Corresponding author: Leonid M. Grigoryev ( lgrigor1@yandex.ru ) © 2019 Non-profit partnership “Voprosy Ekonomiki”.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits to copy and distribute the article for non-commercial purposes, provided that the article is not altered or modified and the original author and source are credited.
Citation:
Grigoryev LM, Popovets L (2019) Sociology of individual tragedies. Homicides and suicides: Cross-country cluster analysis. Russian Journal of Economics 5(3): 251-276. https://doi.org/10.32609/j.ruje.5.47348
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Sociology and psychology closely study the phenomena of homicide and suicide among countries of the world, but both remain little studied in the context of the levels of countries’ development and international comparisons. Developed countries (in terms of GDP per capita) show a decrease in the relative rate of homicides, but the case of suicides is not so explicit. This paper examines the relative levels of suicides and homicides all around the world in the context of socio-economic indices as well as indicators of mental health among the population. Addressing the example of the BRICS countries, the authors discuss the impact of economic imbalances on homicide and suicide levels. The analysis demonstrates that social inequality determines cross-country differences for relative levels in terms of homicide rates, including the course of events in the post-Soviet countries. And in the case of Russia, it is possible to make a conclusion not only about the presence of deep inter-regional differences, but also about a large-scale reduction in the frequency of two tragic phenomena between 2000 and 2017 during the economic recovery.
homicides, suicides, sociology, inequality, Russia, transformation, BRICS
Human progress is never on a continuous upward trajectory, and, even in many economically and socially stable countries, people experience psychological stresses and various personal and social problems. Throughout history, wars, epidemics, and crime — both on an individual and mass scale — all of them resulted in losses of human lives. We are not writing the history of crime, but we believe it’s important to understand that lethal interpersonal violence, as well as suicides, cause a massive annual loss of life without any particular military or social upheaval. The nature of homicide and suicide derives from individual behavior in countries with different cultural codes (
The transition to sustainable development in any country requires solutions to problems which societies are facing at different developmental stages. These stages, apparently, require individual approaches to those problems. Most countries signed the UN Sustainable Development Goals (SDG) Agreement, which describes mankind’s big-picture problems and the tasks aimed at solving them. However, the SDG fails to focus on the acute tragic phenomena of homicides and suicides as social problems. Societal tensions heavily impact individuals, and homicides and suicides represent an extreme degree of that tension. They are quite conspicuous in the life of a society, are displayed by the mass media and mentioned in fictional literature and cinema. However, they remain outside the focus of social studies, and are seen more as an inevitable evil of mental health than as a social problem for a given historical period. We take them as indicators of a society’s lack of well-being along with crime as a whole, or as a result of desperation in the context of perceived personal failures.
Contemporary science is looking for correlations between socially induced life events and how a society’s characteristics (culture, political system, etc.) determine people’s status. However, in our opinion, cultural codes are mostly connected to social characteristics that are determined by the historic process. Social disorders are one of the tragic but persistent characteristics of a given country’s social life. By this we mean individuals committing violence against themselves or other people, namely homicide and suicide.
We believe that improved social analysis of the condition and development of countries by using the indicators of the relative level (per 100,000 people) of the mentioned events could provide an opportunity to measure a society’s developmental level and “stability.” The UN’s 2015 Sustainable Development Goals (Goal 3.4) state the need to reduce infectious diseases and improve mental health, using the suicide rate as one of the indicators. In our opinion, this is not enough. The UN SDGs say nothing about reducing the rates of homicide and suicide as hazardous social phenomena, whereas they should have proposed at least reducing them along with the goals for reducing extreme poverty, disease, and overall mortality (
We intend to demonstrate that these two tragic phenomena in the life of a society not only have their own particular psychological explanations, but are also to some extent dependent on socioeconomic processes. We believe that the rate at which life is lost can be studied within the framework of the existing, long-standing tradition. However, we will review several social hypotheses regarding the values of these indicators across 157 countries with populations exceeding 2 million each in 2016. Our focus will be on:
In other words, our aim is as follows: to identify the basic (stylized) facts about the factors which affect homicide and suicide rates in a society, reflecting elements of anomie in some societies. The term “anomie” is used in this paper in the context given by Emile Durkheim: a state of disintegration and mismatch between the values and goals of social classes (
An important research of the 1990s (
Suicide — both as a psychological and social phenomenon, in particular correlating with homicide — has been studied mostly by American and Western European (Norway, Sweden) scientists. These studies contain a certain (mostly on the mental side) research framework paradigm and a sample of statistical data.
Economic factors were becoming a part of the discourse from time to time. For example, the pioneer researchers in this field,
In 1986 David Lester from Stockton University carried out a research of suicide and homicide rates and living standards, based on Henry and Short’s theory. In that study,
In a body of studies on the correlation between suicide rates and socioeconomic factors, Bijou Yang’s is one of the most comprehensive. In his The Economy and suicide: A time-series study of the United States,
Moving from social disorder indicators to the intuitively opposite one, i.e. the level of happiness, we should mention the theory of Richard Easterlin, who studied the level of social inequality as connected to per capita income.
Statistical analysis of homicide and suicide indicators is a relatively recent course of research (see review in
We should also mention the review by David
We intend to analyze the current situation; that is why we use 2016 data for 157 countries, ascribed to seven clusters. They can be viewed as information on social stratification (keeping all possible limitations in mind): first, as the cluster structure based on each country’s level of development and second as social (decile) structure within individual countries. We rely on the cluster approach to international inequality, as elaborated upon in a number of works (see
We assigned countries in which Islam is the state religion in a separate group (21 countries), as it has a substantial effect on socioeconomic and cultural conditions. In particular, laws of religion, such as the ban on alcohol, are controlled at the state level. The specifics of cultural codes for Muslim countries and their sociopolitical institutions enable us to examine them separately within the framework of our topic.
We selected the following indicators for statistical analysis: mental disorder rate; depression rate; alcohol/drug addiction rate; unemployment rate; GDP (PPP) per capita; calculated “happiness” index; homicide and suicide rates.
The rate of homicide, or mortality caused by interpersonal violence, reflects not only the nature of social connections, but also law enforcement control conditions within the country. We consider this rate to be high in societies undergoing socioeconomic transformation, during which the state’s ability to regulate social relations is reduced (case of anomie). However, these states are not necessarily the poorest. The hypothesis regarding suicide rates is that their high rates may be associated with economic development and reflect personal problems within a social context (bankruptcies, career failure).
We also used the “happiness” indicator (see
Table
Average indices across the 7 clusters, 2016 (157 countries, simple means, rounded).
Cluster No. | Cluster borders, USD thousand per capita | Homicides per 100,000 people | Suicides per 100,000 people | GDP (PPP) per capita, USD thousand | Inequality, income share of 10th decile | Unemployment, % | “Happiness” index | Alcohol/substance use disorders, % | Depression, % | Anxiety disorders, % |
1 | > 35.1 | 1.25 | 14.03 | 53.7 | 24.79 | 6.11 | 7.04 | 2.99 | 4.24 | 5.60 |
2 | 21.1–35.0 | 5.19 | 14.84 | 30.8 | 27.42 | 8.21 | 6.00 | 2.83 | 3.76 | 4.16 |
3 | 14.0–21.0 | 5.77 | 11.88 | 19.5 | n/a | 7.47 | 5.70 | 2.64 | 3.69 | 3.92 |
4 | 7.0–13.9 | 13.39 | 9.02 | 12.4 | 29.28 | 10.78 | 5.29 | 2.56 | 3.30 | 3.59 |
5 | 3.2–6.9 | 5.95 | 7.88 | 5.5 | 31.04 | 4.98 | 4.90 | 2.07 | 3.67 | 3.39 |
6 | 1.8–3.1 | 7.89 | 7.19 | 3.0 | 32.26 | 7.31 | 4.26 | 1.91 | 3.93 | 3.30 |
7 | < 1.8 | 6.21 | 7.40 | 1.5 | 33.24 | 6.40 | 4.02 | 1.91 | 4.25 | 3.37 |
In order to assure that the indicators are stable over time, and to rule out the possibility of a random distribution of their values, we calculated the correlation coefficient between homicide rates in 2000 and in 2016, and for suicide rates in the same years. The correlation between homicide rates in 2000 and 2016 across the 157 countries is 0.93; the same calculation for suicide rates is 0.90. It reveals that the change in homicide and suicide rates for both years is also relatively low. As shown in section 6 below, most of these changes are specific to transitional economies. Thus, we consider that conclusions made regarding the main subject of this research should stay correct for the most years or for any of them. Another notable point is that in the “richest” part of the sample (the 1st cluster of countries), homicide and suicide rates were at nearly the same level in 2000 and in 2016. At the same time, in the 2nd cluster countries (which include many transitional economies) there has been a noticeable reduction in both homicide and suicide rates during the 21st century (details below). In clusters 3 through 7, there have been no major changes except for a slight reduction in “normal” suicide rates for a few countries.
But at the same time, the suicide rate in some countries of the state Islam countries group was higher in 2016 than in 2000, although the overall rate declined. We will study these countries later on in more detail. Therefore, Fig. 1 shows data on homicide and suicide rates across 136 countries in 2016 (i.e. excluding countries with the state religion — Islam), sorted out in ascending order by GDP (PPP) per capita.
Suicide and homicide rates per 100,000 citizens, 136 countries, 2016.
Note: Countries are presented on two scales for the convenience of readers. Sources: World Bank; World Health Organization; Institute for Health Metrics and Evaluation.
Homicide and suicide rates across all countries demonstrate remarkable dynamic. The most significant facts are simple, as shown in Table
To build regression models, we took anxiety disorders’ rate, depression rate, alcohol/substance use disorders rate, GDP (PPP) per capita growth rate, unemployment rate, and inequality level in percent and GDP (PPP) per capita (international dollars). All indicators are those of 2016. To test our hypotheses, we analyzed suicide and homicide rates separately based on data from 157 countries for 2016.
Equations for: homicides, suicides; in all equations N = 136 (without 21 countries with the state Islamic religion); year = 2016. Variables:
The analysis of homicide rates is presented below. We calculated the correlation ratios and composed equations across the entire sample (Table
Correlation between homicide rates and selected indicators across 136 countries, 2016.
Homicides per 100,000 people | |
Suicides per 100,000 people | –0.04 |
GDP (PPP) per capita, $ | 0.21 |
Inequality, % | 0.43 |
Unemployment, % | 0.16 |
Happiness index, points | 0.09 |
Alcohol/substance use disorders, % | 0.13 |
Depression, % | –0.09 |
Anxiety disorders, % | –0.18 |
This correlation table is brief but quite clear. Homicide frequency is negatively correlated with GDP per capita, anxiety disorders and depression and does not correlate with suicide frequency. A positive correlation with the happiness index is evident, as the latter is composed by the GDP per capita logarithm. Inequality, unemployment, and alcohol/substance use disorders create the “positive side” of the correlations, so to speak.
The regression equation H-1 (Table
Equation H-1: Homicides (136 countries).
Const | ineq | anxiety | R 2 | |
Regression coefficients | –5.77 | 0.6 | –1.5 | 0.22 |
t-statistics | 3.73 | –1.955 |
The conclusion from our preliminary analysis for all countries is quite consistent with earlier scientific findings (Lester): inequality is the most significant issue across the entire history of homicide studies, and below we will examine this correlation by clusters.
The suicide rate is a completely different story and far less explicable through social factors (at a glance). Table
Correlation of suicide rates across 136 countries, 2016.
Suicides per 100,000 people | |
Homicides per 100,000 people | –0.04 |
GDP (PPP) per capita, $ | 0.42 |
Inequality, % | –0.37 |
Unemployment, % | –0.03 |
“Happiness” index, points | 0.33 |
Alcohol/substance use disorders, % | 0.60 |
Depression, % | 0.23 |
Anxiety disorders, % | 0.14 |
We should note the positive correlation between suicide frequency and both GDP (equation S-2; Table
Equation S-2: Suicides (136 countries).
Const | alcohol | depr | R 2 | |
Regression coefficients | –4.88 | 3.7 | 1.63 | 0.395 |
t-statistics | 8.57 | 2.8 |
So far we leave one equation that provides the best results: alcoholism/drug addiction and depression. Although at first glance this result seems to be pointing “back” towards psychology, we believe that the social studies and literature (including fiction) cover the growing phenomena of depression and alcoholism in a complex structure of modern society. And many individuals struggle to escape from loneliness and depression and become vulnerable and highly emotional over personal, business, and psychological disasters. These two determinants of suicide rates in the equations could be considered as closely connected to the social life background in developed economies.
Below we carry out more detailed analysis of “normal” homicide and suicide rates based on a country’s level of development, assuming that this will either support the general results and thereby enhance their significance, or produce further considerations for elaborations on the topic.
To identify the specific characteristics of homicide and suicide rates, we examine these indicators in more details by country groups (Table
Correlation of homicide rates by cluster groups.
Number of countries | GDP (PPP) per capita, $ | Inequality, % | Unemployment, % | “Happiness” index, points | Alcohol/substance use disorders, % | Depression, % | Anxiety disorders, % | |
Clusters 1–2 | 43 | –0.37 | 0.41 | –0.09 | –0.14 | 0.29 | –0.14 | –0.43 |
Clusters 3–4 | 35 | –0.39 | 0.50 | –0.04 | 0.29 | 0.15 | 0.09 | –0.01 |
Clusters 5–7 | 58 | 0.15 | 0.45 | 0.39 | 0.4 | 0.22 | 0.01 | –0.01 |
Islamic | 21 | –0.33 | n.a.a) | 0.04 | –0.55 | 0.48 | 0.13 | –0.10 |
The homicide rate index is correlated rather highly with the inequality index for the 136 countries, and for all three calculated equations by groups. For the most developed countries (clusters 1–2, equation H-3; Table
Equation H-3: Homicides (1–2 clusters).
Const | ineq | alcohol | anxiety | R 2 | |
Regression coefficients | –9.1 | 0.64 | 0.17 | –1.63 | 0.45 |
t-statistics | 3.75 | 0.57 | –1.88 |
The homicide rate is higher in countries not just with low GDP (PPP) per capita, but in post-Soviet and Latin American countries (Latvia, Kazakhstan, Romania, Russia, Chile, Columbia, Salvador), which are characterized by a higher level of social disintegration while social institutions are less effective than in the developed Western European countries or, alternatively, in traditional societies.
Homicide rates index in clusters 3–4 (equation H-4; Table
Equation H-4: Homicides (3–4 clusters).
Const | gdp | happ | R 2 | |
Regression coefficients | 0.97 | –0.001 | 5.80 | 0.32 |
t-statistics | –3.3 | 2.75 |
The highest homicide rates are found in Latin American countries (Colombia, Salvador, Guatemala) and South Africa. The lowest homicide rates are found in China, Croatia and Indonesia.
In clusters 5–7 (less developed countries — below 6,500 international dollars per capita), homicide rates still correlate (equation H-5; Table
Equation H-5: Homicides (5–7 clusters).
Const | unemp | alcohol | R 2 | |
Regression coefficients | –4.56 | 0.58 | 2.86 | 0.3 |
t-statistics | 3.53 | 1.7 |
The unemployment in clusters 5–7 significantly increases the homicide rate — so we included it in the equation (inequality left out to avoid multicollinearity). The homicide rate varies noticeably: in Venezuela, Lesotho, and Honduras it is considerably higher than in other countries within the group, particularly over 30 times higher than in Burundi, Laos, and Burkina Faso.
The analysis of the Islamic cluster (21 countries — equation H-6; Table
Equation H-6: Homicides (Islamic countries).
Const | alcohol | happ | R 2 | |
Regression coefficients | 5 | 6.33 | –2.28 | 0.465 |
t-statistics | 2.20 | –2.73 |
Maximum values prevail mostly in poor countries — Afghanistan and Iraq, while the lowest homicide rates are in Egypt, Oman, and Saudi Arabia.
Overall, the analysis across the clusters (levels of development) showed a highly persistent correlation between homicide frequency and inequality. This verifies the analyses in previous studies based on data from developed countries. Thus, this fact can be extrapolated to the 21st century and to developing countries. However, the mechanism for this correlation may become the subject of research: a single mechanism may represent multiple mechanisms until this possibility is not eliminated by analytical means.
The development level has its own role: the role of alcohol/drug addiction increases as the level of development does. The role of depression is especially prominent in clusters 3–4 (transition economies), although inequality negatively correlates with suicide, unlike homicide. We shall also emphasize that “indifference” of the “happiness” indicator to suicide rate (there is a positive correlation in the poorest country group though) might be attributed to the growth rates. Table
Correlation of suicide rates by the cluster groups.
Number of countries | Homicides per 100,000 people | GDP (PPP) per capita, $ | Inequality, % | Unemployment, % | “Happiness” index, points | Alcohol/substance use disorders, % | Depression, % | Anxiety disorders, % | |
Clusters 1–2 | 43 | 0.26 | –0.12 | –0.30 | –0.29 | –0.18 | 0.59 | 0.11 | –0.39 |
Clusters 3–4 | 35 | –0.07 | 0.23 | –0.49 | –0.05 | –0.09 | 0.49 | 0.51 | 0.06 |
Clusters 5–7 | 58 | 0.08 | 0.05 | 0.12 | 0.07 | 0.27 | 0.32 | 0.25 | 0.04 |
Islamic | 21 | 0.08 | 0.09 | n. a. a) | 0.05 | –0.17 | 0.21 | 0.06 | –0.12 |
For the overall suicide rate (equation S-7; Table
Equation S-7: Suicides (136 countries).
Const | unemp | alcohol | anxiety | R 2 | |
Regression coefficients | 14.48 | –0.24 | 2.90 | –1.40 | 0.465 |
t-statistics | –1.29 | 4.27 | –2.34 |
The constant term in the equation is 14.48, i.e. in the full absence of unemployment, alcohol, drug, and anxiety disorders, the suicide rate would be quite high. This means that, in general, it is difficult to explain the variation of this variable through basic social, psychological and economic indicators. The very phenomenon may be the result of complex psychic processes, a reaction to the perception of oneself in a social context as something that has no sense (see
The peak values were found in the Baltic states: Lithuania, Estonia, Latvia, as well as in Russia and the United States. Thus, the suicide rate in Russia is twice as high as the group average. The lowest values, by contrast, are characteristic of Mediterranean countries: Italy, Greece, Spain, and Cyprus, as well as Israel, Turkey, and Panama.
The suicide rates (equation S-8; Table
Equation S-8: Suicides (clusters 3–4).
Const | gdp | alcohol | R 2 | |
Regression coefficients | –3.24 | 0.035 | 3.1 | 0.315 |
t-statistics | 1.88 | 3.5 |
The data indicates increased suicide rates in Belarus and Ukraine. Rates for Serbia and Uruguay were lower than in these countries, but higher than the group average. In Azerbaijan, Indonesia, and the Philippines, where the Muslim population prevails, the suicide rate is 4 times lower than in Belarus and Ukraine.
The suicide rates (equation S-9; Table
Equation S-9: Suicides (clusters 5–7).
Const | alcohol | depr | R 2 | |
Regression coefficients | –4.7 | 2.68 | 1.80 | 0.184 |
t-statistics | 2.83 | 2.35 |
Accordingly, the highest suicide rates in this group were observed in Moldova, India, and less-developed African countries: Lesotho and Kiribati. Honduras and Jamaica are characterized by low suicide rates. The proportionate change in the suicide rate and the level of “happiness” in this group is related to the fact that alcohol and drug consumption increases the mortality rate caused by suicide, but also increases the level of “happiness” within the group.
The analysis of the Islamic cluster (21 countries) shows that the only relatively significant correlation for the suicide rate in this group (–0.2) is with the level of alcohol/substance use disorders. A verification of the regression coefficients for the suicide rate has demonstrated that all variables are insignificant. The suicide rate is relatively high in poorer Yemen and in economically secure Qatar, and is the lowest within Kuwait as shown on Fig. 2.
Suicide and homicide rates per 100,000 people in Muslim countries, 2016.
Sources: World Bank; World Health Organization; Institute for Health Metrics and Evaluation.
An analysis of the character of Muslim society is not a goal of this paper. We would like to state that the facts for most of the world and for the cluster of 21 countries in which Islam is the national religion differ considerably. In this regard, we should note a whole number of specific features. First of all, they include the low homicide and suicide rates in most Muslim countries compared with the other countries under review; the homicide and suicide rates are very close; the factor of growing GDP per capita plays no noticeable role (Table
Average indicators in Muslim countries (excluding Afghanistan, Iraq, and Somalia).
Cluster | Cluster borders, USD thousand per capita | Homicides per 100,000 people | Suicides per 100,000 people | GDP (PPP) per capita, USD thousand | Inequality, share of 10th decile | Unemployment, % | “Happiness” index | Alcohol/substance use disorders, % | Depression, % | Anxiety disorders, % |
Islamic countriesa) | – | 1.87 | 4.17 | 31.28 | 28.1b) | 8.03 | 5.4 | 1.59 | 4.06 | 4.88 |
There are also no significant differences between specific values for the two indicators, as seen in other countries. In this respect, however, we can see an exception to the rule: in Afghanistan, Iraq, and Somalia, violence is rampant due to long-lasting conflicts and a weak (non-existent) centralized power. Another group of three countries can be examined in a similar way: Pakistan, Jordan, and Lebanon, where homicide frequency is close to or exceeds suicide rates. We believe that this is caused by their proximity to Afghanistan and Syria, which have been ravaged by armed conflicts.
To yield more precise conclusions regarding the specifics of suicide indicators, we conducted an analysis across gender and age groups with the same predictors. On the whole, the highest suicide rates were observed in post-Soviet countries: Lithuania, Russia, Belarus, Kazakhstan, and Ukraine (32.0, 31.0, 26.2, 22.5, and 22.4 per 100,000 people, respectively, whereas the average across the 136 countries was 10.3), which are also transitional economies undergoing the formation of political and economic institutions amid a severe economic crisis.
Suicide rates usually rise along with the age of the group analyzed. One possible reason is the feeling of loneliness and of one’s uselessness, caused, among other things, by “failures” of individuals in the highly competitive social system. This is also one of the characteristics of developing and less developed countries: social failure, i.e. a situation of ineffectiveness or inconsistency of the social status and competencies of certain individuals, where opportunities for other individuals are severely limited (
Among people aged 50 to 69, the greatest suicide rates were registered in Lesotho (67.84 per 100,000), Lithuania (53.24), Zimbabwe (52.4), Russia (41.5), and South Korea (41.5), while the overall average for the age group was 17.13. With age, depression leads to more suicides than alcohol/substance use disorders. The most developed country clusters 1–2 are the exception, where working-age people (15–49) commit nearly the same number of suicides as people aged over 70. One of the reasons is, presumably, a reaction to failures associated with one’s career and personal life (personal failures), which, in terms of Henry and Short, differs from social failure, as it implies auto-aggression. Nikos Antonakakis and Alan Collins (2018) found that in high-income countries income increases are likely to lead to deteriorating mental health, while in middle-income countries income rises will rather affect mental health positively.
Suicide is most often associated with alcohol/substance use disorders (corr. 0.7) among men, and with depression among women (corr. 0.3). This is partly caused by the fact that women are generally less prone to alcohol and drug addiction than men (see
Countries with relatively high social inequality demonstrate a wide gap in male and female suicide rates, where male suicide rates are significantly higher than similar indicators in developed countries with low social inequality. However, in difficult social conditions the difference between male and female suicide rates is also low (Nigeria, Bangladesh). In the Netherlands, Norway, and Switzerland, the male suicide rate is almost twice as high as the female rate, but in Estonia, Georgia, Russia, and Panama it is over four times higher. On average, the male suicide rate is approximately 3 times higher than that of the female.
The use of various “happiness” indicators has a long tradition, although economists have not been widely involved in its analysis, since they tend to believe that a growing per capita income has a favorable impact on the feeling of happiness (
Popular in recent years, the “happiness” indicator (mentioned above) is a compound indicator consisting of indexes such as logarithmic GDP per capita, social connections (support by friends and relatives), healthy life expectancy, freedom of choice, charity during past 12 months, perceived corruption, the level of positive and negative emotions (average frequency of the feeling of happiness, joy, anxiety, fun, and anger, respectively), confidence in the national government, the state of democracy, the quality of services, the proportion of the poorest part of the population, i.e. an index reflecting the level of inequality, and level of interpersonal trust. It is a non-specialized index, but it covers many social, political, and psychological factors that influence life satisfaction. Thus, it is a kind of convention explaining why people in countries with stable social institutions and high income might or should be happy.
Thus, there is an important difference between the three variables: national homicide and suicide indicators are statistically observable and both result from the behavior of an individual and his or her reaction to life events. On the other hand, the “happiness” index is, in essence, an estimated indicator reflecting a certain normative hypothesis of its authors: the indicators of which (and the weight of which) should make people happy, with the same principle applied to all populations around the world. This is, undoubtedly, an exaggeration, as the “happiness formula” cannot be the same for the wide variety of countries, levels of development, cultural codes, citizen awareness of democracy and its actual state. In our opinion, it makes more sense for the developed countries. Therefore, we use the “happiness” index cautiously; the more the cluster is closer to the particular value system, the more reliable the “happiness” indicator is. The general hypothesis regarding the estimated “happiness” indicator could be that if it reflected emotional state, it would be in negative correlation with suicide. However, the estimated index also correlates positively with suicide rate in top country clusters (–0.18 coefficient), where social institutions are developed and effective. Below we examine this problem in the BRICS countries.
The average “happiness” index for population around the world has remained roughly the same (5.4 points out of 10.0) over the last 12 years, whereas average well-being has been growing. The studies which referred to these statistics confirmed the paradox that emotional well-being, i.e. happiness, unlike satisfaction with life, is not closely connected with income (
As we noted above, the “happiness” index is rather a target indicator than a survey-based indicator of the emotional attitude of people to their lives. For simplicity, we divided the survey-based “happiness” indicator by the “happiness” index in BRICS countries for 2010–2014 (Table
Comparison of population surveys on “happiness” in BRICS countries with the “happiness” index.
Country | “Happiness” index, pointsa), 2010–2012 | “Happiness” index, points, 2017 | “Happiness” based on surveys, %, 2010–2014b) | Indicator ratio for 2010–2014 |
(а) | (b) | (b) / (a) | ||
Brazil | 6.85 | 6.64 | 92.0 | 13.4 |
Russia | 5.46 | 5.96 | 87.4 | 16.0 |
India | 4.77 | 4.32 | 73.3 | 15.4 |
China | 5.00 | 5.27 | 84.5 | 16.9 |
South Africa | 5.00 | 4.83 | 76.4 | 15.3 |
It should be noted that, in the context of the social and psychological situation in the BRICS countries, the contrast between “happiness” (both estimated and survey-based) and population loss caused by homicide and suicide remains (see Table
Average homicide and suicide rates in BRICS countries.
Country | Homicides per 100,000 people, | Suicides per 100,000 people, | ||||
2000 | 2017 | 2000 | 2017 | |||
Brazil | 32.1 | 31 | 6.3 | 6.1 | ||
Russia | 34 | 14.8 | 44.1 | 25.1 | ||
India | 4.3 | 3 | 19.7 | 15.6 | ||
China | 2.6 | 1 | 14.3 | 7.2 | ||
South Africa | 60 | 28.6 | 24.3 | 11.1 |
The development of the BRICS countries as regional leaders and the improvement of their social institutions influence the situation in neighboring countries. Therefore, the reduction of homicide and suicide rates in Russia, Brazil, and South Africa is not only an indicator of their internal state, not only a part of their transition to sustainable development, but also an example of improvement of their citizens life conditions. There are reasons to suppose that higher incomes in the countries within the group will not cause higher suicide rates. More extensive research is necessary to understand these processes better.
Countries in transition comprise a big important group with a very similar fate over the past 30 years, albeit with very different levels of development and degrees of success in their transformation. Our analysis would be incomplete without at least a brief description of the situation in Russia and other transitional economies. It should be noted that Russian demographers explore the problem of high mortality rates (see
For Russia, where levels of inequality and levels of homicide and suicides remain relatively high compared with other countries, this topic is of high importance for social policy and assessing the state of society as a whole. An in-depth study of this problem is of particular importance for the demographic policy in the country, since the loss of population (especially men) for various reasons not related to the natural factors of disease and age is huge. International sources, however, provide figures about the level of suicides in Russia, which are higher than Russian ones (see Institute for Health Metrics and Evaluation, Fedstat). We use data from international sources in the correlation and regression analysis and international comparisons, but in this section we will apply the national data for a domestic regional perspective.
Russia follows the same paradigm as other Eastern European countries: although the relative homicide and suicide rates are significantly higher than the region’s average, trends are similar. Nevertheless, despite common culture and history, Eastern European countries and Russia are characterized by similar but differently-developing socioeconomic patterns and inequality models. In the Czech Republic, Slovakia, and Serbia, homicide and suicide rates decreased throughout the entire period; as noted in the article “The structure of social inequality in the modern world: measurement problems,” (
The 1990s were a period of notable growth of homicide and suicide ratios in countries undergoing the transformation from a planned to market economy (Table
Homicide and suicide rates per 100,000 people in Eastern European, Baltic, and Transcaucasian countries in 1990, 2000, and 2017, and in the year of peak values.
Country | Homicides | Suicides | Ratio of suicides to homicides | ||||||||||||
1990 | in peak year | peak year | 2000 | 2017 | 1990 | in peak year | peak year | 2000 | 2017 | 2000 | 2017 | ||||
Russia | 18.24 | 38.05 | 1994 | 34.31 | 14.80 | 28.32 | 50.18 | 1994 | 44.18 | 25.09 | 1.29 | 1.70 | |||
Kazakhstan | 13.71 | 20.76 | 1996 | 18.21 | 8.51 | 21.12 | 38.29 | 2005 | 33.43 | 22.99 | 1.84 | 2.70 | |||
Estonia | 11.80 | 24.52 | 1994 | 15.34 | 4.50 | 26.81 | 39.47 | 1994 | 28.01 | 12.74 | 1.83 | 2.83 | |||
Kyrgyzstan | 10.84 | 13.25 | 1994 | 8.83 | 4.21 | 17.09 | 18.36 | 1994 | 17.15 | 10.02 | 1.94 | 2.38 | |||
Latvia | 10.30 | 21.92 | 1994 | 13.40 | 6.87 | 25.81 | 40.88 | 1994 | 28.11 | 16.99 | 2.10 | 2.47 | |||
Moldavia | 9.95 | 15.84 | 1995 | 11.85 | 6.03 | 17.41 | 20.8 | 1995 | 16.92 | 13.64 | 1.43 | 2.26 | |||
Azerbaijan | 8.38 | 14.92 | 1993 | 5.70 | 3.66 | 3.17 | 5.14 | 2007 | 3.14 | 4.07 | 0.55 | 1.11 | |||
Ukraine | 8.38 | 17.79 | 1996 | 16.09 | 10.18 | 19.43 | 31.37 | 1996 | 29.55 | 25.62 | 1.84 | 2.52 | |||
Lithuania | 7.67 | 12.72 | 1994 | 10.33 | 6.02 | 27.97 | 44.77 | 1995 | 40.41 | 27.99 | 3.91 | 4.65 | |||
Belarus | 7.23 | 13.03 | 2002 | 13.30 | 6.83 | 20.33 | 36.95 | 2002 | 33.73 | 19.03 | 2.54 | 2.79 | |||
Turkmenistan | 5.70 | 7.43 | 1998 | 5.84 | 4.08 | 9.06 | 13.34 | 2005 | 11.38 | 8.68 | 1.95 | 2.13 | |||
Uzbekistan | 5.00 | 5.04 | 1991 | 3.43 | 2.56 | 9.16 | 11.13 | 2005 | 10.91 | 9.39 | 3.18 | 3.67 | |||
Georgia | 4.97 | 6.13 | 1993 | 3.94 | 3.84 | 4.81 | 7.49 | 2017 | 5.43 | 7.49 | 1.38 | 1.95 | |||
Serbia | 4.93 | 5.21 | 1997 | 4.57 | 2.46 | 19.43 | 20.94 | 1997 | 19.21 | 12.67 | 4.20 | 5.15 | |||
Romania | 4.44 | 4.50 | 1992 | 3.60 | 2.09 | 9.47 | 11.62 | 1997 | 10.55 | 9.16 | 2.93 | 4.38 | |||
Armenia | 4.27 | 7.21 | 1993 | 4.17 | 3.69 | 3.42 | 8.85 | 2012 | 3.72 | 8.26 | 0.89 | 2.24 | |||
Bulgaria | 3.97 | 5.62 | 1994 | 4.51 | 2.53 | 14.77 | 17.49 | 1997 | 15.53 | 9.48 | 3.44 | 3.75 | |||
Slovakia | 3.66 | 3.66 | 1990 | 3.36 | 2.43 | 15.46 | 15.46 | 1990 | 13.02 | 9.47 | 3.88 | 3.90 | |||
Hungary | 3.47 | 4.00 | 1993 | 3.01 | 1.63 | 33.81 | 33.81 | 1990 | 23.66 | 14.28 | 7.86 | 8.76 | |||
Poland | 3.15 | 3.52 | 1995 | 3.19 | 1.73 | 13.57 | 16.92 | 1999 | 16.49 | 13.95 | 5.17 | 8.06 | |||
Slovenia | 2.31 | 2.40 | 1991 | 1.87 | 0.98 | 27.68 | 30.14 | 1993 | 25.25 | 14.38 | 13.50 | 14.67 | |||
Czech Republic | 2.23 | 2.50 | 1994 | 2.09 | 1.14 | 18.94 | 18.94 | 1990 | 13.96 | 10.77 | 6.68 | 9.45 |
Table
We would notice that countries in transition, which joined the EU, demonstrate low homicide rates and rather high (but decreasing) suicide rates — quite a predictable dynamics for the period up to 2017. Some countries, especially those in the post-Soviet space are showing a great diversity of patterns. In particular, Armenia, Azerbaijan, and Georgia have shown rather modest initial suicide rates, which increased greatly during the 21st century; also Latvia, Lithuania, and Estonia have high suicide rates. These patterns indicate stresses within the societies given all the differences in their socioeconomic situations.
It has been noted (
Russia belongs to the 2nd cluster of countries with its 25 000 international dollars per capita. Although in Russia the murder rate per 100 thousand people is still higher than the average in the group of countries of 1–2 clusters (rather, our indicators are similar for cluster 4), it should also be noted that the number has been decreasing since 2000. A sharp increase in the suicide rate in our country occurred in 1990–2002 (see Fig. 2). A similar problem took place in many other countries that underwent a period of socio-economic transformation. Now it has fallen markedly, but still remains a serious problem.
The weakening of the state (severe anomie of the 1990s), the impoverishment of a significant part of the population in the 1990s with the rapid and pervasive social differentiation, resulted in a “two-humped” leap in the dynamics of interpersonal violence (Fig. 3). Peaks showed up in 1994 and 2001, after that the indicators had been declining slowly but steadily, so in 2017 they reached a minimum over 27 years. It is difficult for us to give a forecast for the future, but we note that the level of the population losses in Russia is comparable with the population losses in Brazil and South Africa. The difference is that in these countries three-quarters of the losses account for murders whereas in Russia almost two-thirds are suicides.
Suicides and homicides per 100,000 people in Russia, 1990–2017.
Note: Here is the national count. The data provided by the Unified Interdepartmental Information and Statistical System (EMISS) differ from the data provided by the Institute for Health Metrics and Evaluation as shown in Table
Economic recovery and strengthening of the Russian state in 2000–2017 had a positive effect on reducing the intensity of the phenomenon of murders and suicides in Russia. Our calculations made it possible to test the hypothesis about the relationship between the level of development and the nature (intensity) of losses within the country by region. Previously, we established an important fact regarding the decrease in the intensity of homicides and suicides from 2000 to 2017 along the entire number of regions (ranked by GRP per capita). Economic growth in Russia in the 2000s was of different intensity before and after 2008, so the increase in per capita income went extremely unevenly over time. It is important to understand what happens to such difficult social problems in the conditions of a gradual normalization of social life (not widely felt prosperity but the absence of a sharp income drop until 2015). During the recession of 2015–2016 the dynamics of both indicators didn’t change, although the ratio of 2017 indices to those of 2014 didn`t shrink much.
Russian regions are far from being homogeneous in their level of development and production structure, which requires a systemic approach (see
We can practically rely on the international comparisons above to formulate a hypothesis regarding the expected indicator rates in regions given different levels of development. Of course, Russia’s regions are not countries with separate histories and institutions. However, there cannot be flat regional distributions of tragedies under discussion. We could assume that the most developed regions should demonstrate relatively low homicide rates, but it is much more difficult to formulate a hypothesis with respect to suicide rates. The actual state of affairs is shown in Table
Weighted average Human development index (HDI) and homicide and suicide rates in Russia by type of region, 2000 and 2017.
Region type | HDI | Homicides per 100,000 people | Suicides per 100,000 people | Share of population, % | ||||||
2017 | 2000 | 2017 | 2000 | 2017 | 2017 | |||||
1. Financial centers | 0.929 | 19.4 | 4.2 | 18.6 | 6.6 | 0.173 | ||||
2. Commodities exporters | 0.901 | 38.7 | 9.6 | 40.8 | 17.4 | 0.031 | ||||
3. Diversified | 0.888 | 24.6 | 5.2 | 37.3 | 9.9 | 0.157 | ||||
4. Manufacturing | 0.879 | 28.0 | 7.7 | 47.1 | 17.4 | 0.120 | ||||
5. Mining | 0.879 | 34.85 | 7.4 | 53.5 | 21.0 | 0.087 | ||||
6. Industrial-agro | 0.859 | 32.6 | 7.7 | 47.2 | 17.0 | 0.110 | ||||
7. Agro-industrial | 0.857 | 24.0 | 5.4 | 38.7 | 14.9 | 0.250 | ||||
8. Less developed commodities | 0.860 | 46.5 | 17.0 | 73.0 | 38.4 | 0.014 | ||||
9. Less developed agro | 0.829 | 37.68 | 4.0 | 39.48 | 6.5 | 0.056 |
The reduction of the relative homicide and suicide parameters by region from 2000 to 2017 reflects both the general trend and the specific aspects of the socioeconomic situation in different types of regions (see Table
The most impressive achievement in the reduction of individual tragedies happened in the most developed and diversified regions. That is quite logical, since they provide the population with opportunities for personal fulfillment. Homicide, as an indirect repercussion of inequality, is supposed to be restricted by the legal and law enforcement system. Suicides in society, caused by despair, personal “dead ends”, or personal career or business failures cannot be avoided completely. However, diversified cities (regions) provide citizens with more choice, opportunities for a new start and self-realization. This may seem paradoxical, given the fact that in the well-off countries in clusters 1–2, the suicide rate is higher than in other clusters. It may be explained in a more detailed analysis of the accompanying factors, social environment, and the regional specifics for other countries — the subject for further research. Russia has one of the world’s highest national suicide rates, and it is quite difficult to say whether it will decline along with economic progress to the level of developed countries, or if it will fluctuate at roughly the same level.
Anyhow, the two phenomena require close attention and research, both in general, regarding the motives for respective dynamics, and the circumstances that cause it (particularly the trend). Such research should have a regional dimension and probably a socio-demographic perspective: age, gender, occupation, etc. However, the overall situation remains difficult. We believe that the rates and trends for these indicators by type of region (rather than for the country as a whole) provide more informative data for researchers into social processes.
Unfortunately, the phenomenon of homicide and suicide is especially common in a number of regions around the world and in Russia. However, both homicide and suicide rates are significantly lower in financial centers and diversified developed regions. This contrast looks even more dramatic within a single country because regions with different levels of development are neighbors in a vast territory. Income and human development indices are higher in states` capitals and developed diversified regions; it is highly close to the world’s country clusters 1–2, in which we can see a high suicide rate but a low homicide rate. In the Sustainable Development Goals Agreement of UN (2015) the world community raised the question of improving the standards of living and reducing inequality. Surprisingly, SDG was shy to mention (or set a goal and an indicator regarding) such tragic aspects of life in modern society as homicide and suicide (the latter appeared only as an indicator of mental health). Given Russia’s difficult demographic situation, homicide and suicide should be considered carefully in social policies. They are the result and the source of a critical socio-psychological condition in many strata within the society and in particular by the regions. In this respect, ensuring prosperity is of paramount importance: a reduction in violence and despair within society could be attributed to reduced homicide and suicide rates.
Our goal was to study homicide and suicide rates dynamics in various countries around the world and to find out whether psychosocial factors prove the presence of elements of anomie within society. We can observe that this process is accompanied by growing isolation, loneliness, and despair and with more intensive perceived “personal failures” which lead to a relative increase in suicide rates. Psychosocial factors, such as alcohol/substance use problems, anxiety disorders and depression, are not reliable indicators of an adverse or some other state of a society.
Based on the results of the study, we came to the following important conclusions.
We are far from reaching assumptions about solutions to social aspects of the homicide and suicide phenomena. We would like to emphasize the insufficient amount of research on this topic. To obtain the best understanding of the socioeconomic context of suicide and its correlation with homicide and the level of “happiness”, future studies should pay particular attention to developed and developing countries (particularly the BRICS countries). Post-Soviet countries are important objects of research as the closest to Russia in terms of culture and similar social anomie in 1990–2018. We believe that study of this phenomenon could become part of the research on the transition from an industrial to a post-industrial society, and the role of cultural codes in the life of modern society. It would be rational and ethical to include this phenomenon in the process of ensuring the sustainable development of the world, which is incompatible with war and crime and with large-scale suicide and interpersonal violence. Individual tragedies matter!