تجاوز إلى المحتوى الرئيسي

Unmasking caries risk: a multi-regional study in Saudi Arabia

Author name : Azhar Iqbal Mohammed Iqbal
Publication Date : 2024-08-02
Journal Name : BMC Oral Health

Abstract

bstract
Background Dental caries are common and troublesome and may affect individuals’ health conditions. It is crucial
to comprehend the caries experience for prevention, management, and enhancing oral health. Techniques such as
CAMBRA can help assess an individual’s risk factors for caries lesions. This study aims to assess the caries risk in five
distinct regions of Saudi Arabia, utilizing the CAMBRA methodology.
Methods This multiregional cross-sectional study was conducted at university dental clinics across the five regions
of Saudi Arabia, using a Caries Management by Risk Assessment (CAMBRA) tool. This study used binary logistic
regression analysis, the Pearson Chi-square test, and descriptive analysis as statistical methods.
Results A total of 551 respondents participated in the study, with 59.7% being male and 40.3% being female. The
age group with the highest proportion was 20–29, making up 31.6% of the participants. All participants exhibited
at least one caries lesion (100%), with white spots (66.4%) and enamel lesions (56.1%) being the most prevalent. The
moderate-risk category encompassed the largest proportion of participants, accounting for 60% of the total. High
caries risk had a significant association with age group (P < 0.001), education (P < 0.001), profession (P < 0.001), and
socio-economic status (P < 0.001). Furthermore, only age and socio-economic status showed a significant relationship
with high caries risk in the multiple logistic regression.
Conclusion The CAMBRA tool indicates a high prevalence of moderate risk across the five regions of Saudi Arabia,
identifying age and socio-economic status as significant predictors of caries risk.

Keywords

Caries, Management, Prevention, Risk

Publication Link

https://doi.org/10.1186/s12903-024-04665-0

Block_researches_list_suggestions

Suggestions to read

HIDS-IoMT: A Deep Learning-Based Intelligent Intrusion Detection System for the Internet of Medical Things
Ahlem . Harchy Ep Berguiga
Generalized first approximation Matsumoto metric
AMR SOLIMAN MAHMOUD HASSAN
Structure–Performance Relationship of Novel Azo-Salicylaldehyde Disperse Dyes: Dyeing Optimization and Theoretical Insights
EBTSAM KHALEFAH H ALENEZY
“Synthesis and Characterization of SnO₂/α-Fe₂O₃, In₂O₃/α-Fe₂O₃, and ZnO/α-Fe₂O₃ Thin Films: Photocatalytic and Antibacterial Applications”
Asma Arfaoui
تواصل معنا