Back

Malocclusion Following Early Primary Tooth Extraction: The Role of Socio-Economic Factors and Parental Awareness in Bangladesh

Hossain, N.

2025-03-01 dentistry and oral medicine
10.1101/2025.02.27.25323050 medRxiv
Show abstract

The research explored the link between premature deciduous teeth removal and malocclusion as well as parent decision-making affected by socioeconomic factors and their knowledge about early primary tooth extraction and its consequences. A study with 308 child-parent pairs evaluated both urban and rural areas of Bangladesh. Clinical examinations of the children were conducted while parents answered structured questionnaires about the matter. Descriptive statistics is conducted along with Chi-Square tests and logistic regression analyses for data examination. Research findings confirmed that early deciduous tooth extraction caused an increased risk of developing malocclusion since 50.0% of patients in the extraction group developed it compared to 26.0% in the non-extraction group (x2 = 6.519, p = 0.011). Parental decision to invest in orthodontic care was influenced by both family financial status and living in an urban area. Higher household earnings (OR = 1.69, p < 0.001) and residing in a city (OR = 7.17, p < 0.001) were discovered as main predictors for willingness to invest. The analysis revealed that 80.5% of parents remained unaware about the connection between early tooth extraction and malocclusion but higher education levels (OR = 0.744, p < 0.001) and urban residence (OR = 0.372, p = 0.005) increased their probability to have this knowledge. Protecting primary teeth prevents malocclusion and demands strategic education programs for parents primarily in rural areas where population has limited education exposure. This study also illustrates how socio-economic factors affect oral health results, which indicates the importance for governments to address limited affordable orthodontic care availability among vulnerable groups in Bangladesh.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.