Evidence map›Paper›PMID 37731393›Full record

SynthesisFrontiers in nutrition2023

Association between ultra-processed food consumption and risk of breast cancer: a systematic review and dose-response meta-analysis of observational studies.

Long Shu, Xiaoyan Zhang, Qin Zhu, Xiaoling Lv, Caijuan Si

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Long ShuDepartment of Nutrition, Zhejiang Hospital, Hangzhou, China.
Xiaoyan ZhangDepartment of Nutrition, Zhejiang Hospital, Hangzhou, China.
Qin ZhuDepartment of Nutrition, Zhejiang Hospital, Hangzhou, China.
Xiaoling LvDepartment of Geriatrics, Zhejiang Hospital, Hangzhou, China.
Caijuan SiDepartment of Nutrition, Zhejiang Hospital, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Some epidemiological studies have examined the association between consumption of ultra-processed food (UPF) and the risk of breast cancer. However, the results were inconsistent. Therefore, we carried out a systematic review and dose-response meta-analysis to examine whether an association exists between high consumption of UPF and breast cancer risk. Methods: PubMed/MEDLINE, ISI Web of Science, EBSCO and CNKI databases were systematically searched from inception to May 2023. The summary relative risks (RRs) and 95% confidence intervals (CIs) associated with UPF consumption and breast cancer were calculated using a random-effects model (DerSimonian-Laird method). Heterogeneity between included studies was examined using the Cochran's Results: Overall, six articles involving 462,292 participants, were eligible to be included in this study. Compared to the lowest consumption, highest consumption of UPF was related to a higher risk of breast cancer (RR = 1.10; 95%CI: 1.00-1.22, Conclusion: Our results indicate that higher consumption of UPF is slightly related to a higher risk of breast cancer. Further studies in particular of large prospective cohort studies are warranted to confirm these results.

Indexed as

breast cancermeta-analysisnovasystematic reviewultra-processed food

Identifiers

PMID37731393
PMCPMC10507475

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.