Factors associated with low levels of aerobic fitness among adolescents

Gonçalves, Eliane Cristina de Andrade; Silva, Diego Augusto Santos

doi:10.1016/j.rppede.2015.06.025

Cited by 13 publications

(10 citation statements)

References 18 publications

(31 reference statements)

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“…Also, differences in weight were found out, with obese people being less likely to have a good fitness level compared to normal and underweight people. This is in line with different findings in the literature confirming that obesity is inversely related to fitness [17,23,[38][39][40][41].…”

Section: Discussionsupporting

confidence: 93%

“…Moreover, fitness is related to academic performance that includes cognitive skills and attitudes (e.g., attention, memory, comprehension), academic behaviors (e.g., organization, attendance, impulse control), and achievement (e.g., standardized test scores, grade point averages) [10][11][12][13]. As mentioned above, scientific literature reports the relation among low fitness levels of adolescents and several factors involving genetic, biological, familiar, environmental, and behavioral aspects, such as female gender, low income, low consumption of dairy products and/or bread/cereals, increased consumption of sweetened beverages, insufficient physical activity level, excessive screen time, and excess body fat [14][15][16][17]. School represents the correct environment where adolescents' fitness could be assessed and monitored [12,18], with the aim of identifying possible low fitness levels and use appropriate interventions to increase them.…”

Section: Introductionmentioning

confidence: 99%

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An Exploratory Analysis of Factors Associated with Health-Related Physical Fitness in Adolescents. The ASSO Project

et al. 2018

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Monitoring physical fitness (fitness) and identifying, since the beginning, possible determinants in youth could be useful to preserve health and avoid morbidities in adulthood. The main objective of this study is to provide details on the fitness levels of a sample of adolescents living in the Southern area of Italy and describe its associations with biological/genetic, socio-cultural/environmental, and lifestyle (physical activity/sedentariness, alcohol/smoking, meal patterns/habits) factors. The study was conducted within the Adolescence Surveillance System for Obesity Prevention (ASSO) project, funded by the Italian Ministry of Health and examining adolescents' lifestyle in relation to obesity. Fitness measures were collected through the ASSO-fitness tests battery (FTB) and examined in relation to 79 selected possible influencing factors, which were collected through a web-based questionnaire included in the ASSO-NutFit software. Logistic regression analyses were performed to assess associations, with ORs and 95% CIs estimated as crude and adjusted. A total of 919 participants were initially recruited, but fitness data were collected for 544 students aged 13-19 (68% M, 32% F). Fitness level was low for 14.2% of the students, medium for 67.8%, and high for 18.0%. The independent determinants of low physical fitness in our sample of adolescents were included in the biological/genetic and physical activity/sedentariness dimensions: female gender (Adj OR 8.33, CI 2.08-33.33), obesity (Adj OR 1.97, CI 1.10-9.22), practicing sport less than 3 h/week (Adj OR 6.09, CI 1.63-22.72), practicing sport with strength/speed as prevalent biomotor ability (Adj OR 8.97, CI 1.43-56.19), using PC/internet for more than 3 h/day (Adj OR 4.46, CI 1.17-16.98). Drinking alcohol was instead a protective factor. This study confirms that females and obese individuals need more attention in the interventions aimed at increasing fitness levels. It suggests that local actions should be implemented with the aim of increasing sport practices and reducing sedentary time spent in front of PC/internet. The focus should be particularly addressed to sports with strength or speed as dominant biomotor abilities.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

An Exploratory Analysis of Factors Associated with Health-Related Physical Fitness in Adolescents. The ASSO Project

et al. 2018

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“…The population of this descriptive, cross-sectional and epidemiological study was composed of adolescents aged 14–19 years enrolled in public high schools of São José, Brazil. This study is part of a macro project entitled "Brazilian Guide for Evaluation of Physical Fitness Related to Health and Life Habits" [ 15 , 16 ] and was approved by the Ethics Committee on Human Research of the Federal University of Santa Catarina (UFSC) under CAAE protocol: 33210414.3 .0000.0121. All procedures performed in the study were in accordance with the ethical standards of the national research committee, the 1964 Helsinki declaration and its later amendments as well as comparable ethical standards.…”

Section: Methodsmentioning

confidence: 99%

Clustering of Risk Factors for Non-Communicable Diseases among Adolescents from Southern Brazil

et al. 2016

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IntroductionThe aim of this study was to investigate the simultaneous presence of risk factors for non-communicable diseases and the association of these risk factors with demographic and economic factors among adolescents from southern Brazil.MethodsThe study included 916 students (14–19 years old) enrolled in the 2014 school year at state schools in São José, Santa Catarina, Brazil. Risk factors related to lifestyle (i.e., physical inactivity, excessive alcohol consumption, smoking, sedentary behaviour and unhealthy diet), demographic variables (sex, age and skin colour) and economic variables (school shift and economic level) were assessed through a questionnaire. Simultaneous behaviours were assessed by the ratio between observed and expected prevalences of risk factors for non-communicable diseases. The clustering of risk factors was analysed by multinomial logistic regression. The clusters of risk factors that showed a higher prevalence were analysed by binary logistic regression.ResultsThe clustering of two, three, four, and five risk factors were found in 22.2%, 49.3%, 21.7% and 3.1% of adolescents, respectively. Subgroups that were more likely to have both behaviours of physical inactivity and unhealthy diet simultaneously were mostly composed of girls (OR = 3.03, 95% CI = 1.57–5.85) and those with lower socioeconomic status (OR = 1.83, 95% CI = 1.05–3.21); simultaneous physical inactivity, excessive alcohol consumption, sedentary behaviour and unhealthy diet were mainly observed among older adolescents (OR = 1.49, 95% CI = 1.05–2.12). Subgroups less likely to have both behaviours of sedentary behaviour and unhealthy diet were mostly composed of girls (OR = 0.58, 95% CI = 0.38–0.89); simultaneous physical inactivity, sedentary behaviour and unhealthy diet were mainly observed among older individuals (OR = 0.66, 95% CI = 0.49–0.87) and those of the night shift (OR = 0.59, 95% CI = 0.43–0.82).ConclusionAdolescents had a high prevalence of simultaneous risk factors for NCDs. Demographic (gender and age) and economic (school shift) variables were associated with the most prevalent simultaneous behaviours among adolescents.

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“…Despite that, our data seems to be in accordance with recent studies. For instance, data from 879 adolescents aged 14-19 year-old from São José, Santa Catarina, showed that they spent 6.5 ± 4.9 hours (85.4% ≥2 h/ day) in front of TV, computer and videogame, 7.0 ± 4.9 h (90.3% ≥2 h/day) among boys and 5.9 ± 4.8 h (81.2% ≥2 h/day)among girls 43 . Data from 515 boys and 716 girls aged 14-17 year-old from Londrina, Paraná, found that most adolescents (93.8% of boys and 87.2% of girls) spent ≥2 h/day in ST 44 .…”

Section: Discussionmentioning

confidence: 99%

Screen time between Portuguese and Brazilian children: a cross-cultural study

Santos

Silva-Santos

Andaki

et al. 2017

Motriz: rev. educ. fis.

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-Aims:To verify differences in screen time (ST) (hours watching TV, using computer and/or video game) and to compare the percentage of meeting ST recommendation between Portuguese and Brazilian children. Methods: The sample comprised 369 children aged 9 year-old from Portugal (n=95) and Brazil (n=274). ST average (h/day), physical activity (PA) and socioeconomic status (SES) were estimated by parental-report questionnaire. The Student t test or the Mann-Whitney U test and binary logistic regression analysis were used to verify differences and associations on ST (<2h/day) between cities. All analyses were stratified by gender and adjusted for age, BMI, PA and SES. Results: The prevalence of meet ST recommendation was 66.7% and 55.3% between Portuguese girls and boys and 25.0% and 16.4%between Brazilian girls and boys. Portuguese girls (1.58±0.84vs3.40 ± 1.76h/day, p<0.05) and boys (1.74 ± 1.18 vs 4.20 ± 2.30 h/day, p<0.05) had significantly less ST than their Brazilian counterparts. Brazilian girls (OR=7.593; p=0.0001) as well as Brazilian boys (OR=6.564; p=0.0001) were more likely to do not meet ST recommendation, compared with their Portuguese counterparts. Conclusions: Portuguese children were approximately seven times more likely to meet ST recommendation than Brazilian children. Differences between countries should be considered in public policy strategies to reduce ST.

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Factors associated with low levels of aerobic fitness among adolescents

Cited by 13 publications

References 18 publications

An Exploratory Analysis of Factors Associated with Health-Related Physical Fitness in Adolescents. The ASSO Project

An Exploratory Analysis of Factors Associated with Health-Related Physical Fitness in Adolescents. The ASSO Project

Clustering of Risk Factors for Non-Communicable Diseases among Adolescents from Southern Brazil

Screen time between Portuguese and Brazilian children: a cross-cultural study

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