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Association between sedentary behavior and dementia: a systematic review and meta-analysis of cohort studies

BMC Psychiatry volume 25, Article number: 451 (2025) Cite this article

Abstract

Objective

This study aimed to assess the association between sedentary behavior (SB) and dementia among the general adult population.

Methods

We queried PubMed, Web of Science, Embase, and Cochrane Library from their inception to November 3, 2024. Two authors independently extracted the data from included studies, including hazard ratios (HRs) and their 95% confidence intervals (CIs), to assess the risk of dementia among individuals with SB. The quality of included studies was assessed using the Newcastle–Ottawa Scale. We used a random effects model if I2 > 50% and p < 0.10; otherwise, a fixed-effect model was used. In addition, we assessed publication bias by funnel plot, and performed leave-one-out sensitivity analysis.

Results

We included ten cohort studies, nine of which were of high quality. Our analysis demonstrated an increased risk of dementia among individuals with SB (pooled HRs, 1.17; 95% CIs, 1.06–1.29). Individuals with high sedentary time (ST), defined by TV viewing, demonstrated a 31% increased risk of dementia compared to those with low ST (pooled HRs, 1.31; 95% CIs, 1.25–1.37). No significantly increased risk for dementia was observed among individuals with high computer usage time (pooled HRs, 0.89; 95% CIs, 0.73–1.09). However, when SB was defined by other methods, individuals with high ST demonstrated a 33% increased risk of dementia compared to those with low ST (pooled HRs, 1.33; 95% CIs, 1.25–1.42).

Conclusion

SB increases the risk of dementia, but SB defined by computer usage time has not shown this association.

Trial registration

CRD42023493109.

Peer Review reports

Introduction

Dementia is a clinical syndrome that encompasses various progressive degenerative brain disorders that affect memory, cognition, behavior, and mood [1]. It is characterized by a gradual deterioration in cognitive function, with Alzheimer's dementia representing the most prevalent form [2]. According to the World Health Organization (WHO), the prevalence of dementia is anticipated to increase from 55 million individuals in 2019 to approximately 139 million by 2050 [3]. As the disease progresses, patients with dementia experience cognitive decline, reduced living ability, and various abnormal mental conditions and behaviors, resulting in their inability to fully care for themselves and the need for long-term car [4]. The increase in patients with dementia will result in an increase in annual costs associated with dementia from $1.3 trillion in 2019 to $2.8 trillion in 2030, imposing a significant burden on patients, caregivers, and society [5].

Sedentary behavior(SB) has been regarded as a growing health concern in aging society, associated with the risk of various chronic diseases [6]. SB is defined as any activity during waking hours, which is characterized by an energy expenditure of 1.5 metabolic equivalents or less, while in a seated or reclined position [7]. Common SB include TV viewing, using electronic devices, and driving a motor vehicle while seated or reclined [8]. Previous studies have indicated that sedentary lifestyle is a risk factor for dementia [9, 10]. Although, physical activity (PA), as a modifiable protective lifestyle factor, is associated with lower incidence of dementia an Alzheimer’s disease (AD) [11,12,13]. Some studies indicate that exercise does not completely reverse various deleterious cardiovascular and metabolic effects caused by SB [14,15,16].

In recent years, there has been a growing interest in the association between SB and dementia [17, 18]. There have been some systematic reviews about the association between SB and dementia [19,20,21], most of which are qualitative studies. Existing quantitative studies used the relative risk (RR) as the effect size metric, and the definition of SB was inconsistent. Actually, a number of new studies have been published in recent years, using hazard ratios (HRs) to quantified the association between SB and dementia, as well as classifying SB into different types. Despite evidence suggesting that the risk direction depends on the type of activity performed during sedentary periods, there has not yet been a meta-analysis exploring the impact of different types of SB on dementia [22].

Therefore, we conducted a meta-analysis of cohort studies in the general adult population and selected HRs as the effect size metric to evaluate the association between SB and the risk of dementia. Additionally, we further explored the effects of different types of SB on dementia to provide more accurate evidence to support intervention strategies for dementia.

Methods

Literature search

We conducted a systematic review following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines and Meta-Analysis (Preferred Reporting Items for Systematic Reviews and Meta-Analyses [PRISMA]) statement [23, 24]. We queried PubMed, Web of Science, Embase, and Cochrane Library from their inception to November 3, 2024 using primary search terms ([sedent* OR sedentary behav* OR sitting OR physical inactivity OR screen time] AND [dementia OR Alzheimer’s disease]). Additionally, we assessed all the included study references and conducted the final retrieval strategy by combining MeSH and related search terms. There were no strict restrictions on publication language.

Study selection

The inclusion criteria were as follows: (1) exposure to SB, (2) cohort studies, (3) diagnosis of dementia according to internationally recognized criteria, and (4) use of HRs to assess the association between SB and dementia.

The exclusion criteria were as follows: (1) use of cross-sectional or case–control study designs; (2) exposure to physical inactivity/activity; (3) assessed outcomes associated with mild cognitive impairment and subjective cognitive decline; and (4) duplicate reports, animal trials, case reports, reviews, letters or commentaries, and abstracts with limited or insufficient data.

Two authors (J-YL and Y-PH) independently assessed the titles and abstracts of the studies using EndNote 20. The full text of the appropriate articles was obtained, and any conflicts were resolved through discussions with a third author (T-HT).

Data extraction

Data from the included studies were collected, which presented details, such as first author, publication year, data source, follow-up period, baseline age, diagnostic criteria for dementia, assessment of sedentary time(ST) or SB, and dementia cases (incidence, %).

For type of SB, we included studies calculating TV viewing time, computer usage time, sitting time, driving time [7]. In addition, for assessment of dementia, we only included studies indicating clear diagnosis of dementia that meet the internationally recognized criteria. Method of assessment included (1) ICD- 10 (A81.0; F00.X-F02.X) [25,26,27,28,29]; (2) hospital impatient record [26, 28]; (3) Japanese long-term care insurance [30, 31]; (4) medical record [27, 32,33,34].

Quality assessment

We assessed the quality of included studies using the Newcastle–Ottawa Scale (NOS), a common methodological tool for cohort studies [35]. Two researchers (J-Y L and Y-P H) independently assessed the quality of these studies, and any conflicts were resolved through a detailed discussion to achieve a consensus score with the third author (T-H T). NOS is a star scoring system (range, 0–9 stars) across three domains: study selection (four stars), group comparability (two stars), and outcome ascertainment (three stars). Studies with seven or more stars were considered high quality.

Analysis

We conducted a meta-analysis of the raw data using Review Manager 5.4 (The Nordic Cochrane Centre, Cochrane Collaboration, Copenhagen, Denmark). HRs and 95% confidence intervals(CIs) were extracted directly from included articles and we calculated pooled HRs with 95% CIs with inverse-variance weighting. We assessed heterogeneity among the included studies using I2 statistics, which represent the total variation percentage [36]. We used a random effects model if I2 > 50% and p < 0.10; otherwise, a fixed-effect model was used. In addition, we assessed publication bias by funnel plot [37, 38], and performed leave-one-out sensitivity analysis [39]. To explore the source of heterogeneity, we conducted subgroup analysis based on definitions of SB, including TV viewing time, computer usage time, and other methods. Evidence quality was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach on the online tool GRADEpro GDT developed by the GRADE Working Group. The GRADE method identifies eight factors that affect the quality of evidence, classifying it into four levels: high, moderate, low, and very low [40].

Results

Characteristics of included studies

Figure 1 illustrates the study selection process. We reviewed 8349 records following the removal of duplicates. Following an examination of titles and abstracts 8268 studies were excluded. Following the exclusion of 44 potentially eligible studies that did not meet the selection criteria, 10 studies were included.

Fig. 1
figure 1

PRISMA flow-diagram showing the study selection process

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Table 1 outlines the characteristics of these ten studies [25,26,27,28,29,30,31,32,33,34]. Published between 2022 and 2024, all ten studies included 3,217,113 participants and conducted in UK and Japan. While nine study data sources were extracted from the UK Biobank and may have overlapped, conducting this review presented no challenges. This was because the follow-up periods, baseline ages, and outcomes varied significantly among the included studies. The years of follow-up for the included studies ranged from 3.4 years to 13.6 years. Different studies defined SB in different ways, which we have grouped into three categories, including TV viewing time, computer usage time, and other methods. And the other methods include driving time, sitting or accelerometer data. Additionally, nine studies [25,26,27,28,29, 31,32,33,34] were rated ≥ 7 stars using the NOS score system, indicating a high quality.

Table 1 Characteristics of included studies
Full size table

Table 2 summarizes the study findings and GRADE assessment for each outcome. While the majority of outcomes exhibited a low level of certainty, the risk of overall dementia and dementia-associated SB, which is defined by computer usage time, exhibited very low certainty due to inconsistency.

Table 2 GRADE summary of findings
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Association between SB and dementia

All studies that assessed the association between SB and dementia, comprised 35,201 patients with dementia and 2,566,944 controls [25,26,27,28,29,30,31,32,33,34]. Significant statistical heterogeneity was observed among these studies (I2 = 88%). Individuals with high ST demonstrated a 17% increased risk of dementia compared to those with low ST (pooled HRs, 1.17; 95% CIs, 1.06–1.29) (Fig. 2).

Fig. 2
figure 2

Meta-analysis of the association between sedentary behavior (overall) and dementia. (a) sedentary behavior defined by TV viewing time; (b) sedentary behavior defined by computer using time

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Subgroup analysis

Five studies assessed the association between SB (defined by TV viewing time) and dementia, which included 11,970 patients with dementia and 765,714 controls [26, 27, 29, 30, 33]. No significant statistical heterogeneity was observed (I2 = 31%). Individuals with high ST demonstrated a 31% increased risk of dementia compared to those with low ST (pooled HRs, 1.31; 95% CIs, 1.25–1.37) (Fig. 3a).

Fig. 3
figure 3

a Meta-analysis of the association between sedentary behavior (defined by TV viewing time) and dementia (b) Meta-analysis of the association between sedentary behavior (defined by computer using time) and dementia (c) Meta-analysis of the association between sedentary behavior (defined by other methods) and dementia

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Five studies assessed the risk of dementia among individuals with SB (defined by computer usage time) and dementia, which included 16,272 patients with dementia and 1,113,528 controls [26, 27, 32, 33]. Significant statistical heterogeneity existed among these five studies (I2 = 87%). No significant difference was observed in the risk of dementia among individuals with low and high ST (pooled HRs, 0.89; 95% CIs, 0.73–1.09) (Fig. 3b).

Five studies provided data on the association between SB (defined by other methods) and dementia [25, 28, 31, 32, 34], which included 6,959 patients with dementia and 687,702 controls. As illustrated in Fig. 1, one study defined SB by driving time [32], one defined by sitting time [31] and one by the sum of TV viewing time, non-occupational computer usage time, and driving time [25]. Two studies measured ST using an accelerometer [28, 34]. No significant statistical heterogeneity was observed among the five studies (I2 = 36%). Meta-analysis results demonstrated that individuals with high ST exhibited a 33% increased risk for dementia compared to those with low ST (pooled HRs, 1.33; 95% CIs, 1.25–1.42) (Fig. 3c).

Publication bias

Publication bias refers to the tendency of statistically significant results to be preferentially reported and published over non-significant and/or invalid results. Asymmetrical funnel plots indicate the potential presence of publication bias (Fig. 4a-d).

Fig. 4
figure 4

a Funnel plot of the association between sedentary behavior (overall) and dementia (b) Funnel plot of the association between sedentary behavior (defined by TV viewing time) and dementia (c) Funnel plot of the association between sedentary behavior (defined by computer using time) and dementia (d) Funnel plot of the association between sedentary behavior (defined by other methods) and dementia

Full size image

Sensitivity analysis

We performed leave-one-out sensitivity analysis, and only minor changes were found in the results, validating that our findings were stable (Table 3).

Table 3 Results of leave-one-out sensitivity analysis (a) meta-analysis of the association between sedentary behavior (overall) and dementia; (b) Meta-analysis of the association between sedentary behavior (defined by TV viewing time) and dementia; (c) Meta-analysis of the association between sedentary behavior (defined by computer using time) and dementia; (d) Meta-analysis of the association between sedentary behavior (defined by other methods) and dementia
Full size table

Discussion

Clinical implications

Our research confirmed the association between sedentary lifestyle and an increased risk of dementia. The relationship was identified between various SB types and dementia risk, which varied based on the type. There was no significant correlation between computer usage time and dementia risk. However, other types of SBs were associated with an increased risk of dementia. Our findings align with those of previous studies that highlight the varied impacts of distinct activities on cognitive function [41, 42]. Engaging in cognitively challenging activities, such as computer usage, has been associated with cognition and posture, and reduces dementia risk [43, 44]. In contrast, passive activities, such as TV viewing have been associated with adverse effects on cognition and posture [45, 46].

In recent years, there have been some systematic reviews about the association between SB and dementia [19,20,21]. Falck RS et al.(2017) were the first to adopt a systematic assessment approach, finding that SB has a significant negative impact on cognitive function, consistent with the conclusions of our study, though their research lacked quantitative analysis and valid measurement tools [19]. The study by Maasakkers CM et al.(2022) included 29 studies did not find an association between SB and dementia. And this study also did not conduct a quantitative analysis [20]. And most of the studies included were cross-sectional, making it difficult to reveal causal relationships, which may account for the differing conclusions compared to this study. Yan S et al.(2020) conducted a meta-analysis of 18 studies, indicating that SB is significantly associated with an increased risk of dementia [21]. However, the studies included in the research lacked consistency in the definition of SB, and most studies defined SB as physical inactivity with different weekly exercise frequency. In addition, the studies included in this research were limited to those published up until March 2018. In recent years, many original studies have been conducted exploring the relationship between SB and dementia, which makes this research lack novelty. What's more, this study selected the RR as the effect size metric. Given the prolonged development of dementia, compared to RR, HRs could more comprehensively reflects the time dimension of the dementia, providing a more thorough risk assessment [47]. Fianlly, none of the three studies further investigated the impact of different types of SB on dementia. Our study clearly defined SB and made strict distinctions between the exposure and control groups, excluding potential biases that could arise from unclear definitions. All were cohort studies using HRs as the effect size metric, which can better reflect causal relationships. At the same time, subgroup analysis reveals the effects of different types of SB, improving the practical relevance of the findings.

Differences in the effects of various sedentary behaviors on dementia may be because of the following reasons. First, previous discussions that associated sitting to health have focused on the reduced muscle engagement while sitting, resulting in adverse physiological consequences [48, 49]. Prolonged uninterrupted sitting is associated with reduced cerebrovascular hemodynamics [50,51,52]. However, this study indicates that the harmful physiological effects of SB may be mitigated by engaging in active cognitive activities (computer usage) compared to passive cognitive activities (watching television). Second, various categories of SB may exhibit distinct behavioral patterns that are correlated with brain health. For example, energy intake during TV viewing may differ from that during other sedentary activities, potentially affecting cardiac metabolism and consequently affecting brain health [53, 54]. Moreover, TV viewing occurs in the evening, coinciding with postprandial sedentary periods that can negatively affect cardiac metabolism, consequently affecting brain health [55].

Clinical practices

Although the mechanisms underlying the variations in the effects of various sedentary behaviors on dementia onset remain unclear, our findings have significant implications. Reducing cognitively passive SB and increasing cognitively active SB may reduce the risk of dementia. Because of the feasibility of intervening in SB, the significance of clinical and public health practices is aimed at dementia prevention. Interventions targeting sedentary behaviors, including health education, may be effective for primary dementia prevention within clinical settings.

Heterogeneity of meta-analysis

In meta-analysis, the I2 statistic indicates the percentage of variation among included studies due to heterogeneity rather than chance [56]. In this study, we used the random-effect model to analyse the relationship between SB and dementia, because a high degree of heterogeneity was observed among all included studies (I2 = 88%). According to the results of subgroup analysis, this problem could be caused by the fact that the definition of SB was inconsistent among all included studies, which might induce bias in effect size estimates. And the high heterogeneity among studies using computer usage time to define SB might be caused by difference in different measures of computer usage time or differences in sample size (presence of studies with comparatively large or small sample sizes). Excessive heterogeneity may result in an inaccurate merging. However, the majority of subjects in this study were from the UK Biobank and shared similar characteristics; therefore, it was justifiable to conduct a merger analysis.

Limitations

This study has several limitations. First, the majority of literature data were from the UK Biobank, with the study population predominantly consisting of Europeans. Consequently, the conclusions are moderately limited, and it remains unclear whether the risk of dementia varies among populations exhibiting sedentary behaviors outside Europe. Second, the majority of studies relied on self-reported ST assessments, potentially resulting in recall bias and measurement errors. Third, the sedentary behaviors in this study primarily focused on TV viewing and computer usage. Therefore, other forms of sedentary behaviors require further assessment. Fourth, due to the limited number of studies, it is difficult to conduct a meta-regression analysis [57]. In conclusion, this study did not assess the dose–effect relationship between SB and the risk of developing dementia, nor did it assess the association between SB and dementia prognosis. Future studies should explore the relationship between SB and dementia.

Conclusion

Our study suggests a relationship between SB and dementia. To further examine this finding and establish a stronger result, more large-scale prospective studies are warranted to provide more information about the details of the association between SB and dementia. An increased rate of dementia occurs in sedentary patients and clinicians should be aware of this possibility.

Data availability

This review was based on previously published data. A detailed assessment of the risk of bias is available upon request.

Abbreviations

HRs:

Hazard ratios

CIs:

Confidence intervals

WHO:

World Health Organization

PA:

Physical activity

AD:

Alzheimer’s disease

ST:

Sedentary time

SB:

Sedentary behavior

RR:

Relative risk

References

  1. Cantone M. Molecular Mechanisms of Dementia. Int J Mol Sci. 2023;24(17):13027.

  2. Soria Lopez JA, González HM, Léger GC. Alzheimer’s disease. Handb Clin Neurol. 2019;167:231–55.

    Article  PubMed  Google Scholar 

  3. World Health Organization (WHO). https://www.who.int/news-room/fact-sheets/detail/dementia. Accessed 15 Mar 2024.

  4. Sefcik JS, Madrigal C, Heid AR, et al. Person-Centered Care Plans for Nursing Home Residents With Behavioral and Psychological Symptoms of Dementia. J Gerontol Nurs. 2020;46(11):17–27.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Alzheimer's Disease International. World Alzheimer report 2023: Reducing Dementia Risk: Never too early, never too late. Alzheimer’s Dis Int. 2023; https://www.alzint.org/resource/world-alzheimer-report-2023/. Accessed 15 Mar 2024. 

  6. Biswas A, Oh PI, Faulkner GE, et al. Sedentary time and its association with risk for disease incidence, mortality, and hospitalization in adults: a systematic review and meta-analysis. Ann Intern Med. 2015;162(2):123–32.

    Article  PubMed  Google Scholar 

  7. Tremblay MS, Aubert S, Barnes JD, et al. Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act. 2017;14(1):75.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Arocha Rodulfo JI. Sedentary lifestyle a disease from xxi century. Sedentarismo, la enfermedad del siglo xxi. Clin Investig Arterioscler. 2019;31(5):233–40.

    PubMed  Google Scholar 

  9. Law LL, Rol RN, Schultz SA, et al. Moderate intensity physical activity associates with CSF biomarkers in a cohort at risk for Alzheimer’s disease. Alzheimers Dement (Amst). 2018;10:188–95.

    Article  PubMed  Google Scholar 

  10. Spartano NL, Davis-Plourde KL, Himali JJ, et al. Self-Reported Physical Activity and Relations to Growth and Neurotrophic Factors in Diabetes Mellitus: The Framingham Offspring Study. J Diabetes Res. 2019;2019:2718465.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Iso-Markku P, Kujala UM, Knittle K, Polet J, Vuoksimaa E, Waller K. Physical activity as a protective factor for dementia and Alzheimer’s disease: systematic review, meta-analysis and quality assessment of cohort and case-control studies. Br J Sports Med. 2022;56(12):701–9.

    Article  PubMed  Google Scholar 

  12. Yu JT, Xu W, Tan CC, et al. Evidence-based prevention of Alzheimer’s disease: systematic review and meta-analysis of 243 observational prospective studies and 153 randomised controlled trials. J Neurol Neurosurg Psychiatry. 2020;91(11):1201–9.

    Article  PubMed  Google Scholar 

  13. Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission [published correction appears in Lancet. 2023;402(10408):1132.

  14. Carter S, Hartman Y, Holder S, Thijssen DH, Hopkins ND. Sedentary Behavior and Cardiovascular Disease Risk: Mediating Mechanisms. Exerc Sport Sci Rev. 2017;45(2):80–6.

    Article  PubMed  Google Scholar 

  15. Knaeps S, Bourgois JG, Charlier R, Mertens E, Lefevre J, Wijndaele K. Ten-year change in sedentary behaviour, moderate-to-vigorous physical activity, cardiorespiratory fitness and cardiometabolic risk: independent associations and mediation analysis. Br J Sports Med. 2018;52(16):1063–8.

    Article  PubMed  Google Scholar 

  16. Patterson R, McNamara E, Tainio M, et al. Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes: a systematic review and dose response meta-analysis. Eur J Epidemiol. 2018;33(9):811–29.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Rist PM, Marden JR, Capistrant BD, Wu Q, Glymour MM. Do physical activity, smoking, drinking, or depression modify transitions from cognitive impairment to functional disability? J Alzheimers Dis. 2015;44(4):1171–80.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Gelber RP, Petrovitch H, Masaki KH, et al. Lifestyle and the risk of dementia in Japanese-american men. J Am Geriatr Soc. 2012;60(1):118–23.

    Article  PubMed  Google Scholar 

  19. Falck RS, Davis JC, Liu-Ambrose T. What is the association between sedentary behaviour and cognitive function? A systematic review. Br J Sports Med. 2017;51(10):800–11.

    Article  PubMed  Google Scholar 

  20. Maasakkers CM, Weijs RWJ, Dekkers C, et al. Sedentary behaviour and brain health in middle-aged and older adults: A systematic review. Neurosci Biobehav Rev. 2022;140:104802.

  21. Yan S, Fu W, Wang C, et al. Association between sedentary behavior and the risk of dementia: a systematic review and meta-analysis. Transl Psychiatry. 2020;10(1):112.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Raichlen DA, Klimentidis YC, Sayre MK, et al. Leisure-time sedentary behaviors are differentially associated with all-cause dementia regardless of engagement in physical activity. Proc Natl Acad Sci USA. 2022;119(35):e2206931119.

  23. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Rev Esp Cardiol (Engl Ed). 2021;74(9):790–9.

    Article  PubMed  Google Scholar 

  24. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283(15):2008–12.

    Article  CAS  PubMed  Google Scholar 

  25. Sun Y, Chen C, Yu Y, et al. Replacement of leisure-time sedentary behavior with various physical activities and the risk of dementia incidence and mortality: A prospective cohort study. J Sport Health Sci. 2023;12(3):287–94.

    Article  PubMed  Google Scholar 

  26. Wu H, Gu Y, Du W, et al. Different types of screen time, physical activity, and incident dementia, Parkinson’s disease, depression and multimorbidity status. Int J Behav Nutr Phys Act. 2023;20(1):130.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zhuang Z, Zhao Y, Song Z, et al. Leisure-Time Television Viewing and Computer Use, Family History, and Incidence of Dementia. Neuroepidemiology. 2023;57(5):304–15.

    Article  PubMed  Google Scholar 

  28. Zhong Q, Zhou R, Huang YN, et al. The independent and joint association of accelerometer-measured physical activity and sedentary time with dementia: a cohort study in the UK Biobank. Int J Behav Nutr Phys Act. 2023;20(1):59. Published 2023 May 17.

  29. Xu C, Cao Z, Lu Z, Hou Y, Wang Y, Zhang X. Associations between Recreational Screen Time and Brain Health in Middle-Aged and Older Adults: A Large Prospective Cohort Study. J Am Med Dir Assoc. 2024;25(8):104990.

  30. Nemoto Y, Sato S, Kitabatake Y, Takeda N, Maruo K, Arao T. Do the Impacts of Mentally Active and Passive Sedentary Behavior on Dementia Incidence Differ by Physical Activity Level? A 5-year Longitudinal Study. J Epidemiol. 2023;33(8):410–8.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Du Z, Sato K, Tsuji T, Kondo K, Kondo N. Sedentary behavior and the combination of physical activity associated with dementia, functional disability, and mortality: A cohort study of 90,471 older adults in Japan. Prev Med. 2024;180:107879.

  32. Takeuchi H, Kawashima R. A Prospective Study on the Relationship Between Driving and Non-occupational Computer Use With Risk of Dementia. Front Aging Neurosci. 2022;14: 854177.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Yuan S, Li W, Ling Y, et al. Associations of screen-based sedentary activities with all cause dementia, Alzheimer’s disease, vascular dementia: a longitudinal study based on 462,524 participants from the UK Biobank. BMC Public Health. 2023;23(1):2141.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Raichlen DA, Aslan DH, Sayre MK, et al. Sedentary Behavior and Incident Dementia Among Older Adults. JAMA. 2023;330(10):934–40.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. Available from: https://www.ohri.ca/programs/clinical_epidemiology\oxford.htm. Accessed 10 Mar 2022.

  36. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res Synth Methods. 2010;1(2):97–111.

    Article  PubMed  Google Scholar 

  38. Hernandez AV, Marti KM, Roman YM. Meta-analysis. Chest. 2020;158(1S):S97–102.

    Article  PubMed  Google Scholar 

  39. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kumar A, Taggarsi M. GRADE quality of evidence and its importance in evidence-based practice. BMJ Evid Based Med. 2021;26(5):228–30.

    Article  PubMed  Google Scholar 

  41. Bakrania K, Edwardson CL, Khunti K, Bandelow S, Davies MJ, Yates T. Associations Between Sedentary Behaviors and Cognitive Function: Cross-Sectional and Prospective Findings From the UK Biobank. Am J Epidemiol. 2018;187(3):441–54.

    Article  PubMed  Google Scholar 

  42. Felez-Nobrega M, Hillman CH, Dowd KP, Cirera E, Puig-Ribera A. ActivPAL™ determined sedentary behaviour, physical activity and academic achievement in college students. J Sports Sci. 2018;36(20):2311–6.

    Article  PubMed  Google Scholar 

  43. Almeida OP, Yeap BB, Alfonso H, Hankey GJ, Flicker L, Norman PE. Older men who use computers have lower risk of dementia. PLoS ONE. 2012;7(8):e44239.

  44. Yates LA, Ziser S, Spector A, Orrell M. Cognitive leisure activities and future risk of cognitive impairment and dementia: systematic review and meta-analysis. Int Psychogeriatr. 2016;28(11):1791–806.

    Article  PubMed  Google Scholar 

  45. Hamer M, Stamatakis E. Prospective study of sedentary behavior, risk of depression, and cognitive impairment. Med Sci Sports Exerc. 2014;46(4):718–23.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Wang JY, Zhou DH, Li J, et al. Leisure activity and risk of cognitive impairment: the Chongqing aging study. Neurology. 2006;66(6):911–3.

    Article  CAS  PubMed  Google Scholar 

  47. Huang Q, Zhao MJ, Luo LS, et al. Discrimination and conversion between hazard ratio and risk ratio as effect measures in prospective studies. Chin J Evid Based Med. 2020;22(10):1221–5.

    Google Scholar 

  48. Hamilton MT. The role of skeletal muscle contractile duration throughout the whole day: reducing sedentary time and promoting universal physical activity in all people. J Physiol. 2018;596(8):1331–40.

    Article  CAS  PubMed  Google Scholar 

  49. Raichlen DA, Pontzer H, Zderic TW, et al. Sitting, squatting, and the evolutionary biology of human inactivity. Proc Natl Acad Sci U S A. 2020;117(13):7115–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Carter SE, Draijer R, Holder SM, Brown L, Thijssen DHJ, Hopkins ND. Regular walking breaks prevent the decline in cerebral blood flow associated with prolonged sitting. J Appl Physiol (1985). 2018;125(3):790–8.

    Article  CAS  PubMed  Google Scholar 

  51. Perdomo SJ, Gibbs BB, Kowalsky RJ, Taormina JM, Balzer JR. Effects of Alternating Standing and Sitting Compared to Prolonged Sitting on Cerebrovascular Hemodynamics. Sport Sci Health. 2019;15(2):375–83.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Wheeler MJ, Dunstan DW, Smith B, et al. Morning exercise mitigates the impact of prolonged sitting on cerebral blood flow in older adults. J Appl Physiol (1985). 2019;126(4):1049–55.

    Article  PubMed  Google Scholar 

  53. Kivimäki M, Singh-Manoux A, Pentti J, et al. Physical inactivity, cardiometabolic disease, and risk of dementia: an individual-participant meta-analysis. BMJ. 2019;365:l1495.

  54. Wagner M, Helmer C, Tzourio C, Berr C, Proust-Lima C, Samieri C. Evaluation of the Concurrent Trajectories of Cardiometabolic Risk Factors in the 14 Years Before Dementia. JAMA Psychiat. 2018;75(10):1033–42.

    Article  Google Scholar 

  55. Ekelund U, Steene-Johannessen J, Brown WJ, et al. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet. 2016;388(10051):1302–10.

    Article  PubMed  Google Scholar 

  56. Kuo CC, Wang CC, Chang WL, Liao TC, Chen PE, Tung TH. Clinical Effects of Baduanjin Qigong Exercise on Cancer Patients: A Systematic Review and Meta-Analysis on Randomized Controlled Trials. Evid Based Complement Alternat Med. 2021;2021:6651238.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Tipton E, Pustejovsky JE, Ahmadi H. Current practices in meta-regression in psychology, education, and medicine. Res Synth Methods. 2019;10(2):180–94.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Institute for Hospital Management, Tsinghua University, Shenzhen International Graduate School (SIGS), Shenzhen, Guangdong, 518055, China

    Jinyan Luo, Yiping Huang, Gangqiang Gao & Ching-Wen Chien

  2. Ecidence-Based Medicine Center, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, Zhejiang, 317000, China

    Tao-Hsin Tung

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  1. Jinyan Luo
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  2. Yiping Huang
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  3. Gangqiang Gao
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  4. Ching-Wen Chien
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Contributions

J-YL, T-HT, C-WC: designed research; J-YL: conducted research; J-YL, Y-PH, and T-HT: selected studies; Y-PH, G-QG, J-YL and T-HT: assessed the quality of the selected studies; J-YL: analyzed data; J-YL, Y-PH, and G-QG: wrote the paper; J-YL, Y-PH, G-QG, C-WC, and T-HT: revised the manuscript critically for important intellectual content; T-HT: had primary responsibility for the final content. All authors read and approved the final manuscript.

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Correspondence to Ching-Wen Chien or Tao-Hsin Tung.

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Luo, J., Huang, Y., Gao, G. et al. Association between sedentary behavior and dementia: a systematic review and meta-analysis of cohort studies. BMC Psychiatry 25, 451 (2025). https://doi.org/10.1186/s12888-025-06887-0

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Keywords

BMC Psychiatry

ISSN: 1471-244X

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