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A comparison of the dietary patterns derived by principal component analysis and cluster analysis in older Australians

Thorpe, Maree G., Milte, Catherine M., Crawford, David and McNaughton, Sarah A. 2016, A comparison of the dietary patterns derived by principal component analysis and cluster analysis in older Australians, International journal of behavioral nutrition and physical activity, vol. 13, no. 1, pp. 1-14, doi: 10.1186/s12966-016-0353-2.

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Title A comparison of the dietary patterns derived by principal component analysis and cluster analysis in older Australians
Author(s) Thorpe, Maree G.
Milte, Catherine M.ORCID iD for Milte, Catherine M. orcid.org/0000-0003-0035-6405
Crawford, DavidORCID iD for Crawford, David orcid.org/0000-0002-2467-7556
McNaughton, Sarah A.ORCID iD for McNaughton, Sarah A. orcid.org/0000-0001-5936-9820
Journal name International journal of behavioral nutrition and physical activity
Volume number 13
Issue number 1
Start page 1
End page 14
Total pages 14
Publisher BioMed Central
Place of publication London, Eng.
Publication date 2016-02-29
ISSN 1479-5868
Keyword(s) principal component analysis
cluster analysis
dietary patterns
comparison
older adults
retirement
Summary BACKGROUND: Despite increased use of dietary pattern methods in nutritional epidemiology, there have been few direct comparisons of methods. Older adults are a particularly understudied population in the dietary pattern literature. This study aimed to compare dietary patterns derived by principal component analysis (PCA) and cluster analysis (CA) in older adults and to examine their associations with socio-demographic and health behaviours. METHODS: Men (n = 1888) and women (n = 2071) aged 55-65 years completed a 111-item food frequency questionnaire in 2010. Food items were collapsed into 52 food groups and dietary patterns were determined by PCA and CA. Associations between dietary patterns and participant characteristics were examined using Chi-square analysis. The standardised PCA-derived dietary patterns were compared across the clusters using one-way ANOVA. RESULTS: PCA identified four dietary patterns in men and two dietary patterns in women. CA identified three dietary patterns in both men and women. Men in cluster 1 (fruit, vegetables, wholegrains, fish and poultry) scored higher on PCA factor 1 (vegetable dishes, fruit, fish and poultry) and factor 4 (vegetables) compared to factor 2 (spreads, biscuits, cakes and confectionery) and factor 3 (red meat, processed meat, white-bread and hot chips) (mean, 95 % CI; 0.92, 0.82-1.02 vs. 0.74, 0.63-0.84 vs. -0.43, -0.50- -0.35 vs. 0.60 0.46-0.74, respectively). Women in cluster 1 (fruit, vegetables and fish) scored highest on PCA factor 1 (fruit, vegetables and fish) compared to factor 2 (processed meat, hot chips cakes and confectionery) (1.05, 0.97-1.14 vs. -0.14, -0.21- -0.07, respectively). Cluster 3 (small eaters) in both men and women had negative factor scores for all the identified PCA dietary patterns. Those with dietary patterns characterised by higher consumption of red and processed meat and refined grains were more likely to be Australian-born, have a lower level of education, a higher BMI, smoke and did not meet physical activity recommendations (all P < 0.05). CONCLUSIONS: PCA and CA identified comparable dietary patterns within older Australians. However, PCA may provide some advantages compared to CA with respect to interpretability of the resulting dietary patterns. Older adults with poor dietary patterns also displayed other negative lifestyle behaviours. Food-based dietary pattern methods may inform dietary advice that is understood by the community.
Language eng
DOI 10.1186/s12966-016-0353-2
Field of Research 111199 Nutrition and Dietetics not elsewhere classified
Socio Economic Objective 920411 Nutrition
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30081936

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.