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Day-to-day intrapersonal variability in mobility patterns and association with perceived stress

A cross-sectional study using GPS from 122 individuals in three European cities

Bibliographic Data

ID15742802
AuthorsJonathan R Olsen (0000-0002-5356-8615, MRC/CSO Social and Public Health Sciences Unit, corresponding author), Natalie Nicholls (0000-0003-0745-7065, MRC/CSO Social and Public Health Sciences Unit), Fiona Caryl (0000-0001-6329-6767, MRC/CSO Social and Public Health Sciences Unit), Juan Orjuela Mendoza (University of Oxford), Luc Int Panis (0000-0002-2558-4351, Flemish Institute for Technological Research), Evi Dons (0000-0002-6745-7246, Flemish Institute for Technological Research), Michelle Laeremans (0000-0002-1406-7893, Flemish Institute for Technological Research), Arnout Standaert (0000-0001-7711-7141, Flemish Institute for Technological Research), Duncan Lee (0000-0002-6175-6800, University of Glasgow), Ione Avila-Palencia (0000-0002-4353-2256, Queen's University Belfast), Audrey de Nazelle (0000-0002-1092-3971, Imperial College London), Mark Nieuwenhuijsen (0000-0001-9461-7981, Universitat Pompeu Fabra), R Mitchell (0000-0003-3827-7155, MRC/CSO Social and Public Health Sciences Unit)
Year2022
Volume19
Pages101172-101172
Publication date2022-07-16
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSSM - Population Health (JOURNAL)
Journal identifiersISSN: 2352-8273 • E-ISSN: 2352-8273
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.ssmph.2022.101172
PMID35865800
OpenAlexW4285585564
LanguageEN
Citations received2
References cited56

Many aspects of our life are related to our mobility patterns and individuals can exhibit strong tendencies towards routine in their daily lives. Intrapersonal day-to-day variability in mobility patterns has been associated with mental health outcomes. The study aims were: (a) calculate intrapersonal day-to-day variability in mobility metrics for three cities; (b) explore interpersonal variability in mobility metrics by sex, season and city, and (c) describe intrapersonal variability in mobility and their association with perceived stress. Data came from the Physical Activity through Sustainable Transport Approaches (PASTA) project, 122 eligible adults wore location measurement devices over 7-consecutive days, on three occasions during 2015 (Antwerp: 41, Barcelona: 41, London: 40). Participants completed the Short Form Perceived Stress Scale (PSS-4). Day-to-day variability in mobility was explored via six mobility metrics using distance of GPS point from home (meters:m), distance travelled between consecutive GPS points (m) and energy expenditure (metabolic equivalents:METs) of each GPS point collected (n = 3,372,919). A Kruskal-Wallis H test determined whether the median daily mobility metrics differed by city, sex and season. Variance in correlation quantified day-to-day intrapersonal variability in mobility. Levene's tests or Kruskal-Wallis tests were applied to assess intrapersonal variability in mobility and perceived stress. There were differences in daily distance travelled, maximum distance from home and METS between individuals by sex, season and, for proportion of time at home also, by city. Intrapersonal variability across all mobility metrics were highly correlated; individuals had daily routines and largely stuck to them. We did not observe any association between stress and mobility. Individuals are habitual in their daily mobility patterns. This is useful for estimating environmental exposures and in fuelling simulation studies

Association (psychology · Cross-sectional study · Geography · Global Positioning System · Interpersonal communication · Intrapersonal communication · Telecommunications · Air Quality and Health Impacts · Computer Science · Demography · Human Mobility and Location-Based Analysis · Medicine · Psychology · Social Psychology · Urban Transport and Accessibility

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    Open Access•Miguel A Vallejo, Laura Vallejo-Slocker et al.•Frontiers in Psychology•2018

  • Use of Ranks in One-Criterion Variance Analysis

    William Kruskal, William H Kruskal et al.•Journal of the American…•1952

  • Metabolic equivalents (Mets) in exercise testing, exercise prescription, and evaluation of functional capacity

    Open Access•M Jetté, K Sidney et al.•Clinical Cardiology•1990

  • Understanding individual mobility patterns from urban sensing data

    Open Access•Francesco Calabrese, Mi Diao et al.•Transportation Research Part C:…•2013

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    Henk Aarts, Theo Paulussen et al.•Health Education Research•1997

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  • An examination of the determinants of day-to-day variability in individuals' urban travel behavior

    Open Access•Eric I Pas, Frank S Koppelman•Transportation•1986

  • Physical Activity through Sustainable Transport Approaches (Pasta)

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Unique citing works2
Citations per year1
Citation span2024 - 2026 (3)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 2

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