Somatic multicomorbidity and disability in patients with psychiatric disorders in comparison to the general population: a quasi-epidemiological investigation in 54,826 subjects from 40 countries (COMET-G study).

BACKGROUND: The prevalence of medical illnesses is high among patients with psychiatric disorders. The current study aimed to investigate multi-comorbidity in patients with psychiatric disorders in comparison to the general population. Secondary aims were to investigate factors associated with metabolic syndrome and treatment appropriateness of mental disorders. METHODS: The sample included 54,826 subjects (64.73% females; 34.15% males; 1.11% nonbinary gender) from 40 countries (COMET-G study). The analysis was based on the registration of previous history that could serve as a fair approximation for the lifetime prevalence of various medical conditions. RESULTS: About 24.5% reported a history of somatic and 26.14% of mental disorders. Mental disorders were by far the most prevalent group of medical conditions. Comorbidity of any somatic with any mental disorder was reported by 8.21%. One-third to almost two-thirds of somatic patients were also suffering from a mental disorder depending on the severity and multicomorbidity. Bipolar and psychotic patients and to a lesser extent depressives, manifested an earlier (15-20 years) manifestation of somatic multicomorbidity, severe disability, and probably earlier death. The overwhelming majority of patients with mental disorders were not receiving treatment or were being treated in a way that was not recommended. Antipsychotics and antidepressants were not related to the development of metabolic syndrome. CONCLUSIONS: The finding that one-third to almost two-thirds of somatic patients also suffered from a mental disorder strongly suggests that psychiatry is the field with the most trans-specialty and interdisciplinary value and application points to the importance of teaching psychiatry and mental health in medical schools and also to the need for more technocratically oriented training of psychiatric residents.

Non-binary gender, vulnerable populations and mental health during the COVID-19 pandemic: Data from the COVID-19 MEntal health inTernational for the general population (COMET-G) study.

BACKGROUND: The COVID-19 pandemic has brought significant mental health challenges, particularly for vulnerable populations, including non-binary gender individuals. The COMET international study aimed to investigate specific risk factors for clinical depression or distress during the pandemic, also in these special populations. METHODS: Chi-square tests were used for initial screening to select only those variables which would show an initial significance. Risk Ratios (RR) were calculated, and a Multiple Backward Stepwise Linear Regression Analysis (MBSLRA) was followed with those variables given significant results at screening and with the presence of distress or depression or the lack of both of them. RESULTS: The most important risk factors for depression were female (RR = 1.59-5.49) and non-binary gender (RR = 1.56-7.41), unemployment (RR = 1.41-6.57), not working during lockdowns (RR = 1.43-5.79), bad general health (RR = 2.74-9.98), chronic somatic disorder (RR = 1.22-5.57), history of mental disorders (depression RR = 2.31-9.47; suicide attempt RR = 2.33-9.75; psychosis RR = 2.14-10.08; Bipolar disorder RR = 2.75-12.86), smoking status (RR = 1.15-5.31) and substance use (RR = 1.77-8.01). The risk factors for distress or depression that survived MBSLRA were younger age, being widowed, living alone, bad general health, being a carer, chronic somatic disorder, not working during lockdowns, being single, self-reported history of depression, bipolar disorder, self-harm, suicide attempts and of other mental disorders, smoking, alcohol, and substance use. CONCLUSIONS: Targeted preventive interventions are crucial to safeguard the mental health of vulnerable groups, emphasizing the importance of diverse samples in future research. LIMITATIONS: Online data collection may have resulted in the underrepresentation of certain population groups.

Modeling Suicidality Risks and Understanding the Phenomenon of Suicidality Under the Loupe of Pandemic Context: National Findings of the COMET-G Study in the Russian Population.

BACKGROUND: Suicidality is a complex clinical phenomenon reflecting vulnerability to suicidal behavior which can be explained via the biopsychosocial paradigm and in relationship with a variety of country-specific factors. Data on suicides within the Russian population are inconsistent (from 11.7 up to 25.1 per 100.000), whereas the population's suicidality risks have not been investigated in detail. Suicidality estimates during the multifactorial influence of the COVID-19 pandemic could serve as a basis to learn more about this mental health indicator. METHODS: The current study is a part of the COMET-G international project (40 countries, n=55.589), which represents an analysis of data collected from Russia's general population (n=7714, 33±12 y.o., 61% female) to estimate suicidality using the Risk Assessment Suicidality Scale (RASS) and its relationships with socio-demographic, clinical, and life-habit characteristics during the COVID-19 pandemic. The evaluation of the statistical data (descriptive statistics, ANOVA, LASSO linear regression, significant at α=0.05) was undertaken using TIBCO Statistica. RESULTS: According to the RASS, at least 20.68%, and up to 29.15%, of the general population in Russia demonstrated increased risk of suicidality during the pandemic. Modelling these risks pointed to the key vulnerabilities related to mental and behavioral disorders, such as (i) current severe depression and a history of mental disorders, (ii) bipolar disorder, (iii) use of illicit drugs surprisingly outranking the alcohol misuse, and psychiatric compounds (hypnotics), highlighting sleep quality deterioration, (iv) a history of suicide attempts and self-harm - though not self-reported changes in depression - in response were predictors of the risk of suicidality, which can be explained by the phenomenon of "learned suicidality", a habitual behavioral suicidality pattern completion accumulated over the background. Such (v) socio-demographic indicators as younger age (disregarding the gender factor), a marital status of single, having no children, living with fewer people in the household, a recent increase in family conflicts, increased need for emotional support, decreased need for communication, and not believing in precautionary measures against COVID-19, contributed to the increase of suicidality risk in the context of the pandemic. CONCLUSIONS: The findings of this study revealed new suicide risk factors that should be taken into account in suicidality risk assessments for the Russian population and in the implementation of suicide prevention programs in the region.