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

Abstract

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 (≤25 th percentile) or less (>25 th 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.

Associations between parental attitudes towards mental illness and self-reported mental health among young people: Evidence from the Health Survey for England

“…This association was consistent across the two scores of prejudice and tolerance, robust to statistical adjustment (including area deprivation and educational attainment), and only meaningfully affected by considering the mother’s own mental health. 39 This association, however, did not extend to young people’s non-specific psychological distress. This suggests that the role of the mother’s attitudes may be stronger for specific conditions that are more liable to under-reporting compared with scores derived from a multi-item scale.…”

Saúde sexual e reprodutiva da mulher com transtorno mental: fatores que moldam a assistência profissional

“…O contexto cultural mostrou-se neste estudo como fator que excede a assistência dos profissionais, tendo sido apontado como influenciador de outras entidades nomeadamente os formuladores de políticas públicas, a família, a sociedade e a própria mulher. Essa mesma concepção foi apontada em um estudo que mostrou que o estigma como determinante sociocultural compartilhado por um coletivo pode ser um fator decisivo que leva às desigualdades e padronização da saúde das pessoas com transtorno mental, restringindo as suas necessidades de foro psiquiátrico (Niedzwiedz, 2019).…”

Validating measures of stigma against those with mental illness among a community sample in Kilifi Kenya

“…In low- and middle-income countries, these tools have been used for general populations (Abi Doumit et al ., 2019 ), community samples (Girma et al ., 2013 ; Reta et al ., 2016 ; Basu et al ., 2017 ; Hartini et al ., 2018 ; Abi Doumit et al ., 2019 ; Niedzwiedz, 2019 ; Tesfaye et al ., 2020 ; Potts and Henderson, 2021 ) and special populations such as health professionals and medical students (Mutiso et al ., 2017 ; Siqueira et al ., 2017 ; Fekih-Romdhane et al ., 2021 ). However, they have also not been validated in most of these settings yet studies that have validated the tools in community samples show that while their original factor structures are retained in some samples (Abelha et al ., 2015 ), they do not hold in others (Brockington et al ., 1993 ; Wolff et al ., 1996 ; Abelha et al ., 2015 ).…”