Validity and reproducibility of a Spanish dietary history
To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information on numerous aspects of the Spanish diet. The validity of food and nutrient intake was estimated using Pearson correlation coefficients betwee...
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Published in: | PloS one Vol. 9; no. 1; p. e86074 |
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Main Authors: | , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
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Public Library of Science
20-01-2014
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Abstract | To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information on numerous aspects of the Spanish diet.
The validity of food and nutrient intake was estimated using Pearson correlation coefficients between the DH-E and the mean of seven 24-hour recalls collected every 2 months over the previous year. The reproducibility was estimated using intraclass correlation coefficients between two DH-E made one year apart.
The correlations coefficients between the DH-E and the mean of seven 24-hour recalls for the main food groups were cereals (r = 0.66), meat (r = 0.66), fish (r = 0.42), vegetables (r = 0.62) and fruits (r = 0.44). The mean correlation coefficient for all 15 food groups considered was 0.53. The correlations for macronutrients were: energy (r = 0.76), proteins (r= 0.58), lipids (r = 0.73), saturated fat (r = 0.73), monounsaturated fat (r = 0.59), polyunsaturated fat (r = 0.57), and carbohydrates (r = 0.66). The mean correlation coefficient for all 41 nutrients studied was 0.55. The intraclass correlation coefficient between the two DH-E was greater than 0.40 for most foods and nutrients.
The DH-E shows good validity and reproducibility for estimating usual intake of foods and nutrients. |
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AbstractList | To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information on numerous aspects of the Spanish diet.
The validity of food and nutrient intake was estimated using Pearson correlation coefficients between the DH-E and the mean of seven 24-hour recalls collected every 2 months over the previous year. The reproducibility was estimated using intraclass correlation coefficients between two DH-E made one year apart.
The correlations coefficients between the DH-E and the mean of seven 24-hour recalls for the main food groups were cereals (r = 0.66), meat (r = 0.66), fish (r = 0.42), vegetables (r = 0.62) and fruits (r = 0.44). The mean correlation coefficient for all 15 food groups considered was 0.53. The correlations for macronutrients were: energy (r = 0.76), proteins (r= 0.58), lipids (r = 0.73), saturated fat (r = 0.73), monounsaturated fat (r = 0.59), polyunsaturated fat (r = 0.57), and carbohydrates (r = 0.66). The mean correlation coefficient for all 41 nutrients studied was 0.55. The intraclass correlation coefficient between the two DH-E was greater than 0.40 for most foods and nutrients.
The DH-E shows good validity and reproducibility for estimating usual intake of foods and nutrients. To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information on numerous aspects of the Spanish diet. The validity of food and nutrient intake was estimated using Pearson correlation coefficients between the DH-E and the mean of seven 24-hour recalls collected every 2 months over the previous year. The reproducibility was estimated using intraclass correlation coefficients between two DH-E made one year apart. The correlations coefficients between the DH-E and the mean of seven 24-hour recalls for the main food groups were cereals (r = 0.66), meat (r = 0.66), fish (r = 0.42), vegetables (r = 0.62) and fruits (r = 0.44). The mean correlation coefficient for all 15 food groups considered was 0.53. The correlations for macronutrients were: energy (r = 0.76), proteins (r = 0.58), lipids (r = 0.73), saturated fat (r = 0.73), monounsaturated fat (r = 0.59), polyunsaturated fat (r = 0.57), and carbohydrates (r = 0.66). The mean correlation coefficient for all 41 nutrients studied was 0.55. The intraclass correlation coefficient between the two DH-E was greater than 0.40 for most foods and nutrients. The DH-E shows good validity and reproducibility for estimating usual intake of foods and nutrients. Objective To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information on numerous aspects of the Spanish diet. Methods The validity of food and nutrient intake was estimated using Pearson correlation coefficients between the DH-E and the mean of seven 24-hour recalls collected every 2 months over the previous year. The reproducibility was estimated using intraclass correlation coefficients between two DH-E made one year apart. Results The correlations coefficients between the DH-E and the mean of seven 24-hour recalls for the main food groups were cereals (r = 0.66), meat (r = 0.66), fish (r = 0.42), vegetables (r = 0.62) and fruits (r = 0.44). The mean correlation coefficient for all 15 food groups considered was 0.53. The correlations for macronutrients were: energy (r = 0.76), proteins (r = 0.58), lipids (r = 0.73), saturated fat (r = 0.73), monounsaturated fat (r = 0.59), polyunsaturated fat (r = 0.57), and carbohydrates (r = 0.66). The mean correlation coefficient for all 41 nutrients studied was 0.55. The intraclass correlation coefficient between the two DH-E was greater than 0.40 for most foods and nutrients. Conclusions The DH-E shows good validity and reproducibility for estimating usual intake of foods and nutrients. Objective To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information on numerous aspects of the Spanish diet. Methods The validity of food and nutrient intake was estimated using Pearson correlation coefficients between the DH-E and the mean of seven 24-hour recalls collected every 2 months over the previous year. The reproducibility was estimated using intraclass correlation coefficients between two DH-E made one year apart. Results The correlations coefficients between the DH-E and the mean of seven 24-hour recalls for the main food groups were cereals (r = 0.66), meat (r = 0.66), fish (r = 0.42), vegetables (r = 0.62) and fruits (r = 0.44). The mean correlation coefficient for all 15 food groups considered was 0.53. The correlations for macronutrients were: energy (r = 0.76), proteins (r = 0.58), lipids (r = 0.73), saturated fat (r = 0.73), monounsaturated fat (r = 0.59), polyunsaturated fat (r = 0.57), and carbohydrates (r = 0.66). The mean correlation coefficient for all 41 nutrients studied was 0.55. The intraclass correlation coefficient between the two DH-E was greater than 0.40 for most foods and nutrients. Conclusions The DH-E shows good validity and reproducibility for estimating usual intake of foods and nutrients. OBJECTIVETo assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information on numerous aspects of the Spanish diet. METHODSThe validity of food and nutrient intake was estimated using Pearson correlation coefficients between the DH-E and the mean of seven 24-hour recalls collected every 2 months over the previous year. The reproducibility was estimated using intraclass correlation coefficients between two DH-E made one year apart. RESULTSThe correlations coefficients between the DH-E and the mean of seven 24-hour recalls for the main food groups were cereals (r = 0.66), meat (r = 0.66), fish (r = 0.42), vegetables (r = 0.62) and fruits (r = 0.44). The mean correlation coefficient for all 15 food groups considered was 0.53. The correlations for macronutrients were: energy (r = 0.76), proteins (r= 0.58), lipids (r = 0.73), saturated fat (r = 0.73), monounsaturated fat (r = 0.59), polyunsaturated fat (r = 0.57), and carbohydrates (r = 0.66). The mean correlation coefficient for all 41 nutrients studied was 0.55. The intraclass correlation coefficient between the two DH-E was greater than 0.40 for most foods and nutrients. CONCLUSIONSThe DH-E shows good validity and reproducibility for estimating usual intake of foods and nutrients. |
Audience | Academic |
Author | Guallar-Castillón, Pilar Graciani, Auxiliadora Laclaustra, Martín Banegas, José Ramón Sagardui-Villamor, Jon Sala-Vila, Aleix Ariza Astolfi, Maria José Benito, Cristina Balboa-Castillo, Teresa Sarrión Pelous, Maria Dolores León-Muñoz, Luz María Artalejo, Fernando Rodríguez |
AuthorAffiliation | 5 Lipid Clinic, Endocrinology and Nutrition Service, Biomedical Research Institute August Pi i Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain 8 Centro Nacional de Investigaciones Cardiológicas (CNIC), Madrid, Spain 2 CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain 6 CIBER de Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain Paris Institute of Technology for Life, Food and Environmental Sciences, France 3 Centro de Salud de Villanueva del Pardillo, Madrid, Spain 4 Department of Public Health, School of Medicine, Universidad de la Frontera, Temuco, Chile 1 Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain 7 Hospital Universitario La Paz, Department of Biochemistry, Madrid, Spain |
AuthorAffiliation_xml | – name: 6 CIBER de Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – name: 4 Department of Public Health, School of Medicine, Universidad de la Frontera, Temuco, Chile – name: 5 Lipid Clinic, Endocrinology and Nutrition Service, Biomedical Research Institute August Pi i Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain – name: Paris Institute of Technology for Life, Food and Environmental Sciences, France – name: 1 Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain – name: 2 CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – name: 7 Hospital Universitario La Paz, Department of Biochemistry, Madrid, Spain – name: 3 Centro de Salud de Villanueva del Pardillo, Madrid, Spain – name: 8 Centro Nacional de Investigaciones Cardiológicas (CNIC), Madrid, Spain |
Author_xml | – sequence: 1 givenname: Pilar surname: Guallar-Castillón fullname: Guallar-Castillón, Pilar organization: Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain ; CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 2 givenname: Jon surname: Sagardui-Villamor fullname: Sagardui-Villamor, Jon organization: Centro de Salud de Villanueva del Pardillo, Madrid, Spain – sequence: 3 givenname: Teresa surname: Balboa-Castillo fullname: Balboa-Castillo, Teresa organization: Department of Public Health, School of Medicine, Universidad de la Frontera, Temuco, Chile – sequence: 4 givenname: Aleix surname: Sala-Vila fullname: Sala-Vila, Aleix organization: Lipid Clinic, Endocrinology and Nutrition Service, Biomedical Research Institute August Pi i Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain ; CIBER de Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 5 givenname: Maria José surname: Ariza Astolfi fullname: Ariza Astolfi, Maria José organization: Hospital Universitario La Paz, Department of Biochemistry, Madrid, Spain – sequence: 6 givenname: Maria Dolores surname: Sarrión Pelous fullname: Sarrión Pelous, Maria Dolores organization: Hospital Universitario La Paz, Department of Biochemistry, Madrid, Spain – sequence: 7 givenname: Luz María surname: León-Muñoz fullname: León-Muñoz, Luz María organization: Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain ; CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 8 givenname: Auxiliadora surname: Graciani fullname: Graciani, Auxiliadora organization: Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain ; CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 9 givenname: Martín surname: Laclaustra fullname: Laclaustra, Martín organization: Centro Nacional de Investigaciones Cardiológicas (CNIC), Madrid, Spain – sequence: 10 givenname: Cristina surname: Benito fullname: Benito, Cristina organization: Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain ; CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 11 givenname: José Ramón surname: Banegas fullname: Banegas, José Ramón organization: Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain ; CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 12 givenname: Fernando Rodríguez surname: Artalejo fullname: Artalejo, Fernando Rodríguez organization: Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPAZ, Madrid, Spain ; CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24465878$$D View this record in MEDLINE/PubMed |
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ContentType | Journal Article |
Copyright | COPYRIGHT 2014 Public Library of Science 2014 Guallar-Castillon et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2014 Guallar-Castillon et al 2014 Guallar-Castillon et al |
Copyright_xml | – notice: COPYRIGHT 2014 Public Library of Science – notice: 2014 Guallar-Castillon et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: 2014 Guallar-Castillon et al 2014 Guallar-Castillon et al |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: PGC JRB FRA. Performed the experiments: JSV AG CB. Analyzed the data: PGC TBC LMLM. Contributed reagents/materials/analysis tools: ASV MJAA MDSP ML. Wrote the paper: PGC FRA. |
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Snippet | To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects information... Objective To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects... OBJECTIVETo assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects... Objective To assess the validity and reproducibility of food and nutrient intake estimated with the electronic diet history of ENRICA (DH-E), which collects... |
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SubjectTerms | Adult Biochemistry Biology Biomarkers Carbohydrates Cereals Correlation Correlation coefficient Correlation coefficients Diet Diet Surveys - instrumentation Diet Surveys - methods Eating Epidemiology European Continental Ancestry Group Fatty acids Feeding Behavior Female Food Food groups Food intake Health care Hospitals Humans Lipids Male Meat Medicine Middle Aged Monounsaturated fatty acids Nutrients Nutrition research Preventive medicine Proteins Public health Reproducibility Reproducibility of Results Social and Behavioral Sciences Spain Studies Surveys and Questionnaires Vegetables |
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Title | Validity and reproducibility of a Spanish dietary history |
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