European Journal of Cardiovascular Medicine

The interplay between thyroid dysfunction and lipometabolic health continues to attract significant scientific attention [1,2]. Thyroid hormones play a crucial role in regulating basal metabolic rate, lipid turnover, vascular reactivity, and cardiac output, making even subtle hormonal disturbances potentially relevant to lipometabolic physiology. Consequently, conditions such as subclinical hypothyroidism (ScH)—characterized by elevated thyroid-stimulating hormone (TSH) with preserved thyroxine (T4) levels—are increasingly being evaluated for their long-term metabolic and vascular implications.[3]

Globally, lipometabolic abnormalities including dyslipedmia and insulin resistance remain one of the leading contributors to morbidity and mortality [4], underscoring the need to understand all possible contributing factors. While overt hypothyroidism is a well-established risk factor for dyslipidemia and hypertension, the evidence for ScH remains less consistent. Several studies have proposed that even mild thyroid dysfunction may impair lipid handling, reduce endothelial relaxation, and increase systemic vascular resistance. Others have failed to demonstrate such associations, leaving the clinical significance of ScH uncertain.[5-10]

In India, where thyroid disorders are relatively prevalent, little work has been done on the topic. [11] Data specific to regional populations—like those from Kashmir—are limited. Socioeconomic factors, dietary habits, altitude, and ethnicity may influence metabolic patterns, making regional research particularly valuable. The present study therefore aimed to assess the association of ScH with important lipometabolic risk markers in a Kashmiri population.

This study was conducted on fifty individuals diagnosed with ScH and fifty age- and gender-matched euthyroid controls. Participants were recruited from the Medical OPD of Government Medical College, Srinagar, and assessments were conducted in the Departments of Biochemistry and General Medicine. Exclusion criteria were selected to minimize confounders and included chronic systemic disease, pregnancy, and the use of medications that might alter thyroid function or metabolic profile. Blood pressure measurements were carried out under controlled conditions to ensure accuracy. After a minimum rest period of ten minutes, systolic and diastolic values were recorded using a standardized sphygmomanometer. Anthropometric parameters—including height, weight, and waist circumference—were documented following universally accepted guidelines. Waist circumference was measured at the upper border of the iliac crest as recommended by the NIH.[12] Diagnosis of ScH relied on NHANES-based criteria, requiring normal circulating T4 levels (0.9–1.9 pg/dL) alongside an elevated TSH (≥4.12 mIU/L).[13] Clinical evaluation A structured, pretested questionnaire was administered to obtain demographic characteristics, past medical history, personal habits, and anthropometric details. This facilitated the identification of potential confounders that could influence lipometabolic risk markers, such as smoking status, diet, or family history. Laboratory analysis Fasting serum samples were collected in the early morning hours to minimize diurnal variation in thyroid and lipid parameters. Standard venipuncture techniques were followed using heparinized tubes, and samples were promptly processed and stored under recommended laboratory conditions to ensure biochemical stability and reliability. Thyroid function tests (TSH, T3, T4) were performed using a sensitive chemiluminescence immunoassay on the Abbott i1000 analyzer. This assay offers high specificity and reproducibility, particularly important for detecting subtle hormonal changes characteristic of ScH. Lipid parameters and fasting glucose levels were assessed via enzymatic methods on the Abbott c4000 analyzer, known for its analytical precision and reliability. Data Analysis Data analysis was performed using Microsoft Excel and IBM SPSS. Descriptive statistics summarized baseline characteristics, while Pearson’s correlation coefficient explored relationships between thyroid parameters and lipometabolic risk factors. Independent t-tests and chi-square tests evaluated group differences, with a p-value <0.05 considered statistically significant. Ethical Considerations The study was approved by the Institutional Ethics Committee (IEC), and informed consent was obtained from all participants. Confidentiality and ethical standards were strictly maintained throughout the study.

Baseline characteristics were comparable between individuals with subclinical hypothyroidism (ScH) and euthyroid controls, minimizing the influence of demographic variability on study outcomes (Figure 1). The mean BMI of the ScH group was 23.72 ± 5.10 kg/m², while the euthyroid group showed a BMI of 25.57 ± 6.35 kg/m²; the difference was not statistically significant (p > 0.05).

Anthropometric, clinical, and biochemical details are summarized in Table 1. Blood pressure parameters did not differ significantly between groups. The ScH group demonstrated a mean systolic blood pressure of 118 ± 12.94 mmHg and a diastolic blood pressure of 73.4 ± 7.45 mmHg, values comparable to those of the euthyroid controls (p > 0.05).

Biochemical analysis also revealed no statistically meaningful differences. In the ScH cohort, fasting blood sugar was 99.02 ± 28.90 mg/dL, triglycerides 166.32 ± 70.50 mg/dL, HDL 43.82 ± 11.44 mg/dL, and LDL 111.58 ± 95.14 mg/dL. Corresponding values among controls—99.3 ± 28.90 mg/dL, 151.06 ± 69.82 mg/dL, 43.28 ± 11.73 mg/dL, and 97.3 ± 34.18 mg/dL, respectively—were not significantly different (p > 0.05). Notably high standard deviations in triglyceride and LDL levels suggested considerable inter-individual variability in lipid indices across both groups.

Tables and figures

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Fig I: Baseline characteristics of patients

Table I : Lipometabolic, clinical and anthropometric parameters of study subjects

The present study found no significant differences across anthropometric, hemodynamic, or lipometabolic parameters between individuals with subclinical hypothyroidism (ScH) and euthyroid controls. These findings suggest that, within this Kashmiri cohort, mild thyroid dysfunction may not exert measurable short-term metabolic effects. This aligns with previous investigations reporting similar outcomes in populations with modest sample sizes or early-stage thyroid dysfunction [5].

Although thyroid hormones play a key role in regulating vascular tone, lipid turnover, and adrenergic responsiveness, the subtle hormonal changes characteristic of ScH may not be sufficient to cause detectable disturbances in blood pressure. The lack of significant differences in systolic and diastolic blood pressures in our study mirrors results from other clinical studies [5]. However, meta-analytic evidence indicates that small but meaningful increases in blood pressure may emerge in larger samples or over longer durations of thyroid dysfunction, suggesting that early alterations may fall below the threshold of detection in smaller cross-sectional analyses [7].

Similarly, the absence of significant lipid abnormalities in this study reflects the heterogeneity observed across the literature. Several studies have demonstrated increased LDL or triglycerides, or reduced HDL levels in ScH, supporting the hypothesis that even mild thyroid dysfunction may adversely influence lipid metabolism [14–16]. Conversely, multiple studies have reported no significant differences in lipid parameters between ScH and euthyroid groups, emphasizing the variability in metabolic expression of the condition [17–19]. Differences in dietary habits, iodine sufficiency, genetic background, assay sensitivity, and definitions of ScH may contribute to these inconsistent findings.

The wide standard deviations in triglyceride and LDL values observed in this cohort further highlight substantial inter-individual variability, which may obscure subtle group-level metabolic effects. Overall, the evidence suggests that the metabolic impact of ScH may be context-dependent, influenced by population characteristics, disease duration, and environmental or lifestyle factors. Larger, longitudinal studies are needed to clarify whether the apparent metabolic neutrality in early ScH persists over time or whether progression to overt hypothyroidism leads to measurable lipometabolic alterations.

Overall, this study indicates that subclinical hypothyroidism may not significantly elevate lipometabolic risk markers such as BMI, LDL,TG, cholesterol, FBG, or blood pressure in the Kashmiri population studied. However, given the heterogeneity of findings across the literature and the plausible biological mechanisms linking thyroid dysfunction to lipometabolic health, regular follow-up remains advisable. Larger longitudinal studies would help clarify whether progression from ScH to overt hypothyroidism is associated with worsening lipometabolic parameters.

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