Alliance for Canadian Health Outcomes Research in Diabetes, School of Public Health, 2-040 Li Ka Shing Centre for Health Research Innovation, University of Alberta, Edmonton, Alberta, Canada.
Wits Reproductive Health & HIV Institute, University of Witwatersrand, Johannesburg, South Africa.
Can J Diabetes. 2016 Aug;40(4):296-303. doi: 10.1016/j.jcjd.2015.11.006. Epub 2016 Mar 10.
Examining the diets of people living with type 2 diabetes may improve understanding of how diet affects disease progression. We derived dietary patterns in adults living with type 2 diabetes and explored associations among patterns, sociodemographic variables and cardiometabolic risk factors.
Dietary patterns were derived from food frequency questionnaires (FFQs) in 196 adults with type 2 diabetes using principal components analysis (PCA). Multilinear regression models were fitted for the differing dietary pattern scores so as to estimate the marginal contribution of each variable explaining variations in diet. Differences in clinical variables across dietary patterns, adjusting for sex, smoking and total energy intake, were assessed.
Three principal components (PCs), or patterns, were identified, explaining 56.5% of the total variance in diet: (PC1) fried foods, cakes and ice cream; (PC2) fish and vegetables; and (PC3) pasta, potatoes and breads. Female sex, current smoker and total energy were significant associated with patterns. Total energy accounted for the greatest amount of variance in each pattern (11.2% for fried foods, cakes and ice cream, 3.89% for fish and vegetables and 9.21% for pasta, potatoes and breads). After adjustment for sex, smoking and total energy, the pasta, potatoes and breads pattern was inversely associated with systolic blood pressure and low-density lipoprotein-cholesterol.
Of the 3 distinct diet patterns characterized, the carbohydrate-based pattern was most closely associated with cardiometabolic risk factors. To better understand and improve self-management by people living with type 2 diabetes through dietary modifications, further improvements in measuring and assessing diet using comparable instruments and comparisons with apparently healthy populations is required.
研究 2 型糖尿病患者的饮食情况，可能有助于了解饮食如何影响疾病进展。我们在 196 例 2 型糖尿病患者中通过食物频率问卷（FFQ）得出了饮食模式，并探讨了这些模式与社会人口统计学变量和心血管代谢风险因素之间的关联。
采用主成分分析（PCA）从 196 例 2 型糖尿病患者的食物频率问卷（FFQ）中得出饮食模式。为了估计每个变量对饮食变化的边际贡献，我们拟合了多元线性回归模型来计算不同饮食模式评分。在调整性别、吸烟和总能量摄入后，评估了不同饮食模式之间的临床变量差异。
确定了三个主要成分（PC）或模式，解释了饮食总方差的 56.5%：（PC1）油炸食品、蛋糕和冰淇淋；（PC2）鱼类和蔬菜；（PC3）面食、土豆和面包。女性、当前吸烟者和总能量与模式显著相关。总能量解释了每个模式中最大的变异量（油炸食品、蛋糕和冰淇淋占 11.2%，鱼类和蔬菜占 3.89%，面食、土豆和面包占 9.21%）。在调整性别、吸烟和总能量后，面食、土豆和面包模式与收缩压和低密度脂蛋白胆固醇呈负相关。
在所描述的 3 种不同饮食模式中，以碳水化合物为基础的模式与心血管代谢风险因素最为密切相关。为了通过饮食调整更好地了解和改善 2 型糖尿病患者的自我管理，需要使用可比工具进一步改进饮食的测量和评估，并与明显健康的人群进行比较。
