[Association of nutrient patterns with serum uric acid in elderly across four Chinese provinces from 2018 to 2019].

Pengfeng Qu, Zhiru Wang, Liusen Wang, Weiyi Li, Hongru Jiang, Jiguo Zhang, Huijun Wang, Bing Zhang, Junhua Han, Aidong Liu, Zhihong Wang
{"title":"[Association of nutrient patterns with serum uric acid in elderly across four Chinese provinces from 2018 to 2019].","authors":"Pengfeng Qu, Zhiru Wang, Liusen Wang, Weiyi Li, Hongru Jiang, Jiguo Zhang, Huijun Wang, Bing Zhang, Junhua Han, Aidong Liu, Zhihong Wang","doi":"10.19813/j.cnki.weishengyanjiu.2025.02.008","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To investigate the relationship between nutrient patterns and serum uric acid levels in the elderly population.</p><p><strong>Methods: </strong>A total of 6288 elderly individuals aged 65 and above were analyzed from the Community-based Cohort Study on Nervous System Diseases baseline survey conducted from 2018 to 2021. Food frequency questionnaires were used to estimate the average daily intake of various foods per person in the past year, based on the frequency and quantity of food consumed per occasion. The average daily consumption of cooking oil and condiments per person was estimated by considering the average monthly household usage of these items and the number of meals prepared at home. Based on the food weights in Dietary Guidelines: Scientific Evidence and Methodological Studies and Chinese Food Composition, daily energy and nutrients intakes were calculated. Nutrient patterns for 24 nutrients, including macronutrients, vitamins and minerals, were extracted using principal component analysis. Quartile regression models were used to analyze the relationship between nutrient patterns and fasting serum uric acid levels.</p><p><strong>Results: </strong>Male elderly, individuals aged ≥75 years, living in rural areas, with junior high school education or above, high income, smokers, drinkers, elderly with low physical activity level, high body mass index(BMI) value or having chronic diseases had significantly higher serum uric acid levels(P&lt;0.05). Four nutrient patterns were extracted: the &apos;carbohydrate-vitamin B_1 pattern&apos;, the &apos;vitamin A-vitamin C pattern&apos;, the &apos;unsaturated fatty acid-vitamin E pattern&apos;, and the &apos;cholesterol pattern&apos;. Each nutrient pattern was divided into four quartiles, with Q1 as the reference. The &apos;unsaturated fatty acid-vitamin E pattern&apos; showed a negative correlation between Q4 and serum uric acid levels at the P10, P25, P50, and P75 quartiles(β-values and 95%CIs:-8.01(-15.55--0.48), -11.33(-17.77--4.89), -15.35(-18.39--5.35), -8.94(-17.46--0.41), P_(trend)&lt;0.05); At the P25 percentile of serum uric acid levels, Q2, Q3, and Q4 were negatively correlated with serum uric acid levels(β-values and 95%CIs:-6.28(-12.49--0.06), -6.86(-12.67--1.06), -11.33(-17.77--4.89), respectively, P_(trend)&lt;0.05). At the P50 percentile of serum uric acid levels, Q3 and Q4 were negatively correlated with blood uric acid levels(β-values and 95%CIs:-7.64(-14.39--0.89), -11.87(-18.39--5.35), respectively, P_(trend)&lt;0.05).</p><p><strong>Conclusion: </strong>The &apos;unsaturated fatty acid-vitamin E pattern&apos; model had a greater impact on intermediate and lower serum uric acid levels in the elderly population, suggesting that targeted dietary interventions may have a lowering effect on intermediate and lower serum uric acid levels.</p>","PeriodicalId":57744,"journal":{"name":"卫生研究","volume":"54 2","pages":"222-228"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"卫生研究","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.19813/j.cnki.weishengyanjiu.2025.02.008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: To investigate the relationship between nutrient patterns and serum uric acid levels in the elderly population.

Methods: A total of 6288 elderly individuals aged 65 and above were analyzed from the Community-based Cohort Study on Nervous System Diseases baseline survey conducted from 2018 to 2021. Food frequency questionnaires were used to estimate the average daily intake of various foods per person in the past year, based on the frequency and quantity of food consumed per occasion. The average daily consumption of cooking oil and condiments per person was estimated by considering the average monthly household usage of these items and the number of meals prepared at home. Based on the food weights in Dietary Guidelines: Scientific Evidence and Methodological Studies and Chinese Food Composition, daily energy and nutrients intakes were calculated. Nutrient patterns for 24 nutrients, including macronutrients, vitamins and minerals, were extracted using principal component analysis. Quartile regression models were used to analyze the relationship between nutrient patterns and fasting serum uric acid levels.

Results: Male elderly, individuals aged ≥75 years, living in rural areas, with junior high school education or above, high income, smokers, drinkers, elderly with low physical activity level, high body mass index(BMI) value or having chronic diseases had significantly higher serum uric acid levels(P<0.05). Four nutrient patterns were extracted: the 'carbohydrate-vitamin B_1 pattern', the 'vitamin A-vitamin C pattern', the 'unsaturated fatty acid-vitamin E pattern', and the 'cholesterol pattern'. Each nutrient pattern was divided into four quartiles, with Q1 as the reference. The 'unsaturated fatty acid-vitamin E pattern' showed a negative correlation between Q4 and serum uric acid levels at the P10, P25, P50, and P75 quartiles(β-values and 95%CIs:-8.01(-15.55--0.48), -11.33(-17.77--4.89), -15.35(-18.39--5.35), -8.94(-17.46--0.41), P_(trend)<0.05); At the P25 percentile of serum uric acid levels, Q2, Q3, and Q4 were negatively correlated with serum uric acid levels(β-values and 95%CIs:-6.28(-12.49--0.06), -6.86(-12.67--1.06), -11.33(-17.77--4.89), respectively, P_(trend)<0.05). At the P50 percentile of serum uric acid levels, Q3 and Q4 were negatively correlated with blood uric acid levels(β-values and 95%CIs:-7.64(-14.39--0.89), -11.87(-18.39--5.35), respectively, P_(trend)<0.05).

Conclusion: The 'unsaturated fatty acid-vitamin E pattern' model had a greater impact on intermediate and lower serum uric acid levels in the elderly population, suggesting that targeted dietary interventions may have a lowering effect on intermediate and lower serum uric acid levels.

[2018 - 2019年中国四省老年人营养模式与血清尿酸的关系]。
目的:探讨老年人营养模式与血清尿酸水平的关系。方法:对2018 - 2021年社区神经系统疾病队列研究基线调查中65岁及以上老年人6288例进行分析。进食频率调查问卷是根据每次进食的频率和数量,估计过去一年中每人每天平均摄取各种食物。人均每日食用油及调味品的消耗量,是根据每月平均家庭用量及在家做饭的次数来估计的。根据《膳食指南:科学依据和方法学研究》和《中国食物成分》中的食物权重,计算每日能量和营养素摄入量。采用主成分分析法提取了包括常量营养素、维生素和矿物质在内的24种营养素的营养模式。采用四分位数回归模型分析营养模式与空腹血清尿酸水平之间的关系。结果:男性老年人、年龄≥75岁、生活在农村、初中及以上文化程度、高收入、吸烟、饮酒、体力活动水平低、身体质量指数(BMI)值高、患有慢性病的老年人血清尿酸水平显著升高(P<0.05)。提取四种营养模式:碳水化合物-维生素B_1模式&apos;维生素a -维生素C模式&apos;不饱和脂肪酸-维生素E模式&apos;和胆固醇模式&apos。每种营养模式分为四个四分位数,以Q1为参考。不饱和脂肪酸-维生素E模式在P10、P25、P50和P75四分位数,Q4与血清尿酸水平呈负相关(β值和95% ci:-8.01(-15.55—0.48)、-11.33(-17.77—4.89)、-15.35(-18.39—5.35)、-8.94(-17.46—0.41),P_(趋势)<0.05);在血清尿酸水平的P25百分位数上,Q2、Q3和Q4与血清尿酸水平呈负相关(β值和95% ci分别为-6.28(-12.49—0.06)、-6.86(-12.67—1.06)、-11.33(-17.77—4.89),P_(趋势)<0.05)。在血清尿酸水平的P50百分位数上,Q3和Q4与血尿酸水平呈负相关(β值和95% ci分别为-7.64(-14.39—0.89)、-11.87(-18.39—5.35),P_(趋势)<0.05)。结论:不饱和脂肪酸-维生素E模式;模型对老年人群中低血清尿酸水平的影响较大,提示有针对性的饮食干预可能对中低血清尿酸水平有降低作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
8734
期刊介绍:
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信