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This study evaluates the impact of socio-economic determinants on the initiation of orthodontic treatment in Romania.

July 5, 2026Open Access

Socio-Economic Determinants of Access to Orthodontic Treatment: A Cross-Sectional Study in the Romanian Population

OBOlimpia BuntaIuliu Hațieganu University of Medicine and Pharmacy DJDoina JizdanIuliu Hațieganu University of Medicine and Pharmacy GCGabriela-Ofelia ChiciudeanUniversity of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca

Key Points

This study evaluates the impact of socio-economic determinants on the initiation of orthodontic treatment in Romania.
Cross-sectional questionnaire-based study conducted in 2025
Data collected from 285 adults via online surveys
Analyzed using descriptive statistics, chi-square tests, and multivariable logistic regression
56.5% of respondents reported having undergone orthodontic treatment
Participants older than 30 years were less likely to have treatment (OR = 0.28, 95% CI: 0.12–0.62, p = 0.002)
Higher self-perceived information levels increased likelihood of treatment (OR = 0.75, 95% CI: 0.59–0.96, p = 0.020)

Abstract

Background: Malocclusion has important functional, esthetic, and psychosocial consequences; however, access to orthodontic treatment remains uneven and strongly influenced by socio-economic factors. While these disparities are well documented internationally, evidence from Romania remains limited. This study aimed to evaluate the influence of socio-economic factors on orthodontic treatment initiation within the Romanian population. Methods: A cross-sectional questionnaire-based study was conducted in 2025 using an online survey distributed through social media and community networks. A total of 285 adults were included. Data were analyzed using descriptive statistics, chi-square tests, and multivariable logistic regression. Results: Overall, 56.5% of respondents reported having undergone orthodontic treatment. Age and self-perceived information level were significantly associated with treatment initiation in the multivariable model. Participants older than 30 years were significantly less likely to have undergone orthodontic treatment compared with those aged 18–30 years (OR = 0.28, 95% CI: 0.12–0.62, p = 0.002). Higher levels of self-perceived information were associated with a greater likelihood of having undergone orthodontic treatment (OR = 0.75, 95% CI: 0.59–0.96, p = 0.020). Income and area of residence were not significantly associated with treatment initiation. However, respondents with lower income levels were significantly more likely to perceive treatment cost as a barrier to orthodontic care. Conclusions: Within this surveyed sample, age and self-perceived information level were independently associated with orthodontic treatment initiation. Although income was not associated with treatment uptake, financial cost remained an important perceived barrier, particularly among lower-income respondents. Given the convenience sampling strategy and limited representativeness of the sample, the findings should be interpreted as exploratory and require confirmation in larger population-based studies.

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