Evidence map›Paper›PMID 42780018›Full record

ArticleFrontiers in nutrition2026

Dietary behavior patterns and short-term pace of aging-evidence from a Chinese cohort.

Xin Huang, Zhaoyang Zhou, Pingting Yang, Jianzhou Yang, Yongmei He, Lu Yin, Jing Deng, Ying Li

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Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xin HuangDepartment of Epidemiology, School of Public Health, Health Science Center, Hunan Normal University, Changsha, Hunan, China.
Zhaoyang ZhouDepartment of Epidemiology, School of Public Health, Health Science Center, Hunan Normal University, Changsha, Hunan, China.
Pingting YangDepartment of Health Management, The Third Xiangya Hospital, Central South University, Changsha, China.
Jianzhou YangDepartment of Epidemiology and Biostatistics, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
Yongmei HeDepartment of Health Management, Aerospace Center Hospital, Beijing, China.
Lu YinInformation Center, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, China.
Jing DengDepartment of Epidemiology, Xiangya School of Public Health, Central South University, Changsha, Hunan, China.
Ying LiDepartment of Health Management, The Third Xiangya Hospital, Central South University, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Unhealthy dietary behaviors have been associated with increased risks of mortality and chronic diseases, yet mortality is a distal endpoint that requires long-term follow-up and is therefore poorly suited for short-term evaluation. Aging, which lies upstream of mortality and is modifiable by lifestyle factors, may serve as a meaningful early intermediate outcome. However, evidence linking dietary behavior patterns to short-term changes in the pace of biological aging remains limited. Therefore, we conducted this study to examine the associations between dietary behavior patterns and short-term changes in the pace of biological aging in a Chinese adult population, and to assess whether these associations vary by follow-up duration and chronological age. Methods: In a longitudinal cohort from two health management centers in China, dietary behavior patterns were identified using data-driven clustering approaches and categorized into low-, moderate-, and high-risk groups. Changes in biological age, estimated from multi-system biomarkers, were used to quantify short-term aging pace. Associations over 12- and 24-month follow-up periods were assessed using weighted longitudinal models. Results: Among 71,579 participants in the longitudinal cohort, higher-risk dietary behavior patterns were associated with greater increases in biological age over 12 months. When dietary behavior pattern was modeled as an ordinal exposure, each per-level increase in dietary risk was associated with a 0.017-year higher change in biological age at 12 months (95% CI: 0.003, 0.030). In contrast, no statistically significant associations were observed at 24 months. Associations were generally consistent across chronological age groups. Exploratory analyses of individual behavioral dimensions showed similar short-term patterns. Conclusion: Adverse dietary behavior patterns were associated with modest but detectable short-term acceleration in biological aging, with attenuation over time. These findings support the use of short-term biological aging measures as intermediate outcomes for evaluating early physiological responses to dietary behaviors.

Indexed as

aging pacebiological agedietary behaviorlatent class analysisprospective cohort

Identifiers

PMID42780018
PMCPMC13597222

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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.