Tracking of Physical Activity, Physical Inactivity, and Health-Related Physical Fitness in Rural Youth

Pate, Russell R.; Trost, Stewart G.; Dowda, Marsha; Ott, A.; Ward, Dianne S.; Saunders, Ruth P.; Felton, Gwen M.

doi:10.1123/pes.11.4.364

Cited by 98 publications

(70 citation statements)

References 23 publications

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“…, whereas ST tracking coefficients were moderate-to-large for boys at all time points (r=0.65-0.40). Pate et al (1999) found that ST tracked moderately well in boys and girls over a 3-year period (r=0.42 and r=0.39 respectively). found that ST tracked moderately well over an 18-month period in boys and girls (r=0.37 and r=0.38 respectively).…”

Section: Resultsmentioning

confidence: 96%

Tracking of sedentary behaviours of young people: A systematic review

Biddle

Pearson

Ross

et al. 2010

Preventive Medicine

534

436

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Objective: To review the empirical evidence concerning the strength of tracking of sedentary behaviors from childhood and adolescence. Methods:Published English language studies were located from computerised and manual searches in 2009. Included studies were prospective, longitudinal studies with at least one sedentary behavior for at least two time-points, with tracking coefficients reported, and included children (aged 3-11 years) and adolescents (12-18 years) at baseline.Results: Based on data from 21 independent samples, tracking coefficients (r) ranged from 0.08 (over 16 years) to 0.73 (over 2 years) for TV viewing, from 0.18 (boys over 3 years) to 0.52 (over 2 years) for electronic game/computer use, from 0.16 (girls over 4 years) to 0.65 (boys over 2 years) for total screen time, and from -0.15 (boys over 2 years) to 0.48 (over 1 year) for total sedentary time. Study follow-up periods ranged from 1 to upto 27 years, and tracking coefficients tended to be higher with shorter follow-ups. Conclusions:Sedentary behaviors track at moderate levels from childhood or adolescence.Data suggest that sedentary behaviors may form the foundation for such behaviors in the future and some may track slightly better than physical activity.

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Section: Resultsmentioning

confidence: 96%

Tracking of sedentary behaviours of young people: A systematic review

Biddle

Pearson

Ross

et al. 2010

Preventive Medicine

534

436

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“…Sendo assim, quanto mais cedo houver intervenções para reduzir o sedentarismo menor a probabilidade do desenvolvimento de obesidade na adolescência e consequentemente menor risco para as doenças crônicas na vida adulta. Foi demonstrado em outros estudos que o maior percentual de crianças e adolescentes que assistem TV em excesso estão nos estratos socioeconômicos menos privilegiados (24,25) . Foi uma surpresa observar que mães com maior escolaridade está associado ao hábito excessivo de assistir TV, uma vez que seria de esperar que mães com mais tempo de educação formal fossem mais conscientes dos prejuízos dessa prática e limitassem a mesma.…”

Section: Resultsunclassified

Fatores associados ao hábito de assistir TV em excesso entre adolescentes

Campagnolo

Vítolo

Gama

2008

Rev Bras Med Esporte

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Objetivo: Avaliar a freqüência com que os adolescentes assistem televisão na região Sul do Brasil e quais fatores estão associados a esse comportamento. Métodos: Estudo transversal, com 722 adolescentes entre 10 e 19 anos. Foi calculado a média de horas diárias que os adolescentes assistiam televisão. Foi realizada análise de regressão logística para analisar possível associação entre fatores sociodemográfico, antropométricos, atividade física, sexo e idade, com o hábito de assistir mais do que 4 horas diárias de televisão. Resultados: Entre os adolescentes estudados, 41,1% assistiam mais do 4 horas de TV por dia. A prevalência de adolescentes que assistiam > 4h de TV foi maior entre aqueles com menos de 16 anos. Ser filho de mãe com escolaridade maior do que 8 anos (OR 1,9; IC 1,25-2,89) e possuir circunferência da cintura maior do que o percentil 80 (OR 2,77; IC 1,33-5,77) foi positivamente associado ao hábito de assistir televisão mais do que 4 horas diá-rias. Conclusões: Maior escolaridade materna e circunferência da cintura maior do que o percentil 80 estão associados ao comportamento de assistir TV em excesso entre os adolescentes. Esses achados devem ser utilizados para direcionar a elaboração de programas de saúde pública, especialmente por meio das escolas, enfocando adolescentes com faixa etária entre 10 e 15 anos, assim como devem servir de alerta para os profissionais de saúde e educadores.Palavras-chave: televisão, adolescente, obesidade. ABSTRACTObjective: to evaluate the frequency adolescents watch TV in southern Brazil and which factors are associated with this behavior. Methods: This was a cross-sectional study. The sample consisted of 722 adolescents between 10 and 19 years of age. Logistic regression analysis was used to verify association between sociodemographic and anthropometric factors, physical activity, age and sex with the adolescents who watched TV for more than four daily hours. Results: Forty-one percent of the adolescents watched more than four daily hours of TV. The prevalence of adolescents who excessively watched TV was higher among those under 16 yr of age (PR 1.92; CI 1.33-2.78). Having a mother with higher educational background (PR 1.51; CI 1.08-2.11), and having waist circumference above 80 percentile (PR 1.63; CI 1.09-2.44) were positively associated with the habit of watching more than 4 hours/day of television. Conclusions: Higher mother educational background and higher waist circumference are associated with excessive television watching. These results can be useful to create health programs at schools, focusing adolescents between 19 and 15 years old. Keywords INTRODUÇÃOA prevalência de excesso de peso entre os adolescentes brasileiros aumentou de 3,7% na década de 70 para 12,6% na década de 90, similar a média de aumento anual dos Estados Unidos (1) . Este quadro é conseqüência do processo de transição nutricional que o Brasil vem passando nas últimas décadas (2) , acompanhado de mudanças no há-bito alimentar da população, o qual passou a ser caracterizado pelo aume...

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“…Tracking is the continuation of an activity over time, and it generally decreases as the intervening time increases, as does participation in most energetic activities (Butcher, 1985;Raitakari et al, 1994). While there is tracking of specific activities over even long periods of time, 5 there is significant intra-and inter-individual variability in the amount of time spent in both specific and general physical activities (Butcher, 1985;Kemper et al, 1989;Kelder et al, 1994;Van Mechelen and Kemper, 1995;Anderssen et al, 1996;Pate et al, 1996Pate et al, ,1999Stofan et al, 1998;Kimm et al, 2000). Stability is the maintenance of a person's relative activity level within a group or cohort over time (Lefevre et al, 2000); and evidence exists that both supports and refutes this phenomenon.…”

Section: Introduction: Context Of the Issuementioning

confidence: 99%

Understanding variability in time spent in selected locations for 7–12-year old children

Xue

McCurdy

Spengler

et al. 2004

J Expo Sci Environ Epidemiol

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This paper summarizes a series of analyses of clustered, sequential activity/location data collected by Harvard University for 160 children aged 7-12 years in Southern California (Geyh et al., 2000). The main purpose of the paper is to understand intra-and inter-variability in the time spent by the sample in the outdoor location, the location exhibiting the most variability of the ones evaluated. The data were analyzed using distribution-free hypothesis-testing (K-S tests of the distributions), generalized linear modeling techniques, and random-sampling schemes that produced ''cohorts'' whose descriptive statistical characteristics were evaluated against the original dataset. Most importantly, our analyses indicate that subdividing the population into appropriate cohorts better replicates parameters of the original data, including the interclass correlation coefficient (ICC), which is a relative measure of the intra-and inter-individual variability inherent in the original data. While the findings of our analyses are consistent with previous assessments of ''time budget'' and physical activity data, they are constrained by the rather homogeneous sample available to us. Owing to a general lack of longitudinal human activity/location data available for other age/gender cohorts, we are unable to generalize our findings to other population subgroups.

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Tracking of Physical Activity, Physical Inactivity, and Health-Related Physical Fitness in Rural Youth

Cited by 98 publications

References 23 publications

Tracking of sedentary behaviours of young people: A systematic review

Tracking of sedentary behaviours of young people: A systematic review

Fatores associados ao hábito de assistir TV em excesso entre adolescentes

Understanding variability in time spent in selected locations for 7–12-year old children

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