Dietary Patterns Derived by Reduced Rank Regression Are Inversely Associated with Type 2 Diabetes Risk across 5 Ethnic Groups in the Multiethnic Cohort

Abstract

Background: Reduced rank regression (RRR) is an approach to identify dietary patterns associated with biochemical markers and risk of type 2 diabetes (T2D). Objective: We aimed to derive dietary patterns associated with adiponectin, leptin, C-reactive protein (CRP), and triglycerides (TGs) and to examine the prospective associations of these patterns with T2D risk in 5 ethnic/racial groups with differences in T2D rates. Methods: The Multiethnic Cohort (MEC) included 215,831 African-American, Japanese-American, Latino, Native Hawaiian, and white adults living in Hawaii and California who completed a validated quantitative food-frequency questionnaire in 1993–1996. T2D status was based on self-report with confirmation by administrative data. Serum CRP and TGs and plasma adiponectin and leptin were measured ∼10 y after baseline in a subset (n = 10,008) of participants. RRR was applied to dietary data and biomarker information of 10,008 MEC participants in the combined population and in each ethnic/racial group. RRR-derived dietary patterns, simplified by removal of foods that were not found to be important, were subsequently evaluated for association with T2D risk in 155,316 cohort members (8687 incident T2D cases diagnosed by 2010) by using Cox proportional hazards regression. Results: Combining ethnic/racial groups, we identified a dietary pattern low in processed and red meat, sugar-sweetened beverages, diet soft drinks, and white rice and high in whole grains, fruit, yellow-orange vegetables, green vegetables, and low-fat dairy that was inversely associated with CRP, TGs, and leptin and positively related to adiponectin. Comparing extreme tertiles, the dietary pattern predicted a 16–28% significantly lower T2D risk in the combined study population and also separately in African Americans, Japanese Americans, Latinos, Native Hawaiians, and whites. Ethnicity-specific derived patterns varied only modestly from the overall pattern and resulted in comparable associations with T2D. Conclusion: This identified dietary pattern may lower T2D risk through its impact on adipokines, by lowering chronic inflammation and dyslipidemia across 5 ethnic/racial groups.

Dietary Patterns Related to Triglyceride and High-Density Lipoprotein Cholesterol and the Incidence of Type 2 Diabetes in Korean Men and Women

“…The consequences of insulin resistance and its compensatory hyperinsulinemia include glucose intolerance, dyslipidemia (increased TG and/or decreased HDL-C), high blood pressure, hyperuricemia, and increased plasminogen activator inhibitor (PAI)-1 activity [23]. Several studies have examined the association between risk of type 2 diabetes and dietary patterns that explain the variation of biomarkers that are linked to diabetes [12,13,14,15,16,17,18,19,20,21]. Biomarkers linked to diabetes that have been used to derive dietary patterns include inflammatory markers (e.g., PAI-1, tumor necrosis factor-α receptor 2, C-reactive protein (CRP), and Interleukin 6) [12,13,19,21], glucose (e.g., HbA1c, HOMA-IR, and fasting glucose) [12,14,16,20], lipid-related metabolites (e.g., TG, HDL-C, adiponectin, and leptin) [12,16,18,21], and uric acids [17].…”

“…Several studies have examined the association between risk of type 2 diabetes and dietary patterns that explain the variation of biomarkers that are linked to diabetes [12,13,14,15,16,17,18,19,20,21]. Biomarkers linked to diabetes that have been used to derive dietary patterns include inflammatory markers (e.g., PAI-1, tumor necrosis factor-α receptor 2, C-reactive protein (CRP), and Interleukin 6) [12,13,19,21], glucose (e.g., HbA1c, HOMA-IR, and fasting glucose) [12,14,16,20], lipid-related metabolites (e.g., TG, HDL-C, adiponectin, and leptin) [12,16,18,21], and uric acids [17]. Food groups that have been frequently reported to be associated with an increased risk of type 2 diabetes have been characterized by high intakes of sugar-sweetened beverages or soft drinks [12,13,14,16,17,21], processed meats [12,13,16,21], red meats [12,15,16,21], refined grains [13,16], white rice [21] or bread [14,19] and low intakes of wine [13,15,16], whole grains [16,21], and yellow [13,16,21] and green [16,21] vegetables.…”

“…Approaches to assess the effects of dietary patterns on the risk of diabetes have been implemented in epidemiologic studies [10,11]. Several previous studies have found significant associations between the risk of type 2 diabetes and posteriori-derived dietary patterns that explain the variation in diabetes-related biomarkers, such as blood glucose, lipids, or inflammatory markers [12,13,14,15,16,17,18,19,20,21].…”

Dietary Patterns of University Students in Jordan: A Cross-Sectional Study

“…For years many nutrients and their effects on health have been studied [3,4]. Foods are a combination of nutrients that interact together and exert diverse health effects [1,[5][6][7]. Studying the dietary patterns gives an insight on the overall diet and is very helpful in investigating their associations with health outcomes and other lifestyle factors [2,8].…”

“…Dietary patterns were evaluated in young adults, children, university students, and people with comorbidities [2,7,8]. Studying dietary patterns of university students has gained considerable investigation [11,12].…”