中国成年人膳食抗氧化能力与 2 型糖尿病之间的关系：一项基于人群的横断面研究。

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2024-03-29 DOI:10.1186/s12986-024-00786-z

Xiaoxia Li, Yixuan Xue, Yadi Zhang, Qingan Wang, Jiangwei Qiu, Jiaxing Zhang, Chan Yang, Yi Zhao, Yuhong Zhang

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引用次数: 0

摘要

背景：较高的膳食抗氧化剂摄入量与较低的2型糖尿病（T2DM）风险有关。然而，通过膳食抗氧化剂质量评分（DAQS）和膳食总抗氧化剂能力（DTAC）评估膳食抗氧化剂的总体能力与T2DM风险的关系，尤其是在膳食相对单一的人群中，很少有研究对其进行全面检测。本研究旨在评估 DAQS、DTAC 与中国农村成年人 T2DM 的相关性：方法：分析了中国西北地区自然人群队列中 12,467 名参与者的数据：方法：分析了来自中国西北地区自然人群队列：宁夏项目的 12,467 名参与者的数据。采用有效的半定量食物频率问卷评估膳食摄入量。根据维生素 A、C 和 E、锌和硒的摄入量计算 DAQS。DTAC 采用血浆铁还原能力测定法进行估算。采用逻辑回归模型评估 DAQS 和 DTAC 与 T2DM 风险的相关性。使用限制性三次样条来评估 DTAC 与 T2DM 之间的潜在非线性关系：结果：1238 名参与者（9.9%）出现了 T2DM。调整混杂因素后，与 DAQS 的最低分层（T1）相比，T2 和 T3 的 T2DM 发生几率比（ORs）分别为 1.03（95% CI 0.82-1.30）和 0.85（95% CI 0.68-1.06）（P = 0.010）。与 T1 相比，最高 T3 的 T2DM ORs 为 0.78（95% CI 0.67-0.91，P-趋势 = 0.008），维生素 A 为 1.34（95% CI 1.15-1.56，P-趋势结论：较高的 DAQS 和 DATC 与较低的 T2DM 风险相关，表明食用富含抗氧化剂的食物可降低 T2DM 风险。

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Association between dietary antioxidant capacity and type 2 diabetes mellitus in Chinese adults: a population-based cross-sectional study.

Background: Higher intakes of dietary antioxidants have been linked to a lower type 2 diabetes mellitus (T2DM) risk. However, few studies have comprehensively examined the overall dietary antioxidant capacity, assessed by dietary antioxidant quality scores (DAQS) and dietary total antioxidant capacity (DTAC), related to T2DM risk, especially in populations consuming relatively monotonous diets. This study aimed to evaluate the associations of DAQS, DTAC, and T2DM among rural Chinese adults.

Methods: Data from 12,467 participants from the Natural Population Cohort of Northwest China: Ningxia Project was analyzed. Dietary intake was assessed using a validated semi-quantitative food frequency questionnaire. DAQS were calculated based on vitamins A, C, and E, zinc (Zn), and selenium (Se) intake. DTAC was estimated using the ferric-reducing ability of plasma assay. Logistic regression models were used to evaluate the associations of DAQS and DTAC with T2DM risk. Restricted cubic splines were used to assess potential non-linear relationships between DTAC and T2DM.

Results: T2DM was observed in 1,238 (9.9%) participants. After adjusting for confounders, compared to the lowest tertiles (T1) of DAQS, the odds ratios (ORs) for T2DM were 1.03 (95% CI 0.82-1.30) in T2 and 0.85 (95% CI 0.68-1.06) in T3 (P = 0.010). Compared to T1, the ORs for T2DM in the highest T3 were 0.78 (95% CI 0.67-0.91, P-trend = 0.008) for vitamin A, 1.34 (95% CI 1.15-1.56, P-trend < 0.001) for vitamin E, 0.83 (95% CI 0.71-0.97, P-trend = 0.007) for Se, and 0.86 (95% CI 0.74-1.01, P-trend = 0.033) for Zn. Compared to the lowest quartile(Q1) of DTAC, the OR in the highest Q4 was 0.96 (95% CI 0.80-1.17, P-trend = 0.024) for T2DM. A non-linear relationship was observed between DATC and T2DM.

Conclusion: Higher DAQS and DATC were associated with a lower T2DM risk, suggesting that consuming antioxidant-rich foods may reduce the T2DM risk.

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来源期刊

Nutrition & Metabolism 医学-营养学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.