How does mental health stigma get under the skin? Cross-sectional analysis using the Health Survey for England

Despite increased awareness of mental health problems, stigma persists. Little research has examined potential health and wellbeing outcomes associated with stigma. The aim of this study was to investigate relationships between mental health stigma, metabolic and cardiovascular biomarkers, as well as wellbeing and quality of life among people with no mental disorder, common mental disorders and severe mental illness. Data were taken from adults aged 16 + years participating in the Health Survey for England in 2014 (N = 5491). Mental health stigma was measured using the 12-item Community Attitudes towards the Mentally Ill (CAMI) scale, intended to measure attitudes around prejudice and exclusion, and tolerance and support for community care. Individuals were divided into six groups based on their mental health (no mental disorder, common mental disorder, severe mental illness) and whether they exhibited more (≤25th percentile) or less (>25th percentile) stigmatising attitudes. Metabolic and cardiovascular biomarker outcomes included systolic and diastolic blood pressure; total cholesterol; high-density lipoprotein (HDL) cholesterol; glycated haemoglobin, body mass index (BMI), waist-hip ratio and resting pulse rate. Biomarkers were analysed individually and as an allostatic load score. Wellbeing was measured using Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) and quality of life via Euro-QoL-5D (EQ-5D). Linear regression models were calculated adjusted for confounders. Compared to individuals with less stigmatising attitudes, results suggested that those with more negative attitudes exhibited poorer wellbeing and quality of life across all mental disorder/stigma groups, including those with no mental disorder (WEMWBS (range 14–70): b = -1.384, 95% CI: -2.107 to -0.661). People with severe mental illness generally had unhealthier biomarker profiles and allostatic load scores, but results were inconsistent for any additional influence of mental health stigma. Reducing stigma may be beneficial for population wellbeing, but further research is needed to clarify whether stigma contributes to adverse biomarkers amongst people with mental illness

Trends in population mental health before and after the 2008 recession: a repeat cross-sectional analysis of the 1991-2010 health surveys of England

<p>Objective: To assess short-term differences in population mental health before and after the 2008 recession and explore how and why these changes differ by gender, age and socio-economic position.</p> <p>Design: Repeat cross-sectional analysis of survey data.</p> <p>Setting: England.</p> <p>Participants: Representative samples of the working age (25–64 years) general population participating in the Health Survey for England between 1991 and 2010 inclusive.</p> <p>Main outcome measures: Prevalence of poor mental health (caseness) as measured by the general health questionnaire-12 (GHQ).</p> <p>Results: Age–sex standardised prevalence of GHQ caseness increased from 13.7% (95% CI 12.9% to 14.5%) in 2008 to 16.4% (95% CI 14.9% to 17.9%) in 2009 and 15.5% (95% CI 14.4% to 16.7%) in 2010. Women had a consistently greater prevalence since 1991 until the current recession. However, compared to 2008, men experienced an increase in age-adjusted caseness of 5.1% (95% CI 2.6% to 7.6%, p<0.001) in 2009 and 3% (95% CI 1.2% to 4.9%, p=0.001) in 2010, while no statistically significant changes were seen in women. Adjustment for differences in employment status and education level did not account for the observed increase in men nor did they explain the differential gender patterning. Over the last decade, socio-economic inequalities showed a tendency to increase but no clear evidence for an increase in inequalities associated with the recession was found. Similarly, no evidence was found for a differential effect between age groups.</p> <p>Conclusions: Population mental health in men has deteriorated within 2 years of the onset of the current recession. These changes, and their patterning by gender, could not be accounted for by differences in employment status. Further work is needed to monitor recessionary impacts on health inequalities in response to ongoing labour market and social policy changes.</p&gt

Employment status and income as potential mediators of educational inequalities in population mental health

We assessed whether educational inequalities in mental health may be mediated by employment status and household income. Poor mental health was assessed using General Health Questionnaire ‘caseness’ in working age adult participants (N = 48 654) of the Health Survey for England (2001–10). Relative indices of inequality by education level were calculated. Substantial inequalities were apparent, with adjustment for employment status and household income markedly reducing their magnitude. Educational inequalities in mental health were attenuated by employment status. Policy responses to economic recession (such as active labour market interventions) might reduce mental health inequalities but longitudinal research is needed to exclude reverse causation

Trends in gender and socioeconomic inequalities in mental health following the Great Recession and subsequent austerity policies: a repeat cross-sectional analysis of the Health Surveys for England

No abstract available

Economic insecurity during the Great Recession and metabolic, inflammatory and liver function biomarkers: analysis of the UK household longitudinal study

Background Economic insecurity correlates with adverse health outcomes, but the biological pathways involved are not well understood. We examine how changes in economic insecurity relate to metabolic, inflammatory and liver function biomarkers. Methods Blood analyte data were taken from 6520 individuals (aged 25–59 years) participating in Understanding Society. Economic insecurity was measured using an indicator of subjective financial strain and by asking participants whether they had missed any bill, council tax, rent or mortgage payments in the past year. We investigated longitudinal changes in economic insecurity (remained secure, increase in economic insecurity, decrease in economic insecurity, remained insecure) and the accumulation of economic insecurity. Linear regression models were calculated for nine (logged) biomarker outcomes related to metabolic, inflammatory, liver and kidney function (as falsification tests), adjusting for potential confounders. Results Compared with those who remained economically stable, people who experienced consistent economic insecurity (using both measures) had worsened levels of high-density lipoprotein (HDL)-cholesterol, triglycerides, C reactive protein (CRP), fibrinogen and glycated haemoglobin. Increased economic insecurity was associated with adverse levels of HDL-cholesterol (0.955, 95%CI 0.929 to 0.982), triglycerides (1.077, 95%CI 1.018 to 1.139) and CRP (1.114, 95%CI 1.012 to 1.227), using the measure of financial strain. Results for the other measure were generally consistent, apart from the higher levels of gamma-glutamyl transferase observed among those experiencing persistent insecurity (1.200, 95%CI 1.110 to 1.297). Conclusion Economic insecurity is associated with adverse metabolic and inflammatory biomarkers (particularly HDL-cholesterol, triglycerides and CRP), heightening risk for a range of health conditions

Sex differences in the association between salivary telomere length and multimorbidity within the US Health & Retirement Study

Background: Telomere length is associated with several physical and mental health conditions, but whether it is a marker of multimorbidity is unclear. We investigated associations between telomere length and multimorbidity by sex. Methods: Data from adults (N = 5,495) aged ≥50 years were taken from the US Health and Retirement Study (2008–14). Telomere length was measured in 2008 from salivary samples. The cross-sectional associations between telomere length and eight chronic health conditions were explored using logistic regression, adjusting for confounders and stratified by sex. Logistic, ordinal and multinomial regression models were calculated to explore relationships between telomere length and multimorbidity (using a binary variable and a sum of the number of health conditions) and the type of multimorbidity (no multimorbidity, physical multimorbidity, or multimorbidity including psychiatric problems). Using multilevel logistic regression, prospective relationships between telomere length and incident multimorbidity were also explored. Results: In cross-sectional analyses, longer telomeres were associated with reduced likelihood of lung disease and psychiatric problems among men, but not women. Longer telomeres were associated with lower risk of multimorbidity that included psychiatric problems among men (OR=0.521, 95% CI: 0.284 to 0.957), but not women (OR=1.188, 95% CI: 0.771 to 1.831). Prospective analyses suggested little association between telomere length and the onset of multimorbidity in men (OR=1.378, 95% CI: 0.931 to 2.038) nor women (OR=1.224, 95% CI: 0.825 to 1.815). Conclusions: Although telomere length does not appear to be a biomarker of overall multimorbidity, further exploration of the relationships is merited particularly for multimorbidity including psychiatric conditions among men

Socioeconomic inequalities in the quality of life of older Europeans in different welfare regimes

Background: Whether socioeconomic inequalities in health and well-being persist into old age and are narrower in more generous welfare states is debated. We investigated the magnitude of socioeconomic inequality in the quality of life of Europeans in early old age and the influence of the welfare regime type on these relationships.<p></p> Methods: Data from individuals aged 50–75 years (n = 16 074) residing in 13 European countries were derived from Waves 2 and 3 of the Survey of Health, Ageing and Retirement in Europe. Slope indices of inequality (SIIs) were calculated for the association between socioeconomic position and CASP-12, a measure of positive quality of life. Multilevel linear regression was used to assess the overall relationship between socioeconomic position and quality of life, using interaction terms to investigate the influence of the type of welfare regime (Southern, Scandinavian, Post-communist or Bismarckian).<p></p> Results: Socioeconomic inequalities in quality of life were narrowest in the Scandinavian and Bismarckian regimes, and were largest by measures of current wealth. Compared with the Scandinavian welfare regime, where narrow inequalities in quality of life by education level were found in both men (SII = 0.02, 95% CI: −1.09 to 1.13) and women (SII = 1.11, 95% CI: 0.05–2.17), the difference in quality of life between the least and most educated was particularly wide in Southern and Post-communist regimes.<p></p> Conclusion: Individuals in more generous welfare regimes experienced higher levels of quality of life, as well as narrower socioeconomic inequalities in quality of life.<p></p&gt

Depression and anxiety among people living with and beyond cancer: a growing clinical and research priority

Background: 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. Conclusion: 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

Inequalities in all-cause and cause-specific mortality across the life course by wealth and income in Sweden: a register-based cohort study

Background: Wealth inequalities are increasing in many countries, but their relationship to health is little studied. We investigated the association between individual wealth and mortality across the adult life course in Sweden. Methods: We studied the Swedish adult population using national registers. The amount of wealth tax paid in 1990 was the main exposure of interest and the cohort was followed up for 18 years. Relative indices of inequality (RII) summarize health inequalities across a population and were calculated for all-cause and cause-specific mortality for six different age groups, stratified by sex, using Poisson regression. Mortality inequalities by wealth were contrasted with those assessed by individual and household income. Attenuation by four other measures of socio-economic position and other covariates was investigated. Results: Large inequalities in mortality by wealth were observed and their association with mortality remained more stable across the adult life course than inequalities by income-based measures. Men experienced greater inequalities across all ages (e.g. the RII for wealth was 2.58 [95% confidence interval (CI) 2.54–2.63) in men aged 55–64 years compared with 2.29 (95% CI 2.24–2.34) for women aged 55–64 years), except among the over 85s. Adjustment for covariates, including four other measures of socio-economic position, led to only modest reductions in the association between wealth and mortality. Conclusions: Wealth is strongly associated with mortality throughout the adult life course, including early adulthood. Income redistribution may be insufficient to narrow health inequalities—addressing the increasingly unequal distribution of wealth in high-income countries should be considered

Depressive symptoms, neuroticism and participation in breast and cervical cancer screening: cross-sectional and prospective evidence from UK Biobank

Objective: To assess the cross‐sectional and prospective associations between depressive symptoms, neuroticism, and participation in breast and cervical screening in the UK. Methods: Women in the UK Biobank cohort with complete data who were eligible for breast cancer screening (aged 50‐70 years, N = 143 461) and/or cervical screening (<65 years, N = 141 753) at baseline recruitment (2006‐2010) and those with follow‐up data (2014‐2019) were identified (N = 11 050 and N = 9780 for breast and cervical screening). Depressive symptoms and neuroticism were self‐reported at baseline (range 0‐12 with higher scores reflecting greater severity). Primary outcomes were reporting being up to date with breast and cervical screening. For prospective analyses, patterns of screening participation from baseline to follow‐up were identified. Logistic regression was used to analyse associations, adjusted for potential confounding factors. Results: More severe depressive symptoms were associated with reduced likelihood of breast (OR = 0.960, 95% CI: 0.950,0.970) and cervical (OR = 0.958, 95% CI: 0.950,0.966) screening participation, in cross‐sectional analyses. Higher neuroticism scores were associated with reduced cervical screening participation, but the opposite was found for breast cancer screening. Examination of individual neuroticism items revealed that anxiety and worry were associated with increased breast screening. At follow‐up, higher baseline depressive symptoms were related to decreased cervical screening (OR = 0.955, 95% CI: 0.913,0.999), but not with breast screening. Conclusions: More severe depressive symptoms may be a barrier for breast and cervical screening and could be an indicator for more proactive strategies to improve uptake