This article is Part 2 of a two-part series. You can read Part 1 here.
Definition of Bipolar disorder
Bipolar disorder (also termed bipolar affective disorder) is defined by the WHO’s International Classification of Diseases (ICD-10) as follows:
“This disorder is characterized by repeated (i.e. at least two) episodes in which the patient’s mood and activity levels are significantly disturbed, this disturbance consisting on some occasions of an elevation of mood and increased energy and activity (mania or hypomania), and on others of a lowering of mood and decreased energy and activity (depression). Characteristically, recovery is usually complete between episodes, and the incidence in the two sexes is more nearly equal than in other mood disorders. As patients who suffer only from repeated episodes of mania are comparatively rare, and resemble (in their family history, premorbid personality, age of onset, and long-term prognosis) those who also have at least occasional episodes of depression, such patients are classified as bipolar.”
The charts here present global data on the prevalence and disease burden of bipolar disorder.
Prevalence of bipolar disorder
The prevalence of bipolar disorder across the world varies from 0.3 to 1.2 percent by country. Globally, an estimated 46 million people in the world had bipolar disorder in 2017, with 52 and 48 percent being female and male, respectively.
In almost all countries women are more likely to experience bipolar disorder than men. Prevalence of bipolar disorder by age can be found here.
Eating disorders are defined as psychiatric conditions defined by patterns of disordered eating. This therefore incorporates a spectrum of disordered eating behaviours. The underlying sources presented here present data only for the disorders of anorexia and bulimia nervosa (as defined below). It is however recognised that a large share of eating disorders fall outwith the definition of either anorexia or bulimia nervosa (these are often termed ‘eating disorders not otherwise specified’; EDNOS) — some estimates report at least 60 percent of eating disorders do not meet the standard criteria.3
It is therefore expected that the data presented below significantly underestimates the true prevalence of eating disorders, since it concerns only clinically-diagnosed anorexia and bulimia nervosa.
“Anorexia nervosa is a disorder exemplified by deliberate weight loss, and associated with undernutrition of varying severity.
For a definite diagnosis, the ICD note that all the following are required:
(a) Body weight is maintained at least 15% below that expected (either lost or never achieved), or Quetelet’s body-mass index4 is 17.5 or less. 4 Quetelet’s body-mass index = weight (kg) to be used for age 16 or more – 139 – Prepubertal patients may show failure to make the expected weight gain during the period of growth;
(b) The weight loss is self-induced by avoidance of “fattening foods”. One or more of the following may also be present: self-induced vomiting; self-induced purging; excessive exercise; use of appetite suppressants and/or diuretics;
(c) There is body-image distortion in the form of a specific psychopathology whereby a dread of fatness persists as an intrusive, overvalued idea and the patient imposes a low weight threshold on himself or herself;
(d) A widespread endocrine disorder involving the hypothalamic – pituitary – gonadal axis is manifest in women as amenorrhoea and in men as a loss of sexual interest and potency. (An apparent exception is the persistence of vaginal bleeds in anorexic women who are receiving replacement hormonal therapy, most commonly taken as a contraceptive pill.) There may also be elevated levels of growth hormone, raised levels of cortisol, changes in the peripheral metabolism of the thyroid hormone, and abnormalities of insulin secretion;
(e) If onset is prepubertal, the sequence of pubertal events is delayed or even arrested (growth ceases; in girls the breasts do not develop and there is a primary amenorrhoea; in boys the genitals remain juvenile). With recovery, puberty is often completed normally, but the menarche is late.”
“Bulimia nervosa is an illness defined by repeated behaviours of overeating, preoccupation with control of body weight, and the adoption of extreme measures to mitigate the impacts of overeating.
For a definite diagnosis, the ICD note that all the following are required:
(a) There is a persistent preoccupation with eating, and an irresistible craving for food; the patient succumbs to episodes of overeating in which large amounts of food are consumed in short periods of time.
(b) The patient attempts to counteract the “fattening” effects of food by one or more of the following: self-induced vomiting; purgative abuse, alternating periods of starvation; use of drugs such as appetite suppressants, thyroid preparations or diuretics. When bulimia occurs in diabetic patients they may choose to neglect their insulin treatment.
(c) The psychopathology consists of a morbid dread of fatness and the patient sets herself or himself a sharply defined weight threshold, well below the premorbid weight that constitutes the optimum or healthy weight in the opinion of the physician. There is often, but not always, a history of an earlier episode of anorexia nervosa, the interval between the two disorders ranging from a few months to several years. This earlier episode may have been fully expressed, or may have assumed a minor cryptic form with a moderate loss of weight and/or a transient phase of amenorrhoea.”
Prevalence of eating disorders
The prevalence of eating disorders (anorexia and bulimia nervosa) ranges from 0.1 to 1 percent by country. Globally an estimated 16 million had clinical anorexia and bulimia nervosa in 2017. Bulimia was more common: around 79 percent had bulimia nervosa.
In every country women are more likely to experience an eating disorder than men. Eating disorders tend to be more common in young adults aged between 15 and 34 years old. Trends in prevalence by age can be found here.
Deaths from eating disorders
Direct deaths can result from eating disorders through malnutrition and related health complications. The chart shows the estimated number of direct deaths from anorexia and bulimia nervosa. Evidence suggests that having an eating disorder can increase the relative risk of suicide; suicide deaths in this case are not included here.
Trends in death rates from eating disorders can be found here.
Schizophrenia is defined by the IHME based on the definition within the WHO’s International Classification of Diseases (ICD-10) as:
“The normal requirement for a diagnosis of schizophrenia is that a minimum of one very clear symptom (and usually two or more if less clear-cut) belonging to any one of the groups listed as (a) to (d) below, or symptoms from at least two of the groups referred to as (e) to (h), should have been clearly present for most of the time during a period of 1 month or more:
- (a) thought echo, thought insertion or withdrawal, and thought broadcasting;
- (b) delusions of control, influence, or passivity, clearly referred to body or limb movements or specific thoughts, actions, or sensations; delusional perception;
- (c) hallucinatory voices giving a running commentary on the patient’s behaviour, or discussing the patient among themselves, or other types of hallucinatory voices coming from some part of the body;
- (d) persistent delusions of other kinds that are culturally inappropriate and completely impossible, such as religious or political identity, or superhuman powers and – 79 – abilities (e.g. being able to control the weather, or being in communication with aliens from another world);
- (e) persistent hallucinations in any modality, when accompanied either by fleeting or half-formed delusions without clear affective content, or by persistent over-valued ideas, or when occurring every day for weeks or months on end;
- (f) breaks or interpolations in the train of thought, resulting in incoherence or irrelevant speech, or neologisms;
- (g) catatonic behaviour, such as excitement, posturing, or waxy flexibility, negativism, mutism, and stupor;
- (h) “negative” symptoms such as marked apathy, paucity of speech, and blunting or incongruity of emotional responses, usually resulting in social withdrawal and lowering of social performance; it must be clear that these are not due to depression or to neuroleptic medication;
- (i) a significant and consistent change in the overall quality of some aspects of personal behaviour, manifest as loss of interest, aimlessness, idleness, a self-absorbed attitude, and social withdrawal.”
The following charts present global-level data on the prevalence of schizophrenia.
Prevalence of schizophrenia
The prevalence of schizophrenia typically ranges from 0.2 to 0.4 percent across countries. It’s estimated that 20 million people in world had schizophrenia in 2017; the number of men and women with schizophrenia was approximately the same (around 10 million each).
Overall the prevalence of schizophrenia is slightly higher in men than women. Prevalence by age can be found here.
DALYs from schizophrenia
Risk factors for mental health
The determinants, onset and severity of mental health disorders are complex – they can rarely be attributed to a single factor. Identifying potential risk factors form an important element of health research, potential prevention and in some cases, appropriate treatment; nonetheless, many risk factors remain only correlates of observed patterns in mental health. They therefore need to be interpreted carefully.
The World Health Organization synthesize the potential contributors to mental health and wellbeing into three categories:4
- individual attributes and behaviours: these can be particular genetic factors or personality traits;
- social and economic circumstances;
- environmental factors.
In the table we see the WHO’s breakdown of potential adverse and protective factors for mental health within these three categories. These factors often interact, compound or negate one another and should therefore not be considered as individual traits or exposures. For example, particular individual traits may make a given person more vulnerable to mental health disorders with the onset of a particular economic or social scenario — the instance of one does not necessarily result in a mental health disorder, but combined there is a significantly higher vulnerability.
|Level||Adverse Factors||Protective Factors|
|Individual attributes||Low self-esteem||Self-esteem, confidence|
|Cognitive/emotional immaturity||Ability to solve problems & manage stress or adversity|
|Difficulties in communicating||Communication skills|
|Medical illness, substance use||Physical health, fitness|
|Social circumstances||Loneliness, bereavement||Social support of family & friends|
|Neglect, family conflict||Good parenting/family interaction|
|Exposure to violence/abuse||Physical security & safety|
|Low income & poverty||Economic security|
|Difficulties or failure at school||Scholastic achievement|
|Work stress, unemployment||Satisfaction & success at work|
|Environmental factors||Poor access to basic services||Equality of access to basic services|
|Injustice & discrimination||Social justice, tolerance, integration|
|Social & gender inequalities||Social & gender equality|
|Exposure to war or disaster||Physical security & safety|
Risk factors through the life-course
The risk factors and influencers on mental health vary significantly for an individual as they move through the life-course. The following are acknowledged risk factors for a given stage of life.5
– Pre-conception and pre-natal period
A given individual’s mental health and wellbeing can be influenced by factors present prior to conception or birth. Pregnancies which are unwanted or in adolescence can increase the likelihood of detrimental behaviours of the mother during pregnancy, and the environmental or family conditions of childhood.6
During pregnancy, detrimental behaviours including tobacco, alcohol and drug use can increase the likelihood of later mental health disorders for children; malnutrition, low-birth weight and micronutrient deficiency (for example, iodine deficiency) can also influence later mental health vulnerabilities.7
– Infancy and early childhood
There is a large base of evidence which shows that emotional attachment in early childhood has a considerable impact on later vulnerability to mental health and wellbeing.8 As a result, particular risk factors include separation from the primary caregiver, in some cases post-natal depression in mothers (which can result in sub-optimal attachment), and parents for whom communication and social interaction is challenging. Child maltreatment and neglect has been found to have a significant impact on vulnerabilities to mental wellbeing.9 Malnutrition, poor access to basic services and disease and parasites are also important contributors.
Childhood conditions form a critical component of health and wellbeing later in life. Negative experiences, either at home or outside of the home (for example, bullying in school) can have lifelong impacts on the development of core cognitive and emotional skills. Poor socioeconomic conditions also have a significant effect on vulnerability to mental health disorders; in a study in Sweden, the authors found that children raised in families of poor socioeconomic backgrounds had an increased risk of psychosis.10
Poor economic resources, shown through poor housing conditions for example, can be seen by children as shameful or degrading and affect aspects of childhood learning, communication and interaction with peers.
Children with a parent who has a mental illness or substance use disorder have a higher risk of psychiatric problems themselves.11 This effect between generations can occur as a result of genetic, biological, psychological and social risk factors.
Adolescence is typically the stage of life where mental health disorders tend to become more apparent. The risk factors and contributors to wellbeing in childhood apply equally to those in adolescence. In addition, several other contributing factors appear. It is in the years of adolescence that the use of substances including alcohol and drugs first appear.
Substance use is particularly hazardous and harmful for adolescents because individuals are still developing both mentally and physically. Peer pressure, and media influences also become more prominent over these years. Exposure to substance use is not only an important risk factor for other mental health disorders, but also linked to poorer educational outcomes, more risky sexual behaviour and increased exposure to violence and conflict.
Experiences and emotional capabilities developed through childhood and adolescence are important factors in the effect that particular events and scenarios in adulthood have on mental health outcomes.
The WHO highlight that critical to wellbeing in adulthood is the allocation and balance between work and leisure time. Exposure to high stress and anxiety is strongly influenced by the share of time working, caring for others, or time spent in an insecure economic environment. Individuals with poor socioeconomic security, and in particular unemployment, are also at higher risk to mental health disorders.
These factors, balanced with the amount of time spent on ‘consumption’ activities, including leisure time and supportive family and friends, often determine the propensity for poor mental health and wellbeing. Community structures can have a significant positive impact on these outcomes — individuals who have poor access to such communities, either through social exclusion, neighbourhood violence/crime, or lack of respite care have a higher risk of mental health disorders.
Physical health also has an important impact on mental wellbeing; an individual’s ‘physical capital’ can influence their sense of esteem and social inclusion. Individuals with chronic illness or disability are at higher risk of poor mental health; this is particularly true for conditions with high rates of stigmatisation, such as HIV/AIDS.
– Older age
Individuals of older age are of notably high risk of poorer mental health and wellbeing. This typically results from notable changes in life conditions (such as a cease in employment which affects both the feeling of contribution and economic freedom), higher social exclusion, and loneliness. This is particularly true when an older individual begins to lose close family and friends. Bereavement in general is an important predictor of mental health disorders such as depression.
A decline in physical health can have major impacts on life capabilities by affecting an individual’s mobility and freedom. Older individuals are also at higher risk of abuse or neglect from carers and in some cases, family members.
Link between mental health and suicide
The link between mental health and substance use disorders and suicide is well-documented.12 It is however true that not all suicides – or suicide attempts – are attributed to underlying mental health or substance use disorders; as shown in the chart, there is not a direct relationship between mental health prevalence and suicide rates.13
We cover suicide statistics more broadly in our full entry on Suicide, however here we attempt to distil the key findings on the links between mental health and substance use and suicide. Although mental health and substance use disorders is within the top-five causes of disease burden globally (as measured by Disability-Adjusted Life Years; DALYs), accounting for approximately 7 percent of the burden, several authors have highlighted that such figures — since they do not include suicide DALYs — underestimate the true cost of mental health disorders.14
Providing a more accurate estimate of total mental health burden therefore requires some understanding of the connection between these disorders and suicide.
Meta-analyses of psychological autopsy studies of suicide across high-income countries suggest that up to 90 percent of suicides occur as a result of an underlying mental health or substance use disorder.15
While available data and studies are more scarce across lower-to-middle income countries, evidence across countries including China, Taiwan and India suggest that this proportion is significantly lower elsewhere.16
These studies suggest a large number of suicides resultant from the ‘dysphoric affect’ and ‘impulsivity’ (which are not defined as a mental and substance use disorder). In such cases, understanding the nature of self-harm methods between countries is important; in these countries a high percentage of self-harming behaviours are carried out through more lethal methods such as poisoning (often through pesticides) and self-immolation. This means that in a high number of cases self-harming behaviours can prove fatal, even if there was not a clear intent to die.
A study by Ferrari et al. (2015) attempted to determine the share disease burden from suicide which could be attributed to mental health or substance use disorders.17
Based on review across a number of meta-analysis studies the authors estimated that 68 percent of suicides across China, Taiwan and India were attributed to mental health and substance use disorders; across other countries this share was approximately 85 percent. In their estimates of total attributable disease burden, the authors concluded that mental health and substance use disorders were responsible for 62 percent of total DALYs from suicide.
Mental health as a risk factor for suicide
Although the total prevalence of mental health and substance use disorders does not show a direct relationship to suicide rates (as shown in the chart above), there are notable links between specific types of mental health disorders and suicide. In their meta-study of the mental health-suicide relationship, Ferrari et al. (2015) assess the pooled relative risk of suicide across a range of mental health and substance use disorders.18 This represents the increased risk of suicide for those with a particular mental health or substance use disorder.
The figures in the table represent estimates of the increased risk of suicide for an individual with one of the following disorders. An individual with depression, for example, is 20 times more likely to die from suicide than someone without; some with anxiety disorder around 3 times; schizophrenia around 13 times; bipolar disorder 6 times; and anorexia 8 times as likely.
|Disorder||Pooled relative risk (95% UI)|
|Major depressive disorder||19.9 (9.5-41.7)|
|Anxiety disorder||2.7 (1.7-4.3)|
|Bipolar disorder||5.7 (2.6-12.4)|
|Anorexia nervosa||7.6 (2.2-25.6)|
|Alcohol dependence||9.8 (9.0-10.7)|
|Opioid dependence||6.9 (4.5-10.5)|
|Psychostimultant dependence||8.2 (3.9-16.9)|
Depression by education level & employment status
The statistics presented in the entry above focus on aggregate estimates of prevalence across total populations. In the chart we present data on depression prevalence across a number of OECD countries, disaggregated by education level and employment status.19 This data is based on self-reported prevalence of depression as requested by surveys. There are multiple reasons why this data may differ from IHME statistics presented above: it is based only on adults aged 25-64 years old, and focuses on self-reported depression only. The lack of differentiation in these surveys between mental health disorders, such as depression, anxiety disorders, and bipolar disorder mean that self-reported depression data may include individuals with these other disorders.
Categories in the chart have been coloured based on education level, with further categorisation based on whether groups are employed, actively seeking employment, and the total of employed, active and unemployed. Across most countries (which you can explore using the “change country” option in the chart) we tend to see the lowest prevalence in depression amongst those with tertiary (postsecondary) education; and highest prevalence in those who did not reach upper secondary education.
It is also notable that the large differences in education level close or disappear when we look only at the sub-group of those employed. Overall, the prevalence of depression appears to be lower in individuals in employment relative to those actively seeking employment, or the total population which also includes the unemployed.
Life satisfaction and mental health
Is the prevalence of mental health disorders reflected in self-reported life satisfaction or happiness? Overall, evidence suggests that there is a negative correlation between prevalence of particular mental health disorders (depression and anxiety have been the most widely assessed) and self-reported life satisfaction. This suggests that life satisfaction and happiness tends to be lower in individuals experiencing particular mental health disorders.
We discuss the link and evidence for this relationship in our entry on Happiness and Life Satisfaction.
Mental health as a risk factor for substance abuse
Mental health is known to be an important risk factor for the development of substance use disorders (either in the form of alcohol or illicit drug dependencies). The increased risk of a substance use disorder varies by mental health disorder type:
- for alcohol dependency the risk is highest in individuals with intermittent explosive disorder, dysthymia, ODD, bipolar disorder and social phobia. This is discussed in our entry on Alcohol Consumption.
- for illicit drug dependency the risk is highest for individuals with intermittent explosive disorder, ADHD, and bipolar disorder. This is discussed in our entry on Substance Use.
Do antidepressants work?
There are a number of options for mental health treatment and recovery — choice of treatment and its effectiveness will be specific to a number of factors including the mental health disorder, its severity, previous treatment and the individual. There is not a single ‘best approach’ to treatment.
One option for treatment of depression is the prescription of antidepressant drugs. But are antidepressant drugs effective in reducing the severity of depression? In the chart we present the results of the latest and largest meta-analysis on antidepressant drug efficacy to date, as published by Cipriani et al. (2018) in The Lancet.20
This meta-analysis assessed the effectiveness of 21 antidepressant drugs relative to a placebo across 522 trials comprising 116,477 participants. Effectiveness, given as the response rate, was measured by the total number of patients who had a reduction of ?50% of the total score on a standardised observer-rating scale for depression. The odds-ratio measures the likelihood of a positive response from the antidepressant relative to the placebo (where a value of 2.0 indicates the antidepressant was twice as likely as the placebo).
As shown, all 21 antidepressant drugs were more effective than the placebo in reducing the severity of depression in adults. They did, however, vary in effectiveness. However, this meta-analysis also reported variance in levels of ‘acceptability’, which measures the the proportion of patients who withdrew for any reason (such as side-effects from the antidepressant drug). The use and choice of antidepressants will therefore be specific to the individual dependent on a range of factors and their response to treatment.
Data availability on mental health
The majority of data presented in this entry is based on estimates from the IHME’s Global Burden of Disease (GBD). This is currently one of the only sources which produces global level estimates across most countries on the prevalence and disease burden of mental health and substance use disorders.
Nonetheless, the GBD acknowledges the clear data gaps which exist on mental health prevalence across the world. Despite being the 5th largest disease burden at a global level (and with within the top three across many countries), detailed data is often lacking. This is particularly true of lower-income countries. The Global Burden of Disease note that the range of epidemiological studies they draw upon for global and national estimates are unequally distributed across disorders, age groups, countries and epidemiological parameters.21 Using these studies to provide full coverage of these disorders is challenging.
To overcome these methodological challenges the authors note:
To deal with this issue and be able to include data derived using various study methodologies and designs, GBD 2013 makes use of DisMod-MR, version 2.0, a Bayesian meta-regression tool. The software makes it possible to pool all of the epidemiological data available for a given disorder into a weighted average, while simultaneously adjusting for known sources of variability in estimates reported across studies. If raw data are not available for a given country, the software produces an imputed estimate for each epidemiological parameter based on data available from surrounding countries. This allowed GBD to include estimates for 188 countries.
Comparison of IHME estimates to other sources
In this entry we have focused on data trends published by the Institute of Health Metrics (IHME) Global Burden of Disease study. This is currently the only source which provides estimates for all countries over time, and across the full range of mental health and substance use disorders. The World Health Organization (WHO) publish estimates on depression only; the comparison of depression prevalence from IHME versus WHO is shown in the scatter plot.
A range of national sources also publish estimated prevalence of depression. In many cases, the ‘boundaries’, or category differentiation in mental health disorders is different from IHME estimates. They are often therefore not directly comparable. For example, the Center for Diseases Control (CDC) in the United States provides information and estimates on combined depression and anxiety disorders, treating anxiety as a subset of depression.
Hannah Ritchie and Max Roser (2018) – “Mental Health”. Published online at OurWorldInData.org.
This is part 2 of a two-part article. Read part 1 here
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