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

Abstract

In recent years, diabetes has become a major global health concern, and India is one of the countries most affected by the growing number of cases. In this review, we explore the diabetes scenario in the Indian community in comparison with global patterns. The extensive literature on diabetes suggests that poor diet, sedentary lifestyles, and genetic predisposition have been risk factors for diabetes. We further discuss disease management and treatment strategies related to diabetes in India, highlighting the challenges in healthcare accessibility and affordability. In addition, particularly in Indian scenarios, the role of traditional medicine as an alternative medicine is also discussed. This overall highlights possible interventions, including the National Diabetes Control Program, telehealth advancements, and community-based awareness campaigns. Therefore, we aim to discuss potential scenarios like rapid urbanization, changing dietary patterns, and socio-economic disparities in the diabetes epidemic in the country, and practical solutions for overall diabetes outcomes.

Key Words: Diabetes; Disease management; Indian community; India’s epidemic condition; Global health concern; Disease management; Diabetes epidemic

Core Tip: Diabetes mellitus is expected to become a global health emergency, with 643 million cases expected by 2030 and 792 million by 2045. India is among the most affected countries, where younger and less fortunate populations are increasingly being impacted by a complex interplay of genetic, environmental, behavioral, and socioeconomic factors. Despite government efforts, issues like poor glycemic control, delayed diagnosis, and limited access to healthcare, especially in rural areas, remain. Gene-environment interactions further raise risk, emphasizing the need for targeted prevention, early detection, and customized treatment regimens.

INTRODUCTION

Diabetes, in general, is a chronic metabolic disorder characterized by sustained hyperglycemia resulting from impaired insulin secretion, action, or sometimes both, and affecting multiple organs (Figure 1). Its etiology includes autoimmune beta cell loss (type 1), hormonal changes during pregnancy [gestational diabetes (GD)], and insulin resistance, which is often linked to obesity and lifestyle choices (type 2). Typical clinical signs include increased thirst, frequent urination, unexplained weight loss, fatigue, and chronic problems with the kidneys, heart, eyes, and nerves[1]. In terms of disease burden, non-communicable diseases (NCDs), particularly type 2 diabetes mellitus (T2DM), are overtaking communicable diseases. Ironically, diabetes has become more prevalent as a result of the economic boom, which is marked by increased industry, urbanization, and income levels. The International Diabetes Federation (2024) reports that over 101 million adults in India currently have diabetes, ranking second only to China. By 2045, that number is expected to rise to 134 million[1]. India’s economic growth has led to urbanization, dietary changes, and a decrease in physical activity, especially among the wealthier classes. This “nutrition transition” has increased the risk of obesity and diabetes as a result of sedentary lifestyles and increased consumption of processed foods[2,3]. Interestingly, despite the fact that diabetes was once believed to be a disease of wealth, recent studies reveal that the prevalence of the disease has significantly increased among low- and middle-income groups in both rural and peri-urban areas. This is attributed to a number of factors, including low health literacy, limited access to nutrient-dense meals, ignorance, economic disparity, and delayed diagnosis and treatment[4]. Over the past 20 years, the prevalence of diabetes in rural India has doubled, indicating a narrowing of the urban-rural divide, according to the Indian Council of Medical Research-India Diabetes study[5]. Because of the increasing prevalence of diabetes in India, it is estimated that the total costs of healthcare, including direct medical expenses and indirect effects like employee absenteeism, will surpass $35 billion annually by 2030[6]. Out-of-pocket costs are still high because so few people have health insurance, especially those with lower incomes. This financial burden is made worse by the early onset of diabetes (usually < 40 years), which affects the most productive demographic[7].

Figure 1  This infographic shows the overall impact of hyperglycemic condition in different organs in the body.

The rising burden of diabetes is particularly evident in India, where its prevalence has surged dramatically over the past few decades. This trend is mirrored in many other developing nations, especially in the Southeast Asian region, where rapid economic growth, urbanization, and dietary shifts contribute to an escalating public health challenge[8]. With an estimated 77 million people with diabetes in 2021 and predictions indicating a continued upward trend in the years to come, India stands out as a particularly notable example in the global context[9]. The complex interplay of genetic predisposition, environmental factors, socioeconomic disparities, and cultural nuances contributes to the escalating diabetes epidemic in India[10-12]. Emerging genomic studies have identified several susceptibility loci associated with type 2 diabetes (T2D) in both Indian and global populations[10]. Beyond genetics, environmental factors like air pollution, endocrine disruptors, and heavy metals contribute to T2D by disrupting glucose metabolism, promoting inflammation, and interacting with genetic susceptibilities through epigenetic mechanisms[11]. Socioeconomic disparities significantly worsen diabetes outcomes in low- and middle-income countries (LMICs) like India. A national family health survey analysis revealed that wealthier, urban, and more educated individuals have substantially greater awareness, treatment access, and disease control compared to their poorer, rural counterparts[12]. Chronic hyperglycemia, the hallmark of uncontrolled diabetes, initiates a cascade of systemic pathophysiology leading to widespread organ failure. Key mechanisms include insulin resistance, oxidative stress, chronic inflammation, and the accumulation of advanced glycation end-products[2,13]. These processes manifest across vital organs: Impaired cerebral glucose regulation disrupts appetite and elevates the risk of cognitive decline and neuropathy[2,13]; skeletal muscle insulin resistance causes fatigue and energy deficits[3,14]; and hepatic insulin resistance promotes hyperglycemia via increased gluconeogenesis[15].

Concurrently, pancreatic β-cell failure diminishes insulin secretion[16], while adipose tissue inflammation and renal overload further exacerbate the metabolic dysregulation[17]. The final common pathway is microvascular and macrovascular damage, including atherosclerosis and coronary artery disease[18], underscoring the critical need for consistent glycemic control. This review examines the global diabetes landscape, focusing on its epidemiology, genetic underpinnings, and management strategies. It provides a comparative analysis of the specific challenges and opportunities within the Indian context, highlighting key disparities and strategic interventions for prevention and improved clinical outcomes.

LATEST GLOBAL PERSPECTIVE ON DIABETES EPIDEMIOLOGY

Diabetes remains a major global health concern, with 536.6 million adults affected in 2024, a prevalence of 10.5% projected to rise to 783.2 million by 2045[1]. The burden is unevenly distributed, with the highest concentrations in the Western Pacific (206 million), South-East Asia (101 million), and the Middle East and North Africa (73 million) regions[19]. China (141 million) and India (101 million) alone account for nearly 40% of global cases[1]. T2D constitutes over 90% of all cases and is strongly associated with modifiable risk factors, including obesity and unhealthy diets. A concerning trend is the rising incidence among younger adults under 40, which is associated with longer disease duration, earlier complications, and increased mortality[20]. Significant geographic and socioeconomic disparities characterize the global diabetes landscape. LMICs bear over 75% of the global diabetes burden, despite frequently lacking robust diagnostic and long-term management systems[19]. While urban areas typically show higher prevalence (12%-15%) than rural regions (6%-8%), epidemiological models now indicate a faster growth rate in rural areas of South Asia, Sub-Saharan Africa, and Latin America[21]. Concurrently, prediabetes affects over 470 million people globally, with up to 70% progressing to T2D without intervention[1,22]. Diabetes accounted for 6.7 million deaths in 2023 alone[1].

In high-income countries, diabetes prevalence remains elevated (11.1% in 2024) and continues to rise, driven by sedentary lifestyles, processed food consumption, and aging populations[1,23]. Although technological innovations in diabetes management are advancing, the increasing incidence of young-onset T2D underscores the urgent need for enhanced preventive strategies[24]. The complex interplay of behavioral, genetic, and environmental factors necessitates coordinated global action focused on prevention, early detection, and equitable healthcare access[25,26] (Figure 2 and Table 1). T2DM constitutes 90%-95% of all global diabetes cases and is strongly linked to modifiable lifestyle factors, making it largely preventable[27]. In contrast, type 1 diabetes (T1D) is an autoimmune disorder characterized by the destruction of pancreatic β-cells, leading to absolute insulin deficiency and accounting for 5%-10% of cases[28]. Additionally, GD mellitus (GDM), a hyperglycemic state first identified during pregnancy, contributes to the overall disease burden and is a significant risk factor for the subsequent development of T2DM[29,30] (Table 2)[10,30]. The global rise in diabetes is marked by a critical shift towards younger-onset T2D, largely driven by unhealthy diets, sedentary behavior, and rising obesity. A report by diabetes United Kingdom noted a nearly 40% increase in T2D cases among those under 40 within five years[31]. While prevalence increases with age and is complicated by comorbidities in older adults[32], early-onset T2D is linked to greater insulin resistance, faster β-cell function decline, and more severe complications, elevating long-term morbidity and mortality[31]. Socioeconomic and ethnic disparities intensify this burden, disproportionately affecting deprived and minority groups. Obesity, a leading global cause of malnutrition, remains a primary risk factor, with higher body mass index correlating to earlier T2D onset[33]. Epidemiologically, diabetes is more common in men, with 17.7 million more men affected than women worldwide[34]. Genetic predisposition also plays a key role, as population-specific genetic variations influence susceptibility, disease progression, and treatment response[35]. Understanding these genetic, environmental, and socioeconomic factors is essential for developing personalized and effective prevention strategies.

Figure 2 This figure shows the estimated prevalence for 2024 and 2025. IDF: International Diabetes Federation.

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.

Risk factors

The escalating global burden of diabetes is driven by a complex interplay of genetic, environmental, lifestyle, and socioeconomic factors. While genetic predisposition plays a role, particularly in T1D and influencing susceptibility to T2D, the rapid increase in global prevalence is largely attributed to modifiable environmental and lifestyle factors.

Genetic factors

Genetic susceptibility contributes to the risk of developing both T1D and T2D. In T1D, specific genetic variations, particularly within the human leukocyte antigen (HLA) complex, are strongly associated with the autoimmune destruction of beta cells[36]. In T2D, numerous genes have been identified that increase the risk of developing the disease, often influencing insulin secretion, insulin sensitivity, or both[37]. However, it’s crucial to understand that genetic predisposition alone does not guarantee the development of T2D; environmental and lifestyle factors play a crucial role in determining whether this genetic susceptibility is expressed. Polygenic risk scores, which combine the effects of multiple genetic variants, are increasingly being used to assess individual risk for T2D[38] (Table 3)[39-64].

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.

Environmental factors

Environmental factors, particularly obesity and Western dietary patterns, significantly drive the onset and progression of T2DM. Diets high in processed foods, saturated fats, and refined carbohydrates promote weight gain and induce oxidative stress, insulin resistance, and systemic low-grade inflammation. These diets also cause gut dysbiosis, which further exacerbates metabolic dysfunction and inflammation[65]. Visceral obesity plays a central role by creating a pro-inflammatory state. Adipose tissue releases elevated levels of inflammatory cytokines (e.g., tumor necrosis factor-α, interleukin-6) and reduces protective adiponectin, impairing insulin signaling. Furthermore, ectopic fat deposition in the liver and pancreas leads to lipotoxicity and β-cell dysfunction, ultimately reducing insulin secretion[66]. These factors, combined with physical inactivity, sleep disorders, and exposure to environmental pollutants, underscore that T2DM is not solely genetic but is heavily influenced by modifiable lifestyle and environmental determinants. Public health strategies must therefore prioritize dietary improvement and obesity prevention to combat the diabetes epidemic.

Lifestyle factors

Physical activity: Regular physical activity is crucial for maintaining insulin sensitivity and glucose homeostasis[67]. Sedentary lifestyles, characterized by prolonged sitting and lack of exercise, significantly increase the risk of T2D[68].

Obesity: Obesity, particularly abdominal obesity, is a major risk factor for insulin resistance and the development of T2D[69]. The relationship between obesity and diabetes is complex and bidirectional, with obesity contributing to diabetes risk and diabetes increasing the risk of further weight gain.

Smoking: Cigarette smoking is associated with an increased risk of T2D and impairs insulin sensitivity and glucose metabolism[70] (Table 4)[71-81].

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.

Socioeconomic factors

Socio-economic factors, such as poverty, limited access to education and healthcare, and food insecurity, also contribute to the global diabetes burden[82]. Individuals from lower socioeconomic backgrounds may have limited access to healthy food choices, safe environments for physical activity, and quality healthcare, all of which can increase their risk of developing diabetes. Furthermore, stress related to poverty and social disadvantage may also play a role (Figure 3).

Figure 3  Determining the modifiable and non-modifiable risk factors for diabetes.

PATHOPHYSIOLOGY

Diabetes mellitus is a complex metabolic disorder characterized by persistent hyperglycemia, or high blood glucose levels. This hyperglycemia arises from defects in either the secretion of insulin, the action of insulin, or sometimes a mixture of both. Understanding the intricate pathophysiological mechanisms underlying these defects is crucial for developing effective prevention and treatment strategies. Here, we further explore the distinct Pathophysiology of both T1D, T2D, and GD (Figure 4). T1D is an autoimmune disorder characterized by the immune-mediated destruction of pancreatic β-cells, the exclusive producers of insulin, a hormone critical for glucose homeostasis. This autoimmune response is primarily driven by autoreactive CD4+ and CD8+ T lymphocytes, which infiltrate the pancreatic islets and initiate β-cell apoptosis[83]. Although the precise etiology remains unclear, a multifactorial interplay of genetic predisposition and environmental triggers is strongly implicated. The HLA complex on chromosome 6p21 is the strongest genetic determinant of T1D susceptibility. Specifically, HLA-DR and HLA-DQ alleles play a key role, with haplotypes such as HLA-DR3-DQ2 (DRB103:01-DQB102:01) and HLA-DR4-DQ8 (DRB104:01-DQB103:02) increasing risk, while HLA-DR2-DQ6 (DRB115:01-DQB106:02) provides protection. These variants influence antigen presentation, leading to improper immune recognition of β-cell antigens like insulin and glutamic acid decarboxylase 65, triggering autoimmunity. The peptide-binding properties of HLA-DQ2 and HLA-DQ8 enhance autoreactive T-cell activation, promoting β-cell destruction. Interactions with non-HLA genes, such as PTPN22 and INS, further modulate risk, highlighting the complex genetic basis of the disease[84]. Environmental factors, including viral infections and dietary influences, have been associated with disease onset, though definitive causal links remain elusive[85]. β-cell destruction occurs through mechanisms such as molecular mimicry, wherein exogenous antigens resemble β-cell epitopes, eliciting an immune response; the generation of autoantibodies against β-cell antigens, such as glutamic acid decarboxylase 65; and the release of pro-inflammatory cytokines by activated T cells[86]. This progressive decline in β-cell mass ultimately leads to a severe insulin deficiency, manifesting as overt hyperglycemia once approximately 80%-90% of β-cells are lost.

Figure 4  Understanding the pathophysiology of type 1 diabetes and type 2 diabetes.

T2D, typically, is a more intricate and multifactorial condition defined by two primary defects: Insulin resistance and impaired insulin secretion. Insulin resistance describes a state where cells, primarily in muscle, fat, and liver tissues, fail to respond appropriately to insulin[87]. Insulin, crucial for glucose uptake by cells, encounters resistance, requiring the pancreas to produce increasingly higher levels of the hormone to achieve the same glucose-lowering effect[88]. Obesity, especially visceral fat accumulation, is a major driver of insulin resistance. Excess adipose tissue releases hormones and inflammatory cytokines that interfere with insulin signaling pathways. Physical inactivity further exacerbates insulin resistance. Dietary patterns high in saturated fats and refined carbohydrates also contribute. Genetic factors also play a role in influencing individual insulin sensitivity[89]. Alongside insulin resistance, impaired insulin secretion develops. Initially, the pancreas compensates for insulin resistance by producing more insulin, leading to hyperinsulinemia. However, over time, the beta cells become overwhelmed and are no longer able to sustain this increased insulin output. This leads to a decline in insulin secretion, a progressive rise in blood glucose levels, and ultimately, the clinical manifestation of T2D[90]. Chronic hyperglycemia itself can further damage beta cells, creating a vicious cycle of worsening insulin deficiency. Furthermore, elevated free fatty acids (lipotoxicity) and chronic low-grade inflammation, often associated with obesity, can also impair beta cell function[91] (Table 5)[77,82,92-118].

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.

A REGIONAL VIEWPOINT ON DIABETES AND EPIDEMIOLOGY

As of 2024, India has approximately 89.8 million adults (aged 20-79 years) living with diabetes, and this number is projected to rise to 101 million by 2025[119]. Additionally, an estimated 136 million individuals in the country are living with prediabetes, indicating a significant population at risk[120]. There is a marked urban–rural disparity, with urban areas showing a prevalence of 15%-20%, while rural areas report a lower prevalence of 8%-12%[119]. When looking at gender distribution, males have a slightly higher prevalence of diabetes compared to females[119]. The most affected age group comprises individuals aged 45-59 years, though there is a growing trend among younger adults aged 30-45 years, reflecting a concerning shift in disease onset[121]. Among the states and union territories, Goa (26.4%), Puducherry (26.3%), and Kerala (25.5%) report the highest diabetes prevalence rates. Other regions with notably high rates include Lakshadweep (23.2%), Chandigarh (20.4%), and Delhi (17.8%)[119]. Conversely, Bihar (4.3%), Mizoram (6%), and Nagaland (approximately 6%) are among the least affected[119]. Key risk factors contributing to the rise in diabetes cases include obesity, physical inactivity, diets high in sugar and fat, family history, smoking, and alcohol consumption[119]. The disease is associated with several serious complications, such as retinopathy, nephropathy, neuropathy, cardiovascular disease, and foot ulcers[119]. The economic burden of diabetes in India is substantial, with an estimated $30 billion spent annually on both direct medical costs and indirect costs[122]. To combat the diabetes epidemic, the Indian government has implemented several initiatives, including the national program for prevention and control of cancer, diabetes, cardiovascular diseases, and stroke[123], Ayushman Bharat, and the E-Sanjeevani teleconsultation services[124]. Recent trends show that diabetes is increasing in rural and lower socio-economic groups, and there is also a rise in T2D among children, which was previously rare[120]. Despite efforts, India continues to face significant challenges, such as late diagnosis, poor glycemic control, and an inadequate healthcare infrastructure, particularly in rural and tribal regions[121]. The Ayushman Bharat program was started in 2018 with the intention of transforming India’s primary healthcare system by establishing Health and Wellness Centers (HWCs), also referred to as Ayushman Arogya Mandirs. These clinics are essential centers for the early detection, prevention, and treatment of NCDs, including T2DM, especially among disadvantaged populations[123]. HWCs conduct population-based screening for diabetes in individuals aged 30 and older using established protocols. Auxiliary nurse midwives and accredited social health activists typically assist community health officers in conducting screenings. For tracking and follow-up, they make use of glucometers and digital tools such as the Clinical and Public Health Committee-NCD portal and Ayushman Bharat Health Account IDs[124]. The three essential antidiabetic medications - glibenclamide, gliclazide, and metformin - are administered to patients with diabetes by HWCs in accordance with the Standard Treatment Guidelines. Monthly follow-ups are provided to patients for glucose monitoring and medication adjustments. eSanjeevani telemedicine services are being used for virtual consultations with medical officers and specialists to support clinical decision-making at the periphery[125,126]. In the treatment of diabetes, HWCs have demonstrated promising outcomes. A multi-state implementation evaluation found that most centers had > 85% of the required diabetes medications on hand, and over 70% of patients with diabetes were initiated on treatment at the HWC level[125,126] (Tables 6, 7, and 8)[119-122,124,127-143].

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

India’s health care system management and treatment

Diabetes management and treatment in India present a complex picture, shaped by a mix of healthcare system structure, access to resources, cultural beliefs, and economic realities. India’s healthcare system is a multi-tiered structure, comprising public and private sectors. Public healthcare facilities, including primary health centers in rural areas and government hospitals in urban centers, provide basic diabetes care. However, access to specialist care and advanced diagnostic facilities can be limited, particularly in rural areas[144]. The private sector plays a significant role, with private clinics and hospitals offering a wider range of services, but often at a higher cost. This mixed system creates disparities in access to quality diabetes care, with those in urban areas and with higher socioeconomic status generally having better access[145]. Many countries face similar challenges regarding healthcare access, but the scale and complexity of India’s population make these challenges particularly acute (Table 9)[146-151].

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.

Overview of diabetes prevention and treatment strategies in India

The treatment and management of diabetes in India are hindered by significant challenges, including disparities in medicine accessibility, affordability, and healthcare infrastructure. Despite government initiatives such as Jan Aushadhi and state-level subsidized pharmacies, essential anti-diabetic medicines remain inadequately available in public healthcare facilities, forcing patients to depend on private pharmacies where prices are often prohibitive. The high out-of-pocket expenditure on diabetes treatment exacerbates financial strain, particularly among low-income populations, contributing to poor adherence and suboptimal disease management[152]. Fixed-dose combinations offer a promising approach to improving compliance and treatment outcomes, but their integration into the healthcare system remains limited. Additionally, prescribing patterns favor costlier branded medicines over generic alternatives, further increasing the financial burden on patients. To enhance diabetes disease management, policymakers must ensure a steady supply of essential medicines in public healthcare facilities, enforce generic prescribing, implement transparent medicine price monitoring, and expand insurance coverage for diabetes care. Strengthening these aspects is essential for improving access to affordable and effective diabetes treatment across India[153] (Table 10)[126-128,154].

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.

Traditional medicine systems like Ayurveda, Siddha, and Unani are commonly used in India for diabetes management, employing herbal formulations such as Gymnema sylvestre (Gurmar), Momordica charantia (Bitter melon), and Trigonella foenum-graecum (Fenugreek), which demonstrate anti-diabetic properties through enhanced insulin secretion and improved glucose uptake[155-157]. Clinical evidence suggests traditional formulations can help regulate blood glucose and manage complications through antioxidant and anti-inflammatory properties[158]. However, significant gaps remain in large-scale validation and standardization. While integration with modern medicine could improve outcomes in resource-limited settings, combining treatments requires medical supervision to avoid adverse effects. Government initiatives like Ayurveda, Yoga, and Naturopathy, Unani, Siddha, and Homeopathy support research and standardization efforts[159].

Traditional and alternative medicine practices are gaining popularity due to their cultural relevance, affordability, and holistic approach, and are increasingly being integrated into conventional diabetes care[160]. For example, Momordica charantia (bitter melon) demonstrates insulin-mimetic and insulin-releasing properties, leading to reductions in glycated hemoglobin A1c (HbA1c) and fasting blood glucose[161]. Similarly, Trigonella foenum-graecum (fenugreek) seeds, rich in soluble fiber, improve glycemic control by slowing carbohydrate digestion and enhancing insulin sensitivity[162]. In Ayurvedic practice, Gymnema sylvestre (“gurmar”) helps manage dietary habits by reducing sugar cravings and supporting pancreatic β-cell regeneration[163].

An Indian randomized controlled trial demonstrated that a standardized polyherbal formulation containing Syzygium cumini, Emblica officinalis, and Tinospora cordifolia significantly reduced HbA1c, fasting plasma glucose, and postprandial glucose levels after 12 weeks of treatment[164]. Complementing herbal interventions, traditional practices like yoga and meditation show empirical support for diabetes management. A meta-analysis of 23 randomized trials confirmed that regular yoga practice significantly reduces body mass index, fasting glucose, and HbA1c in type 2 diabetes patients[165]. These benefits are attributed to improved glucose utilization, enhanced parasympathetic activity, and reduced cortisol levels. Similarly, mindfulness-based interventions indirectly improve glycemic control by alleviating psychological stress and enhancing dietary adherence[166].

Diabetes management employs distinct allopathic and Ayurvedic approaches. Allopathic treatment targets glucose metabolism, using metformin to improve insulin sensitivity[167], sulfonylureas like glibenclamide to stimulate insulin secretion (with hypoglycemia risk)[168], and dipeptidyl peptidase-4 inhibitors such as sitagliptin to enhance incretin effects[169]. Conversely, Ayurveda utilizes polyherbal formulations to restore metabolic balance, employing Gymnema sylvestre to reduce sugar cravings and support β-cell function[170], Momordica charantia with its insulin-mimetic compounds[161], Trigonella foenum-graecum to slow glucose absorption[162], and Emblica officinalis for antioxidant protection of β-cells[171]. Guduchi, or Tinospora cordifolia, has anti-inflammatory, insulin-sensitive, and immune-regulating qualities[164]. Ayurvedic treatments address systemic dysfunctions like Agni (digestion), Ama (toxins), and dosha imbalance to promote metabolic stability. While both systems offer glycemic benefits, combining them requires caution to prevent adverse herb-drug interactions. The World Health Organization Traditional Medicine Strategy (2014-2023) emphasizes the need for evidence-based integration, advocating for research and regulation to ensure safe, standardized use of traditional medicine in managing diabetes[172]. The global report also highlighted the need to standardize regulatory frameworks across countries and the increasing use of digital platforms to sell conventional drugs[173]. Future efforts should prioritize rigorous scientific validation, quality control, and formulation standardization to ensure safety and efficacy, ultimately enhancing diabetes management strategies in India (Table 11)[126,154,174,175].

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.

EFFECTIVE MODELS OF INTERVENTION IN DIABETES PREVENTION AND CONTROL

Several strategies and interventions have shown promise in addressing the growing diabetes burden in India, offering valuable lessons for other LMICs grappling with similar challenges. The National Diabetes Control Program in India, with its focus on early detection, health education, and affordable treatment, provides a potential model for large-scale diabetes management in resource-constrained settings[176]. Community-based initiatives, often driven by nongovernmental organizations and local organizations, have proven effective in raising awareness and promoting early detection, especially among vulnerable populations in both rural and urban settings. These campaigns can be particularly impactful in reaching communities with limited access to formal healthcare[177]. Establishing strong referral systems and integrating community-based initiatives with existing healthcare infrastructure are crucial for ensuring long-term care, a challenge shared by many LMICs, which can be a critical consideration for policymakers as well. The increasing use of telehealth in India offers promising solutions for diabetes management, especially in remote areas[178]. These technologies can improve access to specialist care, remote monitoring, and personalized support. Telehealth can bridge geographical barriers and provide remote monitoring and support, particularly beneficial in LMICs with dispersed populations and limited healthcare infrastructure. While further scientific evaluation and validation are needed, exploring the potential role of traditional practices alongside conventional care is relevant for many LMICs. Collaborative research and knowledge sharing across LMICs can facilitate the development of evidence-based approaches to integrating traditional medicine into diabetes care, not only at the local level but globally too[179] (Figure 5 and Table 12)[122,125,126,133,139,179].

Figure 5 Important national initiatives and policy changes in India concerning the prevention, treatment, and management of diabetes. NPCDCS: National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases and Stroke; HWCs: Health and Wellness Centers; ICMR: Indian Council of Medical Research; INDIAB: India Diabetes; NCD: Noncommunicable diseases; SMS: Short message service; NGOs: Nongovernmental organizations.

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.

CONCLUSION

Diabetes mellitus presents a critical and growing health challenge, particularly in LMICs. Driven by genetic, environmental, and lifestyle factors, its rising prevalence increasingly affects younger and more vulnerable populations. In India, management is hindered by issues of access, affordability, and infrastructure. The national response includes programs like the National Programme for Prevention and Control of Cancer, Diabetes, Cardiovascular Diseases, and Stroke, and Ayushman Bharat, digital health platforms like eSanjeevani, and the integration of Ayurveda, Yoga, and Naturopathy, Unani, Siddha, and Homeopathy systems. Efforts such as the Jan Aushadhi scheme for affordable medicines, yoga-based interventions, and public-private partnerships enhance care. Growing public awareness and digital tools are improving education and monitoring, yet further scientific validation and infrastructure strengthening are needed to effectively address the escalating burden.

India’s diabetes care system leverages a robust network of community health workers for rural outreach, yet it contends with critical challenges, including shortages of medical personnel, essential drugs, and diagnostic tools. These limitations contribute to low screening rates, delayed diagnosis, and fragmented care, exacerbating poor glycemic control and imposing significant financial strain on families. Emerging opportunities through digital health technologies, public-private partnerships, and community-based lifestyle programs offer promising avenues for improved tracking, affordable medication access, and preventive strategies. The growing burden of diabetes-related complications necessitates a strengthened primary healthcare system focused on early detection and personalized prevention. A comprehensive, integrated approach is crucial to mitigate India's substantial diabetes burden, though current assessments remain limited by reliance on secondary data and lack of direct program evaluation.

ACKNOWLEDGEMENTS

We are grateful to the Multidisciplinary Research Unit at Maulana Azad Medical College and Associated Hospitals, Department of Biotechnology, Guru Ghasidas Vishwavidyalaya, Delhi, and Faculty of Medicine, Alatoo International University, Bishkek. We would like to thank Raj Rajeshwar Malinda for their input in language correction.