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DOI 10.1007/s10072-026-08922-8

Медицинская библиотека · Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026

Headache associated with adverse cognitive trajectories in Chinese aging cohort: a group-based trajectory modeling study.

Wang Hong, Deng Weisheng, Qiu Wei

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Аннотация

BACKGROUND

Conflicting evidence exists regarding the associations between headache- and cognition, with conventional methods failing to capture the heterogeneous cognitive trajectories. We investigated dynamic relationships using group-based trajectory modeling (GBTM).

METHODS

This longitudinal analysis included 2,949 participants aged ≥45 from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2020). Headache was ascertained via a standardized questionnaire. Cognitive trajectories were derived from global cognition Z-scores using GBTM. Multinomial logistic regression evaluated headache-cognition associations, adjusting for demographics, health behaviors, and comorbidities. Stratified analyses tested effect modification by demographics, health behaviors, and comorbidities

RESULTS

GBTM identified three cognitive trajectories: low (17.5%), medium (43.8%), and high (38.7%). Headache significantly increased the probability of belonging to low (OR = 1.29, 95% CI: 1.11–1.50; p < 0.001) and medium trajectories (OR = 1.14, 95% CI: 1.01–1.30; p = 0.033). Alcohol, hypertension, and stroke amplified associations, while diabetes paradoxically attenuated them (p for interaction < 0.05).

CONCLUSION

Headache independently predicts adverse cognitive trajectories, with alcohol, hypertension, and stroke acting as critical effect modifiers. Paradoxically, diabetes attenuated this risk. Integrating headache screening into cognitive risk stratification and targeting modifiable factors may mitigate cognitive risk.

Для цитирования: Wang Hong, Deng Weisheng, Qiu Wei. Headache associated with adverse cognitive trajectories in Chinese aging cohort: a group-based trajectory modeling study.. Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology. 2026. DOI: 10.1007/s10072-026-08922-8.

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