Frontiers in Public Health (Jul 2023)

Lifestyle factors that affect cognitive function–a longitudinal objective analysis

  • Noriyuki Kimura,
  • Yuuki Sasaki,
  • Teruaki Masuda,
  • Takuya Ataka,
  • Atsuko Eguchi,
  • Tatsuyuki Kakuma,
  • Etsuro Matsubara

DOI
https://doi.org/10.3389/fpubh.2023.1215419
Journal volume & issue
Vol. 11

Abstract

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BackgroundIdentifying lifestyle factors associated with cognitive decline has critical clinical and public health implications for dementia prevention in later life. The longitudinal associations of sleep and physical activity with cognitive function remain unclear. This study examined whether objectively measured sleep and physical activity were longitudinally associated with cognitive function in older adults over a three-year period.MethodsThis prospective cohort study enrolled 855 community-dwelling adults aged 65 and older, who were followed from 2015 to 2019. All participants were required to wear a wearable sensor for 7 consecutive days every 3 months and had annual cognitive assessments. Wearable sensor data (August 2015–September 2019) and Mini-Mental State Examination (MMSE) scores (August 2015–April 2019) were collected over 3 years of follow-up. First, principal component analysis was conducted to reduce the dimensions of the sleep and physical activity variables to two principal components for inclusion in a mixed-effects model. The sleep index consisted of sleep efficiency, time awake after sleep onset, and waking frequency. The physical activity index was composed of walking comprised steps per day and time devoted to light or moderate-to-vigorous physical activity. A higher sleep index indicated poor sleep quality, whereas a lower physical activity index indicated less physical activity. Second, a linear mixed effect model was used to examine the longitudinal association of sleep and physical activity indices with cognitive decline over time.ResultsIn total, 855 adults were recruited for this study at baseline. Of these, 729 adults (85.3%) completed a measurement of lifestyle factors and an annual cognitive testing, whereas 126 were excluded because of death or loss during follow-up. After adjusting for age, sex, education level, and time, the sleep index was inversely associated with MMSE scores (estimate, −0.06229; standard error, 0.02202; p = 0.0047) and the physical activity index was positively associated with MMSE scores (estimate, 0.06699; standard error, 0.03343; p = 0.0453).ConclusionPoor sleep quality and lower physical activity were significant risk factors for subsequent cognitive decline in older adults. The present study facilitates the development of novel evidence-based interventions for physical activity and sleep quality to delay cognitive decline.

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