Are Boys More Active Than Girls?

Are Boys More Active Than Girls?

Adolescent girls and young women are less likely to be physically active than their male peers, according to a recent study.A study from the United States found that girls and women (ages 12 to 29) reported less physical activity than their male counterparts and physical activity dropped off sharply during the transition from adolescence to young adulthood, with disparities by race and income seen among some groups.

Physical activity is important health behaviour and the data analysis describes patterns and duration of physical activity among adolescents and young adults.

The most recent guidelines recommend at least 60 minutes of moderate to vigorous activity for adolescents per day; for adults, 150 minutes per week of moderate physical activity or 75 minutes per week of vigorous physical activity or an equivalent mix of the two is recommended.

9,472 adolescents and young adults between the ages of 12 and 29 who participated in the National Health and Nutrition Examination Survey from 2007 through 2016 and self-reported physical activity.

No Comments

Leave a Reply

Your email address will not be published. Required fields are marked *

Health
Parents, Do Not Worry! Obese Kids Are As Smart As Their Leaner Peers; Study

Obese kids, or those with lesser aerobic fitness, are as smart as their leaner peers, finds a study, that analysed associations of fitness, motor competence and adiposity with cognition.  The study, led by researchers from the University of Eastern Finland, showed that children with different levels of aerobic fitness or body …

Health
Women, Dancing Can Improve Your Daily Functioning At Old Age: Here’s How

While dancing is touted as a whole-body workout for the youth, it can also reduce the risk of disability in older women, according to a new study. The study showed that dancing was associated with a 73 per cent significantly lower risk of developing disability in walking, eating, bathing, dressing …

Health
New ML models to predict cancer symptoms and severity, says study

Two machine learning models that are able to predict cancer symptoms, as well as their severity, could give doctors a head start in treating the second leading cause of death globally, suggests a study. The models Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) are both able to accurately …