Validity Coefficient of Repeated Measurements of Urinary Marker of Sugar Intake Is Comparable to Urinary Nitrogen as Marker of Protein Intake in Free-living Subjects

Dietary biomarkers-an update on their validity and applicability in epidemiological studies

The aim of this literature review was to identify and provide a summary update on the validity and applicability of the most promising dietary biomarkers reflecting the intake of important foods in the Western diet for application in epidemiological studies. Many dietary biomarker candidates, reflecting intake of common foods and their specific constituents, have been discovered from intervention and observational studies in humans, but few have been validated. The literature search was targeted for biomarker candidates previously reported to reflect intakes of specific food groups or components that are of major importance in health and disease. Their validity was evaluated according to 8 predefined validation criteria and adapted to epidemiological studies; we summarized the findings and listed the most promising food intake biomarkers based on the evaluation. Biomarker candidates for alcohol, cereals, coffee, dairy, fats and oils, fruits, legumes, meat, seafood, sugar, tea, and vegetables were identified. Top candidates for all categories are specific to certain foods, have defined parent compounds, and their concentrations are unaffected by nonfood determinants. The correlations of candidate dietary biomarkers with habitual food intake were moderate to strong and their reproducibility over time ranged from low to high. For many biomarker candidates, critical information regarding dose response, correlation with habitual food intake, and reproducibility over time is yet unknown. The nutritional epidemiology field will benefit from the development of novel methods to combine single biomarkers to generate biomarker panels in combination with self-reported data. The most promising dietary biomarker candidates that reflect commonly consumed foods and food components for application in epidemiological studies were identified, and research required for their full validation was summarized.

Twenty-Four-Hour Urinary Sugars Biomarker in a Vending Machine Intake Paradigm in a Diverse Population

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 (n = 63; 58% Indigenous Americans/Alaska Natives; 60% male; BMI (mean ± SD) = 30.6 ± 7.6 kg.m2) 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 (r = 0.33, p = 0.01). In stratified analyses, the correlation was strongest in females (r = 0.45, p = 0.028), the 18-30 age group (r = 0.44, p = 0.079), Indigenous Americans (r = 0.51, p = 0.0023), and the normal BMI category (r = 0.66, p = 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, p < 0.0001) and explained 31% of 24uSF variance (marginal R2 = 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.

Relative validity of habitual sugar and low/no-calorie sweetener consumption assessed by food frequency questionnaire, multiple 24-h dietary recalls and urinary biomarkers: an observational study within the SWEET project

BACKGROUND

Studies investigating associations between sweeteners and health yield inconsistent results, possibly due to subjective self-report dietary assessment methods.

OBJECTIVES

We compared the performance of a food frequency questionnaire (FFQ), multiple 24-h dietary recalls (24hRs), and urinary biomarkers to estimate intake of sugars and low/no-calorie sweeteners (LNCSs).

METHODS

Participants (n = 848, age 54 ± 12 y) from a 2-y observational study completed 1 semiquantitative FFQ and ≥ 3 nonconsecutive 24hRs. Both methods assessed intake of sugars (mono- and disaccharides, sucrose, fructose, free and added sugars) and sweetened foods and beverages (sugary foods, fruit juice, and sugar or LNCS-containing beverages [sugar-sweetened beverages and low/no-calorie sweetened beverages (LNCSBs)]); 24hRs also included LNCS-containing foods and tabletop sweeteners (low/no-calorie sweetened foods [LNCSFs]). Urinary excretion of sugars (fructose+sucrose) and LNCSs (acesulfame K+sucralose+steviol glucuronide+cyclamate+saccharin) were simultaneously assessed using ultrapressure liquid chromatography coupled to tandem mass spectrometry in 288 participants with 3 annual 24-h urine samples. Methods were compared using, amongst others, validity coefficients (correlations corrected for measurement error).

RESULTS

Median (interquartile range) FFQ intakes ranged from 0 (0-7) g/d for LNCSBs to 94 (73-117) g/d for mono- and disaccharides. LNCSB use was reported by 32% of participants. Median LNCSB+LNCSF intake using 24hRs was 1 (0-50) g/d and reported by 58%. Total sugar excretions were detected in 100% of samples [56 (37-85) mg/d] and LNCSs in 99% of urine samples [3 (1-10) mg/d]. Comparing FFQ against 24hRs showed VCs ranging from 0.38 (fruit juice) to 0.74 (LNCSB). VCs for comparing FFQ with urinary excretions were 0.25 to 0.29 for sugars and 0.39 for LNCSBs; for 24hR they amounted to 0.31-0.38 for sugars, 0.37 for LNCSBs, and 0.45 for LNCSFs.

CONCLUSIONS

The validity of the FFQ against 24hRs for the assessment of sugars and LNCSBs ranged from moderate to good. Comparing self-reports and urine excretions showed moderate agreement but highlighted an important underestimation of LNCS exposure using self-reports.

Current perspectives on global sugar consumption: definitions, recommendations, population intakes, challenges and future direction

Currently, there is considerable emphasis on the relationship between dietary sugar consumption and various health outcomes, with some countries and regions implementing national sugar reduction campaigns. This has resulted in significant efforts to quantify dietary sugar intakes, to agree on terms to describe dietary sugars and to establish associated recommendations. However, this information is infrequently collated on a global basis and in a regularised manner. The present review provides context regarding sugar definitions and recommendations. It provides a global review of the available data regarding dietary sugar intake, considering forms such as total, free and added sugars. A comprehensive breakdown of intakes is provided by age group, country and sugar form. This analysis shows that free sugar intakes as a percentage of total energy (%E) are the highest for children and adolescents (12-14%E) and the lowest for older adults (8%E). This trend across lifecycle stages has also been observed for added sugars. The available data also suggest that, while some reductions in sugar intake are observed in a few individual studies, overall intakes of free/added sugars remain above recommendations. However, any wider conclusions are hampered by a lack of detailed high-quality data on sugar intake, especially in developing countries. Furthermore, there is a need for harmonisation of terms describing sugars (ideally driven by public health objectives) and for collaborative efforts to ensure that the most up-to-date food composition data are used to underpin recommendations and any estimates of intake or modelling scenarios.

Development and validation of a UPLC-MS/MS method for the quantification of sugars and non-nutritive sweeteners in human urine

High-intensity sweeteners ('sweeteners'), such as sucralose, saccharine, acesulfame, cyclamate and steviol, are replacing sugars in many food products, but biomarker-based data on their population-wide exposure, as well as analytical methods that can quantify urinary concentrations of sugars and sweeteners simultaneously, are lacking. Here, we developed and validated an ultra-pressure liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) method to quantify glucose, sucrose, fructose, sucralose, saccharine, acesulfame, cyclamate and steviol glucuronide in human urine. Urine samples were prepared by a simple dilution step containing the internal standards in water and methanol. Separation was achieved on a Shodex Asahipak NH2P-40 hydrophilic interaction liquid chromatography (HILIC) column using gradient elution. The analytes were detected using electrospray ionization in negative ion mode, and selective reaction monitoring was optimized using the [M-H]- ions. Calibration curves ranged between 34 and 19,230 ng/mL for glucose and fructose, and 1.8 to 1,026 ng/mL for sucrose and the sweeteners. The method has acceptable accuracy and precision, which depends on the application of appropriate internal standards. Storage of urine samples in lithium monophosphate gives the best overall analytical performance, and storage at room temperature without any preservatives should be avoided since this leads to reduced glucose and fructose concentrations. With the exception of fructose, all analytes were stable throughout 3 freeze-thaw cycles. The validated method was applied to human urine samples, demonstrating quantifiable concentrations of the analytes which were in the expected range. It is concluded that the method has acceptable performance to quantitatively determine dietary sugars and sweeteners in human urine.

Study protocol of the sweet tooth study, randomized controlled trial with partial food provision on the effect of low, regular and high dietary sweetness exposure on sweetness preferences in Dutch adults

BACKGROUND

Several health organizations recommend lowering the consumption of sweet-tasting foods. The rationale behind this recommendation is that a lower exposure to sweet foods may reduce preferences for sweet tasting foods, thus lowering sugar and energy intake, and in turn aiding in obesity prevention. However, empirical data supporting this narrative are lacking. In fact, relatively little is known about the contribution of long-term sweet taste exposure on one's sweetness preferences.

METHODS

The primary objective of this randomized controlled trial is to assess the effect of low, regular and high dietary sweetness exposure on preference for sweet foods and beverages, and to compare these effects between intervention groups. One hundred and eighty adults aged 18-65 years with a BMI of 18.5-30.0 kg/m² will be recruited and randomly allocated to either: low dietary sweetness exposure (LSE) (10-15% daily energy from sweet tasting foods), regular dietary sweetness exposure (RSE) (25-30% daily energy from sweet tasting foods), or high dietary sweetness exposure (HSE) (40-45% daily energy from sweet tasting foods), for 6 months, followed by a 4-month follow up. Intervention foods are provided ad libitum, covering approximately 50% of the daily number of food items, to include sugar-sweetened, low-calorie-sweetener-sweetened and non-sweet foods. The primary outcome measure is the difference in change in sweetness preference from baseline to 6 months between intervention groups. Secondary outcomes include: change in sweet taste preferences at different time-points; taste intensity perception; behavioral outcomes: food choice and intake, sweet-liker type, food cravings, dietary taste preferences and dietary taste patterns; anthropometric outcomes: body composition, waist-hip circumference, body weight; and biochemical outcomes: glucose variability and biomarkers related to CVD and diabetes.

DISCUSSION

This study will generate important data on the effect of dietary sweetness exposure on sweetness preferences in terms of effect size and change, duration of change and its impact on food intake, body weight status and associated health outcomes.

TRIAL REGISTRATION

The study protocol has been registered on ClinicalTrials.gov (ID no. NCT04497974, Registered 4 August 2020, https://clinicaltrials.gov/ct2/show/NCT04497974 ) and approved by Wageningen's Medical Ethical Committee (ABR no. NL72134).

Establishing 24-Hour Urinary Sucrose Plus Fructose as a Predictive Biomarker for Total Sugars Intake

BACKGROUND

Twenty-four-hour urinary sucrose and fructose (24uSF) has been studied as a biomarker of total sugars intake in two feeding studies conducted in the United Kingdom (UK) and Arizona (AZ). We compare the biomarker performance in these populations, testing whether it meets the criteria for a predictive biomarker.

METHODS

The UK and AZ feeding studies included 13 and 98 participants, respectively, aged 18 to 70 years, consuming their usual diet under controlled conditions. Linear mixed models relating 24uSF to total sugars and personal characteristics were developed in each study and compared. The AZ calibrated biomarker equation was applied to generate biomarker-estimated total sugars intake in UK participants. Stability of the model across AZ study subpopulations was also examined.

RESULTS

Model coefficients were similar between the two studies [e.g., log(total sugars): UK 0.99, AZ 1.03, P = 0.67], as was the ratio of calibrated biomarker person-specific bias to between-person variance (UK 0.32, AZ 0.25, P = 0.68). The AZ equation estimated UK log(total sugar intakes) with mean squared prediction error of 0.27, similar to the AZ study estimate (0.28). Within the AZ study, the regression coefficients of log(total sugars) were similar across age, gender, and body mass index subpopulations.

CONCLUSIONS

Similar model coefficients in the two studies and good prediction of UK sugar intakes by the AZ equation suggest that 24uSF meets the criteria for a predictive biomarker. Testing the biomarker performance in other populations is advisable.

IMPACT

Applications of the 24uSF biomarker will enable improved assessment of the role of sugars intake in risk of chronic disease, including cancer. See related commentary by Prentice, p. 1151.