Characterizing Gray matter atrophy patterns associated with accelerometer-measured sedentary behavior: a population-based study Article Swipe
Minle Tian
,
Xiaolei Han
,
Ming Mao
,
Xiaomeng Li
,
Yi Dong
,
Jihui Ding
,
Qinghua Zhang
,
Shi Tang
,
Xiaojuan Han
,
Lin Song
,
Tingting Hou
,
Lin Cong
,
Yifeng Du
,
Chengxuan Qiu
,
Yongxiang Wang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s11682-025-01054-1
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s11682-025-01054-1
Evidence has linked self-reported sedentary behaviors with dementia and cognitive impairment; however, the underlying mechanisms remain poorly understood. We investigated the associations of accelerometer-measured sedentary behavior patterns with gray matter atrophy patterns in rural-dwelling older adults, while taking into account the manner in which sedentary time is accrued (in short or long bouts). This community-based study involved 911 dementia-free older adults (age ≥ 60 years, 59% women) who participated in both ActiGraph and brain MRI substudies within MIND-China (2018–2020). Sedentary behavior parameters (total sedentary time, mean sedentary bout duration, and sedentary breaks) were recorded with accelerometers. Regional gray matter volumes (GMV) were measured using voxel-based morphometry (VBM) methods. Data were analyzed using the general linear regression models, restricted cubic spline curves, and VBM analysis. There was an inverted U-shaped association between daily sedentary time and GMV in temporal, cingulate, and medial temporal cortex, while longer mean sedentary bout duration was linearly related to decreased GMV in total, frontal, temporal, insula, cingulate, and medial temporal cortex. Greater daily time spent in light or moderate-to-vigorous physical activity (LPA and MVPA) was correlated with larger insula GMV. The VBM analysis suggested that prolonged daily total sedentary time and mean sedentary bout duration were significantly associated with smaller GMV in extensive brain regions, especially in thalamus and insula. In conclusion, gray matter atrophy associated with sedentary behavior in older adults is characterized by reduced GMV in global, frontal, temporal, medial temporal, and cingulate cortex, especially in the insula and thalamus regions.
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- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s11682-025-01054-1
- https://link.springer.com/content/pdf/10.1007/s11682-025-01054-1.pdf
- OA Status
- hybrid
- References
- 43
- OpenAlex ID
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https://openalex.org/W4414670608Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s11682-025-01054-1Digital Object Identifier
- Title
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Characterizing Gray matter atrophy patterns associated with accelerometer-measured sedentary behavior: a population-based studyWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-30Full publication date if available
- Authors
-
Minle Tian, Xiaolei Han, Ming Mao, Xiaomeng Li, Yi Dong, Jihui Ding, Qinghua Zhang, Shi Tang, Xiaojuan Han, Lin Song, Tingting Hou, Lin Cong, Yifeng Du, Chengxuan Qiu, Yongxiang WangList of authors in order
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https://doi.org/10.1007/s11682-025-01054-1Publisher landing page
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https://link.springer.com/content/pdf/10.1007/s11682-025-01054-1.pdfDirect link to full text PDF
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hybridOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007/s11682-025-01054-1.pdfDirect OA link when available
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| abstract_inverted_index.analysis | 187 |
| abstract_inverted_index.analyzed | 111 |
| abstract_inverted_index.behavior | 26, 81, 223 |
| abstract_inverted_index.dementia | 8 |
| abstract_inverted_index.duration | 149, 199 |
| abstract_inverted_index.frontal, | 158, 234 |
| abstract_inverted_index.however, | 12 |
| abstract_inverted_index.inverted | 128 |
| abstract_inverted_index.involved | 57 |
| abstract_inverted_index.linearly | 151 |
| abstract_inverted_index.measured | 103 |
| abstract_inverted_index.methods. | 108 |
| abstract_inverted_index.patterns | 27, 32 |
| abstract_inverted_index.physical | 174 |
| abstract_inverted_index.recorded | 94 |
| abstract_inverted_index.regions, | 209 |
| abstract_inverted_index.regions. | 247 |
| abstract_inverted_index.temporal | 142, 164 |
| abstract_inverted_index.thalamus | 212, 246 |
| abstract_inverted_index.ActiGraph | 72 |
| abstract_inverted_index.Sedentary | 80 |
| abstract_inverted_index.analysis. | 124 |
| abstract_inverted_index.behaviors | 6 |
| abstract_inverted_index.cingulate | 239 |
| abstract_inverted_index.cognitive | 10 |
| abstract_inverted_index.decreased | 154 |
| abstract_inverted_index.duration, | 89 |
| abstract_inverted_index.extensive | 207 |
| abstract_inverted_index.prolonged | 190 |
| abstract_inverted_index.sedentary | 5, 25, 45, 84, 87, 91, 133, 147, 193, 197, 222 |
| abstract_inverted_index.suggested | 188 |
| abstract_inverted_index.temporal, | 138, 159, 235, 237 |
| abstract_inverted_index.MIND-China | 78 |
| abstract_inverted_index.associated | 202, 220 |
| abstract_inverted_index.cingulate, | 139, 161 |
| abstract_inverted_index.correlated | 180 |
| abstract_inverted_index.especially | 210, 241 |
| abstract_inverted_index.mechanisms | 15 |
| abstract_inverted_index.parameters | 82 |
| abstract_inverted_index.regression | 116 |
| abstract_inverted_index.restricted | 118 |
| abstract_inverted_index.substudies | 76 |
| abstract_inverted_index.underlying | 14 |
| abstract_inverted_index.association | 130 |
| abstract_inverted_index.conclusion, | 216 |
| abstract_inverted_index.impairment; | 11 |
| abstract_inverted_index.morphometry | 106 |
| abstract_inverted_index.understood. | 18 |
| abstract_inverted_index.voxel-based | 105 |
| abstract_inverted_index.associations | 22 |
| abstract_inverted_index.investigated | 20 |
| abstract_inverted_index.participated | 69 |
| abstract_inverted_index.characterized | 228 |
| abstract_inverted_index.dementia-free | 59 |
| abstract_inverted_index.self-reported | 4 |
| abstract_inverted_index.significantly | 201 |
| abstract_inverted_index.(2018–2020). | 79 |
| abstract_inverted_index.rural-dwelling | 34 |
| abstract_inverted_index.accelerometers. | 96 |
| abstract_inverted_index.community-based | 55 |
| abstract_inverted_index.moderate-to-vigorous | 173 |
| abstract_inverted_index.accelerometer-measured | 24 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 15 |
| citation_normalized_percentile.value | 0.56421083 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |