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Background <p>Deep overbite is a critical parameter in orthodontic diagnosis and treatment planning, reflecting the excessive vertical overlap of anterior teeth. It not only affects facial esthetics but may also contribute to functional disturbances. It is influenced by a complex interplay of skeletal, dental, and angular factors. Understanding the relative association of these components is critical for accurate diagnosis and effective treatment planning. So, this study aims to determine which skeletal and dental components most significantly affect deep overbite.</p> Materials and methods <p>The study was carried out on 252 pre-treatment lateral cephalograms of Nepalese patients of mixed ethnic backgrounds (Indo-Nepali, Tibeto-Nepali, and Indigenous Nepali) who presented with an overbite of greater than 4&#xa0;mm measured on the lateral cephalogram, in the Department of Orthodontics, BPKIHS, Nepal. Among them, 130 were males and 122 were females. The mean age of the subjects was 22.26 ± 3.85 years (range:16 to 41 years). Lateral cephalograms meeting the inclusion/exclusion criteria were digitally traced using Onyxceph3TM Pro (version 3.2.67) software. Twelve vertical and angular, skeletal and dental parameters from Burstone’s Cephalometrics for Orthognathic Surgery (COGS) analysis were measured. Descriptive analysis was performed for each variable. Multiple linear regression analyses were performed performed to evaluate the association between skeletal and dentoalveolar variables and deep overbite. Iterative backward elimination regression approach was used to assess the association between the variables and deep over bite after considering multicollinearity.</p> Results <p>The final model explained 71.4% of the variance in deep overbite (R²=0.714, <i>p</i> &lt; 0.001). Lower anterior dental height (L1-MP) had the strongest effect on deep overbite. Other significant predictors included lower anterior facial height (ANSGn), mandibular plane angle (MP-HP), upper anterior dental height (U1-NF), upper anterior inclination (U1NFang), Lower anterior inclination (L1MPang) and lower posterior dental height (LM-MP).</p> Conclusion <p>Overbite is predominantly influenced by dentoalveolar factors, particularly incisor position and inclination, while skeletal variables play a secondary role.</p>

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A cephalometric analysis of underlying components of deep overbite malocclusion

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月26日

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  • Avinash Chaudhary,
  • Sushant Pandey,
  • Samikshya Sangroula,
  • Jamal Giri,
  • Prabhat Ranjan Pokharel,
  • Rajesh Gyawali

摘要

Background

Deep overbite is a critical parameter in orthodontic diagnosis and treatment planning, reflecting the excessive vertical overlap of anterior teeth. It not only affects facial esthetics but may also contribute to functional disturbances. It is influenced by a complex interplay of skeletal, dental, and angular factors. Understanding the relative association of these components is critical for accurate diagnosis and effective treatment planning. So, this study aims to determine which skeletal and dental components most significantly affect deep overbite.

Materials and methods

The study was carried out on 252 pre-treatment lateral cephalograms of Nepalese patients of mixed ethnic backgrounds (Indo-Nepali, Tibeto-Nepali, and Indigenous Nepali) who presented with an overbite of greater than 4 mm measured on the lateral cephalogram, in the Department of Orthodontics, BPKIHS, Nepal. Among them, 130 were males and 122 were females. The mean age of the subjects was 22.26 ± 3.85 years (range:16 to 41 years). Lateral cephalograms meeting the inclusion/exclusion criteria were digitally traced using Onyxceph3TM Pro (version 3.2.67) software. Twelve vertical and angular, skeletal and dental parameters from Burstone’s Cephalometrics for Orthognathic Surgery (COGS) analysis were measured. Descriptive analysis was performed for each variable. Multiple linear regression analyses were performed performed to evaluate the association between skeletal and dentoalveolar variables and deep overbite. Iterative backward elimination regression approach was used to assess the association between the variables and deep over bite after considering multicollinearity.

Results

The final model explained 71.4% of the variance in deep overbite (R²=0.714, p < 0.001). Lower anterior dental height (L1-MP) had the strongest effect on deep overbite. Other significant predictors included lower anterior facial height (ANSGn), mandibular plane angle (MP-HP), upper anterior dental height (U1-NF), upper anterior inclination (U1NFang), Lower anterior inclination (L1MPang) and lower posterior dental height (LM-MP).

Conclusion

Overbite is predominantly influenced by dentoalveolar factors, particularly incisor position and inclination, while skeletal variables play a secondary role.