A cancer diagnosis can have a substantial impact on mental health and wellbeing. Depression and anxiety may hinder cancer treatment and recovery, as well as quality of life and survival. We argue ...that more research is needed to prevent and treat co-morbid depression and anxiety among people with cancer and that it requires greater clinical priority. For background and to support our argument, we synthesise existing systematic reviews relating to cancer and common mental disorders, focusing on depression and anxiety. We searched several electronic databases for relevant reviews on cancer, depression and anxiety from 2012 to 2019. Several areas are covered: factors that may contribute to the development of common mental disorders among people with cancer; the prevalence of depression and anxiety; and potential care and treatment options. We also make several recommendations for future research. Numerous individual, psychological, social and contextual factors potentially contribute to the development of depression and anxiety among people with cancer, as well as characteristics related to the cancer and treatment received. Compared to the general population, the prevalence of depression and anxiety is often found to be higher among people with cancer, but estimates vary due to several factors, such as the treatment setting, type of cancer and time since diagnosis. Overall, there are a lack of high-quality studies into the mental health of people with cancer following treatment and among long-term survivors, particularly for the less prevalent cancer types and younger people. Studies that focus on prevention are minimal and research covering low- and middle-income populations is limited.
Research is urgently needed into the possible impacts of long-term and late effects of cancer treatment on mental health and how these may be prevented, as increasing numbers of people live with and beyond cancer.
Older people have been reported to be at higher risk of COVID-19 mortality. This study explored the factors mediating this association and whether older age was associated with increased mortality ...risk in the absence of other risk factors.
In UK Biobank, a population cohort study, baseline data were linked to COVID-19 deaths. Poisson regression was used to study the association between current age and COVID-19 mortality.
Among eligible participants, 438 (0.09%) died of COVID-19. Current age was associated exponentially with COVID-19 mortality. Overall, participants aged ≥75 years were at 13-fold (95% CI 9.13-17.85) mortality risk compared with those <65 years. Low forced expiratory volume in 1 second, high systolic blood pressure, low handgrip strength, and multiple long-term conditions were significant mediators, and collectively explained 39.3% of their excess risk. The associations between these risk factors and COVID-19 mortality were stronger among older participants. Participants aged ≥75 without additional risk factors were at 4-fold risk (95% CI 1.57-9.96, P = 0.004) compared with all participants aged <65 years.
Higher COVID-19 mortality among older adults was partially explained by other risk factors. 'Healthy' older adults were at much lower risk. Nonetheless, older age was an independent risk factor for COVID-19 mortality.
•Willingness to be vaccinated was generally high across the UK population.•Vaccine hesitancy exists in population subgroups.•Black and Pakistani/Bangladeshi ethnic groups had higher levels of vaccine ...hesitancy.•Vaccine hesitancy levels are higher in people with lower education levels.•Focus on ethnic minority and socioeconomic groups is needed during vaccine delivery.
Vaccine hesitancy could undermine efforts to control COVID-19. We investigated the prevalence of COVID-19 vaccine hesitancy in the UK and identified vaccine hesitant subgroups. The ‘Understanding Society’ COVID-19 survey asked participants (n = 12,035) their likelihood of vaccine uptake and reason for hesitancy. Cross-sectional analysis assessed vaccine hesitancy prevalence and logistic regression calculated odds ratios. Overall vaccine hesitancy was low (18% unlikely/very unlikely). Vaccine hesitancy was higher in women (21.0% vs 14.7%), younger age groups (26.5% in 16–24 year olds vs 4.5% in 75 + ) and those with lower education levels (18.6% no qualifications vs 13.2% degree qualified). Vaccine hesitancy was high in Black (71.8%) and Pakistani/Bangladeshi (42.3%) ethnic groups. Odds ratios for vaccine hesitancy were 13.42 (95% CI:6.86, 26.24) in Black and 2.54 (95% CI:1.19, 5.44) in Pakistani/Bangladeshi groups (compared to White British/Irish) and 3.54 (95% CI:2.06, 6.09) for people with no qualifications versus degree. Urgent action to address hesitancy is needed for some but not all ethnic minority groups.
It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on ...the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors.
We studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population.
Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.
Minority ethnic groups have been disproportionately affected by the COVID-19 pandemic. While the exact reasons for this remain unclear, they are likely due to a complex interplay of factors rather ...than a single cause. Reducing these inequalities requires a greater understanding of the causes. Research to date, however, has been hampered by a lack of theoretical understanding of the meaning of ‘ethnicity’ (or race) and the potential pathways leading to inequalities. In particular, quantitative analyses have often adjusted away the pathways through which inequalities actually arise (ie, mediators for the effect of interest), leading to the effects of social processes, and particularly structural racism, becoming hidden. In this paper, we describe a framework for understanding the pathways that have generated ethnic (and racial) inequalities in COVID-19. We suggest that differences in health outcomes due to the pandemic could arise through six pathways: (1) differential exposure to the virus; (2) differential vulnerability to infection/disease; (3) differential health consequences of the disease; (4) differential social consequences of the disease; (5) differential effectiveness of pandemic control measures and (6) differential adverse consequences of control measures. Current research provides only a partial understanding of some of these pathways. Future research and action will require a clearer understanding of the multiple dimensions of ethnicity and an appreciation of the complex interplay of social and biological pathways through which ethnic inequalities arise. Our framework highlights the gaps in the current evidence and pathways that need further investigation in research that aims to address these inequalities.
Understanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study.
The UK Biobank study ...recruited 40-70-year-olds in 2006-2010 from the general population, collecting information about self-defined ethnicity and socioeconomic variables (including area-level socioeconomic deprivation and educational attainment). SARS-CoV-2 test results from Public Health England were linked to baseline UK Biobank data. Poisson regression with robust standard errors was used to assess risk ratios (RRs) between the exposures and dichotomous variables for being tested, having a positive test and testing positive in hospital. We also investigated whether ethnicity and socioeconomic position were associated with having a positive test amongst those tested. We adjusted for covariates including age, sex, social variables (including healthcare work and household size), behavioural risk factors and baseline health.
Amongst 392,116 participants in England, 2658 had been tested for SARS-CoV-2 and 948 tested positive (726 in hospital) between 16 March and 3 May 2020. Black and south Asian groups were more likely to test positive (RR 3.35 (95% CI 2.48-4.53) and RR 2.42 (95% CI 1.75-3.36) respectively), with Pakistani ethnicity at highest risk within the south Asian group (RR 3.24 (95% CI 1.73-6.07)). These ethnic groups were more likely to be hospital cases compared to the white British. Adjustment for baseline health and behavioural risk factors led to little change, with only modest attenuation when accounting for socioeconomic variables. Socioeconomic deprivation and having no qualifications were consistently associated with a higher risk of confirmed infection (RR 2.19 for most deprived quartile vs least (95% CI 1.80-2.66) and RR 2.00 for no qualifications vs degree (95% CI 1.66-2.42)).
Some minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study, which was not accounted for by differences in socioeconomic conditions, baseline self-reported health or behavioural risk factors. An urgent response to addressing these elevated risks is required.
Advances in the early detection of cancer and its treatment have resulted in an increasing number of people living with and beyond breast cancer. Multimorbidity is also becoming more common in this ...population as more people live longer with breast cancer and experience late effects of cancer treatment. Breast cancer survivors have heightened risk of depression, but to what extent multimorbidity affects the mental health of this population is less clear. This study aims to investigate the association between multimorbidity and depression among women living with and beyond breast cancer in the UK Biobank cohort.
Data from UK Biobank (recruitment during 2006 to 2010, aged 40-70 years) were used to identify 8438 women with a previous diagnosis of breast cancer via linked cancer registries in England, Scotland and Wales. The lifetime number of chronic conditions was self-reported and multimorbidity defined as 0, 1, 2, 3, 4 or 5+. The Patient Health Questionnaire (PHQ-2) was used to define participants that were likely to have depression based on their symptom reporting at baseline. Logistic regression models were used to analyse the associations between multimorbidity and depression, accounting for a number of potential sociodemographic confounding variables (including age, ethnicity, socioeconomic deprivation, education level and marital status) and characteristics related to the cancer (number of years since diagnosis and recurrence/secondary cancer).
Multimorbidity was common among breast cancer survivors, with 32.9% of women experiencing one and 30.1% experiencing two or more chronic health conditions. Hypertension (25.8%), painful conditions (18.3%), and asthma (11.6%) were the three most common co-morbid conditions. 5.3% of participants had current depression. A strong, dose-response relationship was found between multimorbidity and the likelihood of depression (OR = 2.09, 95% CI: 1.56-2.79 for two conditions and OR = 6.06, 95% CI: 3.63-10.14 for five or more conditions).
Multimorbidity and depression were strongly associated among female UK Biobank participants with a previous breast cancer diagnosis. This association became increasingly pronounced as the number of chronic comorbid conditions increased. As more people survive cancer for longer, increasing recognition and support for multimorbidity and its impact on mental health is needed.
BackgroundThere are concerns that COVID-19 mitigation measures, including the ‘lockdown’, may have unintended health consequences. We examined trends in mental health and health behaviours in the UK ...before and during the initial phase of the COVID-19 lockdown and differences across population subgroups.MethodsRepeated cross-sectional and longitudinal analysis of the UK Household Longitudinal Study, including representative samples of over 27,000 adults (aged 18+) interviewed in four survey waves between 2015 and 2020. A total of 9748 adults had complete data for longitudinal analyses. Outcomes included psychological distress (General Health Questionnaire-12), loneliness, current cigarette smoking, use of e-cigarettes and alcohol consumption. Cross-sectional prevalence estimates were calculated and multilevel Poisson regression assessed associations between time period and the outcomes of interest, as well as differential associations by age, gender, education level and ethnicity.ResultsPsychological distress increased 1 month into lockdown with the prevalence rising from 19.4% (95% CI 18.7% to 20.1%) in 2017–2019 to 30.6% (95% CI 29.1% to 32.3%) in April 2020 (RR=1.3, 95% CI 1.2 to 1.4). Groups most adversely affected included women, young adults, people from an Asian background and those who were degree educated. Loneliness remained stable overall (RR=0.9, 95% CI 0.6 to 1.5). Smoking declined (RR=0.9, 95% CI=0.8,1.0) and the proportion of people drinking four or more times per week increased (RR=1.4, 95% CI 1.3 to 1.5), as did binge drinking (RR=1.5, 95% CI 1.3 to 1.7).ConclusionsPsychological distress increased 1 month into lockdown, particularly among women and young adults. Smoking declined, but adverse alcohol use generally increased. Effective measures are required to mitigate negative impacts on health.
The effects of coronavirus disease 2019 (COVID-19) on the population's mental health and well-being are likely to be profound and long lasting.
To investigate the trajectory of mental health and ...well-being during the first 6 weeks of lockdown in adults in the UK.
A quota survey design and a sampling frame that permitted recruitment of a national sample was employed. Findings for waves 1 (31 March to 9 April 2020), 2 (10 April to 27 April 2020) and 3 (28 April to 11 May 2020) are reported here. A range of mental health factors was assessed: pre-existing mental health problems, suicide attempts and self-harm, suicidal ideation, depression, anxiety, defeat, entrapment, mental well-being and loneliness.
A total of 3077 adults in the UK completed the survey at wave 1. Suicidal ideation increased over time. Symptoms of anxiety, and levels of defeat and entrapment decreased across waves whereas levels of depressive symptoms did not change significantly. Positive well-being also increased. Levels of loneliness did not change significantly over waves. Subgroup analyses showed that women, young people (18-29 years), those from more socially disadvantaged backgrounds and those with pre-existing mental health problems have worse mental health outcomes during the pandemic across most factors.
The mental health and well-being of the UK adult population appears to have been affected in the initial phase of the COVID-19 pandemic. The increasing rates of suicidal thoughts across waves, especially among young adults, are concerning.
1. Examine the relationship between household wealth, social participation and loneliness among older people across Europe. 2. Investigate whether relationships vary by type of social participation ...(charity/volunteer work, sports/social clubs, educational/training course, and political/community organisations) and gender. 3. Examine whether social participation moderates the association between wealth and loneliness.
Data (N=29,795) were taken from the fifth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE), which was collected during 2013 from 14 European countries. Loneliness was measured using the short version of the Revised-University of California, Los Angeles (R-UCLA) Loneliness Scale. We used multilevel logistic models stratified by gender to examine the relationships between variables, with individuals nested within countries.
The risk of loneliness was highest in the least wealthy groups and lowest in the wealthiest groups. Frequent social participation was associated with a lower risk of loneliness and moderated the association between household wealth and loneliness, particularly among men. Compared to the wealthiest men who often took part in formal social activities, the least wealthy men who did not participate had greater risk of loneliness (OR=1.91, 95% CI: 1.44 to 2.51). This increased risk was not observed among the least wealthy men who reported frequent participation in formal social activities (OR=1.12, 95% CI: 0.76 to 1.67).
Participation in external social activities may help to reduce loneliness among older adults and potentially acts as a buffer against the adverse effects of socioeconomic disadvantage.
•Loneliness among older people is an increasing public health concern.•Loneliness and social participation are socially patterned by wealth.•Social participation may protect against loneliness associated with low wealth.
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