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Body weight in neurological and psychiatric disorders: a large prospective cohort study

Nature Mental Health volume 2, pages 41–51 (2024)Cite this article

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Abstract

There is increasing attention on the associations between body weight and several neurological and psychiatric disorders. Using a total of 438,483 participants from the UK Biobank, we aimed to understand the effects of body mass index (BMI), BMI change and BMI-metabolic health status on the incidence of common neurological and psychiatric disorders. Associations of body weight with six disorders (stroke, dementia, Parkinson’s disease, anxiety, depression and sleep disorders) were analysed by Cox regression models. We performed linear regression models and mediation analysis to explore the underlying mechanisms. Overweight or obesity group had a higher risk of stroke, anxiety, depression and sleep disorders. Metabolically healthy obesity demonstrated a higher risk of depression and sleep disorders. The differing effects of metabolically healthy versus unhealthy obesity on brain structure, dietary intake and inflammatory markers provided clues to the underlying associations. Hence, weight management should be recommended for individuals with obesity irrespective of their metabolic health status.

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Fig. 1: Guideline of the study.
Fig. 2: Non-linear associations between BMI and the risk of neurological and psychiatric disorders.
Fig. 3: Associations of BMI change and BMI-metabolic health status with the risk of neurological and psychiatric disorders.
Fig. 4: Differing effects of MHO versus MUO on brain structure and dietary intake.
Fig. 5: The mediating role of blood inflammatory markers in the relationship between BMI-metabolic health status and neurological and psychiatric disorders.

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Data availability

The data that support the findings of this study are available from UKB project site, subject to registration and application process. Further details can be found at https://www.ukbiobank.ac.uk. The GWAS data of neurological and psychiatric disorders were retrieved from the exogenous population which is publicly available (stroke: https://doi.org/10.1038/s41588-018-0058-3; AD: https://doi.org/10.1038/s41588-019-0358-2; PD: https://doi.org/10.1016/s1474-4422(19)30320-5; major depression: https://doi.org/10.1038/s41588-018-0090-3; anxiety disorders: https://doi.org/10.1038/ng.3888; insomnia: obstructive sleep apnoea: https://doi.org/10.1183/13993003.03091-2020).

Code availability

Packages including ‘survival’ (version 3.5-3), ‘TwoSampleMR’ (version 0.5.6) and ‘mediation’ (version 4.5.0) in R version 4.1.2 were used to perform Cox proportional hazard regression model, MR study and mediation analysis, respectively. The codes of these analyses were available at https://github.com/RongzeWang06/BW. Freesurfer v6.0 and FSL 6.0 were used to process the imaging data, and MATLAB 2018b was used to perform corresponding linear association analysis.

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Acknowledgements

The authors gratefully thank all the participants and professionals contributing to the UKB. This study was funded by the STI2030-Major Projects (2022ZD0211600), National Natural Science Foundation of China (82071201, 82071997), Shanghai Municipal Science and Technology Major Project (2018SHZDZX01), Research Start-up Fund of Huashan Hospital (2022QD002), Excellence 2025 Talent Cultivation Program at Fudan University (3030277001), Shanghai Talent Development Funding for The Project (2019074), Shanghai Rising-Star Program (21QA1408700), 111 Project (B18015) and ZHANGJIANG LAB, Tianqiao and Chrissy Chen Institute and the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, and Shanghai Center for Brain Science and Brain-Inspired Technology, Fudan University. The funding sources had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review or approval of the manuscript; and decision to submit the manuscript for publication.

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  1. These authors contributed equally: Rong-Ze Wang, Yu He.

Authors and Affiliations

  1. Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China

    Rong-Ze Wang, Yu He, Yue-Ting Deng, Yi Zhang, Wei Cheng & Jin-Tai Yu

  2. Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China

    Hui-Fu Wang

  3. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

    Jian-Feng Feng & Wei Cheng

  4. Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China

    Jian-Feng Feng & Wei Cheng

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Contributions

Conceptualization, J.-T.Y.; methodology, R.-Z.W., Y.H. and Y.-T.D.; investigation, R.-Z.W., Y.H., Y.-T.D., H.-F.W. and Y.Z.; writing—original draft, R.-Z.W. and Y.H.; writing—review and editing, R.-Z.W. and Y.H.; funding acquisition, J.-T.Y.; resources, J.-F.F., W.C. and J.-T.Y.; supervision, W.C. and J.-T.Y.

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Correspondence to Jin-Tai Yu.

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Nature Mental Health thanks Raaj Biswas, Richard Musil and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Methods, Tables 1–33 and Figs. 1–3.

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Wang, RZ., He, Y., Deng, YT. et al. Body weight in neurological and psychiatric disorders: a large prospective cohort study. Nat. Mental Health 2, 41–51 (2024). https://doi.org/10.1038/s44220-023-00158-1

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