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Prior evidence suggests that physical activity may reduce the risk of multiple diseases and mortality. However, whether and how physical activity affects the aging process remains largely unexplored. We included 284 479 UK Biobank participants and computed leukocyte telomere length (LTL) deviation (ie, the difference between genetically determined and observed LTL) and biological age acceleration (defined as the discrepancy between the phenotypic age of a person and the average phenotypic age in the cohort of individuals with the same age and sex) as the indexes for aging acceleration. Linear and logistic models were used to estimate the associations of self-reported physical activity items and patterns (identified by principal component analysis), as well as accelerometer-assessed physical activity, with aging acceleration. Analyses of physical activity patterns indicated, a higher level of adherence to activity patterns predominated by strenuous sports, other exercises, walking for pleasure, heavy and light housework, and public transportation use was associated with a lower risk of aging acceleration, whereas a higher level of adherence to patterns predominated by job-related activities was associated with a higher risk of aging acceleration. Analysis among 62 418 participants with accelerometer-measured physical activity corroborated these results. Physical activity, such as strenuous sports and other exercises in leisure time and the use of public transportation, was associated with reduced biological aging. Besides highlighting the importance of engaging in physical activity for healthy aging, our results provide further evidence for the beneficial effect of physical activity on the telomere attrition process.

Background: Attention-deficit/hyperactivity disorder (ADHD) and posttraumatic stress disorder (PTSD) are associated, but it is unclear if this is a causal relationship or confounding. We used genetic analyses and sibling comparisons to clarify the direction of this relationship. Methods: Linkage disequilibrium score regression and 2-sample Mendelian randomization were used to test for genetic correlation (r g) and bidirectional causal effects using European ancestry genome-wide association studies of ADHD (20,183 cases and 35,191 controls) and 6 PTSD definitions (up to 320,369 individuals). Several additional variables were included in the analysis to verify the independence of the ADHD-PTSD relationship. In a population-based sibling comparison (N = 2,082,118 individuals), Cox regression models were fitted to account for time at risk, a range of sociodemographic factors, and unmeasured familial confounders (via sibling comparisons). Results: ADHD and PTSD had consistent r g (r g range, 0.43–0.52; p < .001). ADHD genetic liability was causally linked with increased risk for PTSD (β = 0.367; 95% CI, 0.186–0.552; p = 7.68 × 10 −5). This result was not affected by heterogeneity, horizontal pleiotropy (Mendelian randomization Egger intercept = 4.34 × 10 −4, p = .961), or other phenotypes and was consistent across PTSD datasets. However, we found no consistent associations between PTSD genetic liability and ADHD risk. Individuals diagnosed with ADHD were at a higher risk for developing PTSD than their undiagnosed sibling (hazard ratio = 2.37; 95% CI, 1.98–3.53). Conclusions: Our findings add novel evidence supporting the need for early and effective treatment of ADHD, as patients with this diagnosis are at significantly higher risk to develop PTSD later in life.

Background Evidence is scarce regarding the potential modifying role of disease susceptibility on the association between a prior cancer diagnosis and cardiovascular disease (CVD). Methods We conducted a matched cohort study of UK Biobank including 78,860 individuals with a cancer diagnosis between January 1997 and January 2020, and 394,300 birth year and sex individually matched unexposed individuals. We used Cox model to assess the subsequent relative risk of CVD, which was further stratified by individual genetic predisposition. Results During nearly 23 years of follow-up, an elevated risk of CVD was constantly observed among cancer patients, compared to their matched unexposed individuals. Such excess risk was most pronounced (hazard ratio [HR] = 5.28, 95% confidence interval [CI] 4.90–5.69) within 3 months after a cancer diagnosis, which then decreased rapidly and stabilised for >6 months (HR = 1.22, 95% CI 1.19–1.24). For all the studied time periods, stratification analyses by both levels of polygenic risk score for CVD and by family history of CVD revealed higher estimates among individuals with lower genetic risk predisposition. Conclusions Our findings suggest that patients with a recent cancer diagnosis were at an increased risk of multiple types of CVD and the excess CVD risk was higher among individuals with lower genetic susceptibility to CVD, highlighting a general need for enhanced psychological assistance and clinical surveillance of CVD among newly diagnosed cancer patients.

Emerging evidence suggests inflammation is involved in the development of premenstrual disorders (PMDs). We assessed whether childhood asthma and allergies, as inflammatory conditions that may share etiology with PMDs, are associated with risk of PMDs in adulthood. We conducted a prospective cohort study of 6,524 girls in the Growing Up Today Study between 1996 and 2013. Self- and mother-reported diagnoses of asthma and allergies before age 18 were assessed at baseline and updated multiple times during follow-up. Current premenstrual symptoms and cases of PMDs were evaluated using validated tools in 2013. Log-binomial and linear regressions were employed to assess the associations of asthma/allergies with PMDs and premenstrual symptoms (z score), respectively. At a mean (s.d.) age of 25.7 (3.5) years, 19.3% of participants met the criteria for PMDs. Compared with girls free of asthma, those having asthma had an increased risk of PMDs (adjusted risk ratio (aRR) 1.20 [95% CI 1.07 to 1.34]) and increased symptom score (β = 0.13 [95% CI 0.08 to 0.19]). Allergies were positively associated with PMDs (aRR 1.11 [95% CI 0.99 to 1.24]) and premenstrual symptoms (β = 0.09 [95% CI 0.04 to 0.14]). Specifically, the association with PMDs was statistically significant for food allergy (aRR 1.28 [95% CI 1.06 to 1.54]). The associations between asthma/food allergy and PMDs appeared more pronounced for probable premenstrual dysphoric disorder than for premenstrual syndrome. The findings, which show that individuals with childhood asthma or food allergy are at increased risk of PMDs in adulthood, may provide important evidence for future mechanistic research into inflammation and PMDs.

BackgroundPersistence of physical symptoms after SARS-CoV-2 infection is a major public health concern, although evidence from large observational studies remain scarce. We aimed to assess the prevalence of physical symptoms in relation to acute illness severity up to more than 2-years after diagnosis of COVID-19.MethodsThis multinational study included 64 880 adult participants from Iceland, Sweden, Denmark, and Norway with self-reported data on COVID-19 and physical symptoms from April 2020 to August 2022. We compared the prevalence of 15 physical symptoms, measured by the Patient Health Questionnaire (PHQ-15), among individuals with or without a confirmed COVID-19 diagnosis, by acute illness severity, and by time since diagnosis. We additionally assessed the change in symptoms in a subset of Swedish adults with repeated measures, before and after COVID-19 diagnosis.FindingsDuring up to 27 months of follow-up, 22 382 participants (34.5%) were diagnosed with COVID-19. Individuals who were diagnosed with COVID-19, compared to those not diagnosed, had an overall 37% higher prevalence of severe physical symptom burden (PHQ-15 score ≥ 15, adjusted prevalence ratio [PR] 1.37 [95% confidence interval [CI] 1.23-1.52]). The prevalence was associated with acute COVID-19 severity: individuals bedridden for seven days or longer presented with the highest prevalence (PR 2.25[1.85-2.74]), while individuals never bedridden presented with similar prevalence as individuals not diagnosed with COVID-19 (PR 0.92 [0.68-1.24]). The prevalence was statistically significantly elevated among individuals diagnosed with COVID-19 for eight of the fifteen measured symptoms: shortness of breath, chest pain, dizziness, heart racing, headaches, low energy/fatigue, trouble sleeping, and back pain. The analysis of repeated measurements rendered similar results as the main analysis.InterpretationThese data suggest an elevated prevalence of some, but not all, physical symptoms during up to more than 2 years after diagnosis of COVID-19, particularly among individuals suffering a severe acute illness.FundingThis work was mainly supported by grants from NordForsk (COVIDMENT, grant number 105668 and 138929) and Horizon2020 (CoMorMent, 847776). See Acknowledgements for further details on funding.Research in contextEvidence before the studyAs the majority of the global population has contracted COVID-19, persistence of physical symptoms after SARS-CoV-2 infection (LongCOVID or post COVID-19 condition) has become a major public health concern. We searched PubMed for studies assessing physical symptoms after COVID-19, published by March 22, 2023. The search term was (physical symptoms after covid) AND LitCLONGCOVID [Pubmed filter]. We reviewed 82 studies, after excluding those not on humans or not published in English. High prevalence of multiple physical symptoms, mainly fatigue, shortness of breath, headache, muscle and chest pain, has been reported, mostly based on small samples of hospitalized patients confined to three to six months after diagnosis. A comprehensive assessment of long-term prevalence of physical symptoms beyond six months after diagnosis and among non-hospitalized patients is lacking.Added value of this studyWe included 64 880 participants from the general population of four Nordic countries, of whom 22 382 had been diagnosed with COVID-19 up to 2 years earlier (Implications of the available evidenceOur findings provide timely and valuable evidence to demonstrate the constitution of Long COVID and the long-term health consequences after recovery from COVID-19 in the general population. The long-term risk of severe physical symptom burden is distinctly associated with acute illness severity, highlighting the importance of sustained monitoring of physical symptoms among the group of patients who suffered severe acute illness course.

BackgroundLittle is known regarding the mental health impact of having a significant person (family member and/or close friend) with COVID-19 of different severity.MethodsThe study included five prospective cohorts from four countries (Iceland, Norway, Sweden, and the UK) with self-reported data on COVID-19 and symptoms of depression and anxiety during March 2020-March 2022. We calculated the prevalence ratio (PR) of depression and anxiety in relation to having a significant person with COVID-19 and performed a longitudinal analysis in the Swedish cohort to describe the temporal patterns of the results.Results162,237 and 168,783 individuals were included in the analysis of depression and anxiety, respectively, of whom 24,718 and 27,003 reported a significant person with COVID-19. Overall, the PR was 1.07 (95% CI: 1.05-1.10) for depression and 1.08 (95% CI: 1.03-1.13) for anxiety among significant others of COVID-19 patients. The respective PRs for depression and anxiety were 1.04 (95% CI: 1.01-1.07) and 1.03 (95% CI: 0.98-1.07) if the significant person was never hospitalized, 1.15 (95% CI: 1.08-1.23) and 1.24 (95% CI: 1.14-1.34) if the patient was hospitalized, 1.42 (95% CI: 1.27-1.57) and 1.45 (95% CI: 1.31-1.60) if admitted to the ICU, and 1.34 (95% CI: 1.22-1.46) and 1.36 (95% CI: 1.22-1.51) if the significant person died. Individuals of hospitalized, ICU admitted, or deceased patients showed higher prevalence of depression and anxiety during the entire 12 months after the COVID-19 diagnosis of the significant person.ConclusionsClose friends and family members of critically ill COVID-19 patients show elevated prevalence of depression and anxiety throughout the first year after the diagnosis.

ObjectiveTo explore the prevalence of care-seeking avoidance behavior in relation to gender and to describe the effect of (and potential interaction between) gender and care-seeking on mental health during the COVID-19 pandemic in Sweden.MethodsWe performed a cross-sectional study among 27,562 participants of the Omtanke2020 Study, using data collected at three time points concerning sociodemographic factors, mental health symptoms, and care-seeking behavior. Network analysis and prevalence ratios calculated from modified Poisson regressions were used to explore the relationship between gender, care-seeking behavior, and mental health symptoms (depression, anxiety, and COVID-19-related distress).ResultsIn our study, women reported a higher prevalence of mental health symptoms and avoidance of care-seeking due to COVID-19, compared to men. At baseline and six months thereafter, female gender was positively associated with COVID-19-related distress and previous mental health diagnosis. At 12 months after baseline, female gender was positively associated with anxiety and avoidance of care-seeking for mental health. However, previous mental health diagnosis and care avoidance were more strongly associated with a higher prevalence of mental health symptoms among men, compared to women.ConclusionThis study highlights gender differences in mental health outcomes and care-seeking behavior during the COVID-19 pandemic in Sweden.FundingThis work was supported with grants from Nordforsk (COVIDMENT, 105668 and 138929).

SummaryBackgroundUnderstanding factors associated with mental distress during a pandemic is imperative for planning interventions to reduce the negative mental health impact of future crises. Our aim was to identify factors associated with change in levels of mental distress in the Norwegian adult population at the onset of the Covid-19 pandemic, relative to pre-pandemic levels, and with longitudinal changes in mental distress until vaccination against Covid-19 became widespread in Norway (the first 1.5 years of the pandemic).MethodsThe Norwegian Mother, Father and Child Cohort Study (MoBa) is a prospective longitudinal study with baseline recruitment from 1999-2009. Baseline characteristics and eight waves of data collection during the pandemic (between March 2020 and September 2021) were used for this analysis. Mental distress was measured with the 5-item version of Hopkins Symptoms Checklist (HSCL-5). A piecewise latent growth model was fitted to identify initial change in mental distress (March-early April 2020, adjusting for pre-pandemic mental distress measured during prior years of data collection) and longitudinal changes across the pandemic in three distinct periods.FindingsOur sample consisted of 105 972 adult participants (59.6% females). Mental distress levels peaked at the beginning of the pandemic. Several factors were associated with initial increases in distress: chronic medical conditions, living alone, history of psychiatric disorders, relatively lower educational background, female sex, younger age, and obesity. Several of these factors were also associated with long-term change. Being quarantined or having to isolate was associated with the likelihood of increasing distress during the pandemic. We observed a reduction in distress associated with Covid-19 vaccination status, while being infected with SARS-CoV-2 was associated with increasing distress late in the pandemic.InterpretationPre-pandemic vulnerability factors – like having a chronic disease – as well as Covid-19-related factors – like being quarantined or infected by SARS-CoV-2 – were associated with increased mental distress during the pandemic. This knowledge is important for planning of interventions to support vulnerable individuals during pandemics and other health crises.FundingThe Norwegian Ministry of Health, and Care Services and the Ministry of Education and Research. NordForsk, The Research Council of Norway, The South-Eastern Norway Regional Health Authority.

Background: During the COVID-19 pandemic, individuals with pre-existing mental health problems may have experienced additional stress, which could worsen symptoms or trigger relapse. Objective: To investigate if the number of consultations with general practitioners (GPs) among individuals with a pre-existing common mental health problem during the pandemic differed from pre-pandemic years. Methods: Data on consultations with GPs among 18-65-year-olds registered with common mental health problems in 2017-2021 were retrieved from the Norwegian Control and Payment of Health Reimbursement register. Based on data from the pre-pandemic years (2017-2019), we predicted the number of consultations per week for depression, anxiety disorder, phobia/obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and eating disorders during the pandemic (March 2020-December 2021) among individuals with pre-existing mental health problems. The forecasted and observed trends in GP consultations per week during the pandemic were stratified by diagnosis, gender, and age groups. Results: The observed number of consultations for anxiety disorder, PTSD, and eating disorders were significantly higher than forecasted during extended periods of the two pandemic years. The differences were largest for PTSD (on average 37% higher in men and 47% higher in women during the pandemic), and for eating disorders among women (on average 87% higher during the pandemic). There were only minor differences between the predicted and observed number of consultations for depression and phobia/OCD. Conclusions: During the pandemic, individuals with a recent history of mental health problems were more likely to seek help for anxiety disorder, PTSD, and eating disorders, as compared to pre-pandemic years.

There is emerging evidence that spouses of patients with cancer may have a higher prevalence of mental illness, but these studies have been limited by pre-post designs, focus on a single mental illness, and short follow-up periods.To assess the overall burden of psychiatric disorders among spouses of patients with cancer vs spouses of individuals without cancer and to describe possible changes in this burden over time.This population based cohort study included spouses of patients with cancer (diagnosed 1986-2016 in Denmark and 1973-2014 in Sweden; exposed group) and spouses of individuals without cancer (unexposed group). Members of the unexposed group were individually matched to individuals in the exposed group on the year of birth, sex, and country. Spouses with and without preexisting psychiatric morbidity were analyzed separately. Data analysis was performed between May 2021 and January 2022.Being spouse to a patient with cancer.The main outcome was a clinical diagnosis of psychiatric disorders through hospital-based inpatient or outpatient care. Flexible parametric models and Cox models were fitted to estimate hazard ratios (HRs) with 95% CIs, adjusted for sex, age and year at cohort entry, country, household income, and cancer history.Among 546 321 spouses in the exposed group and 2 731 574 in the unexposed group who had no preexisting psychiatry morbidity, 46.0% were male participants, with a median (IQR) age at cohort entry of 60 (51-68) years. During follow-up (median, 8.4 vs 7.6 years), the incidence rate of first-onset psychiatric disorders was 6.8 and 5.9 per 1000 person-years for the exposed and unexposed groups, respectively (37 830 spouses of patients with cancer [6.9%]; 153 607 of spouses of individuals without cancer [5.6%]). Risk of first-onset psychiatric disorders increased by 30% (adjusted HR, 1.30; 95% CI, 1.25-1.34) during the first year after cancer diagnosis, especially for depression (adjusted HR, 1.38; 95% CI, 1.30-1.47) and stress-related disorders (adjusted HR, 2.04; 95% CI, 1.88-2.22). Risk of first-onset psychiatric disorders increased by 14% (adjusted HR, 1.14; 95% CI, 1.13-1.16) during the entire follow-up, which was similar for substance abuse, depression, and stress-related disorders. The risk increase was more prominent among spouses of patients diagnosed with a cancer with poor prognosis (eg, pancreatic cancer: adjusted HR, 1.41; 95% CI, 1.32-1.51) or at an advanced stage (adjusted HR, 1.31; 95% CI, 1.26-1.36) and when the patient died during follow-up (adjusted HR, 1.29; 95% CI, 1.27-1.31). Among spouses with preexisting psychiatric morbidity, the risk of psychiatric disorders (first-onset or recurrent) increased by 23% during the entire follow-up (adjusted HR, 1.23; 95% CI, 1.20-1.25).In this cohort study of 2 populations in Denmark and Sweden, spouses of patients with cancer experienced increased risk of several psychiatric disorders that required hospital-based specialist care. Our results support the need for clinical awareness to prevent potential mental illness among the spouses of patients with cancer.

BACKGROUND Suicidal behaviors, including suicide deaths and attempts, are major public health concerns. However, previous suicide models required a huge amount of input features, resulting in limited applicability in clinical practice. OBJECTIVE We aimed to construct applicable models (ie, with limited features) for short- and long-term suicidal behavior prediction. We further validated these models among individuals with different genetic risks of suicide. METHODS Based on the prospective cohort of UK Biobank, we included 223 (0.06%) eligible cases of suicide attempts or deaths, according to hospital inpatient or death register data within 1 year from baseline and randomly selected 4460 (1.18%) controls (1:20) without such records. We similarly identified 833 (0.22%) cases of suicidal behaviors 1 to 6 years from baseline and 16,660 (4.42%) corresponding controls. Based on 143 input features, mainly including sociodemographic, environmental, and psychosocial factors; medical history; and polygenic risk scores (PRS) for suicidality, we applied a bagged balanced light gradient-boosting machine (LightGBM) with stratified 10-fold cross-validation and grid-search to construct the full prediction models for suicide attempts or deaths within 1 year or between 1 and 6 years. The Shapley Additive Explanations (SHAP) approach was used to quantify the importance of input features, and the top 20 features with the highest SHAP values were selected to train the applicable models. The external validity of the established models was assessed among 50,310 individuals who participated in UK Biobank repeated assessments both overall and by the level of PRS for suicidality. RESULTS Individuals with suicidal behaviors were on average 56 years old, with equal sex distribution. The application of these full models in the external validation data set demonstrated good model performance, with the area under the receiver operating characteristic (AUROC) curves of 0.919 and 0.892 within 1 year and between 1 and 6 years, respectively. Importantly, the applicable models with the top 20 most important features showed comparable external-validated performance (AUROC curves of 0.901 and 0.885) as the full models, based on which we found that individuals in the top quintile of predicted risk accounted for 91.7% (n=11) and 80.7% (n=25) of all suicidality cases within 1 year and during 1 to 6 years, respectively. We further obtained comparable prediction accuracy when applying these models to subpopulations with different genetic susceptibilities to suicidality. For example, for the 1-year risk prediction, the AUROC curves were 0.907 and 0.885 for the high (>2nd tertile of PRS) and low ( CONCLUSIONS We established applicable machine learning–based models for predicting both the short- and long-term risk of suicidality with high accuracy across populations of varying genetic risk for suicide, highlighting a cost-effective method of identifying individuals with a high risk of suicidality.

Hair analysis of endocannabinoids and N-acylethanolamines has emerged as a promising methodological advancement for the retrospective assessment of cumulative long-term endocannabinoids and N-acylethanolamines secretion in biopsychological research of stress-related symptoms and disorders. In this study, we investigated the influence of the potential associated factors on hair endocannabinoid and N-acylethanolamine levels in 760 adult participants aged between 21 and 86 years old. Gender, age, medication intake, drug use, body mass index, waist circumference, smoking status, alcohol consumption and perceived stress were assessed through questionnaires. Hair endocannabinoid and N-acylethanolamine concentrations were measured through liquid chromatography coupled to tandem mass-spectrometry. Results identified that gender, age, BMI, waist circumference, medication and drug use, hair washing frequency as potential confounding variables of hair endocannabinoid and N-acylethanolamine levels, while no associations were observed with respect to hair dyeing, smoking status, alcohol consumption and perceived stress. The present data indicate that hair endocannabinoids and N-acylethanolamines measurement may be a useful alternative to the current circulating endocannabinoids measurements in biopsychological research with the consideration of possible confounders.

Importance: Maternal immune activation during pregnancy is associated with increased risks of several mental disorders in offspring during childhood, but little is known about how maternal autoimmune diseases during pregnancy are associated with mental health in offspring during and after childhood. Objective: To investigate the association between maternal autoimmune diseases before childbirth and risk of mental disorders among offspring up to early adulthood. Design, Setting, and Participants: This population-based nationwide cohort study used data from Danish national registers on singletons born in Denmark from 1978 to 2015 with up to 38 years of follow-up. Data analyses were conducted from March 1, 2020, through September 30, 2021. Exposures: Maternal autoimmune disease diagnosed before or during pregnancy according to the Danish National Patient Register. Main Outcomes and Measures: The main outcome was mental disorders, defined by hospital diagnoses, in offspring. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% CIs for mental disorders. Results: Of the 2 254 234 singleton infants included in the study (median age, 16.7 years [IQR, 10.5-21.7 years]; 51.28% male), 2.26% were born to mothers with autoimmune diseases before childbirth. Exposed participants had an increased risk of overall mental disorders compared with their unexposed counterparts (HR, 1.16; 95% CI, 1.13-1.19; incidence, 9.38 vs 7.91 per 1000 person-years). Increased risks of overall mental disorders in offspring were seen in different age groups for type 1 diabetes (1-5 years: HR, 1.35 [95% CI, 1.17-1.57]; 6-18 years: HR, 1.24 [95% CI, 1.15-1.33]; >18 years: HR, 1.19 [95% CI, 1.09-1.30]) and rheumatoid arthritis (1-5 years: HR, 1.42 [95% CI, 1.16-1.74]; 6-18 years: HR, 1.19 [95% CI, 1.05-1.36]; >18 years: HR, 1.28 [95% CI, 1.02-1.60]). Regarding specific mental disorders, increased risk after exposure to any maternal autoimmune disorder was observed for organic disorders (HR, 1.54; 95% CI, 1.21-1.94), schizophrenia (HR, 1.35; 95% CI, 1.21-1.51), obsessive-compulsive disorder (HR, 1.42; 95% CI, 1.24-1.63), mood disorders (HR, 1.12; 95% CI, 1.04-1.21), and a series of neurodevelopmental disorders (eg, childhood autism [HR, 1.21; 95% CI, 1.08-1.36] and attention-deficit/hyperactivity disorder [HR, 1.19; 95% CI, 1.12-1.26]). Conclusions and Relevance: In this cohort study in Denmark, prenatal exposure to maternal autoimmune diseases was associated with increased risks of overall and type-specific mental disorders in offspring. Maternal type 1 diabetes and rheumatoid arthritis during pregnancy were associated with offspring's mental health up to early adulthood. Individuals prenatally exposed to autoimmune disease may benefit from long-term surveillance for mental disorders.

BackgroundThe emergence of COVID-19 brought unparalleled changes in people’s lifestyle, including sleep. We aimed to assess the bidirectional association between sleep quality and mental health and describe how sleep and mental health were affected in Sweden during the COVID-19 pandemic (between June 2020 and September 2021).MethodsData were obtained from the Omtanke2020 study. Participants who completed the baseline survey and 8 monthly follow-up surveys were included (N=9035). We described the distribution of sleep and mental health in the different Swedish regions using maps and over the study period with longitudinal graphs adjusting for sex, age, recruitment type (self-recruitment or invitation), and COVID-19 status. The inner relationships between mental health, sleep and covid infection were described through relative importance networks. Finally, we modelled how mental health affects sleep and vice versa using generalized estimating equations with different adjustments.ResultsSeasonal and north-south regional variations were found in sleep and mental health outcomes at baseline and attenuated over time. The seasonal variation of sleep and mental health correlated moderately with the incidence rate of COVID-19 in the sample. Networks indicate that the relationship between COVID-19 incidence and mental health varies over time. We observed a bidirectional relationship between sleep quality and quantity at baseline and mental health at follow-up and vice versa.ConclusionSleep quality and quantity at baseline was associated with adverse symptom trajectories of mental health at follow-up, and vice versa, during the COVID-19 pandemic. There is also a weak relationship between COVID-19 incidence, sleep, and mental health.

Importance: Emerging data suggest that more than two-thirds of premenstrual disorders (PMDs), including premenstrual syndrome and premenstrual dysphoric disorder, have symptom onset during the teen years. Adulthood adiposity has been associated with PMDs; however, the association with childhood and adolescent body size is unknown. Objective: To examine the association between childhood and adolescent body size and risk of PMDs in young adulthood. Design, Setting, and Participants: This prospective cohort study included 6524 US female participants from the Growing Up Today Study (1996-2013). Data were analyzed from February 26, 2020, to June 23, 2021. Exposures: Body mass index (BMI) was estimated using self-reported height and weight through adolescence and converted to BMI for age (z score). Main Outcomes and Measures: In 2013, premenstrual symptoms and identified PMDs were assessed with a validated scale based on the Calendar of Premenstrual Experiences. The associations of BMI for age with PMDs and premenstrual symptoms were examined using log-binomial and linear regressions, respectively. Results: Among 6524 participants (mean [SD] age, 26 [3.5] years; 6108 [93.6%] White), 1004 (15.4%) met the criteria for a PMD. Baseline BMI for age reported at a mean (SD) age of 12.7 (1.1) years was associated with increased risk of PMDs (confounding-adjusted relative risk, 1.09 per unit of z score; 95% CI, 1.03-1.15) and higher burden of premenstrual symptoms (β = 0.06; 95% CI, 0.04-0.08). Associations were particularly pronounced for premenstrual dysphoric disorder and for PMDs with symptom onset before 20 years of age and remained in the absence of psychiatric comorbidities, including depression, anxiety, and disordered eating behavior. When analyzing BMI change over time, individuals with high BMI throughout adolescence had a higher burden of premenstrual symptoms (β = 0.17; 95% CI, 0.08-0.27) compared with those with normal BMI throughout adolescence. Individuals with high BMI early followed by a mild decrease later did not report higher premenstrual symptoms (β = 0.06; 95% CI, 0.00-0.12). Conclusions and Relevance: In this cohort study, childhood body size was associated with PMD risk and premenstrual symptoms in young adulthood. These findings suggest that maintaining a normal body mass in childhood may be considered for lowering the burden of PMDs in adulthood..

Background Childhood abuse and neglect have been associated with premenstrual disorders (PMDs), including premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD). However, the associations of other adverse childhood experiences (ACEs) and the cumulative number of ACEs with PMDs remain to be explored. Methods To evaluate the associations of the cumulative number and types of ACEs with PMDs, we conducted a cross-sectional analysis with a subsample of menstruating women within the Stress-And-Gene-Analysis (SAGA) cohort, assessed for PMDs and ACEs (N=11,973). The cumulative and individual exposure of 13 types of ACEs was evaluated by a modified ACE-International Questionnaire. A modified version of the Premenstrual Symptom Screening Tool was used to identify probable cases of PMDs, further sub-grouped into PMS and PMDD. Prevalence ratios (PRs) of PMDs in relation to varying ACEs were estimated using Poisson regression. Results At a mean age of 34.0 years (standard deviation (SD) 9.1), 3235 (27%) met the criteria of probable PMDs, including 2501 (21%) for PMS and 734 (6%) for PMDD. The number of ACEs was linearly associated with PMDs (fully-adjusted PR 1.12 per ACE, 95% CI 1.11–1.13). Specifically, the PR for PMDs was 2.46 (95% CI 2.21–2.74) for women with 4 or more ACEs compared with women with no ACEs. A stronger association was observed for probable PMDD compared to PMS (p for difference p for interaction Conclusions Our findings suggest that childhood adverse experiences are associated with PMDs in a dose-dependent manner. If confirmed by prospective data, our findings support the importance of early intervention for girls exposed to ACEs to minimize risks of PMDs and other morbidities in adulthood.

Background:Adverse childhood experiences (ACEs) have consistently been associated with elevated risk of multiple adverse health outcomes, yet their contribution to coping ability and psychiatric resilience in adulthood is unclear.Methods:Cross-sectional data were derived from the ongoing Stress-And-Gene-Analysis cohort, representing 30% of the Icelandic nationwide female population, 18–69 years. Participants in the current study were 26,198 women with data on 13 ACEs measured with the ACE-International Questionnaire. Self-reported coping ability was measured with the Connor-Davidson Resilience Scale and psychiatric resilience was operationalized as absence of psychiatric morbidity. Generalized linear regression assuming normal or Poisson distribution were used to assess the associations of ACEs with coping ability and psychiatric resilience controlling for multiple confounders.Results:Number of ACEs was inversely associated with adult resilience in a dose-dependent manner; every 1SD unit increase in ACE scores was associated with both lower levels of coping ability (β = −0.14; 95% CI-0.15,–0.13) and lower psychiatric resilience (β = −0.28; 95% CI-0.29,–0.27) in adulthood. Compared to women with 0 ACEs, women with ≥5 ACEs had 36% lower prevalence of high coping ability (PR = 0.64, 95% CI 0.59,0.70) and 58% lower prevalence of high psychiatric resilience (PR = 0.42; 95% CI 0.39,0.45). Specific ACEs including emotional neglect, bullying, sexual abuse and mental illness of household member were consistently associated with reduced adult resilience. We observed only slightly attenuated associations after controlling for adult socioeconomic factors and social support in adulthood.Conclusions:Cumulative ACE exposure is associated with lower adult resilience among women, independent of adult socioeconomic factors and social support, indicating that adult resilience may be largely determined in childhood.Funding:This work was supported by the European Research Council (Consolidator grant; UAV, grant number 726413), and the Icelandic Center for Research (Grant of excellence; UAV, grant number 163362-051). HBD was supported by a doctoral grant from the University of Iceland Research Fund.

Little is known about the contribution of pregnancy-related parental and perinatal factors to the development of stress-related disorders. We aimed to investigate whether parental/perinatal adversities entail higher risks of stress-related disorders in the offspring, later in life, by accounting for genetic and early environmental factors. Based on the nationwide Swedish registers, we conducted a population-based cohort study of 3,435,747 singleton births (of which 2,554,235 were full siblings), born 1973–2008 and survived through the age of 5 years. Using both population- and sibling designs, we employed Cox regression to assess the association between parental and perinatal factors with subsequent risk of stress-related disorders. We identified 55,511 individuals diagnosed with stress-related disorders in the population analysis and 37,433 in the sibling analysis. In the population-based analysis we observed increased risks of stress-related disorders among offspring of maternal/paternal age

Purpose: Perinatal mental health disorders affect a significant number of women with debilitating and potentially life-threatening consequences. Researchers in Nordic countries have access to high quality, population-based data sources and the possibility to link data, and are thus uniquely positioned to fill current evidence gaps. We aimed to review how Nordic studies have contributed to existing evidence on perinatal mental health. Methods: We summarized examples of published evidence on perinatal mental health derived from large population-based longitudinal and register-based data from Denmark, Finland, Iceland, Norway and Sweden. Results: Nordic datasets, such as the Danish National Birth Cohort, the FinnBrain Birth Cohort Study, the Icelandic SAGA cohort, the Norwegian MoBa and ABC studies, as well as the Swedish BASIC and Mom2B studies facilitate the study of prevalence of perinatal mental disorders, and further provide opportunity to prospectively test etiological hypotheses, yielding comprehensive suggestions about the underlying causal mechanisms. The large sample size, extensive follow-up, multiple measurement points, large geographic coverage, biological sampling and the possibility to link data to national registries renders them unique. The use of novel approaches, such as the digital phenotyping data in the novel application-based Mom2B cohort recording even voice qualities and digital phenotyping, or the Danish study design paralleling a natural experiment are considered strengths of such research. Conclusions: Nordic data sources have contributed substantially to the existing evidence, and can guide future work focused on the study of background, genetic and environmental factors to ultimately define vulnerable groups at risk for psychiatric disorders following childbirth.

Background Suicidal behaviors, including suicide deaths and attempts, are major public health concerns. However, previous suicide models required a huge amount of input features, resulting in limited applicability in clinical practice. Objective We aimed to construct applicable models (ie, with limited features) for short- and long-term suicidal behavior prediction. We further validated these models among individuals with different genetic risks of suicide. Methods Based on the prospective cohort of UK Biobank, we included 223 (0.06%) eligible cases of suicide attempts or deaths, according to hospital inpatient or death register data within 1 year from baseline and randomly selected 4460 (1.18%) controls (1:20) without such records. We similarly identified 833 (0.22%) cases of suicidal behaviors 1 to 6 years from baseline and 16,660 (4.42%) corresponding controls. Based on 143 input features, mainly including sociodemographic, environmental, and psychosocial factors; medical history; and polygenic risk scores (PRS) for suicidality, we applied a bagged balanced light gradient-boosting machine (LightGBM) with stratified 10-fold cross-validation and grid-search to construct the full prediction models for suicide attempts or deaths within 1 year or between 1 and 6 years. The Shapley Additive Explanations (SHAP) approach was used to quantify the importance of input features, and the top 20 features with the highest SHAP values were selected to train the applicable models. The external validity of the established models was assessed among 50,310 individuals who participated in UK Biobank repeated assessments both overall and by the level of PRS for suicidality. Results Individuals with suicidal behaviors were on average 56 years old, with equal sex distribution. The application of these full models in the external validation data set demonstrated good model performance, with the area under the receiver operating characteristic (AUROC) curves of 0.919 and 0.892 within 1 year and between 1 and 6 years, respectively. Importantly, the applicable models with the top 20 most important features showed comparable external-validated performance (AUROC curves of 0.901 and 0.885) as the full models, based on which we found that individuals in the top quintile of predicted risk accounted for 91.7% (n=11) and 80.7% (n=25) of all suicidality cases within 1 year and during 1 to 6 years, respectively. We further obtained comparable prediction accuracy when applying these models to subpopulations with different genetic susceptibilities to suicidality. For example, for the 1-year risk prediction, the AUROC curves were 0.907 and 0.885 for the high (>2nd tertile of PRS) and low ( Conclusions We established applicable machine learning–based models for predicting both the short- and long-term risk of suicidality with high accuracy across populations of varying genetic risk for suicide, highlighting a cost-effective method of identifying individuals with a high risk of suicidality.

Study Objectives To date, few studies have assessed sleep problems among women residing in Subarctic regions. Therefore, the aim of this large-scale population-based study was to assess the prevalence of severe sleep problems and associated factors among Icelandic women, living at 63–66°N. Methods Participants were 29 681 women (18–69 years old) who took part in the Icelandic Stress-And-Gene-Analysis study in 2018–2019. Background information, health-related behavior, and mental health symptoms were assessed with an online questionnaire. The Pittsburgh Sleep Quality Index (PSQI) was used to assess severe sleep problems during the past month. Adjusting for age, marital status, number of children, education, personal income, work schedule, region, and response period, we used modified Poisson log-linear models to obtain prevalence ratios (PRs) with 95% confidence intervals (CIs). Results Overall, 24.2% of women reported severe sleep problems (PSQI >10). Women responding in the winter presented with an overall higher prevalence of severe sleep problems, compared to those responding in the summer (PR 1.21; 95% CI, 1.15 to 1.28). Severe sleep problems were more prevalent among young and late-midlife women, those who were single, had children, socio-economic challenges, worked shifts, and flexible hours. Furthermore, obesity, suboptimal health behaviors, excessive screen time, and mental health problems were associated with severe sleep problems. Conclusion Severe sleep problems are more common among women in Subarctic regions than elsewhere, particularly during winter. These findings motivate the development of preventive strategies and interventions for women in the Subarctic who suffer from sleep problems.

BACKGROUNDThe aim of this multinational study was to assess the development of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis.METHODSParticipants consisted of 247 249 individuals from seven cohorts across six countries (Denmark, Estonia, Iceland, Norway, Scotland, and Sweden) recruited from April 2020 through August 2021. We used multivariable Poisson regression to contrast symptom-prevalence of depression, anxiety, COVID-19 related distress, and poor sleep quality among individuals with and without a diagnosis of COVID-19 at entry to respective cohorts by time (0-16 months) from diagnosis. We also applied generalised estimating equations (GEE) analysis to test differences in repeated measures of mental health symptoms before and after COVID-19 diagnosis among individuals ever diagnosed with COVID-19 over time.FINDINGSA total of 9979 individuals (4%) were diagnosed with COVID-19 during the study period and presented overall with a higher symptom burden of depression (prevalence ratio [PR] 1·18, 95% confidence interval [95% CI] 1·03-1·36) and poorer sleep quality (1·13, 1·03-1·24) but not with higher levels of symptoms of anxiety or COVID-19 related distress compared with individuals without a COVID-19 diagnosis. While the prevalence of depression and COVID-19 related distress attenuated with time, the trajectories varied significantly by COVID-19 acute infection severity. Individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risks of depression and anxiety (PR 0·83, 95% CI 0·75-0·91 and 0·77, 0·63-0·94, respectively), while patients bedridden for more than 7 days were persistently at higher risks of symptoms of depression and anxiety (PR 1·61, 95% CI 1·27-2·05 and 1·43, 1·26-1·63, respectively) throughout the 16-month study period.CONCLUSIONAcute infection severity is a key determinant of long-term mental morbidity among COVID-19 patients.

BackgroundThe ongoing COVID-19 pandemic has had an unprecedented impact on the lives of people globally and is expected to have profound effects on mental health. Yet, self-reported large-scale online surveys on mental health are still relatively uncommon. Here we aim to describe the mental health burden experienced in Sweden using baseline data of the Omtanke2020 Study.MethodSelf-reported baseline data collected over a 12-month period (June 9, 2020-June 8, 2021) from the longitudinal online survey of the Omtanke2020 Study including 27,950 adults in Sweden. Participants were volunteers or actively recruited through existing cohorts and after providing informed consent responded to monthly online questionnaires on socio-demographics, mental and physical health, COVID-19 infection, and impact. Poisson regression was fitted to assess the relative risk of high mental health burden (depression, anxiety, and COVID-19 specific PTSD).ResultThe overall proportion of persons with high level of symptoms was 15.6%, 9.5% and 24.5% for depression, anxiety, and COVID-19 specific PTSD, respectively. Overall, 43.4% of the participants had significant, clinically relevant symptoms for at least one mental health outcome and 7.3% had significant symptoms for all three outcomes. We also observed differences in the prevalence of these symptoms across strata of sex, age, recruitment type, COVID-19 status, region, and seasonality.ConclusionWhile the proportion of persons with high mental health burden remains higher than in pre-pandemic publications, our estimates are lower than previously reported levels of depression, anxiety, and PTSD during the pandemic in Sweden and elsewhere.

Key features • COVIDMENT [www.covidment.is] is a NordForsk-funded research collaboration across six nations, with the overarching aim to significantly advance current knowledge on mental morbidity trajectories associated with the coronavirus disease 2019 (COVID-19) in the general population and in specific risk groups. • From March 2020 through August 2021, 392 817 individuals have been recruited to the seven COVIDMENT cohorts: the Danish Blood Donor Study (N ¼ 71 562), the Estonian Biobank COVID-19 and Mental Health Data Collection cohorts (N ¼ 13 329 and N ¼ 86 116, respectively), the Icelandic COVID-19 National Resilience Cohort (N ¼ 22 849), the Norwegian BRY.DEG2020 (N ¼ 19 343), the Norwegian Mother, Father and Child Cohort Study (N ¼ 132 486), the Scottish Generation Scotland/CovidLife (N ¼ 18 518) and the Swedish Omtanke2020 (N ¼ 28 614). Semi-harmonized questionnaire data have been collected across all COVIDMENT cohorts with longitudinal data available, e.g. through linkage to the national registers. • The average age of participants ranged from 31.8 to 58.5 years across cohorts. The prevalence of depressive symptoms above cut-off point varied considerably across cohorts (4.2–20.8%). The prevalence of depressive symptoms was highest at COVID-19 incidence of 30 cases per week per 100 000 persons, i.e. 14.3% [95% confidence interval (CI): 9.4–21.8%], which was 61.0% (95% CI: 34.0–94.1%) higher than the prevalence at COVID-19 incidence of 0 cases per week per 100 000 persons (P ¼ 1.1 x 10 ^( 6)). •