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This study aimed to evaluate the risk of eating disorders, psychological distress, and health-related quality of life (HRQoL) in people with class 3 obesity (body mass index (BMI) ≥ 40 kg/m2), and the effect of multidisciplinary weight management over 12 months. This retrospective cohort study included all adults with class 3 obesity who enrolled in a weight management program from March 2018 to December 2019. Questionnaires included the Eating Disorder Examination Questionnaire Short (EDE-QS), Kessler Psychological Distress Scale (K10), and 36-Item Short Form Survey (SF-36) for HRQoL. Physical and Mental Component Summary scores (PCS and MCS) were derived from the SF-36. Of 169 participants who completed 12 months in the program, 65.7% (n = 111) completed questionnaires at baseline and 12 months, with 6.0 ± 6.8% weight loss over this period. Compared to baseline, there was significant improvement at 12 months in EDE-QS (15.7 ± 6.6 vs. 13.6 ± 6.2, p = 0.002), K10 (25.7 ± 9.7 vs. 21.2 ± 9.4, p < 0.001), PCS (29.4 ± 10.1 vs. 36.1 ± 10.9, p < 0.001), and MCS scores (40.2 ± 12.4 vs. 44.0 ± 13.4, p = 0.001). All, apart from EDE-QS scores, remained significant after adjusting for weight change. This study highlights the importance of multidisciplinary management in people with class 3 obesity to help reduce eating disorder risk and psychological distress, and improve HRQoL, in addition to weight loss.

Phenotyping trials may not take into account sufficient spatial context to infer quantitative disease resistance of recommended varieties in commercial production settings. Recent ecological theory—the dispersal scaling hypothesis—provides evidence that host heterogeneity and scale of host heterogeneity interact in a predictable and straightforward manner to produce a unimodal (“humpbacked”) distribution of epidemic outcomes. This suggests that the intrinsic artificiality (scale and design) of experimental set-ups may lead to spurious conclusions regarding the resistance of selected elite cultivars, due to the failure of experimental efforts to accurately represent disease pressure in real agricultural situations. In this model-based study we investigate the interaction of host heterogeneity and scale as a confounding factor in the inference from ex-situ assessment of quantitative disease resistance to commercial production settings. We use standard modelling approaches in plant disease epidemiology and a number of different agronomic scenarios. Model results revealed that the interaction of heterogeneity and scale is a determinant of relative varietal performance under epidemic conditions. This is a previously unreported phenomenon that could provide a new basis for informing the design of future phenotyping platforms, and optimising the scale at which quantitative disease resistance is assessed.