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The curvilinear relationship between the age of adults and their mental health in Iran after its peak of COVID-19 cases
Jiyao Chen; Stephen X. Zhang; Yifei Wang; Asghar Afshar Jahanshahi; Maryam Mokhtari Dinani; Abbas Nazarian Madavani; Khaled Nawaser.
Affiliation
  • Jiyao Chen; Oregon State University
  • Stephen X. Zhang; University of Adelaide
  • Yifei Wang; Tongji University
  • Asghar Afshar Jahanshahi; Pontificia Universidad Catolica del Peru
  • Maryam Mokhtari Dinani; Alzahra University
  • Abbas Nazarian Madavani; Shahid Rajaee Teacher Training University
  • Khaled Nawaser; Arvandan Non-profit Higher Education Institute
Preprint in English | medRxiv | ID: ppmedrxiv-20128132
ABSTRACT
The emerging body of research on the predictors of mental health in the COVID-19 pandemic has revealed contradictory findings, which prevent effective psychiatry screening for mental health assistance. This study aims to identify the predictors of nonsomatic pain, depression, anxiety, and distress, especially focusing on age as a nonlinear predictor. We conducted a survey of 474 adults in Iran during April 1-10, 2020, when Iran had just passed its first peak of the COVID-19 pandemic with new confirmed cases. We found that Age had a curvilinear relationship with nonsomatic pain, depression, and anxiety. Age was associated with pain, depression, and anxiety disorders negatively among adults younger than 45 years, but positively among seniors older than 70 years. Adults who were female, unsure about their chronic diseases, and exercised less per day were more likely to have mental health issues. This study advances the use of age as an effective predictor by uncovering a curvilinear relationship between individuals age and mental health issues by using a sample of adults across a wide spectrum of ages. We hope future research on mental health during COVID-19 pays more attention to nonlinear predictors.
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Observational study / Prognostic study Language: English Year: 2020 Document type: Preprint
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