Interaction between mental disorders and social disconnectedness on mortality: a population-based cohort study.

BACKGROUND: Despite the recognised importance of mental disorders and social disconnectedness for mortality, few studies have examined their co-occurrence. AIMS: To examine the interaction between mental disorders and three distinct aspects of social disconnectedness on mortality, while taking into account sex, age and characteristics of the mental disorder. METHOD: This cohort study included participants from the Danish National Health Survey in 2013 and 2017 who were followed until 2021. Survey data on social disconnectedness (loneliness, social isolation and low social support) were linked with register data on hospital-diagnosed mental disorders and mortality. Poisson regression was applied to estimate independent and joint associations with mortality, interaction contrasts and attributable proportions. RESULTS: A total of 162 497 individuals were followed for 886 614 person-years, and 9047 individuals (5.6%) died during follow-up. Among men, interaction between mental disorders and loneliness, social isolation and low social support, respectively, accounted for 47% (95% CI: 21-74%), 24% (95% CI: -15 to 63%) and 61% (95% CI: 35-86%) of the excess mortality after adjustment for demographics, country of birth, somatic morbidity, educational level, income and wealth. In contrast, among women, no excess mortality could be attributed to interaction. No clear trends were identified according to age or characteristics of the mental disorder. CONCLUSIONS: Mortality among men, but not women, with a co-occurring mental disorder and social disconnectedness was substantially elevated compared with what was expected. Awareness of elevated mortality rates among socially disconnected men with mental disorders could be of importance to qualify and guide prevention efforts in psychiatric services.

Prior psychiatric morbidity and differential psychopharmacological treatment patterns: Exploring the heterogeneity of bipolar disorder in a nationwide study of 9594 patients.

OBJECTIVES: Individuals with bipolar disorders (BD) have heterogenic pre-onset illness courses and responses to treatment. The pattern of illness preceding the diagnosis of BD may be a marker of future treatment response. Here, we examined associations between psychiatric morbidity preceding the diagnosis of BD and pharmacological treatment patterns in the 2 years following diagnosis. METHODS: In this register-based study, we included all patients with a diagnosis of BD attending Danish Psychiatric Services between January 1, 2012 and December 31, 2016. We examined the association between a diagnosis of substance use disorder, psychosis (other than schizophrenia or schizoaffective disorder), unipolar depression, anxiety/OCD, PTSD, personality disorder, or ADHD preceding BD and pharmacological treatment patterns following the diagnosis of BD (lithium, valproate, lamotrigine, antidepressants, olanzapine, risperidone, and quetiapine) via multivariable Cox proportional hazards regression adjusted for age, sex, and year of BD diagnosis. RESULTS: We included 9594 patients with a median age of 39 years, 58% of whom were female. Antidepressants, quetiapine, and lamotrigine were the most commonly used medications in BD and were all linked to prior depressive illness and female sex. Lithium was used among patients with less diagnostic heterogeneity preceding BD, while valproate was more likely to be used for patients with prior substance use disorder or ADHD. CONCLUSION: The pharmacological treatment of BD is linked to psychiatric morbidity preceding its diagnosis. Assuming that these associations reflect well-informed clinical decisions, this knowledge may inform future clinical trials by taking participants' prior morbidity into account in treatment allocation.

Association between lithium treatment and renal, thyroid and parathyroid function: A cohort study of 6659 patients with bipolar disorder.

OBJECTIVES: Although potential adverse effects of lithium treatment on renal and endocrine systems have been extensively investigated, most prior studies are limited by selected populations and short follow-up. METHODS: Within the Psychiatric Services of the Central Denmark Region, we identified all patients with bipolar disorder and ≥1 serum-lithium (se-Li) measurements between January 1, 2013, and July 20, 2022, and reference patients with bipolar disorder matched on age, sex, and baseline creatinine. Outcomes were diagnoses of renal, thyroid and parathyroid disease, and blood tests measuring creatinine, estimated glomerular filtration rate (eGFR), thyroid-stimulating hormone (TSH), parathyroid hormone (PTH) and calcium. Analyses included unadjusted multilevel regression to describe changes in biochemical markers, and adjusted Cox regression to compare rates of disease/biochemical outcomes between lithium users and reference patients. RESULTS: Among 1646 lithium users (median age 36 years, 63% women) and 5013 reference patients, lithium users had decreasing TSH and eGFR, stable PTH, and increasing calcium levels over time. Lithium use was associated with increased rates of renal, thyroid and parathyroid disease, and levels of biochemical markers outside normal ranges (hazard rate ratios: 1.07-11.22), but the absolute number of severe outcomes was low (e.g., chronic kidney disease: N = 10, 0.6%). Notably, the rate of blood testing was substantially higher among lithium users than among reference patients (e.g., mean number of creatinine tests during the second year of follow-up: lithium users = 2.5, reference patients = 1.4). CONCLUSIONS: Severely adverse renal and endocrine outcomes are rare during lithium treatment. Observational studies of long-term lithium treatment are prone to detection bias.

Development and validation of a machine learning model for prediction of type 2 diabetes in patients with mental illness.

BACKGROUND: Type 2 diabetes (T2D) is approximately twice as common among individuals with mental illness compared with the background population, but may be prevented by early intervention on lifestyle, diet, or pharmacologically. Such prevention relies on identification of those at elevated risk (prediction). The aim of this study was to develop and validate a machine learning model for prediction of T2D among patients with mental illness. METHODS: The study was based on routine clinical data from electronic health records from the psychiatric services of the Central Denmark Region. A total of 74,880 patients with 1.59 million psychiatric service contacts were included in the analyses. We created 1343 potential predictors from 51 source variables, covering patient-level information on demographics, diagnoses, pharmacological treatment, and laboratory results. T2D was operationalised as HbA1c ≥48 mmol/mol, fasting plasma glucose ≥7.0 mmol/mol, oral glucose tolerance test ≥11.1 mmol/mol or random plasma glucose ≥11.1 mmol/mol. Two machine learning models (XGBoost and regularised logistic regression) were trained to predict T2D based on 85% of the included contacts. The predictive performance of the best performing model was tested on the remaining 15% of the contacts. RESULTS: The XGBoost model detected patients at high risk 2.7 years before T2D, achieving an area under the receiver operating characteristic curve of 0.84. Of the 996 patients developing T2D in the test set, the model issued at least one positive prediction for 305 (31%). CONCLUSION: A machine learning model can accurately predict development of T2D among patients with mental illness based on routine clinical data from electronic health records. A decision support system based on such a model may inform measures to prevent development of T2D in this high-risk population.

Risk of Mania After Methylphenidate in Patients With Bipolar Disorder.

BACKGROUND: Bipolar disorder and attention-deficit/hyperactivity disorder are common comorbidities. Attention-deficit/hyperactivity disorder is commonly treated with stimulants (eg, methylphenidate), which, however, have been suggested to cause treatment-emergent mania in patients with bipolar disorder. Here, we assessed the risk of mania, depressive episodes, and psychiatric admissions after initiation of methylphenidate treatment in patients with bipolar disorder. METHODS: Using Danish health registries, we identified all individuals registered with a diagnosis of bipolar disorder from January 1, 2000, to January 1, 2018, who were treated with methylphenidate. We applied a 1-year mirror-image model to compare the occurrence of mania, depression, and psychiatric admissions in the period leading up to and after methylphenidate treatment initiation. We furthermore assessed the trend in these outcomes from 4 years before to 1 year after initiation of methylphenidate treatment. RESULTS: A total of 1043 patients with bipolar disorder initiated treatment with methylphenidate. The number of manic episodes decreased by 48% after methylphenidate treatment initiation (P = 0.01), both among patients using mood stabilizers (-50%) and among patients not using mood stabilizers (-45%). The number of manic episodes, however, peaked approximately 6 months before methylphenidate. The results were similar for the secondary outcomes. CONCLUSIONS: Initiation of methylphenidate treatment was not associated with an increased risk of mania in patients with bipolar disorder. A decrease in mania, depressive episodes, and psychiatric admissions was observed after methylphenidate. However, these decreases seemed to be driven by regression to the mean after clinical deterioration preceding methylphenidate treatment, rather than by the methylphenidate treatment itself.

Revisiting the association between treatment with antidepressants and mania: A nationwide within-individual study of 3554 patients with bipolar disorder.

INTRODUCTION: Antidepressants are commonly used "off-label" for bipolar depression, despite concerns over the risk of potential treatment-emergent mania (or "manic switch"). Treatment-emergent mania is difficult to study with adequate power in clinical trials as it requires a large group of participants and long follow-up. Therefore, naturalistic register-based studies have been applied to assess this phenomenon. Here, we aimed to replicate previous findings and address key methodological limitations that were not previously taken into account. METHODS: We utilized data from nationwide Danish health registries to identify patients with bipolar disorder treated with an antidepressant, either with or without concomitant treatment with a mood stabilizer (drug treatment proxied via redeemed prescriptions). We plotted the incidence of manic and depressive episodes relative to the initiation of antidepressant treatment and compared the incidence of mania in the period prior to and following initiation of antidepressant treatment (within-individual design). RESULTS: In 3554 patients with bipolar disorder initiating treatment with an antidepressant, the number of manic episodes peaked approximately 3 months prior to initiation of antidepressant treatment, and the number of depressive episodes peaked around the initiation of antidepressant prescription. This temporal pattern suggests that antidepressants were used to treat post-manic depression. CONCLUSION: Within-individual designs do not control sufficiently for confounding by indication, when the treatment indication is time-varying. Thus, results from prior within-individual studies of antidepressant treatment in the context of bipolar disorder may be invalid due to time-varying confounding by indication.

Genetic liability to bipolar disorder and body mass index: A bidirectional two-sample Mendelian randomization study.

OBJECTIVES: Bipolar disorder is associated with increased body mass index (BMI), but it remains undetermined if this association is causal and, if so, in which direction it goes. Here, we sought to answer these questions using bidirectional two-sample Mendelian randomization, a method from genetic epidemiology that uses data from genome-wide association studies (GWAS) to examine whether a risk factor is causal for an outcome METHODS: We used summary statistics from GWAS of bipolar disorder and BMI conducted using data collected by the Psychiatric Genomics Consortium and the UK Biobank, respectively. The genetic instrument for bipolar disorder contained 53 SNPs and explained 0.5% of phenotypic variance, while the genetic instrument for BMI contained 517 SNPs and explained 7.1% of phenotypic variance RESULTS: Our findings suggest that genetic liability to bipolar disorder reduces BMI (slope from Egger regression = -0.195, p = 0.004). It follows that a twofold increase in the genetic liability to bipolar disorder leads to a 0.6 (kg/m2 ) reduction in BMI, predominantly driven by reduced fat mass. Conversely, we found no evidence that BMI causes changes in the risk of developing bipolar disorder CONCLUSION: The results of this study suggest that the increased BMI observed among individuals with bipolar disorder is not a direct consequence of genetic liability to bipolar disorder, but may more likely represent the sum of downstream correlates of manifest bipolar disorder, such as side effects of pharmacological treatment, poor diet, and sedentary lifestyle. As these factors are all modifiable, they can be targeted as part of clinical management.

Pharmacological treatment of bipolar disorder and risk of diabetes mellitus: A nationwide study of 30,451 patients.

OBJECTIVE: While treatment with antipsychotics and antiepileptics have been associated with an increased risk of diabetes mellitus (DM), lithium may have the opposite effect via inhibition of glycogen synthase kinase-3. The aim of this study was to investigate whether treatment of bipolar disorder with lithium, antipsychotics, or antiepileptics is associated with the risk of DM in a real-world clinical setting. METHODS: Using nationwide registers, we identified all patients diagnosed with bipolar disorder in Danish Psychiatric Services from January 1, 1996, to January 1, 2019 (N = 30,451). The risk of developing DM was operationalized via hospital diagnoses and redeemed prescriptions for glucose-lowering drugs. For lithium, antipsychotics, valproate, and lamotrigine, we calculated hazard rate ratios (HRR) for developing DM via adjusted Cox proportional hazards models. Potential cumulative dose-response-like associations were examined using the log-rank test. RESULTS: During follow-up (245,181 person-years), 2107 (6.9%) patients developed DM. Compared with non-users of the respective drugs, we found no clinically or statistically significant difference in the risk of developing DM among patients receiving lithium (n = 11,690; incidence rate of DM/1000 person-years (IR) = 8.87, 95% CI: 8.02-9.90; HRR = 0.94, 95% CI: 0.84-1.06) or lamotrigine (n = 11,785; IR = 7.58, 95% CI: 6.69-8.59; HRR = 0.89, 95% CI: 0.77-1.02), respectively. Conversely, for patients receiving valproate (n = 5171; IR = 12.68, 95% CI: 10.87-14.80; HRR = 1.34, 95% CI: 1.14-1.58) and antipsychotics (n = 22,719; IR = 12.00, 95% CI: 11.14-12.94; HRR = 1.65, 95% CI: 1.45-1.88), respectively, there was increased risk of developing DM. For antipsychotics, we observed a clear cumulative dose-response-like association with the risk of DM. CONCLUSIONS: Treatment with valproate and antipsychotics-but not with lithium and lamotrigine-was associated with increased risk of DM in a real-world cohort of patients with bipolar disorder.

Risk factors for suicide among patients having received treatment with electroconvulsive therapy: A nationwide study of 11,780 patients.

OBJECTIVES: Despite the putative anti-suicidal effect of electroconvulsive therapy (ECT), patients receiving ECT remain at high risk of dying from suicide due to the severity of their underlying mental illness. We aimed to quantify this risk and to identify risk factors for suicide among patients receiving ECT. METHODS: Using nationwide Danish registers, we identified all patients that initiated ECT between 2006 and 2016. These patients were matched on sex and age to 10 reference individuals from the general Danish population. Firstly, we compared 2-year suicide risk between patients initiating ECT and the matched reference individuals. Secondly, we investigated if any patient characteristics were associated with suicide following ECT via Cox proportional hazards regression. RESULTS: A total of 11,780 patients receiving ECT and 117,800 reference individuals were included in the analyses. Among the patients receiving ECT, 161 (1.4%) died from suicide within two years. Compared to the reference individuals, patients having received ECT had a substantially elevated suicide rate (Hazard rate ratio (HRR) = 44.48, 95%CI = 31.12-63.59). Among those having received ECT, the following characteristics were associated with suicide: Male sex (adjusted HRR (AHRR) = 2.32, 95%CI = 1.63-3.30), medium-term higher education (AHRR = 2.64, 95%CI = 1.57-4.44); long-term higher education (AHRR = 3.16, 95%CI = 1.68-5.94), history of substance use disorder (AHRR = 1.51, 95%CI = 1.01-2.26) and history of intentional self-harm/suicide attempt (AHRR = 4.18, 95%CI = 2.76-6.32). CONCLUSIONS: Those who are male, have obtained medium-/long-term higher education, or have a history of substance use disorder or intentional self-harm/suicide attempt, are at particularly elevated risk of suicide following ECT. These findings may guide clinical initiatives to reduce suicides.

Symptom severity and well-being of patients with mental illness during the COVID-19 pandemic: a two-wave survey.

PURPOSE OF THE ARTICLE: To examine changes in symptom severity and well-being during the coronavirus disease 2019 (COVID-19) pandemic among individuals with pre-existing mental illness. MATERIALS AND METHODS: In February 2021, we conducted a follow-up questionnaire-based survey among adults with mental illness, who responded to a similar survey on mental health in June 2020. The participants completed the 18-item Brief Symptom Inventory (BSI-18), the five-item World Health Organization Well-Being Index (WHO-5), and 14 questions evaluating worsening or improvement in mental health using the pre-pandemic period as reference. The survey data were merged with sociodemographic and clinical data from the medical records of all invitees to the first survey, enabling analysis of attrition and weighting of the results. RESULTS: A total of 613 of 992 (62%) invitees participated in the follow-up wave of the survey. The weighted mean WHO-5 and BSI-18 scores were 38 and 27, respectively, and did not differ statistically significantly from the first wave. Multivariate logistic regression showed that having a vocational education (skilled worker/craftsman) was positively associated with reporting deterioration in psychological well-being (OR: 2.95, 95%CI: 1.14-7.81), while being unemployed was negatively associated with reporting deterioration in psychological well-being (OR: 0.20, 95%CI: 0.07-0.56) from the first to the second survey wave. The most common reason for self-reported deterioration in mental health was loneliness (70%). CONCLUSIONS: Approximately one year into the COVID-19 pandemic, the level of symptoms remained high, whereas the level of psychological well-being remained low among patients with mental illness.

Psychometric validation of the full Yale food addiction scale for children 2.0 among adolescents from the general population and adolescents with a history of mental disorder.

OBJECTIVE: Food addiction is a phenotype characterised by an addiction-like attraction to highly processed foods. Adolescence is a sensitive period for developing addictive disorders. Therefore, a valid measure to assess food addiction in adolescents is needed. Accordingly, the aim of the study was to establish a categorical scoring option for the full version of the Yale Food Addiction Scale for Children 2.0 (YFAS-C 2.0), and to psychometrically validate the full YFAS-C 2.0. METHOD: The data stem from the Food Addiction Denmark (FADK) Project. Random samples of 3750 adolescents from the general population aged 13-17 years, and 3529 adolescents with a history mental disorder of the same age were invited to participate in a survey including the full version of the YFAS-C 2.0. A confirmatory factor analysis was carried out and the weighted prevalence of food addiction was estimated. RESULTS: The confirmatory factor analysis of the YFAS-C 2.0 supported a one-factor model in both samples. The weighted prevalence of food addiction was 5.0% in the general population, and 11.2% in the population with a history of mental disorder. CONCLUSIONS: The full version of the YFAS-C 2.0 is a psychometrically valid measure for assessing clinically significant food addiction in adolescents.

Treatment History Characteristics Associated With Use of Isocarboxazid: A Nationwide Register-Based Study.

PURPOSE/BACKGROUND: The monoamine oxidase inhibitor isocarboxazid (Marplan) is occasionally used in the treatment of depression, but there is only little knowledge on the nature of the use of isocarboxazid in clinical practice. We aimed to identify treatment history characteristics associated with this use. METHODS/PROCEDURES: Via the nationwide Danish registers, we identified all adult incident users of isocarboxazid in the period from 2001 to 2018, as well as up to 5 matched controls using another antidepressant (matched on date of redeemed prescription, age, sex, and region of residence). The 5-year treatment history of the isocarboxazid users and the controls was assessed via the Danish registers. The association between treatment history characteristics and isocarboxazid use was examined by multivariate conditional logistic regression. FINDINGS/RESULTS: We identified 1455 isocarboxazid users and 7045 controls using another antidepressant. The following characteristics were associated with statistically significant increased likelihood of receiving isocarboxazid treatment: Prior treatment with a selective serotonin reuptake inhibitor (odds ratio [OR], 1.80 with 95% confidence interval [CI], 1.46-2.23), a serotonin-norepinephrine reuptake inhibitor (OR, 4.90; 95% CI, 4.08-5.89), a noradrenergic and specific serotonergic antidepressant (OR, 1.56; 95% CI, 1.30-1.88), a tricyclic antidepressant (OR, 5.05; 95% CI, 4.19-6.08), other antidepressants (OR, 4.74; 95% CI, 3.74-6.01), lithium (OR, 6.70; 95% CI, 5.08-8.83), an antipsychotic (OR, 1.43; 95% CI, 1.19-1.73), and each diagnosis of depression received in relation to psychiatric hospital treatment (OR, 1.31; 95% CI, 1.23-1.39). Forty percent of those initiating isocarboxazid had received treatment with drugs from 5 or more different psychopharmacological classes in the 5 preceding years. IMPLICATIONS/CONCLUSIONS: These findings suggest that isocarboxazid is typically used for treatment-resistant depression, consistent with guideline recommendations.

Stability of diagnostic coding of psychiatric outpatient visits across the transition from the second to the third version of the Danish National Patient Registry.

OBJECTIVE: In Denmark, data on hospital contacts are reported to the Danish National Patient Registry (DNPR). The ICD-10 main diagnoses from the DNPR are often used as proxies for mental disorders in psychiatric research. With the transition from the second version of the DNPR (DNPR2) to the third (DNPR3) in February-March 2019, the way main diagnoses are coded in relation to outpatient treatment changed substantially. Specifically, in the DNPR2, each outpatient treatment course was labelled with only one main diagnosis. In the DNPR3, however, each visit during an outpatient treatment course is labelled with a main diagnosis. We assessed whether this change led to a break in the diagnostic time-series represented by the DNPR, which would pose a threat to the research relying on this source. METHODS: All main diagnoses from outpatients attending the Psychiatric Services of the Central Denmark Region from 2013 to 2021 (n = 100,501 unique patients) were included in the analyses. The stability of the DNPR diagnostic time-series at the ICD-10 subchapter level was examined by comparing means across the transition from the DNPR2 to the DNPR3. RESULTS: While the proportion of psychiatric outpatients with diagnoses from some ICD-10 subchapters changed statistically significantly from the DNPR2 to the DNPR3, the changes were small in absolute terms (e.g., +0.6% for F2-psychotic disorders and +0.6% for F3-mood disorders). CONCLUSION: The change from the DNPR2 to the DNPR3 is unlikely to pose a substantial threat to the validity of most psychiatric research at the diagnostic subchapter level.

Mental health of patients with mental illness during the COVID-19 pandemic lockdown: a questionnaire-based survey weighted for attrition.

BACKGROUND: Individuals with pre-existing mental illness may be particularly vulnerable to the negative impact that the coronavirus disease 2019 (COVID-19) pandemic seems to have on mental health. Accordingly, the objective of the present study was to assess whether patients with mental illness experienced deterioration in mental health during the COVID-19 lockdown of Denmark in the Spring of 2020. METHODS: We conducted a cross-sectional, questionnaire-based survey coupled with sociodemographic and clinical data from the medical records of all invitees. The latter enabled analysis of attrition and weighting of results. The online questionnaire included the 18-item Brief Symptom Inventory (BSI-18), the five-item World Health Organization Well-Being Index (WHO-5), and 14 questions evaluating worsening or improvement in symptoms during lockdown using the pre-pandemic period as reference. RESULTS: A total of 992 randomly drawn patients with mental illness from the psychiatric services of the Central Denmark Region responded to the questionnaire (response rate = 21.6%). The weighted mean WHO-5 and BSI-18 scores were 38 and 28, respectively. A total of 52% of the respondents reported that their mental health had deteriorated during the lockdown, while 33% reported no change, and 16% reported improvement. The most commonly reported reasons for deterioration were loneliness, disruption of routines, concerns regarding the coronavirus, less contact with family/friends, boredom, and reduced access to psychiatric care. CONCLUSION: More than half of the patients reported worsening of their mental health during the pandemic lockdown. There should be an increased emphasis on ensuring both social and clinical support for individuals with mental illness during pandemics.

Food addiction comorbid to mental disorders in adolescents: a nationwide survey and register-based study.

PURPOSE: Adolescence is a high-risk period for development of addictive behavior. This may also apply to addiction-like eating of highly processed foods-commonly referred to as "food addiction". Adolescents with mental disorder may be at particularly elevated risk of developing food addiction as addiction often accompanies mental disorder. However, there are only few studies in adolescents investigating this potential comorbidity. Therefore, the primary aim of this study was to examine the food addiction symptom load, as measured by the dimensional Yale Food Addiction Scale for Children-version 2.0 (dYFAS-C 2.0), among adolescents with a clinically verified mental disorder. METHOD: A total of 3529 adolescents aged 13-17 were drawn from the Danish Psychiatric Central Research Register, stratified on six major diagnostic categories of mental disorders; psychotic disorders, affective disorders, anxiety disorders, eating disorders, autism spectrum disorders, and attention deficit disorders. Via their parents, these adolescents were invited to participate in a web-based survey. Data on health and socioeconomic factors from the Danish registers were linked to both respondents and non-respondents, allowing for thorough attrition analysis and estimation of weighted dYFAS-C 2.0 scores. RESULTS: A total of 423 adolescents participated in the survey (response rate 12.0%). The mean weighted dYFAS-C 2.0 total score was 13.9 (95% CI 12.6; 14.9) for the entire sample and varied substantially across the diagnostic categories being highest for those with psychotic disorder, mean 18.4 (95% CI 14.6; 14.9), and affective disorders, mean 19.4. (95% CI 16.3; 22.5). Furthermore, the dYFAS-C 2.0 total score was positively correlated with body mass index (BMI) (r = 0.33, p < 0.05). CONCLUSION: Food addiction symptomatology seems to be prevalent among adolescents with mental disorder, particularly affective and psychotic disorders. As obesity is a tremendous problem in individuals with mental disorder further investigation of food addiction in young people with mental disorder is called for. This could potentially aid in the identification of potential transdiagnostic targets for prevention and treatment of obesity in this group. LEVEL OF EVIDENCE: Level IV, Observational cross-sectional descriptive study combined with retrospective register data.

The impact of hospital-diagnosed depression or use of antidepressants on treatment initiation, adherence and HbA1c/LDL target achievement in newly diagnosed type 2 diabetes.

AIMS/HYPOTHESIS: We aimed to assess whether current antidepressant therapy or a history of hospital-diagnosed depression affects diabetes treatment initiation, adherence, and HbA1c and LDL-cholesterol target achievement. METHODS: In this register-based study, we included all individuals from Central and Northern Denmark with newly diagnosed type 2 diabetes, defined as a first-ever HbA1c measurement of ≥48 mmol/mol (6.5%), between 2000 and 2016. Individuals either diagnosed with depression at a psychiatric hospital in the 2 years prior to their diabetes diagnosis or currently receiving treatment with an antidepressant were compared with individuals with type 2 diabetes, but without depression treatment or previous history of depression. Outcome measures included initiation of glucose-lowering drugs and lipid-modifying agents, adherence to these medications (medication possession ratio >80%), and HbA1c (<53 mmol/mol [7%]) and LDL-cholesterol (<2.6 mmol/l) target achievement. The assessment of association between depression or antidepressant treatment and these outcomes was conducted using regression analyses with adjustment for potential confounders. RESULTS: We included a total of 87,650 individuals with first-ever HbA1c-diagnosed type 2 diabetes, of whom 0.9% (n = 784) had hospital-diagnosed depression and 11.4% (n = 9963) currently received antidepressant treatment. Compared with those without depression treatment, treatment with an antidepressant was associated with increased likelihood of glucose-lowering drug initiation (HR 1.39 [95% CI 1.34, 1.44]) and adherence (OR 1.27 [95% CI 1.18, 1.36]), lipid-modifying agent initiation (HR 1.17 [95% CI 1.11, 1.23]) and adherence (OR 1.25 [95% CI 1.09, 1.43]), and achievement of LDL (OR 1.08 [95% CI 1.03, 1.14]) but not HbA1c target (OR 0.99 [95% CI 0.93, 1.06]). The findings were similar for individuals who had hospital-diagnosed depression. CONCLUSIONS/INTERPRETATION: In individuals with newly diagnosed type 2 diabetes, antidepressant treatment and depression were associated with improved diabetes treatment quality. Graphical abstract.

Editorial Perspective: COVID-19 pandemic-related psychopathology in children and adolescents with mental illness.

The coronavirus disease (COVID-19) pandemic is likely to have negative health consequences way beyond those caused by the virus per se - including significant psychological distress. Children and adolescents who already live with a mental illness may be particularly vulnerable to the distress associated with the pandemic - due to, for example, fear of the virus as well as the significant societal changes launched to minimize spread of the virus (social distancing and quarantine). In this editorial perspective, we (a) provide data on COVID-19 pandemic-related psychopathology in children and adolescents from a large psychiatric treatment setting in Denmark, (b) give advice on how the likely harmful effects of the COVID-19 pandemic on the mental health of children and adolescents may be minimized, and (c) propose six lines of research into pandemic-related psychopathology with emphasis on children and adolescents. Finally, we underline the necessity of politicians, health authorities, and funding bodies supporting these research initiatives here and now.

Determining maximal achievable effect sizes of antidepressant therapies in placebo-controlled trials.

OBJECTIVE: Antidepressants outperform placebo with an effect size of around 0.30. It has been suggested that effect sizes as high as 0.875 are necessary for a minimal clinically important difference. Whether such effect sizes are achievable in placebo-controlled trials is unknown. Therefore, we aimed to assess what effect sizes are theoretically achievable in placebo-controlled trials of antidepressants. METHODS: Patient-level analyses comparing Hamilton Depression Rating Scale (HDRS-17) outcomes for simulated antidepressant therapies to placebo-treated participants (n = 2201) from clinical trials of selective serotonin reuptake inhibitors. RESULTS: An optimally effective antidepressant, where all treated participants achieve HDRS-17 scores comparable to those displayed by healthy volunteers (remission-type model), had a maximum effect size of 1.75, with a mean difference of 11.6 points on the HDRS-17. In simulations where patients received an additional 50% symptom reduction over that obtained with placebo (improvement-type model), the maximum effect size was 1.08 with a mean HDRS-17 difference of 7.2. When adjusting for normal rates of treatment discontinuation, maximum effect sizes were 1.10 (remission-type model) and 0.76 (improvement-type model) with HDRS-17 mean differences of 8.8 and 5.6, respectively. CONCLUSIONS: Three methodological issues (i) a large and variable placebo response, (ii) a high rate of dropout and (iii) HDRS-17-ratings significantly larger than zero in healthy volunteers, reduce the degree of treatment-placebo separation achievable in depression trials. Assuming that those who discontinue treatment have only partial response, even a highly effective antidepressant would have difficulties surpassing such effect size cut-offs as have been suggested to signify a minimal clinically important difference.

Food addiction comorbid to mental disorders: A nationwide survey and register-based study.

OBJECTIVE: Substance use disorder is highly prevalent among individuals with mental disorders. However, it remains largely unknown whether this is also the case for "food addiction"-a phenotype characterized by an addiction-like attraction to predominantly highly processed foods with a high content of refined carbohydrates and fat. Therefore, the primary aim of this study was to estimate the weighted prevalence of food addiction among individuals with mental disorders. METHOD: A total of 5,000 individuals aged 18-62 were randomly drawn from eight categories of major mental disorders from the Danish Psychiatric Central Research Register and invited to participate in an online questionnaire-based survey, which included the Yale Food Addiction Scale 2.0. Data on health care and sociodemographics from the Danish registers were linked to all invitees-enabling comprehensive attrition analysis and calculation of the weighted prevalence of food addiction. RESULTS: A total of 1,394 (27.9%) invitees participated in the survey. Across all diagnostic categories, 23.7% met the criteria for food addiction. The weighted prevalence of food addiction was highest among individuals with eating disorders (47.7%, 95%CI: 41.2-54.2), followed by affective disorders (29.4%, 95%CI: 22.9-36.0) and personality disorders (29.0%, 95%CI: 22.2-35.9). When stratifying on sex, the prevalence of food addiction was higher among women in most diagnostic categories. DISCUSSION: Food addiction is highly prevalent among individuals with mental disorders, especially in those with eating disorders, affective disorders and personality disorders. Food addiction may be an important target for efforts aimed at reducing obesity among individuals with mental disorders.

Bipolar disorder and cannabis use: A bidirectional two-sample Mendelian randomization study.

Cannabis use is associated with a number of psychiatric disorders; however, the causal nature of these associations has been difficult to establish. Mendelian randomization (MR) offers a way to infer causality between exposures with known genetic predictors (genome-wide significant single nucleotide polymorphisms [SNPs]) and outcomes of interest. MR has previously been applied to investigate the relationship between lifetime cannabis use (having ever used cannabis) and schizophrenia, depression, and attention deficit hyperactivity disorder (ADHD), but not bipolar disorder, representing a gap in the literature. We conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use. Genetic instruments (SNPs) were obtained from the summary statistics of recent large genome-wide association studies (GWAS). We conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use using inverse variance weighted regression, weighted median regression, and Egger regression. Genetic liability to bipolar disorder was significantly associated with an increased risk of lifetime cannabis use; however, genetic liability to lifetime cannabis use showed no association with the risk of bipolar disorder. The sensitivity analyses showed no evidence for pleiotropic effects. The present findings support a causal effect of liability to bipolar disorder on the risk of using cannabis at least once. No evidence was found for a causal effect of liability to cannabis use on the risk of bipolar disorder. These findings add important new knowledge to the understanding of the complex relationship between cannabis use and psychiatric disorders.