Acute COVID-19 severity and mental health morbidity trajectories in patient populations of six nations: an observational study.

BACKGROUND: Long-term mental and physical health consequences of COVID-19 (long COVID) are a persistent public health concern. Little is still known about the long-term mental health of non-hospitalised patients with COVID-19 with varying illness severities. Our aim was to assess the prevalence 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. METHODS: This observational follow-up study included seven prospectively planned cohorts across six countries (Denmark, Estonia, Iceland, Norway, Sweden, and the UK). Participants were recruited from March 27, 2020, to Aug 13, 2021. Individuals aged 18 years or older were eligible to participate. In a cross-sectional analysis, we contrasted symptom prevalence of depression, anxiety, COVID-19-related distress, and poor sleep quality (screened with validated mental health instruments) among individuals with and without a diagnosis of COVID-19 at entry, 0-16 months from diagnosis. In a cohort analysis, we further used repeated measures to estimate the change in mental health symptoms before and after COVID-19 diagnosis. FINDINGS: The analytical cohort consisted of 247 249 individuals, 9979 (4·0%) of whom were diagnosed with COVID-19 during the study period. Mean follow-up was 5·65 months (SD 4·26). Participants diagnosed with COVID-19 presented overall with a higher prevalence of symptoms of depression (prevalence ratio [PR] 1·18 [95% CI 1·03-1·36]) and poorer sleep quality (1·13 [1·03-1·24]) but not symptoms of anxiety (0·97 [0·91-1·03]) or COVID-19-related distress (1·05 [0·93-1·20]) compared with individuals without a COVID-19 diagnosis. Although the prevalence of depression and COVID-19-related distress attenuated with time, individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risk of depression (PR 0·83 [95% CI 0·75-0·91]) and anxiety (0·77 [0·63-0·94]) than those not diagnosed with COVID-19, whereas patients who were bedridden for more than 7 days were persistently at higher risk of symptoms of depression (PR 1·61 [95% CI 1·27-2·05]) and anxiety (1·43 [1·26-1·63]) than those not diagnosed throughout the study period. INTERPRETATION: Severe acute COVID-19 illness-indicated by extended time bedridden-is associated with long-term mental morbidity among recovering individuals in the general population. These findings call for increased vigilance of adverse mental health development among patients with a severe acute disease phase of COVID-19. FUNDING: Nordforsk, Horizon2020, Wellcome Trust, and Estonian Research Council.

Demographic factors and delay of treatment for alcohol use disorders among 6584 Danish men receiving alcohol treatment.

PURPOSE: This study aimed to investigate the time lag between onset and treatment (treatment delay) for alcohol use disorders (AUD) and associations between demographic factors and treatment delay for AUD. METHODS: The study included 6,584 men registered in the Copenhagen Alcohol Cohort, containing information on civil status, employment status, estimated age at onset of alcohol problems, and age at first outpatient AUD treatment. Data on year of birth, intelligence, and educational level were obtained from the Danish Conscription Database. Information on first hospital AUD treatment was retrieved from Danish national psychiatric registers. Associations between the demographic factors and treatment delay were analysed in separate linear regression models adjusted for year of birth and in a mutually adjusted model including all demographic factors. RESULTS: The mean treatment delay for AUD was 6.9 years (SD = 4.1). After mutual adjustment, an SD increase in intelligence score was associated with 0.17 years increase in treatment delay. Educational level was unrelated to treatment delay. Men with estimated age at onset of alcohol problems at age 20 years or younger had a 5.30 years longer treatment delay than men who had estimated age at onset of alcohol problems at age 51 years or older. Employed men had shorter treatment delays than unemployed men, especially among the oldest birth cohorts. CONCLUSIONS: The treatment delay of 6.9 years highlights the necessity to promote access to AUD treatment, perhaps in particular among adolescents and young individuals. Cognitive factors may affect treatment delay more than non-cognitive personal factors.

Age at onset and age at treatment of alcohol use disorders: Associations with educational level and intelligence.

Associations of educational level and intelligence with age at onset and age at treatment of alcohol use disorders (AUD) are sparsely investigated; however, knowledge about these associations is important for an enhanced understanding of AUD. This study aimed to examine three measures of timing of AUD: estimated age at onset of alcohol problems, age at first registration in an outpatient alcohol clinic, and age at first AUD hospital diagnosis, and to estimate associations of educational level and intelligence with each measure of timing of AUD. The aims were investigated in a register-based study comprising 7,019 Danish men seeking outpatient AUD treatment. Data on educational level and intelligence were obtained from the Danish Conscription Database. Estimated age at onset of alcohol problems and age at first registration in an outpatient alcohol clinic were obtained from the Copenhagen Alcohol Cohort. Age at first AUD hospital diagnosis was retrieved from national Danish psychiatric registers. Among individuals with information on all measures of timing of AUD, 65.8% followed the developmental sequence: estimated age at onset of alcohol problems (M = 32.08 years, SD = 9.3), age at first registration in an outpatient alcohol clinic (M = 39.89 years, SD = 9.5), and age at first AUD hospital diagnosis (M = 42.27 years, SD = 12.4). Adjusted linear regression models revealed significant associations of high educational level and high intelligence with later onset and treatment of AUD, ranging from 0.61 to 0.89 years (p < 0.0001) for educational level and from 0.10 to 0.09 years (p < 0.0001) for intelligence. In conclusion, AUD develops sequentially. High educational level and intelligence were associated with later onset and treatment of AUD, but educational level explained most unique variance. This may indicate that in addition to cognitive factors reflected by both educational level and intelligence, non-cognitive factors only reflected by educational level also are important for the timing of AUD.