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ORIGINAL ARTICLE
Year : 2018  |  Volume : 36  |  Issue : 1  |  Page : 26-32
 

Comparative evaluation and applicability of three different regression equation-based mixed dentition analysis in Northern Uttar Pradesh population


1 Department of Paediatric and Preventive Dentistry, Dr. Z.A Dental College and Hospital, Aligarh Muslim University, Aligarh, India
2 Department of Pedodontics and Preventive Dentistry, Kothiwal Dental College And Research Centre, Moradabad, Uttar Pradesh, India

Date of Web Publication28-Mar-2018

Correspondence Address:
Dr. Akash Bhatnagar
Department of Paediatric and Preventive Dentistry, Dr. Z.A Dental College and Hospital, Aligarh Muslim University, Aligarh - 202 002, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/JISPPD.JISPPD_104_17

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   Abstract 

Aims: This study aims to examine the accuracy and comparative correlation of three regression equation-based mixed dentition analysis in children of Moradabad city, North Uttar Pradesh. Settings and Design: Tanaka–Johnston, Bernabe–Flores-Mir, and Ling–Wong regression equations were developed from a sample of North European, Peru, and Southern Chinese children population, respectively. Hence, it becomes questionable when applied to children of Moradabad city situated in North Uttar Pradesh, India. Subjects and Methods: The study was conducted on a sample of 100 school going children, age range is 11–14 years with complete permanent teeth except third molars. The mesiodistal crown dimensions of all erupted incisors, canines, premolars, and molars were measured with digital calipers with a calibration accuracy of 0.01 mm. The actual tooth measurements were then compared with predicted values using Tanaka–Johnston, Bernabe–Flores-Mir, and Ling–Wong regression equations, respectively using paired t-test. Results: The mean difference between the actual and estimated values of canines and premolars using Tanaka–Johnston, Bernabe–Flores-Mir, and Ling–Wong were clinically and statistically significant (P< 0.001). Conclusions: Mesiodistal dimensions of male samples are larger than female samples. All the three regression equations are not accurately applicable to this population.


Keywords: Digital calipers, mesiodistal width, mixed dentition analysis, regression equations


How to cite this article:
Bhatnagar A, Chaudhary S, Sinha AA, Manuja N, Kaur H, Chaitra T R. Comparative evaluation and applicability of three different regression equation-based mixed dentition analysis in Northern Uttar Pradesh population. J Indian Soc Pedod Prev Dent 2018;36:26-32

How to cite this URL:
Bhatnagar A, Chaudhary S, Sinha AA, Manuja N, Kaur H, Chaitra T R. Comparative evaluation and applicability of three different regression equation-based mixed dentition analysis in Northern Uttar Pradesh population. J Indian Soc Pedod Prev Dent [serial online] 2018 [cited 2019 Nov 15];36:26-32. Available from: http://www.jisppd.com/text.asp?2018/36/1/26/228736





   Introduction Top


Mixed dentition space analysis is the prediction of mesiodistal width of unerupted permanent canines and premolars to determine the discrepancy between the available and required space in each dental arch.[1] Some basic principles for a mixed dentition analysis are as follows: (1) Ease of use by any person with basic training (2) a known minimum systemic error, (3) fast, (4) no any special instrument required, (5) can be carried out directly in the mouth, and (6) used in maxillary and mandibular arches.[2],[3] Early orthodontic intervention is mostly relay on an accurate space analysis. Mixed dentition space analysis is most important criteria in determining whether a treatment plan should involve space maintenance, space regaining, serial extraction, guidance of eruption, or periodic observation.[4],[5],[6]

Probability tables proposed by Black 1897, based on average tooth size were used to calculate the size of unerupted canines and premolars.[7] Later, intraoral radiographs were used to determine the size of unerupted permanent canines and premolars. Because of these methods tended to overestimate/underestimate tooth size, a mathematical proportion was proposed to compensate for image enlargement. Nowadays, the method of space analysis in mixed dentition period based on 45° cephalometric radiograph is used for mixed dentition space analysis. However, it is time-consuming method and requires sophisticated equipment.[8],[9]

Significant linear association between the sum of four lower permanent incisors and the sum of the mesiodistal width of unerupted mandibular permanent canines and premolars reported by Carey. Since then, several simple linear regression equations have been proposed for children of different ethnic and racial origins.[10]

Mixed dentition space analysis based on already erupted permanent teeth are used most widely, especially Tanaka and Johnston method. Tanaka and Johnston's regression analysis (1974) has several advantages such as used for both the arches and both the sexes, no need of any specific equipments and radiograph projections and can be done by beginner or expert.[11]

Bernabe and Flores-Mir [12] regression equation is multiple linear regression equation (MLRE), have been proposed for Peruvian school children and have a significant association between combination of the upper and lower central incisors plus upper first molars and unerupted permanent canines and premolars.

Ling and Wong [13] regression equations are simple linear regression equation have been proposed for Southern Chinese children and have a significant linear association between four lower permanent incisors and the unerupted permanent canines and premolars.

Hence, the constants of these regression equations are based on tooth sizes of different populations and were proved by the previous reported studies that it is difficult to apply in other populations because of the variation in tooth size and racial diversity. This led us to examine the accuracy and comparative correlation of the three regression equation-based mixed dentition analysis and to find a more accurate and precise regression equation in predicting the size of permanent canines and premolars among children of Moradabad population.


   Subjects and Methods Top


Sample selection

The sample comprised 100 children (50 males and 50 females) randomly selected from the senior secondary schools situated in Moradabad city, with a mean age of 12.5 years (11–14 years). The children were selected following an oral examination performed under natural daylight using mouth mirror with good reflecting surface and stainless steel explorer. Ethical approval was obtained from the Institutional Ethical and Review Board of Kothiwal Dental College and Research Centre, Moradabad. Written consent was obtained from the schools and parents of all children who underwent dental examination and impressions recording.

Inclusion criteria

  • Presence of all permanent teeth with the exception of third molars
  • No congenital craniofacial and dental anomalies
  • No previous history of removable and fixed orthodontic treatment
  • Presence of intact dentition.


Exclusion criteria

  • Teeth with proximal restorations, wear, caries, or fracture
  • Dental anomalies which may alter the size, shape, number, or form of the teeth
  • Teeth with enamel hypoplasia
  • Partially erupted teeth.


Selected children were made to sit on a dental chair, and a full depth alginate impression (Vignette Chromatic Dentsply, India) of the maxillary and mandibular arches for each child was made using the standard perforated stainless steel impression trays. Impressions were then washed under running tap water. Study models were fabricated by pouring dental stone (Kalabhai Karson Pvt. Ltd., Mumbai, India). The study models were trimmed using model trimmer and B. P. handle with blade. Base former were used to pour bases for the study models using dental plaster [Figure 1].
Figure 1: Dental study casts

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Measurement of mesiodistal width

Mesiodistal width of maxillary and mandibular incisors, canines, premolars, and first molars were recorded using an electronic digital caliper (Digenetic calipers, Mitutoyo Corporation, Tokyo, Japan). A standardized method proposed by Moorrees and Reed was used to measure the mesiodistal crown widths. The greatest mesiodistal crown width of each tooth was measured between its contact points, with the sliding caliper placed parallel to the occlusal and vestibular surfaces [Figure 2].[14]
Figure 2: Measurement of mesiodistal width

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To ensure the reliability of measurement of mesiodistal width, two investigators blinded to the subjects and to each other measured the dental casts. Only 10 dental study casts were measured per day selected randomly. A high intraclass correlation coefficient = 0.946 ensured the measurement reliability.

Mixed dentition model analysis

In the present study, three regression equation-based mixed dentition analysis was used to predict the mesiodistal width of canines and premolars.

  1. Tanaka and Johnston method:


  2. Y = a + bx

    For maxillary teeth, a = 11.0, b = 0.5,

    For mandibular teeth, a = 10.5, b = 0.5,

    x = sum of four lower incisors.

  3. Bernabe and Flores-Mir method:


  4. Y = 3.763 + 0.37 × X0 + 1.057 × X1 + 0.366 × X2

    X0 = is the sum of the upper and lower permanent central incisors plus the widths of the upper permanent first molars,

    X1 = 0 for mandible and 1 for maxilla,

    X2 = 0 for female and 1 for male.

  5. Ling and Wong method:


  6. Y = a + bx

    For maxillary teeth, male: a = 11.50, b = 0.5 female: a = 10.86, b = 0.5,

    For mandibular teeth, male: a = 10.61, b = 0.5 female: a = 9.85, b = 0.5,

    x = sum of four lower incisors.


Statistical analysis

All analyses were performed on SPSS (SPSS Inc. Version 16.0 Chicago: SPSS Inc) software. Data were summarized as mean ± standard deviation (SD) paired observations were compared by paired t-test (two-tailed test) while independent groups were compared by independent Student's t-test. The level of significance was at P < 0.001.


   Results Top


The distribution of mean ± SD of mesiodistal width of maxillary (C + P 1 + P 2) in males measured by Tanaka–Johnston, Bernabe–Flores-Mir, and Ling–Wong, actual value was 21.264 ± 0.5742, 21.784 ± 0.7221, 21.754 ± 0.5936, 19.536 ± 1.1611, respectively, [Graph 1]. On applying t-test for two dependent groups, we had found the mean differences of mesiodistal width of maxillary (C + P 1 + P 2) in males between Bernabe and Flores-Mir–Ling and Wong (0.0300), was not significant as P > 0.001, while in Tanaka and Johnston–Ling and Wong (−0.4900), Tanaka and Johnston–Bernabe and Flores-Mir (−0.5200), Tanaka and Johnston – actual value (1.7280), Bernabe and Flores-Mir – actual value (2.2480), Ling and Wong – actual value (2.2180) were statistically significant as P < 0.001 [Table 1].
Table 1: Comparison of means of mesiodistal width of maxillary (C + P1 + P2) in males by paired samples t-test

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The distribution of mean ± SD of mesiodistal width of maxillary (C + P 1 + P 2) in females measured by Tanaka and Johnston, Bernabe and Flores-Mir, and Ling and Wong, actual value were 21.146 ± 0.5365, 21.284 ± 0.7138, 20.980 ± 0.5421, 19.222 ± 1.0775, respectively [Graph 2]. On applying t-test for two dependent groups, we had found the mean differences of mesiodistal width of maxillary (C + P 1 + P 2) in females between Tanaka and Johnston–Bernabe and Flores-Mir (−0.1380) was not statistically significant P > 0.001, while in Tanaka and Johnston–Ling and Wong (.1660), Bernabe and Flores-Mir–Ling and Wong (0.3040), Tanaka and Johnston – actual value (1.9240), Bernabe and Flores-Mir – actual value (2.0620), Ling and Wong – actual value (1.7580) were statistically significant as P < 0.001 [Table 2].
Table 2: Comparison of means of mesiodistal width of maxillary (C + P1 + P2) in females by paired samples t-test

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The distribution of mean ± SD of mesiodistal width of mandibular (C + P 1 + P 2) in males measured by Tanaka and Johnston, Bernabe and Flores-Mir, and Ling and Wong, actual value were 20.774 ± 0.5689, 20.736 ± 0.7306, 20.86 ± 0.569, 19.198 ± 1.1118, respectively [Graph 3]. On applying t-test for two dependent groups, we had found the mean differences of mesiodistal width of mandibular (C + P 1 + P 2) in males between Tanaka and Johnston–Bernabe and Flores-Mir (0.0380), Bernabe and Flores-Mir-Ling and Wong (−0.1280), was not statistically significant P > 0.001, while in Tanaka and Johnston–Ling and Wong (−0.0900), Tanaka and Johnston – actual value (1.5760), Bernabe and Flores-Mir – actual value (1.5380), Ling and Wong – actual value (1.6660) were statistically significant as P < 0.001 [Table 3].
Table 3: Comparison of means of mesiodistal width of mandibular (C + P1 + P2) in males by paired samples t-test

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The distribution of mean ± SD of mesiodistal width of mandibular (C + P 1 + P 2) in females measured by Tanaka and Johnston, Bernabe and Flores-Mir, and Ling and Wong, actual value were 20.644 ± 0.5357, 20.198 ± 0.7090, 19.954 ± 0.5758, 18.884 ± 1.0899, respectively [Graph 4]. On applying t-test for two dependent groups, we had found the mean differences of mesiodistal width of mandibular (C + P 1 + P 2) in females between Tanaka and Johnston–Bernabe and Flores-Mir (0.4460), Tanaka and Johnston-Ling, and Wong (.6900), Bernabe and Flores-Mir–Ling and Wong (0.2440), Tanaka and Johnston – actual value (1.7600), Bernabe and Flores-Mir-actual value (1.3140), Ling and Wong-Actual value (1.0700) were significant as P < 0.001 [Table 4].
Table 4: Comparison of means of mesiodistal width of mandibular (C + P1 + P2) in females by paired samples t-test

Click here to view




   Discussion Top


Dental malocclusion in mixed dentition period can occur as a result of genetic and environmental factors. Most of the cases of dental malocclusion start during the mixed dentition period.[15],[16] Regression equations space analysis based on erupted permanent teeth in mixed dentition period are very simple and have good accuracy. Simple Linear regression equation was the first type of regression space analysis to be studied rigorously and to be used extensively in the practical application.[17],[18]

In the present study, 11–14 years age groups was selected as at this age all permanent teeth except third molars in both the arches have erupted into the oral cavity and to minimize the changes in tooth dimension because of attrition, proximal restoration, or caries.[19] Electronic digital caliper was used in the present study for measuring the mesiodistal width accurate to a precision of 0.01 mm.

Tanaka and Johnston (1974) calculated simple linear regression equations for the prediction of the mesiodistal widths of unerupted canines and premolars for a sample of 506 North American orthodontic patients. Since then, their regression equation for prediction of unerupted teeth has been widely used in pediatric dentistry.[20]

In the present study, when Tanaka and Johnston method was applied in male and female samples, there was clinical relevant differences (>1 mm) and statistical significant differences (P< 0.001) was found between the predicted and actual value of canines and premolars teeth in both the arches. Hence, it was concluded that Tanaka and Johnston regression equation overestimate the mesiodistal width of canines and premolars. This is in accordance with studies of Brito et al.,[21] Tahere et al.,[22] Melgaco et al.,[23] Jaiswal et al.,[24] Arslan et al.,[25] Mitter et al.,[26] Srivastava et al.,[27] and Kommineni et al.[28]

Bernabé and Floris-Mir developed a MLRE using sum of permanent maxillary and mandibular central incisors plus the widths of permanent maxillary first molars, and gender as an additional variable. They reported high values of correlation and determination coefficients for a Peruvian school children (r = 0.720 and r2 = 0.604); and considered the sums of the maxillary and mandibular permanent central incisors plus permanent maxillary first molars as the best predictors for the sums of the mesiodistal widths of canines and premolars in both the sexes.[12] However, in the present study, Bernabé and Floris-Mir regression equation overestimate the mesiodistal width of canines and premolars, and significant differences were found between actual and predicted values in male and female samples.

Memon and Fida conducted a study in orthodontic patients of Aga Khan University Hospital, Karachi, and concluded that Bernabe and Flores-Mir regression equation overestimate the mesiodistal width of canines and premolars.[2] The result was similar to our present study.

Ling and Wong developed a simple linear regression equation using sum of four lower incisors which is derived from a sample of 459 Southern Chinese 12 year's children. They concluded that to predict the mesiodistal dimension of canines and premolars, halve the sum of the mesiodistal width of the four lower incisors, and add the respective constants for males (upper, 11.5; lower, 10.5) or females (upper, 11.0; lower, 10.0).[13] In the present study, when Ling and Wong method was applied in male and female samples, statistical significant differences (P< 0.001) was found between the predicted and actual value of canines and premolars teeth in both the arches.

Mahmoud et al.reported that regression equation proposed by Ling and Wong for Southern Chinese samples proved to be highly accurate for female Malay children.[29] However, in the present study, Ling and Wong regression equation showed a significant difference between the actual and predicted values of canines and premolars for both sexes in both the dental arches.

Tooth size and facial structure differ among populations of different ethnic or racial origin. Some of the most commonly used mixed dentition analysis to predict mesiodistal widths of canines and premolars teeth were developed for the United States children. Studies to confirm the reliability and applicability of these mixed dentition analysis in different populations are appropriate.


   Conclusions Top


The present study reveals that Tanaka–Johnston, Bernabe–Flores-Mir, and Ling–Wong regression equations significantly overestimate the mesiodistal widths of permanent canine and premolars of school going children's of Moradabad city, North Uttar Pradesh. Statistically significant difference (P< 0.001) was found between the actual and predicted values when Tanaka–Johnston, Bernabe–Flores-Mir, and Ling–Wong regression equations were applied to this population. Hence, all the three regression equations were not accurately applicable to this population. Further studies are required on different population, to confirm the applicability.

Acknowledgment

We sincerely thank Associate Prof. MK Sharma, ITS Dental Study and Research, Muradnagar, India, for suggestions regarding statistical analyses and generously supporting this study.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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