Prevalence of Age-Related Malocclusion and Dental Anomalies in the Kosovo Region: A Retrospective Analysis

Abstract

Objective

The objective of this study was to assess the association between age and various types of dental malocclusion and anomalies.

Materials and Methods

This retrospective cross-sectional study was conducted on 617 patients from Kosovo visiting orthodontic specialty clinics in Pristina, Kosovo between 2017 and 2023. Patients were divided into two age groups: under 18 years and 18 years or older. Dental anomalies (hypodontia, impaction, ectopic eruption, midline diastema), occlusal relationships (Angle's classification), malocclusion characteristics, and anterior/posterior crowding were assessed and their associations with age were evaluated. Inclusion criteria were complete dental records with no history of orthodontic treatment, no significant medical or dental conditions, and absence of extensive restorations affecting anomaly detection. Patients with maxillofacial trauma, oral pathologies, or syndromic diagnoses were excluded. Data were analyzed with IBM SPSS software version 16.0. Descriptive statistics and Chi-square tests with Bonferroni correction were applied to assess the association between dental anomalies and malocclusion classes. A p-value of <0.05 was considered statistically significant.

Results

Significant associations were observed between age and sagittal plane classification (p = 0.014), upper midline deviation (p = 0.037), posterior crossbite (p = 0.003), and open bite (p = 0.001). Among dental anomalies, hypodontia (p = 0.001), impaction (p = 0.004), and midline diastema (p = 0.001) were observed for their associations with age. No significant association was found with ectopic eruption, deep bite, anterior crossbite, and crowding.

Conclusion

Age significantly influences specific malocclusion patterns and dental anomalies, particularly in sagittal relationships and tooth agenesis. These results emphasize the need for age-specific diagnosis and assessment and early intervention in orthodontic care.

 

MissingLinkText

Keywords

malocclusion - midline deviations - crossbite - open bite - hypodontia - impaction

Introduction

A malocclusion is a misalignment or improper relation between the teeth of the upper and lower dental arches when they approach each other as the jaws close. It is a set of craniofacial morphologic features that may differ from minor to major changes of dental or skeletal origin. They are divided into three groups: sagittal, vertical, and transverse discrepancies.[1] Sagittal patterns include class I, II, and III malocclusions. Vertical discrepancies are related to an increased or reduced vertical dimension of the face, including open and deep bites. The transverse discrepancy is connected with dental arch width and includes crossbite.[2] In orthodontic practice, the type of malocclusion determines the treatment planning choices.

Malocclusion has a multifactorial etiology that comprises both genetic and environmental factors. Specific genes like COL2A1, GHR, and MYO1H are associated with skeletal deformities such as class III malocclusion.[3] Environmental factors, especially harmful oral habits like thumb sucking or biting of the lips or cheeks, tongue thrusting, and mouth breathing, are responsible for the development of malocclusion. Dietary habits, particularly a soft diet, affect masticatory function and dental arch formation.[4] [5] Dental caries, trauma, and cleft lip/palate are also responsible for normal dental and skeletal development. The growing prevalence of these factors, mainly in young children, highlights the need for early attention to prevent malocclusion.[6]

Age plays a key role in the development of dental anomalies and different types of malocclusions. Craniofacial structures contribute to undergo significant changes well beyond adolescence and extend into late adulthood. The age-related dynamic skeletal and dental adaptations may influence the onset of malocclusions predominantly in adults who were untreated in earlier years.[7] Acknowledging these changes is essential for clinicians in planning age-appropriate orthodontic and prosthodontic treatment plans, thus ensuring accurate diagnoses and viable therapeutic consequences.[7] [8]

Numerous studies have demonstrated age-related changes in occlusal traits such as deep bite, open bite, anterior and posterior crossbites, and sagittal classifications. Moreover, anomalies such as hypodontia, ectopic eruption, and tooth impaction may present with differing prevalence in younger versus older populations, likely influenced by developmental, genetic, and environmental factors.[9] [10] Despite these known associations, comprehensive evaluations involving multiple occlusal parameters in relation to age are limited in the literature, especially in populations of Kosovo.

The relation of age and various types of dental malocclusion and anomalies has not been explored in the Kosovan population, hence, the aim of this study was to investigate the association between age and various dental characteristics, including sagittal, transverse, and vertical plane discrepancies, as well as dental anomalies such as hypodontia, impaction, and crowding. By comparing the distribution of these features between individuals under and over 18 years of age, this study provides valuable data to enhance diagnosis and treatment planning in orthodontics and pediatric dentistry.

 

MissingLinkText

Materials and Methods

This retrospective cross-sectional study was carried out on a sample of 617 patients visiting the orthodontic specialty clinics in Kosovo between 2017 and 2023. The patients were divided into two age groups: individuals under 18 years and those 18 years or older. Data were collected from the pretreatment diagnostic records of the patients. The following inclusion criteria were incorporated: archived files, no significant medical and dental history, no extensive restorations that can hinder the identification of dental anomalies, no previous history of orthodontic treatment, Albanian patients from Kosovo, complete dental files including history, examination, orthopantomograms, and photographs. The exclusion criteria were maxillofacial trauma, oral pathologies, and diagnosed syndromes. The following occlusal relationships (regarding Angle's classification) were examined on the study casts: molar and canine sagittal relationships and the coincidence of upper and lower incisal midlines, categorized according to Angle's classification into class I, class II, and class III malocclusion groups. Additionally, the presence of the following dental anomalies was assessed using study models, radiographs, and clinical files: congenitally missing teeth excluding third molars (hypodontia), tooth impaction (defined as a tooth that remains unerupted after complete root development), ectopic eruption (eruption in an abnormal position), and midline diastema (space between the maxillary central incisors). Malocclusion characteristics in the transverse (anterior and posterior crossbite, midline deviation) and vertical (deep bite and open bite) planes were evaluated, along with the presence of anterior and posterior crowding in both arches.

Associations between age and the various dental parameters were analyzed using the Pearson Chi-square test. All assessments were conducted by a single trained operator and afterward verified by an experienced orthodontist to ensure diagnostic consistency.

Data analysis was done by SPSS 16.0 software (SPSS Inc., Chicago, Illinois, United States). Descriptive statistics, along with frequency and prevalence, were performed. The Chi-squared test was used to investigate whether the distribution of the patients with dental anomalies differed between the three classes of malocclusion. The level of significance for each comparison was calculated using the Bonferroni correction. The level of Chi-squared test significance was set at p <0.05.

 

MissingLinkText

Results

This study examined the relationship between age and various dental and skeletal parameters. The subjects were categorized into two age groups: individuals under 18 years and those over 18 years. The association of age with sagittal, transverse, and vertical planes, as well as with specific dental anomalies, was investigated. The detailed results of these associations are presented below.

[Table 1] shows that the association between sagittal plane and age is statistically significant (Pearson Chi-square = 8.605, p-value = 0.014). In individuals under 18 years of age, class I has 36 individuals, class II has 52, and class III has 19. In those over 18 years, class I has 239, class II has 174, and class III has 97. The association between age and transversal plane-upper mid (right/left) is statistically significant (Pearson Chi-square = 4.353, p-value = 0.037). For individuals under 18, six are on the right position, and eight on the left. For those over 18, 46 are on the right and 18 on the left. The association between age and transversal plane-lower mid (right/left) is not statistically significant (Pearson Chi-square = 2.997, p-value = 0.083). Of individuals under 18, 8 are on the right and 6 on the left position. Of those over 18, 10 on the right and 23 in the left. The association between age and transversal plane-anterior crossbite is not statistically significant (Pearson Chi-square = 0.510, p-value = 0.475). Of individuals under 18, 20 have an anterior crossbite, and 87 do not. Of those over 18, 81 have an anterior crossbite and 429 do not. The association between age and transversal plane-posterior crossbite is statistically significant (Pearson Chi-square = 9.079, p-value = 0.003). For individuals under 18, 28 have a posterior crossbite, and 79 do not. For those over 18, 73 have a posterior crossbite, and 437 do not.

Table 1 Association of age with sagittal and transversal plane conditions

A. in sagittal plane	Age
	≤18 age		>18 age		Pearson Chi-square	p -Value
	N	%	N	%	8.605	0.014
Class I	36		239
Class II	52		174
Class III	19		97
A. in transversal plane-upper mid.	Age
	Right		Left		Pearson Chi-square	p -Value
	N	%	N	%	4.353	0.037
<18 age	6		8
>18 age	46		18
A. in transversal plane-lower mid.	Age
	Right		Left		Pearson Chi-square	p -Value
	N	%	N	%	2.997	0.083
<18 age	8		6
>18 age	10		23
A. in transversal plane-anterior crossbite	Age
	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	0.510	0.475
<18 age	20		87
>18 age	81		429
A. in transversal plane-posterior crossbite	Age
	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	9.079	0.003
<18 age	28		79
>18 age	73		437

[Table 2] shows the association between age and vertical plane-deep bite, which is not statistically significant (Pearson Chi-square = 0.870, p-value = 0.351). For individuals under 18, 37 have a deep bite, and 70 do not. In those over 18, 153 have a deep bite, and 357 do not. The association between age and vertical plane-open bite is statistically significant (Pearson Chi-square = 12.742, p-value = 0.001). For individuals under 18, 27 have an open bite, and 80 do not. Of those over 18, 61 have an open bite, and 449 do not.

Table 2 Association of age with vertical plane conditions (deep bite and open bite)

Age	A. in vertical plane—deep bite
	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	0.870	0.351
<18 age	37		70
>18 age	153		357
Age	A. in vertical plane—open bite
	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	12.742	0.001
<18 age	27		80
>18 age	61		449

[Table 3] shows the association between age and hypodontia, which is statistically significant (Pearson Chi-square = 12.931, p-value = 0.001). For individuals under 18, 25 have hypodontia, and 82 do not, while for those over 18, 54 have hypodontia, and 456 do not. The association between age and ectopic is not statistically significant (Pearson Chi-square = 0.932, p-value = 0.334). For individuals under 18, 31 have ectopic anomalies, and 76 do not, whereas for those over 18, 125 have ectopic anomalies, and 385 do not. The p-value suggests that age does not significantly influence the occurrence of ectopic anomalies.

Table 3 Association of age with dental anomalies (hypodontia, ectopic, impaction, and diastema)

Age	Dental anomalies—hypodontia
	Yes		No		Pearson Chi-square			p -Value
	N	%	N	%	12.931			0.001
<18 age	25		82
>18 age	54		456
Age	Dental anomalies—ectopic
	Yes		No		Pearson Chi-square				p -Value
	N	%	N	%	0.932			0.334
<18 age	31		76
>18 age	125		385
Age	Dental anomalies—impaction
	Yes		No		Pearson Chi-square			p -Value
	N	%	N	%	8.345			0.004
<18 age	23		84
>18 age	57		453
Age	Dental anomalies—diastema
	Divergent		Convergent		Parallel		Pearson Chi-square		p -Value
	N	%	N	%	N	%	15.934	0.001
<18 age	1		78		28
>18 age	11		440		59

The association between age and impaction is statistically significant (p-value = 0.004). For individuals under 18, 23 have impaction, and 84 do not, while for those over 18, 57 have impaction, and 453 do not. The association between age and diastema is statistically significant (p-value = 0.001). For individuals under 18, 1 has divergent, 78 have convergent, and 28 have parallel diastema, whereas for those over 18, 11 have divergent, 440 have convergent, and 59 have parallel diastema.

[Table 4] shows the association between age and anterior crowding in the lower arch, which is not statistically significant (Pearson Chi-square = 2.216, p-value = 0.137). For individuals under 18, 52 have anterior crowding, and 55 do not, while for those over 18, 288 have anterior crowding, and 222 do not. The association between age and anterior crowding in the upper arch is also not statistically significant (Pearson Chi-square = 1.925, p-value = 0.165). For individuals under 18, 53 have anterior crowding, and 54 do not, while for those over 18, 290 have anterior crowding, and 220 do not.

Table 4 Association of age with anterior crowding in upper and lower arches

A. in sagittal plane	Anterior crowding—lower arch
	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	2.216	0.137
<18 age	52		55
>18 age	288		222
A. in sagittal plane	Anterior crowding—upper arch
	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	1.925	0.165
<18 age	53		54
>18 age	290		220

The association between age and posterior crowding in the lower arch in [Table 5] is not statistically significant (Pearson Chi-square = 0.553, p-value = 0.457). For individuals under 18, 19 have posterior crowding, and 88 do not, while for those over 18, 76 have posterior crowding, and 434 do not. The association between age and posterior crowding in the upper arch is also not statistically significant (Pearson Chi-square = 0.347, p-value = 0.556). For individuals under 18, 15 have posterior crowding, and 92 do not, while for those over 18, 61 have posterior crowding, and 449 do not.

Table 5 Association of age with posterior crowding in upper and lower arches

A. in sagittal plane	Posterior crowding—lower arch
	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	0.553	0.457
≤18 age	19		88
>18 age	76		434
	Posterior crowding—upper arch
A. in sagittal plane	Yes		No		Pearson Chi-square	p -Value
	N	%	N	%	0.347	0.556
≤18 age	15		92
>18 age	61		449

 

MissingLinkText

Discussion

Significant associations were noted between age and sagittal and transverse plane conditions, giving the impact of aging on craniofacial morphology and occlusal relationships. A significant association between age and sagittal plane conditions (p = 0.014) was seen in individuals over 18 years who showed a higher prevalence of class II and class III malocclusions compared to those 18 years or younger. This suggests that aging contributes to the progression of certain malocclusion classes. A retrospective cross-sectional study by Lauc et al[11] also aligns with our findings. Their study found that dental age was significantly associated with skeletal class II and class III malocclusions. This suggests that deviations in skeletal growth patterns with age could contribute to the development of malocclusions. The cited study and our findings underline the importance of age and growth-related craniofacial changes when diagnosing and planning orthodontic treatment.

In the transverse plane, several associations with age were observed. A significant association exists between age and upper midline deviation (p = 0.037) and the individuals over 18 years were more likely to show right-sided deviations. It was observed that increased left-sided lower midline deviations were present in individuals over 18 years; however, it was not significant (p = 0.083). Regarding posterior crossbite, a higher prevalence in individuals over 18 years was seen, as there was a significant association between age and posterior crossbite occurrence (p = 0.003). In contrast, no significant association is observed between age and anterior crossbite (p = 0.475). These findings support the study of Rodríguez-Olivos et al[12] that stated the age-related differences in malocclusion patterns. They found that certain malocclusions such as posterior crossbite were more prevalent in older age groups, may be due to prolonged exposure to deleterious oral habits. These findings highlight that specific malocclusion patterns, particularly in the sagittal and transverse planes, may not only be age-dependent but reflect accumulative effects of growth disturbances or habits.

The analysis of [Table 2] revealed distinct age-related associations in vertical plane malocclusions, specifically deep bite and open bite conditions.

The association between age and deep bite was not found to be statistically significant (p = 0.351). Among individuals under 18, 37 presented with deep bite, while 70 did not. In the over 18 group, 153 had deep bite, and 357 did not. These findings suggest that deep bite prevalence does not significantly differ between the two age groups. This observation aligns with a study by Awaisi et al,[13] which reported a deep bite prevalence with no significant gender differences. The study also noticed that deep bite prevalence decreases with increasing age, indicating that age may act as an effect modifier in deep bite prevalence.

In contrast, the association between age and open bite is statistically significant (p = 0.001). Among individuals under 18, 27 had an open bite, and 80 did not. Of those over 18, 61 had an open bite, and 449 did not. Overall, while deep bite shows minimal variation across age groups, open bite displays a clear age-related decline. This indicates a higher prevalence of open bite in the younger age group. Our study is consistent with a systematic review and meta-analysis by Avrella et al,[14] who assessed the global prevalence of anterior open bite in children and adolescents. The higher open bite prevalence in younger individuals seen in our study reveals transient malocclusions that improve over time or respond to early habit elimination (e.g., thumb sucking or tongue thrust).

In our present study ([Table 3]), a statistically significant association was found between age and hypodontia (p = 0.001), with a higher prevalence among individuals under 18 years of age. This may be attributed to the timing of tooth development and eruption phases. During this phase, agenesis becomes more clinically apparent and is more likely to be detected through routine dental evaluations. Unlike adults, younger patients are often evaluated during developmental stages, leading to early identification of hypodontia. This finding is supported by the results of Polder et al,[15] who reported that hypodontia is more frequently identified during childhood and adolescence due to the active phases of dental development and eruption. Contrariwise, no significant association was found between age and ectopic eruption (p = 0.334), which aligns with Alotaibi et al,[16] who observed the prevalence of ectopic eruption among children aged 6 to 10 years. This suggests that ectopic eruption may occur irrespective of age group, supporting the opinion that factors other than age, like genetic or local anatomical conditions, may play a more important role. Additionally, a significant association was noted between age and impaction (p = 0.004), with a higher frequency observed in individuals over 18 years. This finding is expected as impactions are diagnosed in late adolescence or adulthood when eruption fails to occur within the expected developmental window. This supports the concept that impactions become more apparent with age due to delayed eruption patterns or space constraints in the dental arch.[16] Our study indicated that the association between age and diastema was also statistically significant (p = 0.001). The distribution of diastema types varied significantly with age. The divergent diastemas were rare overall; however, a relatively higher occurrence of parallel diastemas was noted in younger individuals compared to older ones. In contrast, older individuals predominantly revealed convergent diastemas. This is consistent with the findings of Kolemen et al,[17] reporting a significant difference in the prevalence of midline diastema across age groups (p < 0.001). The highest prevalence was among patients aged ≥30 years (55.8%), followed by those aged <15 years (37.7%). Their findings indicated that diastema can be prevalent in both younger and older age groups.

No statistically significant association was seen between age and anterior and posterior crowding in both the upper and lower arches, indicating that age may not be a strong predictor of crowding. This finding, in agreement with previous studies, proposes that factors other than age, such as genetics, arch dimensions, vertical growth patterns, and environmental impacts, may play more prominent roles in the development of crowding[18] [19]

This is in consistent with our previous study[20] that suggested that age alone may not be a predictor of dental crowding. Our findings highlight the potential role of third molars in mandibular anterior segment crowding and imply other variables, like arch length, tooth size, and eruption pattern, may be more relevant.[20]

 

MissingLinkText

Conclusion

The present study provides valuable perceptions into the association between age and various types of malocclusions across sagittal, transverse, and vertical planes. Significant age-related differences were observed in class II and III malocclusions, transverse anomalies such as midline deviations and posterior crossbite, and in vertical anomalies including open bite and diastema. Hypodontia and impactions were also more dominant in specific age groups. Contrariwise, no significant association was found between age and anterior or posterior crowding in either arch. This suggests that crowding may be due to factors like genetics, arch dimensions, and third molar presence rather than age alone. This study emphasizes the multifactorial nature of malocclusion development and the importance of early diagnosis and customized treatment planning based on age-related trends.

 

MissingLinkText

 

MissingLinkText

Conflict of Interest

None declared.

• References

• 1 Fonseca-Souza G, Renostro-Souza A, Alves-Souza L. et al. Association between dental age and malocclusions: a systematic review. BMC Oral Health 2024; 24 (01) 383
• 2 Saghiri MA, Eid J, Tang CK, Freag P. Factors influencing different types of malocclusion and arch form-a review. J Stomatol Oral Maxillofac Surg 2021; 122 (02) 185-191
• 3 Zhou X, Zhang C, Yao S, Fan L, Ma L, Pan Y. Genetic architecture of non-syndromic skeletal class III malocclusion. Oral Dis 2023; 29 (06) 2423-2437
• 4 Belitz GS, Furlan LJN, Knorst JK. et al. Association between malocclusion in the mixed dentition with breastfeeding and past nonnutritive sucking habits in school-age children. Angle Orthod 2022; 92 (05) 669-676
• 5 Aroucha Lyra MC, Aguiar D, Paiva M. et al. Prevalence of sleep-disordered breathing and associations with malocclusion in children. J Clin Sleep Med 2020; 16 (07) 1007-1012
• 6 Chen H, Lin L, Chen J, Huang F. Prevalence of malocclusion traits in primary dentition, 2010-2024: a systematic review. Healthcare (Basel) 2024; 12 (13) 1321
• 7 Al-Taai N, Persson M, Ransjö M, Levring Jäghagen E, Fors R, Westerlund A. Craniofacial changes from 13 to 62 years of age. Eur J Orthod 2022; 44 (05) 556-565
• 8 Proffit WR, Fields HW, Larson BE, Sarver DM. eds. Chapter 24: Treatment for Adults. In: Contemporary Orthodontics. 6th ed.. St. Louis, MO: Mosby Elsevier; 2019: 599-654
• 9 Yassin SM. Prevalence and distribution of selected dental anomalies among saudi children in Abha, Saudi Arabia. J Clin Exp Dent 2016; 8 (05) e485-e490
• 10 Selmani M, Selmani Bukleta M. Prevalence of dental anomalies in various categories of malocclusion among orthodontic patients in the Kosovo region: a retrospective study. Eur J Gen Dent 2023; 12 (02) 103-108
• 11 Lauc T, Nakaš E, Latić-Dautović M. et al. Dental age in orthodontic patients with different skeletal patterns. BioMed Res Int 2017; 2017: 8976284
• 12 Rodríguez-Olivos LHG, Chacón-Uscamaita PR, Quinto-Argote AG, Pumahualcca G, Pérez-Vargas LF. Deleterious oral habits related to vertical, transverse and sagittal dental malocclusion in pediatric patients. BMC Oral Health 2022; 22 (01) 88
• 13 Awaisi ZH, Khan U, Nihal T, Ghaffar I, Murtaza N. Age as an effect modifier with respect to gender in orthodontics in deep bite prevalence. Prof Med J 2020; 27 (09) 1845-1848
• 14 Avrella MT, Zimmermann DR, Andriani JSP, Santos PS, Barasuol JC. Prevalence of anterior open bite in children and adolescents: a systematic review and meta-analysis. Eur Arch Paediatr Dent 2022; 23 (03) 355-364
• 15 Polder BJ, Van't Hof MA, Van der Linden FP, Kuijpers-Jagtman AM. A meta-analysis of the prevalence of dental agenesis of permanent teeth. Community Dent Oral Epidemiol 2004; 32 (03) 217-226
• 16 Alotaibi RM, Alattas SH, Alandanusi BN. et al. Prevalence and severity of ectopic eruption of first permanent molars in pediatric patients in Makkah, Saudi Arabia. Cureus 2023; 15 (11) e49220
• 17 Kolemen A, Hasan HS, Al Azzawi AM. Medline diastema of orthodontic patients: prevalence and etiology in Erbil population – a cross-sectional study. Int J Res Pharm Sci 2020; 11 (04) 5997-6003
• 18 Shahroom NSB, Jain RK, Nasim I. Association of mandibular arch crowding and vertical growth pattern: a retrospective study. Int J Dent Oral Sci 2021; 8 (08) 4096-4100
• 19 Shigenobu N, Hisano M, Shima S, Matsubara N, Soma K. Patterns of dental crowding in the lower arch and contributing factors. A statistical study. Angle Orthod 2007; 77 (02) 303-310
• 20 Selmani M, Bukleta MS, Duci SB. The role of dental arch dimensions and impacted third molars on mandibular anterior segment crowding. Eur J Dent 2024; 18 (04) 1164-1171

Publication History

Article published online:
19 August 2025