Reducing social inequality has been a priority for policy makers [16, 17, 30, 31]. With a stable population of 3.15 million and availability of the data covering different deprivation levels, Wales was an appropriate study site. Morgensen (1982) suggested that ecologic analysis was preferred for evaluating the effectiveness of proposed interventions [32]. Nadanovsky and Sheiham (1995) concluded that personal health services i.e. services provided by health carers were unimportant in explaining the differences in changes of 12 year old caries levels in the 1970s and 80s, suggesting that further ecologic investigation of workforce issues seems appropriate [33]. Area based measures have been promoted by Locker (1993) for research to identify where deprived groups with relatively poor health live [34]. The 22 LHBs show different demographic profiles, some rural and others urban.
There have been improvements in the oral health of 12-year-olds in Wales over the last 20 years. However, there continues to be a visible social inequality as demonstrated by the oral health statistics for the most and least deprived UAs in Wales, Blaenau Gwent and Monmouth, both in the same LHB. The Welsh DMFT in 2000/01 was 1.09 and at 2016/17 was 0.61. The number of 12-year-olds experiencing dental caries has reduced from 45.1% in 2000/1 to 29.6% in 2016/17 [26]. The mean DMFT for the 29.6% with caries was 2.05. This skewed distribution of caries in communities was recognised by Bratthall (2000), using the DMFT for 12-year-olds in eight countries [35].
For all eight countries the DMFT was below three. However, closer analysis showed that two thirds of the countries’ populations had a DMFT below 1. The DMFT for the other third of the countries’ populations was higher than 3, with the exception of Sweden at 2.82. Bratthall described the DMFT for the third experiencing higher levels of disease as the Significant Caries Index (SiC). To this end, the SiC for Wales was 3.39 in 2004, with six of the 22 UAs having a SiC score less than 3 [26], today all the UAs within LHBs have a SiC score less than 3. The use of the DMFT for those experiencing caries has replaced the need for the SiC.
The percentage experiencing disease showed moderate correlations with the WIMD -0.636, WIMD 50% 0.545 and GDP sites -0.464. The correlation between deprivation indexes and percentage of 12-year-olds experiencing diseased is not a new finding as it shows the inequality in oral health in Wales. Interestingly the negative correlation between GDP sites and percentage experiencing disease suggests the greater the number of dental sites the more people are diseased. This suggests that a proportion of dental workforce is providing oral health care that is not totally based on oral health need. Rehan (2020), in the context of demand for dental workforce, when asked if more dentists were needed stated “if they want to locate in saturated markets or middle- to upper-income urban areas and want a significant self-pay patient base, I would say no.” [36]
The dental workforce in 2019 was 0.579 per thousand population, this compares with 0.349 in 2004 [24]. The dental workforce sites correlate with population levels across the country as reflected by a strong correlation of 0.959 and 0.654 with GDP and CDS sites respectively. Olivia et al (2020) highlight the fact that NHS dental practices in Wales were not socio-economically distributed, suggesting an equitable spatial availability of services from the viewpoint of the positioning of practices [37]. The fact that CDS sites show a weaker correlation may be explained by the fact that historically they may have been positioned to reflect the greater need within the populations they serve. The moderate correlation of 0.447 between the ratio of dentist per 1000 population and the WIMD most deprived 10% supports the work of Olivia et al (2020) and may reflect the decision-making of LHBs with regard to the positioning of dental sites. The negative correlation between population size and the percentage experiencing disease -0.450 suggests that the smaller the population the greater number of 12-year-olds experience disease. This finding may be explained by the cultural norms within the smaller, usually deprived, populations [38, 39]. The negative correlation was also seen for the % diseased and GDP sites -0.464. Consideration should also be given to the fact that the position of a dental site does not necessarily indicate that the patient profile of the dental site reflects the area deprivation profile as demonstrated by Richards et al (2005) [40].
As a measure of deprivation, the associations between the WIMD rank average, WIMD most deprived 10%, WIMD most deprived 50% for each UA show strong correlations between each measure at WIMD / WIMD 10% -0.689, WIMD / WIMD 50% -0.967, WIMD 10% / WIMD 50% 0.545. This would be expected as they are all measuring the same concept, deprivation. However, not all measures showed associations with expected variables suggesting that some are more sensitive than others in different situations. It would be expected that the most deprived 10% would be associated with DMFT and %diseased but no associations were observed here. There was a significant correlation between WIMD rank average and DMFT of 0.653.
Tickle (2002) has questioned the 80:20 distribution of disease in the community [41]. Using 5-year-old data, he suggested that about half of the population disease was confined to a minority of the population and that the disease active high risk children were more commonly found in underprivileged area types; they did not live exclusively in small number of deprived areas. This suggests that a change of emphasis towards prevention is required in general dental practice in line with Department of Health directives [42]. Indeed, the Welsh approach to the development of General Dental Services in Wales focuses on prevention as a cornerstone of care [43]. The Welsh response to the Covid-19 pandemic has highlighted this focus on prevention and service delivery [44]. This response will have the potential to improve access and continuing care to those patients with the greatest need while still providing care for low risk patients at appropriate levels. Watt (2020) identifies the need to reform service delivery in the context of Covid-19 in accordance with the above [45]. Many workers support change within the dental profession while identifying problematic issues for facilitating change [46, 47, 48, 49].
NHS Business Services statistics show that the six-monthly check-up continues to be a significant patient attendance pattern in general dental practice in England and Wales [43]. It has long been reported that this attendance pattern is of questionable value in terms of health gain. The National Institute for Clinical Excellence (2004) has published its guidelines for routine dental monitoring [50]. Similarly, other decision-making processes currently observed in action in general dental practice are questioned in the National Audit Office report (2004) including routine scaling and polishing [19]. The application of minimally invasive procedures (MID) in the presence of a continuing care contract that is risk based is appropriate [51, 52]. The application of MID is not totally practiced both in the UK and internationally [51, 52, 53]. It seems that since the new contract of 2006, little leverage has been placed on dentists by the LHBs to change service delivery to incorporate appropriate dental check-up patterns. Furthermore, the monitoring of service delivery by LHBs has had a focus on equality for dental practitioners rather than equity for patients, however, the response to the Covid-19 crisis has made NHS contracts conditional on risk based continuing care [44]. Richards et al (2020) highlight the fact that contract monitoring has to date, penalised general dental practitioners who wish to operate equitable practice towards their patients [22].
The USWDI showed itself to be a good predictor of health and as such may be of value to service monitors to assess the overall outcome of services. In 2004 similar findings were established using the Glamorgan Dental Index where the investigation of the number of dentists per 1000 population per corresponding WIMD score was undertaken [24].