Influence of an Intervention Targeting a Reduction in Sugary Beverage Intake on the δ13C Sugar Intake Biomarker in a Predominantly Obese, Health-disparate Sample

Overview

Journal Public Health Nutr

Publisher Cambridge University Press

Date 2016 Jun 15

PMID 27297740

Citations 17

Authors

Brenda M Davy

A Hope Jahren

Valisa E Hedrick

Wen You

Jamie M Zoellner

Affiliations

Soon will be listed here.

Abstract

Objective: Controversy exists surrounding the health effects of added sugar (AS) and sugar-sweetened beverage (SSB) intakes, primarily due to a reliance on self-reported dietary intake. The purpose of the current investigation was to determine if a 6-month intervention targeting reduced SSB intake would impact δ13C AS intake biomarker values.

Design: A randomized controlled intervention trial. At baseline and at 6 months, participants underwent assessments of anthropometrics and dietary intake. Fasting fingerstick blood samples were obtained and analysed for δ13C value using natural abundance stable isotope MS. Statistical analysis included descriptive statistics, correlational analyses and multilevel mixed-effects linear regression analysis using an intention-to-treat approach.

Setting: Rural Southwest Virginia, USA.

Subjects: Adults aged ≥18 years who consumed ≥200 kcal SSB/d (≥837 kJ/d) were randomly assigned to either the intervention (n 155) or a matched-contact group (n 146). Participants (mean age 42·1 (sd 13·4) years) were primarily female and overweight (21·5 %) or obese (57·0 %).

Results: A significant group by time difference in δ13C value was detected (P<0·001), with mean (sd) δ13C value decreasing in the intervention group (pre: -18·92 (0·65) ‰, post: -18·97 (0·65) ‰) and no change in the comparison group (pre: -18·94 (0·72) ‰, post: -18·92 (0·73) ‰). Significant group differences in weight and BMI change were also detected. Changes in biomarker δ13C values were consistent with changes in self-reported AS and SSB intakes.

Conclusions: The δ13C sugar intake biomarker assessed using fingerstick blood samples shows promise as an objective indicator of AS and SSB intakes which could be feasibly included in community-based research trials.

Citing Articles

Associations of Food Group Intakes with Serum Carbon Isotope Ratio Values in Youth: Results from 2 Prospective Pediatric Cohort Studies.

Cohen C, Peng M, Davy B, Perng W, Shankar K, Dabelea D J Nutr. 2024; 155(1):293-304.

PMID: 39510505 PMC: 11795691. DOI: 10.1016/j.tjnut.2024.10.052.

The Carbon Isotope Ratio as an Objective Biomarker of Added Sugar Intake: A Scoping Review of Current Evidence in Human Nutrition.

Tripicchio G, Smethers A, Johnson J, Olenginski J, OBrien D, Fisher J Adv Nutr. 2024; 15(9):100281.

PMID: 39094908 PMC: 11406090. DOI: 10.1016/j.advnut.2024.100281.

Kids SIPsmartER reduces sugar-sweetened beverages among Appalachian middle-school students and their caregivers: a cluster randomized controlled trial.

Zoellner J, You W, Porter K, Kirkpatrick B, Reid A, Brock D Int J Behav Nutr Phys Act. 2024; 21(1):46.

PMID: 38664715 PMC: 11046896. DOI: 10.1186/s12966-024-01594-7.

Components in downstream health promotions to reduce sugar intake among adults: a systematic review.

Azhar Hilmy S, Nordin N, Mohd Yusof M, Soh T, Yusof N Nutr J. 2024; 23(1):11.

PMID: 38233923 PMC: 10792802. DOI: 10.1186/s12937-023-00884-3.

Comparison of Total Body Vitamin A Stores Using Individual versus Population C-Natural Abundance of Serum Retinol in Preschool Children and Women Residing in 6 Diverse African Countries.

Gannon B, Sombie O, Zeba A, Medoua Nama G, Bekele T, Woldeyohannes M J Nutr. 2023; 153(4):949-957.

PMID: 36822237 PMC: 10367224. DOI: 10.1016/j.tjnut.2023.02.002.

References

Kahn R, Sievenpiper J . Dietary sugar and body weight: have we reached a crisis in the epidemic of obesity and diabetes?: we have, but the pox on sugar is overwrought and overworked. Diabetes Care. 2014; 37(4):957-62. DOI: 10.2337/dc13-2506. View

Hedrick V, Davy B, Wilburn G, Jahren A, Zoellner J . Evaluation of a novel biomarker of added sugar intake (δ 13C) compared with self-reported added sugar intake and the Healthy Eating Index-2010 in a community-based, rural U.S. sample. Public Health Nutr. 2015; 19(3):429-36. PMC: 5576148. DOI: 10.1017/S136898001500107X. View

Archer E, Pavela G, Lavie C . The Inadmissibility of What We Eat in America and NHANES Dietary Data in Nutrition and Obesity Research and the Scientific Formulation of National Dietary Guidelines. Mayo Clin Proc. 2015; 90(7):911-26. PMC: 4527547. DOI: 10.1016/j.mayocp.2015.04.009. View

Jahren A, Saudek C, Yeung E, Kao W, Kraft R, Caballero B . An isotopic method for quantifying sweeteners derived from corn and sugar cane. Am J Clin Nutr. 2006; 84(6):1380-4. DOI: 10.1093/ajcn/84.6.1380. View

Davy B, Jahren A, Hedrick V, Comber D . Association of δ¹³C in fingerstick blood with added-sugar and sugar-sweetened beverage intake. J Am Diet Assoc. 2011; 111(6):874-8. PMC: 3115617. DOI: 10.1016/j.jada.2011.03.019. View

Zoellner J, Chen Y, Davy B, You W, Hedrick V, Corsi T . Talking health, a pragmatic randomized-controlled health literacy trial targeting sugar-sweetened beverage consumption among adults: rationale, design & methods. Contemp Clin Trials. 2013; 37(1):43-57. PMC: 3939427. DOI: 10.1016/j.cct.2013.11.003. View

Bray G, Popkin B . Dietary sugar and body weight: have we reached a crisis in the epidemic of obesity and diabetes?: health be damned! Pour on the sugar. Diabetes Care. 2014; 37(4):950-6. PMC: 9514031. DOI: 10.2337/dc13-2085. View

Basu S, Mckee M, Galea G, Stuckler D . Relationship of soft drink consumption to global overweight, obesity, and diabetes: a cross-national analysis of 75 countries. Am J Public Health. 2013; 103(11):2071-7. PMC: 3828681. DOI: 10.2105/AJPH.2012.300974. View

Moshfegh A, Rhodes D, Baer D, Murayi T, Clemens J, Rumpler W . The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr. 2008; 88(2):324-32. DOI: 10.1093/ajcn/88.2.324. View

10.

Pereira M . Sugar-sweetened and artificially-sweetened beverages in relation to obesity risk. Adv Nutr. 2014; 5(6):797-808. PMC: 4224219. DOI: 10.3945/an.114.007062. View

11.

Bingham S, Luben R, Welch A, Tasevska N, Wareham N, Khaw K . Epidemiologic assessment of sugars consumption using biomarkers: comparisons of obese and nonobese individuals in the European prospective investigation of cancer Norfolk. Cancer Epidemiol Biomarkers Prev. 2007; 16(8):1651-4. DOI: 10.1158/1055-9965.EPI-06-1050. View

12.

Subar A, Freedman L, Tooze J, Kirkpatrick S, Boushey C, Neuhouser M . Addressing Current Criticism Regarding the Value of Self-Report Dietary Data. J Nutr. 2015; 145(12):2639-45. PMC: 4656907. DOI: 10.3945/jn.115.219634. View

13.

Malik V, Pan A, Willett W, Hu F . Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. Am J Clin Nutr. 2013; 98(4):1084-102. PMC: 3778861. DOI: 10.3945/ajcn.113.058362. View

14.

Thompson F, Subar A, Loria C, Reedy J, Baranowski T . Need for technological innovation in dietary assessment. J Am Diet Assoc. 2010; 110(1):48-51. PMC: 2823476. DOI: 10.1016/j.jada.2009.10.008. View

15.

Huth P, Fulgoni V, Keast D, Park K, Auestad N . Major food sources of calories, added sugars, and saturated fat and their contribution to essential nutrient intakes in the U.S. diet: data from the National Health and Nutrition Examination Survey (2003-2006). Nutr J. 2013; 12:116. PMC: 3751311. DOI: 10.1186/1475-2891-12-116. View