Gestational diabetes mellitus is associated with increased risk of adverse perinatal outcomes. Despite this relationship, ways to prevent gestational diabetes mellitus remain unproven. A recent multicenter pilot study, which was co-authored by Judith Jelsma and Mireille van Poppel from our group, compared the impact of three lifestyle interventions on gestational diabetes mellitus risk; healthy eating [HE], physical activity [PA], and both HE and PA [HE+PA].

The relationship between physical activity and academic performance is a hot topic in contemporary PA literature. Does PA lead to an increased ability to study and acquire cognitive skills? The discussion is still open, and evidence for an acute effect of physical activity on cognitive performance within the school setting is limited. We set out to provide previously untold arguments in favour of PA. The purpose of this study was to gain insight into acute effects of a short physical activity bout on selective attention in primary school children, specifically in the school setting.

Just recently the BJSM published the Consensus Statement from the first Economics of Physical Inactivity Consensus (EPIC) Conference. This consensus summarises the outcome of discussions as they apply to the health and economic burden of physical inactivity, held at the EPIC Conference in 2011 Vancouver. Specifically, the consensus (1) details existing evidence on effective physical inactivity prevention strategies; (2) introduces economic evaluation and its role in health policy decisions; (3) discusses key challenges in establishing and building health economic evaluation evidence (including accurate and reliable costs and clinical outcome measurement) and (4) provides insight into interpretation of economic evaluations in this critically important field.

This manuscript describes a population based cross-sectional study derived from the HUNT study in Norway. The HUNT study measured in a sample 48,882 adults aged 20 years or older, amongst other outcomes, waist circumference, BMI, total cholesterol, HDL cholesterol, blood pressure, non-fasting glucose, gamma glutamyltransferase (GGT) and triglycerides. Adjusted multiple regression models were used to test for associations between these biomarkers and self-reported total sitting time, TV-viewing and leisure-time computer use.