The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Dose–response meta-analysis of ultra-processed food with the risk of cardiovascular events and all-cause mortality: evidence from prospective cohort studies
Abstract
Each additional daily serving of UPF is associated with a 4% higher risk of CVEs and a 2% higher risk of total death. For maintaining good health, one should consume less UPF and more unprocessed or minimally processed food.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Pooled dose-response analysis of nine cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident all cause mortality (risk ratio 1.02, 95% confidence interval 1.01 to 1.03; credibility class III; GRADE moderate).
“Pooled effect estimates from nine dose-response and seven non-dose-response cohorts showed direct associations between greater exposure to ultra-processed foods and higher risks of incident all cause mortality (dose-response risk ratio 1.02, 95% confidence interval 1.01 to 1.03; credibility assessment class III; GRADE assessment moderate”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Pooled dose-response analysis of six cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident cardiovascular disease morbidity (risk ratio 1.04, 95% confidence interval 1.02 to 1.06; credibility class III; GRADE low).
“as well as incident cardiovascular disease morbidity (dose-response risk ratio 1.04, 1.02 to 1.06; class III; low”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Pooled non-dose-response analysis of six cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident cardiovascular disease events such as morbidity and mortality (risk ratio 1.35, 95% confidence interval 1.18 to 1.54; credibility class III; GRADE very low).
“non-dose-response risk ratio 1.35, 1.18 to 1.54; class III; very low”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Pooled non-dose-response analysis of six cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident cardiovascular disease morbidity (risk ratio 1.20, 95% confidence interval 1.09 to 1.33; credibility class III; GRADE low).
“non-dose-response risk ratio 1.20, 1.09 to 1.33; class III; low”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Pooled non-dose-response analysis of seven cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident all cause mortality (risk ratio 1.21, 95% confidence interval 1.15 to 1.27; credibility class II; GRADE low).
“non-dose-response risk ratio 1.21, 1.15 to 1.27; class II; low”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Pooled dose-response analysis of four cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident cardiovascular disease related mortality (risk ratio 1.05, 95% confidence interval 1.02 to 1.08; credibility class IV; GRADE low).
“Four dose-response and five non-dose-response cohorts informed the synthesis of associations between greater exposure to ultra-processed foods and higher risks of incident cardiovascular disease related mortality (dose-response risk ratio 1.05, 1.02 to 1.08; class IV; low”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Heterogeneity and imprecision may be partly explained by the treatment of different effect estimates (hazard ratios, odds ratios, and risk ratios) as approximately equivalent in various meta-analysis studies.
“The heterogeneity and imprecision noted across several of the pooled analyses, as shown by both the evidence classification criteria and GRADE assessments, may be partly explained by the treatment of different effect estimates derived from original research articles (hazard ratios, odds ratios, and risk ratios) as approximately equivalent in various meta-analysis studies.”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Pooled dose-response analysis of six cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident cardiovascular disease events such as morbidity and mortality (risk ratio 1.04, 95% confidence interval 1.02 to 1.06; credibility class III; GRADE low).
“Pooled analyses from six cohorts showed direct associations between greater ultra-processed food exposure and higher risks of incident cardiovascular disease events such as morbidity and mortality (dose-response risk ratio 1.04, 1.02 to 1.06; class III; low”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Pooled non-dose-response analysis of five cohorts showed a direct association between greater ultra-processed food exposure and higher risk of incident cardiovascular disease related mortality (risk ratio 1.50, 95% confidence interval 1.37 to 1.63; credibility class I; GRADE very low).
“non-dose-response risk ratio 1.50, 1.37 to 1.63; class I; very low”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [43]
Citations
Cites
Methods for Trend Estimation from Summarized Dose-Response Data, with Applications to Meta-Analysis
Greenland, S., & Longnecker, M. P. (1992) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116237 · Cited by 2,353
Schnabel, L., Kesse-Guyot, E., Allès, B., Touvier, M., Srour, B., Hercberg, S., Buscail, C., & Julia, C. (2019) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.7289 · Cited by 390
Qin, P., Li, Q., Zhao, Y., Chen, Q., Sun, X., Liu, Y., Li, H., Wang, T., Chen, X., Zhou, Q., et al. (2020) · European Journal of Epidemiology · doi:10.1007/s10654-020-00655-y · Cited by 323
Self-citationUltra-Processed Foods and Incident Cardiovascular Disease in the Framingham Offspring Study
Juul, F., Vaidean, G., Lin, Y., Deierlein, A. L., & Parekh, N. (2021) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2021.01.047 · Cited by 227
Flagged first, then by citations
Research works printed but not linked: 45
- Peeters, 2018, Nat. Rev. Endocrinol., 14, 430, 10.1038/s41574-018-0026-0 · DOI
- Li, 2020, Diabetes Care, 43, 1929, 10.2337/dc20-0256 · DOI
- Monteiro, 2018, Public Health Nutr., 21, 5, 10.1017/S1368980017000234 · DOI · Paper page
- Moubarac, 2013, Public Health Nutr., 16, 2240, 10.1017/S1368980012005009 · DOI
- Martínez Steele, 2016, BMJ Open, 6, e009892, 10.1136/bmjopen-2015-009892 · DOI · Paper page
- Adams, 2015, Int. J. Behav. Nutr. Phys. Act., 12, 160, 10.1186/s12966-015-0317-y · DOI
- Lane, 2021, Obes. Rev., 22, e13146, 10.1111/obr.13146 · DOI · Paper page
- Pagliai, 2021, Br. J. Nutr., 125, 308, 10.1017/S0007114520002688 · DOI · Paper page
- Taneri, 2022, Am. J. Epidemiol., 191, 1323, 10.1093/aje/kwac039 · DOI
- Srour, 2019, Br. Med. J., 365, l1451, 10.1136/bmj.l1451 · DOI · Paper page
- Zhong, 2021, Int. J. Behav. Nutr. Phys. Act., 18, 21, 10.1186/s12966-021-01081-3 · DOI
- Bonaccio, 2021, Am. J. Clin. Nutr., 113, 446, 10.1093/ajcn/nqaa299 · DOI · Paper page
- Du, 2021, J. Nutr., 151, 3746, 10.1093/jn/nxab285 · DOI
- Rico-Campà, 2019, Br. Med. J., 365, l1949, 10.1136/bmj.l1949 · DOI
- Kim, 2019, Public Health Nutr., 22, 1777, 10.1017/S1368980018003890 · DOI
- Blanco-Rojo, 2019, Mayo Clin. Proc., 94, 2178, 10.1016/j.mayocp.2019.03.035 · DOI
- Moher, 2009, Br. Med. J., 339, b2535, 10.1136/bmj.b2535 · DOI · Paper page
- Stroup, 2000, J. Am. Med. Assoc., 283, 2008, 10.1001/jama.283.15.2008 · DOI · Paper page
- G. A.Wells , B. J.Shea , D.O'Connell , J.Peterson , V.Welch , M.Losos and P.Tugwell , The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses , 2000
- Han, 2019, Ann. Intern. Med., 171, 711, 10.7326/M19-0699 · DOI
- Orsini, 2012, Am. J. Epidemiol., 175, 66, 10.1093/aje/kwr265 · DOI
- Bekkering, 2008, Am. J. Epidemiol., 167, 1017, 10.1093/aje/kwn005 · DOI
- Tamakoshi, 2011, Eur. J. Epidemiol., 26, 285, 10.1007/s10654-011-9548-7 · DOI
- Dochi, 2009, Tohoku J. Exp. Med., 217, 37, 10.1620/tjem.217.37 · DOI
- Higgins, 2003, BMJ (Clin. Res. Ed.), 327, 557, 10.1136/bmj.327.7414.557 · DOI · Paper page
- Huang, 2021, Indoor Air, 31, 1722, 10.1111/ina.12867 · DOI
- Santiago de Araújo Pio, 2017, Mayo Clin. Proc., 92, 1644, 10.1016/j.mayocp.2017.07.019 · DOI
- Egger, 1997, Br. Med. J., 315, 629, 10.1136/bmj.315.7109.629 · DOI · Paper page
- Begg, 1994, Biometrics, 50, 1088, 10.2307/2533446 · DOI · Paper page
- Romero Ferreiro, 2021, Public Health Nutr., 1
- Orlich, 2022, Am. J. Clin. Nutr., 115, 1589, 10.1093/ajcn/nqac043 · DOI
- Suksatan, 2021, Nutrients, 14, 174, 10.3390/nu14010174 · DOI · Paper page
- Kim, 2021, Clin. Nutr., 40, 1060, 10.1016/j.clnu.2020.07.007 · DOI
- Harcombe, 2017, Br. J. Sports Med., 51, 1743, 10.1136/bjsports-2016-096550 · DOI
- Li, 2012, CNS Neurosci. Ther., 18, 691, 10.1111/j.1755-5949.2012.00355.x · DOI · Paper page
- Fransen, 2017, Eur. J. Public Health, 27, 274
- Jha, 2014, N. Engl. J. Med., 370, 60, 10.1056/NEJMra1308383 · DOI · Paper page
- Rehm, 2021, Nutrients, 13, 2652, 10.3390/nu13082652 · DOI
- Zhao, 2021, Sports Med., 51, 1439, 10.1007/s40279-021-01452-7 · DOI
- Hall, 2020, Cell Metab., 32, 690, 10.1016/j.cmet.2020.08.014 · DOI
- Alonso-Pedrero, 2020, Am. J. Clin. Nutr., 111, 1259, 10.1093/ajcn/nqaa075 · DOI
- Wang, 2018, Ageing Res. Rev., 48, 11, 10.1016/j.arr.2018.09.002 · DOI
- Egnell, 2021, Int. J. Behav. Nutr. Phys. Act., 18, 38, 10.1186/s12966-021-01108-9 · DOI
- Kelly, 2019, Public Health Nutr., 22, 1125, 10.1017/S1368980018003737 · DOI
- Juul, 2021, Adv. Nutr., 12, 1673, 10.1093/advances/nmab049 · DOI · Paper page
Cited by
Sorted by citations
Lane, M. M., Gamage, E., Du, S., Ashtree, D. N., McGuinness, A. J., Gauci, S., Baker, P., Lawrence, M., Rebholz, C. M., Srour, B., et al. (2024) · BMJ · doi:10.1136/bmj-2023-077310 · Cited by 1,153
Mendoza, K., Smith-Warner, S. A., Rossato, S. L., Khandpur, N., Manson, J. E., Qi, L., Rimm, E. B., Mukamal, K. J., Willett, W. C., Wang, M., et al. (2024) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2024.100859 · Cited by 101
Self-citation
Metadata
- Authors
- Yuan, L., Hu, H., Li, T., Zhang, J., Feng, Y., Yang, X., Li, Y., Wu, Y., Li, X., Huang, H., Hu, F., Chen, C., Zhang, M., Zhao, Y., & Hu, D.
- Affiliations
- Department of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, Guangdong, People's Republic of China
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, People's Republic of China
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
- Department of Endocrinology, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, Guangdong, People's Republic of China
- ORCID
- Hu, Dongsheng
- Venue
- Food & Function
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2023
- Volume
- 14
- Issue
- 6
- Pages
- 2586-2596
- ISSN
- 2042-6496
- 2042-650X
- Cited by
- 53
- References
- 4
- Language
- en
- Funders
- National Natural Science Foundation of China (82073646, 81973152, 82273707)
- Natural Science Foundation of Guangdong Province (2021A1515012503)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review