Hana Kahleova, Tatiana Znayenko-Miller, Arathi Jayaraman, Giulianna Motoa, Laura Chiavaroli, Richard Holubkov, Neal D Barnard
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引用次数: 0
Abstract
Low-fat plant-based diets cause weight loss in clinical trials. However, many foods are highly processed, raising the question as to their effect on body weight. This secondary analysis assessed the associations between changes in processed food intake and weight loss in 244 overweight adults randomly assigned to a vegan (n = 122) or control group (n = 122) for 16 weeks. Three-day dietary records were analyzed using the NOVA system, which categorizes foods from 1 to 4, based on degree of processing. A repeated measure ANOVA, Pearson correlations, and a multivariate regression model were used for statistical analysis. The consumption of animal foods in categories 1-4 decreased in the vegan group, compared with the control group. Body weight decreased in the vegan group (treatment effect - 5.9 kg [95% CI -6.7 to -5.0]; Gxt, p < 0.001). Changes in consumption of animal foods in categories 1-4 were positively associated with changes in body weight: r = + 0.34; p < 0.001 for category 1; r = + 0.18; p = 0.008 for category 2; r = + 0.17; p = 0.01 for category 3; and r = + 0.22; p = 0.001 for category 4. In no NOVA category was the consumption of plant-based processed foods positively and significantly associated with weight gain. The top three independent predictors of weight loss were reduced intakes of processed, unprocessed or minimally processed, and ultra-processed animal foods. These findings suggest that replacing animal products with plant-based foods may be an effective weight-loss strategy, even when processed plant-based foods are included.
期刊介绍:
Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects.
The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases.
Key areas we wish to encourage submissions from include:
-how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes;
-the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components;
-how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved;
-how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.