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Factor analysis is more appropriate to identify overall dietary patterns associated with diabetes when compared with Treelet transform analysis

Factor analysis is more appropriate to identify overall dietary patterns associated with diabetes when compared with Treelet transform analysis
Factor analysis is more appropriate to identify overall dietary patterns associated with diabetes when compared with Treelet transform analysis

Treelet transform (TT) is a proposed alternative to factor analysis for deriving dietary patterns. Before applying this method to nutrition data, further analyses are required to assess its validity in nutritional epidemiology. We aimed to compare dietary patterns from factor analysis and TT and their associations with diabetes incidence. Complete data were available for 7349 women (50-55 y at baseline) from the Australian Longitudinal Study on Women's Health. Exploratory factor analysis and TT were performed to obtain patterns by using dietary data collected from an FFQ. Generalized estimating equations analyses were used to examine associations between dietary patterns and diabetes incidence. Two patterns were identified by both methods: a prudent and a Western dietary pattern. Factor analysis factors are a linear combination of all food items, whereas TT factors also include items with zero loading. The Western pattern identified by factor analysis showed a significant positive association with diabetes [highest quintile: OR = 1.94 (95% CI: 1.25, 3.00); P-trend = 0.001). Both factor analysis and TT involve different assumptions and subjective decisions. TT produces clearly interpretable factors accounting for almost as much variance as factors from factor analysis. However, TT patterns include food items with zero loading and therefore do not represent overall dietary patterns. The different dietary pattern loading structures identified by both methods result in different conclusions regarding the relationship with diabetes. Results from this study indicate that factor analysis might be a more appropriate method for identifying overall dietary patterns associated with diabetes compared with TT.

Adult, Aged, Aged, 80 and over, Australia, Confidence Intervals, Diabetes Mellitus, Diet/statistics & numerical data, Factor Analysis, Statistical, Feeding Behavior, Female, Humans, Longitudinal Studies, Middle Aged, Odds Ratio, Reproducibility of Results, Statistics as Topic/methods
0022-3166
392-398
Schoenaker, Danielle A.J.M.
84b96b87-4070-45a5-9777-5a1e4e45e818
Dobson, Annette J.
e0837e7f-6bcd-4709-8706-899ae2cff1b2
Soedamah-Muthu, Sabita S.
a92e78f0-b28c-44f3-be86-e744fd004ff4
Mishra, Gita D.
02143b82-e536-4915-9b30-3c86cbe1a1fe
Schoenaker, Danielle A.J.M.
84b96b87-4070-45a5-9777-5a1e4e45e818
Dobson, Annette J.
e0837e7f-6bcd-4709-8706-899ae2cff1b2
Soedamah-Muthu, Sabita S.
a92e78f0-b28c-44f3-be86-e744fd004ff4
Mishra, Gita D.
02143b82-e536-4915-9b30-3c86cbe1a1fe

Schoenaker, Danielle A.J.M., Dobson, Annette J., Soedamah-Muthu, Sabita S. and Mishra, Gita D. (2013) Factor analysis is more appropriate to identify overall dietary patterns associated with diabetes when compared with Treelet transform analysis. The Journal of nutrition, 143 (3), 392-398. (doi:10.3945/jn.112.169011).

Record type: Article

Abstract

Treelet transform (TT) is a proposed alternative to factor analysis for deriving dietary patterns. Before applying this method to nutrition data, further analyses are required to assess its validity in nutritional epidemiology. We aimed to compare dietary patterns from factor analysis and TT and their associations with diabetes incidence. Complete data were available for 7349 women (50-55 y at baseline) from the Australian Longitudinal Study on Women's Health. Exploratory factor analysis and TT were performed to obtain patterns by using dietary data collected from an FFQ. Generalized estimating equations analyses were used to examine associations between dietary patterns and diabetes incidence. Two patterns were identified by both methods: a prudent and a Western dietary pattern. Factor analysis factors are a linear combination of all food items, whereas TT factors also include items with zero loading. The Western pattern identified by factor analysis showed a significant positive association with diabetes [highest quintile: OR = 1.94 (95% CI: 1.25, 3.00); P-trend = 0.001). Both factor analysis and TT involve different assumptions and subjective decisions. TT produces clearly interpretable factors accounting for almost as much variance as factors from factor analysis. However, TT patterns include food items with zero loading and therefore do not represent overall dietary patterns. The different dietary pattern loading structures identified by both methods result in different conclusions regarding the relationship with diabetes. Results from this study indicate that factor analysis might be a more appropriate method for identifying overall dietary patterns associated with diabetes compared with TT.

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More information

Accepted/In Press date: 30 November 2012
e-pub ahead of print date: 23 January 2013
Published date: March 2013
Keywords: Adult, Aged, Aged, 80 and over, Australia, Confidence Intervals, Diabetes Mellitus, Diet/statistics & numerical data, Factor Analysis, Statistical, Feeding Behavior, Female, Humans, Longitudinal Studies, Middle Aged, Odds Ratio, Reproducibility of Results, Statistics as Topic/methods

Identifiers

Local EPrints ID: 441985
URI: http://eprints.soton.ac.uk/id/eprint/441985
ISSN: 0022-3166
PURE UUID: f019c0af-e8f2-4356-a24f-c65b1c581494
ORCID for Danielle A.J.M. Schoenaker: ORCID iD orcid.org/0000-0002-7652-990X

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Date deposited: 03 Jul 2020 16:31
Last modified: 09 Jan 2022 04:10

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Contributors

Author: Annette J. Dobson
Author: Sabita S. Soedamah-Muthu
Author: Gita D. Mishra

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