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Association between dietary contribution of ultra-processed foods and urinary concentrations of phthalates and bisphenol in a nationally representative sample of the US population aged 6 years and older

Martínez Steele, Eurídice, Khandpur, Neha, da Costa Louzada, Maria Laura, Monteiro, Carlos Augusto·2020·PLOS ONE
DOI 10.1371/journal.pone.0236738PMC PMC7394369
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  • Nationally representative studies from the USA found higher urinary concentrations of PFAS in people with increased UPF intake.

    “Nationally representative studies from the USA found higher urinary concentrations of PFAS in people with increased UPF intake.72,73”

    From Ultra-processed foods and human health: the main thesis and the evidence (2025) · cites this paper as [72]

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Citations

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Research works printed but not linked: 44

  1. CA Monteiro, 2013, Ultraprocessed products are becoming dominant in the global food system, Obes Rev, 14, 21, 10.1111/obr.12107 · DOI · Paper page
  2. JC Moubarac, 2014, Processed and ultraprocessed food products: consumption trends in Canada from 1938 to 2011, Can J Diet Pract Res, 75, 15, 10.3148/75.1.2014.15 · DOI · Paper page
  3. AP Martins, 2013, Increased contribution of ultra-processed food products in the Brazilian diet (1987–2009), Rev Saude Publica, 47, 656
  4. S Vandevijvere, 2019, Global trends in ultraprocessed food and drink product sales and their association with adult body mass index trajectories, Obes Rev
  5. RD Mendonça, 2016, Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study, Am J Clin Nutr, 104, 1433, 10.3945/ajcn.116.135004 · DOI · Paper page
  6. Canhada et al. Ultra-processed foods, incident overweight and obesity, and longitudinal changes in weight and waist circumference: the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). PHN 2019 · DOI
  7. RD Mendonça, 2017, Ultra-Processed Food Consumption and the Incidence of Hypertension in a Mediterranean Cohort: The Seguimiento Universidad de Navarra Project, Am J Hypertens, 30, 358, 10.1093/ajh/hpw137 · DOI · Paper page
  8. F Rauber, 2015, Consumption of ultra-processed food products and its effects on children’s lipid profiles: a longitudinal study, Nutr Metab Cardiovasc Dis, 25, 116, 10.1016/j.numecd.2014.08.001 · DOI
  9. B Srour, 2019, Ultra-processed food intake and risk of cardiovascular disease: prospective cohort study (NutriNet-Santé), BMJ, 365, l1451, 10.1136/bmj.l1451 · DOI · Paper page
  10. A Rico-Campà, 2019, Association between consumption of ultra-processed foods and all cause mortality: SUN prospective cohort study, BMJ, 365, l1949, 10.1136/bmj.l1949 · DOI
  11. H Kim, 2019, Ultra-processed food intake and mortality in the USA: results from the Third National Health and Nutrition Examination Survey (NHANES III, 1988–1994), Public Health Nutr, 22, 1777, 10.1017/S1368980018003890 · DOI
  12. R Blanco-Rojo, 2019, Consumption of Ultra-Processed Foods and Mortality: A National Prospective Cohort in Spain, Mayo Clin Proc, 94, 2178, 10.1016/j.mayocp.2019.03.035 · DOI
  13. MK Zinöcker, 2018, The Western diet–microbiome–host interaction and its role in metabolic disease, Nutrients, 10, E365, 10.3390/nu10030365 · DOI · Paper page
  14. AC Gore, 2015, EDC-2: the Endocrine Society’s second Scientific Statement on endocrine-disrupting chemicals, Endocr Rev, 36, E1, 10.1210/er.2015-1010 · DOI · Paper page
  15. DC Pacyga, 2019, Dietary Predictors of Phthalate and Bisphenol Exposures in Pregnant Women, Adv Nutr
  16. F Rancière, 2015, Bisphenol A and the risk of cardiometabolic disorders: a systematic review with meta-analysis of the epidemiological evidence, Environ Health, 14, 46, 10.1186/s12940-015-0036-5 · DOI
  17. EG Radke, 2019, Phthalate exposure and metabolic effects: a systematic review of the human epidemiological evidence, Environ Int, 132, 104768, 10.1016/j.envint.2019.04.040 · DOI
  18. B Shoshtari-Yeganeh, 2019, Systematic review and meta-analysis on the association between phthalates exposure and insulin resistance, Environ Sci Pollut Res Int, 26, 9435, 10.1007/s11356-019-04373-1 · DOI
  19. MJ Lopez-Espinosa, 2007, Oestrogenicity of paper and cardboard extracts used as food containers, Food Addit Contam, 24, 95, 10.1080/02652030600936375 · DOI
  20. MA Moreira, 2013, Analysis of phthalate migration to food simulants in plastic containers during microwave operations, Int J Environ Res Public Health, 11, 507, 10.3390/ijerph110100507 · DOI
  21. JP Buckley, 2019, Ultra-processed food consumption and exposure to phthalates and bisphenols in the US National Health and Nutrition Examination Survey, 2013–2014, Environ Int, 131, 105057, 10.1016/j.envint.2019.105057 · DOI · Paper page
  22. AJ Moshfegh, 2008, The USDA Automated Multiple-Pass Method reduces bias in the collection of energy intakes, Am J Clin Nutr, 88, 324, 10.1093/ajcn/88.2.324 · DOI
  23. CA Blanton, 2006, The USDA Automated Multiple-Pass Method accurately estimates group total energy and nutrient intake, J Nutr, 136, 2594, 10.1093/jn/136.10.2594 · DOI
  24. WV Rumpler, 2008, Identifying sources of reporting error using measured food intake, Eur J Clin Nutr, 62, 544, 10.1038/sj.ejcn.1602742 · DOI
  25. AM Calafat, 2015, Optimal exposure biomarkers for nonpersistent chemicals in environmental epidemiology, Environ Health Perspect, 123, A166, 10.1289/ehp.1510041 · DOI
  26. LE Johns, 2015, Exposure assessment issues in epidemiology studies of phthalates, Environ Int, 85, 27, 10.1016/j.envint.2015.08.005 · DOI · Paper page
  27. AR Zota, 2014, Temporal trends in phthalate exposures: findings from the National Health and Nutrition Examination Survey, 2001–2010, Environ Health Perspect, 122, 235, 10.1289/ehp.1306681 · DOI · Paper page
  28. JM Braun, 2012, Variability of urinary phthalate metabolite and bisphenol A concentrations before and during pregnancy, Environmental health perspectives, 120, 739, 10.1289/ehp.1104139 · DOI
  29. KJ Polinski, 2018, Distribution and predictors of urinary concentrations of phthalate metabolites and phenols among pregnant women in the Healthy Start Study, Environ Res, 162, 308, 10.1016/j.envres.2018.01.025 · DOI
  30. CA Monteiro, 2018, The UN Decade of Nutrition, the NOVA food classification and the trouble with ultra-processing, Public Health Nutr, 21, 5, 10.1017/S1368980017000234 · DOI · Paper page
  31. E Martinez Steele, 2016, Ultra-processed foods and added sugars in the US diet: evidence from a nationally representative cross-sectional study, BMJ Open, 6, e009892, 10.1136/bmjopen-2015-009892 · DOI · Paper page
  32. F Juul, 2018, Ultraprocessed food consumption and excess weight among US adults, Br J Nutr, 120, 90, 10.1017/S0007114518001046 · DOI · Paper page
  33. RJ Kuczmarski, 2002, 2000 CDC growth charts for the United States: Methods and development. National Center for Health Statistics, Vital Health Stat, 11
  34. F. E. Harrell, 2001, Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis, 10.1007/978-1-4757-3462-1 · DOI
  35. L Desquilbet, 2010, Dose-response analyses using restricted cubic spline functions in public health research, Stat Med, 29, 1037, 10.1002/sim.3841 · DOI
  36. SE Serrano, 2014, Phthalates and diet: a review of the food monitoring and epidemiology data, Environ Health, 13, 43, 10.1186/1476-069X-13-43 · DOI
  37. XL Cao, 2010, Phthalate esters in foods: sources, occurrence, and analytical methods, Compr Rev Food Sci Food Saf, 9, 21, 10.1111/j.1541-4337.2009.00093.x · DOI
  38. AR Zota, 2016, Recent fast food consumption and bisphenol A and phthalates exposures among the U.S. population in NHANES, 2003–2010, Environ Health Perspect, 124, 1521, 10.1289/ehp.1510803 · DOI
  39. DJ Watkins, 2014, Variability and Predictors of Urinary Concentrations of Phthalate Metabolites during Early Childhood, Environ Sci Technol, 48, 8881, 10.1021/es501744v · DOI
  40. DB Barr, 2005, Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements, Environ Health Perspect, 113, 192, 10.1289/ehp.7337 · DOI
  41. T Geens, 2012, A review of dietary and non-dietary exposure to bisphenol-A, Food Chem Toxicol, 50, 3725, 10.1016/j.fct.2012.07.059 · DOI
  42. X.L. Cao, 2011, Concentrations of bisphenol A in the composite food samples from the 2008 Canadian total diet study in Quebec City and dietary intake estimates, Food Addit. Contam. Part A, 28, 791, 10.1080/19440049.2010.513015 · DOI
  43. XL Cao, 2019, LC-MS/MS analysis of bisphenol S and five other bisphenols in total diet food samples, Food Addit Contam Part A Chem Anal Control Expo Risk Assess, 30, 1
  44. R.L. Prentice, 2011, Evaluation and comparison of food records, recalls, and frequencies for energy and protein assessment by using recovery biomarkers, Am. J. Epidemiol, 591, 10.1093/aje/kwr140 · DOI

Cited by

Sorted by citations

Metadata

Authors
Martínez Steele, E., Khandpur, N., da Costa Louzada, M. L., & Monteiro, C. A.
ORCID
Martínez Steele, Eurídice
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2020-07-31
Volume
15
Issue
7
Pages
e0236738
ISSN
1932-6203
DOI
10.1371/journal.pone.0236738
PMC
PMC7394369
Cited by
113
References
8
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
Fundação de Amparo à Pesquisa do Estado de São Paulo (2018/17972-9, 2015/14900-9)

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