The prevalence and correlates of pre-diabetes in middle- to older-aged Irish adults using three diagnostic methods
Kate Junker1, Claire M Buckley1, Seán R Millar1
1HRB Centre for Health and Diet Research, School of Public Health, University College Cork, Cork, Ireland.
Background And Objectives:
Type 2 diabetes is a leading cause of death and disability worldwide and pre-diabetes is a strong predictor of diabetes development. To date, studies estimating the prevalence of pre-diabetes in the Irish population are sparse and conflicting. Monitoring the prevalence of pre-diabetes and a knowledge of associated factors is required to inform policies and to prevent development of type 2 diabetes. Therefore, this research examined the prevalence and correlates of pre-diabetes in a sample of middle- to older-aged Irish adults using three different methods for diagnosis.
Materials And Methods:
The Mitchelstown Cohort Rescreen (2016/17) was a follow-up, cross-sectional study of the Mitchelstown Cohort Study (2010/11). 1,378 participants were recruited from a random sample of patients attending a single primary care centre. Pre-diabetes was defined using three diagnostic criteria: American Diabetes Association (ADA) glycated haemoglobin A1c (HbA1c) cut-offs between 5.7%-6.4% (39-46 mmol/mol), World Health Organization International Expert Committee (WHO-IEC) HbA1c cut-offs between 6.0%-6.4% (42-46 mmol/mol) and ADA fasting plasma glucose (FPG) cut-offs between 5.6-6.9 mmol/l. Univariate and multivariable logistic regression analyses were used to determine factors associated with pre-diabetes.
Results:
The prevalence of pre-diabetes was found to be 43.9% (95% CI: 41.2%─46.5%), 14.5% (95% CI: 12.7%─16.5%) and 15.8% (95% CI: 13.9%─17.8%) according to HbA1c ADA, HbA1c WHO-IEC and FPG ADA definitions, respectively. Depending on diagnostic method, factors associated with pre-diabetes in univariate analyses included sex, age, marital status, health rating, education and poor diet quality. In multivariable analysis, subjects classified by the FPG ADA pre-diabetes criterion displayed the least optimal metabolic profile defined by overweight and obesity (OR = 2.88, 95% CI: 1.53-5.43), hypertension (OR = 2.27, 95% CI: 1.51-3.40) and low high-density lipoprotein cholesterol concentrations (OR = 1.75, 95% CI: 1.07-2.87).
Conclusions:
The discordance between prevalence estimates according to method of diagnosis is concerning. A National Diabetes Prevention Programme is currently being developed in Ireland. Monitoring the prevalence of pre-diabetes over time will be important to assess the effectiveness of this programme. This study will inform national decision-makers on which definition of pre-diabetes to use for monitoring purposes.
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