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Aims: Exercise interventions positively affect numerous cardiometabolic risk factors. To better evaluate the health effects of exercise training, it may be more appropriate to evaluate risk factors together. The Metabolic Syndrome Severity Score (MetSSS) is a composite score representing cardiometabolic risk. Purpose: To evaluate the relationships between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS in a heterogenous sample of people with complex chronic disease. Material and Methods: Fifty-three people with kidney or liver disease and at least one feature of the metabolic syndrome (MetS) were included. Pearson correlations were conducted between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS. Linear regressions were performed for multi-level categorical variables. Independent variables with an association with MetSSS (P ≤ 0.2) were included in a multiple regression analysis. Results: The 6-minute walk test (6MWT) distance was inversely and independently associated with MetSSS [standardized beta coefficient (β) = −0.31, P = 0.04]. No relationship was found between MetSSS and physical activity or neuromuscular fitness. Mean 6MWT in the highest tertile was 550 m (range: 505–620 m) and 346 m (range: 233–408 m) in the lowest. The analysis showed a medium–large between-group effect for the difference in MetSSS for the lowest and highest tertile of 6MWT [Eta squared (η2) = 0.16, P = 0.01]. Conclusions: Exercise capacity was inversely and independently associated with MetSSS in people with complex chronic disease. Clinical trials with exercise interventions are needed to further investigate if improvements in exercise capacity result in clinically significant changes in the MetSSS. [ABSTRACT FROM AUTHOR]

Background: Digital food records offer efficiencies in collecting and assessing dietary information remotely; however, research into factors impacting their translation into clinical settings is limited., Methods: The study examined factors that may impact the integration of digital food records into clinical dietetic practice by assessing (1) the source and rate of data errors received, (2) the impact of dietitian-adjusted data on dietary variables and (3) the acceptance of use in a complex chronic condition cohort. Adults from specialist clinics enroled in a randomised controlled feasibility trial participated. Participants recorded their dietary intake using a mobile food diary application (Research Food diary, Xyris Software Pty Ltd.); it was analysed via electronic nutrition analysis software (FoodWorks, Xyris Software Pty Ltd.). Records were verified and corrected by a dietitian. Dietary variables assessed before (participant-unadjusted data) and after (dietitian-adjusted data) were compared by the Wilcoxon signed-rank test, Bland-Altman and Passing-Bablok analysis. Surveys and Interviews assessed participants'; acceptance of the mobile application's usability., Results: Errors appeared in 93% of records. Dietitian-adjusted median data were higher for most variables compared to participant-unadjusted median data (p < 0.05, median changes between 0.0% and 64.7%) of 59 participant records (median age 51 years, interquartile range 38-58). There was poor agreement between participant-unadjusted and dietitian-adjusted data for some dietary variables. Sixty-four percent surveyed (n = 32/50) found the app easy to use, whereas 29 interviews provided insights into facilitators and challenges of use., Conclusions: Significant barriers to integrating digital food records into clinical settings exist requiring dietitian adjustment to correct errors which has major implications for estimates of diet quality and intake., (© 2024 The British Dietetic Association Ltd.)