Factors associated with toothache in 12-year-old adolescents in a southeastern state of Brazil.
Nildelaine Cristina CostaMauro Henrique Nogueira Guimarães de AbreuRafaela da Silveira PintoFabiana Vargas-FerreiraRenata de Castro MartinsPublished in: Brazilian oral research (2022)
This cross-sectional study evaluated factors associated with toothache in 12-year-old adolescents from the state of Minas Gerais in Brazil. Secondary data were collected from the SB Minas Gerais 2012 epidemiological survey. The dependent variable was toothache in the past 6 months. The independent variables were grouped into two levels: individual (sex, ethnic group, family income, periodontal condition, dental caries, dental treatment needs, and type of service used) and contextual (allocation factor, Human Development Index, Gini coefficient, gross domestic product, unemployment, illiteracy, basic sanitation, garbage collection, family income, half or a quarter of a minimum wage, primary healthcare coverage, primary oral healthcare team coverage, oral health technician, access to individual dental care, and supervised tooth brushing). A multilevel analysis was performed using the Hierarchical Linear and Nonlinear Modeling Software Program to assess the association of individual and contextual variables with toothache in the last 6 months. The prevalence of toothache in the last six months among the adolescents of this study was 19.1%. An association was found with family income (p <0.001), dental caries (p <0.001), primary oral healthcare team coverage (p = 0.015) and oral health technician (p = 0.008). Socioeconomic conditions and the most prevalent oral diseases, such as dental caries, as well as the use of public services, were related to toothache in adolescents aged 12 years. These findings reinforce the need to develop and implement public policies to address the oral health problems of this population.
Keyphrases
- oral health
- healthcare
- physical activity
- mental health
- young adults
- affordable care act
- palliative care
- quality improvement
- machine learning
- endothelial cells
- drinking water
- risk factors
- health information
- public health
- cross sectional
- data analysis
- magnetic resonance imaging
- artificial intelligence
- pain management
- induced pluripotent stem cells
- diffusion weighted imaging
- big data