Abstract
Introduction: Reducing social inequality along with oral health inequality in Wales, is a policy objective. In this ecological study, the relationships between deprivation, dental workforce, and oral health are explored.
Methods: Twenty-two Unitary Authorities (UAs) serving the population of Wales were studied. The number of dentists was obtained from NHS Business Services as well as the 2019 population figures from StatsWales. As data for whole time
equivalent General Dental Practitioner (GDP) workforce were not available, GDP sites were used. The condition of teeth at the age of 12 years was used as a measure of oral health from the most recent epidemiological survey available. The
relationship between oral health and workforce was established using the Welsh Index of Multiple Deprivation (WIMD).
Results: Associations were observed between dental sites and population as well as between oral health and deprivation. A new composite variable called the University of South Wales Dental Index (USWDI) was introduced by combining the
number of dentists with their corresponding WIMD of the most deprived 10% of the population. Using regression modelling the USWDI demonstrated its superiority in using either the number of dentists or the WIMD most deprived 10% alone to predict decayed, missing, and filled teeth (DMFT).
Conclusion: Workforce levels have increased, and there has been a corresponding improvement in oral health over two decades. At the same time, deprived subgroups continue to experience relatively higher levels of disease. A proportion of the general dental services delivered in Wales has continued to be based on the principle of supply induced demand for care rather than oral health need. Improving oral health in a diverse population like Wales cannot be achieved by increasing dental workforce alone. It is necessary to account for levels of deprivation. USWDI as a predictor of DMFT could be a useful tool to monitor the macro delivery of oral health care for the future in Wales.
Methods: Twenty-two Unitary Authorities (UAs) serving the population of Wales were studied. The number of dentists was obtained from NHS Business Services as well as the 2019 population figures from StatsWales. As data for whole time
equivalent General Dental Practitioner (GDP) workforce were not available, GDP sites were used. The condition of teeth at the age of 12 years was used as a measure of oral health from the most recent epidemiological survey available. The
relationship between oral health and workforce was established using the Welsh Index of Multiple Deprivation (WIMD).
Results: Associations were observed between dental sites and population as well as between oral health and deprivation. A new composite variable called the University of South Wales Dental Index (USWDI) was introduced by combining the
number of dentists with their corresponding WIMD of the most deprived 10% of the population. Using regression modelling the USWDI demonstrated its superiority in using either the number of dentists or the WIMD most deprived 10% alone to predict decayed, missing, and filled teeth (DMFT).
Conclusion: Workforce levels have increased, and there has been a corresponding improvement in oral health over two decades. At the same time, deprived subgroups continue to experience relatively higher levels of disease. A proportion of the general dental services delivered in Wales has continued to be based on the principle of supply induced demand for care rather than oral health need. Improving oral health in a diverse population like Wales cannot be achieved by increasing dental workforce alone. It is necessary to account for levels of deprivation. USWDI as a predictor of DMFT could be a useful tool to monitor the macro delivery of oral health care for the future in Wales.
| Original language | English |
|---|---|
| Article number | 368 |
| Number of pages | 9 |
| Journal | Integrative Journal of Medical Sciences |
| Volume | 8 |
| Issue number | 0 |
| DOIs | |
| Publication status | Published - 15 Jan 2021 |
Keywords
- Dental Workforce
- Deprivation
- Oral Health
- Correlation
- Regression Analysis
- Prevention