Habitual physical activity levels and sedentary time of children in different childcare arrangements from a nationally representative sample of Canadian preschoolers

Statler, Julie; Wilk, Piotr; Timmons, Brian W.; Colley, Rachel C.; Tucker, Patricia

doi:10.1016/j.jshs.2019.03.009

Cited by 7 publications

(7 citation statements)

References 24 publications

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“…It is possible to notice the importance of increasing activity level, decreasing sedentary behavior, and adopting healthy and balanced eating habits during adolescence, to prevent the development of inflammatory process, associated with overweight and body fat [ 2 , 49 ]. In this research, the evaluation of body composition displayed that 22.5% of the adolescents were overweight or obese, in addition to 54% with elevated (above 30%) BF%.…”

Section: Discussionmentioning

confidence: 99%

“…Adolescence is one of the critical moments in life when most behaviors related to lifestyle (LS) are established and can exert influence in adulthood [ 1 ]. In this sense, the promotion of a healthy LS among adolescents should be the target of interventions, since several of the modifiable behavioral risk factors, such as physical inactivity, excessive sedentary behavior, inadequate diet, and alcohol and tobacco use are associated with the occurrence of chronic noncommunicable diseases [ 2 , 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

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Association of Lifestyle and Body Composition on Risk Factors of Cardiometabolic Diseases and Biomarkers in Female Adolescents

Miranda

Amorim

Bastos

et al. 2020

Mediators of Inflammation

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Background. Female adolescents are considered a risk group for cardiometabolic disease due to their lifestyle (LS). Objective. To evaluate the association between LS classes and body composition groups with cardiometabolic disease risk factors and pro- and anti-inflammatory biomarkers in female adolescents. Methods. This cross-sectional study was carried out with female adolescents aged 14 to 19 years, from Viçosa-MG, Brazil. Latent class analysis assessed LS classes. Kinanthropometric measurements were taken together with the body fat percentage (BF%), being analyzed by the Dual Energy X-ray Absorptiometry (DEXA) equipment. Blood pressure and biochemical parameters were analyzed in the Health Division of the Federal University of Viçosa. The pro- and anti-inflammatory biomarkers were analyzed using Luminex technology. Associations with biomarkers were estimated by multiple linear regression. Results. 405 female adolescents were evaluated. The majority, 82.57%, 72.90%, and 65.31%, were classified as inactive by the number of steps, with high screen and cell phone time, respectively. Furthermore, 41.55% did meet the minimum of 60 minutes of moderate-to-vigorous physical activity (MVPA) and 54.69% had high values of BF% (DEXA). The “Sedentary & Inactive LS” class together with the high levels of weight and BF% were associated with increased levels of blood pressure, lipid profile, and uric acid. It was also found that “Inactive & Sedentary LS”, high BF%, insulin resistance, and ultra-sensitive C-reactive protein were associated with the concentrations of proinflammatory biomarkers of tumor necrosis factor-α, interleukin-6, and leptin. Conclusion. We concluded that female adolescents with overweight/obese and high BF% presented higher values of anthropometric indicators, levels of blood pressure, concentration of uric acid and hs-CRP, and lower concentration of HDL. Inactive and Sedentary lifestyle of these girls, along with excess body fat, insulin resistance, and higher concentrations of hs-CRP were associated with the higher concentration proinflammatory markers.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Association of Lifestyle and Body Composition on Risk Factors of Cardiometabolic Diseases and Biomarkers in Female Adolescents

Miranda

Amorim

Bastos

et al. 2020

Mediators of Inflammation

View full text Add to dashboard Cite

show abstract

“…This study shows that boys had a higher tendency to engage in MVPA than girls; however, there were no gender differences in PA behavior other than the MVPA values, which were higher in boys than girls on weekdays. It is important to note that gender differences in PA behavior are still controversial; on the one hand, some studies indicate that boys have higher MVPA than girls [ 4 , 44 ], while others indicate that there are no differences [ 22 ]. This absence of differences may be due to the age of the sample studied, as in the present study, the children were two years old, a stage close to the development of bipedal vertical locomotion and with greater homogeneity at the motor level between genders [ 47 ].…”

Section: Discussionmentioning

confidence: 99%

“…However, a notable limitation to some research in this area has been the lack of consideration for various times throughout the day, different situations and spaces, which may facilitate PA amongst children. For example, in the school context, some studies have shown that preschool children who attend school obtain the same amount of MVPA as those who are not in school [ 22 ]. In contrast, more recent research showed Spanish schools have a modest contribution of 24% to the recommended minimum PA levels [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

When Are Children Most Physically Active? An Analysis of Preschool Age Children’s Physical Activity Levels

et al. 2022

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The levels of physical activity (PA) in the population have decreased, especially at an early age. The aims of the study were: to evaluate the percentage of children meeting PA recommendations for both genders, and to measure steps and PA level at different time intervals during the week. This was an observational cross-sectional study. Seventy-three schoolchildren (36 boys and 37 girls), aged two years (2.12 ± 0.46), were selected to participate in this study. Participants wore an “Actigraph GT3X” accelerometer for seven days to measure the minutes engaged in moderate-to-vigorous physical activity (MVPA) and step volume. The results show 100% of the children studied met the recommended 60 min/day of MVPA, and 50% achieved 120 min/day MVPA and 13,000 steps per day. No gender differences were found. The results of the analysis show a propensity for higher step volumes and PA values from Monday to Friday. In addition, subjects achieved higher step volumes and PA values during “School Time” than “Out-of-School Time”. Given that during “School Time” children showed higher PA and step values, schools represent an important place to help facilitate PA milestones. This study shows the need for further studies and interventions aimed at understanding and improving children’s PA levels at an early age.

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“…To sort and analyze accelerometer data, researchers have developed various cut points or regression equations using vector magnitude (i.e., the square root of the sum of squares of each of the three axes) or vertical axis. This common method for categorizing PA intensities has been extensively used for the data processing of hip-mounted accelerometers in previous studies [27][28][29][30][31][32][33][34][35][36][37]. It is important to keep in mind that cut points are the thresholds of activity counts used to categorize activity as sedentary, light PA, moderate PA, vigorous PA, or very vigorous PA, and thus, is arbitrary in nature (see Figure 1).…”

Section: Activity Count-based Cut Pointsmentioning

confidence: 99%

The Dilemma of Analyzing Physical Activity and Sedentary Behavior with Wrist Accelerometer Data: Challenges and Opportunities

Gao

Liu

McDonough

et al. 2021

JCM

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Physical behaviors (e.g., physical activity and sedentary behavior) have been the focus among many researchers in the biomedical and behavioral science fields. The recent shift from hip- to wrist-worn accelerometers in these fields has signaled the need to develop novel approaches to process raw acceleration data of physical activity and sedentary behavior. However, there is currently no consensus regarding the best practices for analyzing wrist-worn accelerometer data to accurately predict individuals’ energy expenditure and the times spent in different intensities of free-living physical activity and sedentary behavior. To this end, accurately analyzing and interpreting wrist-worn accelerometer data has become a major challenge facing many clinicians and researchers. In response, this paper attempts to review different methodologies for analyzing wrist-worn accelerometer data and offer cutting edge, yet appropriate analysis plans for wrist-worn accelerometer data in the assessment of physical behavior. In this paper, we first discuss the fundamentals of wrist-worn accelerometer data, followed by various methods of processing these data (e.g., cut points, steps per minute, machine learning), and then we discuss the opportunities, challenges, and directions for future studies in this area of inquiry. This is the most comprehensive review paper to date regarding the analysis and interpretation of free-living physical activity data derived from wrist-worn accelerometers, aiming to help establish a blueprint for processing wrist-derived accelerometer data.

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Habitual physical activity levels and sedentary time of children in different childcare arrangements from a nationally representative sample of Canadian preschoolers

Cited by 7 publications

References 24 publications

Association of Lifestyle and Body Composition on Risk Factors of Cardiometabolic Diseases and Biomarkers in Female Adolescents

Association of Lifestyle and Body Composition on Risk Factors of Cardiometabolic Diseases and Biomarkers in Female Adolescents

When Are Children Most Physically Active? An Analysis of Preschool Age Children’s Physical Activity Levels

The Dilemma of Analyzing Physical Activity and Sedentary Behavior with Wrist Accelerometer Data: Challenges and Opportunities

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