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Using cluster analysis to examine dietary patterns: nutrient intakes, gender, and weight status differ across food pattern clusters

Wirfält, Elisabet LU and Jeffery, Robert W (1997) In Journal of the American Dietetic Association 97(3). p.272-279
Abstract
OBJECTIVE: This study explored the usefulness of cluster analysis in identifying food choice patterns of three groups of adults in relation to their energy intake. DESIGN: Food frequency data were converted to percentage of total energy from 38 food groups and entered into a cluster analysis procedure. Subjects in the emerging food group patterns were compared in terms of weight status, demographics, and the nutrition composition of their usual diet. SETTING: Data were collected as part of three studies in two US metropolitan areas using identical protocols. Participants were university employees (103 women and 99 men) who volunteered for a reliability study of health behavior questionnaires and moderately obese volunteers (223 women and... (More)
OBJECTIVE: This study explored the usefulness of cluster analysis in identifying food choice patterns of three groups of adults in relation to their energy intake. DESIGN: Food frequency data were converted to percentage of total energy from 38 food groups and entered into a cluster analysis procedure. Subjects in the emerging food group patterns were compared in terms of weight status, demographics, and the nutrition composition of their usual diet. SETTING: Data were collected as part of three studies in two US metropolitan areas using identical protocols. Participants were university employees (103 women and 99 men) who volunteered for a reliability study of health behavior questionnaires and moderately obese volunteers (223 women and 101 men) to two weight-loss studies who were recruited by newspaper advertisements. STATISTICAL ANALYSIS PERFORMED: Subjects were clustered according to food energy sources using the FASTCLUS procedure in the Statistical Analysis System. One-way analysis of variance and chi 2 analysis were then performed to compared the weight status, nutrient intakes, and demographics of the food patterns. RESULTS: Six food pattern clusters were identified. Subjects in the two clusters associated with high consumption of pastry and meat had significantly higher fat intakes (P = .0001). Subjects in two other clusters, those associated with high intake of skim milk and a broad distribution of energy sources had significantly higher micronutrient levels (P = .0001). Body mass index and the distribution of gender were also significantly different across clusters. CONCLUSIONS: The success of cluster analysis in identifying dietary exposure categories with unique demographic and nutritional correlates suggests that the approach may be useful in epidemiologic studies that examine conditions such as obesity, and in the design of nutrition interventions. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of the American Dietetic Association
volume
97
issue
3
pages
272 - 279
publisher
Elsevier
external identifiers
  • pmid:9060944
  • scopus:1842337451
ISSN
0002-8223
DOI
10.1016/S0002-8223(97)00071-0
language
English
LU publication?
yes
id
0c518dfd-df50-405d-9cd9-05633fe8ec2a (old id 1112216)
date added to LUP
2008-07-21 15:54:52
date last changed
2017-09-24 03:44:47
@article{0c518dfd-df50-405d-9cd9-05633fe8ec2a,
  abstract     = {OBJECTIVE: This study explored the usefulness of cluster analysis in identifying food choice patterns of three groups of adults in relation to their energy intake. DESIGN: Food frequency data were converted to percentage of total energy from 38 food groups and entered into a cluster analysis procedure. Subjects in the emerging food group patterns were compared in terms of weight status, demographics, and the nutrition composition of their usual diet. SETTING: Data were collected as part of three studies in two US metropolitan areas using identical protocols. Participants were university employees (103 women and 99 men) who volunteered for a reliability study of health behavior questionnaires and moderately obese volunteers (223 women and 101 men) to two weight-loss studies who were recruited by newspaper advertisements. STATISTICAL ANALYSIS PERFORMED: Subjects were clustered according to food energy sources using the FASTCLUS procedure in the Statistical Analysis System. One-way analysis of variance and chi 2 analysis were then performed to compared the weight status, nutrient intakes, and demographics of the food patterns. RESULTS: Six food pattern clusters were identified. Subjects in the two clusters associated with high consumption of pastry and meat had significantly higher fat intakes (P = .0001). Subjects in two other clusters, those associated with high intake of skim milk and a broad distribution of energy sources had significantly higher micronutrient levels (P = .0001). Body mass index and the distribution of gender were also significantly different across clusters. CONCLUSIONS: The success of cluster analysis in identifying dietary exposure categories with unique demographic and nutritional correlates suggests that the approach may be useful in epidemiologic studies that examine conditions such as obesity, and in the design of nutrition interventions.},
  author       = {Wirfält, Elisabet and Jeffery, Robert W},
  issn         = {0002-8223},
  language     = {eng},
  number       = {3},
  pages        = {272--279},
  publisher    = {Elsevier},
  series       = {Journal of the American Dietetic Association},
  title        = {Using cluster analysis to examine dietary patterns: nutrient intakes, gender, and weight status differ across food pattern clusters},
  url          = {http://dx.doi.org/10.1016/S0002-8223(97)00071-0},
  volume       = {97},
  year         = {1997},
}