1. Main facts and figures
- in 2014, there were no meaningful differences between ethnic groups in the percentage of adults who had a positive screening for bipolar disorder
- the small number of positive screenings for certain ethnic groups means any apparent differences are too uncertain to draw reliable conclusions
- these figures should not be used as evidence of real differences between ethnic groups in the population as a whole
The ethnic categories used in this data
For this data, the number of people surveyed (the ‘sample size’) was too small to draw any firm conclusions about detailed ethnic categories. Therefore, the data is broken down into the following broad groups, based on the ONS harmonised ethnic group questions for use on national surveys.
- Asian/Asian British
- Black/Black British
- White British
- Other White
2. By ethnicity and sex
|White - British||2.0||2.3||1.8|
|White - Other||2.0||3.1||1.1|
Respondents to the APMS 2014 were assessed for bipolar disorder based on their answers to the Mood Disorder Questionnaire (MDQ), which asks 13 yes/no questions related to lifetime experience of manic or hypomanic symptoms and is based on the Diagnostic and Statistical Manual of Mental Disorders criteria for bipolar spectrum disorders. Survey respondents screened positive if they said they had ever experienced 7 or more common symptoms of bipolar disorder, as well as several other symptoms that occur at the same time. These symptoms must also have caused moderate or serious problems with normal day-to-day life (for example: being unable to work; having family, money or legal troubles; or getting into arguments or fights).
Each survey involved interviewing a large stratified probability sample of the general population, covering people living in private households. The full adult age range was covered, with the youngest participants aged 16 and the oldest over 100.
The two-phase survey design involved an initial interview with the whole sample, followed up with a structured assessment carried out by clinically trained interviewers with a subset of participants. People were assessed or screened for a range of different types of mental disorder, from common conditions like depression and anxiety disorder through to less common neurological and mental conditions such as psychotic disorder, attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD).
The use of a survey to assess mental health conditions is not as reliable as a diagnosis made using a clinical interview. The assessments used have been validated, however, and are among the best available.
The resulting statistics for positive screen for bipolar disorder have been age-standardised. This is because the prevalence of mental disorders is related to age and the age profile can differ considerably between ethnic groups. This adjustment allows comparisons to be made between ethnic groups as if they had the same age profile.
The survey covers people who live in private households. It doesn’t include those who live in institutional settings (such as hospitals or prisons) or in temporary housing (such as hostels or bed and breakfasts) or those who sleep rough. People living in such settings are likely to have worse mental health than those living in private households (Gill et al. 1996; cited in APMS 2014).
Where a selected participant could not take part in a long interview due to a physical or mental health condition, some information about this was recorded by the interviewer on the doorstep. This information may be biased due to it having been collected, often from another household member.
Socially undesirable or stigmatised feelings and behaviours may be underreported. While this is a risk for any study based on self-report data, the study goes some way to minimising this by collecting particularly sensitive information in a self-completion format.
Some people selected for the survey could not be contacted or refused to take part. The achieved response rate (57%) is in line with that of similar surveys (Barnes et al. 2010; cited in APMS 2014). Weighting helps take account of those who were selected for the survey but didn’t take part.
Weighting is used to adjust the results of a survey to make them representative of the population and improve their accuracy. For example, a survey which contains 25% females and 75% males will not accurately reflect the views of the general population, which we know is around 50% male and 50% female.
More detailed information on the weighting used here can be found in the Methods chapter of the Adult Psychiatric Morbidity Survey 2014 (PDF).
The confidence intervals for each ethnic group are available in the ‘download the data’.
1.8% of White British women surveyed screened positive for bipolar disorder. This is a reliable estimate of the percentage of White British women in England who are likely to screen positive for bipolar disorder. Because the APMS results are based on a random sample of adults aged 16 or older, however, it’s impossible to be 100% certain of the true percentage.
It’s 95% certain, however, that somewhere between 1.3% and 2.5% of all White British women in England would screen positive for bipolar disorder. In statistical terms, this is a 95% confidence interval. This means that if 100 random samples were taken, then 95 times out of 100 the estimate would fall between the lower and upper bounds of the confidence interval. But 5 times out of 100 it would fall outside this range.
The smaller the survey sample, the more uncertain the estimate and the wider the confidence interval. For example, fewer women from the Black/Black British ethnic group were sampled for this survey than White British women, so we can be less certain about the estimate for the smaller group. This greater uncertainty is expressed by the wider confidence interval of between 1.2% and 12.5%.
Suppression rules and disclosure control
There is no risk to disclosure as the analysis is based on broad ethnic groups, without further disaggregation. Therefore no data has been suppressed. Risk to disclosure has been accounted for with limitations of the level of disaggregation, size of category groupings, and the maintaining of large underlying populations for analysis. No further suppression or other disclosure control has been applied.
Percentages have been rounded to one decimal point.
Full references for other sources cited in this commentary can be found in the Adult Psychiatric Morbidity Survey: Survey of Mental Health and Wellbeing, England, 2014.
Further technical information
4. Data sources
Type of data
Type of statistic
Every 7 years (further publications dependent on further surveys being commissioned)
Purpose of data source
The Adult Psychiatric Morbidity Survey provides data on the prevalence of treated and untreated psychiatric disorders in English adults aged 16 and over.
5. Download the data
This file contains the following: ethnicity, year, gender, value, denominator, numerator, confidence intervals