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  • 标题:Multidimensional Analysis of Food Consumption Reveals a Unique Dietary Profile Associated with Overweight and Obesity in Adolescents
  • 本地全文:下载
  • 作者:Vanessa M.B. Andrade ; Mônica L.P. de Santana 1, ; Kiyoshi F. Fukutani
  • 期刊名称:Nutrients
  • 电子版ISSN:2072-6643
  • 出版年度:2019
  • 卷号:11
  • 期号:8
  • 页码:1946-1960
  • DOI:10.3390/nu11081946
  • 出版社:MDPI Publishing
  • 摘要:There is a significant increase in overweight and obesity in adolescents worldwide. Here, we performed a cross-sectional study to examine the potential association between food consumption profiles and overweight in a large number of adolescents from Brazil. Sampling by clusters and conglomerates was carried out in students of public schools in Salvador, Brazil, between June and December 2009 and 1496 adolescents were evaluated. Data on socio-epidemiological data, anthropometric status and food consumption were captured. Multivariate analyses, such as hierarchical clustering and correlation networks, were used to perform a detailed description of food consumption profiles. There were differences in age and anthropometric status related to sex. Four clusters of food groups were identified based on the intake profile in the study population. No disparities in food intake were observed in individuals stratified by sex or anthropometric status. Furthermore, network analysis revealed that overweight or obesity were hallmarked by a selectivity in the ingestion of food groups that resulted in the appearance of inverse correlations of consumption, which was not present in eutrophic adolescents. Thus, overweight and obesity are associated with preferential choices of ingestion of specific food groups, which result in the appearance of inverse correlations of consumption. Such knowledge may serve as basis for future targeted nutritional interventions in adolescents.
  • 关键词:dietary intake; food group; adolescents; dietary patterns; anthropometric status; multidimensional statistical analysis dietary intake ; food group ; adolescents ; dietary patterns ; anthropometric status ; multidimensional statistical analysis
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