Literature DB >> 17684141

Epidemiologic assessment of sugars consumption using biomarkers: comparisons of obese and nonobese individuals in the European prospective investigation of cancer Norfolk.

Sheila Bingham1, Robert Luben, Ailsa Welch, Natasa Tasevska, Nick Wareham, Kay Tee Khaw.   

Abstract

We have previously shown that urinary sugars excretion in 24 h urine collections can serve as an independent biomarker of sugars consumption. In the European Prospective Investigation of Cancer (EPIC) Norfolk study of nutrition and cancer, this biomarker in spot urines has been assessed in a cross-sectional comparison of 404 obese individuals aged 45 to 75 years with a body mass index (BMI) of >30 kg/m(2) and 471 normal weight individuals aged 45 to 75 years with a BMI of <25 kg/m(2). In individuals of normal weight, sucrose, protein, and vitamin C intake were positively and highly significantly related to biomarkers in spot urine or plasma (P < 0.001), but there were no significant associations between biomarkers and food intake reports in the obese. Odds ratios for a BMI of >30 were significantly elevated for urinary sucrose [trend per milligram per liter quintile, 1.13; 95% confidence interval (95% CI), 1.02-1.25; P = 0.016], and the odds ratio for urinary sucrose/fructose ratio was highly significant (trend per quintile, 1.264; 95% CI, 1.142-1.401; P < 0.001). No associations for sugars intake and obesity were found using a food frequency questionnaire, and dietary vitamin C was apparently associated with increased risk (P < 0.001) despite an inverse association for plasma vitamin C. Nutritional biomarkers of consumption can complement existing methods for assessing cancer risk from diet in epidemiologic studies.

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Year:  2007        PMID: 17684141     DOI: 10.1158/1055-9965.EPI-06-1050

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  27 in total

1.  The Carbon Isotope Ratios of Serum Amino Acids in Combination with Participant Characteristics can be Used to Estimate Added Sugar Intake in a Controlled Feeding Study of US Postmenopausal Women.

Authors:  Hee Young Yun; Lesley F Tinker; Marian L Neuhouser; Dale A Schoeller; Yasmin Mossavar-Rahmani; Linda G Snetselaar; Linda V Van Horn; Charles B Eaton; Ross L Prentice; Johanna W Lampe; Diane M O'Brien
Journal:  J Nutr       Date:  2020-10-12       Impact factor: 4.798

2.  Consumption of added sugars is decreasing in the United States.

Authors:  Jean A Welsh; Andrea J Sharma; Lisa Grellinger; Miriam B Vos
Journal:  Am J Clin Nutr       Date:  2011-07-13       Impact factor: 7.045

Review 3.  Biomarkers in nutritional epidemiology: applications, needs and new horizons.

Authors:  Mazda Jenab; Nadia Slimani; Magda Bictash; Pietro Ferrari; Sheila A Bingham
Journal:  Hum Genet       Date:  2009-04-09       Impact factor: 4.132

4.  Lifestyle and specific dietary habits in the Italian population: focus on sugar intake and association with anthropometric parameters-the LIZ (Liquidi e Zuccheri nella popolazione Italiana) study.

Authors:  Franca Marangoni; Ovidio Brignoli; Claudio Cricelli; Andrea Poli
Journal:  Eur J Nutr       Date:  2016-05-06       Impact factor: 5.614

5.  Use of a urinary sugars biomarker to assess measurement error in self-reported sugars intake in the nutrition and physical activity assessment study (NPAAS).

Authors:  Natasha Tasevska; Douglas Midthune; Lesley F Tinker; Nancy Potischman; Johanna W Lampe; Marian L Neuhouser; Jeannette M Beasley; Linda Van Horn; Ross L Prentice; Victor Kipnis
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-09-18       Impact factor: 4.254

6.  The carbon isotope ratio of alanine in red blood cells is a new candidate biomarker of sugar-sweetened beverage intake.

Authors:  Kyungcheol Choy; Sarah H Nash; Alan R Kristal; Scarlett Hopkins; Bert B Boyer; Diane M O'Brien
Journal:  J Nutr       Date:  2013-04-24       Impact factor: 4.798

7.  Plasma alkylresorcinols C17:0/C21:0 ratio, a biomarker of relative whole-grain rye intake, is associated to insulin sensitivity: a randomized study.

Authors:  O K Magnusdottir; R Landberg; I Gunnarsdottir; L Cloetens; B Akesson; M Landin-Olsson; F Rosqvist; D Iggman; U Schwab; K-H Herzig; M J Savolainen; L Brader; K Hermansen; M Kolehmainen; K Poutanen; M Uusitupa; I Thorsdottir; U Risérus
Journal:  Eur J Clin Nutr       Date:  2014-02-19       Impact factor: 4.016

8.  Biomarker-predicted sugars intake compared with self-reported measures in US Hispanics/Latinos: results from the HCHS/SOL SOLNAS study.

Authors:  J M Beasley; M Jung; N Tasevska; W W Wong; A M Siega-Riz; D Sotres-Alvarez; M D Gellman; J R Kizer; P A Shaw; J Stamler; M Stoutenberg; L Van Horn; A A Franke; J Wylie-Rosett; Y Mossavar-Rahmani
Journal:  Public Health Nutr       Date:  2016-06-24       Impact factor: 4.022

9.  Influence of an intervention targeting a reduction in sugary beverage intake on the δ13C sugar intake biomarker in a predominantly obese, health-disparate sample.

Authors:  Brenda M Davy; A Hope Jahren; Valisa E Hedrick; Wen You; Jamie M Zoellner
Journal:  Public Health Nutr       Date:  2016-06-14       Impact factor: 4.022

10.  Comparison and validation of 2 analytical methods for measurement of urinary sucrose and fructose excretion.

Authors:  Xiaoling Song; Sandi L Navarro; Pho Diep; Wendy K Thomas; Elena C Razmpoosh; Yvonne Schwarz; Ching-Yun Wang; Mario Kratz; Marian L Neuhouser; Johanna W Lampe
Journal:  Nutr Res       Date:  2013-07-03       Impact factor: 3.315

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