CitationBatis, Carolina R.; Mendez, Michelle A.; Gordon-Larsen, Penny; Adair, Linda S.; Sotres-Alvarez, Daniela T.; Popkin, Barry M.; & (2016). Using Both Principal Component Analysis and Reduced Rank Regression to Study Dietary Patterns and Diabetes in Chinese Adults. Public Health Nutrition, 19(2), 195-203. PMCID: PMC4721264
AbstractObjective: 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 hemoglobin A1c (HbA1c), homeostasis model of insulin resistance (HOMA-IR), and fasting glucose.
Design: We measured diet over a 3-day period with 24-hour recalls and a household food inventory in 2006 and used it to derive PCA and RRR dietary patterns. The outcomes were measured in 2009. Setting: Adults (n = 4,316) 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 to the lowest, was 1.26 (0.76, 2.08) for a modern high-wheat pattern (PCA; wheat products, fruits, eggs, milk, instant noodles and frozen dumplings), 0.76 (0.49, 1.17) for a traditional southern pattern (PCA; rice, meat, poultry, and fish), and 2.37 (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 behaviorally meaningful. It combined the deleterious effects of the modern high-wheat (high intake of wheat buns and breads, deep-fried wheat, and soy milk) with the deleterious effects of consuming the opposite of the traditional southern (low intake 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.
Reference TypeJournal Article
Journal TitlePublic Health Nutrition
Author(s)Batis, Carolina R.
Mendez, Michelle A.
Adair, Linda S.
Sotres-Alvarez, Daniela T.
Popkin, Barry M.