Leisure-time sedentary behaviors are differentially associated with all-cause dementia regardless of engagement in physical activity

Proc Natl Acad Sci U S A. 2022 Aug 30;119(35):e2206931119. doi: 10.1073/pnas.2206931119. Epub 2022 Aug 22.

Abstract

Sedentary behavior (SB) is associated with cardiometabolic disease and mortality, but its association with dementia is currently unclear. This study investigates whether SB is associated with incident dementia regardless of engagement in physical activity (PA). A total of 146,651 participants from the UK Biobank who were 60 years or older and did not have a diagnosis of dementia (mean [SD] age: 64.59 [2.84] years) were included. Self-reported leisure-time SBs were divided into two domains: time spent watching television (TV) or time spent using a computer. A total of 3,507 individuals were diagnosed with all-cause dementia over a mean follow-up of 11.87 (±1.17) years. In models adjusted for a wide range of covariates, including time spent in PA, time spent watching TV was associated with increased risk of incident dementia (HR [95% CI] = 1.24 [1.15 to 1.32]) and time spent using a computer was associated with decreased risk of incident dementia (HR [95% CI] = 0.85 [0.81 to 0.90]). In joint associations with PA, TV time and computer time remained significantly associated with dementia risk at all PA levels. Reducing time spent in cognitively passive SB (i.e., TV time) and increasing time spent in cognitively active SB (i.e., computer time) may be effective behavioral modification targets for reducing risk of dementia regardless of engagement in PA.

Keywords: Alzheimer’s disease; brain health; exercise; sitting; television.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Computers* / statistics & numerical data
  • Dementia* / epidemiology
  • Dementia* / etiology
  • Exercise*
  • Humans
  • Incidence
  • Leisure Activities*
  • Screen Time*
  • Sedentary Behavior*
  • Television* / statistics & numerical data
  • United Kingdom