Muscle fiber-type distribution predicts weight gain and unfavorable left ventricular geometry: a 19 year follow-up study

BACKGROUND: Skeletal muscle consists of type-I (slow-twitch) and type-II (fast-twitch) fibers, with proportions highly variable between individuals and mostly determined by genetic factors. Cross-sectional studies have associated low percentage of type-I fibers (type-I%) with many cardiovascular risk factors. METHODS: We investigated whether baseline type-I% predicts left ventricular (LV) structure and function at 19-year follow-up, and if so, which are the strongest mediating factors. At baseline in 1984 muscle fiber-type distribution (by actomyosin ATPase staining) was studied in 63 healthy men (aged 32–58 years). The follow-up in 2003 included echocardiography, measurement of obesity related variables, physical activity and blood pressure. RESULTS: In the 40 men not using cardiovascular drugs at follow-up, low type-I% predicted higher heart rate, blood pressure, and LV fractional shortening suggesting increased sympathetic tone. Low type-I% predicted smaller LV chamber diameters (P ≤ 0.009) and greater relative wall thickness (P = 0.034) without increase in LV mass (concentric remodeling). This was explained by the association of type-I% with obesity related variables. Type-I% was an independent predictor of follow-up body fat percentage, waist/hip ratio, weight gain in adulthood, and physical activity (in all P ≤ 0.001). After including these risk factors in the regression models, weight gain was the strongest predictor of LV geometry explaining 64% of the variation in LV end-diastolic diameter, 72% in end-systolic diameter, and 53% in relative wall thickness. CONCLUSION: Low type-I% predicts obesity and weight gain especially in the mid-abdomen, and consequently unfavourable LV geometry indicating increased cardiovascular risk

Barriers to the uptake and use of feedback in the context of summative assessment

Despite calls for feedback to be incorporated in all assessments, a dichotomy exists between formative and summative assessments. When feedback is provided in a summative context, it is not always used effectively by learners. In this study we explored the reasons for this. We conducted individual interviews with 17 students who had recently received web based feedback following a summative assessment. Constant comparative analysis was conducted for recurring themes. The summative assessment culture, with a focus on avoiding failure, was a dominant and negative influence on the use of feedback. Strong emotions were prevalent throughout the period of assessment and feedback, which reinforced the focus on the need to pass, rather than excel. These affective factors were heightened by interactions with others. The influence of prior learning experiences affected expectations about achievement and the need to use feedback. The summative assessment and subsequent feedback appeared disconnected from future clinical workplace learning. Socio-cultural influences and barriers to feedback need to be understood before attempting to provide feedback after all assessments. A move away from the summative assessment culture may be needed in order to maximise the learning potential of assessments