Abstract
Background:
Thyroid hormones are essential regulators of energy expenditure, thermogenesis, and body composition. Although overt thyroid dysfunction is well known to alter basal metabolic rate (BMR) and body mass, emerging evidence suggests that even hormonal variations within the reference range may exert measurable effects on metabolic and body composition profiles. Women of reproductive age represent a population particularly sensitive to hormonal oscillations due to the interplay between endocrine, reproductive, and cardiometabolic health.
Objective:
The study aimed to a) analyze thyroid hormone levels (TSH, FT3, FT4) alongside anthropometric and body composition parameters in women of reproductive age; b) examine thyroid hormone levels, BMR, and body composition parameters across age groups; and c) investigate associations of thyroid hormones with BMR, body composition components, and unfavorable body composition patterns (visceral adiposity, elevated metabolic age, obesity) as well as metabolic indicators..
Methods:
A total of 117 women aged 18–45 years were included in this cross-sectional, observational study conducted in Bosnia and Herzegovina between September 2023 and November 2024. Thyroid hormone levels were measured using electrochemiluminescence assays, while body composition was assessed by bioelectrical impedance analysis. Statistical analyses included descriptive methods, Pearson’s correlation, and Chi-square testing, with significance set at p<0.05.
Results:
TSH showed significant positive associations with fat-free mass, muscle mass, and BMR (p<0.05). FT3 was inversely correlated with metabolic age and visceral fat, while FT4 demonstrated weak negative associations with fat-free mass and metabolic age (p<0.05). Significant age-related differences were observed in fat percentage, fat mass, BMI, visceral fat, and metabolic age, with the most unfavorable profiles in women aged 31–40 years.
Conclusion:
Thyroid hormones, even within the reference range, are associated with body composition and metabolic parameters in women of reproductive age. Their role as early indicators of unfavorable metabolic patterns highlights potential implications for reproductive and cardiovascular risk assessment.
Keywords: Thyroid Hormones, Body Composition, Obesity
1. BACKGROUND
Thyroid hormones are key regulators of energy metabolism, thermogenesis, and substrate redistribution across multiple tissues, including skeletal muscle, liver, and brown/white adipose tissue. Through their actions on nuclear receptors and the local conversion of T4 to T3 (via type 2 deiodinase), they modulate basal energy expenditure, lipid and carbohydrate oxidation, as well as body composition. Disorders of thyroid function (hypo- or hyperthyroidism) lead to predictable alterations in basal metabolic rate and body mass; however, accumulating evidence indicates that even variations of thyroid hormones within the reference range exert measurable metabolic effects (1).
The global epidemic of overweight and obesity underscores the importance of better understanding the hormonal determinants of energy balance in women of reproductive age. According to the WHO report, in 2022, 43% of adults were overweight and 16% were obese; these proportions have increased across all regions, with consistently higher rates observed among women in several age-specific groups. Longitudinal data further confirm a decades-long upward trend, with a persistently greater prevalence of obesity among women compared to men (2, 3).
At the same time, thyroid disorders are common in the general population and disproportionately affect women. In iodine-sufficient settings, the prevalence of clinical hypothyroidism is estimated at 1–2%, while subclinical hypothyroidism affects approximately 4–10% of individuals, with higher rates in women. More recent U.S. data estimate the overall prevalence of hypothyroidism at about 4.6%. These conditions are clinically relevant during reproductive years due to their potential effects on fertility, menstrual cycles, and cardiometabolic risk profiles (4, 5).
Several studies in euthyroid populations have demonstrated associations between body composition, energy expenditure, and variations in thyroid hormones. Large cross-sectional analyses have reported that higher TSH and/or lower fT4 correlate with body mass index and fat mass, whereas higher fT3 (and an increased fT3/fT4 ratio) is linked to an unfavorable metabolic profile, including insulin resistance and dyslipidemia. Moreover, both fT3 and fT4 have been shown to be associated with basal metabolic rate (BMR) even in the absence of overt thyroid dysfunction, and longitudinal changes in thyroid status correspond to alterations in energy expenditure (6-8).
Nevertheless, existing evidence has several limitations: heterogeneity in methods for assessing body composition, differences in age and sex distribution of study samples, and insufficient adjustment for potential confounders such as age, BMI, lipid levels, and glycemic status (6, 9). Importantly, studies specifically focused on women of reproductive age remain underrepresented, despite this population exhibiting unique endocrine-metabolic patterns and cardiometabolic risks. In this context, the aim of our study is to investigate in detail the associations of TSH, fT3, and fT4 with basal metabolic rate and body composition parameters in women of reproductive age.
2. OBJECTIVE
The aim of the study were threefold: a) to analyze laboratory values of thyroid hormones (TSH, free triiodothyronine [FT3], and free thyroxine [FT4]) alongside basic anthropometric characteristics and body composition parameters in women of reproductive age; b) to examine thyroid hormone levels, basal metabolic rate (BMR), and body composition parameters across age groups; and c) to investigate the associations of thyroid hormones (TSH, FT3, FT4) with BMR, components of body composition, and unfavorable body composition patterns (visceral adiposity, elevated metabolic age, obesity), as well as with metabolic indicators.
3. PATIENTS AND METHODS
Participants
A total of 117 female participants of reproductive age (18–45 years) were included in the study. The research was conducted in both public and private laboratories across Bosnia and Herzegovina, specifically at Polyclinic Agram Sarajevo, Atrium Laboratory Goražde, General Hospital Tešanj, and the Institute for Health Development, University of Sarajevo, Faculty of Health Studies, during the period from September 2023 to November 2024. The inclusion criteria comprised women of reproductive age (18–45 years) without confirmed diagnoses of cardiovascular diseases, diabetes, or thyroid cancer; participants not using medications that could influence laboratory parameters; non-pregnant and non-lactating participants and those who provided voluntary informed consent to participate. The sample was obtained using the snowball sampling method.
Procedure and Ethical Considerations
Prior to commencing the study, approval was obtained from the management of the University of Sarajevo, Faculty of Health Studies. Participants were informed of the study objectives in accordance with the ethical principles of the Declaration of Helsinki. Participation was voluntary, and all participants signed informed consent before inclusion.
Methods and Measures
The research is an experimental, cross-sectional, observational, descriptive–analytical study.
Laboratory Analysis
The laboratory analysis included the determination of thyroid hormone concentrations (TSH, fT3, fT4) using Cobas e 411 and Mindray BS-480 analyzers, based on the electrochemiluminescence method. Pre-analytical sample preparation involved serum separation by centrifugation at 3600 rpm for 5 minutes. Prior to analyses, routine internal quality control was performed on the analyzers, and the Levey–Jennings control chart with Westgard rules was applied to ensure the accuracy and reliability of the system.
Body Composition Assessment
Body composition parameters were assessed using the Tanita SC 330ST body analyzer. The measurement method was based on bioelectrical impedance, with strict adherence to all prerequisites necessary to ensure accurate results. The body composition parameters analyzed in participants included: body weight, body mass index (BMI), body fat percentage and mass, muscle mass, fat-free mass (FFM), total body water (TBW), basal metabolic rate (BMR), visceral fat level, ideal body weight, bone mass, and metabolic age. Body height was measured using a stadiometer, with an accuracy of 0.1 cm.
Statistical Analysis
Following data collection, all results were entered into an electronic database created in Microsoft Office Excel 365. Statistical analyses were performed using IBM SPSS Statistics, version 27.0 (IBM Corporation, Armonk, NY, USA). A p-value of <0.05 was considered statistically significant. For descriptive statistics, mean values, standard deviation, median, and interquartile range were calculated. The associations between thyroid hormone levels and anthropometric parameters were analyzed using Pearson’s correlation. The correlation coefficient was interpreted as follows: 0.0 to ±0.10 negligible, ±0.11 to ±0.25 weak, ±0.251 to ±0.60 moderate, ±0.61 to ±0.80 strong, and ±0.81 to ±1.0 very strong. The Chi-square test (χ2) was applied to examine differences between expected and observed values within one or more categories of contingency tables. Statistical significance was set at the p<0.05 level.
4. RESULTS
Age Distribution of Participants
The age analysis revealed a mean age of 33.74 ± 7.92 years. The youngest participant was 18 years old, while the oldest was 45 years old. The median age was 35.0 years, with an interquartile range of 26 to 40 years. Further stratification showed that 34.2% of participants were between 18 and 30 years of age, 41.9% were between 31 and 40 years, and 23.9% were between 41 and 45 years.
Laboratory Analysis of Thyroid Hormones
The analysis revealed that the mean value of thyroid-stimulating hormone (TSH) among participants was 3.32 ± 9.24, with a minimum of 0.008 and a maximum of 100.00. The mean value of free triiodothyronine (FT3) was 4.37 ± 1.52, ranging from 1.20 to 16.63. The mean value of free thyroxine (FT4) was 14.89 ± 3.60. When compared with the reference ranges, 84.6% of participants aged 18–30 years, 77.6% of those aged 31–40 years, and 85.7% of those aged 41–45 years had TSH values within the reference range. No statistically significant difference was observed across age groups (p = 0.579). For FT3, 82.5% of participants under 30 years, 69.4% of those aged 31–40 years, and 82.1% of those aged 41–45 years had values within the reference range, with no statistically significant difference detected (p = 0.260). In contrast, FT4 levels were within the reference range in 97.5% of participants under 30 years, 79.6% of those aged 31–40 years, and 85.7% of those aged 41–45 years. A statistically significant difference was identified across these age groups (p = 0.041) (Table 1).
Table 1. Prevalence of Thyroid Hormone Reference Values.
| Parameters | Reference Values | 18-30 years | 31-40 years | 41-45 years | χ2 | p |
|---|---|---|---|---|---|---|
| % | % | % | ||||
| TSH | No | 15.4 | 22.4 | 14.3 | 1.094 | 0.579 |
| Yes | 84.6 | 77.6 | 85.7 | |||
| FT3 | No | 17.5 | 30.6 | 17.9 | 2.698 | 0.260 |
| Yes | 82.5 | 69.4 | 82.1 | |||
| FT4 | No | 2.5 | 20.4 | 14.3 | 6.390 | 0.041 |
| Yes | 97.5 | 79.6 | 85.7 |
Analysis of Anthropometric and Body Composition Parameters
The analysis revealed no significant differences in participants’ height across age groups, with mean values ranging from 167.75 to 168.31 cm. Body weight analysis showed that participants aged 18–30 years had a mean body weight of 66.43 ± 9.10 kg, while those aged 31–40 years had a mean weight of 76.79 ± 17.76 kg. In the 41–45 age group, the mean body weight was 75.80 ± 15.82 kg. A statistically significant difference was observed, indicating that participants under 30 years had significantly lower body weight (F = 4.778, p = 0.010). The percentage of body fat was 27.73 ± 7.69% in participants younger than 30 years, 34.45 ± 7.26% in those aged 31–40 years, and 33.58 ± 8.01% in those aged 41–45 years. A statistically significant difference was detected (F = 7.912, p < 0.001). Similarly, fat mass differed significantly by age group, with younger participants (<30 years) showing significantly lower fat mass (F = 8.850, p < 0.001). No significant differences were observed in fat-free mass (FFM) (F = 0.657, p = 0.521) or skeletal muscle mass (F = 0.946, p = 0.392) across age groups. The proportion of body water was 51.61 ± 6.85% in participants under 30 years, 45.16 ± 7.40% in those aged 31–40 years, and 46.77 ± 5.16% in those aged 41–45 years. A statistically significant difference was found, with younger participants having a higher water percentage (F = 8.825, p < 0.001). Bone mass did not differ significantly across groups (p = 0.408). No significant differences were observed in basal metabolic rate (BMR), with mean values of 1460.2 ± 197.31 kcal in participants younger than 30 years, 1531.06 ± 220.33 kcal in those aged 31–40 years, and 1492.46 ± 228.55 kcal in those aged 41–45 years (F = 1.020, p = 0.364). Metabolic age, however, differed significantly between groups: participants under 30 years had a mean metabolic age of 29.68 ± 14.20 years, those aged 31–40 years had 50.87 ± 13.90 years, and those aged 41–45 years had 46.25 ± 12.57 years (F = 23.312, p < 0.001). When compared to chronological age, participants aged 31–40 years showed particularly unfavorable metabolic age results. Body mass index (BMI) averaged 23.85 ± 3.46 kg/m2 in participants under 30 years, 27.55 ± 4.71 kg/m2 in those aged 31–40 years, and 26.76 ± 5.23 kg/m2 in those aged 41–45 years. A statistically significant difference was detected among groups (F = 6.413, p = 0.002). The estimated ideal body weight showed minimal variation across age groups, ranging from 61.70 ± 5.36 kg to 62.57 ± 5.11 kg, with no statistically significant difference (F = 0.305, p = 0.738) (Table 2).
Table 2. Analysis of Anthropometric and Body Composition Parameters.
| Parameters | 18-30 years | 31-40 years | 41-45 years | F | p | |||
|---|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | |||
| Height (cm) | 167.45 | 6.61 | 168.31 | 6.86 | 168.14 | 4.93 | 0.187 | 0,829 |
| Weight (kg) | 66.43 | 9.10 | 76.79 | 17.76 | 75.80 | 15.82 | 4.778 | 0.010 |
| Fat (%) | 27.73 | 7.69 | 34.45 | 7.26 | 33.58 | 8.01 | 7.912 | <0.001 |
| Fat Mass (kg) | 18.75 | 6.58 | 27.72 | 9.98 | 26.25 | 11.19 | 8.850 | <0.001 |
| Fat-free Mass (kg) | 48.34 | 7.61 | 50.58 | 9.38 | 49.55 | 7.69 | 0.657 | 0.521 |
| Muscle Mass (kg) | 45.87 | 7.24 | 48.00 | 7.10 | 45.68 | 10.83 | 0.946 | 0.392 |
| Total Body Water (kg) | 33.17 | 8.08 | 35.50 | 7.37 | 34.99 | 5.82 | 1.006 | 0.369 |
| Total Body Water (%) | 51.61 | 6.85 | 45.16 | 7.40 | 46.77 | 5.16 | 8.825 | <0.001 |
| Bone Mass (kg) | 3.12 | 3.71 | 2.55 | 0.36 | 2.51 | 0.36 | 0.904 | 0.408 |
| Basal Metabolic Rate (kJ) | 6117.58 | 822.66 | 6407.66 | 926.23 | 6246.86 | 955.42 | 0.985 | 0.377 |
| Basal Metabolic Rate (kcal) | 1460.52 | 197.31 | 1531.06 | 220.33 | 1492.46 | 228.55 | 1.020 | 0.364 |
| Metabolic age | 29.68 | 14.20 | 50.87 | 13.90 | 46.25 | 12.57 | 23.312 | <0.001 |
| Viscelar Fat | 3.39 | 2.70 | 8.11 | 4.97 | 6.93 | 3.61 | 12.864 | <0.001 |
| BMI | 23.85 | 3.46 | 27.55 | 4.71 | 26.76 | 5.23 | 6.413 | 0.002 |
| Idealna weight (kg) | 61.70 | 5.36 | 62.57 | 5.11 | 62.28 | 3.68 | 0.305 | 0.738 |
Categorization of Body Fat Percentage, Visceral Fat, and BMI in Relation to Age
The analysis showed that, based on body fat percentage, 6.5% of participants under 30 years were classified as obese. Among participants aged 31–40 years, the proportion of obesity was 25.5%, while in the 41–45 age group, it was 21.4%. No statistically significant difference was observed (p = 0.067).With respect to visceral fat classification, 25.8% of participants under 30 years had elevated visceral fat levels. In the 31–40 age group, 74.5% demonstrated elevated visceral fat, while in the 41–45 age group, 71.4% had increased visceral fat. A statistically significant difference was confirmed (p < 0.001). Regarding body mass index (BMI), the prevalence of obesity was 6.5% among participants under 30 years, 23.4% among those aged 31–40 years, and 21.4% among those aged 41–45 years. A statistically significant difference was found (p = 0.017) (Table 3).
Table 3. Distribution of Participants According to Body Fat Percentage and Body Mass Index in Relation to Age.
| Classification | Status | 18-30 years |
31-40 years |
41-45 years |
χ2 | p |
|---|---|---|---|---|---|---|
| % | % | % | ||||
| Classification According to Body Fat Percentage | Underweight | 12.9 | 2.1 | 3.6 | 11.788 | 0.067 |
| Normal Fat Percentage | 64.5 | 42.6 | 42.9 | |||
| Excess Fat Percentage | 16.1 | 29.8 | 32.1 | |||
| Obesity | 6.5 | 25.5 | 21.4 | |||
| Classification of Visceral Fat | Normal Amount | 74.2 | 25.5 | 28.6 | 20.617 | <0.001 |
| Increased Amount | 25.8 | 74.5 | 71.4 | |||
| Classification Based on Body Mass Index (BMI) | Underweight | 0.0 | 0.0 | 0.0 | 11.997 | 0.017 |
| Normal Body Weight | 71.0 | 31.9 | 46.4 | |||
| Overweight | 22.6 | 44.7 | 32.1 | |||
| Obesity | 6.5 | 23.4 | 21.4 |
Association Between Thyroid Hormones and Body Composition Parameters in Women of Reproductive Age
The analysis demonstrated that TSH was significantly associated with fat-free mass (FFM, kg) (r = 0.245, p = 0.012), muscle mass (r = 0.242, p = 0.013), and basal metabolic rate (BMR) (r = 0.236, p = 0.016). FT3 values showed significant correlations with metabolic age (r = –0.250, p = 0.010) and visceral fat (r = –0.236, p = 0.015). FT4 values exhibited a weak correlation with FFM (r = –0.196, p = 0.044) and metabolic age (r = –0.233, p = 0.016) (Table 4).
Table 4. Association Between Thyroid Hormones and Body Composition Parameters in Women of Reproductive Age.
| Parameters | TSH | FT3 | FT4 | |
|---|---|---|---|---|
| Height (cm) | r | 0.096 | 0.060 | -0.152 |
| p | 0.322 | 0.537 | 0.115 | |
| Weight (kg) | r | -0.034 | -0.019 | -0.148 |
| p | 0.731 | 0.844 | 0.130 | |
| Fat (%) | r | 0.023 | -0.035 | -0.101 |
| p | 0.817 | 0.720 | 0.304 | |
| Total Body Water (TBW) (%) | r | -0.015 | 0.058 | 0.062 |
| p | 0.878 | 0.558 | 0.528 | |
| Bone Mass (kg) | r | 0.112 | -0.058 | 0.145 |
| p | 0.255 | 0.552 | 0.138 | |
| Basal Metabolic Rate (kcal) | r | 0.234 | -0.106 | -0.186 |
| p | 0.016 | 0.277 | 0.056 | |
| Metabolic Age | r | 0.114 | -0.250 | -0.233 |
| p | 0.246 | 0.010 | 0.016 | |
| Viscelar Fat | r | 0.155 | -0.236 | -0.183 |
| p | 0.113 | 0.015 | 0.060 | |
| Body Mass Index | r | 0.116 | -0.097 | -0.133 |
| p | 0.241 | 0.324 | 0.177 | |
| Ideal Weight (kg) | r | 0.110 | 0.041 | -0.162 |
| p | 0.265 | 0.675 | 0.097 | |
| Degree of Obesity | r | 0.137 | -0.101 | -0.147 |
| p | 0.165 | 0.301 | 0.133 | |
| Fat-free Mass (FFM) | r | 0.245 | -0.130 | -0.196 |
| p | 0.012 | 0.183 | 0.044 | |
| Muscle Mass (kg) | r | 0.242 | -0.060 | -0.162 |
| p | 0.013 | 0.544 | 0.096 | |
5. DISCUSSION
Thyroid dysfunction and hormonal variations, even within the reference range, have long been the subject of research due to their potential impact on energy metabolism, reproductive health, and cardiovascular risk. In the past decade, increasing evidence has suggested that even subtle oscillations in TSH, FT3, and FT4 values may have clinical significance in regulating body composition and metabolic processes in women of reproductive age - a population particularly sensitive to hormonal changes due to interactions with reproductive status and long-term cardiovascular outcomes (10, 11).
Our analyses demonstrated that TSH positively correlates with fat-free mass, muscle mass, and basal metabolic rate, supporting the hypothesis of a metabolic adaptation mechanism involving the preservation of muscle tissue and increased energy expenditure even in euthyroid individuals. These findings align with results from longitudinal population-based studies showing that even minor variations in TSH within the normal range can be associated with changes in body composition and energy balance (12). Elevated TSH may also reflect an adaptive response to increased fat mass through leptin activity and enhanced deiodinase function, as previously confirmed in studies investigating the relationship between thyroid hormones and central adiposity (13). Lower FT3 levels were associated with higher metabolic age and greater visceral adiposity. This pattern suggests a potential protective role of FT3 in maintaining favorable body composition, with reduced FT3 possibly serving as an early marker of adverse metabolic alterations. Recent studies have shown that the FT3/FT4 ratio is strongly linked to insulin resistance and increased cardiometabolic risk, even in individuals without overt thyroid dysfunction (14, 15). Importantly, such patterns may have implications for women’s reproductive health, as disturbances in peripheral hormone conversion have been associated with menstrual dysfunction, polycystic ovary syndrome, and reduced fertility (16).
FT4 values exhibited weak but significant negative associations with fat-free mass and metabolic age, which may indicate reduced tissue sensitivity to the hormone or a less favorable anabolic profile. Previous studies have suggested that low sensitivity to FT4 (measured by the thyroid feedback quantile-based index, TFQI) may be associated with increased risk of metabolic syndrome and type 2 diabetes (17). This association is particularly important in women of reproductive age, in whom the cumulative effects of unfavorable body composition and metabolic disturbances may contribute to earlier onset of cardiovascular disease. On a broader scale, the relationship between thyroid hormones and cardiovascular health has been confirmed in several population studies. Lower-normal TSH levels have been linked to higher ASCVD risk (18), while disturbances in peripheral hormone conversion may contribute to dyslipidemia, hypertension, and subclinical atherosclerosis (19). Among women of reproductive age, such mechanisms present a dual challenge, as they may simultaneously compromise reproductive potential and increase long-term cardiometabolic risk. Overall, the findings indicate that thyroid hormones, even within the reference range, exert a complex and multifactorial influence on body composition, metabolism, reproductive function, and cardiovascular health. This underscores the importance of an integrative approach in evaluating the endocrine profile of women of reproductive age and highlights the potential need to redefine clinical reference values in the context of individual risk, rather than relying solely on absolute laboratory thresholds.
6. CONCLUSION
This study demonstrated that thyroid hormone levels (TSH, FT3, and FT4), even within the reference range, are linked with anthropometric and body composition parameters in women of reproductive age. Differences in BMR and body composition patterns were observed across age groups, underscoring the influence of demographic factors on metabolic status. Furthermore, specific associations were identified between thyroid hormones and unfavorable body composition indicators, including visceral adiposity, elevated metabolic age, and obesity, highlighting their relevance as early metabolic markers. These findings emphasize the integrative role of thyroid hormones in energy regulation, body composition, and metabolic health, with potential implications for reproductive and cardiovascular risk assessment in women of reproductive age.
Patient Consent Form:
All participants were informed about subject of the study.
Author's Contribution:
All authors equally contributed to the conception, preparation, and translation of the manuscript, and fully adhered to ethical standards as well as the principles of research integrity and accuracy.
Conflicts of interest:
There are no conflicts of interest.
Financial support and sponsorship:
None.
REFERENCES
- 1.Mullur R, Liu YY, Brent GA. Thyroid Hormone Regulation of Metabolism. Physiological Reviews . 2014 Apr;94(2):355–382. doi: 10.1152/physrev.00030.2013. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4044302/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.World Health Organization. Obesity and overweight: key facts [Internet] Geneva: WHO; 2025. [cited 2025 May 2]. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight . [Google Scholar]
- 3.Boutari C, Mantzoros CS. A 2022 Update on the Epidemiology of Obesity and a Call to action: as Its Twin COVID-19 Pandemic Appears to Be receding, the Obesity and Dysmetabolism Pandemic Continues to Rage on. Metabolism [Internet] 2022 May 2;133(155217):155217. doi: 10.1016/j.metabol.2022.155217. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9107388/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Vanderpump MPJ. The epidemiology of thyroid disease. British Medical Bulletin. 2011 Sep 1;99(1):39–51. doi: 10.1093/bmb/ldr030. [DOI] [PubMed] [Google Scholar]
- 5.Wyne KL, Nair L, Schneiderman CP, Pinsky B, Antunez Flores O, Guo D, et al. Hypothyroidism Prevalence in the United States: A Retrospective Study Combining National Health and Nutrition Examination Survey and Claims Data, 2009–2019. Journal of the Endocrine Society. 2022 Nov 10;7(1) doi: 10.1210/jendso/bvac172. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Diniz M de FHS, Beleigoli AMR, Benseñor IM, Lotufo PA, Goulart AC, Barreto SM. Rohrmann S, editor. Association between TSH levels within the reference range and adiposity markers at the baseline of the ELSA–Brasil study. PLOS ONE. 2020 Feb 7;15(2):e0228801. doi: 10.1371/journal.pone.0228801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Marzullo P, Minocci A, Mele C, Fessehatsion R, Tagliaferri M, Pagano L, et al. Kaser S, editor. The relationship between resting energy expenditure and thyroid hormones in response to short-term weight loss in severe obesity. PLOS ONE. 2018 Oct 19;13(10):e0205293. doi: 10.1371/journal.pone.0205293. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Maushart CI, Senn JR, Loeliger RC, Siegenthaler J, Bur F, Fischer JGW, et al. Resting Energy Expenditure and Cold-induced Thermogenesis in Patients With Overt Hyperthyroidism. The Journal of Clinical Endocrinology & Metabolism. 2021 Sep 27;107(2):450–461. doi: 10.1210/clinem/dgab706. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Samuels MH, Kolobova I, Antosik M, Niederhausen M, Purnell JQ, Schuff KG. Thyroid Function Variation in the Normal Range, Energy Expenditure, and Body Composition in L-T4–Treated Subjects. The Journal of Clinical Endocrinology & Metabolism. 2017 Apr 28;102(7):2533–2542. doi: 10.1210/jc.2017-00224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Neves JS, Fontes-Carvalho R, Borges-Canha M, Leite AR, von Hafe Madalena, Vale C, et al. Association of thyroid function, within the euthyroid range, with cardiovascular risk: The EPIPorto study. Frontiers in Endocrinology. 2022 Nov 28;:13. doi: 10.3389/fendo.2022.1067801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Agnieszka Adamska, Raczkowski A, Stachurska Z, Marcin Kondraciuk, Krętowski AJ, Adamski M, et al. Body Composition and Serum Concentration of Thyroid Hormones in Euthyroid Men and Women from General Population. Journal of Clinical Medicine [Internet] 2022 Apr 11;11(8):2118–2118. doi: 10.3390/jcm11082118. [cited 2025 May 26] Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9031693/ [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Duntas LH, Biondi B. The Interconnections Between Obesity, Thyroid Function, and Autoimmunity: The Multifold Role of Leptin. Thyroid. 2013 Jun;23(6):646–653. doi: 10.1089/thy.2011.0499. [DOI] [PubMed] [Google Scholar]
- 13.Merchan-Ramirez E, Sanchez-Delgado G, Arrizabalaga-Arriazu C, Acosta FM, Arias-Tellez MJ, Munoz-Torres M, et al. Circulating concentrations of free triiodothyronine are associated with central adiposity and cardiometabolic risk factors in young euthyroid adults. Journal of Physiology and Biochemistry. 2022 Apr 6;78(3):629–640. doi: 10.1007/s13105-022-00881-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Li Y, Zhang Q, Chen L, et al. Impaired sensitivity to thyroid hormones is associated with increased body fat mass/muscle mass ratio (F/M) in the euthyroid population. Diabetol Metab Syndr. 2025;17:128. doi: 10.1186/s13098-025-01693-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Xu Y, Arash Derakhshan, Hysaj O, Wildisen L, Till Ittermann, Pingitore A, et al. The optimal healthy ranges of thyroid function defined by the risk of cardiovascular disease and mortality: systematic review and individual participant data meta-analysis. The Lancet Diabetes & endocrinology. 2023 Oct 1;11(10):743–754. doi: 10.1016/S2213-8587(23)00227-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Brown E, Obeng-Gyasi B, Hall JE, Shekhar S. The Thyroid Hormone Axis and Female Reproduction. International Journal of Molecular Sciences. 2023 Jun 6;24(12):9815–9815. doi: 10.3390/ijms24129815. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Lisowska-Myjak B, Zborowska H, Białek S, Wroczyński P, Kuch M, Skarżyńska E. Exploring associations of anthropometric parameters and serum triglycerides with serum thyroid hormones in young women. Scientific reports. 2022 Oct 17;12(1):17374. doi: 10.1038/s41598-022-22371-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kim JW, Bae HJ, Moon JS, Kim SW. Low Thyrotropin Levels Are Associated With an Increased Risk of Atherosclerotic Cardiovascular Disease in Euthyroid Individuals: The Korea National Health and Nutrition Examination Survey 2013–2015. Journal of Lipid and Atherosclerosis. 2025 Jan 1;14(2):236–236. doi: 10.12997/jla.2025.14.2.236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Kahaly GJ, Liu Y, Luca Persani Hypothyroidism: playing the cardiometabolic risk concerto. Thyroid Research. 2025 May 19;18(1) doi: 10.1186/s13044-025-00233-y. [DOI] [PMC free article] [PubMed] [Google Scholar]