Dietary patterns in the Southampton Women's Survey.
Dietary patterns in the Southampton Women's Survey.
OBJECTIVE: Dietary pattern analysis is receiving increasing attention as a means of summarizing the multidimensional nature of dietary data. This research aims to compare principal component analysis (PCA) and cluster analysis using dietary data collected from young women in the UK. DESIGN: Diet was assessed using a 100-item interviewer-administered food frequency questionnaire. PCA and cluster analysis were used to examine dietary patterns. SETTING: Southampton, UK. SUBJECTS: A total of 6125 non-pregnant women aged 20-34 years. RESULTS: PCA identified two important patterns: a 'prudent' diet and a 'high-energy' diet. Cluster analysis defined two clusters, a 'more healthy' and a 'less healthy' cluster. There was a strong association between the prudent diet score and the two clusters, such that the mean prudent diet score in the less healthy cluster was -0.73 standard deviations and in the more healthy cluster was +0.83 standard deviations; the difference in the high-energy diet score between the two clusters was considerably smaller. CONCLUSIONS: Both approaches revealed a similar dietary pattern. The continuous nature of the outcome of PCA was considered to be advantageous compared with the dichotomy identified using cluster analysis. SPONSORSHIP: The study was funded by the Dunhill Medical Trust, the University of Southampton and the Medical Research Council.
cluster analysis, research, sws, aged, diet, analysis, women
1391-1399
Crozier, S.R.
a97b1967-f6af-413a-8eb0-69fa25534d68
Robinson, S.M.
d2990871-44a1-48ab-b114-599753849c2b
Borland, S.E.
41a1150e-29d0-4d7f-b869-25d627489d7c
Inskip, H.M.
3f941a09-2f75-4b6d-8cb6-7662c4238cfb
SWS Study Group, None
fb963721-ab97-4074-85e8-76f943eb757d
December 2006
Crozier, S.R.
a97b1967-f6af-413a-8eb0-69fa25534d68
Robinson, S.M.
d2990871-44a1-48ab-b114-599753849c2b
Borland, S.E.
41a1150e-29d0-4d7f-b869-25d627489d7c
Inskip, H.M.
3f941a09-2f75-4b6d-8cb6-7662c4238cfb
SWS Study Group, None
fb963721-ab97-4074-85e8-76f943eb757d
Crozier, S.R., Robinson, S.M., Borland, S.E., Inskip, H.M. and SWS Study Group, None
(2006)
Dietary patterns in the Southampton Women's Survey.
European Journal of Clinical Nutrition, 60 (12), .
(doi:10.1038/sj.ejcn.1602469).
Abstract
OBJECTIVE: Dietary pattern analysis is receiving increasing attention as a means of summarizing the multidimensional nature of dietary data. This research aims to compare principal component analysis (PCA) and cluster analysis using dietary data collected from young women in the UK. DESIGN: Diet was assessed using a 100-item interviewer-administered food frequency questionnaire. PCA and cluster analysis were used to examine dietary patterns. SETTING: Southampton, UK. SUBJECTS: A total of 6125 non-pregnant women aged 20-34 years. RESULTS: PCA identified two important patterns: a 'prudent' diet and a 'high-energy' diet. Cluster analysis defined two clusters, a 'more healthy' and a 'less healthy' cluster. There was a strong association between the prudent diet score and the two clusters, such that the mean prudent diet score in the less healthy cluster was -0.73 standard deviations and in the more healthy cluster was +0.83 standard deviations; the difference in the high-energy diet score between the two clusters was considerably smaller. CONCLUSIONS: Both approaches revealed a similar dietary pattern. The continuous nature of the outcome of PCA was considered to be advantageous compared with the dichotomy identified using cluster analysis. SPONSORSHIP: The study was funded by the Dunhill Medical Trust, the University of Southampton and the Medical Research Council.
This record has no associated files available for download.
More information
Published date: December 2006
Keywords:
cluster analysis, research, sws, aged, diet, analysis, women
Identifiers
Local EPrints ID: 61028
URI: http://eprints.soton.ac.uk/id/eprint/61028
ISSN: 0954-3007
PURE UUID: 119f8c83-e75c-4b16-9795-87145b9ba9e8
Catalogue record
Date deposited: 25 Sep 2008
Last modified: 15 Mar 2024 11:21
Export record
Altmetrics
Contributors
Author:
S.R. Crozier
Author:
S.M. Robinson
Author:
S.E. Borland
Author:
H.M. Inskip
Author:
None SWS Study Group
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics