With evidence supporting the use of preventive interventions for prediabetes populations and the use of novel biomarkers to stratify the risk of progression there is a need to evaluate their cost-effectiveness across jurisdictions. Our aim is to summarise and assess the quality and validity of decision models and model-based economic evaluations of populations with prediabetes, evaluate their potential use for the assessment of novel prevention strategies and discuss the knowledge gaps, challenges and opportunities. We searched Medline, Embase, EconLit and NHS EED between 2000 and 2018 for studies reporting computer simulation models of the natural history of individuals with prediabetes and/or used decision models to evaluate the impact of treatment strategies on these populations. Data were extracted following PRISMA guidelines and assessed using modelling checklists. Two reviewers independently assessed 50% of the titles and abstracts to determine whether a full text review was needed. Of these, 10% was assessed by each reviewer to cross-reference the decision to proceed to full review. Using a standardised form, and double extraction, four reviewers each extracted 50% of identified studies. Twenty-nine published decision models that simulate prediabetes populations were identified. Studies showed large variations in the definition of prediabetes and model structure. The inclusion of complications in prediabetes (n=8) and type 2 diabetes (n=17) health states also varied. A minority of studies simulated annual changes in risk factors (glycaemia, HbA1c, blood pressure, BMI, lipids) as individuals progressed in the models (n=7) and accounted for heterogeneity amongst individuals with prediabetes (n=7). Current prediabetes decision models have considerable limitations in terms of their quality and validity and are not equipped to evaluate stratified strategies using novel biomarkers highlighting a clear need for more comprehensive prediabetes decision models. This article is protected by copyright. All rights reserved.

Six focus group discussions were conducted between March and April 2019 with Turkish (n = 24) and Moroccan (n = 20) women in the Netherlands, aged 30-60 years. Questions were based on an extended version of the Health Belief Model. Discussions were transcribed verbatim and thematically analysed.

Sufficient I intake is important for the synthesis of thyroid hormones, which play an important role in normal growth and development. Our aim was to estimate habitual I intake for the Dutch population and the risk of inadequate or excessive intakes. Further, we aimed to provide an insight into the dietary sources of I and the association with socio-demographic factors. Data from the Dutch National Food Consumption Survey 2007-2010 (n 3819; 7-69 years), and from the Dutch food and supplement composition tables were used to estimate habitual I intake with a calculation model. Contribution of food groups to I intake were computed and multiple linear regression was used to examine associations of intakes with socio-demographic factors. A total of ≤2 % of the population had an intake below the estimated average requirement or above the upper level. The main sources of I were bread containing iodised salt (39 %), dairy products (14 %) and non-alcoholic drinks (6 %). I intake (natural sources only, excluding iodised salt and supplements) was positively associated with (parental) education, which could at least partly be attributed to a higher consumption of dairy products. Among children, the consumption of bread, often containing iodised bakery salt, was positively associated with parental education. The I intake of the Dutch population (7-69 years) seems adequate, although it has decreased since the period before 2008. With the current effort to reduce salt intake and changing dietary patterns (i.e. less bread, more organic foods) it is important to keep a close track on the I status, important sources and potential risk groups.

Understanding which factors drive population densities of disease vectors is an important step in assessing disease risk. We tested the hypothesis that the density of ticks from the Ixodes ricinus complex, which are important vectors for tick-borne diseases, is determined by the density of deer, as adults of these ticks mainly feed on deer.