Skip to main content

Advertisement

Log in

Prediabetes defined by HbA1c and by fasting glucose: differences in risk factors and prevalence

  • Original Article
  • Published:
Acta Diabetologica Aims and scope Submit manuscript

Abstract

Aims

To investigate, in a sample of nondiabetic adults from a Spanish community, the differences between prediabetes as defined by HbA1c (“H-prediabetes”) and by fasting plasma glucose (FPG) (“F-prediabetes”) in regard to prevalence and the influence of potential risk factors, adjusting the latter for confounders.

Methods

A total of 1328 nondiabetic participants aged ≥ 18 years were classified as normoglycemic, H-prediabetic [HbA1c 5.7–6.4% (39–47 mmol/mol)] or F-prediabetic (FPG 5.6–6.9 mmol/L). Multivariable analyses were used to compare the impacts of risk factors on the prevalence of H-prediabetes, F-prediabetes and their conjunctive and disjunctive combinations (“HaF-prediabetes” and “HoF-prediabetes,” respectively).

Results

Some 29.9% of participants were HoF-prediabetic, 21.7% H-prediabetic, 16.3% F-prediabetic and only 8.1% HaF-prediabetic. Whatever the definition of prediabetes, increasing age, fasting insulin and LDL cholesterol were each a risk factor after adjustment for all other variables. Increasing BMI and decreasing mean corpuscular hemoglobin (MCH) were additional risk factors for H-prediabetes; male sex and increasing uric acid for F-prediabetes and increasing BMI for HaF-prediabetes. The participants satisfying the compound condition “hypertension or hyperlipidemia or obesity or hyperuricemia” (59.9% of the whole study group) included 83.1% of all subjects with HoF-prediabetes.

Conclusions

In this population, the most sensitive risk factor for detection of prediabetes was age, followed by fasting insulin, LDL cholesterol, BMI, MCH, male sex and uric acid, with differences depending on the definition of prediabetes. MCH, an indirect measure of erythrocyte survival, significantly influences the prevalence of HbA1c-defined prediabetes. This study suggests that screening of individuals with selected risk factors may identify a high proportion of prediabetic persons.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Abbreviations

ADA:

American Diabetes Association

AEGIS:

The A Estrada Glycation and Inflammation Study

CI:

Confidence interval

FPG:

Fasting plasma glucose

F-prediabetes:

Prediabetes according to the FPG criterion (FPG 5.6–6.9 mmol/L)

GMA drugs:

Pharmaceutical drugs affecting glucose metabolism

HbA1c :

Glycated hemoglobin

H-prediabetes:

Prediabetes according to the HbA1c criterion [HbA1c 39–46 mmol/mol (5.7–6.4%)]

HaF-prediabetes:

Prediabetes according to both the FPG and HbA1c criteria

HoF-prediabetes:

Prediabetes according either the HbA1c or the FPG criterion, or both

IFG:

Impaired fasting glucose

OGTT:

Oral glucose tolerance test

References

  1. American Diabetes Association (2010) Diagnosis and classification of diabetes mellitus. Diabetes Care 33(Suppl. 1):S62–S69

    Article  Google Scholar 

  2. Inzucchi SE (2012) Diagnosis of diabetes. N Engl J Med 367:542–550

    Article  CAS  Google Scholar 

  3. American Diabetes Association (2017) Classification and diagnosis of diabetes mellitus. Secion 2. In Standards of Medical Care in Diabetes-2017. Diabetes Care 40(1):S11–S24

    Article  Google Scholar 

  4. Diabetes Prevention Program Research Group (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346:393–403

    Article  Google Scholar 

  5. Goldstein DE, Little RR, Lorenz RA et al (2004) Tests of glycemia in diabetes. Diabetes Care 27:1761–1773

    Article  Google Scholar 

  6. Sacks DB (2011) A1C versus glucose testing: a comparison. Diabetes Care 34:518–523

    Article  Google Scholar 

  7. Warren B, Pankow JS, Matsushita K et al (2017) Comparative prognostic performance of definitions of prediabetes: a prospective cohort analysis of the Atherosclerosis Risk in Communities (ARIC) study. Lancet Diabetes Endocrinol 5(1):34–42

    Article  Google Scholar 

  8. Mann DM, Carson AP, Shimbo D, Fonseca V, Fox CS, Muntner P (2010) Impact of A1C screening criterion on the diagnosis of pre-diabetes among U.S. adults. Diabetes Care 33:2190–2195

    Article  Google Scholar 

  9. Olson DE, Rhee MK, Herrick K, Ziemer DC, Twombly JG, Phillips LS (2010) Screening for diabetes and pre-diabetes with proposed HbA1C-based diagnostic criteria. Diabetes Care 33:2184–2189

    Article  Google Scholar 

  10. James C, Bullard KM, Rolka DB et al (2011) Implications of alternative definitions of prediabetes for prevalence in US adults. Diabetes Care 34:387–391

    Article  Google Scholar 

  11. Nowicka P, Santoro N, Liu H et al (2011) Utility of hemoglobin HbA1C for diagnosing prediabetes and diabetes in obese children and adolescents. Diabetes Care 34:1306–1311

    Article  CAS  Google Scholar 

  12. Pinelli NR, Jantz AS, Martin ET, Jaber LA (2011) Sensitivity and specificity of glycated haemoglobin as a diagnostic test for diabetes and prediabetes in Arabs. J Clin Endocrinol Metab 96:E1680–E1683

    Article  CAS  Google Scholar 

  13. Saukkonen T, Cederberg H, Jokelainen J et al (2011) Limited overlap between intermediate hyperglycemia as defined by A1C 5.7–6.4%, impaired fasting glucose, and impaired glucose tolerance. Diabetes Care 34(10):2314–2316

    Article  CAS  Google Scholar 

  14. Tankova T, Chakarova N, Dakovska L, Atanassova I (2012) Assessment of HbA1c as a diagnostic tool in diabetes and prediabetes. Acta Diabetol 49:371–378

    Article  CAS  Google Scholar 

  15. Sumner AE, Duong MT, Aldana PC et al (2016) A1C combined with glycated albumin improves detection of prediabetes in Africans: the Africans in America Study. Diabetes Care 39:271–277

    CAS  PubMed  Google Scholar 

  16. Heianza Y, Hara S, Arase Y et al (2011) HbA1c 5.7–6.4% and impaired fasting plasma glucose for diagnosis of prediabetes and risk of progression to diabetes in Japan (TOPICS 3): a longitudinal cohort study. Lancet 378:147–155

    Article  CAS  Google Scholar 

  17. Lipska KJ, Inzucchi SE, Van Ness PH et al (2013) Elevated HbA1c and fasting plasma glucose in predicting diabetes incidence among older adults. Are two better than one? Diabetes Care 36:3923–3929

    Article  CAS  Google Scholar 

  18. Eastwood SV, Tillin T, Sattar N, Forouhi NG, Hughes AD, Chaturvedi N (2015) Associations between prediabetes, by three different diagnostic criteria, and incident CVD differ in south Asians and Europeans. Diabetes Care 38:2325–2332

    Article  CAS  Google Scholar 

  19. Diabetes Prevention Program Research Group (2015) HbA1c as a predictor of diabetes and as an outcome in the diabetes prevention program: a randomized clinical trial. Diabetes Care 38:51–58

    Article  Google Scholar 

  20. Anjana RM, Shanthi Rani CS, Deepa M et al (2015) Incidence of diabetes and prediabetes and predictors of progression among Asian Indians: 10-year follow-up of the Chennai Urban Rural Epidemiology Study (CURES). Diabetes Care 38:1441–1448

    Article  Google Scholar 

  21. Gude F, Díaz-Vidal P, Rúa-Pérez C et al (2017) Glycaemic variability and its association with demographics and lifestyles in a general adult population. J Diabetes Sci Technol 11:780–790

    Article  CAS  Google Scholar 

  22. Hoelzel W, Weykamp C, Jeppsson JO et al (2004) IFCC reference system for measurement of haemoglobin HbA 1C in human blood and the National Standardization Schemes in the United States, Japan, and Sweden: a method-comparison study. Clin Chem 50:166–174

    Article  CAS  Google Scholar 

  23. Lipska KJ, De Reheneire N, Van Ness PT et al (2010) Identifying dysglycaemic states in older adults: implications of the emerging use of haemoglobin HbA1c. J Clin Endocrinol Metab 95:5289–5295

    Article  CAS  Google Scholar 

  24. Mostafa SA, Davies MJ, Webb D et al (2010) The potential impact of using glycated haemoglobin as the preferred diagnostic tool for detecting type 2 diabetes mellitus. Diabet Med 27:762–769

    Article  CAS  Google Scholar 

  25. Cosson E, Chiheb S, Cussac-Pillegand C et al (2013) Haemoglobin glycation may partly explain the discordance between HbA1c measurement and oral glucose tolerance test to diagnose dysglycaemia in overweight/obese subjects. Diabetes Metab 39:118–125

    Article  CAS  Google Scholar 

  26. Li J, Ma H, Na L et al (2015) Increased Hemoglobin A1c threshold for prediabetes remarkably improving the agreement between A1c and oral glucose tolerance test criteria in obese population. J Clin Endocrinol Metab 100:1997–2005

    Article  CAS  Google Scholar 

  27. Rosella LC, Lebenbaum M, Fitzpatrick T, Zuk A, Booth GL (2015) The prevalence of undiagnosed and prediabetes diabetes in Canada (2007–2011) according to fasting plasma glucose and HbA1c screening criteria. Diabetes Care 38:1299–1305

    Article  CAS  Google Scholar 

  28. Ho-Pham LT, Do TT, Campbell LV, Nguyen TV (2016) HbA1c-based classification reveals epidemic of diabetes and prediabetes in Vietnam. Diabetes Care 39:e93–e94

    Article  Google Scholar 

  29. Hashimoto Y, Futamura A, Ikushima M (1995) Effect of aging on HbA1c in a working male Japanese population. Diabetes Care 18:1337–1340

    Article  CAS  Google Scholar 

  30. Nuttall QF (1999) Effect of age on percentage of hemoglobin A1c and the percentage of total glycohemoglobin in non-diabetic persons. J Lab Clin Med 134:451–453

    Article  CAS  Google Scholar 

  31. Pani LN, Korenda L, Meigs JB et al (2008) Effect of aging on A1C levels in individuals without diabetes. Evidence from the Framingham offspring study and the National Health and Nutrition Examination Survey 2001–2004. Diabetes Care 31:1991–1996

    Article  Google Scholar 

  32. Selvin E, Zhu H, Brancati FL (2009) Elevated A1C in adults without a history of diabetes in the U.S. Diabetes Care 32:828–833

    Article  Google Scholar 

  33. Rodriguez-Segade S, Rodriguez Garcia J, Garcia-Lopez JM et al (2016) Impact of mean cell hemoglobin on HbA1c-defined glycemia status. Clin Chem 62:1570–1578

    Article  CAS  Google Scholar 

  34. Lorenzo C, Wagenknecht LE, Hanley AJG, Rewers MJ, Karter AJ, Haffner SM (2010) A1C between 5.7 and 6.4% as a marker for identifying pre-diabetes, insulin sensitivity and secretion, and cardiovascular risk factors. Diabetes Care 33:2104–2109

    Article  CAS  Google Scholar 

  35. International Expert Committee (2009) International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 32:1327–1334

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank the people of the northwest-Spanish municipality of A Estrada who agreed to participate in this study.

Funding

This research project was supported by Spain´s Carlos III Institute of Health through research Grants PI16/01395, PI13/02594 and PI11/02219, and through networking grants in relation to its Preventive Activity & Health Promotion Research Network (RD12/0005/0007 and RD16/0007/0006) and Addictive Disorders Network (RD16/0017/0018), in all cases with cofunding from FEDER funds and by a grant from the Xunta de Galicia in relation to its INBIOEST network (ED341D R2016/032).

Author information

Authors and Affiliations

Authors

Contributions

Dr. Santiago Rodriguez-Segade is the guarantor of this work and, as such, had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. SRS designed, researched and wrote the manuscript. JR, LSP, JGJ, MPC JMGL, MAS, ALQ and FG research data and contributed to discussion. FC contributed to discussion, edited the manuscript and made artwork. The final version of the manuscript was approved by all authors.

Corresponding author

Correspondence to Santiago Rodriguez-Segade.

Ethics declarations

Conflict of interest

The authors declare that there is no duality of interest associated with this manuscript.

Ethical approval

The study was reviewed and approved by the clinical research ethics committee of Galicia, Spain (CEIC 2012-025) and conformed with the current Helsinki Declaration.

Informed consent

Written informed consent was obtained from each participant.

Additional information

Managed by Massimo Porta.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 35 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rodriguez-Segade, S., Rodriguez, J., Camiña, F. et al. Prediabetes defined by HbA1c and by fasting glucose: differences in risk factors and prevalence. Acta Diabetol 56, 1023–1030 (2019). https://doi.org/10.1007/s00592-019-01342-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00592-019-01342-5

Keywords

Navigation