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Abstract: SA-PO0885

Ultraprocessed Food Consumption and Kidney-Specific Biological Aging: A Cross-Sectional Analysis in the UK Biobank

Session Information

Category: Health Maintenance, Nutrition, and Metabolism

  • 1500 Health Maintenance, Nutrition, and Metabolism

Authors

  • Hu, Chunchun, Department of Nephrology, Institute of Kidney Diseases, West China Hospital of Sichuan University, Chengdu, China
  • Lin, Wenjun, Department of Nephrology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
  • Ma, Liang, Department of Nephrology, Institute of Kidney Diseases, West China Hospital of Sichuan University, Chengdu, China
  • Fu, Ping, Department of Nephrology, Institute of Kidney Diseases, West China Hospital of Sichuan University, Chengdu, China
Background

Accelerated urbanization has shifted diets toward ultra-processed foods (UPFs), now comprising 50–60% of energy in developed nations and linked to obesity, diabetes, and mortality. Biological aging can be quantified by the Klemera–Doubal Method (KDM), a phenotypic age integrating multisystem clinical indicators. However, research on UPFs and aging has three gaps: the degree of food processing is overlooked, KDM has never been applied, and kidney-specific aging—highly sensitive to UPF-derived additives—remains unexplored.

Methods

This cross-sectional UK Biobank study assessed UPF intake (NOVA4, weight%) and derived overall and kidney-specific biological ages via KDM. Linear regression, cubic splines, and stratified analyses were fully adjusted.

Results

This study introduces food processing degree into biological ageing research, expanding KDM's application in nutritional epidemiology. Findings support reducing UPF intake as a feasible anti-aging strategy, particularly for populations at high risk of metabolic syndrome and chronic kidney disease.

Conclusion

This study links food processing to biological aging, supporting reduced UPF intake as an anti-aging strategy for high-risk populations.

Acknowledgment

This study was conducted using data from UK Biobank (application number 442458). Researchers can apply for access to UK Biobank data at https://www.ukbiobank.ac.uk/.

Funding

  • Government Support – Non-U.S.