A Dietary Pattern Derived by Reduced Rank Regression is Associated with Type 2 Diabetes in An Urban Ghanaian Population

Nutrients. 2015 Jul 7;7(7):5497-514. doi: 10.3390/nu7075233.

Abstract

Reduced rank regression (RRR) is an innovative technique to establish dietary patterns related to biochemical risk factors for type 2 diabetes, but has not been applied in sub-Saharan Africa. In a hospital-based case-control study for type 2 diabetes in Kumasi (diabetes cases, 538; controls, 668) dietary intake was assessed by a specific food frequency questionnaire. After random split of our study population, we derived a dietary pattern in the training set using RRR with adiponectin, HDL-cholesterol and triglycerides as responses and 35 food items as predictors. This pattern score was applied to the validation set, and its association with type 2 diabetes was examined by logistic regression. The dietary pattern was characterized by a high consumption of plantain, cassava, and garden egg, and a low intake of rice, juice, vegetable oil, eggs, chocolate drink, sweets, and red meat; the score correlated positively with serum triglycerides and negatively with adiponectin. The multivariate-adjusted odds ratio of type 2 diabetes for the highest quintile compared to the lowest was 4.43 (95% confidence interval: 1.87-10.50, p for trend < 0.001). The identified dietary pattern increases the odds of type 2 diabetes in urban Ghanaians, which is mainly attributed to increased serum triglycerides.

Keywords: HDL-cholesterol; adiponectin; biomarker; dietary pattern; reduced rank regression; sub-Saharan Africa; triglyceride; type 2 diabetes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers
  • Case-Control Studies
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Diabetes Mellitus, Type 2 / etiology*
  • Diet*
  • Feeding Behavior*
  • Female
  • Ghana / epidemiology
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Odds Ratio
  • Sensitivity and Specificity
  • Socioeconomic Factors
  • Surveys and Questionnaires
  • Urban Health
  • Urban Population*

Substances

  • Biomarkers