Doctors warn that blood sugar monitors are not necessary for people without diabetes and could lead to eating disorders.
The devices, made by companies such as ZOE, are part of the social media-driven personalized diet trend that allows users to monitor their nutritional levels.
The £300 program allows participants to record their food intake and wear a blood sugar monitor for two weeks to measure their blood sugar levels.
However, Professor Partha Kerr, the NHS’s national diabetes adviser, said there was no strong evidence that the device would help people without diabetes.
He warned that using the technology without a medical reason could encourage an obsession with numbers and, in the most extreme cases, “could lead to eating disorders.”
The device allows participants to wear a blood glucose monitor for two weeks to record their food intake and measure their blood sugar levels.
(Getty Images)
Meanwhile, eating disorders charity Beat told BBC News: “People with eating disorders often become obsessed with numbers as part of their illness, so we would never recommend the use of blood sugar monitors to those affected.” he said.
ZOE said in a statement: “ZOE takes a scientifically rigorous approach and is unrivaled in the industry in terms of clinical trials, robust research, and a dedicated team of scientists and nutrition experts that provide useful evidence. We aim to improve health through informed advice.”
This comes after scientists discovered a way to test whether you have diabetes by having your smartphone say just a few sentences.
The team at US-based Klick Labs has created an AI model that can identify whether a person has type 2 diabetes from 6 to 10 seconds of audio, and in tests found 89% in women and 86% in men. It was revealed that the correct answer rate was 1%.
“Our study reveals significant differences in vocalizations between individuals with type 2 diabetes and individuals without, and may change the way the medical community screens for diabetes,” said Jaycee Kaufman, a researcher at the Crick Institute. It has the potential to change.”
“Current detection methods can take a lot of time, travel, and cost. Voice technology has the potential to completely remove these barriers.”
The study involved analyzing 18,000 recordings to identify acoustic features that differentiate non-diabetic patients from diabetic patients. Using signal processing, they were able to detect subtle changes in pitch and intensity that are imperceptible to the human ear.
