Constructing a graphical model of the relationship between physical activity and cognitive function based on a systematic review of prospective evidence
Creators: name: Campbell, Thomas
name: Whyte, Jessica
name: Dr Karl D. Ferguson, Public
name: Cullen, Breda
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Medicine and Health Sciences
subject: Life Sciences
subject: Social and Behavioral Sciences
subject: cognitive decline
subject: cognitive function
subject: DAG
subject: directed acyclic graph
subject: Physical activity

description: Constructing a graphical model of the relationship between physical activity and cognitive function based on a systematic review of prospective evidence Citation: Thomas Campbell, Jessica Whyte, Karl Ferguson, Breda Cullen Background: Elucidating modifiable factors that may confer protection against cognitive decline is an important area of investigation. Physical activity (PA) represents one such factor and has generated substantial evidence regarding its protective benefit. However, in epidemiological research the presence of multiple covariates has posed challenges to obtaining unconfounded estimates of associations between exposure and outcome variables. Causal diagrams, or Directed Acyclic Graphs (DAGs), have emerged as promising tools for addressing these challenges and improving the planning and specification of statistical analyses. This review aims to utilise a recently developed research method for constructing DAGs in a robust and systematic way: Evidence Synthesis for Constructing Directed Acyclic Graphs (ESC-DAGs) (Ferguson, 2019). The method will be applied to observational studies of the relationship between PA and cognitive decline, and the resulting DAG will be used to inform empirical analysis of UK Biobank data (a very large cohort study), in a separate paper. Review Question(s): (a) What clinical and sociodemographic factors, and health behaviours, do the included studies report as being associated with cognitive function/impairment and/or physical activity? (b) How do the studies vary with regard to the covariates included, how these are adjusted for, and the conclusions of the study? Reporting framework: This systematic review will be conducted and reported according to Conducting Systematic Reviews and Meta-analyses of Observational Studies of Etiology (COSMOS-E) (Dekkers et al., 2019). Searches A systematic search of literature will be conducted using the following electronic databases: • Medline on the Ovid platform • Embase on the Ovid platform • PsycINFO on the EBSCOhost (EBSCO) platform In the event that the searches performed on these databases are not sufficiently sensitive (as would be indicated by known relevant papers not being captured), the CINAHL database on EBSCOhost and Web of Science platform may be incorporated to the search strategy. The search terms will incorporate medical subject headings (MeSH terms) which will be adapted for compatibility within each database. The terms used will be based on the following key terms: - Physical activity OR Exercise OR Physical fitness OR Activity level AND - Cognitive Function OR Cognitive Dysfunction OR Cognitive Decline OR Cognitive Aging OR Cognitive Impairment OR Neuropsychological Tests OR Alzheimer’s Disease OR Dementia AND - Longitudinal studies OR Prospective OR Cohort Where applicable the search terms will be modified to include truncation and wildcard characters. Searches will be restricted to English Language publications from 01.01.2005 to 01.07.2020. Additional hand-searching of the reference lists of recent relevant review papers will also be applied. The sensitivity of the search strategy will be tested by checking whether a sample of papers known to be relevant are detected by the search. Types of study to be included Inclusion criteria Longitudinal cohort studies (prospective design). Exclusion criteria Cross-sectional studies, case-control studies, retrospective studies, intervention studies &amp; review papers. Condition or domain being studied Cognitive function as demonstrated by performance on objective cognitive tests. Where the outcome is measured categorically as impaired versus unimpaired, the threshold for impairment will be as defined by study authors but will at a minimum require performance to be one standard deviation below the mean of a healthy comparison group. Population Community dwelling adults, free of cognitive impairment before the period of exposure to physical activity began and aged ≥45 - &lt;80 at baseline. The upper limit of &lt;80 serves to reduce the likelihood of undetected pre-clinical cognitive decline at baseline, which would be expected to higher in older samples (Karr et.al., 2018; Prince et.al., 2014). The lower limit serves to ensure that included samples are at least ‘middle aged’ at baseline, which reflects the Biobank sample (Sudlow et.al., 2015) which will later be used for empirical analysis informed by the findings of this review. Therefore, studies whose entire sample is &lt;45 or ≥80, at baseline, will be excluded. In cases where the sample’s range includes ages both within and out with the ≥45 and &lt;80 range, the study will only be included if the mean age of the sample at baseline is between ≥45 and &lt;80. Exposure Level of physical activity, which may be measured using self-report questionnaires (e.g. the International Physical Activity Questionnaire; Craig et.al., 2003), or objective measures such as actigraphy. Where the exposure is measured categorically as active versus inactive the threshold for inactivity will be as defined by study authors (e.g. not meeting WHO guidance for weekly PA). Comparator Given that the exposure (risk factor) is low physical activity, the unexposed group will be those who engaged in greater levels, as defined by the study authors. Outcome The covariates included in each study (clinical and sociodemographic factors, and health behaviours), and how these were treated in analysis (e.g. as confounders, mediators or moderators). Screening Study titles and/or abstracts will be screened for relevance using a detailed checklist of eligibility criteria. This will be piloted by two researchers (TC and JW) independently using a sample of initial search results, and refined as required. The first author (TC) will screen the full sample of search results and a second researcher (JW) will screen a subset (minimum 100) of the total results at title and abstract stage. Discrepancies will be resolved by consensus. Full text will be obtained for all potentially relevant papers that remain. These will be assessed by the first author using the eligibility checklist, with the second researcher independently assessing a sample of papers for comparison (minimum of 10). Discrepancies will be resolved by consensus, involving a third researcher as required. Reasons for exclusion will be documented. Data extraction (selection and coding) A pro-forma Excel spreadsheet will be used for extracting data from the included papers. This will include: - Citation details: authors, year, title, journal, page - Setting - Comparison group: non/internal/external; matched or not - Method of recruitment - Eligibility criteria applied - Power/sample size calculation: yes/no - Sample size (of exposed and unexposed groups) - Sample demographics for exposed and unexposed groups: age; sex; ethnicity; country; language; education level; socio-economic status - Physical activity definition and measures - Cognitive impairment definition - Cognitive assessments used - Cut-offs applied for ‘impairment’ - Prevalence of impairment/decline in exposed and unexposed groups - Effect sizes/ increased odds/risk in exposed vs unexposed groups - Associated factors: details of variables correlated with physical activity and/or cognitive decline and how these were treated in models - Proportion of missing data and how this was dealt with in the analysis Data extraction will be carried out by the first author. A second researcher will compare a random sample (minimum of 10) of the data extraction forms against the source papers to check for accuracy and completeness. Any ambiguities in completing the forms will be discussed with other members of the research team until consensus is reached. Risk of bias (quality) assessment COSMOS-E guidance (Dekkers et. al., 2019) recommends that the following forms of bias should be assessed when evaluating observational studies: 1. Confounding bias, which results from an association between exposure and outcome being distorted by another variable which is also associated with both. 2. Selection bias, which results from the study population systematically differing from the general population of interest. 3. Information bias, which results from systematic differences in the way data on exposure or outcome are obtained between studies. In order to ensure these forms of bias are appropriately assessed, each included study will be evaluated by the first author for methodological quality and bias using a critical appraisal tool for prospective studies – The Joanna Briggs Institute (JBI) Checklist for Cohort Studies. In addition to this tool, item A2 from the Critical Appraisal Skills Programme (CASP) Cohort Study Checklist will be included, to ensure that selection bias is directly assessed. A second researcher will independently rate a random sample (minimum of 5) of the papers for comparison. Rating discrepancies will be resolved by consensus, involving a third researcher as necessary. Strategy for data synthesis This review does not aim to quantify the relationship between PA and cognitive decline. Rather, the aim of data synthesis here is to elucidate and represent the causal structure of the relationship between these variables and their covariates. This will be achieved by employing the recently developed method Evidence Synthesis for Constructing Directed Acyclic Graphs (ESC-DAG) (Ferguson, 2019). The process involves first producing a DAG for each included study before integrating all of these DAGs into a final model (or group of models). The final model(s) will be used to inform empirical analysis of UK Biobank data (a very large cohort study).Where one dataset has been reported on in two or more eligible articles, only the article which employs better modelling practices (e.g. not adjusting for variables that should be treated as mediators) will be considered in the data synthesis. In the present review the synthesis process will produce a conceptual DAG which aims to comprehensively reflect the covariates present in the eligible studies. During this process it is likely that synthesis of further DAGs will eventually yield no additional variables (i.e. saturation point). Depending on the final number of eligible studies it may be possible to identify and index all of those which contribute unique covariates, and those which only duplicate covariates contributed by other eligible studies. In this case studies will be synthesised in order of greatest to least number of covariates until no further unique contributions remain. In the case that there are vastly more eligible studies than anticipated (e.g. several hundred), they will be synthesised until saturation is judged to have occurred, although it will be acknowledged that this assumption is untestable. As a precedent, in developing the ESC-DAGs method, Ferguson (2020) judged saturation to have occurred in their case at n=49 studies. At the point saturation is judged to occur, this stage of synthesis will be concluded on the assumption that the majority of the most relevant variables used in the pertaining literature have been included. Expert opinion will be sought to further refine the resulting DAGs, i.e. to integrate any variables experts believe to be important but were not captured by the search and synthesis processes. Analysis of subgroups or subsets The synthesis may be subdivided according to key factors such as mental health status, socioeconomic status or different measures of exposure (e.g. objective vs self-report) and outcome (e.g. different cognitive domains). Sub-analyses may also be performed according to different modelling practices, e.g. between studies that treated key variables as confounders versus mediators. Dissemination plans The results will be submitted for publication in peer-reviewed journals and will be included in the first author’s Doctorate in Clinical Psychology thesis. Contact details for further information Thomas Campbell: 0902142c@student.gla.ac.uk Organisational affiliation of the review University of Glasgow http://www.gla.ac.uk/researchinstitutes/healthwellbeing/ Review team members and their organisational affilitations Thomas Campbell, University of Glasgow, NHS Lanarkshire Jessica Whyte, University of Glasgow, NHS Ayrshire &amp; Arran Dr Karl D. Ferguson, Public Health Scotland Dr Breda Cullen, University of Glasgow Stage of review at time of this submission Started Completed Preliminary searches Yes No Piloting of the study selection process Yes No Formal screening of search results against eligibility criteria Yes No Data extraction No No Risk of bias (quality) assessment No No Data analysis No No Example search strategy Database(s): Ovid MEDLINE(R) and In-Process &amp; Other Non-Indexed Citations 1946 to July 17, 2020 Search Strategy: # Searches 1 physical activity/ or fitness/ or exercise/ 2 accelerometer/ or accelerometry/ or actimetry/ 3 (exercis* or physical activit* or fitness* or acceleromet* or actigraph*).tw. 4 1 or 2 or 3 5 attention/ or executive function/ or memory/ or mental capacity/ or mental performance/ or intelligence/ or intelligence test/ or neuropsychological test/ or cognitive function test/ or alzheimer disease/ or dementia/ or cognitive defect/ 6 (cognition or cognitive d#sfunction or intelligence or intelligence tests or neuro?psychological tests or memory or dementia* or alzheimer* disease or IQ or memory or processing speed or visuospatial or executive function or cognitive decline or cognitive ability or cognitive impairment).tw. 7 5 or 6 8 cohort analysis/ or prospective study/ or longitudinal study/ 9 (cohort or follow?up or longitudinal or prospective).tw. 10 8 or 9 11 4 and 7 and 10 12 limit 11 to (english language and yr="2005 - 2021") References - Critical Appraisal Skills Programme (2018). CASP Cohort Study Checklist. [online] Available at: https://casp-uk.net/wp-content/uploads/2018/03/CASP-Cohort-Study-Checklist-2018_fillable_form.pdf. Accessed 11.07.2020 - - Craig, C. L., Marshall, A. L., Sjöström, M., Bauman, A. E., Booth, M. L., Ainsworth, B. E., ... &amp; Oja, P. (2003). International physical activity questionnaire: 12-country reliability and validity. Medicine &amp; science in sports &amp; exercise, 35(8), 1381-1395 - Dekkers, O. M., Vandenbroucke, J. P., Cevallos, M., Renehan, A. G., Altman, D. G., &amp; Egger, M. (2019). COSMOS-E: guidance on conducting systematic reviews and meta-analyses of observational studies of etiology. PLoS Medicine, 16(2), e100274 - Ferguson, K. D., McCann, M., Katikireddi, S. V., Thomson, H., Green, M. J., Smith, D. J., &amp; Lewsey, J. D. (2019). Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs. International Journal of Epidemiology. - Ferguson, K. D. (2020). Methodological Developments in Constructing Causal Diagrams with Counterfactual Analysis of Adolescent Alcohol Harm (Doctoral dissertation, University of Glasgow). - Karr, J. E., Graham, R. B., Hofer, S. M., &amp; Muniz-Terrera, G. (2018). When does cognitive decline begin? A systematic review of change point studies on accelerated decline in cognitive and neurological outcomes preceding mild cognitive impairment, dementia, and death. Psychology and Aging, 33(2), 195 - Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, Sfetcu R, Currie M, Qureshi R, Mattis P, Lisy K, Mu P-F. Chapter 7: Systematic reviews of etiology and risk. In: Aromataris E, Munn Z (Editors). Joanna Briggs Institute Reviewer's Manual. The Joanna Briggs Institute, 2017. Available from https://reviewersmanual.joannabriggs.org/. Accessed 12.07.2020 - Prince, M. J. (2014). World Alzheimer Report 2014: dementia and risk reduction: an analysis of protective and modifiable factors. Alzheimer's Disease International. https://www.alz.co.uk/research/WorldAlzheimerReport2014.pdf Accessed on 20.07.2020 - Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., . . . Landray, M. (2015). UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Medicine, 12(3), e1001779.