Effects on Predictors of Health Span and Longevity. The journals of gerontology. Series A, Biological sciences and medical sciences, 70(9), 1097–1104.
Dent, R., Harris, N., & van Walraven, C. (2023). Validity of two weight prediction models for community-living patients participating in a weight loss program. Scientific reports, 13(1), 11629.
Dent, R., et al. (2020). Factors affecting weight loss variability in obesity. Metabolism: Clinical and Experimental, 113, 154388.
Sanyal, D., & Raychaudhuri, M. (2016). Hypothyroidism and obesity: An intriguing link. Indian journal of endocrinology and metabolism, 20(4), 554–557.
Silva J. E. (1995). Thyroid hormone control of thermogenesis and energy balance. Thyroid: official journal of the American Thyroid Association, 5(6), 481–492.
Iwen, K. A., Oelkrug, R., & Brabant, G. (2018). Effects of thyroid hormones on thermogenesis and energy partitioning. Journal of molecular endocrinology, 60(3), R157–R170.
Fox, C. S., Pencina, M. J., D'Agostino, R. B., Murabito, J. M., Seely, E. W., Pearce, E. N., & Vasan, R. S. (2008). Relations of thyroid function to body weight: cross-sectional and longitudinal observations in a community-based sample. Archives of internal medicine, 168(6), 587–592.
Asvold, B. O., Bjøro, T., & Vatten, L. J. (2009). Association of serum TSH with high body mass differs between smokers and never-smokers. The Journal of clinical endocrinology and metabolism, 94(12), 5023–5027.
Knudsen, N., Laurberg, P., Rasmussen, L. B., Bülow, I., Perrild, H., Ovesen, L., & Jørgensen, T. (2005). Small differences in thyroid function may be important for body mass index and the occurrence of obesity in the population. The Journal of clinical endocrinology and metabolism, 90(7), 4019–4024.
Yavuz, S., Salgado Nunez Del Prado, S., & Celi, F. S. (2019). Thyroid Hormone Action and Energy Expenditure. Journal of the Endocrine Society, 3(7), 1345–1356.
Liu, G., Liang, L., Bray, G. A., Qi, L., Hu, F. B., Rood, J., Sacks, F. M., & Sun, Q. (2017). Thyroid hormones and changes in body weight and metabolic parameters in response to weight loss diets: the POUNDS LOST trial. International journal of obesity (2005), 41(6), 878–886.
Neves, J. S., Souteiro, P., Oliveira, S. C., Pedro, J., Magalhães, D., Guerreiro, V., Costa, M. M., Bettencourt-Silva, R., Santos, A. C., Queirós, J., Varela, A., Freitas, P., Carvalho, D., & AMTCO Group (2019). Preoperative thyroid function and weight loss after bariatric surgery. International journal of obesity (2005), 43(2), 432–436.
Dent, R. M., Penwarden, R. M., Harris, N., & Hotz, S. B. (2002). Development and evaluation of patient-centered software for a weight-management clinic. Obesity research, 10(7), 651–656.
Ard, J. D., Lewis, K. H., Rothberg, A., Auriemma, A., Coburn, S. L., Cohen, S. S., Loper, J., Matarese, L., Pories, W. J., & Periman, S. (2019). Effectiveness of a Total Meal Replacement Program (OPTIFAST Program) on Weight Loss: Results from the OPTIWIN Study. Obesity (Silver Spring, Md.), 27(1), 22–29.
Harper, M. E., Dent, R., Monemdjou, S., Bézaire, V., Van Wyck, L., Wells, G., Kavaslar, G. N., Gauthier, A., Tesson, F., & McPherson, R. (2002). Decreased mitochondrial proton leak and reduced expression of uncoupling protein 3 in skeletal muscle of obese diet-resistant women. Diabetes, 51(8), 2459–2466.
Agnihothri, R. V., Courville, A. B., Linderman, J. D., Smith, S., Brychta, R., Remaley, A., Chen, K. Y., Simchowitz, L., & Celi, F. S. (2014). Moderate weight loss is sufficient to affect thyroid hormone homeostasis and inhibit its peripheral conversion. Thyroid: official journal of the American Thyroid Association, 24(1), 19–26.
Zutinic, A., Blauw, G. J., Pijl, H., Ballieux, B. E., Westendorp, R. G. J., Roelfsema, F., & van Heemst, D. (2020). Circulating Thyroid Hormone Profile in Response to a Triiodothyronine Challenge in Familial Longevity. Journal of the Endocrine Society, 4(10), bvaa117.
Si, K., Hu, Y., Wang, M., Apovian, C. M., Chavarro, J. E., & Sun, Q. (2022). Weight loss strategies, weight change, and type 2 diabetes in US health professionals: A cohort study. PLoS medicine, 19(9), e1004094.
Hatoum, I. J., & Kaplan, L. M. (2013). Advantages of percent weight loss as a method of reporting weight loss after Roux-en-Y gastric bypass. Obesity (Silver Spring, Md.), 21(8), 1519–1525.
Russell, W., Harrison, R. F., Smith, N., Darzy, K., Shalet, S., Weetman, A. P., & Ross, R. J. (2008). Free triiodothyronine has a distinct circadian rhythm that is delayed but parallels thyrotropin levels. The Journal of clinical endocrinology and metabolism, 93(6), 2300–2306.
Welsh, K. J., & Soldin, S. J. (2016). DIAGNOSIS OF ENDOCRINE DISEASE: How reliable are free thyroid and total T3 hormone assays?. European journal of endocrinology, 175(6), R255–R263.
Jonklaas, J., Bianco, A. C., Bauer, A. J., Burman, K. D., Cappola, A. R., Celi, F. S., Cooper, D. S., Kim, B. W., Peeters, R. P., Rosenthal, M. S., Sawka, A. M., & American Thyroid Association Task Force on Thyroid Hormone Replacement (2014). Guidelines for the treatment of hypothyroidism: prepared by the american thyroid association task force on thyroid hormone replacement. Thyroid: official journal of the American Thyroid Association, 24(12), 1670–1751.
Mullur, R., Liu, Y. Y., & Brent, G. A. (2014). Thyroid hormone regulation of metabolism. Physiological reviews, 94(2), 355–382.
Vaitkus, J. A., Farrar, J. S., & Celi, F. S. (2015). Thyroid Hormone Mediated Modulation of Energy Expenditure. International journal of molecular sciences, 16(7), 16158–16175. https://doi.org/10.3390/ijms160716158
Tagliaferri, M., Berselli, M. E., Calò, G., Minocci, A., Savia, G., Petroni, M. L., Viberti, G. C., & Liuzzi, A. (2001). Subclinical hypothyroidism in obese patients: relation to resting energy expenditure, serum leptin, body composition, and lipid profile. Obesity research, 9(3), 196–201.

Table 1 to 3 are available in the Supplementary Files section.

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The Effect of Baseline Thyroid Function on Weight Loss Outcomes in Euthyroid Individuals Undergoing Full Meal Replacement Therapy

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