Journal
INTERNATIONAL JOURNAL OF BEHAVIORAL NUTRITION AND PHYSICAL ACTIVITY
Volume 16, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12966-019-0779-4
Keywords
Longitudinal stability; Behavioural trends; Leisure time physical activity; Lifespan; Competitive exercise; Team exercise
Categories
Funding
- Netherlands Organization for Scientific Research (NWO)
- Netherlands Organisation for Health Research and Development (ZonMW) [904-61-090, 985-10-002, 912-10-020, 904-61-193,480-04-004, 463-06-001, 451-04-034, 400-05-717, 31160008, 016-115-035, 481-08-011, 056-32-010]
- NWO [911-09-032, 480-15-001/674]
- OCW_NWO Gravity program [024.001.003]
- Centre for Medical Systems Biology (CSMB, NWO Genomics)
- Biobanking and Biomolecular Resources Research Infrastructure (BBMRI -NL) [184.021.007, 184.033.111]
- Spinozapremie [NWO-56-464-14192]
- KNAW Academy Professor Award [PAH/6635]
- Amsterdam Public Health research institute
- Neuroscience Amsterdam research institute
- European Science Foundation (ESF) [EU/QLRT-2001-01254]
- European Community's Seventh Framework Program (FP7-HEALTH-F4-2007-2013) [01413: ENGAGE, 602768: ACTION]
- European Research Council [ERC AG 230374, ERC SG 284167, ERC CG 771057]
- National Institutes of Health [NIH R01 DK092127-04]
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BackgroundThe 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.MethodsA 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 80years) and tracking duration (2 to 22-year follow-up), taking into account sex differences, using generalized estimating equations.ResultsTwo-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.ConclusionWe 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.
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