Associations between sociodemographic characteristics and receipt of professional diagnosis in Common Mental Disorder: Results from the Adult Psychiatric Morbidity Survey 2014.

BACKGROUND: Many people with Common Mental Disorders (CMDs), especially men, people from older age groups, and ethnic minority backgrounds, receive no treatment. Self-acknowledgement of mental illness symptoms, and a professional diagnosis are usually required to access treatment. To understand barriers, we therefore tested whether these groups were relatively less likely to self-diagnose a CMD, or to receive a professional diagnosis. METHODS: We analysed data from the 2014 English Adult Psychiatric Morbidity Survey (APMS). We used regression models to examine whether gender, age, and minority ethnic status were associated with professional and self-diagnosis, after controlling for CMD symptoms. RESULTS: 27.3 % of the population reported a professional and self-diagnosis of CMD, 15.9 % a self- diagnosis only, and the remainder no diagnosis. Odds of professional diagnosis were lower for men compared with women (adjusted odds ratio [AOR] 0.54, 95 % confidence intervals [CI] 0.47-0.62). People from White Other (0.49, 0.36-0.67), Black (0.31, 0.18-0.51), and Asian (0.22, 0.15-0.33) groups were less likely than the White British group to receive a professional diagnosis. The least likely age group to have a professional CMD diagnosis (relative to adults aged 16-34) were people aged over 75 (0.52, 0.39-0.69). Patterns were similar for self-diagnosis. LIMITATIONS: Ethnicity categories were heterogeneous. Data are cross-sectional, and selection and response bias are possible. CONCLUSIONS: For every three people who self-diagnose CMD, two have a professional diagnosis. Men, ethnic minority, and older age groups are less likely to receive a diagnosis or self-diagnose after adjustment for presence of symptoms.

A comparison of single and intersectional social identities associated with discrimination and mental health service use: data from the 2014 Adult Psychiatric Morbidity Survey in England.

Inequities in mental health service use (MHSU) and treatment are influenced by social stratification processes linked to socially contextualised interactions between individuals, organisations and institutions. These complex relations underpin observed inequities and their experience by people at the intersections of social statuses. Discrimination is one important mechanism influencing such differences. We compared inequities in MHSU/treatment through single and intersectional status analyses, accounting for need. We assessed whether past-year discrimination differentially influences MHSU/treatment across single and intersecting statuses. Data came from a population survey (collected 2014-2015) nationally representative of English households (N = 7546). We used a theory and datadriven approach (latent class analysis) which identified five intersectional groups in the population comprising common combinations of social statuses. Single status analyses identified characteristics associated with MHSU/treatment (being a sexual minority (adjusted odds ratio (AOR) 1.65 95% CI:1.09-2.50), female (AOR 1.71, 95% CI:1.45-2.02), economically inactive (AOR 2.02, 95% CI:1.05-3.90), in the most deprived quintile (AOR 1.33, 95% CI:1.02-1.74), and Black (AOR 0.36 95% CI:0.20-0.66)). Intersectional analyses detected patterns not apparent from single status analyses. Compared to the most privileged group ("White British, highly educated, employed, high social class"), "Retired White British" had greater odds of MHSU/treatment (AOR 1.88, 95% CI:1.53-2.32) while "Employed migrants" had lower odds (AOR 0.39, 95% CI:0.27-0.55). Past-year discrimination was associated with certain disadvantaged social statuses and greater MHSU/treatment but-except for sexual minorities-adjusting for discrimination had little influence using either analytic approach. Observing patterns only by single social statuses masks potentially unanticipated and contextually varying inequities. The latent class approach offers policy-relevant insights into patterns and mechanisms of inequity but may mask other key intersectional patterns by statuses less common or under represented in surveys (e.g. UK-born ethnic minority groups). We propose multiple, context-relevant, theory-driven approaches to intersectional understanding of mental health inequalities.

Prevalence of common mental disorders and treatment receipt for people from ethnic minority backgrounds in England: repeated cross-sectional surveys of the general population in 2007 and 2014.

BACKGROUND: Concerns persist that some ethnic minority groups experience longstanding mental health inequalities in England. It is unclear if these have changed over time. AIMS: To assess the prevalence of common mental disorders (CMDs) and treatment receipt by ethnicity, and changes over time, using data from the nationally representative probability sample in the Adult Psychiatric Morbidity Surveys. METHOD: We used survey data from 2007 (n = 7187) and 2014 (n = 7413). A Clinical Interview Schedule - Revised score of ≥12 indicated presence of a CMD. Treatment receipt included current antidepressant use; any counselling or therapy; seeing a general practitioner about mental health; or seeing a community psychiatrist, psychologist or psychiatric nurse, in the past 12 months. Multivariable logistic regression assessed CMD prevalence and treatment receipt by ethnicity. RESULTS: CMD prevalence was highest in the Black group; ethnic variation was explained by demographic and socioeconomic factors. After adjustment for these factors and CMDs, odds ratios for treatment receipt were lower for the Asian (0.62, 95% CI 0.39-1.00) and White Other (0.58, 95% CI 0.38-0.87) groups in 2014, compared with the White British group; for the Black group, this inequality appeared to be widening over time (2007 treatment receipt odds ratio 0.68, 95% CI 0.38-1.23; 2014 treatment receipt odds ratio 0.23, 95% CI 0.13-0.40; survey year interaction P < 0.0001). CONCLUSIONS: Treatment receipt was lower for all ethnic minority groups compared with the White British group, and lowest among Black people, for whom inequalities appear to be widening over time. Addressing socioeconomic inequality could reduce ethnic inequalities in mental health problems, but this does not explain pronounced treatment inequalities.

Explaining ethnic variations in adolescent mental health: a secondary analysis of the Millennium Cohort Study.

PURPOSE: The relationship between ethnicity and adolescent mental health was investigated using cross-sectional data from the nationally representative UK Millennium Cohort Study. METHODS: Parental Strengths and Difficulties Questionnaire reports identified mental health problems in 10,357 young people aged 14 (n = 2042 from ethnic minority backgrounds: Mixed n = 492, Indian n = 275, Pakistani n = 496, Bangladeshi n = 221, Black Caribbean n = 102, Black African n = 187, Other Ethnic Group n = 269). Univariable logistic regression models investigated associations between each factor and outcome; a bivariable model investigated whether household income explained differences by ethnicity, and a multivariable model additionally adjusted for factors of social support (self-assessed support, parental relationship), participation (socialising, organised activities, religious attendance), and adversity (bullying, victimisation, substance use). Results were stratified by sex as evidence of a sex/ethnicity interaction was found (P = 0.0002). RESULTS: There were lower unadjusted odds for mental health problems in boys from Black African (OR 0.15, 95% CI 0.04-0.61) and Indian backgrounds (OR 0.42, 95% CI 0.21-0.86) compared to White peers. After adjustment for income, odds were lower in boys from Black African (OR 0.10, 95% CI 0.02-0.38), Indian (OR 0.40, 95% CI 0.21-0.77), and Pakistani (OR 0.49, 95% CI 0.27-0.89) backgrounds, and girls from Bangladeshi (OR 0.18, 95% CI 0.05-0.65) and Pakistani (OR 0.63, 95% CI 0.41-0.99) backgrounds. After further adjustment for social support, participation, and adversity factors, only boys from a Black African background had lower odds (OR 0.16, 95% CI 0.03-0.71) of mental health problems. CONCLUSIONS: Household income confounded lower prevalence of mental health problems in some young people from Pakistani and Bangladeshi backgrounds; findings suggest ethnic differences are partly but not fully accounted for by income, social support, participation, and adversity. Addressing income inequalities and socially focused interventions may protect against mental health problems irrespective of ethnicity.