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BMC Public Health. 2019 Mar 6;19(1):271. doi: 10.1186/s12889-019-6513-y.

Distinct trajectories of physical activity and related factors during the life course in the general population: a systematic review.

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Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland.
Methodology Center for Human Sciences, University of Jyväskylä, Jyväskylä, Finland.



In recent years, researchers have begun applying a trajectory approach to identify homogeneous subgroups of physical activity (PA) in heterogeneous populations. This study systematically reviewed the articles identifying longitudinal PA trajectory classes and the related factors (e.g., determinants, predictors, and outcomes) in the general population during different life phases.


The included studies used finite mixture models for identifying trajectories of PA, exercise, or sport participation. Three electronic databases, PubMed (Medline), Web of Science, and CINAHL, were searched from the year 2000 to 13 February 2018. The study was conducted according to the PRISMA recommendations.


Twenty-seven articles were included and organized into three age group: youngest (eleven articles), middle (eight articles), and oldest (eight articles). The youngest group consisted mainly of youth, the middle group of adults and the oldest group of late middle-aged and older adults. Most commonly, three or four trajectory classes were reported. Several trajectories describing a decline in PA were reported, especially in the youngest group, whereas trajectories of consistently increasing PA were observed in the middle and oldest group. While the proportion of persistently physically inactive individuals increased with age, the proportion was relatively high at all ages. Generally, male gender, being Caucasian, non-smoking, having low television viewing time, higher socioeconomic status, no chronic illnesses, and family support for PA were associated either with persistent or increasing PA.


The reviewed articles identified various PA subgroups, indicating that finite mixture modeling can yield new information on the complexity of PA behavior compared to studying population mean PA level only. The studies also provided novel information how different factors relate to changes in PA during life course. The recognition of the PA subgroups and their determinants is important for the more precise targeting of PA promotion and PA interventions.


PROSPERO registration number: CRD42018088120 .


Exercise; Finite mixture model; Longitudinal; Physical activity; Prospective; Review; Sport participation; Trajectory

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