Early blood sugar changes and damage around teeth

Summarised from:

Clinical attachment loss is cross-sectionally associated with elevated glucose among adults without diabetes
(Journal of Clinical Periodontology; doi: 10.1111/jcpe.13945)

Authors:

Hamdi S. Adam, Rebecca Molinsky, Bruno Bohn, Sumith Roy, Michael Rosenbaum, Bruce Paster, Melana Yuzefpolskaya, Paolo C. Colombo, Panos N. Papapanou, Moïse Desvarieux, David R. Jacobs Jr, Ryan T. Demmer

Summarised by:

Dr Jasmine Loke

Research Topic:

Why does this matter?

Blood glucose can be above the usual range before diabetes develops. Researchers wanted to know whether these early changes were linked to signs of gum damage in younger and middle-aged adults.

What was studied?

The ORIGINS study assessed 1,071 adults aged 20–55 without diagnosed diabetes. Participants had detailed gum examinations and blood tests. Researchers measured loss of support around teeth, the depth of spaces between teeth and gums, and bleeding.

What did the researchers find?

Greater loss of tooth support was associated with a higher prevalence of prediabetes and higher glucose measurements. However, simply grouping people as having moderate or severe periodontitis did not produce a clear association with prediabetes. Deeper gum pockets were linked to measures of insulin resistance, meaning the body responded less effectively to insulin. Different gum measurements therefore gave different results.

What does this mean for me?

Gum findings may contribute to research on early metabolic changes, but a dental examination alone cannot diagnose prediabetes. Nor does this study show that treating gum disease will prevent diabetes. If you are concerned about your risk, you can discuss whether a blood test is appropriate with your healthcare team. A single gum measurement is not a reliable prediction of your future glucose levels.

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.

Read the full article Back to Research

Research  |  11.02.24

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