Susan M Devaraj1, Rachel G Miller1, Trevor J Orchard1, Andrea M Kriska1, Tiffany Gary-Webb1, Tina Costacou2. 1. University of Pittsburgh Graduate School of Public Health, Department of Epidemiology, United States of America. 2. University of Pittsburgh Graduate School of Public Health, Department of Epidemiology, United States of America. Electronic address: CostacouT@edc.pitt.edu.
Abstract
AIMS: Dietary intake provides a potential intervention target to reduce the high risk for coronary artery disease (CAD) in type 1 diabetes. This effort aimed to identify patterns of nutrient intake in young/middle-aged adults with type 1 diabetes and to examine associations between those patterns and development of CAD. METHODS: Principal component analysis was used to derive nutrient intake patterns among 514 individuals with childhood-onset (<17 years old) type 1 diabetes aged 18+ years and free of CAD (defined as CAD death, myocardial infarction, revascularization, ischemia, or study physician diagnosed angina). Cox models were used to assess the association between nutrient patterns and CAD incidence over 30-years of follow-up. RESULTS: Three nutrient principal components (PC) were identified: PC1 (high caffeine and saccharin intake), PC2 (high alcohol and caffeine, lower intake of essential nutrients) and PC3 (higher fiber/micronutrients, low alcohol). In unadjusted Cox models, only PC1 (negatively) and PC2 (positively) were associated with CAD risk. These associations were no longer significant after adjusting for diabetes duration. CONCLUSIONS: Important dietary components underlying the three patterns identified may have been influenced by diabetes duration or age. Future research can continue to explore patterns of nutrient intake over time and CAD development in type 1 diabetes.
AIMS: Dietary intake provides a potential intervention target to reduce the high risk for coronary artery disease (CAD) in type 1 diabetes. This effort aimed to identify patterns of nutrient intake in young/middle-aged adults with type 1 diabetes and to examine associations between those patterns and development of CAD. METHODS: Principal component analysis was used to derive nutrient intake patterns among 514 individuals with childhood-onset (<17 years old) type 1 diabetes aged 18+ years and free of CAD (defined as CAD death, myocardial infarction, revascularization, ischemia, or study physician diagnosed angina). Cox models were used to assess the association between nutrient patterns and CAD incidence over 30-years of follow-up. RESULTS: Three nutrient principal components (PC) were identified: PC1 (high caffeine and saccharin intake), PC2 (high alcohol and caffeine, lower intake of essential nutrients) and PC3 (higher fiber/micronutrients, low alcohol). In unadjusted Cox models, only PC1 (negatively) and PC2 (positively) were associated with CAD risk. These associations were no longer significant after adjusting for diabetes duration. CONCLUSIONS: Important dietary components underlying the three patterns identified may have been influenced by diabetes duration or age. Future research can continue to explore patterns of nutrient intake over time and CAD development in type 1 diabetes.
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