Diabetes mellitus (DM) and thyroid dysfunction are two of the most common endocrine illnesses seen in clinical practice, and their interactions are well-established (Perros P et al. ^[1]). Both disorders significantly affect physiological and metabolic functions, and they frequently interact, making patient care even more challenging. Thyroid hormones control basal metabolic rate and affect the metabolism of carbohydrates, whereas diabetes mellitus is typified by persistent hyperglycemia brought on by insulin resistance or insufficiency (Brenta G et al. and Wang C et al. ^[2,3].

Studies have revealed that thyroid abnormalities are more prevalent in diabetic patients than in the general population, and the link between thyroid dysfunction and diabetes was first identified decades ago. Hage M. and others ^[4]. People with type 2 diabetes mellitus (T2DM) have a higher prevalence of overt and subclinical hypothyroidism, according to the Framingham research and several other epidemiological surveys. MPJ Vanderpump and associates ^[5].

This connection is explained by a number of ways. The characteristic of type 2 diabetes, insulin resistance, may affect thyroid function by changing the metabolism or output of thyroid hormones. ^[6] Duntas LH et al. On the other hand, in diabetic individuals, thyroid dysfunction can make glycaemic control worse. While hyperthyroidism may affect glycaemic control and enhance insulin resistance, hypothyroidism may decrease insulin clearance and cause hypoglycemia. Udiong CEJ et al. and Pearce EN et al. ^[7,8].

Depending on environmental, genetic, and regional variables, the frequency of thyroid abnormalities among diabetes patients varies from 10% to over 30%, according to a number of studies carried out throughout India (Menon UV et al. and Gopinath B et al.^[9,10]). Notably, Unnikrishnan AG et al.^[11] discovered that women with type 2 diabetes had a notably high prevalence of subclinical hypothyroidism in a large population-based investigation conducted in Kerala. Even though this comorbidity is becoming more well recognised, routine thyroid monitoring is frequently disregarded in diabetes treatment, especially in areas with low resources.

The lack of information on thyroid dysfunction in diabetics in rural Tamil Nadu is the driving force for this investigation. Early detection of concomitant endocrine diseases is essential since the rural population is frequently under-represented in research and has limited access to diagnostic facilities. By assessing the prevalence of thyroid dysfunction in diabetes patients and contrasting it with non-diabetic controls in a sub-urban population from Chennai, Tamilnadu, our study seeks to close this information gap.

The negative feedback loop that governs the hypothalamic-pituitary-thyroid (HPT) axis is strict. Because TSH is extremely sensitive to changes in the levels of free thyroxine (T4) and triiodothyronine (T3) in the blood, it has become the gold standard for diagnosing thyroid diseases (Spencer CA et al. ^[12]. The immunofluorescent test technique, which offers dependable sensitivity and specificity, was used in this study to quantify TSH.

In clinical practice, subclinical hypothyroidism is defined by increased TSH with normal T4 levels, but overt hypothyroidism is diagnosed when TSH levels are raised and T4 levels are low. On the other hand, decreased TSH levels, which are frequently accompanied by increased T3 and T4 levels, are indicative of hyperthyroidism (Surks MI et al. ^[13]). These definitions serve as the foundation for interpretation in this study and help classify thyroid dysfunction.

Periodic thyroid function testing is advised for diabetic patients, particularly those over 50 and those with poorly managed diabetes, according to several guidelines, including those from the American Thyroid Association and American Diabetes Association ^[14]. However, there is still uneven application of these suggestions.

The purpose of this study is to evaluate the prevalence of thyroid diseases in the sub-urban population Chennai, Tamilnadu with that of matched non-diabetic controls among known diabetics receiving regular treatment. Guidelines for routine screening and improved care can be developed with the use of knowledge about the pattern of thyroid dysfunction in this population.

Study Design and Population:

This cross-sectional study was conducted in the sub-urban population Chennai, Tamilnadu. A total of 296 subjects were enrolled, comprising 133 known diabetic patients (132 with type 2 diabetes mellitus [T2DM] and 1 with type 1 diabetes mellitus [T1DM]) and 163 age- and sex-matched non-diabetic controls. All diabetic participants were on regular antidiabetic treatment, including monotherapy with oral hypoglycemic agents (OHAs) or combination therapy with OHAs and insulin.

 Inclusion Criteria:

• Adults of either sex, aged 18 years and above.
• Known diabetic patients on regular treatment.
• Age- and sex-matched non-diabetic individuals.

 Exclusion Criteria:

• Pregnant women.
• Individuals taking steroids or dopamine.
• Subjects with a history suggestive of pituitary disorders.

 Data Collection and Laboratory Analysis:

All participants underwent a comprehensive clinical evaluation. Blood samples were collected to measure serum thyroid-stimulating hormone (TSH) levels using the immunofluorescent assay (IFA) method (Biomérieux – Mini Vidas). The reference ranges for TSH were as follows:Lippincott Journals+6IJ Medicine+6PubMed+6

• Hypothyroidism: TSH > 4.5 μIU/mL
• Hyperthyroidism: TSH < 0.25 μIU/mL
• Euthyroid: TSH between 0.25–4.5 μIU/mLSRS Journal

The IFA method is a highly sensitive biochemical assay that accurately reflects alterations in free T3 and free T4 levels. Subjects with abnormal TSH values underwent further evaluation to confirm thyroid dysfunction.

 Statistical Analysis:

Data were analyzed using appropriate statistical methods. A binomial test was employed to assess the significance of differences in the prevalence of thyroid dysfunction between diabetic and non-diabetic groups. A p-value of less than 0.05 was considered statistically significant.

Table 1: Prevalence of Thyroid Dysfunction in Diabetic and Non-Diabetic Subjects

The thyroid status distribution of individuals with and without diabetes is shown in this table. 85.71% (114) of the 133 individuals with diabetes were euthyroid, 10.53% (14) were hypothyroid, and 3.76% (5) were hyperthyroid. In comparison, 32.37% (5) of the non-diabetics (n=163) had hyperthyroidism, 24.54% (40) had hypothyroidism, and 72.39% (118) were euthyroid. Interestingly, the non-diabetic group had a higher prevalence of hypothyroidism than the diabetic group.

Figure 1

Table 2: Gender-wise Distribution of Thyroid Dysfunction

The distribution of thyroid dysfunction by gender in both research groups is seen in this table. Thyroid dysfunction was seen in 8.27% (11) of female diabetics and 6.02% (8) of male diabetics. Thyroid dysfunction was discovered in 12.27% (20) of the men and 15.34% (25) of the females in the non-diabetic group. In both groups, thyroid dysfunction was often more prevalent in females.

Figure 2

Table 3: Age-wise Distribution of Thyroid Dysfunction

The prevalence of thyroid dysfunction rose with age in both groups, according to the age-wise distribution. The age range of 46–60 years old had the highest prevalence of diabetes (6.02%), followed by those over 60 (3.01%). Likewise, among non-diabetics, thyroid dysfunction was most common in those aged 46–60 (12.27%) and older (>60) (12.13%). These results imply that thyroid dysfunction increases with age in both diabetic and non-diabetic individuals.

Figure 3

Table 4: Statistical Analysis of Thyroid Dysfunction Prevalence

The statistical comparison of thyroid dysfunction prevalence across groups with and without diabetes is shown in this table. The difference was statistically significant, as indicated by the p-value of less than 0.05. It was discovered that the non-diabetic group had a much greater rate of thyroid dysfunction, especially hypothyroidism.

Thyroid dysfunction prevalence among diabetics and non-diabetics in sub-urban population Chennai, Tamilnadu was the goal of the current study. Our results showed that the non-diabetic group had a greater prevalence of thyroid diseases (27.6%) than the diabetic group (14.29%), which is in contrast to numerous studies that indicate a higher incidence among diabetics.

Thyroid dysfunction and diabetes mellitus have been shown to be significantly correlated in prior research. According to Menon UV et al. ^[14], a research carried out in rural South India revealed that 20.1% of diabetes individuals had thyroid impairment, with subclinical hypothyroidism being the most prevalent kind.

According to Singh G et al. ^[15], a research conducted in North India revealed that 28% of patients had type 2 diabetes. The results of our investigation, however, diverge, suggesting that possible causes of this disparity should be investigated.

Regular medical monitoring and treatment adherence among diabetes patients may contribute to the early discovery and management of thyroid abnormalities, which might explain the decreased prevalence of thyroid dysfunction among diabetics in our research. On the other hand, those without diabetes could not have regular checkups, which might lead to thyroid problems being undetected.

According to a gender-wise study, females in both groups had a greater prevalence of thyroid dysfunction, which is consistent with previous research showing that females are more susceptible to thyroid diseases. JG Hollowell and associates ^[16]. In line with earlier research emphasising age as a risk factor, the age-wise distribution revealed an increasing tendency of thyroid dysfunction with advancing age. Vanderpump MP et al.^[5]

The necessity of frequent thyroid screening is highlighted by the considerable difference in the incidence of hypothyroidism between diabetes and non-diabetic individuals (p<0.05), particularly in communities with limited access to healthcare services. To avoid consequences and enhance quality of life, thyroid dysfunction must be identified and treated early.
Notwithstanding the insightful findings, our study has certain drawbacks. The capacity to prove causation is limited by the cross-sectional design. Furthermore, even when the sample size is sufficient, it could not be representative of the general population. Larger sample numbers and more longitudinal research are necessary to confirm our findings and investigate the underlying causes.

Our study concludes that in the sub-urban population Chennai, Tamilnadu, thyroid dysfunction is more common in non-diabetic people than in diabetics. In order to enable early diagnosis and treatment, the results highlight the necessity of routine thyroid monitoring in both diabetes and non-diabetic populations. Raising awareness and making thyroid function testing more accessible should be the main goal of public health campaigns, especially in rural regions.

1. Cross-sectional Design: The cross-sectional design of the study limits the capacity to determine causal links between thyroid dysfunction and diabetes. To ascertain the chronological sequence and evolution of thyroid problems in diabetes individuals, longitudinal investigations would be necessary.
2. Single-Center and Rural Population: The results of this study may not be as applicable to larger populations because it was limited to a single sub-urban population Chennai, Tamilnadu. The results could have been impacted by regionally unique environmental, nutritional, and genetic variables.
3. Limited Thyroid Function Assessment: Thyroid function was evaluated only by measuring TSH levels. The failure to assess free T3 and free T4 levels may have resulted in incorrect categorisation, especially in situations of subclinical thyroid disease.
4. Small Sample size: The statistical power for identifying relationships may be impacted by the very small number of people with thyroid disorder, particularly hyperthyroidism, despite the sample's 296 participants.
5. Lack of Data on Autoimmune Markers: tests of thyroid autoantibodies, such as anti-thyroid peroxidase (TPO) or anti-thyroglobulin (Tg) antibodies, were not included in the study. These tests might have shed further light on the cause of hypothyroidism, particularly in connection with autoimmune thyroiditis.
6. Potential Confounding Variables: A number of confounding variables that potentially affect thyroid function were not taken into consideration in this study, including body mass index (BMI), length of diabetes, glycaemic control (HbA1c), usage of certain drugs (such amiodarone or lithium), and family history of thyroid illness.
7. Screening vs. Clinical Diagnosis: Without clinical correlation or confirmatory repeat testing, thyroid dysfunction was diagnosed based only on a single TSH value, potentially overestimating or underestimating the actual prevalence.

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