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Association study of sleep duration and cardiovascular health in the elderly based on federated causal learning
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Miao-shuang CHEN, Qiao DENG, Zong-qi CHANG, Tao ZHANG
Modern Preventive Medicine | 2026, 53(6) : 968 - 972
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Modern Preventive Medicine | 2026, 53(6): 968-972
• Epidemiology and Statistical Methods Advances •
Association study of sleep duration and cardiovascular health in the elderly based on federated causal learning
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Miao-shuang CHEN, Qiao DENG, Zong-qi CHANG, Tao ZHANG
Affiliations
  • Department of Epidemiology and Health Statistics, West China School of Public Health/West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
Published: 2026-03-25 doi: 10.20043/j.cnki.MPM.202511321
Outline
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Objective

To address regional heterogeneity in multicenter studies, and to explore the association between sleep duration and cardiovascular disease (CVD) risk in the Chinese elderly population using a federated causal learning framework.

Methods

Data was obtained from the 2020 China Health and Retirement Longitudinal Study (CHARLS). A total of 10 638 adults aged 60 and above were included. To simulate multi-center collaboration scenarios with real regional heterogeneity, the original dataset was divided into seven geographically distributed datasets. A federated augmented inverse probability weighting (AIPW) estimator was used to estimate causal effects with comparison to centralized models. Subgroup analyses by gender were conducted to explore effect heterogeneity. The robustness of the method was explored by a sensitivity analysis.

Results

Estimations from the federated causal learning models were consistent with those from the centralized model. Abnormal sleep duration was a significant factor influencing CVD risk. Compared to normal sleepers, short sleepers had a significantly increased risk of CVD (OR=1.029, 95% CI:1.016-1.042). Long sleepers also showed elevated risk (OR=1.019, 95% CI:1.005-1.034). The subgroup analysis revealed significant gender differences, and the sensitivity analysis also validated the robustness of the model.

Conclusion

In multicenter research, the federated causal learning systematically controls for confounders and regional heterogeneity. It provides methodological support for future privacy-preserving cross-center collaborative research.

Federated causal learning  /  Regional heterogeneity  /  Sleep duration  /  Elderly people  /  Cardiovascular disease
陈苗双, 邓巧, 常综启, 张韬. 基于联邦因果学习的老年人睡眠时长与心血管健康的关联性研究. 现代预防医学, 2026 , 53 (6) : 968 -972 . DOI: 10.20043/j.cnki.MPM.202511321
Miao-shuang CHEN, Qiao DENG, Zong-qi CHANG, Tao ZHANG. Association study of sleep duration and cardiovascular health in the elderly based on federated causal learning[J]. Modern Preventive Medicine, 2026 , 53 (6) : 968 -972 . DOI: 10.20043/j.cnki.MPM.202511321
Year 2026 volume 53 Issue 6
29
16
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Article Info
doi: 10.20043/j.cnki.MPM.202511321
  • Receive Date:2025-11-20
  • Online Date:2026-11-02
  • Published:2026-03-25
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  • Received:2025-11-20
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    Department of Epidemiology and Health Statistics, West China School of Public Health/West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
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表12种不同金属材料的力学参数
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小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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