Ahern Mary M, Stinson Emma J, Votruba Susanne B, Krakoff Jonathan, Tasevska Natasha
Obesity and Diabetes Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85016, USA.
College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
Nutrients. 2024 Feb 23;16(5):610. doi: 10.3390/nu16050610.
Accurately measuring dietary sugars intake in large-scale epidemiological studies is necessary to understand dietary sugars' true impact on health. Researchers have developed a biomarker that can be used to assess total sugars intake. Our objective is to test this biomarker in diverse populations using an ad libitum intake protocol. Healthy adult participants ( = 63; 58% Indigenous Americans/Alaska Natives; 60% male; BMI (mean ± SD) = 30.6 ± 7.6 kg.m) were admitted for a 10-day inpatient stay. On day 2, body composition was measured by DXA, and over the last 3 days, ad libitum dietary intake was measured using a validated vending machine paradigm. Over the same days, participants collected daily 24 h urine used to measure sucrose and fructose. The 24 h urinary sucrose and fructose biomarker (24hruSF) (mg/d) represents the sum of 24 h urinary sucrose and fructose excretion levels. The association between the 3-day mean total sugars intake and log 24uSF level was assessed using the Pearson correlation. A linear mixed model regressing log-biomarker on total sugars intake was used to investigate further the association between biomarker, diet, and other covariates. Mean (S.D.) total sugars intake for the group was 197.7 g/d (78.9). Log 24uSF biomarker was moderately correlated with total sugars intake ( = 0.33, = 0.01). In stratified analyses, the correlation was strongest in females ( = 0.45, = 0.028), the 18-30 age group ( = 0.44, = 0.079), Indigenous Americans ( = 0.51, = 0.0023), and the normal BMI category ( = 0.66, = 0.027). The model adjusted for sex, age, body fat percent, and race/ethnicity demonstrated a statistically significant association between 24uSF and total sugars intake (β = 0.0027, < 0.0001) and explained 31% of 24uSF variance (marginal R = 0.31). Our results demonstrated a significant relationship between total sugars intake and the 24uSF biomarker in this diverse population. However, the results were not as strong as those of controlled feeding studies that investigated this biomarker.
在大规模流行病学研究中准确测量膳食糖摄入量对于了解膳食糖对健康的真正影响至关重要。研究人员开发了一种可用于评估总糖摄入量的生物标志物。我们的目标是使用自由进食方案在不同人群中测试这种生物标志物。健康成年参与者（n = 63；58%为美洲原住民/阿拉斯加原住民；60%为男性；BMI（均值±标准差）= 30.6±7.6 kg/m²）入院进行为期10天的住院治疗。在第2天，通过双能X线吸收法测量身体成分，在最后3天，使用经过验证的自动售货机模式测量自由膳食摄入量。在同一天，参与者收集每日24小时尿液用于测量蔗糖和果糖。24小时尿蔗糖和果糖生物标志物（24hruSF）（mg/d）代表24小时尿蔗糖和果糖排泄水平的总和。使用Pearson相关性评估3天平均总糖摄入量与log 24uSF水平之间的关联。使用将log生物标志物回归到总糖摄入量的线性混合模型进一步研究生物标志物、饮食和其他协变量之间的关联。该组的平均（标准差）总糖摄入量为197.7 g/d（78.9）。Log 24uSF生物标志物与总糖摄入量呈中度相关（r = 0.33，P = 0.01）。在分层分析中，相关性在女性中最强（r = 0.45，P = 0.028），在18 - 30岁年龄组中（r = 0.44，P = 0.079），在美洲原住民中（r = 0.51，P = 0.0023），以及在正常BMI类别中（r = 0.66，P = 0.027）。对性别、年龄、体脂百分比和种族/族裔进行调整的模型显示24uSF与总糖摄入量之间存在统计学显著关联（β = 0.0027，P < 0.0001），并解释了24uSF变异的31%（边际R² = 0.31）。我们的结果表明在这个多样化的人群中总糖摄入量与24uSF生物标志物之间存在显著关系。然而，结果不如研究该生物标志物的对照喂养研究的结果那么强。
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