New Delhi, Sep 17 (IANS): A team of UK researchers has now linked excessive weight, and not high blood sugar, with an increased risk of long Covid.

Early in the pandemic, research identified diabetes and obesity as risk factors for becoming severely ill with Covid-19.

"We know that many people living with type 2 diabetes are also carrying excess weight. Our early findings support the idea that obesity-related mechanisms may be responsible for the excess risks of Covid-19 associated with diabetes, rather than high blood sugar per se," said Dr Anika Knuppel from University College London.

The findings, to be presented at European Association for the Study of Diabetes (EASD) annual meeting in Stockholm, Sweden (September 19-23), were announced after a meta-analysis of over 30,000 UK adults from nine large prospective cohort studies.

Previous research showed that people with diabetes and obesity are more likely to become severely ill and die if they catch Covid-19, but are no more likely to contract it.

However, the underlying mechanisms, and their role in prolonged post-Covid-19 symptoms (long Covid), remained unclear.

To find out more, researchers looked for associations between a range of clinical characteristics measured before the pandemic -- HbA1c (average blood sugar level), self-reported or medication-based diabetes, body mass index (BMI) and waist-to-hip ratio (WHR) -- and self-reported Covid infection and long Covid.

Long Covid was defined as symptoms that went on or affected functioning for longer than four weeks post-infection and was compared to those reporting symptoms for less than four weeks.

"Our early findings suggest a link of adiposity with Covid-19 infection and long Covid even after taking into account socio-demographic factors and smoking. We need to further explore what makes overweight and obesity at risk of worse outcomes and how this relates to severe casesa, Knuppel explained.

The authors acknowledged that the study was observational and cannot prove that higher BMI increases the risk of Covid-19 infection, and they cannot rule out the possibility that other factors (underlying conditions) or missing data may have affected the results.