Tracking of voluntary exercise behaviour over the lifespan

Matthijs D. Van Der Zee*, Denise Van Der Mee, Meike Bartels, Eco J.C. De Geus

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

BACKGROUND: The aim of many physical activity interventions is to develop life-long habits of regular exercise and sports activities in leisure time. Previous studies that assessed tracking (i.e. the stability of a trait over the lifespan) of leisure time exercise behaviour across various parts of the life span have treated it as a uniform construct by summing all types of leisure time exercise activities into a single summary score for the total volume of exercise. This study provides new insight by additionally determining tracking across leisure time exercise activities in six different domains: (1) team-based versus solitary activities, (2) competitive versus non-competitive activities, and (3) externally paced versus internally paced activities. We also assessed which of the domains of exercise activities best predicted total volume of exercise at follow-up.

METHODS: A large dataset (N = 43,889) from the Netherlands Twin Register (NTR) was used to analyse the tracking of exercise behaviour over time. Using this dataset, we were able to examine tracking as a function of baseline age (8 to 80 years) and tracking duration (2 to 22-year follow-up), taking into account sex differences, using generalized estimating equations.

RESULTS: Two-year tracking coefficients are moderate to high for total volume of exercise across ages at baseline, ranging from .38 to .77 with a median of .57. Tracking coefficients tend to decrease as the distance to follow-up increases, down to a median of .38 for the 22-year tracking coefficients. The patterns of tracking were largely domain-independent and were largely similar for solitary, competitive, non-competitive, externally and internally paced activities. With the exception of team-based activities, tracking was seen to increase as a function of baseline age. Cross-domain tracking did not favour any specific domain of exercise activity as the best predictor for total volume of exercise behaviour and this was true at all baseline ages.

CONCLUSION: We conclude that exercise behaviour is moderately to highly stable across the life span. In particular in adulthood, where the tracking of exercise mimics that of a classical behavioural trait like personality. This stability reinforces existing evidence that exercise habits are hard to change, but at the same time suggests that successful intervention leading to the adoption of exercise habits will tend to last.

Original languageEnglish
Article number17
Pages (from-to)1-11
Number of pages11
JournalInternational Journal of Behavioral Nutrition and Physical Activity
Volume16
DOIs
Publication statusPublished - 4 Feb 2019

Funding

Netherland Twin Register: Funding was obtained from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organisation for Health Research and Development (ZonMW) grants 904–61-090, 985–10-002, 912–10-020, 904–61-193,480–04-004, 463–06-001, 451–04-034, 400–05-717, Addiction-31160008, 016–115-035, 481–08-011, 056–32-010, NWO-Middelgroot-911-09-032, OCW_NWO Gravity program − 024.001.003, NWO-Groot 480–15-001/674, Centre for Medical Systems Biology (CSMB, NWO Genomics), Biobank-ing and Biomolecular Resources Research Infrastructure (BBMRI –NL, 184.021.007 and 184.033.111); Spinozapremie (NWO-56-464-14192), KNAW Academy Professor Award (PAH/6635) to DIB; Amsterdam Public Health research institute (former EMGO+), Neuroscience Amsterdam research institute (former NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community’s Seventh Framework Program (FP7-HEALTH-F4– 2007-2013, grant 01413: ENGAGE and grant 602768: ACTION); the European Research Council (ERC AG 230374, ERC SG 284167 and ERC CG 771057); the National Institutes of Health (NIH R01 DK092127–04); a donation by Mr. JG Landers; and the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA).

FundersFunder number
Amsterdam Public Health Research Institute
Avera Institute for Human Genetics
BBMRI184.033.111, 184.021.007, NWO-56-464-14192
Biomolecular Resources Research Infrastructure
Centre for Medical Systems Biology
ENGAGE602768
European Community’s Seventh Framework Program
FP7-HEALTH-F401413
NWO-Groot480–15-001/674
Netherlands Organization for Scientific Research
Neuroscience Amsterdam research institute
National Institutes of Health
National Institute of Diabetes and Digestive and Kidney DiseasesR01DK092127
European Research CouncilCG 771057, AG 230374, SG 284167
European Science FoundationEU/QLRT-2001-01254
Koninklijke Nederlandse Akademie van WetenschappenPAH/6635
ZonMw451–04-034, 904–61-090, 463–06-001, 985–10-002, 056–32-010, 912–10-020, 400–05-717, 016–115-035, 904–61-193,480–04-004, NWO-Middelgroot-911-09-032, 481–08-011

    Keywords

    • Behavioural trends
    • Competitive exercise
    • Leisure time physical activity
    • Lifespan
    • Longitudinal stability
    • Team exercise

    Fingerprint

    Dive into the research topics of 'Tracking of voluntary exercise behaviour over the lifespan'. Together they form a unique fingerprint.

    Cite this