Mokhtari Ebrahim, Farhadnejad Hossein, Teymoori Farshad, Jahromi Mitra Kazemi, Nikkhah Mehrnaz, Mirmiran Parvin, Azizi Fereidoun
Nutrition and Endocrine Research Center, Research Institute for Endocrine Disorders, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Nutritional Sciences Research Center, Iran University of Medical Sciences, Tehran, Iran.
BMC Nutr. 2025 Feb 7;11(1):33. doi: 10.1186/s40795-025-01022-4.
Since foods are consumed in combinations that also interact with other lifestyle variables such as body mass index(BMI) and physical activity, it is difficult to separate the role of single foods or a lifestyle variable alone in predicting the risk of chronic diseases such as metabolic disorders. Therefore, a suitable way to examine the combined effect of food consumption and its interaction with other lifestyle variables is to derive dietary patterns and lifestyle patterns using appropriate statistical methods. This study aimed to derive two dietary and lifestyle patterns related to hyperinsulinemia and insulin resistance(IR) using reduced rank regression(RRR) analysis.
The current study was conducted on 1063 individuals aged ≥ 25 years old of the Tehran Lipid and Glucose Study who have complete data on fasting blood sugar, plasma insulin, anthropometric variables, and nutritional intakes. Dietary intakes were collected using a food frequency questionnaire. Dietary and lifestyle patterns were identified via RRR analysis, using 34 food groups, BMI, smoking, and physical activity as predictor variables, and fasting serum insulin and HOMA-IR as response biomarkers.
RRR derived a dietary pattern with a higher intake of processed meat, doogh, pickles, lemon juices, fish, and a lower intake of starchy vegetables, garlic and onion, dried fruits, nuts, red meat, dairy products, and coffee as predictive variables for IR and hyperinsulinemia. Also, RRR derived a lifestyle pattern based on the above-mentioned dietary pattern and high BMI as response variables. In the final adjusted model of cross-sectional analysis, the odds of hyperinsulinemia(OR:1.23,95%CI:1.08-1.41,P=0.002) and IR(OR:1.52,95%CI:1.25-1.86,P<0.001) were elevated with increasing each quartile of RRR-derived dietary pattern score. Also, a higher adherence to RRR-derived lifestyle pattern was associated with higher odds of hyperinsulinemia(OR:2.49,95%CI:2.14-2.88,P<0.001) and IR(OR:3.20,95%CI:2.50-4.10,P<0.001). Moreover, after three years of follow-up, the risk of hyperinsulinemia(OR:1.30,95%CI:1.08-1.56,P=0.006) and IR(OR:1.26,95%CI:1.01-1.58,P=0.037) incidence were increased per each quartile increase of the RRR-derived lifestyle pattern.
Our findings suggested that a dietary pattern and lifestyle with elevated BMI level, higher consumption of processed meat, doogh, pickles, lemon juices, and fish, and lower consumption of starchy vegetables, garlic and onion, dried fruits, nuts, red meat, dairy products, coffee may be associated with a higher risk of hyperinsulinemia and IR. It is suggested that further studies with a larger sample size and more extended follow-up duration, especially in other populations with different lifestyles and food habits be performed to confirm the findings of the current study.
由于食物是以组合形式被摄入的,且这些组合还会与其他生活方式变量相互作用,如体重指数(BMI)和身体活动,因此很难单独分离出单一食物或某个生活方式变量在预测代谢紊乱等慢性疾病风险中的作用。所以,一种合适的方法来检验食物消费的综合影响及其与其他生活方式变量的相互作用,就是使用适当的统计方法得出饮食模式和生活方式模式。本研究旨在通过降秩回归(RRR)分析得出与高胰岛素血症和胰岛素抵抗(IR)相关的两种饮食和生活方式模式。
本研究对德黑兰血脂与血糖研究中1063名年龄≥25岁且拥有空腹血糖、血浆胰岛素、人体测量变量和营养摄入完整数据的个体进行。饮食摄入量通过食物频率问卷收集。饮食和生活方式模式通过RRR分析确定,将34个食物组、BMI、吸烟和身体活动作为预测变量,空腹血清胰岛素和HOMA-IR作为反应生物标志物。
RRR得出一种饮食模式,其以加工肉类、酸奶饮料、泡菜、柠檬汁、鱼类摄入量较高,而淀粉类蔬菜、大蒜和洋葱、干果、坚果、红肉、乳制品和咖啡摄入量较低作为IR和高胰岛素血症的预测变量。此外,RRR基于上述饮食模式和高BMI作为反应变量得出一种生活方式模式。在横断面分析的最终调整模型中,随着RRR得出的饮食模式得分每增加一个四分位数,高胰岛素血症(OR:1.23,95%CI:1.08 - 1.41,P = 0.002)和IR(OR:1.52,95%CI:1.25 - 1.86,P < 0.001)的比值升高。同样,对RRR得出的生活方式模式更高的依从性与高胰岛素血症(OR:2.49,95%CI:2.14 - 2.88,P < 0.001)和IR(OR:3.20,95%CI:2.50 - 4.10,P < 0.001)的更高比值相关。此外,在三年随访后,RRR得出的生活方式模式每增加一个四分位数,高胰岛素血症(OR:1.30,95%CI:1.08 - 1.56,P = 0.006)和IR(OR:1.26,95%CI:1.01 - 1.58,P = 0.037)的发病风险增加。
我们的研究结果表明,一种饮食模式和生活方式,即BMI水平升高、加工肉类、酸奶饮料、泡菜、柠檬汁和鱼类消费较高,而淀粉类蔬菜、大蒜和洋葱、干果、坚果、红肉、乳制品、咖啡消费较低,可能与高胰岛素血症和IR的较高风险相关。建议进行样本量更大、随访时间更长的进一步研究,特别是在其他具有不同生活方式和饮食习惯的人群中,以证实本研究的结果。