title: Risk equations for the development of worsened glucose status and type 2 diabetes mellitus in a Swedish intervention program.
abstract: 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.
authors: Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå 901 85, SE, Sweden. anne.neumann@uniklinikum-dresden.de.
authors: Anne
authors: A
authors: Neumann
authors: Margareta
authors: M
authors: Norberg
authors: Olaf
authors: O
authors: Schoffer
authors: Fredrik
authors: F
authors: Norström
authors: Ingegerd
authors: I
authors: Johansson
authors: Stefanie J
authors: SJ
authors: Klug
authors: Lars
authors: L
authors: Lindholm
mesh_terms: D000328:Adult; D001786:Blood Glucose / Q000378:metabolism*; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology* / Q000517:prevention & control; D018450:Disease Progression; D005163:Factor Analysis, Statistical; D005260:Female; D005500:Follow-Up Studies; D018149:Glucose Intolerance / Q000503:physiopathology*; D005951:Glucose Tolerance Test; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011236:Prediabetic State / Q000503:physiopathology*; D018570:Risk Assessment; D012307:Risk Factors; D013548:Sweden
chemical_list: D001786:Blood Glucose