Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
NutriAct - Competence Cluster Nutrition Research Berlin-Potsdam, Germany.
Am J Clin Nutr. 2018 Sep 1;108(3):576-586. doi: 10.1093/ajcn/nqy151.
In previous meta-analyses of prospective observational studies, we investigated the association between food groups and risk of chronic disease.
The aim of the present network meta-analysis (NMA) was to assess the effects of these food groups on intermediate-disease markers across randomized intervention trials.
Literature searches were performed until January 2018. The following inclusion criteria were defined a priori: 1) randomized trial (≥4 wk duration) comparing ≥2 of the following food groups: refined grains, whole grains, nuts, legumes, fruits and vegetables, eggs, dairy, fish, red meat, and sugar-sweetened beverages (SSBs); 2) LDL cholesterol and triacylglycerol (TG) were defined as primary outcomes; total cholesterol, HDL cholesterol, fasting glucose, glycated hemoglobin, homeostasis model assessment insulin resistance, systolic and diastolic blood pressure, and C-reactive protein were defined as secondary outcomes. For each outcome, a random NMA was performed, and for the ranking, the surface under the cumulative ranking curves (SUCRA) was determined.
A total of 66 randomized trials (86 reports) comparing 10 food groups and enrolling 3595 participants was identified. Nuts were ranked as the best food group at reducing LDL cholesterol (SUCRA: 93%), followed by legumes (85%) and whole grains (70%). For reducing TG, fish (97%) was ranked best, followed by nuts (78%) and red meat (72%). However, these findings are limited by the low quality of the evidence. When combining all 10 outcomes, the highest SUCRA values were found for nuts (66%), legumes (62%), and whole grains (62%), whereas SSBs performed worst (29%).
The present NMA provides evidence that increased intake of nuts, legumes, and whole grains is more effective at improving metabolic health than other food groups. For the credibility of diet-disease relations, high-quality randomized trials focusing on well-established intermediate-disease markers could play an important role. This systematic review was registered at PROSPERO (www.crd.york.ac.uk/PROSPERO) as CRD42018086753.
在之前对前瞻性观察研究的荟萃分析中,我们研究了食物组与慢性病风险之间的关系。
本网络荟萃分析(NMA)的目的是评估这些食物组对随机干预试验中中间疾病标志物的影响。
文献检索截至 2018 年 1 月。预先定义了以下纳入标准:1)比较以下 2 种及以上食物组的随机试验(≥4 周):精制谷物、全谷物、坚果、豆类、水果和蔬菜、鸡蛋、乳制品、鱼类、红色肉类和含糖饮料(SSB);2)LDL 胆固醇和三酰甘油(TG)定义为主要结局;总胆固醇、高密度脂蛋白胆固醇、空腹血糖、糖化血红蛋白、稳态模型评估胰岛素抵抗、收缩压和舒张压以及 C 反应蛋白定义为次要结局。对于每个结局,进行随机 NMA,并对排名进行累积排序曲线下面积(SUCRA)的确定。
共确定了 66 项比较 10 种食物组且纳入 3595 名参与者的随机试验(86 份报告)。坚果被评为降低 LDL 胆固醇的最佳食物组(SUCRA:93%),其次是豆类(85%)和全谷物(70%)。对于降低 TG,鱼(97%)排名最佳,其次是坚果(78%)和红色肉类(72%)。然而,这些发现受到证据质量低的限制。当结合所有 10 个结局时,坚果(66%)、豆类(62%)和全谷物(62%)的 SUCRA 值最高,而 SSB 的表现最差(29%)。
本 NMA 提供的证据表明,增加坚果、豆类和全谷物的摄入量比其他食物组更能有效改善代谢健康。对于饮食与疾病关系的可信度,关注既定中间疾病标志物的高质量随机试验可能会发挥重要作用。本系统评价已在 PROSPERO(www.crd.york.ac.uk/PROSPERO)上注册,注册号为 CRD42018086753。