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Risk Factors for the Progression or Regression to Diabetes or Normoglycaemia for Men with Impaired Fasting Glucose

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journal contribution
posted on 2025-10-29, 05:11 authored by Jacob W Harland, Natalie HydeNatalie Hyde, Zoe Shih-Jung Liu, Courtney SwintonCourtney Swinton, Briana RandallBriana Randall, Mark A Kotowicz, Julie PascoJulie Pasco, Kara L Holloway-Kew
AimsReporting of impaired fasting glucose (IFG) prevalence and risk factors for progression to diabetes differs between studies, in part, due to the use of multiple definitions of the condition. We aimed to determine the prevalence of diabetes and IFG in men and identify risk factors for the progression to diabetes and regression to normoglycaemia.Materials and MethodsParticipants were from the Geelong Osteoporosis Study. Diabetes was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L, self‐report of diabetes and/or use of antihyperglycaemic medication. IFG was defined using both American Diabetes Association (IFG‐ADA: FPG 5.6–6.9 mmol/L) and World Health Organisation (IFG‐WHO: FPG 6.1–6.9 mmol/L) criteria. Prevalence of hyperglycaemia at baseline (2001–2006, 1170 men, 20–97 years) was age‐standardised to the 2006 Australian population. Multivariable logistic regression models (n = 416) were used to identify risk factors for the progression to diabetes and regression to normoglycaemia over 15 years.ResultsAge‐standardised prevalence of IFG‐ADA was 18.2% (95% CI 15.7–20.7), 6.2% for IFG‐WHO (95% CI 4.8–7.6) and 7.3% for diabetes (95% CI 5.8–8.8). Higher FPG, glycated haemoglobin, age, body fat percent and lower HDL cholesterol were associated with progression to diabetes, whereas younger age and higher HDL cholesterol were associated with regression. A 1.0 mmol/L increase in FPG resulted in a sixfold greater chance of progression to diabetes over follow‐up (OR 6.44, 95% CI 2.97–13.94; p < 0.001). A prediction model containing age, FPG, HDL cholesterol and HbA1c predicted an optimal FPG cut point for progression of 5.3 mmol/L.ConclusionThis study reports cut points for predicting progression to diabetes that align with the ADA classification of IFG. These data may support future work investigating diabetes prevention strategies.

Funding

Funder: National Health and Medical Research Council | Grant ID: 628582

Funder: National Health and Medical Research Council | Grant ID: 299831

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Open access

  • Yes

Language

eng

Editor/Contributor(s)

Southerland J

Journal

Journal Of Diabetes Research

Volume

2025

Article number

9926306

Pagination

1-13

ISSN

2314-6745

eISSN

2314-6753

Issue

1

Publisher

Hindawi

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