Greater consumption of sugar-sweetened and artificially-sweetened soft drinks is linked to a higher incidence of all-cause mortality, researchers have warned.
“We found that higher soft drink intake was associated with a greater risk of death from any cause regardless of whether sugar-sweetened or artificially-sweetened drinks were consumed,” said study senior author Neil Murphy from International Agency for Research on Cancer in France.
“Our results for sugar-sweetened soft drinks provide further support to limit consumption and to replace them with healthier beverages, preferably water,” Murphy said.
For the study published in the JAMA Internal Medicine, nearly 452,000 men and women from 10 European countries participated.
The study found that drinking two or more glasses per day — compared with less than one glass per month — of soft drinks, sugar-sweetened soft drinks and artificially-sweetened soft drinks was associated with higher risk of death from all causes during an average follow-up of 16 years in which 41,693 deaths occurred.
According to the study, 43 per cent died from cancers, 21.8 per cent from circulatory diseases and 2.9 per cent from digestive diseases.
The findings support public health initiatives to limit soft drink consumption. (IANS)
In a first-ever study on wearable devices to improve surveillance of infectious disease, researchers in the US have achieved real-time flu prediction in five states, using resting heart rate and sleep tracking data from Fitbit users.
Resting heart rate tends to spike during infectious episodes and this is captured by wearable devices such as smartwatches and fitness trackers that track heart rate.
Influenza results in 650,000 deaths worldwide annually. And approximately 7 per cent of working adults and 20 per cent of children aged under five years get flu each year.
“Responding more quickly to influenza outbreaks can prevent further spread and infection, and we were curious to see if sensor data could improve real-time surveillance at the state level,” said study author Dr Jennifer Radin from Scripps Research Translational Institute.
The researchers reviewed de-identified data from 200,000 users who wore a Fitbit wearable device that tracks users’ activity, heart rate and sleep for at least 60 days during the study time.
From the 200,000, 47,248 users from California, Texas, New York, Illinois and Pennsylvania wore a Fitbit device consistently during the study period, resulting in a total of 13,342,651 daily measurements evaluated.
The average user was 43 years old and 60 per cent were female.
De-identified data from the users retrospectively identified weeks with elevated resting heart rate and changes to routine sleep, said the research published in The Lancet Digital Health journal.
“In the future as these devices improve, and with access to 24/7 real-time data, it may be possible to identify rates of influenza on a daily instead of weekly basis,” said Radin.
This data was compared to weekly estimates for influenza-like illness rates reported by the U.S. Centers for Disease Control (CDC).
This is the first time heart rate trackers and sleep data have been used to predict flu, or any infectious disease, in real-time.
With greater volumes of data it may be possible to apply the method to more geographically refined areas, such as county or city-level.
The authors identify several limitations in their study.
Weekly resting heart rate averages may include days when an individual is both sick and not sick, and this may result in underestimation of illness by lowering the weekly averages.
Other factors may also increase resting heart rate, including stress or other infections.