Metabolic syndrome (MetS) is a constellation of interconnected clinical and biochemical abnormalities, including central obesity, insulin resistance, hypertension, dyslipidemia, and impaired glucose tolerance, all of which increase the risk of developing type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD) [1]. Its prevalence has escalated globally, posing a major health burden in both developed and developing nations. In India, lifestyle transitions, urbanization, and dietary changes have significantly contributed to the rising prevalence of MetS [2].

Thyroid dysfunction, particularly hypothyroidism and subclinical hypothyroidism, has emerged as a frequent endocrine disturbance in patients with MetS. The thyroid gland plays a crucial role in regulating metabolism, energy balance, and lipid as well as glucose homeostasis [3]. Consequently, even subtle alterations in thyroid hormone levels may impact components of metabolic syndrome. A growing body of literature suggests a bi-directional relationship between thyroid function and metabolic syndrome components, hinting at a complex physiological interaction between the two conditions [4].

Subclinical hypothyroidism has been significantly associated with increased waist circumference, insulin resistance, and dyslipidemia — cardinal features of MetS [5]. Furthermore, thyroid-stimulating hormone (TSH) levels tend to correlate positively with triglyceride levels and negatively with high-density lipoprotein (HDL) cholesterol, underscoring the endocrine-metabolic link [6]. Conversely, hyperthyroidism, though less common, may exacerbate cardiovascular risk through increased heart rate, cardiac output, and irregularities in lipid metabolism [7].

Recent studies have also indicated that the prevalence of thyroid dysfunction, particularly hypothyroidism, is higher among patients with MetS compared to the general population [8]. The underlying mechanisms are hypothesized to involve adipocyte-derived cytokines, leptin resistance, and altered deiodinase activity, all contributing to hormonal dysregulation and systemic inflammation [9]. Given that both conditions can independently elevate cardiovascular risk, their coexistence in an individual may synergistically worsen outcomes, highlighting the need for early detection and targeted intervention [10].

Understanding the spectrum of thyroid dysfunction in patients with metabolic syndrome is therefore critical for optimizing management and preventing long-term complications. Despite the mounting evidence, data from Indian populations remain limited and scattered, warranting a focused investigation.

This hospital-based cross-sectional study was conducted over a period of 18 months in the Department of Medicine at Raipur Institute of Medical Sciences, Raipur, Chhattisgarh. The study population included patients attending the routine outpatient department (OPD) and those admitted to various wards within the institute. The final sample consisted of 200 consecutive patients who were diagnosed with metabolic syndrome and provided informed written consent for participation.

The sample size was calculated based on a reported prevalence of thyroid dysfunction of approximately 28%, using the standard formula n=Z2×p×(1−p)/E2n = Z^2 \times p \times (1-p) / E^2n=Z2×p×(1−p)/E2, where Z = 1.96 for a 95% confidence level, p = 0.28, q = 0.72, and E = 20% of the prevalence. This yielded a sample size of approximately 200. The study included adults aged between 18 and 75 years who met the diagnostic criteria for metabolic syndrome according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), which requires at least three of the following five criteria: fasting blood glucose >100 mg/dl, serum triglycerides ≥150 mg/dl, HDL cholesterol <40 mg/dl for men or <50 mg/dl for women, blood pressure ≥130/85 mm Hg, and waist circumference >102 cm for males or >88 cm for females.

Exclusion criteria included pregnant women, individuals below 18 or above 75 years of age, severely ill patients, those taking medications known to influence thyroid function (such as estrogen, corticosteroids, iodine-containing drugs, and amiodarone), and patients with a history of gastrointestinal bypass procedures, chronic liver diseases, hepatocellular carcinoma, parenteral nutrition, steatogenic drugs, HIV infection, or those undergoing weight loss therapies.

Following ethical approval from the Institutional Ethics Committee, trained interviewers administered structured questionnaires to collect demographic and clinical information. A complete physical examination was performed, and anthropometric measurements including height, weight, and waist circumference were recorded. Height and weight were used to calculate body mass index (BMI) using the Quetelet index (kg/m²). Waist circumference was measured during mid-respiration at the midpoint between the 10th rib and the iliac crest, on bare skin.

Blood pressure was measured twice over the right arm using a mercury sphygmomanometer in a seated position with a three-minute interval between readings. The average of the two measurements was recorded as the final blood pressure. Venous blood samples were drawn after a 12-hour overnight fast. The samples were centrifuged at 3000 rpm for 10 minutes, and the serum was separated and stored at -8°C until biochemical analysis.

Lipid profiles, including total cholesterol, triglycerides, HDL-C, and LDL-C levels, were analyzed using enzymatic methods on an automated biochemical analyzer. The Friedewald formula was used to calculate LDL-C. Fasting blood glucose levels were measured by the glucose oxidase-peroxidase (GOD-POD) method.

Patients diagnosed with metabolic syndrome were further evaluated for thyroid dysfunction. Serum levels of free triiodothyronine (FT3), free thyroxine (FT4), and thyroid-stimulating hormone (TSH) were estimated using MAGLUMI chemiluminescence immunoassay kits. The reference ranges were as follows: TSH: 0.27–4.2 μIU/ml, FT3: 0.86–2.02 ng/ml, FT4: 5.13–14.06 μg/dl. Based on these levels, patients were categorized as follows: subclinical hypothyroidism (TSH >4.2 μIU/ml with normal FT3 and FT4), overt hypothyroidism (TSH >4.2 μIU/ml with low FT3 and FT4), subclinical hyperthyroidism (TSH <0.27 μIU/ml with normal FT3 and FT4), overt hyperthyroidism (TSH <0.27 μIU/ml with elevated FT3 and FT4), and euthyroid (normal TSH, FT3, and FT4).

All data were analyzed using SPSS software version 26. Quantitative variables were expressed as mean ± standard deviation (SD), and categorical data were presented as percentages. Comparisons between groups were performed using the t-test for normally distributed quantitative data, while the Mann-Whitney U test was applied for non-parametric data. Categorical variables were analyzed using the chi-square test. Pearson’s correlation coefficient was used to assess the relationship between continuous variables. A p-value less than 0.05 was considered statistically significant.

Table 1 presents the classification of patients according to their thyroid function status. Among the 200 individuals with metabolic syndrome, 131 (65.5%) were euthyroid, while the remaining 69 patients exhibited thyroid dysfunction in varying forms. Subclinical hypothyroidism was identified in 23.5%, overt hypothyroidism in 8.5%, and subclinical hyperthyroidism in 1.5%, emphasizing a considerable proportion of thyroid irregularities in this cohort.

Table 2 illustrates the thyroid status distribution across genders. Among males, the majority were euthyroid, with fewer cases of subclinical or overt hypothyroidism. In contrast, females demonstrated a higher prevalence of thyroid dysfunction, particularly subclinical hypothyroidism, suggesting a gender predisposition toward altered thyroid physiology in metabolic syndrome.

Table 3 outlines the correlation between blood pressure status and thyroid dysfunction. Most patients with hypertension were found to have coexisting thyroid abnormalities, while those with normal blood pressure were predominantly euthyroid. This pattern indicates a potential association between raised blood pressure and thyroid imbalances among metabolic syndrome cases.

Table 4 details the average serum TSH values observed in different thyroid states. The mean TSH concentration was lowest in subclinical hyperthyroidism and progressively increased in subclinical and overt hypothyroidism, aligning with the severity of thyroid dysfunction. Euthyroid individuals maintained TSH within the normal range.

Table 5 highlights the comparison of metabolic syndrome components in patients with and without thyroid dysfunction. While abdominal obesity was universally prevalent, significant differences were detected in triglyceride levels, HDL cholesterol, blood pressure, and fasting glucose between the two groups. These findings underline the metabolic impact of thyroid disturbances in affected patients.

Table 1: Distribution of Patients According to Thyroid Status

Table 2: Gender-Wise Distribution of Thyroid Dysfunction

SCH: Subclinical Hypothyroidism, OH: Overt Hypothyroidism, SCHyper: Subclinical Hyperthyroidism

Table 3: Distribution of Thyroid Dysfunction with Blood Pressure

Table 4: Mean TSH Levels in Different Thyroid Status Groups

Table 5: Association Between Thyroid Dysfunction and Metabolic Syndrome Components

The findings of this study demonstrate a strong relationship between thyroid dysfunction and metabolic syndrome (MetS), with a significant proportion of participants exhibiting subclinical or overt hypothyroidism. Among the components of MetS, the most prominent associations were seen with dyslipidemia, hypertension, and elevated fasting glucose. These results add to the growing body of evidence indicating a bidirectional link between thyroid hormone imbalance and metabolic disruptions.

Our observations resonate with the study by Kumar et al., which found that low-normal free T4 levels were significantly associated with increased waist circumference, insulin resistance, and dyslipidemia in euthyroid individuals with MetS. The study emphasized that even subtle thyroid hormone alterations within the normal reference range could influence metabolic parameters adversely [11]. Similarly, Sengupta et al. reported that nearly 30% of patients with MetS had subclinical hypothyroidism, with a notable correlation to low HDL and high triglyceride levels [12].

Verma et al. highlighted the cardiovascular implications of thyroid dysfunction in metabolic syndrome. They found that slight elevations in TSH levels—even within the normal range—were linked to increased systolic blood pressure, hyperglycemia, and unfavorable lipid profiles, reinforcing the role of thyroid hormones in vascular health and metabolic control [13]. This aligns well with our study, where most patients with thyroid dysfunction exhibited multiple altered MetS components.

Kapil et al. also underscored a clear association between hypothyroidism and MetS, particularly among Indian patients, suggesting that the presence of thyroid dysfunction exacerbates the metabolic burden and increases cardiovascular risk. Their work supported the recommendation that routine thyroid screening should be part of MetS evaluation protocols [14]. Furthermore, Roy et al. emphasized the higher prevalence of thyroid dysfunction among MetS patients compared to the general population and advocated for integrating endocrine assessment in metabolic management strategies [15].

Taken together, these studies reinforce the concept that thyroid dysfunction, particularly in its subclinical forms, should not be underestimated in individuals with metabolic syndrome. Early identification and correction of thyroid imbalances could play a key role in improving metabolic outcomes and reducing long-term cardiovascular risks.

This study highlights a substantial prevalence of thyroid dysfunction in patients with metabolic syndrome, with subclinical hypothyroidism being the most common abnormality. Thyroid dysfunction was notably associated with deranged lipid profiles, elevated blood pressure, and impaired fasting glucose levels. The integration of thyroid screening into metabolic syndrome evaluations could enable early intervention, ultimately helping to mitigate the compounded risk of cardiovascular morbidity. Further large-scale studies are warranted to evaluate the impact of treating subclinical thyroid disorders on metabolic control and clinical outcomes.

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