Abstract:

Objectives: The aim of this project is to build a model for predicting oral health services utilization based on supply and demands in Saudi Arabian provinces. Methods: In order to study oral health care utilization the following variables were used as indicators: number of dental visits, number of dentists, dental treatment needs, caries prevalence, and province population. Health care parameters and population data were obtained from Saudi Ministry of Health (MOH) statistical reports and Saudi Central Department of Statistics & Information (CDSI), respectively. Spatial data was obtained from DIVA-GIS and used to display spatial differences. A multiple linear regression model was built to predict the oral health services utilization using the number of visits as dependent variable (i.e. a proxy for oral health services utilization). All other variables served as independent variables. Results: The model revealed that province population (p-value= 0.001) and number of dentists (p-value= 0.028) have the greatest influence on oral health services utilization. Treatment need illustrated borderline statistically signification relationship to oral health services utilization (p-value=0.065). Although caries prevalence has a great impact on the model, its association with service utilization was not statistically significant. Conclusion: This project suggests that province population and number of dentists working in the province can predict oral health services utilization in Saudi Arabia. A better estimation could be built when data for unmet oral health needs and detailed regional data (such as sub-province, or city level data) are available.

Introduction:Oral behavior, oral health awareness, perceived dental needs, dental caries level and SES influence frequency of dental visits and dental demands (1, 2, 3, 4). There is a lack of region-level determinants for dental treatment deprivation, except for area demographics, based on current WHO index (5).The Saudi Ministry of Health (MOH) statistical report of 2011 revealed an average population to dentist ratio of around 10,000 people/dentist. Nationwide dental caries prevalence among schoolchildren found that average caries prevalence in Saudi Arabian provinces is about 83.9% with 60% unmet dental treatments needs (6).

Factors Influencing Prediction of Oral Health Services Utilization in Saudi Arabia Yaser Alsahafi BDS, MSD1, PhD Candidate2

1Preventive Dental Sciences, Taibah University College of Dentistry2Environmental and Global Health, University of Florida College of Public Health and Health Professions

References:1. Lopez, R., Baelum, V., 2007. ‘Factors associated with dental attendance among adolescents in Santiago, Chile.’, BioMed Central Oral Health,

Vol 7, no.4, pp. 1-7.2. Muirhead, V.E., Quiñonez, C., Figueiredo, R., Locker, D., 2009, ‘Predictors of dental care utilization among working poor Canadians’,

Community Dental Oral Epidemiology. Vol. 37, no. 3, pp.199-208.3. Correa, M.B., Peres, M.A., Peres, K.G., Horta, B.L., Gigante, D.P., Demarco, F.F., 2010, ‘Life-course Determinants of Need for Dental

Prostheses at Age 24’, Journal of Dental Research, Vol 89, no. 7, pp. 733-738.4. Zubiene, J., Milciuviene, S., Klumbiene, J., 2009, ‘Evaluation of dental care and the prevalence of tooth decay among middle-aged and elderly

population of Kaunas city.’, Stomatologija. , Vol. 11, no. 2, pp.42-7.5. Aleksejuniene, J., Brukiene, V., 2008, ‘Do socio-economic disparities in dental treatment needs exist in Lithuanian adolescents?’,

Stomatologija, Vol. 10, no.3, pp.101-6.6. Aldosari A. National Campaign to Prevent Dental Caries [Internet]. Riyadh (KSA): NCPDC; 2008. [cited 2013 March 20]. Available from:

http://www.ncpdc.org.sa/statisticcaries2. php 7. Central Department of Statistics and Information [Internet]. Riyadh (KSA): Central Department of Statistics and Information; 2010. [cited 2013

November 23]. Available from: http://www.cdsi.gov.sa/english/index.php?option=com_conten t&view=article&id=84&Itemid=172.

Materials and Methods:For province-level demand, province caries prevalence and dental treatment need were obtained from the National Campaign to Prevent Dental Caries (NCPDC) in Saudi Arabia. Province population size was retrieved from the Saudi Ministry of Economy and Planning (7). For province-level supply, number of dentists and dental facilities were obtained from MOH. The number of dental visits in MOH was used as a proxy for oral healthcare utilization. Given that all the variables involved are continuous variables multiple linear regression (MLR) was performed for evaluating the prediction (SPSS, 21.0). The MLR was built to fit (satisfy) the following equation, using SPSS:Y= b0 + b1 * (province population) + b2 * (caries prevalence) + b3 * (dental need) + b4 * (no. of dentists) + ε.

Variable Mean Median Std deviation Min - Max

Caries Prevalence 82.07% 81.9% 5.8% 71.4 – 8.94%

No. of dental Visits 42926 21604 46488.7 6882 - 150335

No. Dentists 201.09 103 173.4 54 - 577

Dental treatments need 58.77% 62.6% 10.3% 38.4 – 70. 6%

Population over 10 yr old 1551650.27 735682 1787613.3 294896 - 6097077

Population per dentist 7494.8 7266.7 2510.9 3476.2 - 10723.37

Table1: Descriptive of oral health parameters

Model B Std. Error t Sig.95% Confidence Interval

Lower Bound Upper Bound

(Constant) 38629.91 37650.25 1.03 .344 -53496.9 130756.8

Population over 10 yr old

.100 .016 6.18 .001 .06 .14

No. of Dentists -232.63 81.06 -2.87 .028 - 431.0 -34.3

Caries Prev. -97124.14 62405.05 -1.56 .171 -249823.8 55575.5

Treatment needs 76727.97 33991.8 2.26 .065 -6447.1 159902.9

Table2: Parameters for best fit prediction model

Objective:

The aim of this study is to determine the factors influencing the prediction oral health utilization in Saudi Arabia.

Results:

The model satisfies the following equation:No. of dental visits= 38629.91 + 0.1*(pop.>10) - 232.67*(no of Dentists) - 97124.14*(Caries Prev.)+76727.97*(treatment needs)

Conclusion:Predicting oral health services utilization is helpful in planning for workforce and facilities to meet demands. In Saudi Arabia, province population is a major predictor for utilization. Additionally, the availability of dentists seems to be a good predictor of whether services are utilized. Better prediction could be implemented if further information were available.

Abstract # 93