Severe gum disease and early changes in blood glucose

Summarised from:

Periodontal infection, impaired fasting glucose and impaired glucose tolerance: results from the Continuous National Health and Nutrition Examination Survey 2009–2010
(Journal of Clinical Periodontology; doi: 10.1111/jcpe.12258)

Authors:

Nidhi Arora, Panos N. Papapanou, Michael Rosenbaum, David R. Jacobs Jr, Moïse Desvarieux, Ryan T. Demmer

Summarised by:

Dr Dominika Antoniszczak

Research Topic:

Why does this matter?

Blood glucose can become higher than normal before someone develops diabetes. Different tests capture different aspects of glucose regulation, so a link with one test does not necessarily mean a link with all of them.

What was studied?

Researchers analysed 1,165 US adults without diabetes. They examined the gums and measured glucose after fasting and two hours after a glucose drink. The second test shows how effectively the body handles a glucose load. They also accounted for factors including age, smoking and body size.

What did the researchers find?

Severe periodontitis was associated with higher odds of impaired glucose tolerance: glucose remaining above normal after the drink. The estimated odds were about 1.9 times those in the comparison group. This does not mean that each person’s probability of developing diabetes doubled. The relationship with impaired fasting glucose was weaker and not statistically clear. People with impaired glucose tolerance also had higher levels of some inflammation markers.

What does this mean for me?

The results suggest that gum health and early glucose changes may be connected, but they do not establish that gum disease causes diabetes. A gum examination cannot diagnose prediabetes, and the study did not test whether dental treatment prevents diabetes. If you are concerned about your diabetes risk, discuss appropriate testing with your healthcare team alongside looking after your gums.

What should I keep in mind?

This study provides a snapshot rather than showing what happened first. People in the comparison groups may differ in ways the researchers could not fully measure, such as other health conditions, medicines or access to care. Statistical adjustment helps, but cannot remove every difference. A relationship seen across a group is also not a forecast for one person. The findings are best viewed as a reason for further research, not proof that changing one measurement will prevent or treat another condition.

Read the full article Back to Research

Research  |  08.04.14

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