TY - JOUR
T1 - Association of Self-Reported Sleep Characteristics With Neuroimaging Markers of Brain Aging Years Later in Middle-Aged Adults
AU - Cavaillès, Clémence
AU - Dintica, Christina
AU - Habes, Mohamad
AU - Leng, Yue
AU - Carnethon, Mercedes R.
AU - Yaffe, Kristine
N1 - Publisher Copyright:
Copyright © 2024 American Academy of Neurology.
PY - 2024/10/23
Y1 - 2024/10/23
N2 - Objectives To determine the association between early midlife sleep and advanced brain aging patterns in late midlife. Methods Using the CARDIA study, we analyzed sleep data at baseline and 5 years later, focusing on short sleep duration, bad sleep quality (SQ), difficulty initiating and maintaining sleep (DIS and DMS), early morning awakening (EMA), and daytime sleepiness. These were categorized into 0–1, 2–3, and >3 poor sleep characteristics (PSC). Brain MRIs obtained 15 years later were used to determine brain age through a machine learning approach based on age-related atrophy. Results This cohort study included 589 participants (mean age 40.4 ± 3.4 years, 53% women). At baseline, around 70% reported 0–1 PSC, 22% reported 2%–3%, and 8% reported >3 PSC. In multivariable linear regression analyses, participants with 2–3 or >3 PSC had 1.6-year (β = 1.61, 95% CI 0.28–2.93) and 2.6-year (β = 2.64, 95% CI 0.59–4.69) older brain age, respectively, compared with those with 0–1 PSC. Of the individual characteristics, bad SQ, DIS, DMS, and EMA were associated with greater brain age, especially when persistent over the 5-year followup. Discussion Poor sleep was associated with advanced brain age in midlife, highlighting the importance of investigating early sleep interventions for preserving brain health.
AB - Objectives To determine the association between early midlife sleep and advanced brain aging patterns in late midlife. Methods Using the CARDIA study, we analyzed sleep data at baseline and 5 years later, focusing on short sleep duration, bad sleep quality (SQ), difficulty initiating and maintaining sleep (DIS and DMS), early morning awakening (EMA), and daytime sleepiness. These were categorized into 0–1, 2–3, and >3 poor sleep characteristics (PSC). Brain MRIs obtained 15 years later were used to determine brain age through a machine learning approach based on age-related atrophy. Results This cohort study included 589 participants (mean age 40.4 ± 3.4 years, 53% women). At baseline, around 70% reported 0–1 PSC, 22% reported 2%–3%, and 8% reported >3 PSC. In multivariable linear regression analyses, participants with 2–3 or >3 PSC had 1.6-year (β = 1.61, 95% CI 0.28–2.93) and 2.6-year (β = 2.64, 95% CI 0.59–4.69) older brain age, respectively, compared with those with 0–1 PSC. Of the individual characteristics, bad SQ, DIS, DMS, and EMA were associated with greater brain age, especially when persistent over the 5-year followup. Discussion Poor sleep was associated with advanced brain age in midlife, highlighting the importance of investigating early sleep interventions for preserving brain health.
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U2 - 10.1212/WNL.0000000000209988
DO - 10.1212/WNL.0000000000209988
M3 - Article
C2 - 39442064
AN - SCOPUS:85207703864
SN - 0028-3878
VL - 103
JO - Neurology
JF - Neurology
IS - 10
M1 - e209988
ER -