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Association between self‐reported oral disease/conditions and symptoms of depression among Iraqi individuals
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Abstract<sec><title>Aims

The negative impact of oral diseases on the function, economy, and general health of the population is well‐documented. In the last decades, evidence linking increased expression of depression and oral diseases/conditions has significantly increased. The aim of this study is to assess the association between oral disease/conditions and self‐reported symptoms of depression individuals.

Methods

A specially designed questionnaire was distributed via social media for 1 week. It consisted of two main sections; the first section was dedicated to collect demographic variables and self‐reported symptoms of oral diseases. The second section, Patient Health Questionnaire‐9 (PHQ‐9), was used to assess the severity of depression via nine questions using a 4‐point Likert scale. Association between depression and oral disease was determined by linear regression analysis.

Results

A total of 1975 participants responded fully to the questionnaire and were included in the final analysis. The majority of participants, about 60%, showed mild to moderate symptoms of depression, while 8.9% expressed severe symptoms. Oral diseases positively associated with depression were caries, missing teeth, gingival bleeding, gingival recession, teeth mobility, and dry mouth (R2 = .155). In contrast, increased esthetic level of teeth/gingiva significantly decreased the feeling of depression.

Conclusions

Results indicated that oral diseases, particularly those adversely affecting function and esthetics, were associated with symptoms of depression in Iraqi individuals. These findings highlighted the importance of maintaining oral health as part of the general psychological wellbeing of the population.

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Wed Nov 02 2022
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Publication Date
Tue Mar 28 2017
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Compare between simex and Quassi-likelihood methods in estimation of regression function in the presence of measurement error
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       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

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