Thursday April 2, 2020

Here’s Why Older Obese Workers Are at a High Risk of Losing Jobs

After analysing the data, the research has shown that women with obesity or severe obesity had greater odds of prolonged sickness absence compared with women of normal weight

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Obese
Although obesity is becoming more prevalent in children and adolescents, the highest prevalence is seen amongst men and women in their fifties, sixties and seventies, they said. Pixabay

Older workers with obesity are at a higher risk of prolonged sickness absence or losing their jobs for health reasons than those of normal weight, say researchers.

The study, published in the International Journal of Environmental Research and Public Health, also revealed that women were affected significantly more than men.

“Our study demonstrates the link between obesity and health problems that affect people’s ability to work, particularly in older female workers,” said study lead author Karen Walker, Professor at the University of Southampton in the UK.

“As a result, the burden of obesity in an aging population can be expected to hinder attempts to encourage work to older ages,” Walker added.

Obesity is a major and growing public health problem, with future projections estimating that there will be more than one billion people affected globally by 2030.

According to the researchers, being obese or overweight is a major risk factor for non-communicable diseases including diabetes; cardiovascular diseases; musculoskeletal disorders and common mental health conditions.

Although obesity is becoming more prevalent in children and adolescents, the highest prevalence is seen amongst men and women in their fifties, sixties and seventies, they said.

For the findings, the research team studied the association between body mass index (BMI) and prolonged sickness absence, cutting down at work and health-related job loss among 2,299 men and 2,425 women aged between 50 and 64 years.

The participants in the study reported their height and weight at the start of the study, and then provided information about their ability to work after 12 and 24 months as part of Medical Research Council’s Health and Employment after Fifty (HEAF) Study.

After analysing the data, the research has shown that women with obesity or severe obesity had greater odds of prolonged sickness absence compared with women of normal weight.

Obese
Older workers with obesity are at a higher risk of prolonged sickness absence or losing their jobs for health reasons than those of normal weight, say researchers. Pixabay

Those with severe obesity were also the most likely to cut down, avoid, or change what they did at work because of health problems and were almost three times as likely to lose their job because of their health.

Among the men taking part in the survey, there was a slightly increased risk of prolonged sickness absence amongst those with obesity but no evidence of an association between above-average BMI and health-related job loss, the study said.

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“These results should give employers an incentive to introduce measures that can help their employees maintain a healthy weight,” Walker said. (IANS)

 

Next Story

Can AI Predict Diabetes Accurately? Find it Out Here

AI to predict future diabetes cases with 94% accuracy

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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)