تجاوز إلى المحتوى الرئيسي

Sociobehavioural Factors Associated With Child Oral Health During COVID-19

Author name : Gudipaneni Ravi Kumar
Publication Date : 2023-03-01
Journal Name : International Dental Journal

Abstract

Objectives
The aim of this study was to identify the sociobehavioural factors that influenced children's oral health during the COVID-19 pandemic.
Methods
The online cross-sectional study was conducted in Al Jouf Province in the northern region of Saudi Arabia. A total of 960 parents of children aged 5 to 14 years were invited by multistage stratified random sampling. Descriptive, multinomial, and multiple logistic regression analyses were performed to estimate odds ratios and determine the relationship between independent and dependent variables. P < .05 was considered statistically significant.
Results
Of the 960 participants, 693 (72.1%) reported that their child had 1 or more untreated dental decay. The children of uneducated parents were 1.6-fold more likely to have 1 or more untreated dental decay (adjusted odds ratio [AOR], 1.66; 95% CI, 0.74–3.73; P < .001). The children of unemployed parents were 4.3-fold more likely to have a financial burden for a child dental visit (AOR, 4.34; 95% CI, 2.73–6.89; P < .001). Parents from a rural area were 26.3-fold more likely to have spent a lag period of over 2 years since their child's last dental visit (AOR, 26.34; 95% CI, 7.48–92.79; P < .001). Nursery-level children were 5.4-fold more likely to need immediate care (AOR, 5.38; 95% CI, 3.01–9.60; P < .001).
Conclusions
The present study demonstrated a very high prevalence of 1 or more untreated dental decay in our cohort. Children of rural areas, uneducated, unemployed, widow/divorced, low- and middle-income parents and nursery school children were linked to poorly predictive outcomes of child oral health during the pandemic.

Keywords

COVID-19 pandemicSelf-reported child oral healthSelf-perceived need of dental careDental visiting patternOral health care affordability

Publication Link

https://doi.org/10.1016/j.identj.2022.12.003

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