Application of geographic information systems and simulation modelling to dental public health: Where next?

Spatial-temporal distribution of maxillofacial injuries resulting from intimate partner violence against women

BACKGROUND/AIM

Maxillofacial trauma resulting from intimate partner violence (IPV) represents an important oral health problem. In this sense, the aim of this study was to investigate the spatial-temporal distribution of maxillofacial trauma resulting from IPV against women, using a geostatistical approach.

MATERIALS AND METHODS

An ecological study was carried out including the analysis of confirmed IPV cases against women treated at a Center for Forensic Medicine and Dentistry over a four-year observation period, as well as the evaluation of population data from the victims' places of residence extracted from the last demographic census of the Brazilian Institute of Geography and Statistics. Statistical analysis included: (i) finite mixture modeling to establish incidence trajectory patterns; (ii) Getis-Ord indicator (Gi*) for spatial autocorrelation; (iii) spatial regression analysis (p < .05).

RESULTS

Two distinct trajectory patterns (TP1 and TP2) related to IPV incidence were identified using finite mixture modeling, suggesting spatial-temporal disparities at the regional level. In TP1, it was observed that IPV incidence was relatively low and remained stable over time, covering almost two-thirds (62.0%) of investigated spatial units. TP2 was characterized by higher IPV incidence with a tendency to increase in the last year, including more than one-third of neighborhoods (38.0%). Autocorrelation analysis showed a predominance of hot areas (hotspots) in the Eastern zone (p < .05) and in the Western zone (p < .05); and cold areas (coldspots) in the Northern zone (p < .05). In addition, statistically significant association was observed among neighborhoods with higher percentage of households with family householder without income and higher incidence of maxillofacial trauma resulting from IPV against women (β = 5.305; SE = 1.741; p = .002).

CONCLUSIONS

The findings indicate an association between higher IPV incidence against women, maxillofacial trauma, and socio-spatial vulnerability.

Socio-demographic and familial factors associated with hospital admissions and repeat admission for dental caries in early childhood: A population-based study

OBJECTIVES

Dental caries remains a complex childhood condition often requiring preventable hospital admissions. There are limited population-based epidemiological studies that use large and linked data sets to quantify the clinical, socio-demographic and familial risk factors related to hospital admissions for dental caries. The aim of this study was to describe and quantify the rates, socio-demographic, clinical characteristics and familial factors including repeat admissions associated with young children admitted to hospital for dental caries.

METHODS

This cohort study (n = 33,438) used longitudinally linked hospital admission data among all children aged <six years in NSW, Australia. Socio-demographic and admission characteristics of children and those with one versus two or more admissions for dental caries were compared. Familial risk factors were analysed for a restricted cohort of families with two or more children (n = 18,174) using multivariable logistic regression to assess the familial factors associated with multiple hospital admissions for dental caries adjusting for other socio-demographic characteristics.

RESULTS

There were 33,438 children aged <six years who had 34,446 hospital admissions for dental caries between 2001 and 2014. The annual rate of 4.3 per 1000 children remained unchanged over the period. Most admissions required general anaesthesia (96%), and 8.4% of children had repeat admissions. Children living in disadvantaged or in regional and rural areas attending public hospitals were more likely to have dental extractions during the admission. Children from the same family had a 2.7-fold increased odds of admission if the first child admitted was less than three years of age (adjusted odd ratio 2.69; 95% CI: 2.36-3.07), a 1.5 fold increase for socioeconomic disadvantage (aOR 1.45; 1.19 - 1.77) and a 1.9 fold increase of admission if the family had 4 or more children (aOR1.88; 1.47 - 2.42).

CONCLUSIONS

Findings highlight socio-demographic inequities associated with hospital admission for dental caries. The provision of targeted dental care programs for 'at-risk' families should address these inequalities and presents an opportunity to reduce dental caries related hospitalizations.

Regional Variation in Restorative Treatment Need among Finnish Young People

Aim

To evaluate the regional variation in restorative treatment need among Finnish young people based on the socioeconomic factors.

Materials and Methods

This cross-sectional study was conducted in 20 garrisons of the Finnish Defence Forces in January and July 2011. The study population comprised 13,819 Finnish conscripts born in the beginning of 1990s, including females. A computer-based survey was done together with clinical oral examination to gather background information, e.g., educational status. Furthermore, average annual income of the conscript's residence municipality was achieved from the Statistics of Finland. The zip code of the place of residence of each conscript was later extracted from the Mildoc^® system. Georeferenced place of residence and income status were merged as information on provinces' level in a dataset. The association between the outcome variable and explanatory variables was determined by using the generalized linear mixed model, and geomaps were constructed.

Results

Mean D value was 1.41 ranging from 0.89 (Kymenlaakso) to 2.33 (Kainuu). Higher education and high-income level were protective factors for restorative treatment need. Restorative treatment need was also low in those areas with high (OR: 0.70, 95% CI: 0.56–0.87) and medium (OR: 0.79, 95% CI: 0.70–0.89) yearly income compared to low yearly income. The high odds for the need of restorative treatment were discovered in Northern Ostrobothnia (OR: 2.26, 95% CI: 1.53–3.33) followed by Central Ostrobothnia (OR: 2.08, 95% CI: 1.17–3.70), Uusimaa (OR: 1.55, 95% CI: 1.16–2.08), and Central Finland (OR: 1.54, 95% CI: 1.10–2.16) compared to Varsinais-Suomi.

Conclusion

In conclusion, there is a significant regional variation in restorative treatment need among Finnish young people in their twenties based on the socioeconomic factors.

Distribution of Australian dental practices in relation to the ageing population

OBJECTIVE

The purpose of this study was to analyse and map the distribution of the ageing population, by sociodemographic profiling, in private and public dental practices in Australia.

BACKGROUND

The rapid increase in the aged population in Australia requires a comprehensive approach to ensure accessibility to geriatric dental services. However, the availability of dental services for the older people requires further investigation of the demographic distribution of need.

MATERIALS AND METHODS

Dental practices were located and mapped against the ageing population data. The address for each dental practice in Australia was compiled from online access sources. Australian socioeconomic data were integrated with dental practices, clinic locations and older populations using Geographic Information System (GIS) technology.

RESULTS

There was an uneven distribution of dental practices across Australia's States and Territories (NT and ACT). Tasmania had the highest ratio of private practices to the older population (1:1000) and the highest percentages of this ageing cohort (32%, 61%) that lived more than 5 km from private and public dental practices respectively. Higher percentages of dental practices were located in areas of lower socioeconomic status in Tasmania, Queensland and South Australia (47%, 42% and 38%) respectively, however, these areas were associated with higher ageing population densities.

CONCLUSION

There is a geographic maldistribution of dental practices in relation to the spatial distribution of Australia's older population, with the inequity most pronounced in the most disadvantaged areas. This inequality requires a National approach to match dental services to the population that they serve.

Neighborhood Contexts and Oral Health Outcomes in a Pediatric Population: An Exploratory Study

Aims: This study aimed to explore the impacts of neighborhood-level socioeconomic contexts on the therapeutic and preventative dental quality outcome of children under 16 years. Materials and Methods: Anonymized billing data of 842 patients reporting to a university children’s dental over three years (March 2017–2020) met the inclusion criteria. Their access to care (OEV-CH-A), topical fluoride application (TFL-CH-A) and dental treatment burden (TRT-CH-A) were determined by dental quality alliance (DQA) criteria. The three oral health variables were aggregated at the neighborhood level and analyzed with Canadian census data. Their partial postal code (FSA) was chosen as a neighborhood spatial unit and maps were created to visualize neighborhood-level differences. Results: The individual-level regression models showed significant negative associations between OEV-CH-A (p = 0.027) and TFL-CH-A (p = 0.001) and the cost of dental care. While there was no significant association between neighborhood-level sociodemographic variables and OEV-CH-A, TRT-CH-A showed a significant negative association at the neighborhood level with median household income and significant positive association with percentage of non-official first language (English or French) speakers. Conclusion: Initial analysis suggests differences exist in dental outcomes according to neighborhood-level sociodemographic variables, even when access to dental care is similar.

Dental specialist workforce and distribution in the United Kingdom: a specialist map

Objectives To illustrate, identify and assess a contemporary model of the geographic distribution of specialist dentists in relation to population age groups and rurality.Methods All UK dental specialists registered with the General Dental Council were extracted and paired with publicly available locations of work. Geographic information system tools were used to map specialist locations against population and rural-urban classifications of England, Wales, Scotland and Northern Ireland. The latest 2019 population estimates and health board areas were superimposed to create a specialist map. All other data were collected at the smallest geographic statistical areas and corresponding population data from the latest census.Results A total of 4,439 specialist titles were held by 3,041 individuals, linked to 3,459 unique locations of work. Specialist locations were mapped against 135 Clinical Commissioning Groups (CCGs) of England, seven Local Health Boards of Wales, 14 Health Boards of Scotland and five Health and Social Care Trusts of Northern Ireland. NHS Central London CCG had the highest specialist dentists per 100,000 people at 118.9; paediatric dentists per 20,000 children at 6.4; orthodontic dentists per 20,000 schoolchildren at 23.2; oral surgery dentists at 4.8 per 20,000 adults; and prosthodontic dentists at 7.2 per 20,000 adults. Orthodontics and oral surgery had the highest specialist-to-population ratios at 1:45,545 and 1:77,510, compared to oral and maxillofacial radiology and oral microbiology with the lowest ratios of 1:2,178,316 and 1:9,024,452, respectively. In England, Wales, Scotland and Northern Ireland, there were 79.5% (n = 42,140,039), 55.6% (n = 1,703,248), 46.9% (n = 2,481,996) and 42.9% (n = 776,295) of the respective populations that lived within 2.5 km of a specialist location. There were significant disparities in rural proximity to specialist locations across all nations. In Scotland, 40.8% of the rural population lived outside 10 km of a specialist location.Conclusions Stark inequalities exist in the geographic distribution of UK specialist dentists and high disparities were found in accessing a specialist, especially for vulnerable populations.

Estimating Health over Space and Time: A Review of Spatial Microsimulation Applied to Public Health

There is an ongoing demand for data on population health, for reasons of resource allocation, future planning and crucially to address inequalities in health between people and between populations. Although there are regular sources of data at coarse spatial scales, such as countries or large sub-national units such as states, there is often a lack of good quality health data at the local level. One method to develop reliable estimates of population health outcomes is spatial microsimulation, an approach that has its roots in economic studies. Here, we share a review of this method for estimating health in populations, explaining the different approaches available and examples where the method is applied successfully for creating both static and dynamic populations. Recent notable advances in the method that allow uncertainty to be represented are highlighted, along with the evolving approaches to validation that are an ongoing challenge in small-area estimation. The summary serves as a primer for academics new to the area of research as well as an overview for non-academic researchers who consider using these models for policy evaluations.

Public transport access to NHS dental care in Great Britain

Objective Access to transport is a common barrier to oral health. Greater dependence on public transport has shown delayed oral healthcare, lack of usual source of care and greater unmet health needs. This study examined the spatial accessibility of the population of Great Britain to public transport in providing access to oral healthcare.Methods A total of 8,791 dental practices in Great Britain were identified and geocoded. There were 10,444 rail, metro and light rail stops and 348,961 bus and tram stops. Geographic information systems were utilised to integrate the dental practice locations and public transport points to respective census tracts of each nation containing population data, deprivation measures, and classification of rural and urban areas.Results Almost all dental clinics in Great Britain were located within 400 m of bus and tram stops or 800 m of a rail, metro or light rail stop. Similarly, in Scotland and England, 92% lived within any public transport (within 400m of bus and tram stops or 800m of a rail, metro or light rail stop), and in Wales, 84.2% lived within any public transport stop. However, only 75.1%, 79.6% and 60.4% of the population of Scotland, England and Wales had access to a high-frequency bus stop, respectively. In Scotland, England and Wales, 40.7%, 33.7% and 38.3% of rural residents did not have access to any public transport and only 4.9%, 7.5% and 14.6% of the rural residents had access to an optimal bus stop, respectively. In Wales, 19.5% of older adults do not have access to a bus stop.Conclusion Some transport-disadvantaged groups do not have adequate access to public transport services. There is a compelling need to address public transport integration with oral health facilities to ensure equality in accessing integral services.

Geographic Information Systems in Spatial Epidemiology: Unveiling New Horizons in Dental Public Health

Objectives:

Research on the role of environment and place in various aspects of dental public health using geographic information systems (GIS) is escalating rapidly. Yet, the understanding of GIS and the analytical tools that it offers are still vaguely understood. This narrative review therefore draws from the utilization of GIS in the dental public health research.

Materials and Methods:

Electronic databases such as Google Scholar, PUBMED, and Scopus were searched using terms “spatial epidemiology,” “GIS,” “geographic information systems,” “health geography,” “environment public health tracking,” “spatial distribution,” “disease mapping,” “geographic correlation studies,” “cartography,” “big data,” and “disease clustering” through December 2019.

Results:

This review builds upon the prospects of GIS application in various aspects of dental public health. Studies were classified as: (1) GIS for mapping of disease, population at risk, and risk factors; (2) GIS in geographic correlation studies; (3) GIS for gauging healthcare accessibility and spatial distribution of healthcare providers. We also identified the commonly used GIS analytical techniques in oral epidemiology.

Conclusions:

We anticipate that this review will spur advancement in the utilization of spatial analytical techniques and GIS in the dental public health research.