Association between Dietary Share of Ultra-Processed Foods and Urinary Concentrations of Phytoestrogens in the US
Abstract
:1. Introduction
2. Subjects and Methods
2.1. Data Source, Population and Sampling
2.2. Urinary Phytoestrogen Measurement
2.3. Food Classification According to Processing
2.4. Assessing Energy Content
2.5. Data Analysis
3. Results
3.1. Contribution of Nova food Groups to Total Energy Intake
3.2. Association between Consumption of Ultra-Processed Foods and Urinary Phytoestrogen Concentrations
4. Discussion
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Paterni, I.; Granchi, C.; Minutolo, F. Risks and Benefits Related to Alimentary Exposure to Xenoestrogens. Crit. Rev. Food Sci. Nutr. 2016. [Google Scholar] [CrossRef] [PubMed]
- Wang, L.Q. Mammalian phytoestrogens: Enterodiol and enterolactone. J. Chromatogr. B 2002, 777, 289–309. [Google Scholar] [CrossRef]
- Sirotkin, A.V.; Harrath, A.H. Phytoestrogens and their effects. Eur. J. Pharmacol. 2014, 741, 230–236. [Google Scholar] [CrossRef] [PubMed]
- Cassidy, A. Potential risks and benefits of phytoestrogen-rich diets. Int. J. Vitam. Nutr. Res. 2003, 73, 120–126. [Google Scholar] [CrossRef] [PubMed]
- Tuohy, P.G. Soy infant formula and phytoestrogens. J. Paediatr. Child Health 2003, 39, 401–405. [Google Scholar] [CrossRef] [PubMed]
- Branca, F.; Lorenzetti, S. Health effects of phytoestrogens. Forum Nutr. 2005, 57, 100–111. [Google Scholar]
- Vitale, D.C.; Piazza, C.; Melilli, B.; Drago, F.; Salomone, S. Isoflavones: Estrogenic activity, biological effect and bioavailability. Eur. J. Drug Metab. Pharmacokinet. 2013, 38, 15–25. [Google Scholar] [CrossRef] [PubMed]
- Bhagwat, S.; Haytowitz, D.B.; Holden, J.M. USDA Database for the Isoflavone Content of Selected Foods, Release 2.0. U.S. Department of Agriculture, Agricultural Research Service, Nutrient Data Laboratory Home Page, 2008. Available online: http://www.ars.usda.gov/nutrientdata/isoflav (accessed on 12 February 2017). [Google Scholar]
- U.S. Department of Agriculture, Agricultural Research Service. USDA Database for the Flavonoid Content of Selected Foods, Release 3.0. Nutrient Data Laboratory Home Page, 2011. Available online: http://www.ars.usda.gov/nutrientdata/flav (accessed on 12 February 2017). [Google Scholar]
- Grace, P.B.; Taylor, J.I.; Low, Y.L.; Luben, R.N.; Mulligan, A.A.; Botting, N.P.; Dowsett, N.; Welch, A.A.; Khaw, K.T.; Wareham, N.J.; et al. Phytoestrogen Concentrations in Serum and Spot Urine as Biomarkers for Dietary Phytoestrogen Intake and Their Relation to Breast Cancer Risk in European Prospective Investigation of Cancer and Nutrition-Norfolk. Cancer Epidemiol. Biomark. Prev. 2004, 13, 698–708. [Google Scholar]
- Eldrige, A.; Kwolek, W. Soybean isoflavones: Effect of environment and variety on composition. J. Agric. Food Chem. 1983, 31, 394–396. [Google Scholar] [CrossRef]
- Wang, H.-J.; Murphy, P.A. Isoflavone composition of American and Japanese soybeans in Iowa: Effects of variety, crop year and location. J. Agric. Food Chem. 1994, 42, 1674–1677. [Google Scholar] [CrossRef]
- Wang, H.-J.; Murphy, P.A. Isoflavone content in commercial soybean foods. J. Agric. Food Chem. 1994, 42, 1666–1673. [Google Scholar] [CrossRef]
- Thompson, L.U.; Rickard, S.E.; Cheung, F.; Kenaschuk, E.O.; Obermeyer, W.R. Variability in anticancer lignan levels in flaxseed. Nutr. Cancer 1997, 27, 26–30. [Google Scholar] [CrossRef] [PubMed]
- Setchell, K.D.; Cole, S.J. Variations in isoflavone levels in soy foods and soy protein isolates and issues related to isoflavone databases and food labeling. J. Agric. Food Chem. 2003, 51, 4146–4155. [Google Scholar] [CrossRef] [PubMed]
- Lampe, J.W. Isoflavonoid and lignan phytoestrogens as dietary biomarkers. J. Nutr. 2003, 133, 956S–964S. [Google Scholar] [PubMed]
- Seow, A.; Shi, C.Y.; Franke, A.A.; Hankin, J.H.; Lee, H.P.; Yu, M.C. Isoflavonoid levels in spot urine are associated with frequency of dietary soy intake in a population-based sample of middle aged and older Chinese in Singapore. Cancer Epidemiol. Biomark. Prev. 1998, 7, 135–140. [Google Scholar]
- French, M.R.; Thompson, L.U.; Hawker, G.A. Validation of a phytoestrogen food frequency questionnaire with urinary concentrations of isoflavones and lignan metabolites in premenopausal women. J. Am. Coll. Nutr. 2007, 26, 76–82. [Google Scholar] [CrossRef] [PubMed]
- Maskarinec, G.; Singh, S.; Meng, L.; Franke, A.A. Dietary soy intake and urinary isoflavone excretion among women from a multiethnic population. Cancer Epidemiol. Biomark. Prev. 1998, 7, 613–619. [Google Scholar]
- Jaceldo-Siegl, K.; Fraser, G.E.; Chan, J.; Franke, A.; Sabate, J. Validation of soy protein estimates from a food-frequency questionnaire with repeated 24-h recalls and isoflavonoid excretion in overnight urine in a western population with a wide range of soy intakes. Am. J. Clin. Nutr. 2008, 87, 1422–1427. [Google Scholar] [PubMed]
- Lampe, J.W.; Gustafson, D.R.; Hutchins, A.M.; Martini, M.C.; Li, S.; Wahala, K.; Grandits, G.A.; Potter, J.D.; Slavin, J.L. Urinary isoflavonoid and lignan excretion on a western diet: Relation to soy, vegetable, and fruit intake. Cancer Epidemiol. Biomark. Prev. 1999, 8, 699–707. [Google Scholar]
- Monteiro, C.A. Nutrition and health. The issue is not food, nor nutrients, so much as processing. Public Health Nutr. 2009, 12, 729–731. [Google Scholar] [CrossRef] [PubMed]
- Ludwig, D.S. Technology, diet, and the burden of chronic disease. JAMA 2011, 305, 1352–1353. [Google Scholar] [CrossRef] [PubMed]
- Moodie, R.; Stuckler, D.; Monteiro, C.; Sheron, N.; Neal, B.; Thamarangsi, T.; Lincoln, P.; Casswell, S.; Lancet NCD Action Group. Profits and pandemics: Prevention of harmful effects of tobacco, alcohol, and ultra-processed food and drink industries. Lancet 2013, 381, 670–679. [Google Scholar] [CrossRef]
- Monteiro, C.A.; Cannon, G.; Levy, R.B.; Claro, R.M.; Moubarac, J.-C. Ultra-processing and a new classification of foods. In Introduction to U.S. Food System. Public Health, Environment, and Equity; Neff, R., Ed.; Jossey Bass A Wiley Brand: San Francisco, CA, USA, 2015. [Google Scholar]
- Food and Agriculture Organization. Guidelines on the Collection of Information on Food Processing through Food Consumption Surveys; FAO: Rome, Italy, 2015. [Google Scholar]
- World Health Organization. Ultra-Processed Food and Drink Products in Latin America: Trends, Impact on Obesity, Policy Implications; Panamerican Health Organization: Washington, DC, USA, 2015. [Google Scholar]
- Stuckler, D.; McKee, M.; Ebrahim, S.; Basu, S. Manufacturing epidemics: The role of global producers in increased consumption of unhealthy commodities including processed foods, alcohol, and tobacco. PLoS Med. 2012, 9, e1001235. [Google Scholar] [CrossRef] [PubMed]
- Monteiro, C.A.; Cannon, G. The impact of transnational ‘Big Food’ companies on the South: A view from Brazil. PLoS Med. 2012, 9, e1001252. [Google Scholar] [CrossRef] [PubMed]
- Monteiro, C.A.; Moubarac, J.C.; Cannon, G.; Popkin, B.M. Ultra-processed products are becoming dominant in the global food system. Obes. Rev. 2013, 14 (Suppl. S2), 21–28. [Google Scholar] [CrossRef] [PubMed]
- Juul, F.; Hemmingsson, E. Trends in consumption of ultra-processed foods and obesity in Sweden between 1960 and 2010. Public Health Nutr. 2015, 18, 3096–3107. [Google Scholar] [CrossRef] [PubMed]
- Mendonça, R.D.; Pimenta, A.M.; Gea, A.; de la Fuente-Arrillaga, C.; Martinez-Gonzalez, M.A.; Lopes, A.C.; Bes-Rastrollo, M. Ultraprocessed food consumption and risk of overweight and obesity: The University of Navarra Follow-Up (SUN) cohort study. Am. J. Clin. Nutr. 2016, 104, 1433–1440. [Google Scholar] [CrossRef] [PubMed]
- Louzada, M.L.; Baraldi, L.G.; Steele, E.M.; Martins, A.P.; Canella, D.S.; Moubarac, J.C.; Levy, R.B.; Cannon, G.; Afshin, A.; Imamura, F.; et al. Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults. Prev. Med. 2015, 81, 9–15. [Google Scholar] [CrossRef] [PubMed]
- Canella, D.S.; Levy, R.B.; Martins, A.P.; Claro, R.M.; Moubarac, J.C.; Baraldi, L.G.; Cannon, G.; Monteiro, C.A. Ultra-processed food products and obesity in Brazilian households (2008–2009). PLoS ONE 2014, 9, e92752. [Google Scholar] [CrossRef] [PubMed]
- Rauber, F.; Campagnolo, P.D.; Hoffman, D.J.; Vitolo, M.R. Consumption of ultra-processed food products and its effects on children’s lipid profiles: A longitudinal study. Nutr. Metab. Cardiovasc. Dis. 2015, 25, 116–122. [Google Scholar] [CrossRef] [PubMed]
- Tavares, L.F.; Fonseca, S.C.; Garcia Rosa, M.L.; Yokoo, E.M. Relationship between ultra-processed foods and metabolic syndrome in adolescents from a Brazilian Family Doctor Program. Public Health Nutr. 2012, 15, 82–87. [Google Scholar] [CrossRef] [PubMed]
- Martinez Steele, E.; Baraldi, L.G.; Louzada, M.L.; Moubarac, J.C.; Mozaffarian, D.; Monteiro, C.A. Ultra-processed foods and added sugars in the US diet: Evidence from a nationally representative cross-sectional study. BMJ Open 2016, 6, e009892. [Google Scholar] [CrossRef] [PubMed]
- Martinez Steele, E.; Popkin, B.M.; Swinburn, B.; Monteiro, C.A. The share of ultra-processed foods and the overall nutritional quality of diets in the US: evidence from a nationally representative cross-sectional study. Population Health Metrics 2017. (accepted for publication). [Google Scholar] [CrossRef] [PubMed]
- Monteiro, C.A.; Levy, R.B.; Claro, R.M.; de Castro, I.R.; Cannon, G. Increasing consumption of ultra-processed foods and likely impact on human health: Evidence from Brazil. Public Health Nutr. 2010, 14, 5–13. [Google Scholar] [CrossRef] [PubMed]
- Louzada, M.L.; Martins, A.P.; Canella, D.S.; Baraldi, L.G.; Bertazzi, R.L.; Claro, R.M.; Moubarac, J.C.; Cannon, G.; Monteiro, C.A. Ultra-processed foods and the nutritional dietary profile in Brazil. Rev. Saúde Pública 2015, 49. [Google Scholar] [CrossRef] [PubMed]
- Louzada, M.L.; Martins, A.P.; Canella, D.S.; Baraldi, L.G.; Bertazzi, R.L.; Claro, R.M.; Moubarac, J.C.; Cannon, G.; Monteiro, C.A. Impact of ultra-processed foods on micronutrient content in the Brazilian diet. Rev. Saúde Pública 2015, 49. [Google Scholar] [CrossRef] [PubMed]
- Moubarac, J.-C.; Martins, A.P.B.; Claro, R.M.; Levy, R.B.; Cannon, G.; Monteiro, C.A. Consumption of ultra-processed foods and likely impact on human health. Evidence from Canada. Public Health Nutr. 2012, 16, 1–9. [Google Scholar] [CrossRef] [PubMed]
- Johnson, C.L.; Paulose-Ram, R.; Ogden, C.L.; Carroll, M.D.; Kruszon-Moran, D.; Dohrmann, S.M.; Curtin, L.R. National Health and Nutrition Examination Survey: Analytic guidelines, 1999–2010; Vital Health Stat 2; National Center for Health Statistics: Hyattsville, MD, USA, 2013; Volume 161.
- NHANES. MEC In-Person Dietary Interviewers Procedures Manual. 2009. Available online: https://www.cdc.gov/nchs/data/nhanes/nhanes_09_10/mec_in_person_dietary_procedures_manual_mar_2010.pdf (accessed on 12 February 2017). [Google Scholar]
- NHANES. Phone Follow-Up Dietary Interviewer Procedures Manual. 2009. Available online: https://www.cdc.gov/nchs/data/nhanes/nhanes_09_10/phone_follow_up_dietary_procedures_manual_mar_2010.pdf (accessed on 12 February 2017). [Google Scholar]
- Moshfegh, A.J.; Rhodes, D.G.; Baer, D.J.; Murayi, T.; Clemens, J.C.; Rumpler, W.V.; Paul, D.R.; Sebastian, R.S.; Kuczynski, K.C.; Ingwersen, L.A.; et al. The USDA Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am. J. Clin. Nutr. 2008, 88, 324–332. [Google Scholar] [PubMed]
- Blanton, C.A.; Moshfegh, A.J.; Baer, D.J.; Kretsch, M.J. The USDA Automated Multiple-Pass Method accurately estimates group total energy and nutrient intake. J. Nutr. 2006, 136, 2594–2599. [Google Scholar] [PubMed]
- Rumpler, W.V.; Kramer, M.; Rhodes, D.G.; Moshfegh, A.J.; Paul, D.R.; Kramer, M. Identifying sources of reporting error using measured food intake. Eur. J. Clin. Nutr. 2008, 62, 544–552. [Google Scholar] [CrossRef] [PubMed]
- Automated Multiple-Pass Method. United States Department of Agriculture. Agriculture Research Service. Available online: http://www.ars.usda.gov/ba/bhnrc/fsrg (accessed on12 February 2017).
- National Health and Nutrition Examination Survey. NHANES Response Rates and Population Totals. Response Rates. Available online: http://www.cdc.gov/nchs/nhanes/response_rates_CPS.htm (accessed on 12 February 2017).
- Laboratory Procedure Manual. Phytoestrogens in Urine NHANES 2009–2010. Bioactive Dietary Compounds Laboratory (BDCL); Nutritional Biomarkers Branch (NBB); Division of Laboratory Sciences (DLS); National Center for Environmental Health (NCEH). Available online: https://www.cdc.gov/nchs/data/nhanes/nhanes_09_10/Phyto_F_met_phytoestrogens.pdf (accessed on 12 February 2017).
- Laboratory Procedure Manual. Urinary Creatinine. University of Minnesota, January 2011. Available online: https://www.cdc.gov/nchs/data/nhanes/nhanes_09_10/ALB_CR_F_met_creatinine.pdf (accessed on 12 February 2017).
- Lyles, R.H.; Fan, D.; Chuachoowong, R. Correlation coefficient estimation involving a left censored laboratory assay variable. Statist. Med. 2001, 20, 2921–2933. [Google Scholar] [CrossRef] [PubMed]
- Croghan, C.; Egeghy, P.P. Methods of Dealing with Values below the Limit of Detection Using SAS. In Presented at Southeastern SAS User Group, St. Petersburg, FL, USA, 22–24 September 2003.
- Monteiro, C.A.; Levy, R.B.; Claro, R.M.; de Castro, I.R.R.; Cannon, G. A new classification of foods based on the extent and purpose of their processing. Cad. Saúde Pública 2010, 26, 2039–2049. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Moubarac, J.C.; Parra, D.C.; Cannon, G.; Monteiro, C.A. Food Classification Systems Based on Food Processing: Significance and implications for policies and actions: A systematic literature review and assessment. Curr. Obes. Rep. 2014, 3, 256–272. [Google Scholar] [CrossRef] [PubMed]
- Monteiro, C.A.; Cannon, G.; Levy, R.B.; Claro, R.M.; Moubarac, J.C. The Food System. Processing. The big issue for disease, good health, well-being. World Nutr. 2012, 3, 527–569. [Google Scholar]
- Ahuja, J.K.A.; Montville, J.B.; Omolewa-Tomobi, G.; Heendeniya, K.Y.; Martin, C.L.; Steinfeldt, L.C.; Anand, J.; Adler, M.E.; LaComb, R.P.; Moshfegh, A.J. USDA Food and Nutrient Database for Dietary Studies, 5.0; U.S. Department of Agriculture, Agricultural Research Service, Food Surveys Research Group: Beltsville, MD, USA, 2012.
- U.S. Department of Agriculture, Agricultural Research Service. USDA National Nutrient Database for Standard Reference, Release 24. Nutrient Data Laboratory Home Page, 2011. Available online: http://www.ars.usda.gov/ba/bhnrc/ndl (accessed on 12 February 2017). [Google Scholar]
- Barnes, S. The biochemistry, chemistry and physiology of the isoflavones in soybeans and their food products. Lymphat. Res. Biol. 2010, 8, 89–98. [Google Scholar] [CrossRef] [PubMed]
- Valentin-Blasini, L.; Blount, B.C.; Caudill, S.P.; Needham, L.L. Urinary and serum concentrations of seven phytoestrogens in a human reference population subset. J. Expo. Anal. Environ. Epidemiol. 2003, 13, 276–282. [Google Scholar] [CrossRef] [PubMed]
- Clavel, T.; Doré, J.; Blaut, M. Bioavailability of lignans in human subjects. Nutr. Res. Rev. 2006, 19, 187–196. [Google Scholar] [CrossRef] [PubMed]
- Xu, C.; Liu, Q.; Zhang, Q.; Jiang, Z.Y.; Gu, A. Urinary enterolactone associated with liver enzyme levels in US adults: National Health and Nutrition Examination Survey (NHANES). Br. J. Nutr. 2015, 114, 91–97. [Google Scholar] [CrossRef] [PubMed]
- Xu, C.; Liu, Q.; Zhang, Q.; Gu, A.; Jiang, Z.Y. Urinary enterolactone is associated with obesity and metabolic alteration in men in the US National Health and Nutrition Examination Survey 2001–10. Br. J. Nutr. 2015, 113, 683–690. [Google Scholar] [CrossRef] [PubMed]
- Reger, M.K.; Zollinger, T.W.; Liu, Z.; Jones, J.; Zhang, J. Urinary phytoestrogens and cancer, cardiovascular, and all‑cause mortality in the continuous National Health and Nutrition Examination Survey. Eur. J. Nutr. 2016, 55, 1029–1040. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rowland, I.; Faughnan, M.; Hoey, L.; Wahala, K.; Williamson, G.; Cassidy, A. Bioavailability of phyto-oestrogens. Br. J. Nutr. 2003, 89, S45–S58. [Google Scholar] [CrossRef] [PubMed]
- Subar, A.F.; Freedman, L.S.; Tooze, J.A.; Kirkpatrick, S.I.; Boushey, C.; Neuhouser, M.L.; Thompson, F.E.; Potischman, N.; Guenther, P.M.; Tarasuk, V.; et al. Addressing Current Criticism Regarding the Value of Self-Report Dietary Data. J. Nutr. 2015, 145, 2639–2645. [Google Scholar] [CrossRef] [PubMed]
- Bingham, S.; Luben, R.; Welch, A.; Tasevska, N.; Wareham, N.; Khaw, K.T. Epidemiologic assessment of sugars consumption using biomarkers: Comparisons of obese and nonobese individuals in the European Prospective Investigation of Cancer Norfolk. Cancer Epidemiol. Biomark. Prev. 2007, 16, 1651–1654. [Google Scholar] [CrossRef] [PubMed]
- Lafay, L.; Mennen, L.; Basdevant, A.; Charles, M.A.; Borys, J.M.; Eschwège, E.; Romon, M. Does energy intake underreporting involve all kinds of food or only specific food items? Results from the Fleurbaix Laventie Ville Sante (FLVS) study. Int. J. Obes. Relat. Metab. Disord. 2000, 24, 1500–1506. [Google Scholar] [CrossRef] [PubMed]
- Pryer, J.A.; Vrijheid, M.; Nichols, R.; Kiggins, M.; Elliott, P. Who are the “low energy reporters” in the dietary and nutritional survey of British adults? Int. J. Epidemiol. 1997, 26, 146–154. [Google Scholar] [CrossRef] [PubMed]
- Slining, M.M.; Yoon, E.F.; Davis, J.; Hollingsworth, B.; Miles, D.; Ng, S.W. An Approach to Monitor Food and Nutrition from “Factory to Fork”. J. Acad. Nutr. Diet. 2015, 115, 40–49. [Google Scholar] [CrossRef] [PubMed]
- Setchell, K.D.R.; Brown, N.M.; Desai, P.; Zimmer-Nechimias, L.; Wolfe, B.; Jakate, A.S.; Creutzinger, V.; Heubi, J.E. Bioavailability, disposition, and dose-response effects of soy isoflavones when consumed by healthy women at physiologically typical dietary intakes. J. Nutr. 2003, 133, 1027–1035. [Google Scholar] [PubMed]
Quintile of Dietary Share of Ultra-Processed Foods (% of Total Energy Intake) b | ||||||
---|---|---|---|---|---|---|
All Quintiles | Q1 | Q2 | Q3 | Q4 | Q5 | |
(n = 2,692) | (n = 539) | (n = 530) | (n = 521) | (n = 540) | (n = 562) | |
(2,153 kcal) | (2,040.5 kcal) | (2,212.1 kcal) | (2,143.0 kcal) | (2,143.9 kcal) | (2,227.6 kcal) | |
Unprocessed or minimally processed foods | 29.2 | 50.7 | 35.7 | 29.5 | 20.8 | 9.4 * |
Meat (includes poultry) | 8.2 | 13.2 | 10.5 | 8.7 | 6.3 | 2.4 * |
Fruit and freshly squeezed fruit juices | 4.7 | 7.7 | 5.1 | 5.2 | 3.6 | 2.0 * |
Milk and plain yoghurt | 4.3 | 5.6 | 4.6 | 5 | 4.1 | 2.2 * |
Grains | 3 | 7.4 | 3.9 | 1.9 | 1.4 | 0.4 * |
Roots and tubers | 1.4 | 2.3 | 1.9 | 1.8 | 0.9 | 0.4 * |
Eggs | 1.5 | 2.1 | 2.1 | 1.7 | 1.3 | 0.5 * |
Pasta | 1.3 | 2.8 | 1.8 | 0.9 | 0.9 | 0.2 * |
Fish and sea food | 1 | 1.9 | 1.3 | 0.9 | 0.5 | 0.4 * |
Legumes | 0.9 | 2 | 1.1 | 0.7 | 0.3 | 0.1 * |
Vegetables | 0.7 | 1.3 | 0.7 | 0.7 | 0.5 | 0.3 * |
Other unprocessed or minimally processed foods 1 | 2 | 4.4 | 2.5 | 1.9 | 0.9 | 0.4 * |
Processed culinary ingredients | 3.2 | 5.6 | 4.1 | 3.1 | 2.1 | 1.0 * |
Sugar 2 | 1.3 | 1.9 | 1.7 | 1.5 | 0.9 | 0.5 * |
Plant oils | 1.3 | 2.7 | 1.7 | 0.9 | 0.7 | 0.3 * |
Animal fats 3 | 0.5 | 0.7 | 0.6 | 0.6 | 0.5 | 0.2 * |
Other processed culinary ingredients 4 | 0.04 | 0.12 | 0.04 | 0.03 | 0.01 | 0.01 |
Unprocessed or minimally processed foods + Processed culinary ingredients | 32.4 | 56.2 | 39.8 | 32.6 | 22.9 | 10.4 * |
Processed foods | 9.8 | 15.3 | 13.2 | 9.2 | 7.5 | 3.9 * |
Cheese | 3.5 | 4 | 4.6 | 3.8 | 3.3 | 2.0 * |
Ham and other salted, smoked or canned meat or fish | 1.3 | 1.4 | 1.6 | 1.7 | 1.5 | 0.6 |
Vegetables and other plant foods preserved in brine | 0.8 | 0.8 | 0.9 | 0.7 | 0.7 | 0.3 * |
Other processed foods 5 | 4.2 | 9.1 | 6.1 | 2.9 | 2.1 | 0.9 * |
Ultra-processed foods | 57.8 | 28.5 | 47 | 58.2 | 69.6 | 85.6 * |
Breads | 9.8 | 6.9 | 9.8 | 11.5 | 11.5 | 9.4 * |
Soft and fruit drinks 6 | 7.3 | 3.1 | 5.3 | 7 | 8.9 | 11.9 * |
Cakes, cookies and pies | 5.7 | 2 | 4.3 | 6.7 | 7.7 | 7.6 * |
Salty-snacks | 4.5 | 1.6 | 3.9 | 4.2 | 5.5 | 7.4 * |
Frozen and shelf-stable plate meals | 3.6 | 0.6 | 2.1 | 2.6 | 4.6 | 7.9 * |
Pizza (ready-to-eat/heat) | 3.7 | 0.2 | 1.5 | 2.7 | 4.6 | 9.8 * |
Breakfast cereals | 2.5 | 1.7 | 2.6 | 2.9 | 2.8 | 2.7 |
Sauces, dressings and gravies | 2.5 | 2 | 2.4 | 2.8 | 3.4 | 1.9 |
Reconstituted meat or fish products | 2.5 | 0.6 | 2.6 | 2.3 | 3.1 | 3.9 * |
Sweet-snacks | 2.4 | 1.3 | 1.9 | 2.1 | 3.1 | 3.8 * |
Ice cream and ice pops | 2.1 | 0.8 | 1.4 | 2.1 | 2.6 | 3.7 * |
Desserts 7 | 1.7 | 1.5 | 1.4 | 1.6 | 1.9 | 1.9 |
French fries and other potato products | 1.7 | 0.4 | 0.9 | 1.7 | 2 | 3.6 * |
Sandwiches and hamburgers on bun (ready-to-eat/heat) | 1.5 | 0.1 | 0.6 | 0.9 | 1.7 | 3.9 * |
Milk-based drinks | 1.4 | 0.8 | 1.3 | 1.3 | 1.4 | 2 |
Instant and canned soups | 0.8 | 0.7 | 0.5 | 1 | 0.9 | 0.9 |
Other ultra-processed foods 8 | 3.9 | 4 | 4.4 | 4.6 | 3.7 | 2.9 |
Total | 100 | 100 | 100 | 100 | 100 | 100 |
Quintile of Dietary Share of Ultra-Processed Foods (% of Total Energy Intake) b | ||||||||
---|---|---|---|---|---|---|---|---|
Q1 | Q2 | Q3 | Q4 | Q5 | All Quintiles | |||
Enterolignans (GM c) | Enterodiol | Crude (ng/mL) (n = 2,692) | 52.7 | 42.9 | 38.4 | 35.8 | 33.1 * | 40.05 |
Normalized by creatinine (µg/g) (n = 2,692) | 61.2 | 49.2 | 39.8 | 38.3 | 31.6 * | |||
Normalized and adjusted for socio-demographic variables d (n = 2,428) | 60.8 | 51.9 | 38.3 | 39.3 | 33.6 * | |||
Normalized and adjusted for socio-demographic + other variables (n = 2,403) e | 60.6 | 50.7 | 38.5 | 40.0 | 35.1 * | |||
Enterolactone | Crude (ng/mL) | 255.6 | 224.4 | 226.2 | 209.7 | 176.4 | 216.9 | |
Normalized by creatinine (µg/g) | 297.1 | 257.2 | 234.4 | 224.3 | 168.4 * | |||
Normalized and adjusted for socio-demographic variables d | 291.8 | 261.2 | 219.0 | 237.5 | 186.9 * | |||
Normalized and adjusted for socio-demographic + other variables e | 281.1 | 258.0 | 222.8 | 245.1 | 200.1 | |||
Isoflavones (GM) | Daidzein | Crude (ng/mL) | 57.3 | 66.8 | 70.9 | 70.0 | 82.3 | 69.0 |
Normalized by creatinine (µg/g) | 66.6 | 76.6 | 73.5 | 74.9 | 78.6 | |||
Normalized and adjusted for socio-demographic variables d | 67.7 | 79.9 | 72.1 | 74.3 | 71.7 | |||
Normalized and adjusted for socio-demographic + other variables e | 68.9 | 79.8 | 72.5 | 74.9 | 71.6 | |||
O-Desmethylangolensin (O-DMA) | Crude (ng/mL) | 4.2 | 4.9 | 4.3 | 4.9 | 5.5 | 4.7 | |
Normalized by creatinine (µg/g) | 4.9 | 5.6 | 4.4 | 5.2 | 5.2 | |||
Normalized and adjusted for socio-demographic variables d | 5.0 | 5.8 | 4.3 | 5.2 | 5.1 | |||
Normalized and adjusted for socio-demographic + other variables e | 5.1 | 5.7 | 4.2 | 5.3 | 5.2 | |||
Equol | Crude (ng/mL) | 6.8 | 7.6 | 8.5 | 7.8 | 9.0 | 7.9 | |
Normalized by creatinine (µg/g) | 7.9 | 8.7 | 8.8 | 8.4 | 8.6 | |||
Normalized and adjusted for socio-demographic variables d | 8.9 | 8.9 | 8.7 | 8.2 | 7.9 | |||
Normalized and adjusted for socio-demographic + other variables e | 8.8 | 8.9 | 8.8 | 8.2 | 7.9 | |||
Genistein | Crude (ng/mL) | 27.9 | 29.4 | 35.6 | 31.5 | 38.8 | 32.4 | |
Normalized by creatinine (µg/g) | 32.5 | 33.7 | 36.9 | 33.7 | 37.1 | |||
Normalized and adjusted for socio-demographic variables d | 32.4 | 34.8 | 35.9 | 32.7 | 34.6 | |||
Normalized and adjusted for socio-demographic + other variables e | 32.6 | 34.8 | 36.4 | 32.8 | 34.4 |
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Martínez Steele, E.; Monteiro, C.A. Association between Dietary Share of Ultra-Processed Foods and Urinary Concentrations of Phytoestrogens in the US. Nutrients 2017, 9, 209. https://doi.org/10.3390/nu9030209
Martínez Steele E, Monteiro CA. Association between Dietary Share of Ultra-Processed Foods and Urinary Concentrations of Phytoestrogens in the US. Nutrients. 2017; 9(3):209. https://doi.org/10.3390/nu9030209
Chicago/Turabian StyleMartínez Steele, Eurídice, and Carlos A. Monteiro. 2017. "Association between Dietary Share of Ultra-Processed Foods and Urinary Concentrations of Phytoestrogens in the US" Nutrients 9, no. 3: 209. https://doi.org/10.3390/nu9030209
APA StyleMartínez Steele, E., & Monteiro, C. A. (2017). Association between Dietary Share of Ultra-Processed Foods and Urinary Concentrations of Phytoestrogens in the US. Nutrients, 9(3), 209. https://doi.org/10.3390/nu9030209