Type 2 diabetes mellitus (T2DM) has become one of the defining non-communicable disease challenges of the twenty-first century. The International Diabetes Federation estimated that approximately 589 million adults aged 20–79 years were living with diabetes in 2024, a global prevalence of about 11.1%, projected to rise to 853 million by 2050 [1]. India bears a disproportionate share of this burden: the ICMR-INDIAB study, the largest nationally representative survey of metabolic non-communicable diseases in the country, reported a weighted diabetes prevalence of 11.4% and prediabetes prevalence of 15.3% among adults, corresponding to an estimated 101 million people with diabetes and 136 million with prediabetes, alongside strikingly high prevalences of abdominal obesity and dyslipidaemia [2].

Insulin resistance — the failure of peripheral tissues to respond normally to circulating insulin — is typically the earliest detectable metabolic lesion, frequently preceding overt hyperglycaemia by many years [3]. Reaven's 1988 Banting Lecture crystallized the observation that resistance to insulin-mediated glucose disposal underlies a cluster of abnormalities including hyperinsulinaemia, dyslipidaemia, and hypertension, a constellation he termed Syndrome X and which is now widely known as the metabolic syndrome [3]. Indian and other South Asian populations display a distinctive metabolic phenotype: greater insulin resistance, higher percentage body fat, and more visceral adiposity at any given BMI than European populations, together with lower lean mass — the "thin-fat" phenotype first described in Indian neonates [4] and subsequently confirmed in adult cohorts, where Asian Indian men showed greater insulin resistance relative to body size than matched Western populations [5].

A substantial body of evidence has established that obesity is accompanied by a state of chronic, low-grade systemic inflammation that directly contributes to insulin resistance. The seminal demonstration that tumour necrosis factor-alpha (TNF-α) is over-expressed in the adipose tissue of obese animals and contributes directly to insulin resistance established adipose tissue as an immunometabolic organ [6], a finding subsequently confirmed in human obesity [7]. Obesity is further characterized by macrophage infiltration of adipose tissue [8,9] and by dysregulation of adipocyte-derived hormones: reduced levels of the insulin-sensitising adipokine adiponectin [10], relative leptin resistance [11], and elevated resistin [12]. Prospective cohort data have shown that elevated C-reactive protein and interleukin-6 (IL-6) independently predict the future development of both T2DM and cardiovascular disease [13,14], underscoring the clinical, and not merely mechanistic, relevance of the inflammatory profile of insulin resistance. In parallel, the atherogenic dyslipidaemia of insulin resistance — elevated triglycerides and VLDL-cholesterol with reduced HDL-cholesterol — arises from loss of insulin-mediated suppression of hepatic VLDL production and is now recognized as a hallmark of the dysmetabolic state [15].

Despite this extensive international literature, comparatively few studies have characterized the combined clinical, glycemic, lipid, and inflammatory phenotype of insulin resistance in Indian hospital-based populations, where the disease burden is among the highest in the world and where the metabolic phenotype differs materially from Western cohorts. A tertiary care teaching centre, serving a clinically diverse population across the full spectrum from normoglycaemia to established diabetes, offers a valuable setting in which to characterize these correlates and to anchor them to simple, clinically accessible indices such as HOMA-IR. This study was therefore undertaken to compare anthropometric, glycemic, lipid, and inflammatory/adipokine profiles between insulin-resistant subjects and matched controls in this setting, and to identify the clinical and biochemical parameters most strongly associated with insulin resistance severity.

Study design and ethics: This hospital-based, comparative case-control study was conducted in the Department of Physiology at a tertiary care teaching hospital, in collaboration with the outpatient/diabetes clinic, over a proposed duration of two years. The protocol was approved by the Institutional Ethics Committee and conducted in accordance with the Declaration of Helsinki and the ICMR National Ethical Guidelines for Biomedical and Health Research Involving Human Participants (2017). Written informed consent was obtained from all participants, with assured confidentiality and voluntary withdrawal at any stage. Study population: Participants were recruited from the outpatient department, health check-up clinics, and community screening camps. Cases comprised individuals aged 18–60 years with insulin resistance, defined as HOMA-IR ≥2.5, and/or clinical overweight/obesity, metabolic syndrome, or newly diagnosed drug-naïve T2DM. Controls were age- and sex-matched healthy individuals with normal fasting glucose and HOMA-IR and no personal or family history of diabetes or metabolic disease. Exclusion criteria included type 1 diabetes or established T2DM on insulin/insulin-sensitizing therapy, pregnancy/lactation, acute or chronic infection, malignancy, autoimmune disease, conditions causing secondary insulin resistance, significant hepatic/renal impairment, use of drugs affecting insulin sensitivity within 3 months, and recent major surgery or hospitalization. Sample size: Sample size was calculated using the formula for comparison of means between two independent groups (n = 2×[(Zα/2+Zβ)²×σ²]/d²), with Zα/2=1.96 (α=0.05) and Zβ=0.84 (80% power), using pooled standard deviation and clinically meaningful difference estimates from published literature, computed in G*Power/nMaster software with 10–15% inflation for attrition. This yielded a minimum of 60 subjects per group. Clinical and anthropometric assessment: Each participant underwent a structured interview and clinical examination recording demographic, medical, family, and medication history. Height, weight, BMI, waist circumference, hip circumference, and waist-hip ratio were measured by standardized technique. Blood pressure was recorded in the seated position after 5 minutes' rest (mean of two readings). Physical activity was assessed using a validated questionnaire (IPAQ) and dietary intake by 24-hour recall/food frequency questionnaire. Sample collection and biochemical investigations: After a 10–12 hour overnight fast, venous blood was drawn under aseptic conditions; for OGTT-based assessments, a further sample was drawn 2 hours after a standard 75 g oral glucose load. Fasting and post-load plasma glucose were measured by the glucose oxidase-peroxidase method; fasting serum insulin by chemiluminescence immunoassay/ELISA; HbA1c by HPLC; and a complete lipid profile (total cholesterol, triglycerides, HDL-C, LDL-C, VLDL-C) by standard enzymatic methods. HOMA-IR, HOMA-β, and QUICKI were calculated using standard formulae. Serum TNF-α, IL-6, hs-CRP, leptin, adiponectin, and resistin were measured by validated sandwich ELISA, performed in duplicate. Statistical analysis: Data were analysed using SPSS v26.0/GraphPad Prism. Normality was assessed by Shapiro-Wilk test; continuous variables were expressed as mean±SD or median (IQR) as appropriate, and compared by independent-samples t-test/Mann-Whitney U test (two groups) or ANOVA/Kruskal-Wallis (more than two groups). Categorical variables were compared by chi-square/Fisher's exact test. Correlations were assessed by Pearson's/Spearman's coefficients. A two-tailed p<0.05 was considered statistically significant.

A total of 120 subjects completed the study: 60 insulin-resistant cases (HOMA-IR ≥2.5) and 60 age- and sex-matched controls.

Table 1. Demographic and Anthropometric Characteristics

Groups were well matched for age and sex, confirming valid comparability. Insulin-resistant subjects had markedly higher BMI, waist circumference (~18 cm greater), waist-hip ratio, and blood pressure, reproducing the classical clustering of central obesity and hypertension that defines the metabolic syndrome and confirming the case group represents a biologically coherent, centrally obese phenotype.

Table 2. Glycemic Parameters and Indices of Insulin Resistance

Fasting and post-load glucose, HbA1c, and fasting insulin were all significantly higher in cases, producing a ~3.5-fold elevation in HOMA-IR and a corresponding fall in QUICKI. Glucose values remained largely in the prediabetic range (mean HbA1c 6.1%), and the modestly elevated HOMA-β in cases is consistent with compensatory hyperinsulinaemia characteristic of the early, beta-cell-compensated stage of insulin resistance, rather than established diabetes.

Table 3. Serum Lipid Profile

The insulin-resistant group showed a classical atherogenic dyslipidaemia — elevated total cholesterol, triglycerides, LDL-C, and VLDL-C, with reduced HDL-C — consistent with hepatic insulin resistance-driven VLDL overproduction and reciprocal HDL depletion.

Pro-inflammatory cytokines (TNF-α, IL-6), hs-CRP, leptin, and resistin were markedly elevated, while adiponectin was significantly reduced, in insulin-resistant subjects — a profile consistent with obesity-driven, macrophage-mediated adipose tissue inflammation and loss of the protective, insulin-sensitising adipokine adiponectin

Table 4. Serum Inflammatory Markers and Adipokines

Table 5. Selected Correlations with Anthropometric/Inflammatory Parameters

BMI correlated positively with TNF-α and negatively with adiponectin, tracing a direct relationship between adiposity and the inflammatory/adipokine disturbance that characterizes the insulin-resistant phenotype in this cohort.

This case-control study demonstrates that insulin-resistant subjects attending a tertiary care teaching centre exhibit a coherent clinical phenotype of central adiposity, atherogenic dyslipidaemia, and chronic low-grade inflammation with adipokine dysregulation, closely mirroring the pathophysiological model of insulin resistance established in the international literature.

The markedly greater waist circumference and waist-hip ratio observed in cases, more pronounced than the difference in BMI alone, is consistent with long-standing evidence that central, visceral adiposity is more strongly linked to insulin resistance than total body fat, since visceral fat is metabolically more active, more heavily infiltrated by pro-inflammatory macrophages, and delivers free fatty acids preferentially to the liver via the portal circulation [15]. This is particularly relevant in Indian and other South Asian populations, who are recognized to carry greater visceral adiposity and insulin resistance at any given BMI than Western populations — the "thin-fat" phenotype first documented in Indian neonates [4] and subsequently in adult cohorts, where Asian Indian men showed disproportionately greater insulin resistance relative to body size compared with matched Western men [5].

The approximately 3.5-fold elevation in HOMA-IR, together with the modestly elevated HOMA-β observed in cases, is best interpreted as evidence of compensatory hyperinsulinaemia — the physiological attempt of pancreatic beta cells to overcome peripheral insulin resistance and maintain glucose homeostasis, a phase that Reaven's original formulation of Syndrome X, and subsequent work by DeFronzo and Ferrannini, identified as the characteristic early stage preceding beta-cell decompensation and overt T2DM [3]. The finding that mean HbA1c in cases (6.1%) remained largely within the prediabetic range supports the interpretation that this cohort predominantly captures this early, compensated stage.

The atherogenic dyslipidaemia observed — elevated triglycerides and VLDL-cholesterol with reduced HDL-cholesterol — is a well-established biochemical correlate of hepatic insulin resistance. Loss of insulin-mediated suppression of hepatic VLDL-triglyceride production, combined with increased hepatic substrate delivery from an expanded, lipolytically dysregulated visceral fat depot, is now recognized as the central mechanism driving this dyslipidaemic pattern [15]; the reciprocal fall in HDL-cholesterol reflects accelerated catabolism of triglyceride-enriched HDL particles generated by cholesteryl-ester-transfer-protein-mediated lipid exchange with VLDL.

The inflammatory and adipokine findings in this study are consistent with the now well-established concept of obesity-associated insulin resistance as a state of chronic, low-grade inflammation originating in dysfunctional adipose tissue. The seminal observation that adipose TNF-α is over-expressed in obesity and directly contributes to insulin resistance [6,7], together with subsequent demonstration that obese adipose tissue is infiltrated by activated macrophages that are a major source of circulating TNF-α and IL-6 [8,9], provides a coherent explanation for the elevated cytokine and hs-CRP levels observed here. The concurrent adipokine changes — elevated leptin (suggestive of leptin resistance) and resistin [12], with reduced adiponectin [10] — reinforce this picture; adiponectin normally exerts insulin-sensitising, anti-inflammatory actions, and its loss removes a physiological brake on both metabolic and inflammatory dysregulation. Prospective data confirming that elevated CRP and IL-6 independently predict future T2DM and cardiovascular disease [13,14] underscore that these findings are not merely descriptive but carry direct clinical prognostic relevance for this cohort.

Limitations: The cross-sectional case-control design precludes causal inference; single-centre recruitment may limit generalizability; and dietary, physical activity, and genetic contributors to the observed associations were not fully captured.

Insulin-resistant subjects attending this tertiary care teaching centre display a clinically and biochemically coherent phenotype of central adiposity, compensatory hyperinsulinaemia, atherogenic dyslipidaemia, and chronic low-grade inflammation with adipokine dysregulation. These findings reproduce, in an Indian hospital-based population, the pathophysiological model of obesity-driven inflammatory insulin resistance established internationally, and provide the clinical and biochemical foundation against which the molecular signal-transduction abnormalities of insulin resistance — examined in a companion analysis of this cohort — can be meaningfully interpreted.

1. International Diabetes Federation. IDF Diabetes Atlas. 11th ed. Brussels: International Diabetes Federation; 2025.
2. Anjana RM, Unnikrishnan R, Deepa M, Pradeepa R, Tandon N, Das AK, et al. Metabolic non-communicable disease health report of India: the ICMR-INDIAB national cross-sectional study (ICMR-INDIAB-17). Lancet Diabetes Endocrinol. 2023;11(7):474-489.
3. Reaven GM. Banting Lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988;37(12):1595-1607.
4. Yajnik CS, Fall CHD, Coyaji KJ, Hirve SS, Rao S, Barker DJP, et al. Neonatal anthropometry: the thin-fat Indian baby. The Pune Maternal Nutrition Study. Int J Obes. 2003;27(2):173-180.
5. Chandalia M, Abate N, Garg A, Stray-Gundersen J, Grundy SM. Relationship between generalized and upper body obesity to insulin resistance in Asian Indian men. J Clin Endocrinol Metab. 1999;84(7):2329-2335.
6. Hotamisligil GS, Shargill NS, Spiegelman BM. Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science. 1993;259(5091):87-91.
7. Hotamisligil GS, Arner P, Caro JF, Atkinson RL, Spiegelman BM. Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest. 1995;95(5):2409-2415.
8. Xu H, Barnes GT, Yang Q, Tan G, Yang D, Chou CJ, et al. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J Clin Invest. 2003;112(12):1821-1830.
9. Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW Jr. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest. 2003;112(12):1796-1808.
10. Yamauchi T, Kamon J, Waki H, Terauchi Y, Kubota N, Hara K, et al. The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med. 2001;7(8):941-946.
11. Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR, et al. Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med. 1996;334(5):292-295.
12. Steppan CM, Bailey ST, Bhat S, Brown EJ, Banerjee RR, Wright CM, et al. The hormone resistin links obesity to diabetes. Nature. 2001;409(6818):307-312.
13. Pradhan AD, Manson JE, Rifai N, Buring JE, Ridker PM. C-reactive protein, interleukin 6, and risk of developing type 2 diabetes mellitus. JAMA. 2001;286(3):327-334.
14. Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000;342(12):836-843.
15. Adiels M, Olofsson SO, Taskinen MR, Borén J. Overproduction of very low-density lipoproteins is the hallmark of the dyslipidemia in the metabolic syndrome. Arterioscler Thromb Vasc Biol. 2008;28(7):1225-1236.
16. DeFronzo RA, Ferrannini E. Insulin resistance: a multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care. 1991;14(3):173-194.
17. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412-419.

Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, et al. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab. 2000;85(7):2402-2410.