Moslehi Nazanin, Rahimi Sakak Fatemeh, Mahdavi Maryam, Mirmiran Parvin, Azizi Fereidoun
Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Front Nutr. 2022 Jul 28;9:812701. doi: 10.3389/fnut.2022.812701. eCollection 2022.
Visceral obesity is a significant predictor of cardiovascular disease (CVD). Diet may associate with CVD risk through its effects on visceral adiposity. This study aimed to find dietary patterns (DPs) related to indicators of visceral adiposity and to determine whether the DPs were associated with CVD risk.
This prospective study included 2,496 participants of the Tehran Lipid and Glucose Study (TLGS) without CVD, who were followed from the third study examination (2005-2008; baseline) to March 2018. DPs at baseline were determined using reduced rank regression (RRR) and partial least squares regression (PLS). The response variables were age and BMI-adjusted waist circumference (WC) and age-adjusted visceral adiposity index (VAI).
Two and three DPs were retained with RRR and PLS, respectively. The first patterns of each method were mainly characterized by adjusted-WC (RRR: 10.8%, PLS: 8.6%); none of them were associated with CVD risk. The second pattern of RRR and the third pattern of PLS were mainly explained by adjusted-VAI (RRR: 3.3, PLS: 2.1%). After adjusting for CVD risk factors, the hazard ratios [95% confidence intervals (CI)] for CVD in the second and third tertiles of the RRR-pattern 2 were 1.76 (1.15, 2.69) and 1.55 (1.00, 2.43) vs. the first tertile (-trend: 0.058). This pattern had high positive loadings for non-leafy vegetables, pickled vegetables, fried vegetables, and bread and high negative loadings for eggs, cakes, butter, jam-honey, red meat, poultry, fish, juice, non-fermented dairy, and fruits. Per one SD increase in PLS-pattern 3 score, the risk of CVD was 19% higher (95%CI = 3-38%). This positive association was also observed across tertiles of the pattern (p-trend: 0.032). This pattern was characterized by high intakes of leafy vegetables, non-leafy vegetables, organ meat, soft drinks, olive oil, pickled vegetables, fried vegetables, and bread and low intakes of biscuits, cakes, butter, eggs, and non-fermented dairy.
For each of the RRR and PLS approaches, a visceral-related DP that was positively linked to CVD was identified. These two patterns had a modest correlation. The pattern generated by PLS explained more variations in food groups and offered stronger evidence of association with CVD than the RRR-derived pattern.
内脏型肥胖是心血管疾病（CVD）的重要预测指标。饮食可能通过对内脏脂肪的影响与CVD风险相关。本研究旨在找出与内脏脂肪指标相关的饮食模式（DPs），并确定这些DPs是否与CVD风险相关。
这项前瞻性研究纳入了德黑兰脂质与葡萄糖研究（TLGS）中2496名无CVD的参与者，从第三次研究检查（2005 - 2008年；基线）开始随访至2018年3月。使用降秩回归（RRR）和偏最小二乘回归（PLS）确定基线时的DPs。反应变量为年龄和体重指数调整后的腰围（WC）以及年龄调整后的内脏脂肪指数（VAI）。
RRR和PLS分别保留了两种和三种DPs。每种方法的第一种模式主要以调整后的WC为特征（RRR：10.8%，PLS：8.6%）；它们均与CVD风险无关。RRR的第二种模式和PLS的第三种模式主要由调整后的VAI解释（RRR：3.3，PLS：2.1%）。在调整CVD危险因素后，RRR模式2的第二和第三三分位数中CVD的风险比[95%置信区间（CI）]分别为1.76（1.15，2.69）和1.55（1.00，2.43），而第一三分位数为对照（-趋势：0.058）。这种模式对非叶菜类蔬菜、泡菜、炒蔬菜和面包有高正负荷，对鸡蛋、蛋糕、黄油、果酱 - 蜂蜜、红肉、家禽、鱼、果汁、非发酵乳制品和水果有高负负荷。PLS模式3得分每增加一个标准差，CVD风险高19%（95%CI = 3 - 38%）。在该模式的三分位数中也观察到这种正相关（p - 趋势：0.032）。这种模式的特征是叶菜类蔬菜、非叶菜类蔬菜、内脏肉、软饮料、橄榄油、泡菜、炒蔬菜和面包的摄入量高，而饼干、蛋糕、黄油、鸡蛋和非发酵乳制品的摄入量低。
对于RRR和PLS方法，均识别出一种与内脏相关且与CVD呈正相关的DPs。这两种模式有适度的相关性。与RRR衍生的模式相比，PLS生成的模式在食物组中解释的变异更多，且与CVD关联的证据更强。
