Risk equations for the development of worsened glucose status and type 2 diabetes mellitus in a Swedish intervention program

Abstract

BackgroundSeveral 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.MethodsIndividuals 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.ResultsIn 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.ConclusionsThe 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.

The cost-effectiveness of interventions targeting lifestyle change for the prevention of diabetes in a Swedish primary care and community based prevention program

“…Hence, all hypothetical persons must have developed any of the three pre-diabetic states before the development of T2D. The transition probabilities in this study were extracted from a previous study based on the Västerbotten Intervention Program (VIP) [22] and they depend on the following risk factors: sex, age, education, triglyceride, blood pressure, body mass index (BMI), smoking, physical activity, snus use, nutrition, marital status, family history of T2D and self-reported health status (Table 1). In the model, all those risk factors could be adjusted according to the lifestyle of the individual.…”

“…In the model, all those risk factors could be adjusted according to the lifestyle of the individual. The transition probabilities were estimated based on the logistic regression of transitions in the VIP by estimating the risk of changing to a different glucose state depending on a range of risk factors [22] (Table 2). …”

“…The characteristics of the population without the intervention were based on the distribution of the characteristics in the VIP population at first examination with any of the pre-diabetic states [22] (Table 3). The success of the intervention was defined by changes in three characteristics, i.e., BMI, physical activity and nutrition, at the starting year: a weight reduction of 5% [29], an increase in physical activity by 13% [30] and an increase by 10% of the proportion of individuals consuming at least five portions of fruits and vegetables per day [6].…”

“…In the starting year, 66.2, 27.2 and 6.6% of the hypothetical persons in the model had IFG, IGT or IFG and IGT, respectively, based on the distribution of participants at first examination in the VIP in the years between 1990 and 1999 [22]. …”

“…However, no study to our knowledge has estimated the cost-effectiveness of T2D prevention strategies from a population-based perspective, including healthy individuals and also considering IFG and IGT as two distinct pre-diabetic states. Previous research has, nonetheless, shown that IFG and IGT are different regarding risk of developing a worsened health state and quality of life [22–25]. Norris and colleagues consequently underlined that further research is needed to define the duration of the pre-diabetes phase and to identify measurable risk factors for progression to T2D and its complications [26].…”