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Br Dent J 2016;221: 65–69 http://dx.doi.org/10.1038/sj.bdj.2016.525

Credit: © kotoffei/[iStock/Getty Images Plus

One suspects that there is has been an intuitive connection between systemic health and oral health since mankind first had time to think about wellbeing rather than merely survival. It does make sense. What has possibly made us deviate from this link has been the tendency to divorce the mouth from the rest of the body by making dentistry a separate entity and specialism.

This study set out to try and quantify the relationship by asking the question, 'Are lower than average oral health scores observed for those patients who report problems with general health and high risk lifestyle factors?' Using an impressively large sample of over 37,000 patients who were both examined by a dentist and asked to complete a self-assessment questionnaire, the authors found that patient-reported general health and risk factors were indeed negatively associated with an overall composite oral health score outcome.

The results are of importance on various levels. The very fact that patients were asked questions on risk factors such as diabetes status, tobacco use and alcohol consumption in association with a dental examination provided an important prompt for them to wonder why. Is there a connection? What is the connection? This, in addition to raising self-awareness of their personal health and consumption patterns.

Such data collection may also serve a purpose in modelling future questionnaires or instruments that allow people to have a more accurate self-assessment prior to, or in association with, oral care, prevention and treatment. Similarly, from a professional viewpoint, the preliminary information from that which is essentially a screening exercise, could form an early warning system to alert clinicians to propensities towards oral ill health as well as giving important information to allow for meaningful dialogue between dentist, dental team member and patient.

Listen to Stephen Hancocks' summary of this research via the BDJ Youtube Channel http://bit.ly/BDJYouTube

Author Q&A with Praveen Sharma University of Birmingham chool of Dentistry

How important are big datasets to dentistry?

Big data has become vitally important in dentistry as well as medicine for several reasons:

Firstly, the larger the dataset the greater the power and validity of the findings and the less likely they have arisen due to chance; secondly, larger studies tend to be enriched with greater diversity of human volunteers (eg, behaviours, ethnicity) and as a result, their findings are more generalisable; thirdly, with large datasets, pre-planned analyses of subgroups within the dataset and adjusting for confounders are more valid.

What were the challenges in carrying out this research?

There are many challenges from this type of research. Cross-sectional analyses do not allow the determination of causality, only associations between an exposure (eg periodontal disease) and an outcome (eg having poor general health). This type of research allows us to comment on an association between the two: as periodontal health worsens, patients are more likely to report worse general health but does NOT allow us to say that worsening periodontal health causes worse general health. This is because there might be other factors, such as age, smoking etc, that explain the association between exposure and outcome. These are called 'confounding factors'. Statistically adjusting for confounding factors allows us to, in part, account for their presence but these cannot be ruled out because firstly, not all confounders are measured or measured accurately, and secondly, the relationship between the confounder and exposure/outcome is often complex.

What would you like to do next?

The exciting thing about DEPPA (Denplan's pateint assessment tool) is that it is ongoing and embedded within those practices. Indeed, 70,000 assessments have already been created by 630 dentists. Patients are now starting to have repeat assessments done and this creates a rich source of data from 'real world practice' about what characteristics predict oral health outcomes, which treatments are most effective, and what the risk and disease profiles are of individual practices – something critically important for service design and health economic planning.