Risk equations for the development of worsened glucose status and type 2 diabetes mellitus in a Swedish intervention program
2013 (English)In: BMC Public Health, ISSN 1471-2458, E-ISSN 1471-2458, Vol. 13, 1014Article in journal (Refereed) Published
Background: Several studies investigated transitions and risk factors from impaired glucose tolerance (IGT) to type 2 diabetes mellitus (T2D). However, there is a lack of information on the probabilities to transit from normal glucose tolerance (NGT) to different pre-diabetic states and from these states to T2D. The objective of our study is to estimate these risk equations and to quantify the influence of single or combined risk factors on these transition probabilities. Methods: Individuals who participated in the VIP program twice, having the first examination at ages 30, 40 or 50 years of age between 1990 and 1999 and the second examination 10 years later were included in the analysis. Participants were grouped into five groups: NGT, impaired fasting glucose (IFG), IGT, IFG&IGT or T2D. Fourteen potential risk factors for the development of a worse glucose state (pre-diabetes or T2D) were investigated: sex, age, education, perceived health, triglyceride, blood pressure, BMI, smoking, physical activity, snus, alcohol, nutrition and family history. Analysis was conducted in two steps. Firstly, factor analysis was used to find candidate variables; and secondly, logistic regression was employed to quantify the influence of the candidate variables. Bootstrap estimations validated the models. Results: In total, 29 937 individuals were included in the analysis. Alcohol and perceived health were excluded due to the results of the factor analysis and the logistic regression respectively. Six risk equations indicating different impacts of different risk factors on the transition to a worse glucose state were estimated and validated. The impact of each risk factor depended on the starting or ending pre-diabetes state. High levels of triglyceride, hypertension and high BMI were the strongest risk factors to transit to a worsened glucose state. Conclusions: The equations could be used to identify individuals with increased risk to develop any of the three pre-diabetic states or T2D and to adapt prevention strategies.
Place, publisher, year, edition, pages
BioMed Central, 2013. Vol. 13, 1014
Diabetes mellitus, type 2, Pre-diabetic state, Prevention & control, Risk factors, Glucose, Sweden, Logistic models, Factor analysis, statistical, Early intervention, Life style
Public Health, Global Health, Social Medicine and Epidemiology
IdentifiersURN: urn:nbn:se:umu:diva-85814DOI: 10.1186/1471-2458-13-1014ISI: 000329290200002OAI: oai:DiVA.org:umu-85814DiVA: diva2:695865