Characterizing nutrient patterns of food items in adolescent diet using data from a novel citizen science project and the US National Health and Nutrition Examination Survey (NHANES)

被引:4
作者
Treitler, Jonah T. [1 ,2 ]
Tekle, Senait [2 ]
Ushe, Jennifer [3 ]
Zanin, Linda [3 ]
Capshaw, Teri [3 ]
Tardieu, Gregory [3 ]
Libin, Alexander [4 ]
Zeng, Qing [2 ]
机构
[1] Thomas Jefferson High Sch Sci & Technol, Alexandria, VA USA
[2] George Washington Univ, Biomed Informat Ctr, Washington, DC 20052 USA
[3] Alexandria City Publ Sch, Alexandria, VA USA
[4] Georgetown Howard Univ Ctr Clin & Translat Sci GHU, Washington, DC USA
基金
美国国家卫生研究院;
关键词
adolescents; citizen science; nutrients; diet; cluster analysis; schools; CHILDREN;
D O I
10.3389/fnut.2023.1233141
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Introduction: A healthy diet is essential for promoting good health during adolescence and mitigating disease risks in adulthood. This underscores the need for improved nutrition education and increased access to healthier food choices. However, the accuracy of dietary data poses a significant challenge in nutritional research.Methods: We utilized and analyzed a novel dietary record dataset collected through a high school citizen science project to address this issue. We focused on nutrients rather than food groups to characterize adolescent dietary patterns. The same analyses were performed on the 2019-2021 National Health and Nutrition Examination Survey data for comparison.Results: Based on the U.S. Food and Drug Administration's recommended daily value (DV) for nutrients, the majority of food items in our citizen science dataset are low (i.e., <5% DV) in lipids, fiber, potassium, calcium, iron, sugar, and cholesterol. Only a minority of items are high (i.e., >20% DV) in macro and micronutrients. The clustering analysis identified nine food clusters with distinct nutrient profiles that vary significantly in size. The analyses on the NHANES data yielded similar findings, but with higher proportions of foods high in energy, lipids, carbohydrates, sugar, iron, and sodium compared with those of the citizen science dataset.Discussion: This study demonstrates the potential of citizen science projects in gathering valuable dietary data and understanding adolescent nutrient intake. Identifying critical nutrient gaps can guide targeted nutrition education and the provision of accessible healthier food options, leading to positive health outcomes during adolescence and beyond.
引用
收藏
页数:10
相关论文
共 26 条
[1]   Global Patterns of Adolescent Fruit, Vegetable, Carbonated Soft Drink, and Fast-Food Consumption: A Meta-Analysis of Global School-Based Student Health Surveys [J].
Beal, Ty ;
Morris, Saul S. ;
Tumilowicz, Alison .
FOOD AND NUTRITION BULLETIN, 2019, 40 (04) :444-459
[2]   Dietary Intake Following Experimentally Restricted Sleep in Adolescents [J].
Beebe, Dean W. ;
Simon, Stacey ;
Summer, Suzanne ;
Hemmer, Stephanie ;
Strotman, Daniel ;
Dolan, Lawrence M. .
SLEEP, 2013, 36 (06) :827-834
[3]  
Centers for Disease Control and Prevention, 2020, Healthy Eating for a Healthy Weight
[4]  
Centers for Disease Control and Prevention/National Center for Health Statistics, NHANES Tutorials
[5]  
Centers for Disease Control and Prevention/National Center for Health Statistics, NHANES measuring guides for the dietary recall interview
[6]  
Chen Te-Ching, 2020, Vital Health Stat 2, P1
[7]   Intakes of nutrients and food categories in Canadian children and adolescents across levels of sugars intake: cross-sectional analyses of the Canadian Community Health Survey 2015 Public Use Microdata File [J].
Chiavaroli, Laura ;
Wang, Ye Flora ;
Ahmed, Mavra ;
Ng, Alena Praneet ;
DiAngelo, Chiara ;
Marsden, Sandra ;
Sievenpiper, John L. .
APPLIED PHYSIOLOGY NUTRITION AND METABOLISM, 2022, 47 (04) :415-428
[8]   A meta-analysis of the reproducibility of food frequency questionnaires in nutritional epidemiological studies [J].
Cui, Qi ;
Xia, Yang ;
Wu, Qijun ;
Chang, Qing ;
Niu, Kaijun ;
Zhao, Yuhong .
INTERNATIONAL JOURNAL OF BEHAVIORAL NUTRITION AND PHYSICAL ACTIVITY, 2021, 18 (01)
[9]   Statistical power for cluster analysis [J].
Dalmaijer, Edwin S. ;
Nord, Camilla L. ;
Astle, Duncan E. .
BMC BIOINFORMATICS, 2022, 23 (01)
[10]   Exploring the association between mental wellbeing, health-related quality of life, family affluence and food choice in adolescents [J].
Davison, Jenny ;
Stewart-Knox, Barbara ;
Connolly, Paul ;
Lloyd, Katrina ;
Dunne, Laura ;
Bunting, Brendan .
APPETITE, 2021, 158