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1.
JMIR Ment Health ; 9(3): e34898, 2022 Mar 11.
Article in English | MEDLINE | ID: covidwho-1770922

ABSTRACT

BACKGROUND: The mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. OBJECTIVE: We aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. METHODS: Data used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse-Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants' location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. RESULTS: This study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=-0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=-0.07, P<.001) the subsequent periodicity of mobility. CONCLUSIONS: Several phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.

2.
Occup Environ Med ; 2022 Mar 20.
Article in English | MEDLINE | ID: covidwho-1752900

ABSTRACT

OBJECTIVES: The COVID-19 pandemic has disrupted the social and working lives of many. Past studies have highlighted worsening mental health during the pandemic, but often rely on small samples or infrequent follow-up. This study draws on fortnightly assessments from a large occupational cohort to describe differing trajectories of mental health between April 2020 and April 2021 and individual characteristics associated with these trajectory types. METHODS: King's College London Coronavirus Health and Experiences of Colleagues at King's is an occupational cohort study at a large university in London, UK. Participants (n=2241) completed online questionnaires fortnightly between April 2020 and April 2021. Symptoms of anxiety and depression were assessed using Generalised Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9). RESULTS: On average, participants reported low levels of anxiety and depression (GAD-7 and PHQ-9 scores of 0-9, consistent with 'none', 'minimal' or 'mild' symptoms) throughout the year, with symptoms highest in April 2020 and decreasing over the summer months when no lockdown measures were in place. However, we observed more severe and variable symptoms among subgroups of participants. Four trajectory types for anxiety and depression were identified: 'persistent high severity' (6%-7% of participants), 'varying symptoms, opposing national cases' (4%-8%), 'varying symptoms, consistent with national cases' (6%-11%) and 'persistent low severity' (74%-84%). Younger age, female gender, caring responsibilities and shielding were associated with higher severity trajectory types. CONCLUSIONS: These data highlight differing individual responses to the pandemic and underscore the need to consider individual circumstances when assessing and treating mental health. Aggregate trends in anxiety and depression may hide greater variation and symptom severity among subgroups.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-324731

ABSTRACT

Background: The COVID-19 pandemic is a novel population-level stressor. As such, it is important to examine pandemic-related changes in mental health and to identify which individuals are at greatest risk of worsening symptoms. Methods: Online questionnaires were administered to 34,465 individuals in the UK, recruited from existing cohorts or via social media. Around one third (n = 12,718) with prior diagnoses of depression or anxiety completed pre-pandemic mental health assessments, allowing prospective investigation of symptom change. We examined changes in depression, anxiety and PTSD symptoms using prospective, retrospective and global ratings of change assessments. We also examined the effect of key risk factors on changes in symptoms.Outcomes: Prospective analyses showed small decreases in depression (PHQ-9: - .43 points) and anxiety symptoms (GAD-7: -.33 points), and increases in PTSD symptoms (PCL-6: .22 points). Conversely, retrospective analyses demonstrated large significant increases in depression (2.40 points) and anxiety symptoms (1.97 points) and 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Using both prospective and retrospective symptom measures, regression analyses demonstrated that worsening depression, anxiety and PTSD symptoms were associated with i) prior mental health diagnoses, ii) female gender;iii) young age, and iv) unemployed or student status.Interpretation: We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously-reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias underestimating prior symptom severity.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322262

ABSTRACT

We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiting the spread of COVID-19. We analysed data extracted from smartphone and wearable devices and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the UK, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post-hoc Dunns tests to assess differences in these features among baseline, pre-, and during-lockdown periods. We also studied behavioural differences by age, gender, body mass index (BMI), and educational background. We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between pre- and during-lockdown periods. We saw reduced sociality as measured through mobility features, and increased virtual sociality through phone usage. People were more active on their phones, spending more time using social media apps, particularly around major news events. Furthermore, participants had lower heart rate, went to bed later, and slept more. We also found that young people had longer homestay than older people during lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more. RADAR-base can be used to rapidly quantify and provide a holistic view of behavioural changes in response to public health interventions as a result of infectious outbreaks such as COVID-19.

5.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-319097

ABSTRACT

Background: The UK population’s mental health declined at the pandemic onset. Convenience sample surveys indicate recovery began soon after. Using a probability sample, we tracked average mental health during the pandemic, characterised distinct mental health trajectories and identified predictors of deterioration.Methods: Secondary analysis of five waves of UK Household Longitudinal Survey from late April-early October 2020 and pre-pandemic data, 2018-2019. Mental health was assessed in 19,763 adults (≥16 years) using 12-item General Health Questionnaire. Latent class growth models identified discrete mental health trajectories and fixed-effects regression identified predictors of change in mental health.Findings: Average population mental health deteriorated with onset of the pandemic and did not begin improving until July 2020. Latent class analysis identified six distinct mental health trajectories up to October 2020. Three-quarters had consistently good (46·2%) or very good (30·9%) mental health. Two ‘recovery’ groups (15·8%) initially experienced marked declines in mental health, improving to their pre-pandemic levels by October. For 4·8%, mental health steadily deteriorated and for 2·3% it was very poor throughout. These two groups were more likely to have pre-existing mental or physical ill-health, live in deprived neighbourhoods and be non-white. Infection with COVID-19, local lockdown and financial difficulties all predicted subsequent mental health deterioration.Interpretation: Between April-October 2020, the mental health of most UK adults remained resilient or returned to pre-pandemic levels. One-in-fourteen experienced deteriorating or consistently poor mental health. People living in areas affected by lockdown, struggling financially, with pre-existing conditions or COVID infection might benefit most from early intervention.Funding Statement: None.Declaration of Interests: None.Ethics Approval Statement: Ethics approval was granted by the University of Essex Ethics Committee for the COVID-19 web and telephone surveys (ETH1920-1271).

6.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-315649

ABSTRACT

This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilises data from the ongoing EU IMI RADAR-CNS research project that is investigating the feasibility of wearable devices and smart phones to monitor individuals with multiple sclerosis (MS), depression or epilepsy. Aspart of the project protocol, heart-rate data was collected from participants using a Fitbit wristband. The presence of COVID-19 in the cohort in this work was either confirmed through a positive swab test, or inferred through the self-reporting of a combination of symptoms including fever, respiratory symptoms, loss of smell or taste, tiredness and gastrointestinal symptoms. Experimental results indicate that our proposed contrastive convolutional auto-encoder (contrastive CAE), i. e., a combined architecture of an auto-encoder and contrastive loss, outperforms a conventional convolutional neural network (CNN), as well as a convolutional auto-encoder (CAE) without using contrastive loss. Our final contrastive CAE achieves 95.3% unweighted average recall, 86.4% precision, anF1 measure of 88.2%, a sensitivity of 100% and a specificity of 90.6% on a testset of 19 participants with MS who reported symptoms of COVID-19. Each of these participants was paired with a participant with MS with no COVID-19 symptoms.

7.
JMIR Res Protoc ; 10(12): e32653, 2021 Dec 21.
Article in English | MEDLINE | ID: covidwho-1599213

ABSTRACT

BACKGROUND: Multi-parametric remote measurement technologies (RMTs) comprise smartphone apps and wearable devices for both active and passive symptom tracking. They hold potential for understanding current depression status and predicting future depression status. However, the promise of using RMTs for relapse prediction is heavily dependent on user engagement, which is defined as both a behavioral and experiential construct. A better understanding of how to promote engagement in RMT research through various in-app components will aid in providing scalable solutions for future remote research, higher quality results, and applications for implementation in clinical practice. OBJECTIVE: The aim of this study is to provide the rationale and protocol for a 2-armed randomized controlled trial to investigate the effect of insightful notifications, progress visualization, and researcher contact details on behavioral and experiential engagement with a multi-parametric mobile health data collection platform, Remote Assessment of Disease and Relapse (RADAR)-base. METHODS: We aim to recruit 140 participants upon completion of their participation in the RADAR Major Depressive Disorder study in the London site. Data will be collected using 3 weekly tasks through an active smartphone app, a passive (background) data collection app, and a Fitbit device. Participants will be randomly allocated at a 1:1 ratio to receive either an adapted version of the active app that incorporates insightful notifications, progress visualization, and access to researcher contact details or the active app as usual. Statistical tests will be used to assess the hypotheses that participants using the adapted app will complete a higher percentage of weekly tasks (behavioral engagement: primary outcome) and score higher on self-awareness measures (experiential engagement). RESULTS: Recruitment commenced in April 2021. Data collection was completed in September 2021. The results of this study will be communicated via publication in 2022. CONCLUSIONS: This study aims to understand how best to promote engagement with RMTs in depression research. The findings will help determine the most effective techniques for implementation in both future rounds of the RADAR Major Depressive Disorder study and, in the long term, clinical practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT04972474; http://clinicaltrials.gov/ct2/show/NCT04972474. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/32653.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-293948

ABSTRACT

Background: There is growing global concern about the potential impact of the Covid-19 pandemic on population mental health. We examine changes in adult mental health in the UK population before and during the lockdown. <br><br>Methods: Secondary analysis of the UK Household Longitudinal Study Waves 6 (2014/15) to 9 (2018/19), matched to the Covid-19 web-survey completed by 17,452 panel members 23-29 April 2020. Mental health was assessed using the 12-item General Health Questionnaire (GHQ). Repeated cross-sectional analyses were conducted to examine annual temporal trends. Fixed effects regression models were fitted to identify within-person change compared to preceding trends. <br><br>Findings: Mean population GHQ-12 score increased from 11·5 (95% confidence interval: 11·3–11·6) in 2018/19 to 12·6 (12·5–12·8) in April 2020, one month into lockdown. This was 0·48 (0·07-0·90) points higher than expected when accounting for prior upward trends between 2013 and 2019. Comparing scores within-individuals, adjusting for time-trends and predictors, increases were greatest in 18-24-year-olds (2·7, 1·89-3·48), 25-34-year-olds (1·6, 0·96-2·18), women (0·9, 0·50-1·35), and people living with young children (1·45, 0·79-2·12). People employed before the pandemic averaged a notable increase (0·6;0·20-1·06). <br><br>Interpretation: In late April 2020, mental health in the UK deteriorated compared to trends pre-Covid, particularly in young people, women and those living with young children. Those in employment before the pandemic also experienced greater deterioration one month into lockdown, perhaps due to actual or anticipated redundancy. While deterioration occurred across income groups, we anticipate inequalities may widen over time, as in other causes of recessions.<br><br>Funding Statement: This study was unfunded.<br><br>Declaration of Interests: The authors declare no competing interests. <br><br>Ethics Approval Statement: The data used are publicly available via UK Data Service repository (study numbers 6614 and 8644), and do not require ethical assessment for academic research purposes.

9.
Occup Environ Med ; 79(4): 259-267, 2022 04.
Article in English | MEDLINE | ID: covidwho-1484054

ABSTRACT

OBJECTIVES: To characterise the baseline King's College London Coronavirus Health and Experiences of Colleagues at King's cohort and describe patterns of probable depression and anxiety among staff and postgraduate research students at a large UK university in April/May 2020. METHODS: An online survey was sent to current staff and postgraduate research students via email in April 2020 (n=2590). Primary outcomes were probable depression and anxiety, measured with the Patient Health Questionnaire-9 and Generalised Anxiety Disorder-7, respectively. Secondary outcomes were alcohol use and perceived change in mental health. Outcomes were described using summary statistics and multivariable Poisson regression was used to explore associations with six groups of predictors: demographics and prior mental health, living arrangements, caring roles, healthcare, occupational factors and COVID-19 infection. All analyses were weighted to account for differences between the sample and target population in terms of age, gender, and ethnicity. RESULTS: Around 20% of staff members and 30% of postgraduate research students met thresholds for probable depression or anxiety on the questionnaires. This doubled to around 40% among younger respondents aged <25. Other factors associated with probable depression and anxiety included female gender, belonging to an ethnic minority group, caregiving responsibilities and shielding or isolating. Around 20% of participants were found to reach cut-off for hazardous drinking on Alcohol Use Disorders Identification Test, while 30% were drinking more than before the pandemic. CONCLUSIONS: Our study shows worrying levels of symptoms of depression, anxiety and alcohol use disorder in an occupational sample from a large UK university in the months following the outbreak of the COVID-19 pandemic.


Subject(s)
Alcoholism , COVID-19 , Aged , Alcoholism/epidemiology , Anxiety/epidemiology , Anxiety/psychology , COVID-19/epidemiology , Depression/epidemiology , Depression/psychology , Female , Humans , Mental Health , Minority Groups , Pandemics , SARS-CoV-2 , Students/psychology , United Kingdom/epidemiology , Universities
10.
Pattern Recognit ; 123: 108403, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1482848

ABSTRACT

This study proposes a contrastive convolutional auto-encoder (contrastive CAE), a combined architecture of an auto-encoder and contrastive loss, to identify individuals with suspected COVID-19 infection using heart-rate data from participants with multiple sclerosis (MS) in the ongoing RADAR-CNS mHealth research project. Heart-rate data was remotely collected using a Fitbit wristband. COVID-19 infection was either confirmed through a positive swab test, or inferred through a self-reported set of recognised symptoms of the virus. The contrastive CAE outperforms a conventional convolutional neural network (CNN), a long short-term memory (LSTM) model, and a convolutional auto-encoder without contrastive loss (CAE). On a test set of 19 participants with MS with reported symptoms of COVID-19, each one paired with a participant with MS with no COVID-19 symptoms, the contrastive CAE achieves an unweighted average recall of 95.3 % , a sensitivity of 100 % and a specificity of 90.6 % , an area under the receiver operating characteristic curve (AUC-ROC) of 0.944, indicating a maximum successful detection of symptoms in the given heart rate measurement period, whilst at the same time keeping a low false alarm rate.

11.
Lancet Reg Health Eur ; 11: 100228, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1458579

ABSTRACT

BACKGROUND: People with mental disorders and intellectual disabilities experience excess mortality compared with the general population. The impact of COVID-19 on exacerbating this, and in widening ethnic inequalities, is unclear. METHODS: Prospective data (N=167,122) from a large mental healthcare provider in London, UK, with deaths from 2019 to 2020, used to assess age- and gender-standardised mortality ratios (SMRs) across nine psychiatric conditions (schizophrenia-spectrum disorders, affective disorders, somatoform/ neurotic disorders, personality disorders, learning disabilities, eating disorders, substance use disorders, pervasive developmental disorders, dementia) and by ethnicity. FINDINGS: Prior to the World Health Organization (WHO) declaring COVID-19 a public health emergency on 30th January 2020, all-cause SMRs across all psychiatric cohorts were more than double the general population. By the second quarter of 2020, when the UK experienced substantial peaks in COVID-19 deaths, all-cause SMRs increased further, with COVID-19 SMRs elevated across all conditions (notably: learning disabilities: SMR: 9.24 (95% CI: 5.98-13.64), pervasive developmental disorders: 5.01 (95% CI: 2.40-9.20), eating disorders: 4.81 (95% CI: 1.56-11.22), schizophrenia-spectrum disorders: 3.26 (95% CI: 2.55-4.10), dementia: 3.82 (95% CI: 3.42, 4.25) personality disorders 4.58 (95% CI: 3.09-6.53)). Deaths from other causes remained at least double the population average over the whole year. Increased SMRs were similar across ethnic groups. INTERPRETATION: People with mental disorders and intellectual disabilities were at a greater risk of deaths relative to the general population before, during and after the first peak of COVID-19 deaths, with similar risks by ethnicity. Mortality from non-COVID-19/ other causes was elevated before/ during the pandemic, with higher COVID-19 mortality during the pandemic. FUNDING: ESRC (JD, CM), NIHR (JD, RS, MH), Health Foundation (JD), GSK, Janssen, Takeda (RS).

13.
BMJ Open ; 11(6): e051687, 2021 06 30.
Article in English | MEDLINE | ID: covidwho-1290907

ABSTRACT

INTRODUCTION: The COVID-19 pandemic has had profound effects on the working lives of healthcare workers (HCWs), but the extent to which their well-being and mental health have been affected remains unclear. This longitudinal cohort study aims to recruit a cohort of National Health Service (NHS) HCWs, conducting surveys at regular intervals to provide evidence about the prevalence of symptoms of mental disorders, and investigate associated factors such as occupational contexts and support interventions available. METHODS AND ANALYSIS: All staff, students and volunteers working in the 18 participating NHS Trusts in England will be sent emails inviting them to complete a survey at baseline, with email invitations for the follow-up surveys sent 6 months and 12 months later. Opening in late April 2020, the baseline survey collects data on demographics, occupational/organisational factors, experiences of COVID-19, validated measures of symptoms of poor mental health (eg, depression, anxiety, post-traumatic stress disorder), and constructs such as resilience and moral injury. These surveys will be complemented by in-depth psychiatric interviews with a sample of HCWs. Qualitative interviews will also be conducted, to gain deeper understanding of the support programmes used or desired by staff, and facilitators and barriers to accessing such programmes. ETHICS AND DISSEMINATION: Ethical approval for the study was granted by the Health Research Authority (reference: 20/HRA/210, IRAS: 282686) and local Trust Research and Development approval. Cohort data are collected via Qualtrics online survey software, pseudonymised and held on secure university servers. Participants are aware that they can withdraw from the study at any time, and there is signposting to support services if participants feel they need it. Only those consenting to be contacted about further research will be invited to participate in further components. Findings will be rapidly shared with NHS Trusts, and via academic publications in due course.


Subject(s)
COVID-19 , Pandemics , Cohort Studies , England/epidemiology , Health Personnel , Humans , Longitudinal Studies , SARS-CoV-2 , State Medicine
14.
Occup Environ Med ; 78(11): 801-808, 2021 11.
Article in English | MEDLINE | ID: covidwho-1286749

ABSTRACT

OBJECTIVES: This study reports preliminary findings on the prevalence of, and factors associated with, mental health and well-being outcomes of healthcare workers during the early months (April-June) of the COVID-19 pandemic in the UK. METHODS: Preliminary cross-sectional data were analysed from a cohort study (n=4378). Clinical and non-clinical staff of three London-based NHS Trusts, including acute and mental health Trusts, took part in an online baseline survey. The primary outcome measure used is the presence of probable common mental disorders (CMDs), measured by the General Health Questionnaire. Secondary outcomes are probable anxiety (seven-item Generalised Anxiety Disorder), depression (nine-item Patient Health Questionnaire), post-traumatic stress disorder (PTSD) (six-item Post-Traumatic Stress Disorder checklist), suicidal ideation (Clinical Interview Schedule) and alcohol use (Alcohol Use Disorder Identification Test). Moral injury is measured using the Moray Injury Event Scale. RESULTS: Analyses showed substantial levels of probable CMDs (58.9%, 95% CI 58.1 to 60.8) and of PTSD (30.2%, 95% CI 28.1 to 32.5) with lower levels of depression (27.3%, 95% CI 25.3 to 29.4), anxiety (23.2%, 95% CI 21.3 to 25.3) and alcohol misuse (10.5%, 95% CI 9.2 to 11.9). Women, younger staff and nurses tended to have poorer outcomes than other staff, except for alcohol misuse. Higher reported exposure to moral injury (distress resulting from violation of one's moral code) was strongly associated with increased levels of probable CMDs, anxiety, depression, PTSD symptoms and alcohol misuse. CONCLUSIONS: Our findings suggest that mental health support for healthcare workers should consider those demographics and occupations at highest risk. Rigorous longitudinal data are needed in order to respond to the potential long-term mental health impacts of the pandemic.


Subject(s)
COVID-19/psychology , Health Personnel/psychology , Pandemics , Adult , Anxiety/epidemiology , Anxiety/etiology , COVID-19/epidemiology , Cross-Sectional Studies , Depression/epidemiology , Depression/etiology , Female , Health Personnel/statistics & numerical data , Humans , Male , Middle Aged , Occupational Diseases/epidemiology , Occupational Diseases/etiology , Occupational Diseases/psychology , Pandemics/statistics & numerical data , Prevalence , Psychology , Stress Disorders, Post-Traumatic/epidemiology , Stress Disorders, Post-Traumatic/etiology , Suicidal Ideation , Surveys and Questionnaires , United Kingdom/epidemiology
15.
Clin Transl Immunology ; 10(6): e1292, 2021.
Article in English | MEDLINE | ID: covidwho-1258049

ABSTRACT

OBJECTIVES: It remains unknown how inflammatory marker levels differ amongst individuals susceptible to coronavirus disease 2019 (COVID-19), prior to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the onset of the cytokine storm. We used genetic risk scores to model how susceptibility to severe COVID-19 correlates with baseline levels of 35 inflammatory markers, by testing their impact in a SARS-CoV-2-negative population cohort. Because of the established effects of age and body mass index on severe COVID-19 risk, we further considered how these variables interacted with genetic risk to affect inflammatory marker levels. METHODS: We accessed data on 406 SARS-CoV-2-negative individuals as part of a UK population study. Multiplex electrochemiluminescence methods were applied to blood serum, and 35 inflammatory markers were assayed. Corresponding genotype data, alongside results from a large genome-wide association study of severe COVID-19, allowed us to construct genetic risk scores and to test their impact on inflammatory protein levels. RESULTS: Our results revealed that a higher genetic risk for severe COVID-19 was associated with lower blood levels of interferon gamma (IFN-γ), vascular endothelial growth factor D (VEGF-D) and tumor necrosis factor alpha (TNF-α). Inflammatory profiles of those with high genetic risk increasingly diverge from the norm in association with age and obesity. CONCLUSION: Our results support the theory that individuals at risk of severe COVID-19 have a deficient innate immunity marked by reduced levels of inflammatory markers at baseline, including IFN-γ, VEGF-D and TNF-α. We hypothesise that a secondary overactive adaptive immune response may subsequently explain the high levels of cytokines observed in SARS-CoV-2-positive COVID-19 patients.

16.
Lancet Psychiatry ; 8(7): 610-619, 2021 07.
Article in English | MEDLINE | ID: covidwho-1219821

ABSTRACT

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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. FUNDING: None.


Subject(s)
COVID-19/complications , Mental Disorders/epidemiology , Mental Health/statistics & numerical data , Models, Statistical , Adolescent , Adult , Female , Humans , Longitudinal Studies , Male , Middle Aged , Surveys and Questionnaires , United Kingdom/epidemiology , Young Adult
17.
Int J Environ Res Public Health ; 18(6)2021 03 10.
Article in English | MEDLINE | ID: covidwho-1124957

ABSTRACT

Coronavirus disease (COVID-19) and resulting restrictions have significantly impacted physical activity levels. However, objectively measured changes in physical activity levels among UK university students during lockdown are understudied. Using data collected via remote measurement technology from a mobile physical activity tracker, this study aimed to describe the longitudinal trajectories of physical activity following the start of lockdown among students at a large UK university, and to investigate whether these trajectories varied according to age, gender, and ethnicity. Continuous physical activity data for steps walked per week (n = 730) and miles run per week (n = 264) were analysed over the first period of lockdown and subsequent restriction easing using negative binomial mixed models for repeated measures. Throughout the observation period, more steps were walked by males compared to females, and by White groups compared to all other ethnic groups combined. However, there was a gradual increase in the number of steps walked per week following the commencement of lockdown, irrespective of sociodemographic characteristics. For females only, there was a decrease in the number of miles run per week following lockdown. The long-term impact of the pandemic on physical health is unknown, but our results highlight changes in physical activity which could have implications for physical health.


Subject(s)
COVID-19 , Coronavirus , Communicable Disease Control , Exercise , Female , Humans , Male , SARS-CoV-2 , Students , United Kingdom , Universities
18.
Lancet Reg Health Eur ; 4: 100071, 2021 May.
Article in English | MEDLINE | ID: covidwho-1104123

ABSTRACT

BACKGROUND: Self-report data on mental distress indicate a deterioration of population mental health in many countries during the COVID-19 pandemic. A Norwegian epidemiological diagnostic psychiatric interview survey was conducted from January to September 2020, allowing for comparison of mental disorder and suicidal ideation prevalence from before through different pandemic periods. Prevalence of suicide deaths were compared between 2020 and 2014-2018. METHODS: Participants from the Trøndelag Health Study (HUNT) in Trondheim were recruited through repeated probability sampling. Using the Composite International Diagnostic Interview (CIDI 5.0) (n = 2154), current prevalence of mental disorders and suicidal ideation was examined in repeated cross-sectional analyzes. Data on suicide deaths was retrieved from the Norwegian Cause of Death Registry and compared for the months March to May in 2014-2018 and 2020. FINDINGS: Prevalence of current mental disorders decreased significantly from the pre-pandemic period (January 28th to March 11th 2020; 15•3% (95% CI 12•4-18•8)) to the first pandemic period (March 12th - May 31st; 8•7% (6•8-11•0)). Prevalences were similar between the pre-pandemic period and the interim (June 1st July 31st; 14•2% (11•4-17•5)) and second periods (August 1st-September 18th; 11•9% (9•0-15•6)). No significant differences were observed in suicidal ideation or in suicide deaths. INTERPRETATION: Except for a decrease in mental disorders in the first pandemic period, the findings suggest stable levels of mental disorders, suicidal ideation and suicide deaths during the first six months of the COVID-19 pandemic compared to pre-pandemic levels. Potential methodological and contextual explanations of these findings compared with findings from other studies are discussed. FUNDING: None.

20.
Br J Psychiatry ; 217(4): 540-542, 2020 10.
Article in English | MEDLINE | ID: covidwho-853428

ABSTRACT

The effects of the COVID-19 pandemic on population mental health are unknown. We need to understand the scale of any such impact in different sections of the population, who is most affected and how best to mitigate, prevent and treat any excess morbidity. We propose a coordinated and interdisciplinary mental health science response.


Subject(s)
Coronavirus Infections , Mental Disorders , Pandemics , Pneumonia, Viral , Preventive Psychiatry/methods , Psychosocial Support Systems , Public Health/methods , Betacoronavirus/pathogenicity , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/psychology , Coronavirus Infections/therapy , Humans , Mental Disorders/epidemiology , Mental Disorders/prevention & control , Mental Disorders/virology , Mental Health , Mental Health Services/organization & administration , Mental Health Services/standards , Pneumonia, Viral/epidemiology , Pneumonia, Viral/psychology , Pneumonia, Viral/therapy , Quality Improvement , Research Design , Risk Assessment/methods , SARS-CoV-2
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