You're using an outdated browser. Please upgrade to a modern browser for the best experience.
Epidemiology of Lean/Normal-Weight Type 2 Diabetes
Edit

Several epidemiologic data have continued to support the existence of lean diabetes in populations living in low-income countries of Asia and Africa, and others studies pointed to a high prevalence of diabetes in normal-weight non-white populations, even in high-income settings such as the U.S.

type 2 diabetes mellitus normal-weight pathophysiology

1. Introduction

The ongoing dramatic increase in incidence and prevalence of type 2 diabetes (T2D) is largely explained by the global epidemic of obesity, due to the known linkage between these two conditions [1]. It has been recently observed that any pattern of life-course exposure to obesity, i.e., thinness increasing weight or overweight from both early and late adulthood trajectories, may raise the risk for T2D development with respect to a stable normal body mass index (BMI) [2]. On the other hand, most overweight and obese individuals never develop diabetes, and conversely some normal-weight individuals are diabetic so that obese and non-obese subclasses of T2D are currently used in clinical practice.
An adult-onset non-insulin-dependent diabetes with low/normal BMI has been known since 1955, when Hugh-Jones first reported it in Jamaica as a unique form of diabetes among lean individuals that lacked the clinical features of both type 1 diabetes (T1D) and T2D [3]. Over the following decades, cases of leanness-associated diabetes emerged in many other low- and middle-income countries from Asiatic and African continents. In 1985, the WHO officially recognized a “malnutrition related diabetes mellitus” (MRDM) characterized by a resistance to the development of ketosis, partial resistance to insulin action, extreme degree of wasting and emaciation, and onset of symptoms before the age of 35 years [4]. In 1999, this clinical entity was dropped from WHO classification of diabetes due to a lack of substantial evidence for malnutrition or protein deficiency as independent causes of disease [5]. However, several epidemiologic data have continued to support the existence of lean diabetes in populations living in low-income countries of Asia and Africa, and others studies pointed to a high prevalence of diabetes in normal-weight non-white populations, even in high-income settings such as the U.S. [6][7][8][9][10]. More recently, some authors have classified the entire population of subjects with diabetes, both T1D and T2D, into five clusters based on the presence of six variables (age at diagnosis, BMI, glutamate decarboxylase antibodies, HbA1c, β-cell function, and insulin resistance). Those subgroups seem differently associated with diabetes complications and the classification could help clinicians identify patients at higher risk and tailor therapy [11].
Nevertheless, the lean/normal-weight T2D remains, to date, an understudied topic that deserves consideration for at least two reasons. Firstly, the largest increase in diabetes prevalence in the coming years is expected in non-obese, non-white individuals who represent the majority of the world if considering that nearly half of the globally estimated 463 million adults with diabetes live in India and China [12]. Due to the continuous migratory flows of Asian and other ethnic groups such as asylum-seekers refugees from conflict areas in the Middle East and Northern Africa, the number of people with diabetes will dramatically increase even among non-white ethnic minorities living in high-income Western countries [13][14]. A second point for interest is the still dilemmatic “obesity paradox”. Decade ago, a great sensation was raised by the results of a pooled analysis of longitudinal observational studies showing that adults with normal weight at the time of diabetes appearance had higher mortality than those overweight or obese [15]. Similar results were reported in other studies on individuals with diabetes [16][17]. In recent large meta-analyses, U-shaped associations between BMI and all-cause mortality in people with diabetes were observed with nadirs in the range of overweight or mild obesity [18][19][20]. Other authors did not confirm the phenomenon, or remarked the poor appropriateness of BMI as a measure of adiposity [21]. Moreover, they observed that most studies did not control for preexisting chronic illness and smoking status, or suffered from other limitations such as reverse causation, selection and treatment bias, and a one-time measurement of weight [22]. Even taking into account these opposite data, a protective effect of excess weight on mortality in diabetes cannot be denied with certainty and the question remains unsolved [23].
Whereas scientists from all over the world have spent great efforts to understand the mechanisms linking obesity to diabetes, the pathophysiology of lean T2D is still debated. Knowing eventual specific metabolic and physiologic drivers of the disease in normal-weight individuals is of great relevance for implementation of an effective prevention and an individualized clinical management in order to reduce the global burden of diabetes [24].

2. Epidemiology of Lean/Normal-Weight T2D

A few studies have assessed the frequency of T2D in white normal-weight populations, for example those documenting a prevalence of 5.1% in Australian adults and an incidence of 15% in a male Swedish cohort [25][26].
According to data collected in the last twenty years, populations from Asia and Africa are at risk for T2D at much lower levels of BMI than other ethnic groups, suggesting the need for lowering their current targets for ideal body weight [27][28].
A 2.1% incidence of MDRD was reported in a sub-Saharan African rural area, and a study examining the T2D prevalence in Zambia and Western Cape of South Africa found values of 2.9% and 9.4%, respectively, two-thirds of which were associated to under- or normal-weight [8][29].
In a nationally representative sample from China, T2D prevalence was 4.5% in individuals with a BMI < 18.5 kg/m2 and 7.6% in those with a BMI of 18.5–24.9 kg/m2 [7]. A similar 7.8% prevalence was found in subjects with a BMI < 25 kg/m2 in a nationally representative survey from mainland China [30]. In an underdeveloped area of South China, 68.2% of instances of newly detected T2D were from non-obese diabetics [31]. In a Japanese population, over 60% of the subjects with diabetes were not obese [32].
India is referred as one of the T2D capitals, with a predicted prevalence of 151.4 million indigenous South Asians affected by 2045 [33]. A study in semi-urban/rural India found most hyperglycemia in undernourished people [6]. Overall, T2D in Asian Indians is characterized by younger age of onset and relatively low BMI [34]. An analysis of the U.K. Biobank containing four large ethnic groups, established that to have the same diabetes risk as white participants with a BMI  > 30 kg/m2, the equivalent BMI in South Asians was only 22 kg/m2 [35]. Cross-sectional analyses using representative samples of Asian Indians (South Asia CARRS-Chennai Study) and whites (U.S. NHANES Survey) demonstrated a significant ethnic difference in T2D prevalence in men, 5.4%/23.5% in under- and normal-weight Asian Indians and 0.0%/6.1% in their white counterparts. In women, the prevalence was 5.6%/13.6% in under- and normal-weight Asian Indians and 2.3%/2.8% in whites [36].
Most data come from ethnic minorities living in high-income Western countries. A study cohort of 18,000 T2D patients living in Chicago showed that around 13% had a BMI ranging from 17 to 25 kg/m2 and that Asians had a five-fold higher prevalence in the lean group (17% vs. 4%) [9]. In a large racially/ethnically and geographically diverse cohort of adults who were all members of integrated health care systems to correct for disparities in access to services, the age-standardized prevalence of diabetes increased across BMI categories among all groups. However, the prevalence of diabetes and prediabetes at low to normal BMI was 3.5 and 5%, respectively, in white subjects, and 7.3 to 10.2% and 9.6 to 18% in the various racial/ethnic groups, being the higher values registered in Hawaiians/Pacific Islanders and Asians [10]. A recently published systematic review and meta-analysis of prospective cohort studies (minimum 12-month follow-up, over 2.69 million participants from 20 countries) using ethnic-specific BMI categories, emphasized the crucial role of obesity demonstrating an increasing T2D risk of 0.93 for underweight, 2.24 for overweight, 4.56 for obesity, and 22.97 for severe obesity with respect to normal-weight. Interestingly, the underweight resulted a protective factor against T2D only in non-Asian people (RR = 0.68, 95% CI: 0.40–0.99, I2 = 56.1%, n = 6) [37].
Overall, these results suggest that environmental and genetic factors beyond obesity may contribute to the disproportionate burden of disease in non-white populations with ancestry from low- and middle-income countries.

References

  1. Kahn, S.E.; Hull, R.L.; Utzschneider, K.M. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 2006, 444, 840–846.
  2. Yacamán-Méndez, D.; Trolle-Lagerros, Y.; Zhou, M.; Monteiro Ponce de Leon, A.; Gudjonsdottir, H.; Tynelius, P.; Lager, A. Life-course trajectories of weight and their impact on the incidence of type 2 diabetes. Sci Rep. 2021, 11, 12494, Erratum in: Sci. Rep. 2021, 11, 18602.
  3. Hugh-Jones, P. Diabetes in Jamaica. Lancet 1955, 269, 891–897.
  4. WHO Study Group on Diabetes Mellitus & World Health Organization. Diabetes Mellitus: Report of a WHO Study Group ; World Health Organization: Geneva, Switzerland, 1985; Available online: https://apps.who.int/iris/handle/10665/39592 (accessed on 30 August 2022).
  5. World Health Organization. Definition, Diagnosis and Classification of Diabetes Mellitus and Its Complications: Report of a WHO Consultation. Part 1, Diagnosis and Classification of Diabetes Mellitus; World Health Organization: Geneva, Switzerland, 1999; Available online: https://apps.who.int/iris/handle/10665/66040 (accessed on 30 August 2022).
  6. Maiti, S.; Sinha, N.K.; Khan, M.M.; Das, P.K.; Chattopadhyay, J.C. Diabetes in rural individuals of different nutritional status and the alarming situation demands focus more on its under-nutrition association. Arch. Physiol. Biochem. 2015, 121, 26–31.
  7. Yang, W.; Lu, J.; Weng, J.; Jia, W.; Ji, L.; Xiao, J.; Shan, Z.; Liu, J.; Tian, H.; Ji, Q.; et al. Prevalence of diabetes among men and women in China. N. Engl. J. Med. 2010, 362, 1090–1101.
  8. Alemu, S.; Dessie, A.; Seid, E.; Bard, E.; Lee, P.T.; Trimble, E.R.; Phillips, D.I.; Parry, E.H. Insulin-requiring diabetes in rural Ethiopia: Should we reopen the case for malnutrition-related diabetes? Diabetologia 2009, 52, 1842–1845.
  9. Coleman, N.J.; Miernik, J.; Philipson, L.; Fogelfeld, L. Lean versus obese diabetes mellitus patients in the United States minority population. J. Diabetes Complicat. 2014, 28, 500–505.
  10. Zhu, Y.; Sidell, M.A.; Arterburn, D.; Daley, M.F.; Desai, J.; Fitzpatrick, S.L.; Horberg, M.A.; Koebnick, C.; McCormick, E.; Oshiro, C.; et al. Racial/Ethnic Disparities in the Prevalence of Diabetes and Prediabetes by BMI: Patient Outcomes Research To Advance Learning (PORTAL) Multisite Cohort of Adults in the U.S. Diabetes Care 2019, 42, 2211–2219.
  11. Ahlqvist, E.; Storm, P.; Käräjämäki, A.; Martinell, M.; Dorkhan, M.; Carlsson, A.; Vikman, P.; Prasad, R.B.; Aly, D.M.; Almgren, P.; et al. Novel subgroups of adult-onset diabetes and their association with outcomes: A data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018, 6, 361–369.
  12. International Diabetes Federation IDF Diabetes Atlas, 10th Edition . 2021. Available online: http://www.diabetesatlas.org/ (accessed on 3 October 2022).
  13. US Census Bureau. American Community Survey 1-Year Estimates: ‘Asian Alone or in Any Combination by Selected Groups’. 2017. Available online: https://www.census.gov/history/pdf/acs15yr-korean62017.pdf (accessed on 30 August 2022).
  14. Office of National Statistics (2011) UK Population by Ethnicity: Population of England and Wales. Available online: https://www.ethnicity-facts-figures.service.gov.uk/uk-population-by-ethnicity/national-and-regional-populations/population-of-england-andwales/latest#data-sources (accessed on 30 August 2022).
  15. Carnethon, M.R.; De Chavez, P.J.; Biggs, M.L.; Lewis, C.E.; Pankow, J.S.; Bertoni, A.G.; Golden, S.H.; Liu, K.; Mukamal, K.J.; Campbell-Jenkins, B.; et al. Association of weight status with mortality in adults with incident diabetes. JAMA 2012, 308, 581–590, Erratum in: JAMA 2012, 308, 2085.
  16. Doehner, W.; Erdmann, E.; Cairns, R.; Clark, A.L.; Dormandy, J.A.; Ferrannini, E.; Anker, S.D. Inverse relation of body weight and weight change with mortality and morbidity in patients with type 2 diabetes and cardiovascular co-morbidity: An analysis of the PROactive study population. Int. J. Cardiol. 2012, 162, 20–26.
  17. McEwen, L.N.; Karter, A.J.; Waitzfelder, B.E.; Crosson, J.C.; Marrero, D.G.; Mangione, C.M.; Herman, W.H. Predictors of mortality over 8 years in type 2 diabetic patients: Translating Research Into Action for Diabetes (TRIAD). Diabetes Care 2012, 35, 1301–1309.
  18. Zaccardi, F.; Dhalwani, N.N.; Papamargaritis, D.; Webb, D.R.; Murphy, G.J.; Davies, M.J.; Khunti, K. Nonlinear association of BMI with all-cause and cardiovascular mortality in type 2 diabetes mellitus: A systematic review and meta-analysis of 414,587 participants in prospective studies. Diabetologia 2017, 60, 240–248.
  19. Chang, H.W.; Li, Y.H.; Hsieh, C.H.; Liu, P.Y.; Lin, G.M. Association of body mass index with all-cause mortality in patients with diabetes: A systemic review and meta-analysis. Cardiovasc. Diagn. Ther. 2016, 6, 109–119.
  20. Kwon, Y.; Kim, H.J.; Park, S.; Park, Y.G.; Cho, K.H. Body Mass Index-Related Mortality in Patients with Type 2 Diabetes and Heterogeneity in Obesity Paradox Studies: A Dose-Response Meta-Analysis. PLoS ONE 2017, 12, e0168247.
  21. Tobias, D.K.; Pan, A.; Jackson, C.L.; O’Reilly, E.J.; Ding, E.L.; Willett, W.C.; Manson, J.E.; Hu, F.B. Body-mass index and mortality among adults with incident type 2 diabetes. N. Engl. J. Med. 2014, 370, 233–244, Erratum in: N. Engl. J. Med. 2014, 370, 1368.
  22. Han, S.J.; Boyko, E.J. The Evidence for an Obesity Paradox in Type 2 Diabetes Mellitus. Diabetes Metab. J. 2018, 42, 179–187.
  23. Banack, H.R.; Stokes, A. The ‘obesity paradox’ may not be a paradox at all. Int. J. Obes. 2017, 41, 1162–1163.
  24. Gloyn, A.L.; Drucker, D.J. Precision medicine in the management of type 2 diabetes. Lancet Diabetes Endocrinol. 2018, 6, 891–900.
  25. Dalton, M.; Cameron, A.J.; Zimmet, P.Z.; Shaw, J.E.; Jolley, D.; Dunstan, D.W.; Welborn, T.A.; AusDiab Steering Committee. Waist circumference, waist-hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J. Intern. Med. 2003, 254, 555–563.
  26. Skarfors, E.T.; Selinus, K.I.; Lithell, H.O. Risk factors for developing non-insulin dependent diabetes: A 10 year follow up of men in Uppsala. BMJ 1991, 303, 755–760.
  27. Chiu, M.; Austin, P.C.; Manuel, D.G.; Shah, B.R.; Tu, J.V. Deriving ethnic-specific BMI cutoff points for assessing diabetes risk. Diabetes Care 2011, 34, 1741–1748.
  28. Caleyachetty, R.; Barber, T.M.; Mohammed, N.I.; Cappuccio, F.P.; Hardy, R.; Mathur, R.; Banerjee, A.; Gill, P. Ethnicity-specific BMI cutoffs for obesity based on type 2 diabetes risk in England: A population-based cohort study. Lancet Diabetes Endocrinol. 2021, 9, 419–426, Erratum in: Lancet Diabetes Endocrinol. 2021, 9, e2.
  29. Bailey, S.L.; Ayles, H.; Beyers, N.; Godfrey-Faussett, P.; Muyoyeta, M.; du Toit, E.; Yudkin, J.S.; Floyd, S. Diabetes mellitus in Zambia and the Western Cape province of South Africa: Prevalence, risk factors, diagnosis and management. Diabetes Res. Clin. Pract. 2016, 118, 1–11.
  30. Wang, L.; Gao, P.; Zhang, M.; Huang, Z.; Zhang, D.; Deng, Q.; Li, Y.; Zhao, Z.; Qin, X.; Jin, D.; et al. Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013. JAMA 2017, 317, 2515–2523.
  31. Tang, Z.; Fang, Z.; Huang, W.; Liu, Z.; Chen, Y.; Li, Z.; Zhu, T.; Wang, Q.; Simpson, S.; Taylor, B.V.; et al. Non-Obese Diabetes and Its Associated Factors in an Underdeveloped Area of South China, Guangxi. Int. J. Environ. Res. Public Health 2016, 13, 976.
  32. Kashima, S.; Inoue, K.; Matsumoto, M.; Akimoto, K. Prevalence and characteristics of non-obese diabetes in Japanese men and women: The Yuport Medical Checkup Center Study. J. Diabetes 2015, 7, 523–530.
  33. International Diabetes Federation (2017) Clinical Practice Recommendations fo Rmanaging Type 2 Diabetes in Primary Care. Available online: https://www.idf.org/e-library/guidelines/128-idf-clinicalpractice-recommendations-for-managing-type-2-diabetes-inprimary-care.html (accessed on 30 August 2022).
  34. Gujral, U.P.; Pradeepa, R.; Weber, M.B.; Narayan, K.M.; Mohan, V. Type 2 diabetes in South Asians: Similarities and differences with white Caucasian and other populations. Ann. N. Y. Acad. Sci. 2013, 1281, 51–63.
  35. Ntuk, U.E.; Gill, J.M.; Mackay, D.F.; Sattar, N.; Pell, J.P. Ethnic-specific obesity cutoffs for diabetes risk: Cross-sectional study of 490,288 UK biobank participants. Diabetes Care 2014, 37, 2500–2507.
  36. Gujral, U.P.; Mohan, V.; Pradeepa, R.; Deepa, M.; Anjana, R.M.; Narayan, K.M. Ethnic differences in the prevalence of diabetes in underweight and normal weight individuals: The CARRS and NHANES studies. Diabetes Res. Clin. Pract. 2018, 146, 34–40.
  37. Yu, H.J.; Ho, M.; Liu, X.; Yang, J.; Chau, P.H.; Fong, D.Y.T. Association of weight status and the risks of diabetes in adults: A systematic review and meta-analysis of prospective cohort studies. Int. J. Obes. 2022, 46, 1101–1113.
More
Information
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : , , , , , , , , , , , ,
View Times: 615
Revisions: 2 times (View History)
Update Date: 09 Jan 2023
Academic Video Service