加拿大超加工食品消费和心脏代谢风险:加拿大健康措施调查的横断面分析。

IF 3.9 2区 医学 Q2 NUTRITION & DIETETICS
Angelina Baric, Vasanti S Malik, Anthea Christoforou
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引用次数: 0

摘要

背景:超加工食品(UPF)占加拿大饮食的近50%。其他国家的研究已经开始涉及高upf摄入量和负面健康结果,包括体重指数、腰围、血压和不利的脂质谱。在加拿大,还没有对UPF消费与心脏代谢风险之间的关系进行人口水平的检查。方法:根据加拿大健康措施调查(2016/17和2018/19),本研究调查加拿大人(19-79岁,n = 6517) UPF消费与心脏代谢危险因素的关系。通过食物频率问卷收集的膳食数据,采用NOVA分类系统对食品加工程度进行评分,并将其分类为UPF或非UPF。参与者根据UPF的每日摄入量被分成四分位数。通过家庭问卷收集社会人口学和生活方式变量,并在诊所访问期间测量心脏代谢结果。多变量线性回归分析分别评估了心脏代谢危险因素与UPF四分位数之间的关系,同时调整了各种社会人口统计学和生活方式变量。敏感性分析还调整了水果和蔬菜摄入量(每天食用份数),以确定饮食质量对这一关系的影响。所有分析都经过加权处理,以确保国家代表性。结果:每天的UPF摄入量从最低的1.2到最高的5.8不等。与UPF消费最低的四分之一相比,最高的人更可能是男性,在收入最低的四分之一中,黑人或白人,家庭教育程度较低,体育活动和久坐时间较多。调整后,UPF消耗与BMI、WC、舒张压、HBA1C、c反应蛋白、白细胞(WBC)、空腹甘油三酯(TG)和空腹胰岛素呈正相关。水果和蔬菜摄入量减弱了与所有结果的关联,而BMI、WC、WBC和TG仍然与UPF消耗的增加显著相关。结论:这项研究是加拿大第一个针对不同心脏代谢风险因素的人群水平UPF摄入量的研究,并为越来越多的文献证明UPF摄入对健康有害的影响提供了新的证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ultra-processed food consumption and cardiometabolic risk in Canada: a cross-sectional analysis of the Canadian health measures survey.

Background: Ultra-processed food (UPF) contributes to nearly 50% of Canadians' diets. Research in other countries has begun to implicate high intakes of UPFs and negative health outcomes, including body mass index, waist circumference, blood pressure, and unfavourable lipid profiles. There have been no population level examinations of the relationship between UPF consumption and cardiometabolic risk in Canada.

Methods: Drawing on the Canadian Health Measures Survey (2016/17 and 2018/19), this study investigates the relationship between UPF consumption and cardiometabolic risk factors among Canadians (ages 19-79, n = 6517). Dietary data collected by Food Frequency Questionnaire was classified as UPF or not using the NOVA classification system which scores foods by degree of processing. Participants were grouped into quartiles based on the daily servings of UPF. Sociodemographic and lifestyle variables were collected via household questionnaire and cardiometabolic outcomes were measured during a clinic visit. Multivariable linear regression analyses separately assessed the association between cardiometabolic risk factors and UPF quartiles while adjusting for various sociodemographic and lifestyle variables. Sensitivity analyses additionally adjusted for fruit and vegetable intake (servings/day) to determine the effect of diet quality on this relationship. All analyses were weighted to ensure national representativeness.

Results: UPF servings per day ranged from 1.2 in the lowest and 5.8 in the highest quartile. Compared to the lowest quartiles of UPF consumption, those in the highest were more likely to be male, in the lowest income quartile, Black or White, have lower household education, and higher physical activity and sedentary time. After adjustments, UPF consumption was positively associated with BMI, WC, diastolic BP, HBA1C, c-reactive protein, white blood cells (WBC), fasting triglycerides (TG), and fasting insulin. Fruit and vegetable intake attenuated the association for all outcomes, while BMI, WC, WBC, and TG remained significantly associated with increased UPF consumption.

Conclusion: This study is the first Canadian study looking at population level intakes of UPF across various cardiometabolic risk factors and adds to the growing body of literature demonstrating the detrimental health effects associated with UPF consumption.

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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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