Comparing individual-, family-, and community-level effects on the oral health of preschool children: a multilevel analysis of national survey data

Abstract

Background Early childhood is a critical stage for the prevention of dental caries. The prevalence of caries in preschool children is still high in Taiwan, where National Health Insurance covers 99% of the population. The effort to improve the oral health of preschool children should be based on conceptual model that encompasses more than individual-level factors. This study input nationwide survey data in a conceptual model to evaluate the effects of comprehensive factors related to the high prevalence of caries in preschool children. Methods This observation study examined factors related to the oral health of preschool children by employing a comprehensive multilevel model to analyse nationally representative data from the Taiwan Oral Health Survey of Preschool Children (TOHPC) 2017–2018. Individual-level, family-level and community-level contextual effects were evaluated through multilevel analysis in this study. The proportional change in variance (PCV) was used to compare the multilevel model with the null model and individual-level, family-level, and community-level context effects. Results The estimated deft index for preschool children was 1.34 (1.22–1.47) at age 3, 2.20 (2.08–2.32) at age 4, and 3.05 (2.93–3.18) at age 5. The overall prevalence of caries in preschool children in Taiwan was 34.27% (30.76%, 37.78%) at age 3, 51.67% (48.99%, 54.35%) at age 4, and 62.05% (59.66%, 64.44%) at age 5. The model that included the individual-, family-, and community-context levels exhibited the highest reduction of variance (PCV = 53.98%). The PCV was further reduced to 35.61% when only the level of accessibility to dental services for individuals, families, and the community was considered. For the model in which no community-context cofactors were considered and the model considering only the individual level, the PCVs were 20.37% and 5.52%, respectively. Conclusions Our findings indicate the key components that affect oral health in preschool children and can serve as a reference for policy makers. The most notable finding of this study is that to improve the oral health of preschool children, community-level factors should be targeted. To rely solely on dentists for leading oral health education programs for children is impractical and inefficient. Training more professional oral health educators to provide additional community-based oral health promotion campaigns is critical. We suggest training more professional oral health educators to provide more community-based oral health promotion campaigns.

Involvement of Different Stakeholder Groups in Ensuring Children’s Dental Public Health: Analysis and Perspectives

“…Враховуючи те, що зміцнення стоматологічного громадського здоров'я потребує комплексного підходу, який об'єднує зусилля різних стейкхолдерів: медичних спеціалістів, громадськості, урядових структур, недержавних організацій та інших груп [6], великої актуальності набуває аналіз доцільності долучення різних зацікавлених сторін у процес його забезпечення для дитячого населення, що і стало підґрунтям для проведення даного дослідження.…”

“…Середній рівень підтримки таких функції із забезпечення стоматологічного ГЗ дітей, як використання правових та управлінських інструментів для профілактики хвороб порожнини рота і покращення стану стоматологічного здоров'я дитячого населення та наукове забезпечення системи стоматологічного громадського здоров'я дитячого населення може вказувати на те, що деякі аспекти управління та правові норми можуть бути вдосконалені для підвищення ефективності стоматологічного ГЗ. Важливо враховувати, що науковий підхід може визначати ефективність профілактичних заходів та лікування, тому це необхідно враховувати при розробці стратегій вдосконалення [6].…”

Professional Development: Theoretical Basis and Innovative Technologies

“…The names of the variables are taken from the World Bank's World Development Indicators (2023) and a dataset indicating the historic implementation of carbon taxes and ETS around the world by Ritchie & Rosado (2022). The full list of variables is presented in Table 1 with their respective descriptions and the form in which they are used in the regression analysis.…”

“…Problems such as political pressure to reduce carbon taxes may also lower overall efficiency as decision-makers may not have confidence in a pricing mechanism that may not be active in the future. Thus, the focus should be directed to the appropriate design of carbon pricing mechanisms and political feasibility in a given country.MethodologyThe dataset was compiled from the World Bank's(2023) World Development Indicators, supplemented with information on carbon taxation and Emissions Trading Systems from Our World in Data (Ritchie & Rosado, 2022). The paper utilizes a panel dataset consisting of various European countries, covering a period from 2000 to 2014.…”