Physical activity from adolescence to young adulthood : patterns of change, and their associations with activity domains and sedentary time

BackgroundLongitudinal studies demonstrate an average decline in physical activity (PA) from adolescence to young adulthood. However, while some subgroups of adolescents decrease activity, others increase or maintain high or low activity. Activity domains may differ between subgroups (exhibiting different PA patterns), and they offer valuable information for targeted health promotion. Hence, the aim of this study was to identify PA patterns from adolescence to young adulthood; also to explore the associations of (i) changes in PA domains and in sedentary time, (ii) sociodemographic factors, and (iii) self-rated health with diverging PA patterns.MethodsThe observational cohort study data encompassed 254 adolescents at age 15 and age 19. K-means cluster analysis for longitudinal data was performed to identify participant clusters (patterns) based on their accelerometry-measured moderate-to-vigorous PA (MVPA). Logistic regressions were applied in further analysis.ResultsFive PA patterns were identified: inactivity maintainers (n=71), activity maintainers (n=70), decreasers from moderate (to low) PA (n=61), decreasers from high (to moderate) PA (n=32), and increasers (n=20).At age 15, participation in sports clubs (SC, 41-97%) and active commuting (AC, 47-75%) was common in all the patterns. By age 19, clear dropout from these activities was prevalent (SC participation mean 32%, AC 31-63%). Inactivity maintainers reported the lowest amount of weekly school physical education.Dropout from SC - in contrast to non-participation in SC - was associated with higher odds of being a decreaser from high PA, and with lower odds of being an inactivity maintainer. Maintained SC participation was associated with higher odds of belonging to the decreasers from high PA, and to the combined group of activity maintainers and increasers; also with lower odds of being an inactivity maintainer. Maintenance/adoption of AC was associated with decreased odds of being an inactivity maintainer. Self-reported health at age 19 was associated with the patterns of maintained activity and inactivity.ConclusionsPA patterns diverge over the transition to adulthood. Changes in SC participation and AC show different associations with diverging PA patterns. Hence, tailored PA promotion is recommended.Peer reviewe

Physical activity from adolescence to young adulthood: patterns of change, and their associations with activity domains and sedentary time

BackgroundLongitudinal studies demonstrate an average decline in physical activity (PA) from adolescence to young adulthood. However, while some subgroups of adolescents decrease activity, others increase or maintain high or low activity. Activity domains may differ between subgroups (exhibiting different PA patterns), and they offer valuable information for targeted health promotion. Hence, the aim of this study was to identify PA patterns from adolescence to young adulthood; also to explore the associations of (i) changes in PA domains and in sedentary time, (ii) sociodemographic factors, and (iii) self-rated health with diverging PA patterns.MethodsThe observational cohort study data encompassed 254 adolescents at age 15 and age 19. K-means cluster analysis for longitudinal data was performed to identify participant clusters (patterns) based on their accelerometry-measured moderate-to-vigorous PA (MVPA). Logistic regressions were applied in further analysis.ResultsFive PA patterns were identified: inactivity maintainers (n = 71), activity maintainers (n = 70), decreasers from moderate (to low) PA (n = 61), decreasers from high (to moderate) PA (n = 32), and increasers (n = 20).At age 15, participation in sports clubs (SC, 41–97%) and active commuting (AC, 47–75%) was common in all the patterns. By age 19, clear dropout from these activities was prevalent (SC participation mean 32%, AC 31–63%). Inactivity maintainers reported the lowest amount of weekly school physical education.Dropout from SC – in contrast to non-participation in SC – was associated with higher odds of being a decreaser from high PA, and with lower odds of being an inactivity maintainer. Maintained SC participation was associated with higher odds of belonging to the decreasers from high PA, and to the combined group of activity maintainers and increasers; also with lower odds of being an inactivity maintainer. Maintenance/adoption of AC was associated with decreased odds of being an inactivity maintainer. Self-reported health at age 19 was associated with the patterns of maintained activity and inactivity.ConclusionsPA patterns diverge over the transition to adulthood. Changes in SC participation and AC show different associations with diverging PA patterns. Hence, tailored PA promotion is recommended.</p

Exploring parental secretive eating of sugary foods and drinks, and its associations with food consumption in families

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Longitudinal physical activity patterns and the development of cardiometabolic risk factors during adolescence

Purpose: To examine the associations between longitudinal physical activity (PA) patterns and the development of cardiometabolic risk factors from adolescence to young adulthood.Methods: This cohort study encompassed 250 participants recruited from sports clubs and schools, and examined at mean age 15 and 19. Device-measured moderate-to-vigorous PA was grouped into five patterns (via a data-driven method, using inactivity maintainers as a reference). The outcomes were: glucose, insulin, homeostasis model assessment for insulin resistance (HOMA-IR), total cholesterol, HDL and LDL cholesterol, triglycerides, blood pressure, and body mass index (BMI). Linear growth curve models were applied with adjustment for sex, age, fruit/vegetable consumption, cigarette/snuff use, and change in the device wear-time.Results: Insulin and BMI increased among decreasers from moderate to low PA (beta for insulin 0.23, 95% CI 0.03-0.46; beta for BMI 0.90; CI 0.02-1.78). The concentration of HDL cholesterol decreased (beta -0.18, CI -0.31 to -0.05) and that of glucose increased (beta 0.18, CI 0.02-0.35) among decreasers from high to moderate PA. By contrast, among increasers, blood pressure declined (systolic beta -6.43, CI -12.16 to -0.70; diastolic beta -6.72, CI -11.03 to -2.41).Conclusions; Already during the transition to young adulthood, changes in PA are associated with changes in cardiometabolic risk factors. Favorable blood pressure changes were found among PA increasers. Unfavorable changes in BMI, insulin, glucose, and HDL cholesterol were found in groups with decreasing PA. The changes were dependent on the baseline PA and the magnitude of the PA decline.Peer reviewe

Longitudinal physical activity patterns and the development of cardiometabolic risk factors during adolescence

Abstract Purpose: To examine the associations between longitudinal physical activity (PA) patterns and the development of cardiometabolic risk factors from adolescence to young adulthood. Methods: This cohort study encompassed 250 participants recruited from sports clubs and schools, and examined at mean age 15 and 19. Device-measured moderate-to-vigorous PA was grouped into five patterns (via a data-driven method, using inactivity maintainers as a reference). The outcomes were: glucose, insulin, homeostasis model assessment for insulin resistance (HOMA-IR), total cholesterol, HDL and LDL cholesterol, triglycerides, blood pressure, and body mass index (BMI). Linear growth curve models were applied with adjustment for sex, age, fruit/vegetable consumption, cigarette/snuff use, and change in the device wear-time. Results: Insulin and BMI increased among decreasers from moderate to low PA (β for insulin 0.23, 95% CI 0.03–0.46; β for BMI 0.90; CI 0.02–1.78). The concentration of HDL cholesterol decreased (β −0.18, CI −0.31 to −0.05) and that of glucose increased (β 0.18, CI 0.02–0.35) among decreasers from high to moderate PA. By contrast, among increasers, blood pressure declined (systolic β −6.43, CI −12.16 to −0.70; diastolic β −6.72, CI −11.03 to −2.41). Conclusions: Already during the transition to young adulthood, changes in PA are associated with changes in cardiometabolic risk factors. Favorable blood pressure changes were found among PA increasers. Unfavorable changes in BMI, insulin, glucose, and HDL cholesterol were found in groups with decreasing PA. The changes were dependent on the baseline PA and the magnitude of the PA decline