BACKGROUND Studies have suggested that number of siblings and birth order is associated with obesity. However, studies combining these exposures are needed. This study aimed at investigating obesity in children and young adults in regard to different combinations of family size and birth order. METHODS Two cohorts selected from the general population were investigated: The Copenhagen School H...

The objective of this study is to examine the association between impulsivity and weight status in a large sample of the adult general population in France, and the influence of gender on this relationship. A total of 11,929 men and 39,114 women participating in the NutriNet-Santé cohort were selected in this cross-sectional analysis. The Barratt Impulsiveness Scale (BIS-11) was used to assess ...

Symbolic regression via genetic programming is a ƒexible approach to machine learning that does not require up-front speci€cation of model structure. However, traditional approaches to symbolic regression require the use of protected operators, which can lead to perverse model characteristics and poor generalisation. In this paper, we revisit interval arithmetic as one possible solution to allo...

Introduction: Since 2006, the number of seriously injured bicyclists in The Netherlands has increased significantly. This is also the case for sport cyclists. Over 80% of sport cyclists are male. We propose three factors that may contribute to involvement in sport cycling crashes among males: Bunch riding (cycling in a group), the inflow of sport cyclists with little experience and a competitiv...

BACKGROUND Most children in affluent developed countries do not meet basic physical activity recommendations. This study assessed primary caregiver knowledge of the UK recommendations on physical activity for children and examined the relationship between knowledge and components of parental support and modelling of physical activity. METHODS Data were from a large, community-based twin birth...

To detect the sensor faults of the plant with min-disturbance, a weighted least squares interval regression model is proposed. The output of the proposed model is an interval band which can resist the disturbance influence and give correct sensor fault alarm. Additionally, the time complexity of this model is low because only a set of linear equations can determine the parameters. The experimen...

The prediction of a response random interval-valued set from an explanatory one has been examined in previous developments. These developments have considered an interval arithmetic-based linear model between the random interval-valued sets and a least squares regression analysis. The least squares approach involves a generalized L2-metric between interval data; this metric weights squared dist...