Who is at risk of mental illness?
Mental Illness: A condition which causes serious disorder in a person's behaviour or thinking.
Mental Illness: A condition which causes serious disorder in a person's behaviour or thinking.
Fact 1: About half of the mental disorders begin before the age of 14.
Fact 2: Neuropsychiatric disorders (eg. Eating Disorders, Depression, Bipolar disorder, etc.) are among the leading causes of worldwide disability in young people.
Fact 3: Around 20% of world’s children and adolescents have mental disorders or problems.
Fact 4: About 23% of all years are lost because of disability by mental and substance use disorders, make it the leading cause of disability worldwide.
Fact 5: War and disasters have a large impact on mental health and psychosocial well-being.
In this project, we will mainly look at the prevalence of mental disorders over the world. We will also look at its impact (quantified with Disability-Adjusted Life Year (DALY)) and its correlation with Life Satisfaction, Education and Employment with chosen environment. Our data comes from the Global Burden of Disease (GBD) database. This is a database maintained by The Institute for Health Metrics and Evaluation (IHME), part of the University of Washington, and provide rigurous data about the world population health. Their dataaset provide the various causes of illness, including physical and mental illness, from 1990-2017. All the data of this project have been retrieved from the GBD, which we cleaned and analyzed using techniques learnt from the EPFL ADA course.
Note that the map above does not include substance abuse as a type of mental illness. Furthermore, the legend is narrower on the top because we wanted to highlight and show changes for countries with higher mental illness prevalence.
As can be seen in the map above, the countries’ share of population with mental illness consistently falls between 9% to 17%. The countries that the highest mental illness prevalence include: United States, Australia, Greenland and Iran.
The United States’ darkest period for mental illness fall between 1997 – 2009, which includes the time period when the 9/11 terrorist attack and financial crisis occurred. The 9/11 attack in 2001 resulted in almost 3K deaths and over 6K injuries. It led to a steep decline in the stock market index, followed by public backlash against those that came from specific race/religion groups. Furthermore, the financial crisis starting in 2007 resulted in the loss of 8.7 million jobs in the US alone. Hence, it may be possible to attribute the high mental illness prevalence during these years to the economic and social repercussions of these two events.
Mental disorders related deaths occur throughout the world, affecting individuals of all nations, cultures, religions and genders. We can see from the graph below that the prevalence of mental disorders does not show a direct relationship with the death rates. We also realized that the increase in death number is not only caused by the increase of the population, since the death rate (number of death over 100 000 people) also increases over years. In fact, statistics show that countries with highest mental disorder related death rates in the world are incredibly diverse.
Today, it is widely accepted by major scientific associations that addiction is a "brain disease". The DSM-V lists criteria for classifying addictions as mental health condition is called "Substance Use Disorder." Prior to 2016, the dataset provided by GHDx also included "Substance Use Disorder" as a type of "Mental Disorder".
For all the analysis on deaths caused by mental illness (graph just above), we included alcohol use and drug use disorders to make it more comprehensive. If we take a look at the number of deaths caused by mental disorders, we can see that substance use disorders (drug and alcohol use) contribute to more than 100 k deaths per year. Specifically, Russia, Australia, the United States and Nordic countries appear to have the highest direct deaths rates reported from substance use disorders in 2016. China, India and the United States had the highest direct deaths from anorexia and bulimia nervosa, with more than 60 deaths each in 2016.
Let's take the look at the total number of mental disorder related deaths. Russia had the highest death rate at over 25 deaths per 100,000; this was followed closely by the United States with just over 24 per 100,000. Furthermore. it is worth noting that Russia has a decreasing death rates after peaking at 50 deaths per 100,000 in 2005, whereas the death rates for the United States has been increasing since 1990.
Panama, Mexico and Nicaragua had a relatively low prevalence of mental illness of 12% comparing to other North America countries such as Canada (18%) and the United States (21%) in 2016. It is also reported that the world lowest suicide rates are concentrated in the Caribbean Islands. Perhaps surprisingly, only about 0.3 deaths per 100,000 were reported in Egypt.
These mental disordered related deaths do not include indirect suicide deaths and doctor-assisted suicide, which may significantly underestimate the true mortality impact of such disorders.
A research by World Health Organization (WHO) determined that the two most common mental disorders are anxiety and depression. Let’s see if it is true. Instructions: Hover to see the percentage and the raw number of the population for each mental disorder.
The percentages in the following graph is obtained by: (People having a specific mental disorder)/(Toal number of people having mental disorders.)
Indeed, among all the people having mental disorders, more than 50% are victims of either anxiety or depressive disorders. On a global scale, only very few people have schizophrenia and eating disorders, despite the increasing cases of obesity and the general fashion trend that values skinniness.
Let's take a closer look at the trend per mental disorder in different parts of the world.
Instruction: Double-click on the label (mental disorder) to view one mental disorder only at a time. The trend will be seen clearer.
As we can see, in this graph of population percentage (ill people / total population), in every continent, anxiety and depression are the top mental illnesses. We can also observe that Americas generally have a higher percentage of mentally ill population among all continents, varying from 0.23% to 5.3% over the years, followed by Europe, varying from 0.24% to 4.46%. Interestingly, these are the richest and most developed countries. While researchers cannot give an explanation for this phenomena, we will attempt to provide some guesses later in Life Satisfaction section.
On a general trend, we noticed that the prevalence percentage of anxiety and depressive disorders steadily increases by small rate over years. It seems that the advancement in the technologies intended to make people life better did not necessarily made the population over the world happier. According to a study by Lambert in 2006, this is related to the change in our lifestyle. The effort-based rewards, defined as a base level of physical activity to provide life's basic resources, has diminished over years as our society turned more industrialized, technologically advanced and service-oriented.
We also noticed a steady decrease in related with childhood mental disorders, i.e. conduct disorders, Attention-Deficit/Hyperactivity Disorder (ADHD) and Idiopathic developmental intellectual disability. This might be due to medical advances and a wider social acceptance of these diseases.
Let’s look at the ranking of the continents per mental disorder in the most recent year, 2017.
This graph has the same results as the above, except it is organized by mental disorders. The global value is given as a reference.
Europe and America stand at the top for depression and anxiety, but also for eating disorders, and bipolar disorders. As mentioned above, developed and rich countries are indeed the ones that are most affected by mood based disorders.
Africa has the highest population share for Attention-Deficit/Hyperactivity Disorder (ADHD) and Conduct disorders (not surprising since this is related to ADHD). A study from M. Döpfner et al. (2008) has related higher prevalence of ADHD with families of lower socioeconomic status and families from urban areas, but this doesn’t explain why Americans end in second place in the ranking.
Surprisingly, while there is a general stereotype portraying how Asian (especially Eastern Asian) students are smart at school, Asia ranks first in the Idiopathic developmental intellectual disability and schizophrenia. While the reason is still unknown, from our research, we think that it might be related to the inequalility of the avaibility of the medical resources in the developing countries.
The graph on the left shows that prevalence of mental disorders for different age groups can vary significantly by country.
We can see a peaking of prevalence in older adulthood (between age of 35 to 45) in the United States. Starting from age 40, the prevalence of population with mental disorders in the United States ranks the highest among all 5 countries.
Now taking Australia for example, there is an observable trend towards higher prevalence among young age groups, especially between age of 15 to 30, with prevalence doubled for the same age group in China. However, Australia has a decreasing prevalence rates in older age groups, ranking the lowest among all 5 countries for population above age 60.
Now, if we take a look at prevalence rates in China and Russian, we can observe a huge jump in prevalence of mental illness between children to adolescents. However, the rates grow at a much lower speed at older adulthood.
Prevalence rates also vary quite a lot for different types of mental disorders.
We are susceptible to anxiety disorder at an early age of 1 to 4. The prevalence rates of anxiety disorder increased more than 10 times between the age of 5 to 9 and again for about 2.5 times between age of 10 to 14.
Depressive disorder, however, has a much higher prevalence in older age groups. It outnumbers anxiety disorder from the age of 45 and remains to be the most prevalent mental disorder since then.
Eating disorder is only observed between the age range of 10 to 50, along with bipolar disorder and schizophrenia, making up a small percentage of population who are diagnosed with mental illness.
This graph shows the prevalence of people with mental disorders for each age range worldwide.
Comparing with the first graph in this section, we can see a similar trend where mental disorders are most prevalence in adulthood.
Let’s first look at the change in total mental disorders’ prevalence of female vs male population over the years. To compare between each continents, we decided to take the percentage of the population affected by mental illness per gender: (Male having mental disorder in continent A / Total number of male population in continent A * 100)
We notice that on a global trend, female tend to be more affected by mental disorders. This fact has been confirmed by a study done by Gulland (2016). This is true for America, Europe and Asia, where the share of female population having mental disorders are generally 0.4-2% higher than the share of male population. We can also observe that the rate of people having mental disorders is increasing over the years. Surprisingly, we observe the exact opposite in Africa and in Oceania. The trend is somehow decreasing of the lastest years, and men are more likely affected by mental disorders than women. Unfortunately, we have not found any research that explain this phenomena.
Let’s look at how the impact of each mental disorder on male/female population varies.
We chose one main country per continent, and compared it to a global scale to see if there is a difference. The percentage calculation is following: (Number of male having disorder A in location A) / (Total number of people having disorder A in location A)
Instructions: Hover on each subplot to observe the exact percentage.
In first observation, we realized that women are more affected by mental illness than men. However, after segementing mental disorders into specific types, we realized that women are only affected by a few of these types, while men are targeted by a majority. Indeed, we observe that women tend be more affected by depression, anxiety and eating disorders all over the world, while men tend to be more affected by autism, intellectual disabilities, attention-deficit disorders and conduct disorders. The large difference between gender is specifically significant in eating disorders, autism, conduct disorders and attention-deficit disorders. While no studies confirm our guesses, for autism, conduct disorders and attention-deficit disorders, we suspect that the gender difference might be related to how these diseases get transmitted through genes. The trend in eating disorders is clearly related by how modern societies value skinniness as a female beauty fashion.
The above graph shows the global depression prevalence as a % of the population, based on education and employment. Education is split into 3 categories—below upper secondary, upper secondary and post-secondary, and tertiary education. Employment is split into 2 overlapping categories—active and employed. Active considers all people in the labour force—this includes those who are employed, but also those who are unemployed but looking for work.
From the graph, it is clear that depression prevalence decreases as education level increases. Furthermore, depression prevalence is lower for employed rather than active, for all three levels of education. This negative correlation between depression prevalence and education/employment is intuitive—a person with higher education and is employed will on average experience more personal development, increased perspective of self-worth, and be more economically stable. Financial stability and self-fulfillment are contributing factors to the lower depression prevalence levels.
We decided to perform a hypothesis test to test the difference in depression prevalence between the active and employed groups. Using a two-sided t-test, we arrived at a final p-value of 0.0669035101009. Using a 10% significance level, we rejected our null hypothesis and concluded that there is a significant difference in depression prevalence between active and employed groups. As seen above, unemployed people tend to be more depressed. (Details of the hypothesis formulation and calculations in Show More)
Hypothesis Test - Difference of Means between Employed & Active
Let’s conduct a hypothesis test on the difference in means in depression prevalence between employed and active groups using a two-sided t-test. We first formulate our hypothesis:
H0: Mean of employed group depression = Mean of active group depression
H1: Mean of employed group depression != Mean of active group depression
Below are variables we need to conduct the p-test:
Sample size:
$$N = 81$$
Sample Means and Difference:
$$mean_{employed} = 5.323097530864199$$
$$mean_{active} = 6.143745679012348$$
$$diff = 0.8206481481481491$$
Variances and Standard Deviation:
$$var_{employed} = 7.518851839243827$$
$$var_{active} = 8.508507546512345$$
$$s = \sqrt{{var_{employed} + var_{active}} \over 2} = 2.8308443427497183$$
T-statistics and Degrees of Freedom:
$$t = {{mean_{employed} - mean_{active}} \over s\sqrt{2 \over N}} = -1.8448816686405103$$
$$df = 2N – 2 = 160$$
Final P-Value:
$$p-value = 0.0669035101009$$
Using a 10% level of significance, we reject the null hypothesis and conclude that there is a difference in depression prevalence between active and employed groups.
Life satisfaction data was obtained from the World Happiness Report. The happiness level is self-ranked by participants from each country who ranked the quality of their lives from a scale of 0-10. Top ranked countries had common high values in areas including: income, life expectancy, social support, freedom, trust and generosity.
Prior to plotting this graph, our team hypothesized that mental illness prevalence and life satisfaction would have a negative correlation—the higher the life satisfaction of a country, the lower the rate of mental illness, right?
That is not what the data depicts, however. In fact, the Pearson’s correlation coefficient between mental illness prevalence and life satisfaction is positive at 0.477. We conducted some research online to identify the cause of this positive correlation, and we came across studies that indicated that data on mental illness may be lacking in developing countries, which are often countries with lower life satisfaction. For example, a developed country such as Canada will educate students and parents on mental disorders from an early age, and universities will offer and encourage treatment. On the other hand, a developing country such as India may ignore the severity of mental illness, perhaps having the perspective that it is not a real concern or illness, given the other problems the country is facing such as poverty. Hence it is possible that a person from a country with lower life satisfaction such as India will not even realize that they are affected by mental illness due to lack of education. Or, they may be unwilling to admit their disease due to fear of shame or judgement.
From our project, we can see that mental disorders can occur to everyone in the world, and the rate of occurance is slowly increasing over the years. Mental health disorders are complex and can take many forms. The cure for certain disorders is still unknown, and moreoever, many people do not realize that they are affected by a disorder (this is especially true for depression and anxiety).
All the datas collected by IHME are based on a combination of sources, including medical and national records, epidemiological data, in addition to survey data. To go farther in our analysis and to assure the quality of our data, we will have to collect data from other similar datase and do a comparison. This way, we could be certain that our interpretations are precise and accurate.