The potential impact of the COVID-19 pandemic on population mental health is of increasing global concern. We examine changes in adult mental health in the UK population before and during the ...lockdown.
In this secondary analysis of a national, longitudinal cohort study, households that took part in Waves 8 or 9 of the UK Household Longitudinal Study (UKHLS) panel, including all members aged 16 or older in April, 2020, were invited to complete the COVID-19 web survey on April 23-30, 2020. Participants who were unable to make an informed decision as a result of incapacity, or who had unknown postal addresses or addresses abroad were excluded. Mental health was assessed using the 12-item General Health Questionnaire (GHQ-12). Repeated cross-sectional analyses were done to examine temporal trends. Fixed-effects regression models were fitted to identify within-person change compared with preceding trends.
Waves 6-9 of the UKHLS had 53 351 participants. Eligible participants for the COVID-19 web survey were from households that took part in Waves 8 or 9, and 17 452 (41·2%) of 42 330 eligible people participated in the web survey. Population prevalence of clinically significant levels of mental distress rose from 18·9% (95% CI 17·8-20·0) in 2018-19 to 27·3% (26·3-28·2) in April, 2020, one month into UK lockdown. Mean GHQ-12 score also increased over this time, from 11·5 (95% CI 11·3-11·6) in 2018-19, to 12·6 (12·5-12·8) in April, 2020. This was 0·48 (95% CI 0·07-0·90) points higher than expected when accounting for previous upward trends between 2014 and 2018. Comparing GHQ-12 scores within individuals, adjusting for time trends and significant predictors of change, increases were greatest in 18-24-year-olds (2·69 points, 95% CI 1·89-3·48), 25-34-year-olds (1·57, 0·96-2·18), women (0·92, 0·50-1·35), and people living with young children (1·45, 0·79-2·12). People employed before the pandemic also averaged a notable increase in GHQ-12 score (0·63, 95% CI 0·20-1·06).
By late April, 2020, mental health in the UK had deteriorated compared with pre-COVID-19 trends. Policies emphasising the needs of women, young people, and those with preschool aged children are likely to play an important part in preventing future mental illness.
None.
The COVID-19 pandemic has adversely affected population mental health. We aimed to assess temporal trends in primary care-recorded common mental illness, episodes of self-harm, psychotropic ...medication prescribing, and general practitioner (GP) referrals to mental health services during the COVID-19 emergency in the UK.
We did a population-based cohort study using primary care electronic health records from general practices registered on the UK Clinical Practice Research Datalink (CPRD). We included patient records from Jan 1, 2010, to Sept 10, 2020, to establish long-term trends and patterns of seasonality, but focused primarily on the period January, 2019–September, 2020. We extracted data on clinical codes entered into patient records to estimate the incidence of depression and anxiety disorders, self-harm, prescriptions for antidepressants and benzodiazepines, and GP referrals to mental health services, and assessed event rates of all psychotropic prescriptions and self-harm. We used mean-dispersion negative binomial regression models to predict expected monthly incidence and overall event rates, which were then compared with observed rates to assess the percentage reduction in incidence and event rates after March, 2020. We also stratified analyses by sex, age group, and practice-level Index of Multiple Deprivation quintiles.
We identified 14 210 507 patients from 1697 UK general practices registered in the CPRD databases. In April, 2020, compared with expected rates, the incidence of primary care-recorded depression had reduced by 43·0% (95% CI 38·3–47·4), anxiety disorders by 47·8% (44·3–51·2), and first antidepressant prescribing by 36·4% (33·9–38·8) in English general practices. Reductions in first diagnoses of depression and anxiety disorders were largest for adults of working age (18–44 and 45–64 years) and for patients registered at practices in more deprived areas. The incidence of self-harm was 37·6% (34·8–40·3%) lower than expected in April, 2020, and the reduction was greatest for women and individuals aged younger than 45 years. By September, 2020, rates of incident depression, anxiety disorder, and self-harm were similar to expected levels. In Northern Ireland, Scotland, and Wales, rates of incident depression and anxiety disorder remained around a third lower than expected to September, 2020. In April, 2020, the rate of referral to mental health services was less than a quarter of the expected rate for the time of year (75·3% reduction 74·0–76·4).
Consequences of the considerable reductions in primary care-recorded mental illness and self-harm could include more patients subsequently presenting with greater severity of mental illness and increasing incidence of non-fatal self-harm and suicide. Addressing the effects of future lockdowns and longer-term impacts of economic instability on mental health should be prioritised.
National Institute for Health Research and Medical Research Council.
The mental health of the UK population declined at the onset of the COVID-19 pandemic. Convenience sample surveys indicate that recovery began soon after. Using a probability sample, we tracked ...mental health during the pandemic to characterise mental health trajectories and identify predictors of deterioration.
This study was a secondary analysis of five waves of the UK Household Longitudinal Study (a large, national, probability-based survey that has been collecting data continuously since January, 2009) from late April to early October, 2020 and pre-pandemic data taken from 2018-19. Mental health was assessed using the 12-item General Health Questionnaire (GHQ-12). We used latent class mixed models to identify discrete mental health trajectories and fixed-effects regression to identify predictors of change in mental health.
Mental health was assessed in 19 763 adults (≥16 years; 11 477 58·1% women and 8287 41·9% men; 3453 17·5% participants from minority ethnic groups). Mean population mental health deteriorated with the onset of the pandemic and did not begin improving until July, 2020. Latent class analysis identified five distinct mental health trajectories up to October 2020. Most individuals in the population had either consistently good (7437 39·3% participants) or consistently very good (7623 37·5% participants) mental health across the first 6 months of the pandemic. A recovering group (1727 12·0% participants) showed worsened mental health during the initial shock of the pandemic and then returned to around pre-pandemic levels of mental health by October, 2020. The two remaining groups were characterised by poor mental health throughout the observation period; for one group, (523 4·1% participants) there was an initial worsening in mental health that was sustained with highly elevated scores. The other group (1011 7·0% participants) had little initial acute deterioration in their mental health, but reported a steady and sustained decline in mental health over time. These last two groups were more likely to have pre-existing mental or physical ill-health, to live in deprived neighbourhoods, and be of Asian, Black or mixed ethnicity. Infection with SARS-CoV-2, local lockdown, and financial difficulties all predicted a subsequent deterioration in mental health.
Between April and October 2020, the mental health of most UK adults remained resilient or returned to pre-pandemic levels. Around one in nine individuals had deteriorating or consistently poor mental health. People living in areas affected by lockdown, struggling financially, with pre-existing conditions, or infection with SARS-CoV-2 might benefit most from early intervention.
None.
Children of parents with mental disorder face multiple challenges.
To summarise evidence about parental mental disorder and child physical health.
We searched seven databases for cohort or ...case-control studies quantifying associations between parental mental disorders (substance use, psychotic, mood, anxiety, obsessive-compulsive, post-traumatic stress and eating) and offspring physical health. Studies were excluded if: they reported perinatal outcomes only (<28 days) or outcomes after age 18; they measured outcome prior to exposure; or the sample was drawn from diseased children. A meta-analysis was conducted. The protocol was registered on the PROSPERO database (CRD42017072620).
Searches revealed 15 945 non-duplicated studies. Forty-one studies met our inclusion criteria: ten investigated accidents/injuries; eight asthma; three other atopic diseases; ten overweight/obesity; ten studied other illnesses (eight from low-and middle-income countries (LMICs)). Half of the studies investigated maternal perinatal mental health, 17% investigated paternal mental disorder and 87% examined maternal depression. Meta-analysis revealed significantly higher rates of injuries (OR = 1.15, 95% CI 1.04-1.26), asthma (OR = 1.26, 95% CI 1.12-1.41) and outcomes recorded in LMICs (malnutrition: OR = 2.55, 95% CI 1.74-3.73; diarrhoea: OR = 2.16, 95% CI 1.65-2.84). Evidence was inconclusive for obesity and other atopic disorders.
Children of parents with mental disorder have health disadvantages; however, the evidence base is limited to risks for offspring following postnatal depression in mothers and there is little focus on fathers in the literature. Understanding the physical health risks of these vulnerable children is vital to improving lives. Future work should focus on discovering mechanisms linking physical and mental health across generations.
None.
Deaths in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic in England and Wales were unevenly distributed socioeconomically and geographically. However, the full scale of ...inequalities may have been underestimated to date, as most measures of excess mortality do not adequately account for varying age profiles of deaths between social groups. We measured years of life lost (YLL) attributable to the pandemic, directly or indirectly, comparing mortality across geographic and socioeconomic groups.
We used national mortality registers in England and Wales, from 27 December 2014 until 25 December 2020, covering 3,265,937 deaths. YLLs (main outcome) were calculated using 2019 single year sex-specific life tables for England and Wales. Interrupted time-series analyses, with panel time-series models, were used to estimate expected YLL by sex, geographical region, and deprivation quintile between 7 March 2020 and 25 December 2020 by cause: direct deaths (COVID-19 and other respiratory diseases), cardiovascular disease and diabetes, cancer, and other indirect deaths (all other causes). Excess YLL during the pandemic period were calculated by subtracting observed from expected values. Additional analyses focused on excess deaths for region and deprivation strata, by age-group. Between 7 March 2020 and 25 December 2020, there were an estimated 763,550 (95% CI: 696,826 to 830,273) excess YLL in England and Wales, equivalent to a 15% (95% CI: 14 to 16) increase in YLL compared to the equivalent time period in 2019. There was a strong deprivation gradient in all-cause excess YLL, with rates per 100,000 population ranging from 916 (95% CI: 820 to 1,012) for the least deprived quintile to 1,645 (95% CI: 1,472 to 1,819) for the most deprived. The differences in excess YLL between deprivation quintiles were greatest in younger age groups; for all-cause deaths, a mean of 9.1 years per death (95% CI: 8.2 to 10.0) were lost in the least deprived quintile, compared to 10.8 (95% CI: 10.0 to 11.6) in the most deprived; for COVID-19 and other respiratory deaths, a mean of 8.9 years per death (95% CI: 8.7 to 9.1) were lost in the least deprived quintile, compared to 11.2 (95% CI: 11.0 to 11.5) in the most deprived. For all-cause mortality, estimated deaths in the most deprived compared to the most affluent areas were much higher in younger age groups, but similar for those aged 85 or over. There was marked variability in both all-cause and direct excess YLL by region, with the highest rates in the North West. Limitations include the quasi-experimental nature of the research design and the requirement for accurate and timely recording.
In this study, we observed strong socioeconomic and geographical health inequalities in YLL, during the first calendar year of the COVID-19 pandemic. These were in line with long-standing existing inequalities in England and Wales, with the most deprived areas reporting the largest numbers in potential YLL.
In the presence of heterogeneous treatment effects, it is desirable to divide patients into subgroups based on their expected response to treatment. This is formalised via a personalised treatment ...recommendation: an algorithm that uses biomarker measurements to select treatments. It could be that multiple, rather than single, biomarkers better predict these subgroups. However, finding the optimal combination of multiple biomarkers can be a difficult prediction problem.
We described three parametric methods for finding the optimal combination of biomarkers in a personalised treatment recommendation, using randomised trial data: a regression approach that models outcome using treatment by biomarker interactions; an approach proposed by Kraemer that forms a combined measure from individual biomarker weights, calculated on all treated and control pairs; and a novel modification of Kraemer's approach that utilises a prognostic score to sample matched treated and control subjects. Using Monte Carlo simulations under multiple data-generating models, we compare these approaches and draw conclusions based on a measure of improvement under a personalised treatment recommendation compared to a standard treatment. The three methods are applied to data from a randomised trial of home-delivered pragmatic rehabilitation versus treatment as usual for patients with chronic fatigue syndrome (the FINE trial). Prior analysis of this data indicated some treatment effect heterogeneity from multiple, correlated biomarkers.
The regression approach outperformed Kraemer's approach across all data-generating scenarios. The modification of Kraemer's approach leads to improved treatment recommendations, except in the case where there was a strong unobserved prognostic biomarker. In the FINE example, the regression method indicated a weak improvement under its personalised treatment recommendation algorithm.
The method proposed by Kraemer does not perform better than a regression approach for combining multiple biomarkers. All methods are sensitive to misspecification of the parametric models.
We would like to draw attention to evidence of substantial bias in the article published in this journal by Jack et al. (BMC Med 18:1-12, 2020). They provide an analysis of antidepressant prescribing ...to children and young people (CYP; ages 5 to 17) in primary care in England and reported that only 24.7% of CYP prescribed SSRIs for the first time were seen by a child and adolescent psychiatrist--contrary to national guidelines. We believe that their analysis is based on incomplete data that misses a large proportion of specialist mental health contacts. This is because the dataset Jack et al. used to capture specialist mental health contact--The Hospital Episode Statistics (HES) dataset--has poor coverage, as most CYP mental health services do not submit data. We demonstrate the level of underreporting with an analysis of events in a large primary care dataset where there has been a record of definite contact with CYP mental health services. We report that as many as three quarters of specialist CYP contacts with mental health specialists are missed in the HES dataset, indicating that the figure presented by Jack et al. is substantially wrong. Keywords: Children and young people (CYP), Antidepressants, Prescriptions, Primary care, Secondary care
Most reports of pregnancy outcome in women with kidney transplants are single-center, retrospective, and include small numbers and few are compared with controls. The aim of this study was to collect ...information about pregnancy outcomes among all kidney transplant recipients in the United Kingdom, managed with current antenatal and nephrologic care, and to compare these data with a contemporaneous control group.
Pregnant women with a kidney transplant were identified through the UK Obstetric Surveillance System (UKOSS) between January 1, 2007 and December 31, 2009. Data on a comparison cohort were obtained from the UKOSS database, containing information on comparison women identified in previous studies. Outcomes were also compared with national data.
There were 105 pregnancies identified in 101 recipients. Median prepregnancy creatinine was 118 μmol/L. Preeclampsia developed in 24% compared with 4% of the comparison group. Median gestation at delivery was 36 weeks, with 52% of women delivering at <37 weeks, significantly higher than the national rate of 8%. Twenty-four infants (24%) were small for gestational age (<10th centile). There were two (2%) cases of acute rejection. Potential predictive factors for poor pregnancy outcome included >1 previous kidney transplant (P=0.03), first trimester serum creatinine >125 μmol/L (P=0.001), and diastolic BP >90 mmHg in the second (P=0.002) and third trimesters (P=0.05).
Most pregnancies in the United Kingdom in women with kidney transplants are successful but rates of maternal and neonatal complications remain high.
Little information exists about the prevalence of children exposed to maternal mental illness. We aimed to estimate the prevalence of children and adolescents exposed to maternal mental illness in ...the UK between 2005 and 2017 using primary care data.
In this national retrospective cohort study, we included children aged 0–16 years born between Jan 1, 1991, and Dec 31, 2015, who were linked to their mothers and registered on the primary care Clinical Practice Research Datalink (CPRD) between 2005 and 2017. We extracted data on diagnosis, symptoms, and therapy from the CRPD to define the following maternal mental illnesses: depression, anxiety, non-affective psychosis, affective psychosis, eating disorders, personality disorders, alcohol misuse disorder, and substance misuse disorder. We also extracted data on socioeconomic status from the Index of Multiple Deprivation 2010 and data on ethnicity from the Hospital Episode Statistics dataset. The main outcome was prevalence of maternal mental illness. Prevalence was calculated for each 2-year period of childhood (from age 0–<2 to 14–<16 years) using marginal predictions from a logistic regression model. We used survival analysis to estimate the incidence and cumulative risk of children experiencing maternal mental illness by age 16 years.
We identified 783 710 children registered in the UK CPRD mother-baby link database, and included 547 747 children (381 685 mothers) in our analysis. Overall prevalence of maternal mental illness was 23·2% (95% CI 23·1–23·4), which increased during childhood (21·9%, 21·7–22·1 among the 0–<2 year age group vs 27·3%, 26·8–27·8 among the 14–<16 year age group). Depression and anxiety were the most prevalent maternal mental illnesses. The proportion of children exposed to maternal mental illness increased from 22·2% (21·9–22·4) between 2005 and 2007 to 25·1% (24·8–25·5) between 2015 and 2017. Geographically, the highest prevalence of maternal mental illness was observed in Northern Ireland (29·8%, 29·0–30·5). In England, prevalence of maternal mental illness was highest among children in the most deprived areas (28·3%, 27·8–28·8). The incidence of maternal mental illness was highest between 0–3 months (26·7 per 100 person years, 26·4–27·1). By age 16 years, the cumulative risk of maternal mental illness was 53·1% (52·8–53·3).
One in four children aged 0–16 years are exposed to maternal mental illness and the prevalence of diagnosed and treated maternal mental illness is increasing. Policy makers and commissioners should consider this information and channel resources to target individuals in greatest need.
The European Research Council and the National Institute for Health Research.
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