卫生研究

目的 了解老年人群营养素模式与血尿酸水平的关系。方法 选取“神经系统疾病专病社区队列研究(2018—2021年)”基线调查6288名65岁及以上老年人作为研究对象。采用食物频率调查法收集过去一年的食物消费频率和消费量，以及家庭平均每月食用油和调味品消费情况，计算平均每人每日不同食物、食用油和调味品消费量。利用《膳食指南科学证据和方法学研究》中食物组权重和单一食物权重，结合《中国食物成分表》,计算平均每人每日能量和营养素的摄入量；利用主成分分析法对纳入的宏量营养素、维生素和矿物质等24种营养素提取营养素模式。采用分位数回归模型分析不同营养素模式与空腹血尿酸水平的关系。结果 老年男性、≥75岁、农村、初中及以上学历、高收入、有吸烟饮酒习惯、低身体活动水平、高体质指数者血尿酸水平较高(P<0.05)。共提取“碳水化合物-维生素B₁模式”、“维生素A-维生素C模式”、“不饱和脂肪酸-维生素E模式”、“胆固醇模式”4种营养素模式。将每一种营养素模式评分四等分，并以Q1为参照。“不饱和脂肪酸-维生素E模式”最高四分位评分与P10、P25、P50、P75分位血尿酸水平均呈负相关[β(95%CI)]分别为：-8.01(-15.55～-0.48),-11.33(-17.77～-4.89),11.87(-18.39～-5.35),-8.94(-17.46～-0.41),P_趋势<0.05;在血尿酸水平P25分位时，Q2、Q3、Q4与血尿酸水平呈负相关关系[β(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;在血尿酸水平P50分位时，Q3、Q4与血尿酸水平呈负相关关系[β(95%CI)]分别：-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”对老年人群的中等及以下血尿酸水平影响较大，提示有针对性的膳食干预可能对中等及以下血尿酸水平有降低作用。

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 B₁ 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.