Horse racing requires jockeys to weigh in prior to each competition, with failure automatically excluding the jockey from competition. As such, many jockeys frequently employ long- and short-term “wasting” weight-loss techniques that can be harmful to health. This study aimed to explore jockeys’ social norms and experiences regarding wasting and the effects of wasting on their mental health. Six professional jockeys with a minimum of 2 years professional riding experience were recruited from a range of stud-racing yards in Ireland. From individual participant interviews, an interpretative-phenomenological-analysis approach revealed four themes: “Day in, day out,” “Horse racing is my life,” “You just do what you have to do,” and “This is our world.” Themes were interpreted through social-identity theory, which highlighted how wasting is an acceptable in-group norm among jockeys, irrespective of relationship problems and mental health consequences. Recommendations are offered for intervening to support jockeys’ mental health.
Tanya McGuane, Stephen Shannon, Lee-Ann Sharp, Martin Dempster and Gavin Breslin
Matthew Pearce, Tom R.P. Bishop, Stephen Sharp, Kate Westgate, Michelle Venables, Nicholas J. Wareham and Søren Brage
Harmonization of data for pooled analysis relies on the principle of inferential equivalence between variables from different sources. Ideally, this is achieved using models of the direct relationship with gold standard criterion measures, but the necessary validation study data are often unavailable. This study examines an alternative method of network harmonization using indirect models. Starting methods were self-report or accelerometry, from which we derived indirect models of relationships with doubly labelled water (DLW)-based physical activity energy expenditure (PAEE) using sets of two bridge equations via one of three intermediate measures. Coefficients and performance of indirect models were compared to corresponding direct models (linear regression of DLW-based PAEE on starting methods). Indirect model beta coefficients were attenuated compared to direct model betas (10%–63%), narrowing the range of PAEE values; attenuation was greater when bridge equations were weak. Directly and indirectly harmonized models had similar error variance but most indirectly derived values were biased at group-level. Correlations with DLW-based PAEE were identical after harmonization using continuous linear but not categorical models. Wrist acceleration harmonized to DLW-based PAEE via combined accelerometry and heart rate sensing had the lowest error variance (24.5%) and non-significant mean bias 0.9 (95%CI: −1.6; 3.4) kJ·day−1·kg−1. Associations between PAEE and BMI were similar for directly and indirectly harmonized values, but most fell outside the confidence interval of the criterion PAEE-to-BMI association. Indirect models can be used for harmonization. Performance depends on the measurement properties of original data, variance explained by available bridge equations, and similarity of population characteristics.