Total Sedentary Time and Cognitive Function in Middle-Aged and Older Adults: A Systematic Review and Meta-analysis

Abstract

Background: An estimated 47 million people have dementia globally, and around 10 million new cases are diagnosed each year. Many lifestyle factors have been linked to cognitive impairment; one emerging modifiable lifestyle factor is sedentary time.

Objective: To conduct a systematic review and meta-analysis of peer-reviewed literature examining the association between total sedentary time with cognitive function in middle-aged and older adults under the moderating conditions of (a) type of sedentary time measurement; (b) the cognitive domain being assessed; (c) looking at sedentary time using categorical variables (i.e., high versus low sedentary time); and (d) the pattern of sedentary time accumulation (e.g., longer versus shorter bouts). We also aimed to examine the prevalence of sedentary time in healthy versus cognitively impaired populations and to explore how experimental studies reducing or breaking up sedentary time affect cognitive function. Lastly, we aimed to conduct a quantitative pooled analysis of all individual studies through meta-analysis procedures to derive conclusions about these relationships.

Methods: Eight electronic databases (EMBASE; Web of Science; PsycINFO; CINAHL; SciELO; SPORTDiscus; PubMed; and Scopus) were searched from inception to February 2021. Our search included terms related to the exposure (i.e., sedentary time), the population (i.e., middle-aged and older adults), and the outcome of interest (i.e., cognitive function). PICOS framework used middle-aged and older adults where there was an intervention or exposure of any sedentary time compared to any or no comparison, where cognitive function and/or cognitive impairment was measured, and all types of quantitative, empirical, observational data published in any year were included that were published in English. Risk of bias was assessed using QualSyst.

Results: Fifty-three studies including 83,137 participants met the inclusion criteria of which 23 studies had appropriate data for inclusion in the main meta-analysis. The overall meta-analysis suggested that total sedentary time has no association with cognitive function (r = -0.012 [95% CI - 0.035, 0.011], p = 0.296) with marked heterogeneity (I² = 89%). Subgroup analyses demonstrated a significant negative association for studies using a device to capture sedentary time r = -0.035 [95% CI - 0.063, - 0.008], p = 0.012). Specifically, the domains of global cognitive function (r = -0.061 [95% CI - 0.100, - 0.022], p = 0.002) and processing speed (r = -0.067, [95% CI - 0.103, - 0.030], p < 0.001). A significant positive association was found for studies using self-report (r = 0.037 [95% CI - 0.019, 0.054], p < 0.001). Specifically, the domain of processing speed showed a significant positive association (r = 0.057 [95% CI 0.045, 0.069], p < 0.001). For prevalence, populations diagnosed with cognitive impairment spent significantly more time sedentary compared to populations with no known cognitive impairments (standard difference in mean = -0.219 [95% CI - 0.310, - 0.128], p < 0.001).

Conclusions: The association of total sedentary time with cognitive function is weak and varies based on measurement of sedentary time and domain being assessed. Future research is needed to better categorize domains of sedentary behaviour with both a validated self-report and device-based measure in order to improve the strength of this relationship. PROSPERO registration number: CRD42018082384.

Keywords: Cognition; Cognitive decline; Meta-analysis; Middle-aged; Older adults; Sedentary behaviour; Systematic review.

Fig. 1

PRISMA flow diagram of the search and screening process in review of sedentary behaviour with cognitive function

Fig. 2

Forest plot of all studies reporting on an association of sedentary behaviour with cognitive function based on method of measurement (device or self-report) and cognitive domain

Fig. 3

Forest plot of all eligible studies for the meta-analysis reporting on the association of sedentary behaviour with cognitive function using a random-effects model. ACE-III Addenbrooke’s Cognitive Examination, ADAS-cog Alzheimer’s Disease Assessment Scale—Cognitive, MMSE Mini Mental State Examination, 3MS Modified Mini Mental State Examination, MoCA Montreal Cognitive Assessment. Note a is the SALSA cohort, b is the PATH cohort, c is the SGS cohort, and d is the SLAS2 cohort reported within one paper

Fig. 4

Funnel plot for all eligible studies in the meta-analysis reporting on the association of sedentary behaviour with cognitive function using a random-effects model

Fig. 5

Forest plot of all eligible studies for the meta-analysis that used a device as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with cognitive function using a random-effects model. c is the SGS cohort. ADAS-cog Alzheimer’s Disease Assessment Scale—Cognitive, MMSE Mini Mental State Examination, MoCA Montreal Cognitive Assessment

Fig. 6

Forest plot of all eligible studies for the meta-analysis that used a device as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with the cognitive domain of global cognitive function using a random-effects model. c is the SGS cohort. ADAS-cog Alzheimer’s Disease Assessment Scale—Cognitive, MMSE Mini Mental State Examination, MoCA Montreal Cognitive Assessment

Fig. 7

Forest plot of all eligible studies for the meta-analysis that used a device as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with the cognitive domain of processing speed using a random-effects model. RT reaction time; TMT A Trail Making Test A

Fig. 8

Forest plot of all eligible studies for the meta-analysis that used a device as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with the cognitive domain of working memory using a random-effects model. TMT B Trail Making Test B

Fig. 9

Forest plot of all eligible studies for the meta-analysis that used a device as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with the cognitive domain of episodic memory using a random-effects model. HVLT-R Hopkins Verbal Learning Test-Revised

Fig. 10

Forest plot of all eligible studies for the meta-analysis that used a device as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with the cognitive domain of cognitive flexibility using a random-effects model. TMT B Trail Making Test B

Fig. 11

Forest plot of all eligible studies for the meta-analysis that used self-report as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with cognitive function using a random-effects model. MMSE Mini Mental State Examination, 3MS Modified Mini Mental State Examination. Note a is the SALSA cohort, b is the PATH cohort, and d is the SLAS2 cohort reported within one paper

Fig. 12

Forest plot of all eligible studies for the meta-analysis that used self-report as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with the cognitive domain of global. MMSE Mini Mental State Examination, 3MS Modified Mini Mental State Examination, SR self-report. Note a is the SALSA cohort, b is the PATH cohort, and d is the SLAS2 cohort reported within one paper

Fig. 13

Forest plot of all eligible studies for the meta-analysis that used self-report as the method a measurement for sedentary behaviour reporting on the association of sedentary behaviour with the cognitive domain of processing speed using a random-effects model. TMT A Trail Making Test A, DSST Digit Symbol Substitution Test. Note a is a population with over 7 h of sleep, and b is a population with under 7 h of sleep

Fig. 14

Forest plot of all eligible studies for the meta-analysis that reported on the prevalence of sedentary time for a clinical (i.e., diagnosed with cognitive impairment) versus non-clinical (i.e., cognitively healthy) population. a are females, and b are males. Cog impaired, cognitively impaired, CD cognitive decline, MCI mild cognitive impairment, AD Alzheimer’s disease