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Background <p>Physical activity is a modifiable lifestyle factor linked to better brain health in older adults, yet the optimal parameters (e.g., frequency, duration), and person-specific interactions (e.g., age, sex), remain unclear.</p> Methods <p>We developed a novel algorithm to isolate real-world physical activity “sessions” (at least 10&#xa0;min at greater than or equal to 40 steps/min) from 30 days of wrist actigraphy data in 279 older adults without dementia. Ridge regression models assessed associations of 42 in- and out-of-session physical activity features and their interactions with demographics on cognition and neuroimaging outcomes.</p> Results <p>79% of participants engaged in at least one physical activity session (“exercisers”). Exercisers had lower white matter hyperintensity burden compared to non-exercisers. Session frequency and session step cadence emerged as the most important predictors of brain health, particularly for white matter health indices and executive function, with relatively stronger associations in females. Out-of-session features and all interactions with age were least predictive.</p> Conclusions <p>Physical activity session frequency and cadence were the most robust predictors of brain health, emphasizing the importance of physical activity structure over quantity for dementia prevention strategies.</p>

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The active ingredients: physical activity features linked to healthy brain aging

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月5日

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  • Claire J. Cadwallader,
  • Pedro Pinheiro-Chagas,
  • Rowan Saloner,
  • Laura Fenton,
  • Anna M. VandeBunte,
  • May Lin,
  • Albert Pham,
  • Coty Chen,
  • Valentina E. Diaz,
  • Molly Olzinski,
  • Sophia Licata,
  • Lana Callies,
  • Carina Lo,
  • Jessica Buxton,
  • Yann Cobigo,
  • Gil Rabinovici,
  • Joel H. Kramer,
  • Kaitlin B. Casaletto,
  • Emily W. Paolillo

摘要

Background

Physical activity is a modifiable lifestyle factor linked to better brain health in older adults, yet the optimal parameters (e.g., frequency, duration), and person-specific interactions (e.g., age, sex), remain unclear.

Methods

We developed a novel algorithm to isolate real-world physical activity “sessions” (at least 10 min at greater than or equal to 40 steps/min) from 30 days of wrist actigraphy data in 279 older adults without dementia. Ridge regression models assessed associations of 42 in- and out-of-session physical activity features and their interactions with demographics on cognition and neuroimaging outcomes.

Results

79% of participants engaged in at least one physical activity session (“exercisers”). Exercisers had lower white matter hyperintensity burden compared to non-exercisers. Session frequency and session step cadence emerged as the most important predictors of brain health, particularly for white matter health indices and executive function, with relatively stronger associations in females. Out-of-session features and all interactions with age were least predictive.

Conclusions

Physical activity session frequency and cadence were the most robust predictors of brain health, emphasizing the importance of physical activity structure over quantity for dementia prevention strategies.