Association between physical activity levels in mid-life with physical activity in old age: a 20-year tracking study in a prospective cohort

ObjectivesThis study aims to examine the tracking and predictability of physical activity in old age from overall physical activity and participation in sport, recreational activity and walking in mid-life.DesignProspective population-based cohort study.SettingBritish Regional Heart Study participants recruited from primary care centres in the UK in 1978–1980.Participants and outcome measuresMen (n=3413) self-reported their physical activity at baseline, 12, 16 and 20-year follow-ups and were categorised as inactive or active and having high or low participation in sport, walking and recreational activities. Tracking was assessed using kappa statistics and random effects models. Logistic regression estimated the odds of being active at 20-year follow-up according to physical activity participation in mid-life.ResultsAmong 3413 men (mean age at baseline 48.6±5.4 years) with complete data, tracking of overall physical activity was moderate (kappa: 0.23–0.26). Tracking was higher for sports participation (kappa: 0.35–0.38) compared with recreational activity (kappa: 0.16–0.24) and walking (kappa: 0.11–0.15). Intraclass correlation coefficients demonstrated similar levels of stability and only marginally weakened after controlling for covariates. Compared with inactive men, being active at baseline was associated with greater odds of being active at 20-year follow-up (OR 2.7, 95% CI 2.4 to 3.2) after adjusting for sociodemographic, health and lifestyle variables. Playing sport in mid-life was more strongly associated with being active at 20-year follow-up than other domains, particularly when sport participation began earlier in life.ConclusionBeing physically active in mid-life increases the odds of being active in old age. Promoting physical activity in later life might be best achieved by promoting sport participation earlier in the life course.

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Results From Kenya’s 2016 Report Card on Physical Activity for Children and Youth

Journal of Physical Activity and Health ◽

10.1123/jpah.2016-0359 ◽

2016 ◽

Vol 13 (s2) ◽

pp. S195-S200 ◽

Cited By ~ 9

Author(s):

Vincent O. Onywera ◽

Stella K. Muthuri ◽

Sylvester Hayker ◽

Lucy-Joy M. Wachira ◽

Florence Kyallo ◽

...

Keyword(s):

Physical Activity ◽

Sport Participation ◽

Sports Participation ◽

Well Being ◽

Report Card ◽

Active Transportation ◽

Overweight And Obesity ◽

Children And Youth ◽

World Health ◽

Activity Levels

Background:Kenya’s 2016 report card aimed to highlight the health and well-being of Kenyan children and youth using the best available evidence on the physical activity of Kenyan children and youth. The report pointed at areas where Kenya was succeeding and areas where more action is required.Methods:Inclusive analyses of available data sources on the core indicators related to physical activity and body weights of Kenyan children and youth (5 to 17 years) were conducted. These were assigned grades based on a set of specific criteria.Results:Results show that Active Play, Active Transportation, Overweight and Obesity, and Sedentary Behavior were favorable with a grade of B. Overall Physical Activity, Organized Sport Participation, and School (infrastructure, policies, and programs) each received a grade of C, while Family and Peers, Government and Nongovernment organizations, as well as the Community and the Built Environment were assigned grade D.Conclusions:Over 72% of Kenyan children and youth use active transportation to and from school and in their daily lives. Although majority of the children and youth have normal body weight, there is need to ensure that they meet and maintain the physical activity levels recommended by the World Health Organization. More needs to be done especially in relation to the governmental and nongovernmental organizations, organized sports participation, as well as involvement of family and peers in promoting healthy active lifestyles among Kenyan children and youth. More representative data for all indicators are required in Kenya.

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Tracking of Physical Activity, Sport Participation, and Sedentary Behaviors over Four Years of High School

Sustainability ◽

10.3390/su10093104 ◽

2018 ◽

Vol 10 (9) ◽

pp. 3104 ◽

Cited By ~ 7

Author(s):

Lovro Štefan ◽

Marjeta Mišigoj-Duraković ◽

Antonela Devrnja ◽

Hrvoje Podnar ◽

Vilko Petrić ◽

...

Keyword(s):

Physical Activity ◽

High School ◽

High School Students ◽

Screen Time ◽

Sport Participation ◽

Sports Participation ◽

Sedentary Behaviors ◽

School Students ◽

And Gender

Background: The aim of the present study was to investigate the extent of tracking of physical activity (PA), sports participation (SP), and sedentary behaviors (SB) over four years of high school education among the Croatian Physical Activity in Adolescence Longitudinal Study (CRO-PALS) cohort. Methods: In this investigation, participants were 844 high school students (15.6 years at baseline; 49% girls). The SHAPES questionnaire was used to assess PA, SP, and SB at ages 15, 16, 17, and 18 and tracking was assessed using generalized estimating equations. Results: Tracking coefficients for PA were similar in both sexes, ranged from 0.49 to 0.61, and indicated moderate tracking, while the tracking of SB tended to be somewhat higher over the four years of follow-up (β = 0.60–0.72). Youth that participated in sports at baseline had a 16 to 28 times higher odds of continued participation at follow-up, depending on the type of sport and gender. Finally, both low physical activity and high screen time showed strong tracking in both genders. Conclusion: PA and SB tracked moderately between ages 15 and 18. Moreover, the strong tracking of low PA and high screen time indicates that the detection of these risk factors at the beginning of high school should be advocated.

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Determinants of changes in physical activity levels in late adolescence; prospective analysis in urban communities

Proceedings of the 12th International Conference on Kinanthropology ◽

10.5817/cz.muni.p210-9631-2020-39 ◽

2020 ◽

Author(s):

Natasa Zenic ◽

Admir Terzic ◽

Ivan Kvesic

Keyword(s):

Physical Activity ◽

Logistic Regression ◽

Sport Participation ◽

Rank Order ◽

T Test ◽

Childhood And Adolescence ◽

Activity Levels ◽

Related Factors ◽

Physical Activity Levels

Purpose: Physical activity levels (PA-levels) significantly decline during adolescence, and sport participation during childhood and adolescence is frequently emphasized as protec-tive factors of PA-decline. However, there is a lack of studies which specifically examined sport-related factors and its influence on changes in PA (PA-changes) in adolescence. This study aimed to prospectively observe sport factors as: (i) correlates of PA-levels and (ii) pre-dictors of PA-changes in the period between 16 and 18 years of age among urban adoles-cents from Bosnia and Herzegovina. Methods: The sample of participants comprised 324 adolescents (44% females) who were prospectively observed over two testing waves: (i) baseline, when participants were 16 years old; and (ii) follow-up, 20 months later (18 years of age). The variables were collected by previously validated questionnaires including questions on predictors (sociodemographic variables and various sport factors [current/former/ever participation in individual and team sports, experience in sports, competitive result achieved]), and criteria (PA level obtained at study baseline and follow up, measured by Physical Activity Questionnaire for Adolescents [PAQ-A], and difference between PA-levels at baseline and follow-up). The t-test was used to compare PA-levels. The associations between variables were evidenced by: (i) Spear-man’s rank order correlations (between predictors and PA-levels), and (ii) logistic regression analysis (between predictors, and PA-changes observed as binomial criterion [PA-incline vs. PA-decline] – excluding those participants who reported active sport participation at study baseline). Results: The PA-level significantly declined over the study course (t-test: 6.60, p < 0.01). Sport-related predictors were significantly associated with PA at baseline (Spearman’s R: 0.33–0.45, p < 0.01), and PAat follow-up (Spearman’s R: 0.32-0.45, p < 0.01). Meanwhile, there was no significant correlation between studied predictors and differences in PA-levels between baseline and follow-up. Also, logistic regression did not reveal any significant influ-ence of predictors obtained at study baseline and PA-changes observed as binomial criterion (PA-incline vs PA-decline). Conclusion: While studied sport-related predictors significantly influence the PA-levels in the age of 16 and 18, with the higher level of PA among those adolescents who are actively in-volved in sports, sport-participation do not predict changes in PA-levels over the observed period of life. Knowing the influence of PAon overall health status, future studies should pro-vide additional details on possible predictors of PA-changes in adolescence.

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Familial and Parental Predictors of Physical Activity in Late Adolescence: Prospective Analysis over a Two-Year Period

Healthcare ◽

10.3390/healthcare9020132 ◽

2021 ◽

Vol 9 (2) ◽

pp. 132

Author(s):

Damir Sekulic ◽

Dora Maric ◽

Sime Versic ◽

Ante Zevrnja ◽

Admir Terzic ◽

...

Keyword(s):

Physical Activity ◽

Sport Participation ◽

Sociodemographic Factors ◽

Male Gender ◽

Repeated Measurements ◽

Parental Conflict ◽

Activity Levels ◽

Targeted Interventions ◽

Paternal Education

Children’s health behaviors are highly influenced by their parents and family. This study aimed to prospectively evaluate the parental/familial factors associated with physical activity levels (PALs) among older adolescents. The participants were 766 adolescents, who were prospectively observed at baseline (when they were 16 years of age), at first follow-up measurement (FU1; 17 years of age), and second follow-up measurement (FU2; 18 years of age). Sociodemographic factors (age, gender, socioeconomic status, and sport participation) and parental/familial variables were evaluated at baseline. PALs (evidenced by the Physical-Activity Questionnaire-for-Adolescents) were prospectively evidenced at baseline, FU1, and FU2. Factorial analysis of variance for repeated measurements showed a significant decrease in PALs during the study course (F = 83.05, p < 0.001). Sport participation and male gender were significant predictors of PALs at baseline, FU1, and FU2. Logistic regression, controlled for sport participation and male gender, evidenced paternal education as a significant predictor of baseline PALs. Parental conflict was a significant predictor of PALs in all three testing waves. The significant influence of paternal education on the children’s PALs existed from younger adolescence until the age of 17 years. The association between parental conflict and PALs developed in older adolescence. These results should be used in the development of specific and targeted interventions aimed at the improvement of PALs and a reduction of sedentarism in youth.

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How Adolescent Sports Participation, Family, and School Resources Impact Later-Life Physical Activity Levels

Innovation in Aging ◽

10.1093/geroni/igaa057.1626 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 503-504

Author(s):

Thalida Arpawong ◽

Margaret Gatz ◽

Tara Gruenewald ◽

Catalina Zavala ◽

Dominika Seblova ◽

...

Keyword(s):

Physical Activity ◽

Monozygotic Twins ◽

Sports Participation ◽

Later Life ◽

School Level ◽

Future Research ◽

School Resources ◽

Activity Levels ◽

Pair Correlations ◽

Family Ses

Abstract Engaging in physical activity (PA) in adulthood has multiple protective health effects in later ages. However, unknown are the extent to which PA habits are laid down earlier in life and persist into adulthood, and the extent to which greater opportunities for PA during adolescence stem from differences in socioeconomic status (SES) which then affect opportunities for PA. We investigated potential mechanisms underlying these relationships using the longitudinal Project Talent Twin and Sibling Study (assessments in 1960 and 2014). With this design, we are able to hold genetics constant by modeling relationships between monozygotic twins (who share 100% of their genes) and therefore isolate effects of contextual factors on later-life PA (mean age ~70). We found that higher family SES (ß=.39, p<.0001) and sports participation in adolescence (ß=.05, p<.0001) predicted PA 55 years later, adjusted for gender and physical limitations. This held true when partialling out genetic variation that could otherwise explain these relationships. More education also predicted later-life PA (ß=.12, p<.0001) separately from family SES and partially mediated the effect of family SES on PA. While school-level resources (e.g., availability of sports and recreation opportunities) did not predict later life PA, they did associate with adolescent sports participation (ß=.26, p=0.007). Overall, later-life physical activity was influenced by earlier life sports participation and education, with family rearing resources being more important than high school resources. As twin pair correlations suggest gender differences, future research will examine whether family or school resources differentially benefit males or females for later-life physical activity.

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Sports Participation in Youth as a Predictor of Physical Activity: A 5-Year Longitudinal Study

Journal of Physical Activity and Health ◽

10.1123/jpah.2015-0526 ◽

2016 ◽

Vol 13 (7) ◽

pp. 704-711 ◽

Cited By ~ 14

Author(s):

Michelle Hardie Murphy ◽

David Anthony Rowe ◽

Catherine B. Woods

Keyword(s):

Physical Activity ◽

Sports Participation ◽

Later Life ◽

Self Report ◽

Related Factors ◽

Sports Club ◽

Club Sports ◽

Elite Level

Background:The contribution of sports related factors to predicting long-term physical activity (PA) are unclear. The purpose of this study is to examine tracking of PA during key transition periods in youth and to determine the longitudinal associations between sports club participation and PA.Methods:Participants (n = 873, baseline age 10 to 18 years) completed self-report surveys in 2009 and 2014 that included the PACE+ PA tool and sports club participation questions. Spearman correlations assessed PA tracking. ANCOVA analyses examined predictors (sports participation at baseline) of PA (follow-up), adjusting for (a) age and sex; and (b) age, sex, and baseline PA.Results:Tracking of PA was weak-to-moderate (ρ = .16 to .47). Greater sports participation frequency at baseline significantly predicted PA at follow-up (P < .01). Involvement in club sports at an elite level had a medium-to-large effect on PA levels 5 years later [d = .75 adjusting for (a); d = .60 adjusting for (b)].Conclusion:PA should be promoted in youth as tracking coefficients suggest it can, to an extent, continue into later life. The standard achieved in sport has a role in predicting later PA. PA promotion strategies should include frequent, high quality opportunities for sports participation.

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The Impact of Scholastic Factors on Physical Activity Levels during the COVID-19 Lockdown: A Prospective Study on Adolescents from Bosnia and Herzegovina

Children ◽

10.3390/children8100877 ◽

2021 ◽

Vol 8 (10) ◽

pp. 877

Author(s):

Damir Sekulic ◽

Daria Ostojic ◽

Andrew Decelis ◽

‪José Castro-Piñero ◽

Tatjana Jezdimirovic ◽

...

Keyword(s):

Physical Activity ◽

Grade Point Average ◽

Bosnia And Herzegovina ◽

Sport Participation ◽

Activity Levels ◽

Grade Point ◽

Physical Activity Levels ◽

A Prospective Study ◽

The Impact

Scholastic factors (academic achievement) are hypothesized to be important determinants of health-related behaviors in adolescents, but there is a lack of knowledge on their influence on physical activity levels (PAL), especially considering the COVID-19 pandemic and the imposed lockdown. This study aimed to investigate the associations between scholastic factors and PAL before and during the pandemic lockdown. The participants were adolescents form Bosnia and Herzegovina (n = 525, 46% females), who were observed prospectively at the baseline (before the pandemic lockdown) and during the lockdown in 2020 (follow-up). The scholastic factors (grade point average, behavioral grade, school absences, unexcused absences) were evidenced at the baseline (predictors). The outcome (PAL) was evaluated using the Physical Activity Questionnaire for Adolescents at the baseline and the follow-up. Gender, age, parental/familial conflict, and sport participation were observed as confounders. No significant influence of the predictors on PAL were evidenced at the baseline or at the follow-up. The scholastic variables were significantly associated with the changes of PAL which occurred due to pandemic lockdown, with a lower risk for negative changes in PAL among adolescents who were better in school (OR = 0.56, 95%CI: 0.34–0.81, and OR = 0.66, 95%CI: 0.34–0.97, for the grade point average and behavioral grade, respectively). Students who do well in school are probably more aware of the health benefits of proper PAL, and therefore are devoted to the maintenance of their PAL even during the home-confinement of lockdown. Public health authorities should focus more on helping adolescents to understand the importance and benefits of proper PAL throughout the school system.

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Cognitive Impairment and Physical Activity in Old Age: The Impact on All-Cause Mortality in a 15-Year Follow-Up of the Bambuí Cohort Study of Aging

SSRN Electronic Journal ◽

10.2139/ssrn.3557992 ◽

2020 ◽

Author(s):

Erico Castro-Costa ◽

Jerson Laks ◽

Cecilia Godoi Campos ◽

Josélia OA Firmo ◽

Maria Fernanda Lima-Costa ◽

...

Keyword(s):

Physical Activity ◽

Cohort Study ◽

Cognitive Impairment ◽

Old Age ◽

All Cause Mortality ◽

The Impact

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Leisure time physical activity throughout adulthood is associated with lower medicare costs: evidence from the linked NIH-AARP diet and health study cohort

BMJ Open Sport & Exercise Medicine ◽

10.1136/bmjsem-2021-001038 ◽

2021 ◽

Vol 7 (1) ◽

pp. e001038

Author(s):

Diarmuid Coughlan ◽

Pedro F Saint-Maurice ◽

Susan A Carlson ◽

Janet Fulton ◽

Charles E Matthews

Keyword(s):

Physical Activity ◽

Healthcare Costs ◽

Middle Age ◽

Leisure Time Physical Activity ◽

Early Adulthood ◽

Later Life ◽

Health Study ◽

Activity Levels ◽

Physical Activity Levels ◽

Medicare Costs

BackgroundThere is limited information about the association between long-term leisure time physical activity (LTPA) participation and healthcare costs. The purpose of this study was to investigate the association between LTPA over adulthood with later life healthcare costs in the USA.MethodsUsing Medicare claims data (between 1999 and 2008) linked to the National Institutes of Health-American Association of Retired Persons (NIH-AARP) Diet and Health Study, we examined associations between nine trajectories of physical activity participation throughout adulthood with Medicare costs.ResultsCompared with adults who were consistently inactive from adolescence into middle age, average annual healthcare costs were significantly lower for maintainers, adults who maintained moderate (–US$1350 (95% CI: –US$2009 to –US$690) or −15.9% (95% CI: −23.6% to −8.1%)) or high physical activity levels (–US$1200 (95% CI: –US$1777 to –US$622) or −14.1% (95% CI: −20.9% to −7.3%)) and increasers, adults who increased physical activity levels in early adulthood (–US$1874 (95% CI: US$2691 to –US$1057) or −22.0% (95% CI: −31.6% to −12.4%)) or in middle age (–US$824 (95% CI: –US$1580 to –US$69 or −9.7% (95% CI −18.6% to −0.8%)). For the four trajectories where physical activity decreased, the only significant difference was for adults who increased physical activity levels during early adulthood with a decline in middle age (–US$861 (95% CI:–US$1678 to –US$45) or −10.1% (95% CI: −19.7% to −0.5%)).ConclusionOur analyses suggest the healthcare cost burden in later life could be reduced through promotion efforts supporting physical activity participation throughout adulthood.

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An empirical example of analysis using a two-stage modeling approach: within-subject association of outdoor context and physical activity predicts future daily physical activity levels

Translational Behavioral Medicine ◽

10.1093/tbm/ibaa107 ◽

2020 ◽

Author(s):

Chih-Hsiang Yang ◽

Jaclyn P Maher ◽

Aditya Ponnada ◽

Eldin Dzubur ◽

Rachel Nordgren ◽

...

Keyword(s):

Physical Activity ◽

Vigorous Physical Activity ◽

Wearable Sensors ◽

Activity Levels ◽

Two Stage ◽

Modeling Approach ◽

Source Program ◽

Modeling Strategy ◽

Stage Modeling

Abstract People differ from each other to the extent to which momentary factors, such as context, mood, and cognitions, influence momentary health behaviors. However, statistical models to date are limited in their ability to test whether the association between two momentary variables (i.e., subject-level slopes) predicts a subject-level outcome. This study demonstrates a novel two-stage statistical modeling strategy that is capable of testing whether subject-level slopes between two momentary variables predict subject-level outcomes. An empirical case study application is presented to examine whether there are differences in momentary moderate-to-vigorous physical activity (MVPA) levels between the outdoor and indoor context in adults and whether these momentary differences predict mean daily MVPA levels 6 months later. One hundred and eight adults from a multiwave longitudinal study provided 4 days of ecological momentary assessment (during baseline) and accelerometry data (both at baseline and 6 month follow-up). Multilevel data were analyzed using an open-source program (MixWILD) to test whether momentary strength between outdoor context and MVPA during baseline was associated with average daily MVPA levels measured 6 months later. During baseline, momentary MVPA levels were higher in outdoor contexts as compared to indoor contexts (b = 0.07, p < .001). Participants who had more momentary MVPA when outdoors (vs. indoors) during baseline (i.e., a greater subject-level slope) had higher daily MVPA at the 6 month follow-up (b = 0.09, p < .05). This empirical example shows that the subject-level momentary association between specific context (i.e., outdoors) and health behavior (i.e., physical activity) may contribute to overall engagement in that behavior in the future. The demonstrated two-stage modeling approach has extensive applications in behavioral medicine to analyze intensive longitudinal data collected from wearable sensors and mobile devices.

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