Login / Signup

Dental pain prevalence associated with caries experience in pediatric patients in a clinical sample in Mexico.

César Tadeo Hernández-MartínezSandra Isabel Jiménez-GayossoSalvador Eduardo Lucas-RincónNorma Leticia Robles-BermeoNuria Patiño MarínJuan José Villalobos RodeloCarlo Eduardo Medina-SolísGerardo Maupome
Published in: Brazilian oral research (2021)
The aim of this study was to identify if the prevalence of dental pain (past and / or present) is associated with caries experience in Mexican children, as well as to characterize factors associated with dental pain. A cross-sectional study was conducted in a consecutive sample of 309 children 2 to 12 years old who were patients at a dental school clinic in Toluca, Mexico. Data were collected from clinical records. The dependent variable had three categories: 0 = have never had dental pain, 1 = had dental pain before the appointment, and 2 = current dental pain. Non-parametric statistical tests were used in the analysis. A multivariate multinomial logistic regression model was generated in Stata 11.0. Average age was 5.71 ± 2.43 years and 50.8% were boys. The joint dmft+DMFT index was 9.11 ± 4.19. It was observed that 56.6% of children did not report having experienced dental pain, 30.7% reported having previously had dental pain, and 12.6% had pain when the clinical appointment took place. In the multivariate model, variables associated (p < .05) with previous dental pain were age (OR = 1.13); the dmft + DMFT index (OR = 1.13), having had a last dental visit for curative/emergency reasons (OR = 2.41) and prior experience of dental trauma (OR = 2.59). For current pain, only the joint dmft + DMFT index (OR = 1.10, p < 0.05) had significant associations. Almost half of the children had experienced dental pain in their lifetime. Since caries experience is a factor associated with dental pain, decreasing caries levels may ameliorate suffering from dental pain in children.
Keyphrases
  • chronic pain
  • oral health
  • pain management
  • neuropathic pain
  • healthcare
  • emergency department
  • primary care
  • spinal cord injury
  • spinal cord
  • risk factors
  • machine learning