RESULTS: Of 963 participants, 451 (46.8%) had depression and 512 (53.2%) had no depression who were either normal (n = 169, 17.5%) or had distress (n = 343, 35.6%). Participants had higher odds of having depression when living with two people (adjusted odds ratio [AOR] = 3.896, p = 0.001), three people (AOR = 2.622, p < 0.001) or four people (AOR = 3.135, p < 0.001). Participants with three children had higher odds of having depression (AOR = 2.084, p = 0.008), whereas having only one child was a protective factor for depression (AOR = 0.481, p = 0.01). Participants had higher odds of having depression when self-employed (AOR = 3.825, p = 0.003), retired (AOR = 4.526, p = 0.001), being housekeeper (AOR = 7.478, p = 0.004), not working by choice (AOR = 5.511, p < 0.001), or unemployed (AOR = 3.883, p = 0.009). Participants had higher odds of depression when living in a small town (AOR = 3.193, p < 0.001) or rural area (AOR = 3.467, p < 0.001). Participants with no chronic medical illness had lower odds of having depression (AOR = 0.589, p = 0.008).
CONCLUSION: In Malaysia during the COVID-19 pandemic, people who are living with two, three, or four people, having three children, living in a small town or rural areas, and having unstable income have higher odds of having depression. Urgent intervention for those at risk of depression is recommended.
MATERIALS AND METHODS: This is an observational cross-sectional study. A protocol gathering sociodemographic variables as well as depression, anxiety and suicidality and conspiracism was assembled, and data were collected anonymously and online from April 2020 through March 2021. The sample included 12,488 subjects from 11 countries, of whom 9,026 were females (72.2%; aged 21.11 ± 2.53), 3,329 males (26.65%; aged 21.61 ± 2.81) and 133 "non-binary gender" (1.06%; aged 21.02 ± 2.98). The analysis included chi-square tests, correlation analysis, ANCOVA, multiple forward stepwise linear regression analysis and Relative Risk ratios.
RESULTS: Dysphoria was present in 15.66% and probable depression in 25.81% of the total study sample. More than half reported increase in anxiety and depression and 6.34% in suicidality, while lifestyle changes were significant. The model developed explained 18.4% of the development of depression. Believing in conspiracy theories manifested a complex effect. Close to 25% was believing that the vaccines include a chip and almost 40% suggested that facemask wearing could be a method of socio-political control. Conspiracism was related to current depression but not to history of mental disorders.
DISCUSSION: The current study reports that students are at high risk for depression during the COVID-19 pandemic and identified specific risk factors. It also suggested a role of believing in conspiracy theories. Further research is important, as it is targeted intervention in students' groups that are vulnerable both concerning mental health and conspiracism.
METHODS: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
RESULTS: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
CONCLUSION: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.
METHOD: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density.
RESULTS: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001).
CONCLUSION: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.
METHODS: Data analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun's electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries).
RESULTS: This analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p
MATERIAL AND METHODS: During the COVID-19 pandemic, an online questionnaire gathered data from 55,589 participants from 40 countries (64.85% females aged 35.80 ± 13.61; 34.05% males aged 34.90±13.29 and 1.10% other aged 31.64±13.15). Distress and probable depression were identified with the use of a previously developed cut-off and algorithm respectively.
STATISTICAL ANALYSIS: Descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses and Factorial Analysis of Variance (ANOVA) tested relations among variables.
RESULTS: Probable depression was detected in 17.80% and distress in 16.71%. A significant percentage reported a deterioration in mental state, family dynamics and everyday lifestyle. Persons with a history of mental disorders had higher rates of current depression (31.82% vs. 13.07%). At least half of participants were accepting (at least to a moderate degree) a non-bizarre conspiracy. The highest Relative Risk (RR) to develop depression was associated with history of Bipolar disorder and self-harm/attempts (RR = 5.88). Suicidality was not increased in persons without a history of any mental disorder. Based on these results a model was developed.
CONCLUSIONS: The final model revealed multiple vulnerabilities and an interplay leading from simple anxiety to probable depression and suicidality through distress. This could be of practical utility since many of these factors are modifiable. Future research and interventions should specifically focus on them.
METHODS: Data for 6972 patients with bipolar I disorder were obtained at 75 collection sites in 41 countries in both hemispheres. The best model to assess the relation between the threshold for UVB sufficient for vitamin D production and age of onset included 1 or more months below the threshold, family history of mood disorders, and birth cohort. All coefficients estimated at P ≤ 0.001.
RESULTS: The 6972 patients had an onset in 582 locations in 70 countries, with a mean age of onset of 25.6 years. Of the onset locations, 34.0% had at least 1 month below the threshold for UVB sufficient for vitamin D production. The age of onset at locations with 1 or more months of less than or equal to the threshold for UVB was 1.66 years younger.
CONCLUSION: UVB and vitamin D may have an important influence on the development of bipolar disorder. Study limitations included a lack of data on patient vitamin D levels, lifestyles, or supplement use. More study of the impacts of UVB and vitamin D in bipolar disorder is needed to evaluate this supposition.
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.
METHODS: Data from 7488 patients with BD I were collected at 75 sites in 42 countries. The first episode occurred at 591 onset locations in 67 countries at a wide range of latitudes in both hemispheres. Solar insolation values were obtained for every onset location, and the ratio of the minimum mean monthly insolation to the maximum mean monthly insolation was calculated. This ratio is largest near the equator (with little change in solar insolation over the year), and smallest near the poles (where winter insolation is very small compared to summer insolation). This ratio also applies to tropical locations which may have a cloudy wet and clear dry season, rather than winter and summer.
RESULTS: The larger the change in solar insolation throughout the year (smaller the ratio between the minimum monthly and maximum monthly values), the greater the likelihood the first episode polarity was depression. Other associated variables were being female and increasing percentage of gross domestic product spent on country health expenditures. (All coefficients: P ≤ 0.001).
CONCLUSION: Increased awareness and research into circadian dysfunction throughout the course of BD is warranted.
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.