Social gradients in oral health status in Korea population

Inequalities by sex on remaining teeth in adults: A decomposition analysis

OBJECTIVE

To identify which social determinants of health explain the gap in the remaining teeth between men and women.

METHODS

A secondary analysis of data from the Chilean National Health Survey (CNHS) 2016-2017 was performed on the number of remaining teeth in adults. The explanatory variables were organized into structural and intermediate social determinants of health according to the WHO framework. The contribution of both groups and the contribution of each individual explanatory variable to the remaining teeth gap was estimated using the Blinder-Oaxaca decomposition analysis.

RESULTS

The predicted average number of remaining teeth for men was 23.4 and 21.0 for women, thus a mean difference of 2.4 teeth. 49.8% of the inequality between men and women was due to the different distribution (endowments) of the predictors in the model. Among them, structural determinants of health, namely education level (15.8%) and employment status (17.8%), contributed the most. Intermediate determinants had no relevant contribution to explain the gap.

CONCLUSIONS

Results revealed that the difference in the mean number of remaining teeth between men and women was mainly explained by two structural determinants: education level and employment status. The lack of explanatory power of intermediate determinants and the large explanatory power of structural determinants means that tackling oral health inequity in Chile requires strong political commitment. The role of intersectoral and intersectional public policies to address gender inequalities in oral health in Chile is discussed.

The effects of orthodontic treatment on personal dental expenditures in South Korea: a follow-up study using Korean health panel survey

BACKGROUND

This study aimed to investigate the effects of orthodontic treatment on cumulative out-of-pocket (OOP) expenditures for up to 8 years and the factors contributing to changes in individual OOP dental expenses.

METHODS

The data of adults aged ≥19 years, 218 with experience of orthodontic treatment (OT group) and 654 without experience of orthodontic treatment (non-OT group) were extracted from the Korea Health Panel Survey between 2009 and 2017 using the propensity score matching method. The total personal OOP expenditure for dental care incurred after orthodontic treatment in the OT group and that incurred in the matched non-OT group were calculated. Since dependent variables, cumulative dental expenditures, were continuous with excess zeros, Tweedie compound Poisson linear models were used to explore the influence of orthodontic treatment experience and demographic and socioeconomic factors, including private insurance, on per capita OOP dental expenditures.

RESULTS

The OT group had socioeconomic characteristics distinct from those of general dental patients. The Box-Cox transformed per capita OOP expenditures for dental care in the OT group were lower than those in the non-OT group (P < 0.05). When all covariates were held constant, the non-OT group spent 1.4-times more on OOP dental expenditures, but this was not statistically significant (P > 0.1). The data from those with higher incomes revealed the opposite trend (P < 0.05), while the other covariates were not statistically significant.

CONCLUSIONS

Orthodontic treatment had no positive or negative effect on future oral care use. This finding is similar to the inconsistent results of previous clinical studies on oral health and orthodontic treatment.

Trends in Self-Rated Poor Oral Health Among all Age Populations in Korea from 2007 to 2015: Monitoring Expansion of Dental Insurance

OBJECTIVES

This study explored trends in self-rated poor oral health (SRPOH) from 2007 to 2015 among all age groups to monitor changes after the expansion of dental insurance.

METHODS

Repeated cross-sectional data from 2007 to 2015 Korea National Health and Nutrition Examination Surveys were collected and analysed. The respondents (n = 20,199) were categorised into four age groups: 0-19, 20-44, 45-64, and ≥65 years. The outcome variable was SRPOH, with independent variables being socioeconomic factors, sex, household income, and education. The age-sex standardised prevalence rate was calculated to determine trends, and complex samples logistic regression analysis was performed to confirm the factors affecting SRPOH.

RESULTS

Self-rated poor oral health prevalence decreased significantly from 2007 to 2009 (25%) to 2013 to 2015 (14%) in the age groups of 0-19 and 20-44 years (P < 0.05), whereas the SRPOH prevalence in the age groups of 45-64 and ≥65 years did not undergo any significant changes. Although the prevalence decreased by 6% among older adults, over 40% older women still experienced SRPOH. A sex gap increased with age but did not change over time. SRPOH was strongly associated with sex, income, and education across all age groups; the association did not notably change from 2007 to 2015.

CONCLUSIONS

Self-rated poor oral health improved among younger people in Korea. The gender gap in the prevalence increased with age and persisted over time. However, income was the strongest determinant of SRPOH among all age groups, regardless of dental insurance expansion. Further studies should aim to draw causal inferences to explore the policy impact of dental insurance benefits.

Self-reported oral hygiene practices with emphasis on frequency of tooth brushing: A cross-sectional study of Mexican older adults aged 60 years or above

The objective of the study was to characterize self-reported oral hygiene practices among Mexican older adults aged ≥60 years, and to measure the association between frequency of tooth brushing and a set of sociodemographic, socioeconomic, and dental variables.We conducted a cross-sectional study of 139 older adults aged ≥60 years in Pachuca, Mexico. A questionnaire and a clinical dental examination were administered to identify specific variables. We determined frequency of tooth brushing (or cleaning of dentures or prostheses) and use of toothpaste, mouthwash, and dental floss among respondents. Non-parametric testing was performed for statistical analysis and a multivariate logistic regression model was generated with Stata 11 software to determine frequency of tooth brushing.In our study sample, 53.2% of participants reported brushing their teeth at least once a day, 50.4% always using toothpaste, 16.5% using mouthwash and 3.6% using floss for their oral hygiene. In general, younger and female respondents used oral hygiene aids more than the others. Our multivariate model yielded an association (P < .05) between tooth brushing at least once daily and the following variables: having functional dentition (OR = 12.60), lacking health insurance (OR = 3.72), being retired/pensioned (OR = 4.50), and suffering from a chronic disease (OR = 0.43).The older adults in our sample exhibited deficient oral hygiene behaviors. The results suggest certain socioeconomic inequalities in oral health. The findings of this study should be considered when designing dental care instructions for older adults.

Out-Of-Pocket Expenditures on Dental Care for Schoolchildren Aged 6 to 12 Years: A Cross-Sectional Estimate in a Less-Developed Country Setting

Aim: The objective of this study was to estimate the Out-Of-Pocket Expenditures (OOPEs) incurred by households on dental care, as well as to analyze the sociodemographic, economic, and oral health factors associated with such expenditures. Method: A cross-sectional study was conducted among 763 schoolchildren in Mexico. A questionnaire was distributed to parents to determine the variables related to OOPEs on dental care. The amounts were updated in 2017 in Mexican pesos and later converted to 2017 international dollars (purchasing power parities-PPP US $). Multivariate models were created: a linear regression model (which modeled the amount of OOPEs), and a logistic regression model (which modeled the likelihood of incurring OOPEs). Results: The OOPEs on dental care for the 763 schoolchildren were PPP US $53,578, averaging a PPP of US $70.2 ± 123.7 per child. Disbursements for treatment were the principal item within the OOPEs. The factors associated with OOPEs were the child's age, number of dental visits, previous dental pain, main reason for dental visit, educational level of mother, type of health insurance, household car ownership, and socioeconomic position. Conclusions: The average cost of dental care was PPP US $70.2 ± 123.7. Our study shows that households with higher school-aged children exhibiting the highest report of dental morbidity-as well as those without insurance-face the highest OOPEs. An array of variables were associated with higher expenditures. In general, higher-income households spent more on dental care. However, the present study did not estimate unmet needs across the socioeconomic gradient, and thus, future research is needed to fully ascertain disease burden.