| Title: | Accelerometer-derived hourly segmentation of daily physical activity frequency and brain health: A prospective cohort study in middle-aged/older adults |
| Journal: | Journal of Affective Disorders |
| Published: | 2 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41780695/ |
| DOI: | https://doi.org/10.1016/j.jad.2026.121528 |
Publication 17546
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Abstract
Physical activity (PA) is known to enhance brain health; however, prior research has predominantly concentrated on the total volume of PA, often overlooking the frequency of daily PA on an hourly basis. This prospective cohort study examined 69,393 middle-aged and older adults, utilizing wrist-worn accelerometer data to assess PA. A novel PA frequency score was developed, which integrated light PA (LPA) and moderate-to-vigorous PA (MVPA) across 18 hourly segments (6:00 AM-12:00 AM). Participants were categorized into Inactive, Active, and Very Active groups. After adjusting for potential confounders, it was observed that individuals in the Active and Very Active groups exhibited a reduced risk of developing brain disorders such as dementia, anxiety, depression, migraine, Parkinson's disease, and stroke over a median follow-up period of 7.41 years. Magnetic Resonance Imaging (MRI) findings demonstrated that each unit increase in the PA frequency score correlated with a 51.55 mm3 reduction in white matter hyperintensities, effectively offsetting approximately two months of typical age-related WMH progression. It is important to note that these findings may be particularly relevant to middle-aged and older adults, as the initial diagnoses of depression or anxiety in this demographic likely represent late-onset sub-phenotypes. These results demonstrate that most associations remained statistically significant independent of the total volume of LPA/MVPA, underscoring the significance of increasing the number of hourly active segments that may contribute to maintaining brain health, thereby providing novel evidence for public health initiatives.</p>
5 Authors
- Zhouhua Li
- Yuexiu Lei
- Zheyu Wen
- Linshan Duan
- Zheman Xiao
1 Application
| Application ID | Title |
|---|---|
| 143136 | Toward precision medicine in the comorbidity of epilepsy and headaches based on multimodal imaging genomics analysis |
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