Development of a short food frequency questionnaire to assess diet quality in UK adolescents using the National Diet and Nutrition Survey.

Adolescents Diet quality Dietary assessment National Diet and nutrition survey Short food frequency questionnaire

Journal

Nutrition journal
ISSN: 1475-2891
Titre abrégé: Nutr J
Pays: England
ID NLM: 101152213

Informations de publication

Date de publication:
12 01 2021
Historique:
received: 17 07 2020
accepted: 13 12 2020
entrez: 12 1 2021
pubmed: 13 1 2021
medline: 30 9 2021
Statut: epublish

Résumé

UK adolescents consume fewer fruits and vegetables and more free sugars than any other age group. Established techniques to understand diet quality can be difficult to use with adolescents because of high participant burden. This study aimed to identify key foods that indicate variation in diet quality in UK adolescents for inclusion in a short food frequency questionnaire (FFQ) and to investigate the associations between adolescent diet quality, nutritional biomarkers and socio-demographic factors. Dietary, demographic and biomarker data from waves 1-8 of the National Diet and Nutrition Survey rolling programme were used (n=2587; aged 11-18 years; 50% boys; n=≤997 biomarker data). Principal component analysis (PCA) was applied to 139 food groups to identify the key patterns within the data. Two diet quality scores, a 139-group and 20-group, were calculated using the PCA coefficients for each food group and multiplying by their standardised reported frequency of consumption and then summing across foods. The foods with the 10 strongest positive and 10 strongest negative coefficients from the PCA results were used for the 20-group score. Scores were standardised to have a zero mean and standard deviation of one. The first PCA component explained 3.0% of variance in the dietary data and described a dietary pattern broadly aligned with UK dietary recommendations. A correlation of 0.87 was observed between the 139-group and 20-group scores. Bland-Altman mean difference was 0.00 and 95% limits of agreement were - 0.98 to 0.98 SDs. Correlations, in the expected direction, were seen between each nutritional biomarker and both scores; results attenuated slightly for the 20-group score compared to the 139-group score. Better diet quality was observed among girls, non-white populations and in those from higher socio-economic backgrounds for both scores. The diet quality score based on 20 food groups showed reasonable agreement with the 139-group score. Both scores were correlated with nutritional biomarkers. A short 20-item FFQ can provide a meaningful and easy-to-implement tool to assess diet quality in large scale observational and intervention studies with adolescents.

Sections du résumé

BACKGROUND
UK adolescents consume fewer fruits and vegetables and more free sugars than any other age group. Established techniques to understand diet quality can be difficult to use with adolescents because of high participant burden. This study aimed to identify key foods that indicate variation in diet quality in UK adolescents for inclusion in a short food frequency questionnaire (FFQ) and to investigate the associations between adolescent diet quality, nutritional biomarkers and socio-demographic factors.
METHODS
Dietary, demographic and biomarker data from waves 1-8 of the National Diet and Nutrition Survey rolling programme were used (n=2587; aged 11-18 years; 50% boys; n=≤997 biomarker data). Principal component analysis (PCA) was applied to 139 food groups to identify the key patterns within the data. Two diet quality scores, a 139-group and 20-group, were calculated using the PCA coefficients for each food group and multiplying by their standardised reported frequency of consumption and then summing across foods. The foods with the 10 strongest positive and 10 strongest negative coefficients from the PCA results were used for the 20-group score. Scores were standardised to have a zero mean and standard deviation of one.
RESULTS
The first PCA component explained 3.0% of variance in the dietary data and described a dietary pattern broadly aligned with UK dietary recommendations. A correlation of 0.87 was observed between the 139-group and 20-group scores. Bland-Altman mean difference was 0.00 and 95% limits of agreement were - 0.98 to 0.98 SDs. Correlations, in the expected direction, were seen between each nutritional biomarker and both scores; results attenuated slightly for the 20-group score compared to the 139-group score. Better diet quality was observed among girls, non-white populations and in those from higher socio-economic backgrounds for both scores.
CONCLUSIONS
The diet quality score based on 20 food groups showed reasonable agreement with the 139-group score. Both scores were correlated with nutritional biomarkers. A short 20-item FFQ can provide a meaningful and easy-to-implement tool to assess diet quality in large scale observational and intervention studies with adolescents.

Identifiants

pubmed: 33430892
doi: 10.1186/s12937-020-00658-1
pii: 10.1186/s12937-020-00658-1
pmc: PMC7802176
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5

Subventions

Organisme : Medical Research Council
ID : MC_UU_12011/4
Pays : United Kingdom
Organisme : Department of Health
ID : RP-PG-0216-20004
Pays : United Kingdom

Références

Lancet. 1986 Feb 8;1(8476):307-10
pubmed: 2868172
J Nutr. 2010 Jul;140(7):1280-6
pubmed: 20484545
J Am Diet Assoc. 2004 Sep;104(9):1375-83
pubmed: 15354153
Public Health Nutr. 2017 Apr;20(5):870-882
pubmed: 27846923
Public Health Nutr. 2001 Oct;4(5):989-97
pubmed: 11784412
Lancet. 2016 Jun 11;387(10036):2423-78
pubmed: 27174304
Br J Nutr. 2009 Aug;102(4):610-8
pubmed: 19203423
Curr Opin Lipidol. 2002 Feb;13(1):3-9
pubmed: 11790957
Qual Life Res. 2003 May;12(3):229-38
pubmed: 12769135
Int J Pediatr Obes. 2011 Feb;6(1):2-11
pubmed: 20874449
Br J Nutr. 2016 Nov;116(9):1633-1645
pubmed: 27823581
Nutrients. 2018 Feb 06;10(2):
pubmed: 29415478
J Nutr Health Aging. 2017;21(3):247-253
pubmed: 28244562
Br J Nutr. 2013 Jun;109(11):2067-78
pubmed: 23110799
Epidemiol Health. 2014 Jul 22;36:e2014009
pubmed: 25078382
J Acad Nutr Diet. 2013 Feb;113(2):297-306
pubmed: 23168270
Eur J Clin Nutr. 2004 Aug;58(8):1166-73
pubmed: 15054430
Stat Methods Med Res. 1992;1(1):69-95
pubmed: 1341653
Maturitas. 2009 Jan 20;62(1):1-8
pubmed: 19128905
Eur J Clin Nutr. 2005 Dec;59(12):1387-96
pubmed: 16160702
Eur J Clin Nutr. 2017 Apr;71(4):458-467
pubmed: 28120854
BMC Public Health. 2013 Jun 08;13:562
pubmed: 23759064
J Am Diet Assoc. 2011 Feb;111(2):230-40
pubmed: 21272697
Br J Nutr. 2006 May;95(5):860-9
pubmed: 16611375
PLoS Med. 2016 Jun 07;13(6):e1002036
pubmed: 27270749
Eur J Clin Nutr. 2010 Jan;64(1):99-104
pubmed: 19756032
Nutr J. 2018 Jun 4;17(1):58
pubmed: 29866150
Nutrients. 2019 Jul 17;11(7):
pubmed: 31319451
Public Health Nutr. 2014 May;17(5):1069-77
pubmed: 23635946
J Nutr. 2008 Feb;138(2):364-70
pubmed: 18203905
Nutr Res Pract. 2011 Aug;5(4):322-8
pubmed: 21994527
BMJ. 2018 Jun 13;361:k2396
pubmed: 29898951
BMC Med. 2017 Nov 15;15(1):202
pubmed: 29137630
PLoS One. 2014 Nov 03;9(11):e111619
pubmed: 25365261
Eur J Nutr. 2016 Jun;55(4):1789-97
pubmed: 26212034
Public Health Nutr. 2014 Jul;17(7):1476-85
pubmed: 23782861
Clin Chem. 1994 Mar;40(3):411-6
pubmed: 8131277

Auteurs

Sarah Shaw (S)

MRC Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton, Tremona Road, Southampton, SO16 6YD, UK. ss@mrc.soton.ac.uk.
NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK. ss@mrc.soton.ac.uk.

Sarah Crozier (S)

MRC Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton, Tremona Road, Southampton, SO16 6YD, UK.

Sofia Strömmer (S)

MRC Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton, Tremona Road, Southampton, SO16 6YD, UK.
NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK.

Hazel Inskip (H)

MRC Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton, Tremona Road, Southampton, SO16 6YD, UK.
NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK.

Mary Barker (M)

MRC Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton, Tremona Road, Southampton, SO16 6YD, UK.
NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK.

Christina Vogel (C)

MRC Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton, Tremona Road, Southampton, SO16 6YD, UK.
NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH