## 4 Discussion  
This study analyzes data from a questionnaire on self-reported health from migrants and refugees in seven countries in the European Union to assess the effect of sociodemographic \begin{table}
\begin{tabular}{l c c} \hline \hline  & **Odds Ratio** & **(95\% Confidence Interval)** \\ \hline \hline \multicolumn{3}{l}{**Model 1**} \\ \hline Education (years) & 1.083 ** & (1.019, 1.145) \\ General health (score) & 1.017 ** & (1.005, 1.030) \\ Age (years) & 1.023 & (0.994, 1.054) \\ Gender (females) & 2.319 ** & (1.236, 4.349) \\ No possession of any kind of permission & 1.187 & (0.637, 2.212) \\ Country of origin \({}^{*}\) & 0.697 & (0.120, 4.067) \\ Nigeria & 0.240 ** & (0.067, 0.860) \\ Syria & 0.160 ** & (0.050, 0.516) \\ Other & 0.406 & (0.132, 1.247) \\ Have at least one child (no) & 1.278 & (0.710, 2.297) \\ \hline \multicolumn{3}{l}{**Model 2**} \\ \hline \hline Education (years) & 1.100 ** & (1.036, 1.168) \\ Mental health (score) & 1.020 ** & (1.007, 1.034) \\ Age (years) & 1.029 ** & (0.997, 1.061) \\ Gender (females) & 2.429 ** & (1.265, 4.663) \\ Possession of any kind of permission & 1.137 & (0.600, 2.155) \\ Country of origin \({}^{*}\) & 0.470 & (0.078, 2.829) \\ Nigeria & 0.208 ** & (0.055, 0.786) \\ Syria & 0.120 ** & (0.035, 0.418) \\ Other & 0.299 ** & (0.094, 0.951) \\ Have at least one child (no) & 1.482 & \\ \hline \multicolumn{3}{l}{**\(p<0.01\); ** \(p<0.05\); \({}^{*}p<0.1\). \({}^{*}\) compared with migrants from Afghanistan.} \\ \end{tabular}
\end{table} 
Table 6: Logistic regression models that investigated the impact of quality of life, presence of any kind of permission and demographics on migrants brushing their teeth daily (dependent variable). \begin{table}
\begin{tabular}{l c c} \hline \hline  & **Odds Ratio** & **(95\% Confidence Interval)** \\ \hline Gender (females) & 1.162 & (0.752, 1.796) \\ Marital status\({}^{+}\) & & \\ Engaged/married/living with partner & 1.311 & (0.763, 2.253) \\ Separated/divorced & 1.521 & (0.578, 4.004) \\ Widowed & 4.387 ** & (1.689, 11.391) \\ No possession of any kind of permission & 0.648 ** & (0.419, 1.001) \\ Have no children & 2.043 ** & (1.271, 3.283) \\ Last visit to the dentist \({}^{++}\) & & \\ \(<\)1 year & 0.436 ** & (0.231, 0.821) \\ \(>\)1 year & 0.322 ** & (0.169, 0.613) \\ \hline \multicolumn{3}{l}{\({}^{**}\)\(p<0.01\); \({}^{**}\)\(p<0.05\); \({}^{*}p<0.1\). \({}^{*}\) compared with single status. \({}^{**}\) compared with never.} \\ \end{tabular}
\end{table} 
Table 5: _Cont._graphic factors, as well as other determinants, that may predict poor self-reported dental health of newly arrived migrants, including discrimination and mental and general health. Of the migrants that comprised the sample, the majority identified as male, designated their country of origin as within the Middle East North Africa (MENA) region, and reported their permission status as legal in their country of interview (i.e., granted asylum). Generally, one out of four migrants had never visited a dentist, while almost half of them reported having poor dental health (a finding corroborated in the literature) [35; 36]. Previous studies identified barriers to oral healthcare (affordability, awareness, and accommodation) and focused on cultural sensitivity in diets to form recommendations for improving dental health and access [37; 38]. Oral health status is influenced by a complex interrelation of factors, as stressed by [PERSON] et al. (2021) [38] and this paper tried to explore different sociodemographic factors, as well as other determinants, that may affect oral healthcare uptake in a specific population with specific vulnerabilities, as reported by the migrants themselves in the context of a large European project. Our study shows that better self-perceived dental health is mainly associated with younger age, higher educational level, legal immigration permission, better general and mental health, childlessness, lower discrimination sense, and never having visited the dentist.