Construction and validation of a novel nutrient-based index for risk of aging using an interpretable machine learning framework: results from two population-based studies.

Rui Qiang Li, Ting Yu Lu, Jiao Wang, Wei Sen Zhang, Jun Du, Ya Li Jin, Jun Tao Kan, Tai Hing Lam, Kar Keung Cheng, Emma Yun-Zhi Huang, Lin Xu

School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Guangzhou, Guangdong Province, China.School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Road, Guangzhou, Guangdong Province, China. · pubmed

Paper

Abstract

Population aging is becoming increasingly prominent. Although various dietary factors have been associated with aging in older people, no dietary score specifically related to phenotypic aging has yet been developed.

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper claims to construct and validate a novel nutrient-based index that predicts the risk of aging. This research is relevant as it seeks to establish a dietary score specifically related to phenotypic aging, addressing factors that may influence the biological processes of aging rather than merely treating age-related diseases.

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