Saturday January 18, 2020

Mother’s Lifestyle Choices Linked to Obesity Risk in Adolescents

The risk of obesity was also lower among children of mothers who consumed low or moderate levels of alcohol compared with those whose mothers abstained from alcohol

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Disinfectants
Representational image. Pixabay

Adolescents whose mothers follow a healthy diet, exercise regularly, and refrain from smoking may be 75 per cent less likely to develop obesity, according to a study.

The findings also suggested that children of women who maintained a healthy body weight and did not smoke had 56 per cent and 31 per cent lower risk of obesity respectively.

“The study demonstrates that an overall healthy lifestyle really outweighs any individual healthy lifestyle factors followed by mothers when it comes to lowering the risk of obesity in their children,” said Qi Sun, from the Harvard University’s T.H. Chan School of Public Health, in the US.

For the study, published in the journal The BMJ, the team examined data from 24,289 children aged between nine and 18 years of age, who were born to 16,945 women. They looked at the association between a mother’s lifestyle and the risk of obesity among their children and adolescents.

mother
Representational image. Pixabay

The results showed that 5.3 per cent of the group developed obesity during a median five year follow-up period. Maternal obesity, smoking, and physical inactivity were strongly associated with obesity among children and adolescents.

While the greatest drop in obesity risk was seen when mothers and children followed healthy lifestyle habits, many of the healthy habits had a noticeable impact on the risk of childhood obesity when assessed individually.

Also Read: Obesity And Smoking: Roadblocks In Arthritis Treatment

The risk of obesity was also lower among children of mothers who consumed low or moderate levels of alcohol compared with those whose mothers abstained from alcohol.

Further, mothers’ dietary patterns were not associated with obesity in their children, possibly because children’s diets are influenced by many factors, including school lunches and available food options in their neighbourhoods. (IANS)

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Here’s how MRI may Predict Intelligence Level in Children

MRI may predict intelligence level in children

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Researchers have found that MRI scanning can help predict the intelligence level in children. Pixabay

Researchers have used ensemble methods based on deep learning 3D analysis networks to answer the global Magnetic Resonance Imaging (MRI) prevision challenge for children.

Importantly, they made predictions for both the fluid intelligence level and the target variable independent from age, gender, brain size or MRI scanner used.

MRI is a common technique used to obtain images of human internal organs and tissues. Scientists wondered whether the intelligence level can be predicted from an MRI brain image.

“Our team develops deep learning methods for computer vision tasks in MRI data analysis, amongst other things,” said study researcher Ekaterina Kondratyev from Skolkovo Institute of Science and Technology (Skoltech) in Russia.

“In this study, we applied ensembles of classifiers to 3D of super precision neural networks: with this approach, one can classify an image as it is, without first reducing its dimension and, therefore, without losing valuable information,” said Kondratyeva.

The US National Institutes of Health (NIH) database contains a total of over 11,000 structural and functional MRI images of children aged 9-10.

MRI
MRI is a common technique used to obtain images of human internal organs and tissues. Pixabay

In 2013, NIH launched the first grand-scale study of its kind in adolescent brain research, Adolescent Brain Cognitive Development, to see if and how teenagers’ hobbies and habits affect their further brain development.

NIH scientists launched an international competition, making the enormous NIH database available to a broad community for the first time ever.

The participants were given a task of building a predictive model based on brain images.

As part of the competition, the Skoltech team applied neural networks for MRI image processing.

To do this, they built a network architecture enabling several mathematical models to be applied to the same data in order to increase the prediction accuracy, and used a novel ensemble method to analyse the MRI data.

In their recent study, Skoltech researchers focused on predicting the intelligence level, or the so called “fluid intelligence”, which characterises the biological abilities of the nervous system and has little to do with acquired knowledge or skills.

Importantly, they made predictions for both the fluid intelligence level and the target variable independent from age, gender, brain size or MRI scanner used.

Also Read- Severity of Autism Spectrum Disorder Varies Among Twins: Study

The results of the study helped find the correlation between the child’s “fluid intelligence” and brain anatomy.

Although the prediction accuracy is less than perfect, the models produced during this competition will help shed light on various aspects of cognitive, social, emotional and physical development of adolescents. (IANS)