Home Prediabetes: what are we talking about?
Article Open Access

Prediabetes: what are we talking about?

A translation of this article can be found here: https://doi.org/10.1515/almed-2021-0030
  • Javier Escalada San Martín EMAIL logo
Published/Copyright: July 26, 2021

Intermediate hyperglycemia (or prediabetic status) is an umbrella term for two entities: impaired fasting glucose (IFG) and glucose intolerance (GI). Different definitions have been proposed for these two overlapping conditions, according to the normal range of glycemia established. The American Diabetes Association (ADA), the World Health Organization (WHO), and the International Diabetes Federation (IDF) identify a category of hyperglycemic situations between normal glycemia and diagnosis of diabetes mellitus (DM) based on fasting glycemia in plasma or glycemia in venous plasma 2 h after 75 g OGTT (oral glucose tolerance test) [1]. More recently, it has been incorporated the possibility of diagnosis based on plasmatic HbA1c levels. For IFG diagnosis, these organizations establish different ranges of fasting glycemia in plasma (100 vs. 110 mg/dL) and normal HbA1c levels (5.7 vs. 6%). At present, the diagnostic criteria for prediabetes are well established (see Figure 1)

Figure 1: 
Diagnosis of preDM and DM (ADA* vs. WHO#).
ADA, American Diabetes Association; DM, diabetes mellitus; IFG, impaired fasting glucose; Gl, glycemia; GI, glucose intolerance; N, normal; WHO, World Health Organization; OGTT, oral glucose tolerance test.
Figure 1:

Diagnosis of preDM and DM (ADA* vs. WHO#).

ADA, American Diabetes Association; DM, diabetes mellitus; IFG, impaired fasting glucose; Gl, glycemia; GI, glucose intolerance; N, normal; WHO, World Health Organization; OGTT, oral glucose tolerance test.

Why is diagnosis of these entities important?

The prevalence of prediabetes is not a minor issue. According to the most recent data published in Spain in the di@bet.es study [2], the prevalence of IFG and GI is 3.4 and 9.2%, respectively. In addition, these are situations at a high risk of developing diabetes and cardiovascular disease (CV). Thus, patients with IFG are five times more likely to develop DM [3] and the cardiovascular risk is higher (nonfatal acute myocardial infarction [AMI]) and cerebrovascular events (relative risk [RR]: 1.19), with higher mortality rates (RR: 1.28), as compared to nondiabetic population [3]. On the other hand, GI is associated with a higher risk of developing diabetes, as compared to IFG. This risk is six-fold higher that in patients with normal glycemia (RR: 6.02 [95%CI: 4.66–7.38]), and up to 12 times higher in patients with both associated (RR: 12.21 [95%CI: 4.32–20.10]) [3]. GI is also associated with a higher risk of cardiovascular mortality (RR: 1.48) and general death (RR: 1.66) [3].

These data, however, is challenged by a recent cohort study [4] conducted in a sample of older adults (mean age 75.6 years) who, despite the high prevalence of prediabetes (diagnosis of IFG and/or HbA1c), restoration of normal glycemia, or death were more frequent than progression to diabetes. These results suggest that prediabetes may not be a solid diagnostic entity in older adults. Further research is needed in this population.

What can we do?

A diversity of studies has been conducted to assess the effectiveness of different pharmacological and nonpharmacological interventions in the prevention of diabetes and its associated cardiovascular comorbidities in patients with prediabetes [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]. The clinical benefits of primary prevention interventions for DM2 have been demonstrated in patients with GI, but not with IFG alone or in patients diagnosed with prediabetes based on HbA1c levels.

Lifestyle and some antidiabetic drugs are effective in the prevention of DM. An analysis of recent studies on the effectiveness of lifestyle changes and pharmacological interventions is detailed below.

One of the latest studies on lifestyle changes is the European Diabetes Intervention Study [15], which is an extension of the Finnish study published in 2001 [9] and carried out in three European countries (Finland, United Kingdom and the Netherlands) to validate the findings of an initial Finnish study. After a 3.1 year follow-up, the incidence of DM decreased by 57% in the intervention group, as compared to the control group (hazard ratio [HR]: 0.42 [95%CI: 0.29–0.60], p<0.001). The incidence of DM was 65% lower in the participants who experienced a weight loss ≥ 5% 1 year after the intervention (HR: 0.35 [95%CI: 0.22–0.56], p<0.001). The incidence of diabetes further decreased in patients who maintained a constant weight loss of ≥5% for 2 and 3 years (79 and 89% reduction, respectively) [15]. It is worth mentioning an intervention study on lifestyle habits undertaken by the DE-PLAN-CAT group in Spain, which revealed a 36.5% reduction in the incidence of diabetes after an average follow-up of 4 years [16].

In relation to pharmacological interventions for the prevention of diabetes, the highest reduction in progression to diabetes was obtained in the ACT-NOW study with pioglitazone [17], which achieved a 72% reduction in the treatment group, as compared to placebo, although it was accompanied with a weight gain of 3.9 vs. 0.8 kg (p<0.001) and an increase in the incidence of peripheral edema (12.9 vs. 6.4%; p=0.007). The Diabetes Prevention Program (DPP) study had previously demonstrated that metformin (850 mg/BID) was effective in reducing prediabetes progression to diabetes by 31%, as compared to placebo. Of note, a 51% reduction was achieved through lifestyle changes [10]. Finally, liraglutide (a GLP-1 receptor agonist) has also been proven to significantly reduce progression to DM2 (2% in the treatment group vs. 6% in the control group) in a 3-year follow-up study [18].

In patients with morbid obesity, the most effective approach was bariatric surgery (odds ratio 0.16 [95%CI: 0.11–0.24]) [17].

Conclusive data on its effect on cardiovascular morbidity and mortality has not been obtained due to the short duration of studies. Acarbose has demonstrated to be effective in reducing cardiovascular complications in the STOP-NIDDM study [12], but this finding is based on only 48 events, and its results should be interpreted with caution since assessing its effects on CV morbidity and mortality was not within the scope of this study.

A recent meta-analysis revealed that the use of lifestyle changes and medication in adult patients with prediabetes reduced the incidence of DM2 by 39 and 36%, respectively. Nevertheless, medication is less effective in the long-term (its effects are not maintained over time), whereas the effects of lifestyle changes are maintained after the intervention [19].

This study confirms previous results, as weight loss was found to be the primary factor associated with progression to DM2. The risk of progression to DM2 decreased by 7% per lost kilogram which, in clinical terms, is very relevant.

The accusation of “prediabetes business”

There is solid evidence about the beneficial effects of lifestyle interventions. However, the main limitation of these interventions is patient’s difficulty in maintaining the recommended lifestyle changes; therefore, pharmacological prevention emerges as an alternative for some patients. Despite the data available on the effectiveness of pharmacological interventions in reducing the incidence of diabetes, the indication of hypoglycemic drugs for prediabetes has not yet been approved.

Some authors suggest that prediabetes is a diagnostic invention intended to make the population use medications unnecessarily [20]. This statement, however, is challenged by solid data. On the one hand, only ADA [21] clearly considers the possibility of using metformin in the prevention of DM2 in patients at a very high risk of developing diabetes, such as patients with GI (level of evidence A), IFG (E level), or HbA1c of 5.7–6.4% (E level), especially in the presence of a BMI >35 kg/m2, age < 60 years (higher efficacy within this range of age demonstrated in the DPP study) or in women with a previous diagnosis of gestational diabetes (A level of evidence). On the other hand, a study recently published in Diabetes Care revealed that the use of metformin in patients with prediabetes is <1%, which demonstrates that pharmacological interventions are not frequent in the prevention of DM2 [22].

Finally, after doubts were raised about the reality or relevance of prediabetes, research is increasingly focused on it as a real entity and its categorization into subtypes [23]. The different metabolic groups identified are associated with future complications associated with prediabetes, insulin resistance, future risk of DM2 and mortality. These subphenotypes might reflect key pathological features potentially associated with metabolic complications in the future. However, the purpose of phenotype identification is not to classify individual patients in clinical practice, but to provide guidance about the design of strategies for the prevention and management of cardiovascular and kidney diseases and DM2. We expect further news about this interesting condition to better understand prediabetes.


Corresponding author: Javier Escalada San Martín, Director, Department of Endocrinology and Nutrition, Clínica Universidad de Navarra, Avenida Pío XII, 36, 31008, Pamplona, Spain; Chair, Spanish Society of Endocrinology and Nutrition, Center for Biomedical Research Network on the Physiopathology of Obesity and Nutrition (CIBEROBN), Madrid, Spain; and Navarra Institute for Health Research (IdiSNA), Pamplona, Spain, E-mail:

  1. Article Note: The original article can be found here: https://doi.org/10.1515/almed-2021-0030.

  2. Research funding: None declared.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: Authors state no conflict of interest.

  5. Informed consent: Informed consent was obtained from all individuals included in this study.

  6. Ethical approval: The local Institutional Review Board deemed the study exempt from review.

References

1. American Diabetes Association. Classification and diagnosis of diabetes: standards of medical care in diabetes—2021. Diabetes Care 2021;44(1 Suppl):S15-33. https://doi.org/10.2337/dc21-S002.Search in Google Scholar PubMed

2. Soriguer, F, Goday, A, Bosch-Comas, A, Bordiú, E, Calle-Pascual, A, Carmena, R, et al.. Prevalence of diabetes mellitus and impaired glucose regulation in Spain: the Di@bet.es Study. Diabetologia 2012;55:88–93. https://doi.org/10.1007/s00125-011-2336-9.Search in Google Scholar PubMed PubMed Central

3. Santaguida, PL, Balion, C, Hunt, D, Morrison, K, Gerstein, H, Raina, P, et al.. Diagnosis, prognosis, and treatment of impaired glucose tolerance and impaired fasting glucose. Evid Rep Technol Assess 2005;128:1–11.Search in Google Scholar

4. Rooney, MR, Rawlings, AM, Pankow, JS, Echouffo Tcheugui, JB, Coresh, J, Sharrett, AR, et al.. Risk of progression to diabetes among older adults with prediabetes. JAMA Intern Med 2021;181:511–9. e208774. https://doi.org/10.1001/jamainternmed.2020.8774.Search in Google Scholar PubMed PubMed Central

5. Soriguer, F, Valdés, S, Tapia, MJ, Esteva, I, Ruiz de Adana, MS, Almaraz, MC, et al.. Validation of the FINDRISC (FINnish Diabetes RIsk SCore) for prediction of the risk of type 2 diabetes in a population of southern Spain. Pizarra Study. Med Clínica 2012;138:371–6. https://doi.org/10.1016/j.medcli.2011.05.025.Search in Google Scholar PubMed

6. Costa, B, Barrio, F, Piñol, JL, Cabré, JJ, Mundet, X, Sagarra, R, et al.. Shifting from glucose diagnosis to the new HbA1c diagnosis reduces the capability of the Finnish Diabetes Risk Score (FINDRISC) to screen for glucose abnormalities within a real-life primary healthcare preventive strategy. BMC Med 2013;11:45. https://doi.org/10.1186/1741-7015-11-45.Search in Google Scholar PubMed PubMed Central

7. Tuomilehto, J, Lindstrom, J, Eriksson, JG, Valle, TT, Hämäläinen, H, Ilanne-Parikka, P, et al.. Finnish Diabetes Prevention Study Group. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med 2001;344:1343–50. https://doi.org/10.1056/nejm200105033441801.Search in Google Scholar

8. Mata-Cases, M, Artola, S, Escalada, J, Ezkurra-Loyola, P, Ferrer-García, JC, Fornos, JA, et al.. Consensus on the detection and management of prediabetes. Consensus and Clinical Guidelines Working Group of the Spanish Diabetes Society. Rev Clin Esp 2015;215:117–29. https://doi.org/10.1016/j.rceng.2014.10.001.Search in Google Scholar

9. Gerstein, HC, Yusuf, S, Bosch, J, Pogue, J, Sheridan, P, Dinccag, N, et al.. Effect of rosiglitazone on the frequency of diabetes in patients with impaired glucose tolerance or impaired fasting glucose: a randomised controlled trial. Lancet 2006;368:1096–105. https://doi.org/10.1016/S0140-6736(06)69420-8.Search in Google Scholar PubMed

10. Knowler, WC, Barrett-Connor, E, Fowler, SE, Hamman, RF, Lachin, JM, Walker, EA, et al.. Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346:393–403. https://doi.org/10.1056/NEJMoa012512.Search in Google Scholar PubMed PubMed Central

11. Pan, XR, Li, GW, Hu, YH, Wang, JX, Yang, WY, An, ZX, et al.. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care 1997;20:537–44. https://doi.org/10.2337/diacare.20.4.537.Search in Google Scholar PubMed

12. Chiasson, JL, Josse, RG, Gomis, R, Hanefeld, M, Karasik, A, Laakso, M, et al.. STOP-NIDDM Trail Research Group. STOP-NIDDM Trial Research Group. Acarbose for prevention of type 2 diabetes mellitus: the STOP-NIDDM randomised trial. Lancet 2002;359:2072–77. https://doi.org/10.1016/s0140-6736(02)08905-5.Search in Google Scholar PubMed

13. Gillies, CL, Abrams, KR, Lambert, PC, Cooper, NJ, Sutton, AJ, Hsu, RT, et al.. Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis. BMJ 2007;334:299. https://doi.org/10.1136/bmj.39063.689375.55.Search in Google Scholar PubMed PubMed Central

14. Norris, SL, Zhang, X, Avenell, A, Gregg, E, Schmid, CH, Lau, J. Long-term non-pharmacological weight loss interventions for adults with prediabetes. Cochrane Database Syst Rev 2005;2:CD005270. https://doi.org/10.1002/14651858.CD005270.Search in Google Scholar PubMed

15. Penn, L, White, M, Lindström, J, den Boer, AT, Blaak, E, Eriksso, JG, et al.. Importance of weight loss maintenance and risk prediction in the prevention of type 2 diabetes: analysis of European Diabetes Prevention Study RCT. PloS One 2013;8:e57143. https://doi.org/10.1371/journal.pone.0057143.Search in Google Scholar PubMed PubMed Central

16. Costa, B, Barrio, F, Cabré, JJ, Piñol, JL, Cos, X, Solé, C, et al.. Delaying progression to type 2 diabetes among high-risk Spanish individuals is feasible in real-life primary healthcare settings using intensive lifestyle intervention. Diabetologia 2012;55:1319–28. https://doi.org/10.1007/s00125-012-2492-6.Search in Google Scholar PubMed

17. DeFronzo, RA, Tripathy, D, Schwenke, DC, Banerji, M, Bray, GA, Buchanan, TA, et al.. for the ACT NOW Study. Pioglitazone for diabetes prevention in impaired glucose tolerance. N Engl J Med 2011;364:1104–15. https://doi.org/10.1056/nejmoa1010949.Search in Google Scholar PubMed

18. le Roux, CW, Astrup, A, Fujioka, K, Greenway, F, Lau, DCW, Van Gaal, L, et al.. SCALE Obesity Prediabetes NN8022-1839 Study Group. 3 years of liraglutide versus placebo for type 2 diabetes risk reduction and weight management in individuals with prediabetes: a randomised, double-blind trial. Lancet 2017;389:1399–409. https://doi.org/10.1016/S0140-6736(17)30069-7.Search in Google Scholar PubMed

19. Haw, JS, Galaviz, K, Straus, AN, Kowalski, AJ, Magee, MJ, Weber, MB, et al.. Long-term sustainability of diabetes prevention approaches: a systematic review and meta-analysis of randomized clinical trials. JAMA Intern Med 2017;177:1808–17. https://doi.org/10.1001/jamainternmed.2017.6040.Search in Google Scholar PubMed PubMed Central

20. Piller, C. Dubious diagnosis. Science 2019;363:1026–31. https://doi.org/10.1126/science.363.6431.1026.Search in Google Scholar PubMed

21. American Diabetes Association. Prevention or delay of type 2 diabetes: standards of medical care in diabetes-2021. Diabetes Care 2021;44(1 Suppl):S34-9. https://doi.org/10.2337/dc21-S003.Search in Google Scholar PubMed

22. Tseng, E, Yeh, HC, Maruthur, N. Metformin use in prediabetes among U.S. Adults, 2005–2012. Diabetes Care 2017;40:887–93. https://doi.org/10.2337/dc16-1509.Search in Google Scholar PubMed PubMed Central

23. Wagner, R, Heni, M, Tabák, AG, Machann, J, Schick, F, Randrianarisoa, E, et al.. Pathophysiology-based subphenotyping of individuals at elevated risk for type 2 diabetes. Nat Med 2021;27:49–57. https://doi.org/10.1038/s41591-020-1116-9.Search in Google Scholar PubMed

Published Online: 2021-07-26

© 2021 Javier Escalada San Martín, published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Prediabetes: what are we talking about?
  4. Prediabetes ¿de qué estamos hablando?
  5. Review / Artículo de Revisión
  6. Update and clinical management of anti-DNA auto-antibodies
  7. Actualización y manejo clínico de los anticuerpos anti-ácido desoxirribonucleico
  8. ¿Debemos adaptarnos los laboratorios clínicos a la realidad del paciente con enfermedad renal crónica en la cuantificación de la hormona paratiroidea?
  9. Should clinical laboratories adapt to the reality of chronic kidney disease in the determination of parathyroid hormone?
  10. Measurement and clinical usefulness of bilirubin in liver disease
  11. Bilirrubina: Medición y utilidad clínica en la enfermedad hepática
  12. Guidelines and Recommendations / Guias y Recomendaciones
  13. Management of post-analytical processes in the clinical laboratory according to ISO 15189:2012. Considerations about the management of clinical samples, ensuring quality of post-analytical processes, and laboratory information management
  14. Gestión del proceso posanalítico en los laboratorios clínicos según los requisitos de la norma ISO 15189:2012. Consideraciones sobre la gestión de muestras clínicas, aseguramiento de la calidad en el proceso posanalítico y gestión de la información del laboratorio
  15. Original Article / Artículo Original
  16. A descriptive and validation study of a predictive model of severity of SARS-COV-2 infection
  17. Estudio descriptivo y validación de un modelo predictivo de severidad en pacientes con infección por SARS-CoV-2
  18. Real-world assessment of Fluorecare SARS-CoV-2 Spike Protein Test Kit
  19. Evaluación de la prueba Fluorecare de anticuerpos contra la proteína Spike del SARS-CoV-2 en la práctica real
  20. Estimation of change limits (deltacheck) in clinical laboratory
  21. Estimación de los límites de cambio (deltacheck) en el laboratorio clínico
  22. An opportunity to emphasize the relevance of laboratory medicine
  23. Guías de práctica clínica: oportunidad para visibilizar la importancia de la medicina del laboratorio
  24. Case Report / Caso Clínico
  25. A novel variant in the COL4A3 gene: etiology of Alport syndrome type 2 in a 38-year-old male with suspected hereditary kidney disease
  26. Nueva variante en el gen COL4A3: etiología de un síndrome de Alport tipo 2 en varón de 38 años con sospecha de nefritis hereditaria
Downloaded on 24.11.2025 from https://www.degruyterbrill.com/document/doi/10.1515/almed-2021-0034/html
Scroll to top button