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This study compared the effects of a low-fat vegan diet to those of a portion-controlled diet in people with type 1 diabetes. Over 12 weeks, the average total daily dose of insulin decreased significantly and insulin sensitivity increased significantly in the vegan group, while no significant changes were observed in the group receiving the portion-controlled diet. Total and LDL cholesterol decreased in the vegan group, as did the ratio of blood urea nitrogen to creatinine. A1C decreased in both groups. These findings suggest that a low-fat vegan diet may yield improvements in insulin sensitivity, insulin requirements, glycemic control, and markers of cardiovascular and renal health compared with a portion-controlled diet in people with type 1 diabetes.
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Brain magnetic resonance imaging frequently reveals white matter lesions (WMLs) in older adults. They are often associated with cognitive impairment and risk of dementia. Given the continuous search for the optimal segmentation algorithm, we broke down this question by exploring whether the output of algorithms frequently used might be biased by the presence of different influencing factors. We studied the impact of age, sex, blood glucose levels, diabetes, systolic blood pressure and hypertension on automatic WML segmentation algorithms. We evaluated three widely used algorithms (BIANCA, LPA and LGA) using the population-based 1000BRAINS cohort (N = 1166, aged 18-87, 523 females, 643 males). We analysed two main aspects. Firstly, we examined whether training data (TD) characteristics influenced WML estimations, assessing the impact of relevant factors in the TD. Secondly, algorithm's output and performance within selected subgroups defined by these factors were assessed. Results revealed that BIANCA's WML estimations are influenced by the characteristics present in the TD. LPA and LGA consistently provided lower WML estimations compared to BIANCA's output when tested on participants under 67 years of age without risk cardiovascular factors. Notably, LPA and LGA showed reduced accuracy for these participants. However, LPA and LGA showed better performance for older participants presenting cardiovascular risk factors. Results suggest that incorporating comprehensive cohort factors like diverse age, sex and participants with and without hypertension in the TD could enhance WML-based analyses and mitigate potential sources of bias. LPA and LGA are a fast and valid option for older participants with cardiovascular risk factors.
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Objective: Evidence suggests that changes in dietary advanced glycation end-products (AGEs) may influence body weight, but the effects of different dietary patterns remain to be explored.The aim of this study was to compare the effects of a Mediterranean and a low-fat vegan diet on dietary AGEs and test their association with body weight. Materials and methods: In this randomized cross-over trial, 62 overweight adults were assigned to a Mediterranean or a low-fat vegan diet for 16-week periods in random order, separated by a 4-week washout. Body weight was the primary outcome. Three-day diet records were analyzed using the Nutrition Data System for Research software and dietary AGEs were estimated, using an established database. Statistical approaches appropriate for crossover trials were implemented. Results: Dietary AGEs decreased by 73%, that is, by 9,413 kilounits AGE/day (95% -10,869 to -7,957); p < 0.001, compared with no change on the Mediterranean diet (treatment effect -10,303 kilounits AGE/day [95% CI -13,090 to -7,516]; p < 0.001). The participants lost 6.0 kg on average on the vegan diet, compared with no change on the Mediterranean diet (treatment effect -6.0 kg [95% CI -7.5 to -4.5]; p < 0.001). Changes in dietary AGEs correlated with changes in body weight (r = +0.47; p < 0.001) and remained significant after adjustment for total energy intake (r = +0.39; p = 0.003). Conclusion: Dietary AGEs did not change on the Mediterranean diet but decreased on a low-fat vegan diet, and this decrease was associated with changes in body weight, independent of energy intake. Clinical trial registration: https://clinicaltrials.gov/, identifier NCT03698955.