2 resultados para Age, relative, number of years

em Bioline International


Relevância:

100.00% 100.00%

Publicador:

Resumo:

Aim: This prospective cohort study was to evaluate the independent and mutual effects of socioeconomic, oral health behaviors and individual clinical factors, including enamel hypomineralization, as possible risk factors for increase in caries experience in second primary molar (SPM) over a period of 2-years. Methods: Children (n=216) aged 4-6 years were examined for hypomineralized second primary molar (HSPM) and dental caries in school settings and were recalled every 6 months. The caregivers filled out a semi-structured questionnaire about their socio-demographic and oral health-related behaviors. Data analysis was performed using a hierarchical model with three levels. Multiple analyses were performed at each level and variables with p<0.20 were tested by stepwise multiple Generalized Estimating Equation. Results: At final examination, 33.3% of the children had developed new caries lesions in SPM. The model showed that the number of years of mother’s schooling and the caregiver´s perception about their children’s caries experience played a protective role in the incidence of dental caries. Children who had white spot lesions were more likely to develop new carious lesions in SPM. Children with HSPM showed no higher incidence of caries in their SPM than those without HSPM. Conclusions: Clinical, socioeconomic and behavioral factors impacted on caries development in primary second molars. However, further studies are required to better understand the role of HSPM in caries development in other age groups.

Relevância:

100.00% 100.00%

Publicador:

Resumo:

It is important to identify groups of people vulnerable to a disease condition. Aim: To determine the association between social vulnerability to caries and caries status of children in Ile-Ife, Nigeria. Methods: A composite vulnerability index for caries was developed using data generated for 992 children. Wilks’ Lambda test to verify relationship between vulnerability and its variables. Logistic regression analysis was conducted to determine if the social vulnerability for caries index was a good predictor for caries status. Results: The social vulnerability to caries index could not predict caries status. The study found that sex, age and number of siblings were the significant predictors of caries status in the study population. Females (AOR: 1.63; 95%CI: 1.08 – 2.46; p=0.02) and children with more than two siblings had higher odds of having caries (AOR: 2.61; 95%CI: 1.61 – 4.24; p<0.001) while children below 5 years had lower odds of having caries (AOR: 0.62; 95%CI: 0.39 – 1.00; p=0.05) Conclusions: The social vulnerability index for caries could not predict the caries status of children in the study population. Sensitive tools to identify children with caries in the study population should be developed.