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Kim, Lee, Kim, Jeon, and Chang: Logistic regression analysis of factors affecting survival of permanent second molars in Korean adults
Original Article

J Korean Acad Oral Health 2013;37(4):232-240.

Published online: 12 December 2013

DOI: https://doi.org/10.11149/jkaoh.2013.37.4.232

Logistic regression analysis of factors affecting survival of permanent second molars in Korean adults

Gwang-Seok Kim, Hae-Jin Lee, Young-Sam Kim, Jae-Gyu Jeon, Kee-Wan Chang

Department of Preventive and Community Dentistry, Institute of Oral-Bio Science, Chonbuk National University School of Dentistry, Jeonju, Korea

Corresponding Author: Kee-Wan Chang Department of Preventive and Community Dentistry, Institute of Oral-Bio Science, Chonbuk National University School of Dentistry, 567 Baeje-daero, Deokjin-gu, Jeonju 561-756, Korea Tel: +82-63-270-4034 Fax: +82-63-270-4035 E-mail: prevdent@chonbuk.ac.kr

Received 2 December 2013       Revised 18 December 2013       Accepted 26 December 2013

Copyright © 2013 Journal of Korean Academy of Oral Health

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objectives

The purpose of this study was to analyze the factors affecting the survival of permanent second molars in Korean adults using logistic regression analysis.

Methods

This National survey was conducted in 2006 and was performed in 3 stages comprising stratified sampling, age, sex, and region. This study included 15,777 persons, aged 2-95 years. The raw data was analyzed using SPSS software v12.0 and the relationship between the 9 variables and the tooth survival rate was analyzed by frequency and cross-tabulation. Logistic regression analysis using the functional weightage of the age, sex, regions of the Korean population was also performed. Entry was at level of 5%, while removal was at a 10% level during logistic regression analysis. The nine variables used for analysis were age, socio-economic level, monthly family income, sex, frequency of toothbrushing per day, diabetes, educational level, smoking, and frequency of snack intake per day.

Results & Conclusions

The most significant explanatory variables, in increasing order of significance, were age, socioeconomic status, and diabetes. As age increased by 10 years, the survival rate of second molars decreased at a slow rate 7.5% to 9.5%. The survival rate of the second molar of an individual engaged in activities, such as farming, stock breeding, and fishing decreased from 64.4% to 78.8% as compared to people at high positions in various companies and in society.

Keywords: Korean, Logistic regression analysis, Second molar, Survival rate of tooth

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Fig. 1.
Survival rate of maxillary & mandible second molar. #17: Maxillary right second molar, #27: Maxillary left second molar, #37: Mandible left second molar, #47: Mandible right second molar. Survival rate=Existence teeth number/Arrested teeth number×100 (%).
jkaoh-37-232f1.tif
Table 1.
Sample distribution reflecting weight
Age Frequency Percent valid percent Cumulative perce
2-5 1,042 6.6 6.6 6.6
6 201 1.3 1.3 7.9
7 211 1.3 1.3 9.2
8 219 1.4 1.4 10.6
9 225 1.4 1.4 12.0
10 232 1.5 1.5 13.5
11 231 1.5 1.5 15.0
12 235 1.5 1.5 16.5
13 233 1.5 1.5 17.9
14 221 1.4 1.4 19.3
15 211 1.3 1.3 20.7
16 206 1.3 1.3 22.0
18-24 1,604 10.2 10.2 32.2
25-29 1,242 7.9 7.9 40.0
30-34 1,387 8.8 8.8 48.8
35-44 2,823 17.9 17.9 66.7
45-54 2,302 14.6 14.6 81.3
55-64 1,446 9.2 9.2 90.5
65-74 1,010 6.4 6.4 96.9
75+ 494 3.1 3.1 100.0
Total 15,777 100.0 100.0

2006 Korean national oral health survey.

Table 2.
Logistic regression model estimation to survival of teeth #17
Variable B S.E. Significance probability Exp (B)
Economic activity 0.000
High rank executives and staff member or manager Standard
Expert, technician ―0.001 0.447 0.999 0.999
Clerk 0.102 0.295 0.730 1.107
Service workers ―0.609 0.211 0.004 0.544
Functional workers ―0.748 0.210 0.000 0.473
Agriculture, animal husbandry, fishing industry ―1.340 0.217 0.000 0.262
Soldier and et cetera ―0.941 0.215 0.000 0.390
Age ―0.100 0.004 0.000 0.905
Toothbrushing number ―0.108 0.053 0.043 0.898
Smoking period ―0.009 0.004 0.040 0.091
Constant 7.715 0.322 0.000 2,241.332

1 Stage entered variable: Age, 2 Stage entered variable: Economic activity, 3 Stage entered variable: Smoking period, 4 Stage entered variable:Toothbrushing number.

Table 3.
Logistic regression model estimation to survival of teeth #27
Variable B S.E. Significance probability Exp (B)
Economic activity 0.000
High rank executives and staff member or manager Standard
Expert, technician ―0.392 0.360 0.277 0.676
Clerk ―0.286 0.238 0.228 0.751
Service workers ―0.410 0.190 0.031 0.664
Functional workers ―0.423 0.191 0.027 0.655
Agriculture, animal husbandry, fishing industry ―1.034 0.199 0.000 0.356
Soldier and et cetera ―0.752 0.196 0.000 0.471
Age ―0.096 0.004 0.000 0.908
Diabetes ―0.466 0.156 0.003 0.628
Toothbrushing number ―0.214 0.051 0.000 0.808
Cookie intake ―0.266 0.064 0.000 0.767
Constant 7.641 0.307 0.000 2,082.390

1 Stage entered variable: Age, 2 Stage entered variable: Economic activity, 3 Stage entered variable: Toothbrushing number, 4 Stage entered variable:Cookie intake, 5 Stage entered variable: Diabetes.

Table 4.
Logistic regression model estimation to survival of teeth #37
Variable B S.E. Significance probability Exp (B)
Economic activity 0.000
High rank executives and staff member or manager Standard
Expert, technician ―1.171 0.380 0.002 0.310
Clerk ―0.531 0.269 0.049 0.588
Service workers ―1.156 0.216 0.000 0.315
Functional workers ―1.488 0.214 0.000 0.226
Agriculture, animal husbandry, fishing industry ―1.472 0.226 0.000 0.230
Soldier and et cetera ―1.549 0.221 0.000 0.212
Family income 0.097 0.030 0.001 1.102
Sex ―0.295 0.085 0.001 0.745
Age ―0.078 0.004 0.000 0.925
Constant 6.394 0.287 0.000 598.489

1 Stage entered variable: Age, 2 Stage entered variable: Economic activity, 3 Stage entered variable: Sex, 4 Stage entered variable: Family income.

Table 5.
Logistic regression model estimation to survival of teeth #47
Variable B S.E. Significance probability Exp (B)
Educational standards 0.141 0.049 0.004 1.151
Economic activity 0.000
High rank executives and staff member or manager Standard
Expert, technician ―1.582 0.643 0.014 0.206
Clerk ―1.511 0.650 0.020 0.221
Service workers ―1.930 0.635 0.002 0.145
Functional workers ―2.163 0.634 0.001 0.115
Agriculture, animal husbandry, fishing industry ―2.123 0.640 0.001 0.120
Soldier and et cetera ―2.072 0.639 0.001 0.126
Age ―0.082 0.004 0.000 0.922
Toothbrushing number ―0.173 0.047 0.000 0.842
Constant 7.288 0.741 0.000 1,462.554

1 Stage entered variable: Age, 2 Stage entered variable: Economic activity, 3 Stage entered variable: Toothbrushing number, 4 Stage entered variable:Educational standards.

Table 6.
Statistical significance per variable (activity exclusion per job
Variable Molar
#17 #27 #37 #47
Age N N N N
Economic activity* P P P P
Diabetes* X N X X
Sex (male-based)* X X N X
Family income X X P X
Smoking period N X X X
Toothbrushing number N N X N
Cookie intake X N X X
Educational standards* X X X P

*Nominal variable. P, Significance of positive; N, Significance of negative; X is no signi cance.

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