The growing concern of Type 5 diabetes mellitus: A narrative review

From nutritional deprivation to metabolic failure: The emergence of T5DM

Type 2 diabetes mellitus is the most common form of diabetes and usually starts in adulthood; it is characterised by insulin resistance or insufficient insulin production [11]. Type 1 diabetes mellitus is a chronic condition in which the pancreas secretes little or no insulin [10]. Gestational diabetes mellitus occurs during pregnancy and poses high risks for both the mother and the child [12]. According to the IDF, diabetes encompasses diverse subtypes beyond the common type 1, type 2, and gestational forms. Approximately 1.5–2% of global cases consist of heterogeneous subtypes, including monogenic forms, autoimmune variants like latent autoimmune diabetes in adults, and secondary diabetes resulting from underlying pathologies or medications [13]. Despite their lower prevalence, these forms are clinically significant due to their distinct pathophysiology and specialized management requirements.

First identified in Jamaica in 1955, malnutrition-related diabetes primarily affects young, lean individuals (BMI <19 kg/m²) in LMICs. These patients are frequently misdiagnosed with type 1 diabetes mellitus; however, they present a unique clinical phenotype: they do not develop ketonuria or ketosis despite profound hyperglycemia and high insulin requirements [2]. In 1985, the World Health Organisation (WHO) formally recognised MRDM, dividing it into two subclasses: Fibrocalculous pancreatic diabetes (FCPD) and protein-deficient pancreatic diabetes [7]. Although the WHO withdrew this classification in 1999, citing a lack of causal evidence [5, 14], the clinical reality in resource-poor regions has led to a modern revitalisation of these categories under the contemporary IDF framework, type 3c (formerly FCPD), categorised as "diabetes of the exocrine pancreas." This subtype is defined by physical, obstructive damage. Chronic undernutrition triggers non-alcoholic pancreatitis and the formation of pancreatic calculi (stones), leading to structural destruction of the organ [7, 14]. T5DM (formerly protein-deficient pancreatic diabetes) represents a functional insulin deficiency in a structurally "clean" pancreas. It is driven by the impact of severe early-life undernutrition on β-cell development and metabolic programming rather than mechanical injury [2, 7].

In a study of South Asian populations, Lontchi-Yimagou et al. [15] provided compelling evidence that “low BMI diabetes” (LD) commonly represents a metabolically distinct subtype of diabetes that does not fit the conventional classifications of type 1 or type 2 diabetes mellitus. In their state-of-the-art study utilizing advanced metabolic phenotyping, including C-peptide deconvolution, hyperinsulinemic-euglycemic clamp studies, and ¹H-NMR spectroscopy, LD individuals were directly compared with demographically matched cohorts of type 1 diabetes mellitus, type 2 diabetes mellitus, and nondiabetic controls. The LD group displayed a markedly reduced total insulin secretory response, which was significantly lower than that of both lean nondiabetic controls and individuals with T2D. Despite this impairment in insulin secretion, LD individuals exhibited preserved insulin sensitivity, as evidenced by lower endogenous glucose production and higher peripheral glucose uptake than T2D individuals. Additionally, visceral adiposity and hepatic lipid accumulation, hallmarks of insulin resistance in T2D patients, were significantly lower in the LD group. These findings strongly support the hypothesis that LD is not simply a lean variant of T2D but rather a distinct metabolic entity, likely influenced by early-life undernutrition, environmental stressors, and possibly unique genetic or epigenetic factors.

Some scholars argue that the heterogeneity, diagnostic uncertainty, and declining epidemiological relevance of MRDM render its reclassification as a distinct type of diabetes—referred to as “T5DM”—currently unnecessary [16]. They suggest that MRDM represents one end of the spectrum of type 2 diabetes (T2D), characterised by an earlier onset, significant insulin deficiency, and a heightened risk of microvascular complications [17]. However, given its distinct pathophysiology, low-BMI diabetes aligns closely with the emerging framework of recently named T5DM.

The pathophysiological link: from deprivation to disease

Nutrition plays a critical role in the developmental programming of children. The physical and cognitive development of children is strongly dependent on their nutritional status, which is determined by the availability and levels of essential nutrients [18]. Poor nutrition during the early stages of development (fetal or infant stages) may induce epigenetic modifications in gene expression that increase susceptibility to diseases and adverse long-term health outcomes, some of which may be irreversible [19]. Possible biological mechanisms include alterations in tissue development that affect maternal nutritional and metabolic profiles, as well as impaired placental function, which ultimately affect fetal growth and development [20].

Pregnancy involves many metabolic adaptations and epigenetic regulators that drive changes in beta cell function, ensuring an adequate supply of nutrients to the developing fetus [21].

Impairment of pancreatic development during a critical growth period results in reduced β-cell mass and function, ultimately leading to reduced insulin secretory capacity and increased susceptibility to metabolic disorders, including diabetes [20]. Severe acute malnutrition has been linked to malabsorption and impaired glucose metabolism due to pancreatic dysfunction [22]. Protein deficiency has been reported to impair insulin secretion, resulting in the pancreas's inability to produce sufficient insulin to regulate blood glucose levels [22]. This can result in T5DM, characterised by insulin secretory defects rather than resistance. Early-life malnutrition negatively affects pancreatic β-cell development, critical for insulin production and glucose homeostasis, ultimately leading to a lasting reduction in insulin secretion that persists into adulthood [23]. Similarly, maternal malnutrition, low birth weight, and childhood malnutrition are risk factors for this type of diabetes [24]. Moreover, studies on animals have shown that maternal protein deficiency leads to reduced beta-cell mass and impaired regeneration of beta cells in offspring [25]. Similarly, research in humans indicates that neonates classified as small for gestational age have fewer islet cells and a lower pancreatic blood supply [21].

Emerging evidence suggests that problems with the incretin axis, which is essential for maintaining balanced blood sugar levels, may be a key pathological feature MRDM [26]. In cases of chronic undernutrition, such as starvation or early-life malnutrition, the incretin response of the gut is weakened. This leads to changes in the expression of signaling molecules such as PAK1 and β-catenin. These disruptions can reduce GLP-1 production and secretion from intestinal L cells. As a result, this contributes to the impaired insulin response typical of MRDM [22–26].

Experimental studies in rats have shown that when a fetus does not receive enough nutrition, the liver produces fewer growth hormone receptors, and the IGF-1 signaling pathways become weaker, leading to lasting impairments in somatic growth and metabolic efficiency [27].

This condition is much more common in poor countries, where malnutrition remains widespread and access to diabetes treatments is limited [2]; thus, proper identification and classification of T5DM are essential for creating suitable diagnostic guidelines, management approaches, and public health initiatives [4].

Regional-specific manifestations of T5DM

Malnutrition, a major global health challenge, is closely linked to the emerging burden of T5DM. In 2024, 42.8 million children under five were affected by wasting, including 12.2 million with severe wasting. The burden is greater in Asia (30.0 million) and Africa (11.7 million), with substantially lower prevalence in Latin America, the Caribbean (0.6 million) and Oceania (0.1 million); Australia and New Zealand reported fewer than 0.1 million cases [6]. Stunting affects 150.2 million children globally, concentrated largely in Southern Asia and Africa [6]. Paradoxically, these same high-burden regions for undernutrition are also experiencing a rising burden of T5DM, estimated to affect 20–25 million people worldwide, with the majority of cases concentrated in Southern Asia and Africa [2, 3]. While most common in LMICs, T5DM also affects vulnerable groups in high-income settings, including individuals facing food insecurity and migrants with early-life undernutrition, where it may be under-recognised [2, 9].

The global distribution of T5DM reflects significant structural inequalities in health, as this condition disproportionately affects populations in resource-constrained environments [28]. Below, we present geographic and population-specific perspectives on how this disease manifests.

South Asia

T5DM is a major health issue in South Asia, especially in Bangladesh, India and Pakistan. It has been established that young-onset type 2 diabetes in South Asians has a distinct clinical presentation, such as earlier onset, low BMI, and a rapid β-cell decline [15, 29, 30]. Moreover, genetic predisposition and intrauterine fetal programming, combined with subsequent overconsumption of nutrients and refined carbohydrates, leading to the epidemic, are contributing features of the South Asian phenotype [31, 32]. Among the resource-limited countries, malnutrition-related diabetes is a poorly studied subject in Bangladesh, although prevalence rates are high [8]. Additionally, income-based disparities show that underweight individuals are primarily found among poorer population groups [33]. Considering the limitations of BMI in assessing obesity among South Asians, more body composition indices are necessary to address the rising burden of metabolic disease in the region [34]. Furthermore, the identification of T5DM in India underscores the urgent need for integrated strategies that address nutritional vulnerabilities from early childhood through adulthood [35].

Sub-saharan Africa

Malnutrition-related diabetes is unevenly distributed in Sub-Saharan Africa, and this situation is predetermined by endemic food insecurity and chronic undernutrition [15, 36]. T5DM in Sub-Saharan Africa is manifested in lean individuals without autoimmune evidence, and has been incorrectly diagnosed as type 1 diabetes [37]. Moreover, the burden of the T5DM is mostly borne in nations such as Nigeria, where food insecurity and stunting are the key factors contributing to the risk of T5DM [38, 39]. Additionally, the burden of the condition in Africa, which has remained historically underestimated, has led to poor management and outcomes [40].

Caribbean and Latin America

The Caribbean is known to be a location of early identification of T5DM, with the first incidence reported in 1955 in Jamaica [2, 41]. Irrespective of this historical background, the disease has been largely ignored; however, chronic undernutrition has continued to be an occurrence in areas with food insecurity and geopolitical tensions [40]. In the Caribbean and Latin America, there is a dual challenge of metabolic diseases and undernutrition. Most of the region is undergoing a nutritional transition, yet chronic undernutrition remains a significant issue [42]. This ongoing problem predisposes individuals to develop T5DM [8]. Furthermore, recognizing T5DM as a distinct clinical entity in nations like Mexico, where socio-political shifts often dictate access to healthcare, is critical. Such identification has far-reaching implications for community health, potentially averting diagnostic errors and substandard therapeutic interventions common among high-risk, vulnerable populations [41].

While the overarching driver of T5DM is rooted in global resource constraints [29], the specific catalysts for the disease vary by regional socioeconomic contexts. In South Asia, inequality is primarily income-based, where the poor face distinct nutritional vulnerabilities [33, 35]. In contrast, the burden in Sub-Saharan Africa is linked to endemic food insecurity and its physical impact on pancreatic development [36]. Meanwhile, in the Caribbean and Latin America, the condition is exacerbated by geopolitical instability and the complexities of a rapid nutritional transition [41].

Diagnosis and management of T5DM

The increased prevalence of T5DM in resource-limited regions demands heightened clinical awareness to ensure early diagnosis and management of this disorder [2, 5, 43]. Diagnosing T5DM involves a thorough evaluation of clinical features, relevant laboratory results, and the careful exclusion of other diabetes types [24]. The IDF working group is in the process of establishing standardised diagnostic criteria [2].

T5DM typically appears in adolescents and young adults and may present symptoms like type 1 diabetes, such as weight loss, excessive thirst, frequent urination, and fatigue. However, a key diagnostic signature of T5DM is a body mass index typically below 19 kg/m2. Crucially, unlike T1DM, these patients do not show signs of autoimmune β-cell destruction, and they remain uniquely "ketone-resistant" despite dangerously elevated glucose levels [5]. According to the recent IDF classification, malnutrition-related diabetes is mainly differentiated through pancreatic imaging to distinguish between type 5 and type 3c. Type 5 is the non-calcific variant, where the pancreas is underdeveloped but structurally "clean" (Table 1). Case reports from Ethiopia described children who met the Type 5 criteria: severe wasting, hyperglycemia without ketonuria, but without pancreatic calcification [5, 44, 45]. In Nigeria, Ubani et al. [46] and Oputa [47] reported cases of diabetes mellitus with pancreatic calcifications. While these patients share the type 5 phenotype of low BMI and malnutrition, the presence of stones confirms FCPD (Type 3c), which often necessitates adjunctive enzyme replacement therapy due to exocrine failure.

Test results		Disease		Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)
		Yes	No
Reid’s score ≥ 5	Positive	10	15	37.0	94.5	40.1	93.8
	Negative	17	258
Swede score ≥ 5	Positive	20	150	74.1	45.0	11.8	94.6
	Negative	7	123
Swede score ≥ 8	Positive	3	21	11.1	92.3	12.5	91.3
	Negative	24	252
a High-grade indicates a score of ≥5 in both tests; PPV indicates positive predictive value; NPV, negative predictive value

Test	Sensitivity (%)	Specificity (%)	Positive predictive value (%)	Negative predictive value (%)
Reid’s score ≥ 5	37.0	94.5	40.0	93.8
Swede score ≥ 5	74.1	45	11.8	94.6
Swede score ≥ 8	11.1	92.3	12.5	91.3

Test	Sensitivity (%)	Specificity (%)	Positive predictive value (%)	Negative predictive value (%)
Reid’s score ≥ 5	37.0	94.5	40.0	93.8
Swede score ≥ 5	74.1	45	11.8	94.6
Swede score ≥ 8	11.1	92.3	12.5	91.3

Narakas classification	Total 200 (100%)	Grade 1 72 (36%)	Grade 2 64 (32%)	Grade 3 50 (25%)	Grade 4 14 (7%)
Complete recoverya	107 (54)	60 (83)	40 (63)	7 (14)	-
Near complete functional recovery but partial deformitya	22 (11)	5 (7)	10 (16)	6 (12)	1 (7)
Partial recovery with gross functional defect    and deformity	31 (16)	7 (10)	13 (20)	10 (20)	1 (7)
No significant improvement	40 (20)	-	1 (1.5)	27 (54)	12 (86)
aSatisfactory recovery bGrade 1, C5, 6, 7 improvement; Grade 2, C5, 6, 7 improvement; Grade 3, panpalsy C5, 6, 7, 8, 9, Grade 4, panpalsy with Hornon’s syndrome.

Narakas classification	Total 200 (100%)	Grade-1 72 (36%)	Grade-2 64 (32%)	Grade-3 50 (25%)	Grade-4 14 (7%)
Complete recoverya	107 (54)	60 (83)	40 (63)	7 (14)	-
Near complete functional recovery but partial deformitya	22 (11)	5 (7)	10 (16)	6 (12)	1 (7)
Partial recovery with gross functional defect    and deformity	31 (16)	7 (10)	13 (20)	10 (20)	1 (7)
No significant improvement	40 (20)	-	1 (1.5)	27 (54)	12 (86)
aSatisfactory recovery bGrade 1, C5, 6, 7 improvement; Grade 2, C5, 6, 7 improvement; Grade 3, panpalsy C5, 6, 7,8,9, Grade 4, panpalsy with Hornon’s syndrome.

The problem of misclassification, combined with the effects of comorbid infections and financial constraints, complicates management processes. [5, 45]. Classifying T5DM as either Type 1 or Type 2 often leads to delays in diagnosis and incorrect treatments, which can worsen patient health [4].

Management of T5DM

While global treatment protocols for T5DM continue to evolve, it is crucial to recognise this "diabetes of poverty" for timely diagnosis and to prevent potentially life-threatening mismanagement [3]. Unlike type 1 or type 2 diabetes, patients with T5DM may develop episodes of severe hypoglycaemia, despite persistent hyperglycaemia, highlighting the need for careful, individualised therapy [2]. Addressing malnutrition in LMICs requires more than just nutrition-specific measures, which can reduce stunting by only about 20%. It is essential to implement broader nutrition-sensitive interventions in areas such as agriculture, education, and social protection to tackle the underlying drivers of malnutrition, including poverty, food insecurity, and poor sanitation [1, 2].

Management of malnutrition-related diabetes follows the C-peptide–guided approach proposed by Garg [24], which classifies patients into three groups. Group A (C-peptide >1.0 ng/mL, mild disease) is managed with sulfonylureas, with metformin if needed. Group B (severe hyperglycaemia or oral therapy failure) requires insulin with careful dose titration. Group C (intermediate reserve) benefits from combined oral agents and low-dose basal insulin. Across all the treatment groups, nutritional support with adequate protein, energy intake, and micronutrient supplementation is essential for long-term metabolic stability [24].

The advantages of addressing the root causes of malnutrition extend beyond just preventing diseases; they also contribute to improved national development, a higher standard of living, and sustainable growth aligned with the 2030 development agenda. However, to realise these benefits and tackle the rising threat of T5DM in LMICs, accurately diagnosing and characterising this condition is an essential first step. This process is crucial for avoiding misdiagnoses, tailoring effective treatments, enhancing health outcomes, and improving food sourcing within the country.

Limitations

This review is limited by its reliance on previously published literature, which may vary in quality, methodology, and regional representation. In addition, evidence from LMICs remains sparse, and underreporting or misdiagnosis may contribute to important gaps in the available epidemiological data. As a narrative review, quantitative synthesis or meta-analysis was not conducted, and publication bias cannot be ruled out completely.

Conclusion

Recommendations include integrating T5DM into national health policies with clear guidelines; developing nutrition training for women, expectant mothers, and young children focused on protein supplementation and breastfeeding; launching campaigns to educate communities on the links between malnutrition and diabetes; investing in sustainable food systems and supporting smallholder farmers to address economic shocks; and establishing long-term studies and national registries to monitor T5DM; and promoting multisectoral collaboration to tackle malnutrition's root causes.

Lesion-size	Histopathology report						Total
	CIN1	CIN2	CIN3	ICC	CC	SM
0–5 mm	73	0	0	0	5	5	83
6–15 mm	119	18	1	4	0	0	142
>15 mm	1	8	31	23	12	0	75
Total	193	26	32	27	17	5	300
CIN indicates cervical intraepithelial neoplasia; ICC, invasive cervical cancer; CC, chronic cervicitis; SM, squamous metaplasia

		Histopathology report						Total
		CIN1	CIN2	CIN3	ICC	CC	SM
Lesion -Size	0-5  mm	73	0	0	0	5	5	83
	6-15  mm	119	18	1	4	0	0	142
	>15  mm	1	8	31	23	12	0	75
Total		193	26	32	27	17	5	300
CIN indicates Cervical intraepithelial neoplasia; ICC, Invasive cervical cancer; CC, Chronic cervicitis; SM, Squamous metaplasia

Group	Didactic posttest marks (%)	Flipped posttest marks (%)	Difference in marks (mean improvement)	P
<50%	63.2 (9.4)	82.2 (10.8)	19.0	<0.001
≥50%	72.4 (14.9)	84.2 ( 10.3)	11.8	<0.001
Data presented as mean (standard deviation)