Dietary carotenoids and breast cancer risk: evidence from a large population-based incident case-control study.

IF 4.1 2区 医学 Q2 NUTRITION & DIETETICS
Bahar Darouei, Torsten Bohn, Farhad Vahid, Reza Amani-Beni, Shaghayegh Haghjooy Javanmard, Kazem Zendehdel, Ibrahim Abdollahpour
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引用次数: 0

Abstract

Background: Although mechanistic studies suggest protective roles for carotenoids against breast cancer (BC), human studies yield inconsistent findings. Few have comprehensively evaluated dietary intake of individual and grouped carotenoids in relation to BC risk.

Methods: This population-based case-control study recruited 600 patients with newly diagnosed BC and 600 healthy controls. Dietary carotenoid intake was assessed using a validated 168-item food frequency questionnaire. The intake levels of α-carotene, β-carotene, β-cryptoxanthin, lutein/zeaxanthin, lycopene, astaxanthin, phytoene, phytofluene, neoxanthin, violaxanthin, and total carotenoids were categorized into quartiles. Logistic regression models were employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for BC risk, controlling for potential confounders.

Results: Higher intake of lycopene, phytoene, phytofluene, total non-provitamin A and provitamin A, β-carotene, lutein/zeaxanthin, as well as total carotenoids was significantly associated with reduced BC risk Lycopene showed the strongest inverse association (Q4 vs. Q1: OR = 0.23; 95% CI: 0.14-0.37). Total provitamin A (Q4 OR = 0.46; 95% CI: 0.29-0.75) and total non-provitamin A carotenoids (Q4 OR = 0.25; 95% CI: 0.15-0.41) also showed strong protective associations. Total carotenoid (Q4 OR = 0.34, 95% CI: 0.20-0.56, p < 0.001) intake also showed inverse associations across all quartiles. Conversely, α-carotene, β-cryptoxanthin, astaxanthin, neoxanthin, and violaxanthin displayed weaker or inconsistent associations.

Conclusion: These findings support an inverse association between dietary intake of specific carotenoids, particularly lycopene, lutein/zeaxanthin, and colorless carotenoids (phytoene and phytofluene) and BC risk. Promoting a carotenoid-rich diet may represent a feasible strategy for BC prevention.

Abstract Image

Abstract Image

饮食类胡萝卜素与乳腺癌风险:来自大型人群事件病例对照研究的证据
背景:虽然机制研究表明类胡萝卜素对乳腺癌(BC)有保护作用,但人类研究结果不一致。很少有人全面评估单独和分组类胡萝卜素的饮食摄入与BC风险的关系。方法:这项基于人群的病例对照研究招募了600名新诊断的BC患者和600名健康对照者。膳食类胡萝卜素摄入量评估使用一个有效的168项食物频率问卷。α-胡萝卜素、β-胡萝卜素、β-隐黄质、叶黄素/玉米黄质、番茄红素、虾青素、phytoene、phytofluene、新黄质、紫黄质和总类胡萝卜素的摄入水平按四分位数划分。采用Logistic回归模型估计BC风险的比值比(ORs)和95%置信区间(CIs),控制潜在混杂因素。结果:较高的番茄红素、植物烯、植物流感素、总非维生素原A和维生素原A、β-胡萝卜素、叶黄素/玉米黄质以及总类胡萝卜素摄入量与降低BC风险显著相关。番茄红素表现出最强的负相关(Q4 vs. Q1: OR = 0.23; 95% CI: 0.14-0.37)。总维生素原A (Q4 OR = 0.46; 95% CI: 0.29-0.75)和总非维生素原A类胡萝卜素(Q4 OR = 0.25; 95% CI: 0.15-0.41)也显示出很强的保护作用。总类胡萝卜素(Q4 OR = 0.34, 95% CI: 0.20-0.56, p)结论:这些发现支持特定类胡萝卜素,特别是番茄红素、叶黄素/玉米黄质和无色类胡萝卜素(植物烯和植物流感素)的饮食摄入与BC风险呈负相关。提倡富含类胡萝卜素的饮食可能是预防BC的可行策略。
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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
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.
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