Diabetes: A comprehensive review of the Indian landscape in contrast with global trends

Table 1 An extensive analysis of diabetes trends worldwide in 2025

Global diabetes epidemiology (2025)
Ref.	International Diabetes Federation[25], 2023; World Health Organization[26], 2025
Aspect	Details
Global prevalence	Approximately 589 million adults (20-79 years) are living with diabetes, representing 11.1% of the global adult population; projected to rise to 853 million by 2050
Undiagnosed cases	An estimated 252 million adults are unaware they have diabetes, highlighting a substantial gap in diagnosis and awareness
Type distribution	Type 2 diabetes accounts for over 90% of all diabetes cases worldwide
Regional burden	Low- and middle-income countries (LMICs) bear the majority of the burden, with over 75% of people with diabetes residing in these regions
Mortality	Diabetes is responsible for over 3.4 million deaths annually, equating to one death every 9 seconds
Economic impact	Global health expenditure on diabetes has reached USD 1 trillion, marking a 338% increase over the last 17 years
Risk factors	Key risk factors include obesity, sedentary lifestyle, unhealthy diet, smoking, alcohol consumption, hypertension, dyslipidemia, age, genetic predisposition, and family history
COVID-19 impact	The COVID-19 pandemic has exacerbated diabetes risk factors due to increased sedentary behavior and disrupted healthcare services, leading to higher morbidity and mortality among diabetic patients
Prevention strategies	Primary prevention: Lifestyle interventions, public health education, and community-level initiatives; secondary prevention: Early diagnosis through screening, especially in high-risk populations; tertiary prevention: Comprehensive disease management to prevent complications

LMICs: Low- and middle-income countries; USD: United States Dollar; COVID-19: Coronavirus disease 2019.

Table 2 Classification of diabetes, highlighted by the American diabetes association

Classification of diabetes
Ref.		Joseph et al[10], 2022; International Diabetes Federation[30], 2025
Diabetes type	Etiology/pathophysiology	Clinical and diagnostic features
Type 1 diabetes mellitus	An autoimmune-mediated destruction of pancreatic β-cells, often involving islet cell autoantibodies (e.g., GAD65, IA-2); this leads to absolute insulin deficiency; affects both children and adults, including latent autoimmune diabetes in adults (LADA)	Acute onset with symptoms like polyuria, polydipsia, weight loss, and fatigue; ketoacidosis is common at presentation; diagnosed by low C-peptide levels, presence of autoantibodies, and fasting hyperglycemia
Type 2 diabetes mellitus	Characterized by insulin resistance and a progressive decline in β-cell function; influenced by obesity, sedentary lifestyle, age, and genetic predisposition; often preceded by prediabetes (impaired glucose tolerance or fasting glucose)	Insidious onset, often asymptomatic for years; commonly diagnosed via routine screening; associated with metabolic syndrome; HbA1c ≥ 6.5%, fasting glucose ≥ 126 mg/dL, or 2-hour OGTT ≥ 200 mg/dL
Gestational diabetes mellitus (GDM)	Glucose intolerance is first recognized during pregnancy, typically in the 2nd or 3rd trimester; caused by hormonal changes leading to insulin resistance (e.g., placental lactogen, estrogen, cortisol)	Screened between 24-28 weeks of gestation using OGTT; usually asymptomatic but can lead to macrosomia, preeclampsia, and neonatal hypoglycemia; increases lifetime risk of T2DM

GAD65: Glutamic acid decarboxylase 65; IA-2: Protein phosphatase-like islet antigen 2; LADA: Latent autoimmune diabetes in adults; HbA1c: Glycated hemoglobin; OGTT: Oral glucose tolerance tests; GDM: Gestational diabetes mellitus; T2DM: Type 2 diabetes mellitus.

Table 3 Genes associated with type 1 diabetes, type 2 diabetes, and gestational diabetes

Genes associated with type 1 diabetes
Ref.	Ke et al[39], 2022; Nejentsev et al[40], 2009
Gene Symbol	Key function/mechanism	Variant types	Clinical significance	Primary population-specific data
HLA	Antigen presentation; strongest genetic risk factor	HLA Haplotypes	High-risk alleles	European, Scandinavian, Hispanic
INS	Thymic insulin expression; immune tolerance	VNTR	Risk alleles	European, Asian
IL2RA	Altered Treg function and immune tolerance	SNPs	Risk alleles	European, Asian
PTPN22	Reduced inhibitory signaling in lymphocytes	SNPs	Risk alleles	European, Asian
IFIH1	Viral RNA sensor; reduced antiviral response	Rare Variants	Protective alleles	European
BACH2	Affects lymphocyte development; autoimmunity	SNPs	Risk alleles	European
TYK2	Influences beta-cell survival and immune responses	SNPs	Risk alleles	European
CLEC16A	Impaired autophagy affects antigen presentation	SNPs	Risk alleles	European
CD226	T-cell activation	SNPs	Risk alleles	European
CCR5	Chemokine receptor; T-cell migration	Deletion (Δ32)	Protective allele	European
CTLA4	Immune checkpoint regulation	SNPs	Risk alleles	Various populations
STAT4	Signal transduction in inflammatory responses	SNPs	Risk alleles	Various populations
EPO	Linked to T1D complications (nephropathy)	SNPs	Risk alleles	Various populations
NOS3	Associated with vascular complications	SNPs	Risk alleles	Various populations
MIR375	MicroRNA regulating insulin secretion & beta-cell mass	MicroRNA	Regulatory role	Various populations
Genes associated with type 2 diabetes
Ref.	Gloyn et al[41], 2003; Dornbos et al[42], 2022; Kumar et al[43], 2024; Flannick et al[44], 2019; Shi et al[45], 2025; Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, and Novartis Institutes of BioMedical Research et al[46], 2007; Abu Aqel et al[47], 2024; Russ-Silsby et al[48], 2025; Gerber et al[49], 2017; Fuchsberger et al[50], 2016; Hwang et al[51], 2023; Udler et al[52], 2019; Morris et al[53], 2012
TCF7 L2	Wnt signaling regulates insulin secretion	SNPs	Strongest common risk allele	European, Hispanic, Asian
PPARG	Nuclear receptor; influences insulin sensitivity	Missense (Pro12Ala)	Risk and Protective alleles	Predominantly European
SLC30A8	Zinc transporter in insulin granules	Loss-of-function	Protective allele	Multiethnic cohorts
KCNJ11	Potassium channel regulates insulin secretion	Missense (E23K)	Confirmed risk allele	Global distribution
FTO	Regulates appetite and adiposity	Intronic SNPs	Risk allele via obesity	Worldwide (strongest in Europeans)
GCK	Glucose-sensing enzyme; modulates β-cell function	Missense, Nonsense	Risk and rare MODY alleles	European populations
MTNR1B	Melatonin receptor; impairs insulin secretion	SNPs	Risk alleles	European and Asian populations
IRS1	Mediates insulin signaling; insulin resistance	SNPs	Risk allele	European and Asian populations
HHEX	Pancreas development; impaired insulin secretion	SNPs	Risk alleles	Asian and European populations
CDKAL1	β-cell insulin secretion regulator	SNPs	Risk alleles	European populations
KCNQ1	Potassium channel; affects β-cell electrical activity	SNPs	Risk alleles	East Asian populations
WFS1	Linked to beta-cell survival and apoptosis	SNPs	Risk alleles	European populations
ANK1	Linked to insulin secretion defects	SNPs	Risk alleles	European populations
GIPR	Influences insulin release and glucose tolerance	Missense, SNPs	Risk alleles	European populations
PDX1	Influences beta-cell function and development	SNPs	Risk alleles	European populations
Genes associated with gestational diabetes
Ref.	Lu et al[54], 2024; Keels et al[55], 2024; Liang et al[56], 2024; Mittal et al[57], 2025; Fan et al[58], 2021; Sladek et al[59], 2007; Gwenzi and Brenner[60], 2024; Li et al[61], 2020; Goyal et al[62], 2023; Saini[63], 2010; Sayyed Kassem et al[64], 2023
TCF7 L2	Wnt signaling regulates insulin secretion	SNPs	Higher susceptibility to GDM	Chinese Han population
MTNR1B	Melatonin receptor; influences circadian rhythm	SNPs	Elevated fasting glucose; GDM risk	Russian women
GCK	Glucose-sensing enzyme in β-cells	SNPs	Impaired glucose sensing and GDM	Multiple populations
IRS1	Mediates insulin signaling; insulin resistance	SNPs	Increased insulin resistance; GDM	Multiple populations
KCNJ11	Potassium channel; insulin release	SNPs	Altered secretion; GDM risk	Multiple populations
CDKAL1	β-cell insulin secretion regulator	SNPs	Impaired secretion; GDM risk	Women < 30 years
HHEX	Pancreas development regulator	SNPs	Increased GDM risk	Multiple populations
SLC30A8	Zinc transporter in insulin granules	SNPs	Defective insulin storage; GDM	North Indian population
CDKN2A/2B	Regulate β-cell cycle; impair proliferation	SNPs	Increased GDM risk	Multiple populations
KCNQ1	Potassium channel; β-cell function	SNPs	Altered insulin secretion	Multiple populations
HNF1B	Transcription factor for pancreas development	SNPs	Reduced insulin secretion	Multiple populations
ABCC8	Regulates insulin secretion via K⁺ channels	SNPs	Disrupted insulin control; GDM	Multiple populations
KIAA0825	Potential oncogene; linked to high glucose	SNPs	Elevated glucose levels	Chinese Han population
FOXC2	Adipocyte differentiation and insulin sensitivity	SNPs	Protective effect against GDM	Multiple populations
HKDC1	Hexokinase is involved in glucose metabolism	SNPs	Impaired glucose metabolism; GDM risk	Multiple populations
TRA2A, NPM3, PHF5A, PLXNA3	RNA splicing, cell cycle, signaling (biomarkers)	SNPs	Diagnostic utility for GDM	Multiple populations

HLA: Human leukocyte antigen; T1D: Type 1 diabetes; INS: Insulin; VNTR: Variable Number Tandem Repeat; IL: Interleukin; SNPs: Single nucleotide polymorphism; PTPN22: Protein tyrosine phosphatase non-receptor type 22; IFIH1: Interferon induced with helicase C domain 1; BACN2: BTB domain and CNC homolog 2; TYK2: Tyrosine kinase 2; CLEC6A: C-type lectin domain containing 16A; CCR5: C-C motif chemokine receptor 5; HIV: Human immunodeficiency virus; CTLA4: Cytotoxic T-lymphocyte associated protein 4; STAT4: Signal transducer and activator of transcription 4; EPO: Erythropoietin; NOS3: Nitric oxide synthase 3; TCF7 L2: Transcription factor 7 like 2; PPARG: Peroxisome proliferator-activated receptor gamma; SLC30A8: Solute carrier family 30 member 8; KCNJ11: Potassium inwardly rectifying channel subfamily J member 11; FTO: Fat mass and obesity associated gene; GCK: Glucokinase; MTNR1B: Melatonin receptor 1B; IRS1: Insulin receptor substrate 1; HHEX: Hematopoietically expressed homeobox; PDX1: Pancreatic and duodenal homeobox 1; KCNQ1: Potassium voltage-gated channel subfamily Q member 1; CDKAL1: Cyclin dependent kinase 5 regulatory subunit associated protein 1-like 1; WFS1: Wolframin ER transmembrane glycoprotein; ANK1: Ankyrin 1; GIPR: Gastric inhibitory polypeptide receptor; T2D: Type 2 diabetes; MODY: Maturity Onset Diabetes of the Young; CDKN2A/CDKN2B: Cyclin dependent kinase inhibitor 2A/2B; HNF1B: Hepatocyte nuclear factor 1 beta; ABCC8: ATP-binding cassette subfamily C member 8; FOXC2: Forkhead Box C2; TRA2A: Transformer 2 alpha homolog; NPM3: Nucleophosmin/nucleoplasmin 3; PHF5A: PHD-finger domain protein 5 A; PLXNA3: Plexin A3; HKDC1: Hexokinase domain containing 1; GDM: Gestational diabetes.

Table 4 Demonstration of environmental factor interaction with gene causing diabetes

Ref.	Kleinberger et al[71], 2015; Cerf et al[72], 2013; Pervjakova et al[73], 2022; Crudele et al[74], 2023; Guidotti et al[75], 2013; Andersen et al[76], 2012; Landin-Olsson[77], 2002; Garcia-Gutierrez[78], 2024; Schulz et al[79], 2021; Kota et al[80], 2012; Pilla et al[81], 2022
Environmental factor	Type of diabetes affected	Gene(s) involved	Mechanism of interaction
Obesity/high-fat diet	T2D	TCF7 L2, FTO, PPARG	Alters gene expression involved in insulin sensitivity and metabolism through epigenetic changes
Physical inactivity	T2D	PPARG, IRS1	Reduces insulin sensitivity via modulation of glucose metabolism genes
Maternal nutrition	GDM, T2D	IGF2, H19, PDX1	Epigenetic modifications affecting pancreatic beta-cell development and fetal metabolic programming
Endocrine disruptors (e.g., BPA)	T2D	PPARG, GLUT4	Mimics or blocks hormonal action, disrupting insulin signaling and glucose transport
Chronic stress/cortisol	T2D	NR3C1, FKBP5	Alters glucocorticoid receptor expression and function, affecting glucose metabolism
Smoking	T2D, GDM	CYP1A1, GSTM1	Increases oxidative stress and induces insulin resistance
Air pollution (PM2.5, NO2)	T2D	GSTP1, NFE2 L2	Induces oxidative stress and systemic inflammation, impairing insulin signaling
Vitamin D deficiency	T1D, T2D	VDR	Modulates immune response and beta-cell function, increasing susceptibility
Viral infections	T1D	HLA-DR, INS	Triggers autoimmune destruction of pancreatic beta cells in genetically susceptible individuals
Gut microbiome dysbiosis	T1D, T2D, GDM	NOD2, TLR4	Alters immune homeostasis and promotes systemic inflammation, impacting insulin sensitivity
Chemical EXPosure (e.g., pesticides, phthalates)	T2D	PPARG, IRS1	Acts as an endocrine disruptor, interfering with insulin signaling pathways
Sleep/circadian disruption	T2D	CLOCK, BMAL1	Alters circadian regulation of metabolic gene expression, leading to impaired glucose metabolism
Socioeconomic status (SES)	All types	Multiple genes	Influences access to healthcare, nutrition, and stress levels, leading to epigenetic modifications

GDM: Gestational diabetes mellitus; T1D: Type 1 diabetes; T2D: Type 2 diabetes; TCF7 L2: Transcription factor 7 like 2; FTO: Fat mass and obesity associated; PPARG: Peroxisome proliferator activated receptor gamma; IRS1: Insulin receptor substrate 1; IGF2: Insulin like growth factor 2; H19: H19 imprinted maternally expressed transcript; PDX1: Pancreatic and duodenal homeobox 1; GLUT4: Glucose transporter type 4; NR3C1: Nuclear receptor subfamily 3 group C member 1; FKBP5: FKBP prolyl isomerase 5; CYP1A1: Cytochrome P450 family 1 subfamily A member 1; GSTM1: Glutathione S-transferase Mu 1; GSTP1: Glutathione S-transferase Pi 1; NFE2 L2: NFE2 like BZIP transcription factor 2; VDR: Vitamin D receptor; HLA-DR: Major histocompatibility complex, class II, DR beta; INS: Insulin; NOD2: Nucleotide binding oligomerization domain containing 2; TLR4: Toll like receptor 4; CLOCK: Clock circadian regulator; BMAL1: Aryl hydrocarbon receptor nuclear translocator like; SES: Socioeconomic status.

Table 5 The pathophysiological processes and genetic network that underlie type 1 diabetes mellitus, type 2 diabetes mellitus, and gestational diabetes mellitus

Pathophysiology of T1D with genetic network
Ref.	Landin-Olsson[77], 2002; Liu et al[82], 2023; Noble and Valdes[92], 2011; Bacchetta and Roncarolo[93], 2024; James et al[94], 2023; Yang et al[95], 2024; Herold and Krischer JP[96], 2024; Mancuso et al[97], 2023; Wang et al[98], 2024; De Franco[99], 2020; Abdul-Ghani and DeFronzo[100], 2008
Pathophysiological process	Description	Key genes
Autoimmune beta-cell destruction	Insulin insufficiency results from CD4+ and CD8+ T-cell-mediated immune destruction of pancreatic β-cells	HLA-DR, HLA-DQ, INS, PTPN22
Antigen presentation and immune activation	β-cell antigens are presented by MHC class II molecules to autoreactive T-cells, initiating an immune response	HLA-DR3, HLA-DR4, HLA-DQ8
T-cell receptor signaling and immune regulation	Defective regulatory T-cell function and abnormal activation of T-cells contribute to loss of immune tolerance	PTPN22, CTLA4, IL2RA, FOXP3
β-cell stress and apoptosis	Endoplasmic reticulum stress and exposure to proinflammatory cytokines lead to apoptosis of β-cells	INS, EIF2AK3, TXNIP
Cytokine-mediated inflammation	Inflammatory cytokines like IFN-γ, TNF-α, and IL-1β induce β-cell dysfunction and promote cell death	IFIH1, IL2RA, STAT4, IL-10
Genetic susceptibility and environmental triggers interaction	Viral infections and other environmental factors interact with genetic predispositions to initiate autoimmunity	HLA, IFIH1, PTPN22
Defective central and peripheral tolerance	Autoreactive T-cells escape elimination in the thymus or are not suppressed in peripheral tissues	AIRE, FOXP3, CTLA4
Innate immune response dysregulation	Abnormal innate immune activity enhances proinflammatory responses and autoimmunity	IFIH1, TLR7, NOD2
Pancreatic islet inflammation (Insulitis)	Persistent infiltration of immune cells into pancreatic islets leads to chronic inflammation and β-cell damage	CXCL10, CCR5
Beta-cell regeneration failure	Impaired β-cell regenerative capacity limits the replacement of destroyed insulin-producing cells	PDX1, MAFA
Autoantibody production	Production of autoantibodies against β-cell proteins marks autoimmune activity and precedes clinical diagnosis	INS, GAD65, IA-2, PTPRN
Pathophysiology of T2D with a genetic network
Ref.	Liu et al[101], 2021; Febbraio and Karin[102], 2021;Donath[103], 2014; Zhu et al[104], 2025; Dhatariya[105], 2022; Zhang et al[106], 2016; Wu et al[107], 2023
Pathophysiological process	Description	Key genes
Insulin resistance	Decreased insulin sensitivity of peripheral tissues (liver, muscle, and fat)	IRS1, PPARG, TCF7 L2, INSR, AKT2
Impaired insulin secretion	Pancreatic β-cells’ inability to detect glucose and release insulin	KCNJ11, ABCC8, HNF1A, TCF7 L2, GLIS3
Lipotoxicity and ectopic fat accumulation	Fatty acid buildup in the liver and muscles disrupts insulin transmission.	PNPLA3, SREBF1, FABP4
Mitochondrial dysfunction	The metabolism of glucose is impacted by decreased oxidative phosphorylation and ATP generation	NDUFS4, UCP2, SIRT1
Inflammation and immune activation	Insulin resistance is facilitated by persistent low-grade inflammation	TNF, IL-6, NLRP3, TLR4
Adipokine dysregulation	Metabolic homeostasis is disturbed by an imbalance in adipokines, such as leptin and adiponectin	LEP, ADIPOQ, RETN
Glucose transport dysfunction	Lower glucose uptake is caused by decreased GLUT4 translocation in muscle and fat	SLC2A4, AS160
Hepatic gluconeogenesis overactivity	Overproduction of glucose in the liver in spite of hyperglycemia	G6PC, PCK1, FOXO1, CREB
Β-cell dedifferentiation and apoptosis	β-cell failure is a result of both increased apoptosis and loss of β-cell identity	PDX1, MAFA, NKX6-1, FOXO1
Gut microbiota and metabolic endotoxemia	Changes in the microbiota impact insulin sensitivity and inflammation	NOD2, TLR5, FFAR2
Pathophysiology of GDM with genetic network
Ref.	Damm et al[108], 2016; Kwak et al[109], 2012; Godfrey[110], 2002; Wicklow and Retnakaran[111], 2023; Dias et al[112], 2023; Franzago et al[113], 2019; Ruchat et al[114], 2013; Neven et al[115], 2022; Ibrahim et al[116], 2022; Zhang et al[117], 2022; Niu et al[118], 2023
Pathophysiological process	Description		Key genes
Progressive insulin resistance in pregnancy	Later in pregnancy, maternal insulin resistance is increased by placental hormones (such as hPL, estrogen, and progesterone)		IRS1, PPARG, INSR, SOCS3
Inadequate β-cell adaptation	Hyperglycemia results from the inability of pancreatic β-cells to compensate for the increased demand for insulin		TCF7 L2, HNF1A, GCK, CDKAL1
Placental hormonal dysregulation	Systemic insulin resistance and disturbed glucose metabolism are caused by altered placental hormone production		LEP, TNF, PAPP-A, PSGs
Adipokine imbalance and metabolic stress	Insulin signaling and energy homeostasis are hampered by decreased adiponectin and elevated leptin/resistin		ADIPOQ, LEP, RETN, NAMPT
Inflammation and oxidative stress	Insulin resistance is brought on by cytokine-mediated inflammation (IL-6, TNF-α) through interference with signaling		IL-6, TNF, CRP, NLRP3
Epigenetic modifications and fetal programming	Changes in miRNA and DNA methylation impact long-term results and maternal-fetal metabolism		DNMT3B, miR-29a, miR-103, MEG3
Obesity-associated insulin resistance	Insulin resistance and the risk of GDM are increased by maternal obesity via inflammatory and hormonal mechanisms		FTO, MC4R, SLC30A8, IL-1β
Gut microbiota alterations and endotoxemia	Endotoxemia and chronic inflammation brought on by microbial imbalance exacerbate insulin resistance		TLR4, NOD2, FFAR2, LBP
Mitochondrial dysfunction	β-cell dysfunction and reduced ATP generation are caused by impaired mitochondrial oxidative capability		UCP2, SIRT3, MFN2
Impaired insulin signaling pathway	The absorption and use of glucose are impacted by disruptions in the insulin receptor and downstream signaling.		INSR, IRS2, AKT2
Endocrine disruptor exposure and GDM risk	Through epigenetic modifications, EDCs like BPA and phthalates may affect β-cell activity and insulin sensitivity		ESR1, NR3C1, PPARG

T1D: Type 1 diabetes; HLA: Human leukocyte antigen; INS: Insulin; PTPN22: Protein tyrosine phosphatase non-receptor type 22; CTLA4: Cytotoxic T-lymphocyte associated protein 4; IL2RA: Interleukin-2 receptor alpha; FOXP3: Forkhead box P3; EIF2AK3: Eukaryotic translation initiation factor 2 alpha kinase 3; TXNIP: Thioredoxin interacting protein; IFIH1: Interferon induced with helicase C domain 1; STAT4: Signal transducer and activator of transcription 4; IL-10: Interleukin 10; AIRE: Autoimmune regulator; TLR7: Toll-like receptor 7; NOD2: Nucleotide-binding oligomerization domain containing 2; CXCL10: C-X-C motif chemokine ligand 10; CCR5: C-C motif chemokine receptor 5; PDX1: Pancreatic and duodenal homeobox 1; MAFA: MAF BZIP transcription factor A; GAD65: Glutamic acid decarboxylase 65; IA-2: Protein phosphatase-like islet antigen 2; PTPRN: Protein tyrosine phosphatase receptor type N; IRS1: Insulin receptor substrate 1; PPARG: Peroxisome proliferator-activated receptor gamma; TCF7 L2: Transcription factor 7 Like 2; INSR: Insulin receptor; AKT2: AKT serine/threonine kinase 2; KCNJ11: Potassium inwardly rectifying channel subfamily J member 11; ABCC8: Adenosine triphosphate binding cassette subfamily C member 8; HNF1A: Hepatocyte nuclear factor 1 alpha; GLIS3: GLIS family zinc finger 3; PNPLA3: Patatin-like phospholipase domain containing 3; SREBF1: Sterol regulatory element binding transcription factor 1; FABP4: Fatty acid binding protein 4; NDUFS4: NADH ubiquinone oxidoreductase subunit S4; UCP2: Uncoupling protein 2; SIRT: Sirtuin; TNF: Tumor necrosis factor; IL-6: Interleukin 6; NLRP3: NLR family pyrin domain containing 3; TLR4: Toll like receptor 4; LEP: Leptin; ADIPOQ: Adiponectin; RETN: Resistin; SLC2A4: Solute carrier family 2 member 4; GLUT4: Glucose transporter type 4; AS160: Akt Substrate of 160; G6PC: Glucose-6-phosphatase catalytic subunit; PCK1: Phosphoenolpyruvate carboxykinase 1; FOXO1: Forkhead box O1; CREB: CAMP response element-binding protein; NKX6-1: NK6 homeobox 1; TLR5: Toll-like receptor 5; FFAR2: Free fatty acid receptor 2; SOCS3: Suppressor of cytokine signaling 3; GCK: Glucokinase; CDKAL1: CDK5 regulatory subunit associated protein 1 like 1; PAPP-A: Pregnancy-associated plasma protein A; PSGs: Pregnancy-specific beta-1-glycoproteins; NAMPT: Nicotinamide phosphoribosyltransferase; CRP: C-reactive protein; DNMT3B: DNA methyltransferase 3 beta; miR-29a: MicroRNA-29a; miR-103: MicroRNA-103; MEG3: Maternally expressed 3; FTO: Fat mass and obesity-associated gene; MC4R: Melanocortin 4 receptor; SLC30A8: Solute carrier family 30 member 8; IL1β: Interleukin 1 beta; LBP: Lipopolysaccharide binding protein; MFN2: Mitofusin 2; IRS2: Insulin receptor substrate 2; ESR1: Estrogen receptor 1; NR3C1: Nuclear receptor subfamily 3 group C member 1; GDM: Gestational diabetes mellitus; EDC: Epidermal differentiation complex; BPA: Bisphenol A.

Table 6 An Indian view of the epidemiology of diabetes (2024-2025)

Epidemiology of diabetes (2024-2025)
Parameter	Details
Ref.	Duncan et al[119], 2025; Indian Council of Medical Research[120], 2023; The Times of India[121], 2025; MedBound Times[122]; India Today NE[124]
Total diabetics (20-79 years)	As of 2024, approximately 89.8 million individuals in India have diabetes, projected to rise to 101 million by 2025
Prediabetes prevalence	An estimated 136 million Indians have prediabetes, highlighting a critical population requiring preventive interventions
Urban vs rural prevalence	Urban areas report a higher prevalence (15%-20%) compared to rural areas (8%-12%), though rural rates are rising steadily
Gender distribution	Males show a slightly higher prevalence, though women, especially those with a history of gestational diabetes, are significantly affected
Age group most affected	Adults aged 45-59 years are most affected, with a concerning increase in cases among those aged 30-45
Top states/UTs by prevalence (%)	Goa (26.4%), Puducherry (26.3%), and Kerala (25.5%) report the highest prevalence rates
Least affected states	Bihar (4.3%), Mizoram (6%), and Nagaland (approximately 6%) have the lowest reported prevalence
Key risk factors	Obesity, physical inactivity, unhealthy diets, family history, and tobacco/alcohol use are major contributors
Complications	Includes retinopathy, nephropathy, neuropathy, cardiovascular disease, and diabetic foot ulcers
Economic burden	Diabetes costs India an estimated $30 billion annually in direct and indirect costs
Government initiatives	Key programs include the National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases, and Stroke (NPCDCS), Ayushman Bharat, and eSanjeevani teleconsultation services
Recent trends	The disease burden is shifting towards rural areas and lower socio-economic groups, with a rise in type 2 diabetes among children and adolescents
Challenges	Key hurdles include late diagnosis, poor glycemic control, inadequate healthcare infrastructure in rural regions, and a lack of public awareness

UTs: Union Territories; NPCDCS: National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases, and Stroke.

Table 7 Demonstration of diabetes prevalence across Indian states and Union Territories for 2023 and 2024, n (%)

Comparison of diabetes prevalence across all Indian states and Union Territories (2023 and 2024)
Ref.	Anjana et al[127], 2023; International Diabetes Federation[128], 2023; Ministry of Electronics and Information Technology[129]; Anjana et al[130], 2023; Anjana et al[131], 2024; Anjana et al[132], 2011; Mahajan et al[133], 2025; National Family Health Survey[134]
State/Union Territory	Prevalence		Urban		Rural		Key risk factors
Southern States	2023	2024	2023	2024	2023	2024
Andhra Pradesh	12.5	13.0	14.7	15.3	10.6	11.0	Rice-heavy diet
Karnataka	11.9	12.4	14.2	14.7	9.8	10.3	IT sector sedentary jobs
Kerala	19.4	20.1	23.1	23.8	16.2	16.9	Aging population
Tamil Nadu	15.7	16.3	18.9	19.5	12.8	13.3	Genetic predisposition
Telangana	13.1	13.7	15.8	16.4	10.9	11.4	Processed food consumption
Northern States
Delhi (National Capital Territory)	15.3	15.9	16.8	17.4	8.2	8.6	Urban stress, pollution
Haryana	9.2	9.7	12.1	12.7	7.3	7.7	High body mass index (> 25) prevalence
Himachal Pradesh	7.8	8.3	9.5	10.0	6.7	7.2	Alcohol consumption
Jammu and Kashmir	6.9	7.4	8.7	9.3	5.8	6.2	Low screening rates
Punjab	14.2	14.8	16.5	17.1	12.1	12.7	Wheat-heavy diet
Rajasthan	7.1	7.6	9.3	9.8	6.2	6.6	Limited healthcare access
Uttarakhand	8.3	8.8	10.6	11.2	7.1	7.6	Tourism-related dietary shifts
Western States
Goa	12.3	12.9	14.9	15.5	9.8	10.3	Alcohol, seafood diet
Gujarat	10.8	11.4	13.1	13.8	8.9	9.4	Trans-fat consumption
Maharashtra	12.8	13.3	15.3	15.9	10.4	10.8	Stress, fast-food culture
Eastern States
Bihar	5.7	6.1	8.4	8.9	4.9	5.3	Low awareness
Jharkhand	6.2	6.7	8.9	9.5	5.3	5.7	Tribal health disparities
Odisha	7.5	8.0	10.1	10.8	6.4	6.9	Rice-based malnutrition
West Bengal	9.7	10.3	12.4	13.1	7.6	8.1	Sweetened food culture
North-Eastern States
Assam	6.8	7.3	9.2	9.7	5.9	6.3	Betel nut consumption
Manipur	7.8	8.3	10.5	11.0	6.7	7.1	Rapid urbanization
Meghalaya	6.5	6.9	8.3	8.7	5.8	6.1	Indigenous dietary patterns
Mizoram	7.1	7.6	9.7	10.3	6.2	6.7	Smoking prevalence
Nagaland	6.3	6.7	8.6	9.1	5.5	5.8	Low health infrastructure
Sikkim	8.9	9.5	11.2	11.8	7.6	8.0	Alcohol use
Tripura	7.4	7.9	9.8	10.4	6.5	7.0	Rapid lifestyle changes
Union Territories
Chandigarh	13.5	15.2	14.1	18.0	9.3	12.4	Affluence-linked obesity
Puducherry	14.6	14.1	17.3	14.7	11.9	9.7	French-influenced diet

Table 8 Demonstration of diabetes prevalence across Indian projection for 2025, n (%)

Diabetes prevalence across Indian States and Union Territories (2025 Projections)
Ref.	Ministry of Health and Family Welfare[135], 2024; International Diabetes Federation[136], 2025; Government of Goa[137], 2025; Makkar et al[138], 2025; International Diabetes Federation[139], 2025; Ministry of Health and Family Welfare[140], 2024; Imai et al[141], 1988; International Diabetes Federation[142]; Ministry of Health and Family Welfare Government of India[143]
State/Union Territory	2025 prevalence	Urban	Rural	Key risk factors
Andhra Pradesh	13.1	15.6	11.2	Rice-heavy diet, low activity
Bihar	6.4	9.0	5.5	Low awareness, processed food uptake
Delhi (National Capital Territory)	16.5	17.8	9.1	Pollution, stress, and obesity
Goa	14.0	16.3	11.2	Alcohol, seafood, tourism diet
Gujarat	11.5	14.0	9.4	High trans-fat intake
Karnataka	12.7	15.1	10.6	IT sector inactivity
Kerala	20.8	24.3	17.5	Aging, sedentary jobs
Maharashtra	14.1	16.7	11.9	Fast-food culture, stress
Punjab	15.1	17.6	13.2	Wheat-based diet, low exercise
Tamil Nadu	17.2	20.1	14.0	Genetic risk + urban lifestyle
Telangana	14.3	17.0	12.1	IT corridor stress
Uttar Pradesh	7.2	10.0	6.0	Low screening rates
West Bengal	10.5	13.2	8.4	Sweetened food habits

Table 9 Key components of India’s diabetes care ecosystem infrastructure, access, and policy recommendations

India’s approach to healthcare: Treatment and management[146-151]
Ref.	World Health Organization[146], 2022; Muralidharan[147], 2024; Mohan et al[148], 2007; International Diabetes Federation[149], 2023; Anjana et al[150], 2017; Ranasinghe et al[151], 2024
Component	Details
National program	NPCDCS (2010) - screening, lifestyle advice, free medication/diagnostics at PHCs; implemented in 600+ districts
Primary care infrastructure	Health and Wellness Centers (HWCs) - diabetes screening, lifestyle education, digital health records via ABHA ID
Private sector role	Handles approximately 70% of diabetes cases; offers specialist care, advanced diagnostics, but with higher out-of-pocket expenses
Affordable medicines	Jan Aushadhi Kendras supply low-cost generics (Metformin, glimepiride, basic insulin)
Diagnostic access	Public labs provide subsidized HbA1c, glucose, and lipid profile tests; mobile units support rural outreach
Insulin availability	Cold chain limitations in rural areas; limited access to analogs and newer injectables (GLP-1, SGLT2i) in the public sector
Digital health tools	eSanjeevani: Govt. teleconsultation platform - private apps (BeatO, 1 mg, HealthifyMe), sugar tracking, online consults, lifestyle advice
Challenges	Poor awareness and treatment adherence - high cost in the private sector - rural supply chain gaps - fragmented care and follow-up
Policy recommendations	Universal screening - subsidized diagnostics and newer drugs - better referral system - rural insulin supply - integrate nutrition and mental health

NPCDCS: National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases, and Stroke; PHCs: Primary health centers; HWCs: Health and Wellness Centers; HbA1c: Glycated hemoglobin; GLP-1: Glucagon-like peptide-1; SGLT2i: Sodium-glucose cotransporter-2 inhibitors; ABHA ID: Ayushman Bharat Health Account ID.

Table 10 Availability and cost of essential diabetes treatments across health sectors in India

Diabetes prevention, treatment options, and management stratigies
Ref.	Government of India[126], 2023; Anjana et al[127], 2023; International Diabetes Federation[128], 2023; Prasanna Kumar et al[154], 2024
Aspect	Details
Essential drugs	Metformin, glimepiride, insulin (human), and pioglitazone are included in the National List of Essential Medicines (NLEM)
Generic drug access	Available via Jan Aushadhi Kendras (government-run generic medicine outlets) at 50%-90% lower cost than branded versions
Insulin access	Human insulin is widely available; analogs (e.g., glargine, lispro) are expensive and less accessible in rural Primary Health Centers (PHCs)
Cost burden	Monthly cost [branded insulin + oral antidiabetic drugs (OADs)]: Approximately 1500-3000; generics: 300-800
Public sector availability	State-run hospitals provide free/basic medications; stockouts and geographic variation are common
Private sector access	Full range of medications available, but high out-of-pocket (OOP) expenses; patients often switch to cheaper or irregular treatment
Innovative treatments	Newer classes like sodium-glucose cotransporter 2 inhibitors (SGLT2i), glucagon-like peptide-1 receptor agonists (GLP-1 RA), and dipeptidyl peptidase-4 inhibitors (DPP-4i) are limited to metropolitan areas and private hospitals due to cost and awareness gaps
Insurance coverage	Partial under Ayushman Bharat - Pradhan Mantri Jan Arogya Yojana (AB-PMJAY); many private plans do not cover chronic outpatient department (OPD) care
Policy recommendations	Expand NLEM to include newer drugs - ensure insulin cold chain in rural areas- Subsidize analog insulins

NLEM: National List of Essential Medicines; PHCs: Primary health centers; OADs: Oral antidiabetic drugs; OOP: Out-of-pocket; SGLT2i: Sodium-glucose cotransporter 2 inhibitors; GLP-1 RA: Glucagon-like peptide-1 receptor agonists; DPP-4i: Dipeptidyl peptidase-4 inhibitors; OPD: Outpatient department; AB-PMJAY: Ayushman Bharat - Pradhan Mantri Jan Arogya Yojana.

Table 11 Traditional medicine systems and Ayurveda, Yoga, Unani, Siddha, and Homeopathy-based approaches in diabetes care in India

Indian perspective on the function of traditional and alternative medicine in the treatment of diabetes
Ref.	Government of India[126], 2023; Prasanna Kumar KM et al[154], 2024; Central Council for Research in Ayurvedic Sciences (CCRAS)[174], 2023; Council of Scientific and Industrial Research (CSIR), Ministry of AYUSH[175], 2023
Aspect	Details
Systems involved	India’s pluralistic healthcare system includes AYUSH: Ayurveda, Yoga, Unani, Siddha, and Homeopathy; these systems emphasize holistic approaches focusing on mind-body balance and lifestyle regulation for diabetes care
Popular herbs used	Gymnema sylvestre (Gurmar): Glucose-lowering effect, β-cell regeneration; Momordica charantia (Bitter gourd): Insulin-like compounds; Trigonella foenum-graecum (Fenugreek): Improves insulin sensitivity
Ayurvedic formulations	Common preparations include Chandraprabha Vati, Nishamalaki Churna, Dhanvantari Kashayam, and proprietary formulations like Diabecon and BGR-34, used as adjunct therapies for glycemic control
Yoga and lifestyle therapy	Yoga practices such as Surya Namaskar, Pranayama, and meditation have shown benefits in improving glycemic control, insulin sensitivity, and stress reduction in clinical and observational studies
Usage statistics	An estimated 20%-25% of Indian diabetes patients utilize some form of AYUSH therapy, commonly in conjunction with allopathic treatments
Evidence and Limitations	Preliminary studies and small-scale clinical trials indicate the efficacy of several AYUSH therapies; however, there is a lack of large-scale RCTs, standardization, and systematic safety evaluations
Government support	NMITLI project on herbal anti-diabeticsAYUSH research portal for data consolidation, government funding for clinical trials, and establishment of integrative healthcare centers
Challenges	Key barriers include quality control of herbal products, unregulated markets, potential herb-drug interactions, and poor disclosure by patients to conventional healthcare providers
Policy recommendations	Promote large-scale RCTs and meta-analyses to validate efficacy, develop standardized, quality-controlled formulations, establish integrative diabetes care clinics, and enhance patient education

AYUSH: Ayurveda, Yoga, Unani, Siddha, and Homeopathy; BGR-34: BRAIN glucose retention-34; RCTs: Randomized controlled trials.

Table 12 Strategies and models for diabetes prevention and management in India

Diabetes prevention and management in India
Ref.	MedBound Times[122]; Ministry of Health and Family Welfare[125], 2022; Government of India[126], 2023; Mahajan et al[133], 2025; International Diabetes Federation[139], 2025; Mohan et al[179], 2024
Strategy/intervention	Key features	Impact/remarks
NPCDCS	National program for NCD screening, health promotion, and free medication at primary health centers	Screened 150+ million people; improved early detection in low-income groups
Ayushman Bharat HWCs	Network of health centers providing primary care, diabetes screening, and counseling	Expanded preventive care in rural/underserved areas; a pillar of Universal Health Coverage
mDiabetes Initiative	WHO-MoHFW SMS program delivering lifestyle advice in 12 languages	Reached 1+ million people; cost-effective digital health model
Jan Aushadhi Scheme	Government pharmacies provide low-cost generic diabetes medicines	Reduced out-of-pocket expenses; improved drug access in rural areas
eSanjeevani Telemedicine	Government teleconsultation platform for diabetes follow-up and specialist access	100+ million consultations; improved care continuity in remote areas
Yoga and Lifestyle Initiatives	AYUSH-led programs promoting yoga and stress management for diabetes	Evidence shows reduced HbA1c; culturally accepted prevention strategy
ICMR-INDIAB study	National study on diabetes prevalence and risk factors	Data revealed 100+ million diabetics; informed national policy
Public-Private Partnerships	Collaborations with pharma/NGOs for insulin access and diabetes education	Enhanced care in underserved communities through targeted programs

NPCDCS: National Programme for Prevention and Control of Cancer, Diabetes, CVD and Stroke; NCDs: Non-communicable diseases; HWCs: Health and Wellness Centers; WHO: World Health Organization; SMS: Short message service; ICMR–INDIAB: Indian Council of Medical Research-India Diabetes; AYUSH: Ayurveda, Yoga, Unani, Siddha, and Homeopathy; HbA1c: Glycated hemoglobin; NGOs: Nongovernmental organizations.