Thursday April 2, 2020

Poor Sleep During Infancy Can Lead to Depression: Study

Poor sleep in infancy linked to behavioural issues

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Infancy
Poor quality sleep during infancy can be an indicator of depression, anxiety and behavioural problems among toddlers. Pixabay

Researchers have found that disrupted and poor quality sleep in the earliest months of a child’s life or infancy can be an indicator of depression, anxiety and behavioural problems among toddlers. This is a health news.

The study, published in the journal BMJ Paediatrics Open, found a clear relationship between sleep problems in infancy such as frequent night wakings, short sleep duration or difficulty in falling asleep and particular emotional and behavioural problems at 24 months of age.

Although childhood sleep problems are extremely common and their association with daytime behavioural difficulties is well recognised, this study shows for the first time how sleep problems in infancy and very early childhood are associated with emotional and behavioural problems later in childhood.

“Our results show that infants who sleep for shorter periods of time, take longer to fall asleep and wake up more frequently during the night are more likely to show emotional and behavioural problems in later stages of childhood,” said lead researcher Isabel Morales-Munoz from University of Birmingham in the UK. “It’s likely that sleep quality in these early months and the development of self-regulation – the ability to control our behaviour – are closely intertwined,” Morales-Munoz added.

Infancy
There is a clear relationship between sleep problems in infancy such as frequent night wakings, short sleep duration or difficulty in falling asleep and particular emotional and behavioural problems at 24 months of age. Pixabay

For the findings, the research team studied the results of two sleep questionnaires completed by parents within the CHILD-SLEEP birth-cohort, a large study cohort based in southern Finland.

For this specific study, the researchers obtained information from nearly 1700 parents who completed a baseline questionnaire, and reported on sleep habits of their children at 3, 8, 18 and 24 months. These results were compared with a separate questionnaire on emotional and behavioural symptoms, which was completed by 950 parents at the child´s age of 24 months..

The researchers found that high frequency of night wakings at 3 months was strongly linked to emotional, behavioural and self-regulation (the ability to control emotions and behaviours) problems in toddlers.

Further, infants who experienced shorter sleep duration, who took longer to fall asleep and who experienced frequent night wakings at different stages of early childhood were likely to find problems in regulating their behaviour and emotions at the age of 24 months, leading to disrupting emotions and behaviours, such as temper tantrums. The study contributes to recent research on the role of early sleep problems in socio-emotional development.

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The research suggests that infant sleep problems may be due to a variety of mechanisms, including genetic and environmental factors. “Environmental factors, such as sleeping practices in the family, parental reactions to crying and parental stress also play an important part in a child’s sleep and socioemotional development,” Morales-Munoz added. (IANS)

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Can AI Predict Diabetes Accurately? Find it Out Here

AI to predict future diabetes cases with 94% accuracy

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AI diabetes
Researchers have revealed that with the help of artificial intelligence (AI) their trained computer model predicted the future incidence of diabetes. Pixabay

Researchers have revealed that with the help of artificial intelligence (AI) their trained computer model predicted the future incidence of diabetes with an overall accuracy of 94.9 per cent.

Artificial intelligence (AI) is the development of computer systems able to perform tasks that normally require human intelligence. Diabetes is linked to increased risks of severe health problems, including heart disease and cancer. Preventing diabetes is essential to reduce the risk of illness and death.

“Currently, we do not have sufficient methods for predicting which generally healthy individuals will develop diabetes,” said study lead author Akihiro Nomura from Kanazawa University in Japan. “Using machine learning, it could be possible to precisely identify high-risk groups of future diabetes patients better than using existing risk scores,” Nomura added.

For the findings, published in the Journal of the Endocrine Society, the researchers investigated the use of a type of artificial intelligence called machine learning in diagnosing diabetes.

AI diabetes
Artificial intelligence (AI) is the development of computer systems able to perform tasks that normally require human intelligence. Pixabay

Machine learning is a type of AI that enables computers to learn without being explicitly programmed. The research team analysed 509,153 nationwide annual health checkup records from 139,225 participants from 2008 to 2018 in the city of Kanazawa in Japan.

Among them, 65,505 participants without diabetes were included. The data included physical exams, blood and urine tests and participant questionnaires.

Patients without diabetes at the beginning of the study who underwent more than two annual health checkups during this period were included.

New cases of diabetes were recorded during patients’ checkups, the researchers said.

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The researchers identified a total of 4,696 new diabetes patients (7.2 per cent) in the study period. Their computer model predicted the future incidence of diabetes with an overall accuracy of 94.9 per cent.

According to the authors, the next plan is to perform clinical trials to assess the effectiveness of using statins to treat groups of patients identified by the machine learning model as being at high risk of developing diabetes. (IANS)