Polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS), is a common, heterogeneous endocrine–metabolic disorder affecting women of reproductive age [1]. A recent global meta-analysis estimated its prevalence at 12.1% using the Rotterdam criteria [2]. Diagnosis in adults requires at least two of three features—clinical or biochemical hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology or elevated anti-Müllerian hormone—after excluding alternative disorders [3].

Obesity is common in PMOS and may aggravate insulin resistance, hyperandrogenism, ovulatory dysfunction and cardiometabolic risk [4,5]. Thyroid dysfunction is also clinically relevant because it may produce overlapping reproductive and metabolic manifestations. Meta-analyses have demonstrated higher frequencies of subclinical hypothyroidism and autoimmune thyroid disease among women with PCOS than among unaffected controls [6,7]. Furthermore, population-based evidence suggests that increasing body mass index is associated with higher thyroid-stimulating hormone (TSH) and lower free thyroxine (FT4) concentrations, indicating a potential interaction between adiposity and thyroid function [8].

Indian studies have similarly reported an increased burden of thyroid abnormalities among women with PCOS [9]. However, evidence directly comparing TSH, FT4 and free triiodothyronine (FT3) between obese and non-obese women with PMOS, particularly in district-hospital populations, remains limited. Therefore, this study aimed to compare thyroid function parameters and biochemical thyroid dysfunction between obese and non-obese women with PMOS attending District Hospital, Chitradurga, and to assess their associations with BMI and waist circumference.

Objectives

Primary objective

1. To compare serum thyroid-stimulating hormone, free triiodothyronine and free thyroxine levels between obese and non-obese women with polyendocrine metabolic ovarian syndrome.

Secondary objectives

2. To determine and compare the prevalence and pattern of biochemical thyroid dysfunction, including subclinical hypothyroidism, overt hypothyroidism, subclinical hyperthyroidism and overt hyperthyroidism, between obese and non-obese women with polyendocrine metabolic ovarian syndrome.
3. To assess the association of body mass index and other anthropometric parameters with serum thyroid-stimulating hormone, free triiodothyronine and free thyroxine levels among women with polyendocrine metabolic ovarian syndrome.

Study design and participants

A hospital-based comparative cross-sectional study was conducted at District Hospital, Chitradurga, Karnataka, from December 2025 to May 2026. The study included 200 premenopausal women diagnosed with polyendocrine metabolic ovarian syndrome (PMOS; formerly polycystic ovary syndrome), comprising 100 obese and 100 non-obese participants. PMOS was diagnosed using the 2023 international criteria, requiring at least two of the following after exclusion of alternative causes: ovulatory dysfunction, clinical or biochemical hyperandrogenism, and polycystic ovarian morphology or an elevated anti-Müllerian hormone level.

Participants were classified as obese when BMI was ≥25 kg/m² and as non-obese when BMI was 18.5–24.9 kg/m². Pregnant, lactating or postmenopausal women; those receiving thyroid medication; and those with pituitary disease, severe systemic illness or other endocrine disorders that could explain the clinical presentation were excluded. Written informed consent was obtained from all participants.

Data collection and laboratory assessment

Demographic characteristics, menstrual and reproductive history, PMOS features, thyroid-related symptoms, diabetes or prediabetes status, and use of metformin or hormonal contraceptives were recorded using a structured proforma. Body weight and height were measured using standardised procedures, and BMI was calculated as weight in kilograms divided by height in metres squared. Waist circumference was measured using a non-stretchable tape, and waist-to-height ratio was calculated.

Venous blood was collected under aseptic conditions, and serum thyroid-stimulating hormone (TSH), free thyroxine (FT4) and free triiodothyronine (FT3) were measured using an automated chemiluminescent immunoassay on the same analytical platform throughout the study. Laboratory-specific adult reference intervals were used; the TSH reference range was 0.27–4.20 mIU/L. Thyroid status was classified as euthyroid, subclinical hypothyroidism, overt hypothyroidism, subclinical hyperthyroidism or overt hyperthyroidism according to the TSH, FT4 and FT3 results.

Statistical analysis

Continuous variables were summarised as mean with standard deviation or median with interquartile range, according to their distribution, and categorical variables as frequencies and percentages. Between-group comparisons were performed using the independent-samples t-test, Welch t-test or Mann–Whitney U test for continuous variables and the chi-square or Fisher–Freeman–Halton exact test for categorical variables.

Associations of BMI and waist circumference with thyroid parameters were assessed using Spearman correlation and multivariable linear regression. TSH was natural-log transformed, and regression effects were expressed as percentage change. Multivariable logistic regression was used to estimate the association between obesity and biochemical thyroid dysfunction after adjustment for age, diabetes or prediabetes, metformin use and hormonal contraceptive use. Effect estimates were reported with 95% confidence intervals, and a two-sided p value <0.05 was considered statistically significant. Analyses were performed using SPSS version 26.

Study population and participant characteristics

All 200 participants were included in the analysis, comprising 100 obese and 100 non-obese women with PMOS. Compared with the non-obese group, obese participants were older and had greater BMI, waist circumference, and waist-to-height ratio. Ovulatory dysfunction, diabetes or prediabetes, and metformin use were also more frequent in the obese group, whereas the prevalence of hyperandrogenism, ovarian-marker criteria, and thyroid-related symptoms was similar between groups (Table 1).

Thyroid function parameters

Serum TSH was higher in the obese group than in the non-obese group [median 2.64 (IQR 2.21-4.07) vs 2.21 (IQR 1.65-2.74) mIU/L; U = 6500.5, p < 0.001]. Mean FT4 was lower in obese participants [1.23 (SD 0.20) vs 1.32 (SD 0.19) ng/dL; mean difference -0.09 ng/dL, 95% CI -0.14 to -0.03; p = 0.001]. FT3 levels did not differ between groups (p = 0.517) (Table 2 and Figure 1).

Biochemical thyroid dysfunction

Biochemical thyroid dysfunction was present in 24 (24.0%) obese participants and 12 (12.0%) non-obese participants (risk ratio 2.00, 95% CI 1.06-3.77; p = 0.027). The association remained significant after adjustment for age, diabetes or prediabetes, metformin use, and hormonal contraceptive use (adjusted OR 2.56, 95% CI 1.15-5.71; p = 0.021).

Subclinical hypothyroidism was the most frequent abnormality in both groups, occurring in 16 (16.0%) obese and 7 (7.0%) non-obese participants. The overall distribution of the five thyroid-status categories did not differ significantly between groups (exact p = 0.210) (Table 3 and Figure 2).

Association of anthropometric measures with thyroid parameters

BMI and waist circumference were positively correlated with TSH and inversely correlated with FT4; neither measure was associated with FT3.

In adjusted linear models, each 1 kg/m² increase in BMI was associated with a 3.05% increase in TSH and a 0.012 ng/dL decrease in FT4.

Each 5 cm increase in waist circumference was associated with a 6.57% increase in TSH and a 0.027 ng/dL decrease in FT4. Adjusted associations with FT3 remained non-significant (Table 4).

Table 1. Participant characteristics according to BMI group

Values are mean (SD), median (IQR), or n (%) as indicated. Independent-samples t-tests, Welch t-tests, Mann-Whitney U tests, and Pearson chi-square tests were used as appropriate. BMI, body mass index; IQR, interquartile range; PMOS, polyendocrine metabolic ovarian syndrome; SD, standard deviation.

Table 2. Comparison of thyroid function parameters between BMI groups

Group differences are obese minus non-obese. †Median difference; no confidence interval was estimated. TSH was compared using the Mann-Whitney U test; FT4 and FT3 were compared using independent-samples t-tests. CI, confidence interval; FT3, free triiodothyronine; FT4, free thyroxine; IQR, interquartile range; SD, standard deviation; TSH, thyroid-stimulating hormone.

Table 3. Prevalence and pattern of biochemical thyroid dysfunction

The crude prevalence comparison used a Pearson chi-square test. The adjusted odds ratio was obtained from logistic regression controlling for age, diabetes or prediabetes, metformin use, and hormonal contraceptive use. The distribution across all five mutually exclusive thyroid-status categories was compared using the Fisher-Freeman-Halton exact test (p = 0.210). aOR, adjusted odds ratio; CI, confidence interval; RR, risk ratio.

Table 4. Associations of BMI and waist circumference with thyroid function parameters

Panel A. Spearman rank correlations

denotes Spearman's rank correlation coefficient.

Panel B. Adjusted linear regression

Separate models were fitted for BMI and waist circumference. All models were adjusted for age, diabetes or prediabetes, metformin use, and hormonal contraceptive use. TSH was natural-log transformed; effects are therefore expressed as percentage change. CI, confidence interval; FT3, free triiodothyronine; FT4, free thyroxine; TSH, thyroid-stimulating hormone.

In this comparative study of 200 women with PMOS, obese participants had higher serum TSH, lower FT4 and a twofold greater prevalence of biochemical thyroid dysfunction than non-obese participants, whereas FT3 was comparable between groups. These differences persisted after adjustment for age, diabetes or prediabetes, metformin use and hormonal contraceptive use. Moreover, BMI and waist circumference showed dose-dependent positive associations with TSH and inverse associations with FT4, without corresponding associations with FT3. Together, these findings suggest that general and central adiposity are associated predominantly with the TSH–FT4 axis rather than with a uniform reduction in circulating thyroid hormones.

The observed association between obesity and thyroid dysfunction is consistent with some, but not all, PCOS literature. In an Indian study of 287 women with PCOS, Nayak et al. reported that 61% were overweight; however, subclinical hypothyroidism did not differ significantly between lean and overweight groups. Overweight participants were nevertheless older and had higher testosterone and systolic and diastolic blood pressures [10]. In contrast, Tagliaferri et al. studied 154 women with PCOS and 88 controls and found subclinical hypothyroidism in 14% and 1%, respectively. Among obese women with PCOS, TSH correlated with insulin secretion, clamp-measured insulin resistance, dehydroepiandrosterone sulphate and cortisol, indicating that body weight modified the metabolic relevance of TSH [11]. Mueller et al. similarly found that a TSH threshold near 2 mIU/L best identified insulin resistance; women above this threshold had higher BMI and greater insulin resistance, and the association remained independent of age and BMI [12]. Compared with these studies, the present analysis strengthens the evidence for an adiposity–thyroid relationship by demonstrating both categorical differences between equally sized BMI groups and continuous associations with BMI and waist circumference.

The hormonal pattern also merits consideration. Ganie et al. compared 62 women with PCOS and subclinical hypothyroidism with 291 euthyroid women with PCOS. Mean TSH was 7.13 versus 2.51 mIU/L, while FT3 and FT4 were comparable; triglycerides were higher in the subclinical hypothyroidism group, but phenotypic manifestations and insulin-resistance measures were not materially different [13]. In a larger Bangladeshi study of 465 women with PCOS, Kamrul-Hasan et al. reported subclinical hypothyroidism in 10.8% and anti-thyroid peroxidase antibody positivity in 18.3%. Overweight or obesity was more frequent in the subclinical hypothyroidism group than in euthyroid participants (90.0% vs 75.2%), as was central obesity (88.0% vs 73.7%); median TSH was 7.38 versus 1.32 mIU/L and mean FT4 was 1.09 versus 1.31 ng/dL. Despite these differences, glucose and lipid measurements were largely similar between groups [14]. The lower FT4 and unchanged FT3 observed in the present study may therefore represent an early or compensated alteration in thyroid physiology, although longitudinal measurements are required to establish persistence.

The overall prevalence of subclinical hypothyroidism in the present cohort was 11.5%, increasing from 7% in non-obese to 16% in obese participants. These estimates lie within the range reported in previous PCOS cohorts, although direct comparison is influenced by the TSH threshold used. Huang et al. identified subclinical hypothyroidism in 60 of 428 Chinese women with PCOS (14.0%) using a TSH threshold of 5.0 mIU/L. Its distribution did not differ across PCOS phenotypes, but TSH remained positively associated with LDL cholesterol after adjustment for age, BMI, waist-to-hip ratio, fasting glucose, insulin resistance and free androgen index; a TSH value of 4.07 mIU/L best identified elevated LDL cholesterol [15]. Benetti-Pinto et al. found subclinical hypothyroidism in 19 of 168 women (11.3%) using a 4.5–10 mIU/L definition. Their cohort was young and predominantly obese, with a mean age of 24 years and BMI of 33.4 kg/m²; women with subclinical hypothyroidism had higher LDL cholesterol (122.6 vs 105.6 mg/dL) and prolactin (17.7 vs 14.0 ng/mL), but no major differences in insulin resistance or PCOS phenotype [16]. These prevalence estimates closely approximate the current findings despite differences in population and laboratory definitions.

Conversely, studies using lower TSH thresholds have reported higher prevalence. Bedaiwy et al. classified TSH >2.5 mIU/L as subclinical hypothyroidism in 137 women with PCOS and identified a prevalence of 21.9%. Mean age, BMI and mean metabolic measurements were similar between thyroid groups; nevertheless, abnormal fasting glucose was three times more likely in women with subclinical hypothyroidism (OR 3.01, 95% CI 1.12–8.07), and abnormal HOMA was associated with an OR of 3.70 (95% CI 1.14–12.00), independent of age and BMI [17]. This threshold-related variation supports the use of assay-specific adult reference intervals and cautions against comparing prevalence without considering the operational definition. It also explains why the present prevalence of all biochemical thyroid dysfunction—24% in obese and 12% in non-obese participants—should not be equated directly with studies restricted to subclinical hypothyroidism.

A notable contribution of the present study is its direct comparison of equally sized obese and non-obese PMOS groups, with simultaneous measurement of TSH, FT4 and FT3 and assessment of both BMI and waist circumference. Most comparator studies classified participants according to thyroid status or compared PCOS with unaffected controls. The persistence of the association after multivariable adjustment, together with concordant findings for BMI and waist circumference, reduces—but does not eliminate—the likelihood that age, dysglycaemia or medication use fully explains the results. The similarity of thyroid-related symptoms between groups further indicates that clinical symptoms alone may not reliably distinguish biochemical abnormalities.

The study has several limitations. Its cross-sectional design precludes determination of whether adiposity alters thyroid function or thyroid dysfunction contributes to weight gain. Recruitment from a single district hospital may limit generalisability, and the obese group was older and had more dysglycaemia and medication exposure despite statistical adjustment. Thyroid function was assessed once; transient TSH abnormalities could therefore have been misclassified. Thyroid antibodies, thyroid ultrasonography, iodine status and detailed dietary or inflammatory variables were not assessed, preventing distinction between obesity-related physiological changes and autoimmune thyroid disease. In particular, the high anti-thyroid peroxidase positivity among participants with subclinical hypothyroidism in the Bangladeshi cohort suggests that unmeasured autoimmunity may contribute to the observed association [14]. Finally, dichotomising BMI may reduce information, although the continuous regression analyses partly address this limitation.

Obese women with PMOS had higher TSH, lower FT4 and a greater burden of biochemical thyroid dysfunction than non-obese women, while FT3 remained similar. The independent associations with both BMI and waist circumference support adiposity as an important modifier of thyroid biochemical status in PMOS. These findings justify careful thyroid assessment in metabolically high-risk women with PMOS, while prospective studies incorporating repeat testing, thyroid autoantibodies and longitudinal weight change are needed to determine causality and clinical consequences.

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