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      Distinct trajectories of leisure time physical activity and predictors of trajectory class membership: a 22 year cohort study

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          Abstract

          Background

          Prospective studies linking social factors to long term patterns of physical activity are lacking. In this 22 year longitudinal study, we seek to identify long term patterns of involvement in leisure time physical activity (LTPA), and explore socioeconomic and demographic predictors of distinct LTPA trajectories.

          Methods

          Among 2102 individuals aged 18–60 years in 1981 who participated in the 1981 Canada Fitness Survey/1988 Campbell's Survey of Well-Being, 1186 (56.4%) completed questionnaires for the 2002/04 follow-up. Complete data on LTPA at all 3 surveys were available for 884 participants. Latent class growth analysis was used to identify major classes of LTPA trajectories; predictors of class membership were identified using polytomous logistic regression.

          Results

          Four latent classes were identified: inactive, increasers, active, and decreasers (53%, 26%, 12%, and 9% of participants, respectively). Women, older participants, those with lower household income, and with lower educational attainment, were significantly less likely to follow active (Vs. inactive) trajectories of LTPA. Disadvantaged groups with respect to education and income were also significantly more likely to follow decreasing (Vs. active) trajectories.

          Conclusion

          There is a need for continued efforts to increase overall population levels of LTPA, particularly among socially disadvantaged groups with respect to income and education, who are most likely to experience unfavorable trajectories of LTPA.

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          Most cited references31

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          Physical activity from childhood to adulthood: a 21-year tracking study.

          The aim of this study was to investigate stability of physical activity from childhood and adolescence to adulthood in multiple age cohorts, and analyze how well adult physical activity can be predicted by various physical activity variables measured in childhood and adolescence. The data were drawn from the Cardiovascular Risk in Young Finns Study. The study was started in 1980, when cohorts of randomly sampled boys and girls aged 3, 6, 9, 12, 15, and 18 years (total of 2309 subjects) were examined for the first time. The measurements were repeated in 1983, 1986, 1989, 1992, and 2001. In 2001, the subjects (n =1563, 68%) were aged 24, 27, 30, 33, 36, and 39 years, respectively. Physical activity was measured by means of a short self-report questionnaire that was administered individually in connection with a medical examination. On the basis of a questionnaire, a physical activity index (PAI) was calculated. There were no significant differences in the 1980 PAI between participants and dropouts in 2001. Spearmans rank order correlation coefficients for the 21-year tracking period varied from 0.33 to 0.44 in males, and from 0.14 to 0.26 in females. At shorter time intervals the correlation was higher. On average, the tracking correlation was lower in females than in males. Persistent physical activity, defined as a score in the most active third of the PAI in two or three consecutive measurements, increased the odds that an individual would be active in adulthood. Odds ratios for 3-year continuous activity versus continuous inactivity varied from 4.30 to 7.10 in males and 2.90 to 5.60 in females. The corresponding odds ratios for 6-year persistence were 8.70 to 10.80 and 5.90 to 9.40. It was concluded that a high level of physical activity at ages 9 to 18, especially when continuous, significantly predicted a high level of adult physical activity. Although the correlations were low or moderate, we consider it important that school-age physical activity appears to influence adult physical activity, and through it, the public health of the general population.
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            A questionnaire for the assessment of leisure time physical activities.

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              Tracking of physical activity and physical fitness across the lifespan.

              Although different indicators of physical activity and different methods of analysis are used, it appears that physical activity tracks at low to moderate levels during adolescence, from adolescence into adulthood, and across various ages in adulthood. Tracking of inactivity is less often studied. Measures of performance- and health-related physical fitness (strength, flexibility, motor fitness, aerobic power) track significantly across childhood and adolescence, but correlations are low to moderate. Limited data that span adolescence into adulthood indicate somewhat higher interage correlations for flexibility, static strength, and power. Data for different periods in adulthood are not available. Presently, it is common to criticize focus on motor and sport skills in physical education and competitive sports as contrary to health and fitness goals (e.g., James, 1995; Livingstone, 1994; Simons-Morton et al., 1988). There is a need, however, to distinguish between youth or community sports and highly specialized sport for the elite. Sports activities, be they competitive or recreational, are probably the major form of physical activity during childhood and adolescence, and perhaps in young adulthood. Though low to moderate, the tracking of various activity indicators, most of which include sport participation, suggests that sport activities during childhood and youth may form the foundation for activity habits in the future.
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                Author and article information

                Journal
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central
                1479-5868
                2008
                7 November 2008
                : 5
                : 57
                Affiliations
                [1 ]Centre de recherche du Centre Hospitalier Universitaire Sainte-Justine, 3175, Côte-Sainte-Catherine Montréal (Québec), H3T 1C5, Canada
                [2 ]Département de médecine sociale et préventive, Université de Montréal, Canada
                [3 ]CRCHUM-Centre de recherche du Centre Hospitalier de l'Université de Montréal, Centre de Recherche Léa-Roback sur les Inégalités Sociales de Santé de Montréal, Canada
                [4 ]Canadian Fitness and Lifestyle Research Institute, School of Public Health, University of Sydney, Australia
                [5 ]Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA
                Article
                1479-5868-5-57
                10.1186/1479-5868-5-57
                2613394
                18990250
                7932648e-8ec8-4617-9bde-926fedce0ec4
                Copyright © 2008 Barnett et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 7 January 2008
                : 7 November 2008
                Categories
                Research

                Nutrition & Dietetics
                Nutrition & Dietetics

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