title: Using both principal component analysis and reduced rank regression to study dietary patterns and diabetes in Chinese adults.
abstract: OBJECTIVE
  We examined the association between dietary patterns and diabetes using the strengths of two methods: principal component analysis (PCA) to identify the eating patterns of the population and reduced rank regression (RRR) to derive a pattern that explains the variation in glycated Hb (HbA1c), homeostasis model assessment of insulin resistance (HOMA-IR) and fasting glucose.
  
  
  METHODS
  We measured diet over a 3 d period with 24 h recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009.
  
  
  METHODS
  Adults (n 4316) from the China Health and Nutrition Survey.
  
  
  RESULTS
  The adjusted odds ratio for diabetes prevalence (HbA1c≥6·5 %), comparing the highest dietary pattern score quartile with the lowest, was 1·26 (95 % CI 0·76, 2·08) for a modern high-wheat pattern (PCA; wheat products, fruits, eggs, milk, instant noodles and frozen dumplings), 0·76 (95 % CI 0·49, 1·17) for a traditional southern pattern (PCA; rice, meat, poultry and fish) and 2·37 (95 % CI 1·56, 3·60) for the pattern derived with RRR. By comparing the dietary pattern structures of RRR and PCA, we found that the RRR pattern was also behaviourally meaningful. It combined the deleterious effects of the modern high-wheat pattern (high intakes of wheat buns and breads, deep-fried wheat and soya milk) with the deleterious effects of consuming the opposite of the traditional southern pattern (low intakes of rice, poultry and game, fish and seafood).
  
  
  CONCLUSIONS
  Our findings suggest that using both PCA and RRR provided useful insights when studying the association of dietary patterns with diabetes.
authors.affiliation: 1Department of Nutrition and Carolina Population Center,University of North Carolina at Chapel Hill,137 East Franklin Street,Chapel Hill,NC 27516,USA.
authors.forename: Carolina
authors.initials: C
authors.lastname: Batis
authors.affiliation: 1Department of Nutrition and Carolina Population Center,University of North Carolina at Chapel Hill,137 East Franklin Street,Chapel Hill,NC 27516,USA.
authors.forename: Michelle A
authors.initials: MA
authors.lastname: Mendez
authors.affiliation: 1Department of Nutrition and Carolina Population Center,University of North Carolina at Chapel Hill,137 East Franklin Street,Chapel Hill,NC 27516,USA.
authors.forename: Penny
authors.initials: P
authors.lastname: Gordon-Larsen
authors.affiliation: 2Department of Biostatistics,University of North Carolina at Chapel Hill,Chapel Hill,NC,USA.
authors.forename: Daniela
authors.initials: D
authors.lastname: Sotres-Alvarez
authors.affiliation: 1Department of Nutrition and Carolina Population Center,University of North Carolina at Chapel Hill,137 East Franklin Street,Chapel Hill,NC 27516,USA.
authors.forename: Linda
authors.initials: L
authors.lastname: Adair
authors.affiliation: 1Department of Nutrition and Carolina Population Center,University of North Carolina at Chapel Hill,137 East Franklin Street,Chapel Hill,NC 27516,USA.
authors.forename: Barry
authors.initials: B
authors.lastname: Popkin
mesh_terms: D000328:Adult; D001786:Blood Glucose / Q000378:metabolism; D002681:China; D003920:Diabetes Mellitus / Q000097:blood / Q000209:etiology* / Q000517:prevention & control; D004032:Diet; D005191:Family Characteristics; D005247:Feeding Behavior; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007333:Insulin Resistance; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys; D016017:Odds Ratio; D025341:Principal Component Analysis; D012107:Research Design
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin
keywords: Diabetes; Dietary patterns; Principal component analysis; Reduced rank regression