Abstract
Purpose
The purpose of this paper is to determine the relationship between socioeconomic status (SES) and oral health among Thai adults.
Design/methodology/approach
This study is a cross-sectional analytical study using secondary data from the 7th Thailand National Oral Health Survey (2012). Age group 35–44 years old samples were used to represent the working age population. Oral health outcome was determined by untreated dental caries. SES was indicated by income, education and occupational groups. Demographic background, oral health-related behavior and access to dental service were adjusted for analysis. Binary logistic regression analysis was performed to determine the relationship between independent variables and oral health outcome.
Findings
People with lower education showed a higher odds ratio for having untreated dental caries before and after controlling for related variables. Those living in the north and northeast, using additional cleaning tools and going to the public provider for dental service also showed better oral health.
Research limitations/implications
The limitation of this study is that the cross-sectional study cannot indicate casual relationships. The national oral health survey was not designed to find relationships between factors. The access to data and measurement of SES was limited. The policy maker should emphasize on people with lower education which have a higher risk for dental caries to improve oral health in disadvantaged groups. Future research should include all related factors in the study including diet and knowledge about oral health. Moreover, oral health outcome is a long-term effect which accumulated through a lifetime. The social class might change over time and so do behaviors.
Originality/value
There is socioeconomic inequality in dental caries of Thai working age population.
Keywords
Citation
Amornsuradech, S. and Vejvithee, W. (2019), "Socioeconomic inequality and dental caries among Thai working age population: Analysis of Thailand National Oral Health Survey", Journal of Health Research, Vol. 33 No. 6, pp. 517-528. https://doi.org/10.1108/JHR-03-2019-0060
Publisher
:Emerald Publishing Limited
Copyright © 2019, Sirinthip Amornsuradech and Warangkana Vejvithee
License
Published in Journal of Health Research. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
Oral health is directly related to general health and quality of life[1]. Dental caries is one of the main oral health problems that affect people of all ages[2]. The global prevalence of untreated dental caries in the permanent teeth was about 35 percent, according to data in 2017[3].
One of the basic determinants that affect a population’s oral health is socioeconomic status (SES). Socioeconomic inequality in oral health is defined as differences in the prevalence or incidence of oral health problems between individual people of higher and lower SES[4]. Environmental and socio-cultural risk factors also relate to oral health with intermediary risk factors such as behavior and oral health services[5]. The lower social classes are at greater risk of illness and mortality compared to their peers in a higher position[6]. Social inequality in oral health is a principal global challenge for improving oral health among populations in spite of attempts to reduce the gap across social hierarchies[5]. However, there are few studies focusing on socioeconomic inequality affecting the oral health status in developing countries including Thailand[7]. Research on inequalities in oral health could help to minimize the gap between the rich and the poor[8].
The Thailand National Oral Health Survey (TNOHS) is one means of obtaining data on the oral health status, behavior and risk factors of oral diseases in the Thai population[9]. Data from the survey are not only used in building oral health policy and programs, but also used in solving oral health problems at the national level and comparing the oral health condition, behavior and related risk factors with previous surveys at national and international levels. The TNOHS reports provide descriptive data of oral health status and related factors of all age groups and comparison between regions, which represent the oral health status of the Thai population.
This study aims to determine the relationship between the SES and oral health outcome of Thai adults using data from The 7th TNOHS (2012). It would provide more understanding of socio-behavioral determinants related to oral health and benefit policymakers involved in improving the status of oral health in Thailand. The study hypothesis is that:
There is a relationship between SES and oral health among the Thai population.
Methods
Source of data
This study used secondary data from the 7th TNOHS which is a cross-sectional national survey conducted in 2012. A stratified multistage sampling technique was used in the survey. The data collection method for TNOHS included oral examination by licensed dentists and an interview. The oral examination was standardized and calibrated among the survey team following WHO Oral Health Survey Methods[10]. In the survey, index age groups were categorized based on different dentition and oral conditions, risk factors and behavior which varied by age group. There were seven age groups including 3, 5, 12, 15, 35-44, 60–69 and 80–89 years old. The population in this study included all samples from the 35–44 years old age group which represents the working age population. Permission to access and use the data was approved by the Dental Health Bureau, Ministry of Public Health, Thailand.
Socioeconomic variables
Income, education and occupational groups were used as indicators of SES. Income refers to average income per month separated by lower income (0–15,000 baht) and higher income (more than 15,000 baht). Education was indicated by the highest education level completed and was separated into completing primary education or lower and at least secondary education. Occupational groups were categorized as Personal Business, Wage-earner/freelance, Agriculture, Housekeeper and others.
Oral health variables
Evidence of untreated dental caries was used as an indicator of oral health status. Untreated caries indicates the prevalence of dental caries at the time of the survey. The outcome was categorized by the number of teeth with untreated dental caries which are “0 dental caries” and “1 or more dental caries.”
Other related variables
Personal background variables
Personal background variables included age, gender, marital status, area of residence, region of residence and diabetes mellitus condition.
Behavioral variables
Factors related to oral health included individual and environmental factors[11]. Additionally, behavior also determined the social determinants of oral health[12]. Data from TNOHS also provided oral health-related behaviors from the interview including tooth brushing, use of fluoride toothpaste and use of additional cleaning tools. Tooth brushing was categorized into brushing at least two times a day or less than two times a day. Use of fluoride toothpaste was categorized into use or no use of fluoride toothpaste. Use of additional cleaning tools included those who use dental floss or an interdental brush. Smoking status refers to non-smokers and smokers which included former smoker and current smoker.
Access to dental service variables
Access to dental service was determined by the frequency of dental visits in the past year, type of dental service use (public or private provider) and health insurance coverage which include Civil Servant Medical Benefits Scheme (CSMBS), Social Security Scheme (SSS) and Universal Coverage (UC).
Ethical consideration
The study was approved by the Ethics Review Committee for Research Involving Human Research Subjects, Health Science Group, Chulalongkorn University (COA No. 095/2018).
Statistical analysis
Data were analyzed with SPSS Software version 22, using Chulalongkorn University’s license. Descriptive analysis was presented in frequency, percentage, for categorical variables and presented in mean and standard deviation for the continuous variable.
The relationship between SES and dental caries was determined by binary logistic regression. Bivariate analysis without controlling for other variables and multivariate analysis with control for different groups of independent variables were performed to assess changes in significance and the coefficient.
Results
A total of 1,518 eligible subjects were included in the study. Distributions of independent and dependent variables are shown in Table I. About fourth-fifths of the population had an average income at 0–15,000 baht per month. Almost 40 percent of the population had completed secondary education with agriculture being the most popular occupation. There were more females than males in this study with about 80.0 percent of them married. Distribution of area and region of residence were distributed according to the sample design. Few people at this age had diabetes. More than 85 percent brushed their teeth twice a day and used fluoride toothpaste, while only 10.7 percent used additional cleaning tools. About 27 percent were current smokers and former smokers. Surprisingly, only 37.7 percent went to the dentist in the past year. More than 70 percent went to a public provider indicating a high percentage of the population with UC coverage. For dental caries status, 35.2 percent of the population presented one or more dental caries.
Bivariate analysis
Table II shows the result from binary logistic regression analysis for dental caries age 35–44 years old. All SES variables presented significant effects of having at least one dental caries. Those who were educated to a lower level and had a lower income significantly showed more odds ratio (OR) of having dental caries compared to those at higher levels. In the comparison of occupations, housekeepers had the highest OR of having dental caries, followed by wage-earners, business and agriculture employees. The personal background showed no significant OR.
Multivariate analysis
Table III shows the multivariate result of SES when controlling for each group of variables. Education obviously showed significant coefficients in all models, while income and occupation did not show any significance. This indicates that people with lower education were more at risk of developing dental caries while other SES variables showed no significant difference in having dental caries.
When controlling for two groups of variables at a time in Table IV, only some variables remained significant. In Model 7, where all variables were controlled, education increased the magnitude but decreased at a significant level. Use of additional cleaning tools was a significant advantage across with those who did not use additional cleaning tools showing higher OR than those who did. Furthermore, the north and northeast regions showed lower OR than Bangkok in all models.
Discussion
This study aimed to determine the relationship between SES and oral health outcome among Thai working age adults using data from the 7th TNOHS. Among all three SES variables, lower educated individuals showed a significantly higher risk for dental caries in the 35–44 years adult population as presented in table III and IV.
Similar to this study, education also showed the strongest associations with dental outcome in one Spanish study for SES inequality. When assessing the role of potential mediators such as behavioral and psychosocial characteristics, associations did not disappear. When including the three indicators of socioeconomic position in the model, attenuated education and income gradients remained and the occupation-related gradient disappeared[13]. A recent study of the Japanese population also found a higher risk for poor oral health in the lower education group[14]. However, for this study, income and occupational groups did not show significant result like other studies[15]. It might be because of the limited measurement in the survey.
Education could lead to health knowledge and increase cognitive skills for health-promoting behavior[16]. People with higher education are aware of their health more than those with a lower education level. Better education could also lead to high income and better occupation together with better social capital[17].
The strength of this study is the reliable outcome variable due to actual oral examination and standardization by dentists which is better than using self-reporting or perception methods. Moreover, the sample was drawn from across regions and provinces across Thailand supplying a broad spectrum of the population. Furthermore, WHO methodology used in the survey makes it possible to compare the result and situation with other countries.
The limitation of this study is that it is a cross-sectional study which cannot tell the causal relationship. Moreover, the national oral health survey was designed to obtain oral health status of Thai population but not to find relationships between factors. The access to data was limited and the measurement of SES was also a limitation. Some related variables such as diet and knowledge about oral health were also not available in the survey.
Policymakers should focus on people with lower education who have a higher risk of dental caries to improve oral health in disadvantaged groups. Future research should include all related factors in the study including diet. Moreover, future surveys should also include all related factors and knowledge about oral health. Furthermore, oral health outcome is a long-term study that requires data accumulated through a lifetime. Because an individual’s behaviors and social class might change over time, it is important to draw attention to this clause too. Performing multilevel analyses or studies of a population’s entire life could expand the understanding of the relationship[18].
Conclusion
SES related to dental caries indicates socioeconomic inequality in oral health amongst Thai working age adults. Education was the most significant factor among socioeconomic variables compared to income and occupation. Area of residence, oral health-related behavior and access to dental service also related to oral health. However, this study could not indicate causal relationships and lack of some related variables. Future policy should emphasize support for disadvantaged groups to improve their oral health.
Distributions of independent and dependent variables
| Variables | n=1,518 | % |
|---|---|---|
| SES | ||
| Income per month (baht) | ||
| 0–15,000 | 1,242 | 81.9 |
| >15,000 | 275 | 18.1 |
| Education | ||
| Primary complete or lower | 928 | 61.1 |
| At least secondary complete | 590 | 38.9 |
| Occupation | ||
| Business | 191 | 12.6 |
| Wage-earner/freelance | 310 | 20.4 |
| Agriculture | 568 | 37.4 |
| Housekeeper | 90 | 5.9 |
| Othersa | 359 | 23.6 |
| Personal background | ||
| Ageb (mean ± SD) | 39.58 ± 2.78 | |
| Gender | ||
| Male | 726 | 47.8 |
| Female | 792 | 52.2 |
| Marital status | ||
| Previously married | 83 | 5.5 |
| Married | 1,215 | 80.0 |
| Single | 220 | 14.5 |
| Area of residence | ||
| Bangkok | 134 | 8.8 |
| Other urban | 465 | 30.6 |
| Rural | 919 | 60.5 |
| Region of residence | ||
| Central | 317 | 20.9 |
| North | 257 | 16.9 |
| Northeast | 554 | 36.5 |
| South | 256 | 16.9 |
| Bangkok | 134 | 8.8 |
| Having diabetes mellitus | ||
| Yes | 49 | 3.5 |
| No | 1,370 | 96.5 |
| Behavior | ||
| Frequency of tooth brushing | ||
| Less than 2 times/day | 127 | 8.4 |
| At least 2 times/day | 1,391 | 91.6 |
| Use of fluoride toothpaste | ||
| No | 197 | 13.0 |
| Yes | 1,317 | 87.0 |
| Use additional cleaning tools | ||
| No | 1,355 | 89.3 |
| Yes | 163 | 10.7 |
| Smoking status | ||
| Smoker | 422 | 27.8 |
| Non-smoker | 1,096 | 72.2 |
| Access to dental service | ||
| Frequency of dental visit | ||
| Less than once a year | 945 | 62.3 |
| At least once a year | 573 | 37.7 |
| Place for dental service | ||
| Public provider | 443 | 76.0 |
| Private provider | 140 | 24.0 |
| Health insurance coverage | ||
| CSMBS | 206 | 13.8 |
| SSS | 226 | 15.2 |
| UC | 1,058 | 71.0 |
| Oral health outcome | ||
| Dental caries | ||
| 0 | 984 | 64.8 |
| ⩾1 | 534 | 35.2 |
Notes: aOthers in occupational groups include employee/government worker, associates of network/clubs, elderly with income, studying and finding a job; bage is presented in mean ± standard deviation (SD); CSMBS, Civil Servant Medical Benefit Scheme; SSS, Social Security Scheme; UC, Universal Health Coverage
Bivariate analysis using binary logistic regression for having one or more dental caries in 35–44 years old age group
| Model 0 | |||
|---|---|---|---|
| Independent variables | OR | p-value | Sig. |
| SES | |||
| Income per month(baht) | |||
| 0–15,000 | 1.375 | 0.028 | * |
| >15,000 (ref) | |||
| Education | |||
| Primary complete or less | 1.745 | <0.000 | *** |
| At least secondary complete (ref) | |||
| Occupation | |||
| Business | 1.665 | 0.007 | ** |
| Wage-earner/freelance | 1.844 | <0.000 | *** |
| Agriculture | 1.227 | 0.165 | |
| Housekeeper | 1.927 | 0.007 | ** |
| Others (ref) | |||
| Personal background | |||
| Age | 1.019 | 0.329 | |
| Gender | |||
| Male | 0.866 | 0.183 | |
| Female | |||
| Marital status | |||
| Previously married | 1.225 | 0.449 | |
| Married | 1.130 | 0.432 | |
| Single (ref) | |||
| Area of residence | |||
| Bangkok | 1.024 | 0.901 | |
| Other urban | 0.880 | 0.286 | |
| Rural (ref) | |||
| Region of residence | |||
| Central | 1.206 | 0.379 | |
| North | 0.951 | 0.821 | |
| Northeast | 0.674 | 0.052 | |
| South | 1.286 | 0.251 | |
| Bangkok (ref) | |||
| Having diabetes mellitus | |||
| Yes | 0.665 | 0.215 | |
| No (ref) | |||
| Behavior | |||
| Frequency of tooth brushing | |||
| Less than 2 times/day | 1.507 | 0.029 | * |
| At least 2 times/day (ref) | |||
| Use of fluoride toothpaste | |||
| No | 1.403 | 0.030 | * |
| Yes(ref) | |||
| Use of additional cleaning tools | |||
| No | 2.626 | <0.000 | *** |
| Yes (ref) | |||
| Smoking status | |||
| Smoker | 1.146 | 0.252 | |
| Non-smoker (ref) | |||
| Access | |||
| Frequency of dental visit | |||
| Less than once a year | 1.098 | 0.401 | |
| At least once a year (ref) | |||
| Place for dental service | |||
| Public provider | 0.774 | 0.205 | |
| Private provider (ref) | |||
| Health insurance coverage | |||
| CSMBS | 0.622 | 0.005 | ** |
| SSS | 0.763 | 0.084 | |
| UC (ref) | |||
Notes: 95% CI; n=1,518. SES, socioeconomic status; ref, reference; CSMBS, Civil Servant Medical Benefit Scheme; SSS, Social Security Scheme; UC, Universal Health Coverage; OR, odds ratio; Sig., significant level; N/C, not calculated due to automatic exclusion during analysis in SPSS. *p⩽0.05; **p⩽0.01; ***p⩽0.001, level of significance of odds ratio
Multivariate analysis using binary logistic regression for having one or more dental caries in 35–44 years old age group (95% CI)
| Model 1 | Model 2 | Model 3 | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Independent variables | OR | p-value | Sig. | OR | p-value | Sig. | OR | p-value | Sig. |
| SES | |||||||||
| Income per month (baht) | |||||||||
| 0–15,000 | 1.308 | 0.103 | 1.028 | 0.861 | 1.465 | 0.158 | |||
| >15,000 (ref) | |||||||||
| Education | |||||||||
| Primary complete or less | 1.765 | <0.000 | *** | 1.644 | <0.000 | *** | 2.361 | <0.000 | *** |
| At least secondary complete (ref) | |||||||||
| Occupation | |||||||||
| Business | 1.250 | 0.288 | 1.191 | 0.391 | 0.828 | 0.649 | |||
| Wage-earner/freelance | 1.238 | 0.277 | 1.170 | 0.404 | 1.119 | 0.749 | |||
| Agriculture | 0.839 | 0.364 | 0.732 | 0.081 | 0.594 | 0.152 | |||
| Housekeeper | 1.050 | 0.863 | 1.243 | 0.420 | 0.933 | 0.877 | |||
| Others (ref) | |||||||||
| Personal background | |||||||||
| Age | 1.016 | 0.440 | |||||||
| Gender | |||||||||
| Male | |||||||||
| Female | 0.964 | 0.761 | |||||||
| Marital status | |||||||||
| Previously married | 1.141 | 0.647 | |||||||
| Married | 0.942 | 0.725 | |||||||
| Single (ref) | |||||||||
| Area of residence | |||||||||
| Bangkok | 0.705 | 0.150 | |||||||
| Other urban | 0.962 | 0.784 | |||||||
| Rural (ref) | |||||||||
| Region of residence | |||||||||
| Central | 0.802 | 0.226 | |||||||
| North | 0.578 | 0.006 | ** | ||||||
| Northeast | 0.492 | <0.000 | *** | ||||||
| South | N/C | N/C | |||||||
| Bangkok (ref) | |||||||||
| Having diabetes mellitus | |||||||||
| Yes | 0.611 | 0.143 | |||||||
| No (ref) | |||||||||
| Behavior | |||||||||
| Frequency of tooth brushing | |||||||||
| Less than 2 times/day | 1.360 | 0.110 | |||||||
| At least 2 times/day (ref) | |||||||||
| Use of fluoride toothpaste | |||||||||
| No | 1.348 | 0.061 | |||||||
| Yes (ref) | |||||||||
| Use of additional cleaning tools | |||||||||
| No | 2.278 | <0.000 | *** | ||||||
| Yes (ref) | |||||||||
| Smoking status | |||||||||
| Smoker | 1.072 | 0.574 | |||||||
| Non-smoker (ref) | |||||||||
| Access | |||||||||
| Frequency of dental visit | |||||||||
| Less than once a year | 0.919 | 0.884 | |||||||
| At least once a year (ref) | |||||||||
| Place for dental service | |||||||||
| Public provider | 0.676 | 0.074 | |||||||
| Private provider (ref) | |||||||||
| Health insurance coverage | |||||||||
| CSMBS | 0.857 | 0.691 | |||||||
| SSS | 0.639 | 0.179 | |||||||
| UC (ref) | |||||||||
| −2 Log likelihood | 1,775.101 | 1,901.215 | 691.109 | ||||||
| Cox & Snell R2 | 0.041 | 0.040 | 0.060 | ||||||
| Nagelkerke R2 | 0.057 | 0.055 | 0.083 | ||||||
Notes: SES, socioeconomic status; ref, reference; CSMBS, Civil Servant Medical Benefit Scheme; SSS, Social Security Scheme; UC, Universal Health Coverage; OR, odds ratio; Sig., significant level; N/C, not calculated due to automatic exclusion during analysis in SPSS. Model 1: SES variables adjusted for background variables; Model 2: SES variables adjusted for behavioral variables; Model 3: SES variables adjusted for access variables. *p⩽0.05; **p⩽0.01; ***p⩽0.001, level of significance of odds ratio
Multivariate analysis using binary logistic regression for having one1 or more dental caries in 35–44 years old age group (95% CI)
| Model 4 | Model 5 | Model 6 | Model 7 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Independent variables | OR | p-value | Sig. | OR | p-value | Sig. | OR | p-value | Sig. | OR | p-value | Sig. |
| SES | ||||||||||||
| Income per month (baht) | ||||||||||||
| 0–15,000 | 1.158 | 0.384 | 1.617 | 0.093 | 1.260 | 0.402 | 1.345 | 0.315 | ||||
| >15,000 (ref) | ||||||||||||
| Education | ||||||||||||
| Primary complete or less | 1.611 | 0.001 | *** | 2.150 | 0.002 | ** | 2.251 | 0.001 | *** | 1.970 | 0.007 | ** |
| At least secondary complete (ref) | ||||||||||||
| Occupation | ||||||||||||
| Business | 1.146 | 0.526 | 1.017 | 0.970 | 0.788 | 0.569 | 0.967 | 0.940 | ||||
| Wage-earner /freelance | 1.109 | 0.605 | 1.347 | 0.423 | 1.026 | 0.944 | 1.282 | 0.509 | ||||
| Agriculture | 0.771 | 0.187 | 0.636 | 0.236 | 0.542 | 0.096 | 0.624 | 0.225 | ||||
| Housekeeper | 0.947 | 0.849 | 0.881 | 0.791 | 0.942 | 0.896 | 0.876 | 0.784 | ||||
| Others (ref) | ||||||||||||
| Personal background | ||||||||||||
| Age | 1.019 | 0.371 | 1.055 | 0.123 | 1.060 | 0.103 | ||||||
| Gender | ||||||||||||
| Male | 0.757 | 0.072 | 0.885 | 0.558 | 0.610 | 0.067 | ||||||
| Female | ||||||||||||
| Marital status | ||||||||||||
| Previously married | 1.105 | 0.732 | 2.114 | 0.142 | 1.764 | 0.272 | ||||||
| Married | 0.901 | 0.547 | 1.007 | 0.980 | 0.832 | 0.552 | ||||||
| Single (ref) | ||||||||||||
| Area of residence | ||||||||||||
| Bangkok | 0.722 | 0.187 | 0.552 | 0.152 | 0.545 | 0.152 | ||||||
| Other urban | 1.008 | 0.957 | 0.875 | 0.564 | 0.926 | 0.745 | ||||||
| Rural (ref) | ||||||||||||
| Region of residence | ||||||||||||
| Central | 0.724 | 0.082 | 0.667 | 0.165 | 0.615 | 0.104 | ||||||
| North | 0.530 | 0.002 | ** | 0.471 | 0.032 | * | 0.438 | 0.022 | * | |||
| Northeast | 0.437 | <0.000 | *** | 0.526 | 0.018 | * | 0.458 | 0.006 | ** | |||
| South | N/C | N/C | N/C | N/C | N/C | N/C | ||||||
| Bangkok (ref) | ||||||||||||
| Having diabetes mellitus | ||||||||||||
| Yes | 0.619 | 0.158 | 1.025 | 0.963 | 1.082 | 0.886 | ||||||
| No (ref) | ||||||||||||
| Behavior | ||||||||||||
| Frequency of tooth brushing | ||||||||||||
| Less than 2 times/day | 1.617 | 0.020 | * | 1.150 | 0.704 | 1.380 | 0.398 | |||||
| At least 2 times/day (ref) | ||||||||||||
| Use of fluoride toothpaste | ||||||||||||
| No | 1.367 | 0.063 | 1.171 | 0.565 | 1.157 | 0.614 | ||||||
| Yes (ref) | ||||||||||||
| Use of additional cleaning tools | ||||||||||||
| No | 2.560 | <0.000 | *** | 2.471 | 0.002 | ** | 2.866 | 0.001 | *** | |||
| Yes (ref) | ||||||||||||
| Smoking status | ||||||||||||
| Smoker | 1.321 | 0.093 | 1.133 | 0.588 | 1.710 | 0.077 | ||||||
| Non-Smoker (ref) | ||||||||||||
| Access | ||||||||||||
| Frequency of dental visit | ||||||||||||
| Less than once a year | 1.121 | 0.848 | 0.954 | 0.936 | 1.170 | 0.797 | ||||||
| At least once a year (ref) | ||||||||||||
| Place for dental service | ||||||||||||
| Public provider | 0.631 | 0.053 | 0.600 | 0.025 | * | 0.521 | 0.009 | ** | ||||
| Private provider (ref) | ||||||||||||
| Health insurance coverage | ||||||||||||
| CSMBS | 0.961 | 0.921 | 0.905 | 0.797 | 1.016 | 0.968 | ||||||
| SSS | 0.706 | 0.318 | 0.641 | 0.187 | 0.709 | 0.330 | ||||||
| UC (ref) | ||||||||||||
| −2 Log likelihood | 1,741.143 | 643.144 | 679.542 | 625.777 | ||||||||
| Cox & Snell R2 | 0.063 | 0.073 | 0.079 | 0.102 | ||||||||
| Nagelkerke R2 | 0.086 | 0.101 | 0.109 | 0.142 | ||||||||
Notes: SES, socioeconomic status; ref. reference; CSMBS, Civil Servant Medical Benefit Scheme; SSS, Social Security Scheme; UC, Universal Health Coverage; OR, odds ratio; Sig: significant level; N/C, not calculated due to automatic exclusion during analysis in SPSS. Model 4: SES variables adjusted for background and behavioral variables; Model 5: SES variables adjusted for background and access variables; Model 6: SES variables adjusted for behavioral and access variables; Model 7: SES variables adjusted for income, education, occupation, personal background, behavioral and access. *p⩽0.05; **p⩽0.01; ***p⩽0.001, level of significance of odds ratio
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Acknowledgements
The authors are grateful to the Dental Health Bureau, Ministry of Public Health, Thailand for their support.