Journal Article
Meta-Analysis
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Physical Exercise and Health, 6: Sedentary Time, Independent of Health-Related Physical Activity, as a Risk Factor for Dementia in Older Adults.

Sedentary behaviors are leisurely behaviors that occur during waking hours performed while lying down or seated; examples are relaxing, conversing, using a smartphone, watching television, traveling in private or public transport, and thinking or working at a desk. Sedentary behaviors are common in everyday life; the average person spends 9-10 h/d sedentary. Findings from meta-analyses show that higher levels of physical activity are associated with a reduced risk of dementia and that near-absence of moderate to vigorous physical activity is associated with an increased risk of dementia. Sedentariness is a clearly defined construct that is more than just low levels of physical activity. Sedentariness, therefore, merits independent study. In this context, a recent cohort study, conducted in elderly subjects (mean age, 67 years) who were followed for a mean of 6.7 years, found that sedentariness, independent of current levels of moderate to vigorous physical activity, was associated in a dose-dependent fashion with the risk of incident dementia; the finding held true when reverse causation was addressed through the exclusion of subjects who developed dementia within 4 years of follow-up. The adjusted 10-year risk of dementia rose from about 8% with sedentariness at 10 h/d to about 23% with sedentariness at 15 h/d; the difference is clinically meaningful. Limitations of studies in the field are that residual confounding cannot be excluded, and that no randomized controlled trials exist upon which guidance may be based. Nevertheless, it could be prudent to decrease sedentary behaviors if only because these have also been associated with other adverse physical and mental health outcomes. Additional subjects explained in this article include reverse causation and how it may be dealt with during research design and data analysis, individual participant data meta-analysis, and making sense of results that are reported in terms of "per 1,000 person-years."

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