Associations of Suicide and Subjective Well-Being

Abstract

The aim of this study is to examine relationships between suicide and subjective well-being. Correlation and regression analysis are conducted on 81 countries’ aggregate data from United Nation agencies. Generally, suicide is not significantly related to life satisfaction; or negative affect, or positive social emotion, but significantly negatively related to positive self-emotion, or positive interpersonal emotion. In preventing suicide, subjective well-being’s affective aspect might play a more important role than its cognitive aspect, positive affect might play a more important role than negative affect, and the personal aspect of positive affect might play a more important role than the social aspect.

Keywords

suicide subjective well-being positive affect human development report hierarchical multiple linear regression.

Subjective well-being is a person’s cognitive and affective evaluations of his or her life (Diener, Lucas, & Oishi, 2002). Many empirical studies have suggested a negative relationship between self-destruction and happiness and positive affect (Hirsch, Duberstein, & Unutzer, 2009; Koivumaa-Honkanen, Honkanen, Koskenvuo, & Kaprio, 2003), and between life satisfaction and self-destruction (Fujino, Mizoue, Tokui, & Yoshimura, 2005; Heisel & Flett, 2004; Yao et al., 2014), and a positive one between self-destruction and negative affect (Soares et al., 2016). However, results reported by other empirical studies slightly or even totally differ. For example, in one study, suicide related negatively to life satisfaction or happiness, but suicide was more relevant to life satisfaction or happiness in older than in younger people (Bray & Gunnell, 2006). In another study, indicators of life satisfaction or happiness predicted men’s, but not women’s, suicide rates (SURs; Voracek, 2009). For another example, quality of life (including life satisfaction) was found related positively to SURs (Lester, 1989). And in industrialized countries, SURs were found significantly and positively associated with happiness (Lester, 2002). Similarly, older people in Nordic countries have reported the highest life satisfaction, the most comfortable income level, and relatively better general health among all countries studied; nevertheless, older people’s SURs were still higher (Wu, Värnik, Tooding, Värnik, & Kasearu, 2014).

By using large data sets for most of the comparatively more developed countries, this manuscript also reports the results of the relationship between suicide and subjective well-being. One strength of the study is inclusion of data for a larger number of nations, with representative sampling. Another strength might be use of measures from a publicly used data source for variables studied and inclusion of several dimensions of well-being, rather than a single overall variable. Still another strength might be the discussion’s consideration of leading and current theories of suicide with regard to findings for investigated variables.

Then, some specific hypotheses for SURs according to subjective well-being’s various components are proposed as follow: SURs decrease as life satisfaction increase (Hypotheses 1), and also decrease as positive affect increase (Hypotheses 2), and will increase as negative affect increases (Hypotheses 3).

Data

The research uses data of related indicators as independent and control variables in the statistical tables of the Human Development Report (HDR) 2010 (United Nations Development Programme, 2010), with the exception that SURs as the dependent variable are from World Health Statistics 2016 (World Health Organization, 2016). Note that all data in this study are relevant not at the individual level but at the country level.

There are altogether 169 countries with available human development index in the HDR 2010, and these countries are divided quarterly (i.e., 42 very high, 43 high, 42 medium, and 42 low human development countries). Both the HDR 2010 and World Health Statistics 2016 provided data from most of these 169 countries, but medium and low development countries are excluded from this study because of the problem of poor-quality suicide data usually occurring in the developing countries (World Health Organization, 2019). Considering the reason for robustness, data only from 81 comparatively more developed countries (i.e., 42 very high, plus 43 high, but minus 4 countries missing for suicide data) are used. Countries included in this study are listed in Table 1.

Table 1.

Countries Presented in This Study (Data of the Corresponding Countries Are Missing for the Indicators in Brackets).

Very high human development

Norway, Australia, New Zealand, United States, Ireland, Liechtenstein (IGC, PHY, OLS, PUL, TWR, SSN, NEI, SUR), Netherlands, Canada, Sweden, Germany, Japan, Republic of Korea, Switzerland, France, Israel, Finland, Iceland (IGC, PUL), Belgium, Denmark, Spain, Hong Kong SAR (PHY, SUR), Greece, Italy, Luxembourg (IGC, PUL), Austria, United Kingdom, Singapore, Czech Republic, Slovenia, Andorra (IGC, PUL, TWR, SSN, NEI, SUR), Slovakia, United Arab Emirates (IGC), Malta (IGC, PUL), Estonia, Cyprus (IGC), Hungary, Brunei Darussalam (IGC, OLS, PUL, TWR, SSN, NEI), Qatar (PUL), Bahrain (IGC, OLS, PUL), Portugal, Poland, Barbados (IGC, PHY, OLS, PUL, TWR, SSN, NEI).

High human development

Bahamas (IGC, PHY, OLS, PUL, TWR, SSN, NEI), Lithuania, Chile, Argentina, Kuwait (IGC), Latvia, Montenegro, Romania, Croatia, Uruguay, Libyan Arab Jamahiriya (IGC, OLS, PUL, SSN, NEI), Panama, Saudi Arabia (IGC), Mexico, Malaysia, Bulgaria, Trinidad and Tobago, Serbia, Belarus, Costa Rica, Peru (PHY), Albania, Russian Federation, Kazakhstan, Azerbaijan, Bosnia and Herzegovina, Islamic Republic of Iran, The former Yugoslav Republic of Macedonia (IGC, OLS, PUL, TWR, SSN, NEI), Brazil, Georgia, Bolivarian Republic of Venezuela, Armenia, Ecuador, Belize, Colombia, Jamaica, Tunisia (PUL), Jordan, Turkey, Algeria (PUL), Tonga (IGC, OLS, PUL, TWR, SSN, NEI, SUR).

Note. SUR = suicide rates; IGC = Income Gini coefficient; PHY = physician; OLS = overall life satisfaction; PUL = purposeful life; TWR = treated with respect; SSN = social support network; NEI = negative experience index; Hong Kong SAR = Hong Kong Special Administrative Region of the People’s Republic of China.

And the explanations of all variables included in this study are listed in Table 2. The detailed definition of SURs, as the dependent variable, is as follows: Estimated total number of deaths from purposely self-inflicted injuries, in the total population or of a given sex or age, divided by the total number of the reference population, expressed per 100,000 people.

Table 2.

Explanation of Variables.

	Variables	Notes	Year	Abbreviations
Independent variables	Overall life satisfaction	0–10	2006–2009	OLS
	Elements of happiness: Purposeful life	%	2006–2009	PUL
	Elements of happiness: Treated with respect	%	2006–2009	TWR
	Elements of happiness: Social support network	%	2006–2009	SSN
	Negative experience index	0–100	2006–2009	NEI
Dependent variable	Suicide rates	per 100,000people	2012	SUR
Control variable	Gross national income per capita	$	2010	GNI
	Mean years of schooling	Years	2010	MYS
	Income Gini coefficient	0–100	2000–2010	IGC
	Deaths due to indoor and outdoor air and water pollution	Per 1,000,000 people	2004	DDP
	Physician	Per 10,000people	2000–2009	PHY

Subjective well-being, as independent variables, was usually measured in its three aspects: life satisfaction, positive affect, and negative affect. Here, subjective well-being’s cognitive dimension was represented by the overall life satisfaction (OLS) index; its measures are based on ladder-of-life questions, which ask respondents to rate their life from the worst (0) to the best (10). Negative affect is measured though the negative experience index (NEI), compiled by asking whether the respondent experienced anger, pain, or worry much of the previous day. Positive affect is the percentage of respondents answering yes to having one of the three happiness elements: purposeful life (PUL), treated with respect (TWR), and social support network (SSN). PUL means positive self-emotion or positive affect between the individual and the self, TWR means positive interpersonal emotion or positive affect between the self and others, and SSN is positive social emotion or positive affect between the individual and society.

The reason why the five control variables are chosen is that this study is conducted within the human development framework. On one hand, in the HDR, human development is measured by three aspects: income, education, and health. Correspondingly, gross national income per capita, mean years of schooling, and physicians per 10,000 people are chosen. On the other hand, the human development process seems nonlinear, and the Kuznets, or inverted U-shaped curves in the modern econometric, are used to describe a nonlinear process, and two main types of Kuznets are as follows: the income Kuznets curve (Kuznets, 1955), which may suggest loss in potential human development due to inequality and, second, the environmental Kuznets curve, suggesting human development effects from environmental threats (Shafik, 1994). Thus, in this study, inequality and environment, that is, income Gini coefficient and deaths due to indoor and outdoor air and water pollution, are set as two other control variables.

Results

Table 3 displays Pearson correlation coefficients between SURs and subjective well-being indexes, as well as partial correlation coefficients between SURs and subjective well-being indexes by controlling for some social variables. Generally speaking, these correlation analyses show that, of all subjective well-being variables, PUL and TWR had stronger negative association with SURs (p < .01), followed by NEI (p < .05), while SSN and OLS had no significant association with SURs.

Table 3.

Pearson Correlation Coefficients.

SUR	Control Variables	OLS	PUL	TWR	SSN	NEI
Correlation		−.114	−.581**	−.360**	.127	−.238*
	GNI	−.213	−.581**	−.445**	.150	−.160
	MYS	−.192	−.508**	−.403**	.098	−.133
	IGC	−.088	−.427**	−.371**	.143	−.095
	DDP	−.232	−.583**	−.430**	.087	−.148
	PHY	−.155	−.526**	−.449**	.115	−.120

Note. SUR = suicide rates; GNI = gross national income per capita; MYS = mean years of schooling; IGC = Income Gini coefficient; DDP = deaths due to indoor and outdoor air and water pollution; PHY = physician; OLS = overall life satisfaction; PUL = purposeful life; TWR = treated with respect; SSN = social support network; NEI = negative experience index.

*Significant at the .05 level (two-tailed).

**Significant at the .01 level (two-tailed).

To estimate effects of subjective well-being on suicide more precisely, hierarchical multiple linear regressions are conducted by controlling some social variables listed earlier. Table 4 shows summaries of hierarchical multiple linear regression models. In the five hierarchical models, with five control variables in the first block and one independent variable in the second block, the first and second greatest increases in values of R², adjusted R², and F are, respectively, caused by addition of variables TWR and PUL. The F changes brought about by addition of variables TWR and PUL, respectively, are both significant. Besides, effects of TWR and PUL on SUR are significant in their respective models. While in the five hierarchical models with nine control and independent variables in the first block and one independent variable in the second block, the first and second greatest increases in values of R², adjusted R², and F are, respectively, brought about by addition of variables TWR and SSN; the F change brought by addition of variables TWR and SSN are significant. Besides, effects of TWR and SSN on SUR are significant. These results seem quite similar to those of the correlation analysis, but an exception is the positive effect of SSN on SUR.

Table 4.

Results of Hierarchical Multivariate Regression Analysis.

Model		R ²			Adjusted R²			F			Standardized coefficients in two-block model
Block 1	Block 2	R ₁ ²	R ₂ ²	R² change	Adjusted R₁²	Adjusted R₂²	Adjusted R² change	F ₁	F ₂	F change	GNI	MYS	IGC	DDP	PHY	OLS	PUL	TWR	SSN	NEI
GNI, MYS, IGC, DDP, PHY	OLS	.248	.264	.016	.186	.190	.004	4.015**	3.583**	1.321	−.088	.252	−.177	−.300*	.159	−.172
GNI, MYS, IGC, DDP, PHY	PUL	.213	.334	.121	.145	.264	.119	3.133	4.757**	10.351**	−.112	.139	−.056	−.206	.052		−.441**
GNI, MYS, IGC,DDP, PHY	TWR	.248	.372	.124	.186	.309	.123	4.015**	5.916**	11.851**	−.022	.175	−.076	−.244*	.234			−.405**
GNI, MYS, IGC,DDP, PHY	SSN	.248	.251	.003	.186	.176	−.010	4.015**	3.345**	0.243	−.214	.232	−.241	−.255	.157				.067
GNI, MYS, IGC,DDP, PHY	NEI	.248	.255	.007	.186	.180	−.006	4.015**	3.415**	0.560	−.189	.218	−.237	−.264*	.151					−.087
GNI, MYS, IGC,DDP, PHY,PUL, TWR,SSN, NEI	OLS	.433	.444	.011	.338	.339	.001	4.575***	4.227***	1.054	.051	.084	.048	−.118	.105	−.218	−.269	−.359*	.338*	−.034
GNI, MYS, IGC,DDP, PHY,OLS, TWR,SSN, NEI	PUL	.406	.444	.038	.307	.339	.032	4.103***	4.227***	3.583	.051	.084	.048	−.118	.105	−.218	−.269	−.359*	.338*	−.034
GNI, MYS, IGC,DDP, PHY,OLS, PUL,SSN, NEI	TWR	.380	.444	.064	.276	.339	.063	3.679**	4.227***	6.091*	.051	.084	.048	−.118	.105	−.218	−.269	−.359*	.338*	−.034
GNI, MYS, IGC,DDP, PHY,OLS, PUL,TWR, NEI	SSN	.398	.444	.046	.298	.339	.041	3.970**	4.227***	4.338*	.051	.084	.048	−.118	.105	−.218	−.269	−.359*	.338*	−.034
GNI, MYS, IGC,DDP, PHY,OLS, PUL,TWR, SSN	NEI	.443	.444	.001	.350	.339	−.011	4.766***	4.227***	0.098	.051	.084	.048	−.118	.105	−.218	−.269	−.359*	.338*	−.034

Note. Dependent variable: SUR. SUR = suicide rates; OLS = overall life satisfaction; PUL = purposeful life; TWR = treated with respect; SSN = social support network; NEI = negative experience index; GNI = gross national income per capita; MYS = mean years of schooling; IGC = income Gini coefficient; DDP = deaths due to indoor and outdoor air and water pollution; PHY = physician.

*Significant at the .05 level.

**Significant at the .01 level.

***Significant at the .001 level.

Conclusions

The introduction presented three hypotheses, including negative relationships between life satisfaction and SUR, positive affect and SUR, and positive relationships between negative affect and SUR. Based on the three hypotheses, negative relationships, respectively, between five independent variables—OLS, NEI, percentage of yes answers to having a PUL, being TWR, and having an SSN—and the dependent variable, SUR are inferred (note that on the NEI, 0 = most negative, while 100 = least negative). Generally, this study’s empirical results show no significant statistical relationship between life satisfaction and SUR and no significant or relatively weaker significant statistical relationship between negative affect and SUR. These results seem not to support, or at least not fully to support, Hypotheses 1 and 3 of this study and some orthodox academic views (Fujino et al., 2005; Heisel & Flett, 2004; Soares et al., 2016; Yao et al., 2014). However, they are quite similar to some unorthodox views in related topics (Bray & Gunnell, 2006; Voracek, 2009; Wu et al., 2014).

In contrast, this study’s empirical results show complex statistical relationships between positive affect and SUR. On one hand, the significant negative statistical relationship between percentage of yes answers to being TWR and SUR in all this study’s correlation and regression analyses, and the significant, negative statistical relationship between percentage of yes answers to having a PUL and SUR in almost all this study’s correlation and regression analyses seem consistent, or at least not inconsistent with Hypothesis 2 and some orthodox views in related topics (Hirsch et al., 2009; Koivumaa-Honkanen et al., 2003). Empirical results here seem to suggest that there exists a significant negative statistical relationship between positive self-emotion and self-destruction and a significant negative statistical relationship between positive interpersonal emotion and self-destruction.

On the other hand, the insignificant statistical relationship between percentage of yes answers to having an SSN and SUR and even the unusually significant positive effect of SSN on SUR in the regression model seem fully inconsistent with Hypothesis 2 and some orthodox views (Hirsch et al., 2009; Koivumaa-Honkanen et al., 2003) but also consistent with some previous research results that differ slightly from orthodox views (Bray & Gunnell, 2006; Voracek, 2009) or even differ totally from orthodox views (Lester, 2002). This study’s empirical results seem to suggest that no significant negative statistical relationship or even a significant positive statistical relationship between positive social emotion and self-destruction exists.

In summary, this study’s empirical results lead to three conclusions. The first is affective rather than cognitive: This conclusion means that subjective well-being’s affective (rather than cognitive) aspect may play a more important role in preventing suicide due to the more significant negative statistical relationship between TWR (and PUL) and SURs than that between OLS and SURs. The second is positive rather than negative: This conclusion means that positive (rather than negative) affect may play a more important role in preventing suicide due to the more significant negative statistical relationship between TWR (and PUL) and SURs than that between NEI and SURs. The third is personal rather than social: This conclusion means that the personal (rather than social) aspect of positive affect may play a more important role in preventing suicide due to the more significant negative statistical relationship between TWR (and PUL) and SURs than that between SSN and SURs.

Next, the research’s findings are discussed in light of existing mainstream theories of suicide. According to Durkheim (1966), a low degree of social integration might result in suicide. That is to say, too little social integration leads to increased suicide because individuals lack connection to something that transcends them. This study’s empirical results seem not to support Durkheim’s classical theory, for some social affect, such as perceptions of having a support network, does not correlate significantly with SURs and, in a regression operation, even had significant, positive effect on SURs.

However, the interpersonal theory of suicide (Joiner, 2005; Van Orden et al., 2010) addressed some limitations of purely sociological approaches by attempting to synthesize both interpersonal and intrapersonal variables influencing suicidal behavior. Some findings of the present research seem consistent, or at least not contradictory, with interpersonal theory, for this study’s results showed that some types of interpersonal affect, such as perceptions of respectful treatment, are negatively and significantly correlated with SURs and have significantly negative effect on SURs.

Generally, Durkheim’s theory takes little account of individual factors. If all individuals in a society are exposed to shifts in social forces, why then do only certain individuals—a very small subset at that—die by suicide? In contrast, Shneidman’s (1987) theory focused on individual factors, with psychache referring mainly to emotional pain reaching intolerable intensity, as primary in causing suicide. Particularly worth noting is that related research (You, Song, Wu, Qin, & Zhou, 2014) confirmed psychache had stronger power predicting suicidal ideation and suicide attempt than life satisfaction, as evidenced by its greater standardized regression coefficients. This study supports this by showing significant associations between some of subjective well-being’s affective elements and SURs, as well as nonsignificant associations between subjective well-being’s cognitive dimension and SURs.

Besides, in this study, correlational significance between some positive affect elements and SURs, greater than that between negative affect and SURs (p < .01 vs. p < .05), seems more consistent with some nonmainstream theories of suicide. One is humanistic psychology (Rogers, Bromley, Mcnally, & Lester, 2011), emphasizing people’s positive nature and value, and viewing a suicide as one who cannot realize his or her own potential; thus life becomes meaningless, in contrast to mainstream theories, such as Shneidman’s focus on psychache as negative affect.

Limitations

A possible limitation relates to ecological fallacy, which occurs in drawing conclusions about individuals based only on group data analyses. In this study, persons reporting the least happiness are not necessarily those who commit suicide, thus, that the relationship studied here lies between overall subjective well-being ratings for a country and that country’s overall SUR should be emphasized. Thus, the present work may have more policy implications than clinical significance and be more instructive for public health officials than for psychiatrists. For example, clinical psychiatrists usually focus on the association between a given individual’s level of subjective well-being and his risk of completing suicide, but the first concern of the public health officials here should be the relationship between overall subjective well-being level for a region or country and that region or country’s overall SUR.

Public Health Implications

Some policy and public health implications may be derived from this study. Rather than cognitive, the first implication is affective; this may suggest that improving living standards and life satisfaction has quite a limited effect on reducing SURs. Rather than negative, the second is positive; this may suggest that improving mental-health services and resistance to negative emotions has quite a limited effect on reducing SURs. Rather than social, the third implication is personal; this may suggest that improving social welfare and sense of social security has quite a limited effect on reducing SURs.

In contrast, a social culture of optimism, egalitarianism, and individualism can, together or separately, seem helpful to reducing SURs due to the very significant, negative statistical relationship between TWR (and PUL) and SURs. And this public health implication can derive not only from this study, based on overall cross-sectional data from developed countries, but also from other studies based on time-series data from developing countries, with individuals as units of investigation.

For example, some researchers (Wang, Chan, & Yip, 2014) found that China’s SUR had obviously declined for the last 20 years. Unusually, this occurred without significantly improved mental-health services and national publicity to reduce suicides. Researchers (Sha, Yip, & Law, 2017) thought the decline nationally was caused by a steep decline in rural suicides, especially those of females. Researchers’ causal analysis focused on recent migration, for huge numbers of farmers, including 40 million female farmers annually, left their homes to find urban jobs, thus changing Chinese social structure. Rural females large-scale migration efficaciously avoided three previous self-destruction risks: females’ subordinate status in the family, family contraventions, and past suicide tools. Hence, rural women’s migration was one cardinal reason for the decline in Chinese self-destruction.

In the framework of this research, although living standards and general satisfaction of formerly rural women may have risen, they have to face many new life problems: pollution, food safety, and property prices, just like urban residents. Furthermore, in cities, former farmers are often treated as second-class citizens. Thus, using increased life satisfaction and decreased negative affect to explain Chinese female farmers’ decline in SUR seems unreasonable.

In comparison, Chinese female farmers’ waxing and waning of three happiness elements might be key for reducing their SURs. Migration liberates them from parental pressures, bad marriages, overbearing mothers-in-law, and other tensions of poor, rural life. That is, by moving to the city, women farmers lost their traditional SSN but gained opportunities to work and live independently and purposely (PUL) and be TWR at least by their husbands and family members.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biography

Ge Qian, PhD, is a lecturer of moral education at the Shanghai University of Finance and Economics. Dr. Qian’s primary research focuses on two areas: one is subjective well-being, the other is bibliometrics.

References

Bray

Gunnell

(2006). Suicide rates, life satisfaction and happiness as markers for population mental health. Social Psychiatry & Psychiatric Epidemiology, 41(5), 333–337.

Diener

Lucas

R. E.

Oishi

(2002). Subjective well-being: The science of happiness and life satisfaction. In Snyder

C. R.

Lopez

S. J.

(Eds.), Handbook of positive psychology (pp. 463–473). New York, NY: Oxford University Press.

Durkheim, E. (1966). Suicide: a Study in Sociology. New York, US: The Free Press.

Fujino

Mizoue

Tokui

Yoshimura

(2005). Prospective cohort study of stress, life satisfaction, self-rated health, insomnia, and suicide death in Japan. Suicide & Life-Threatening Behavior, 35(2), 227–236.

Heisel

M. J.

Flett

G. L.

(2004). Purpose in life, satisfaction with life, and suicide ideation in a clinical sample. Journal of Psychopathology & Behavioral Assessment, 26(2), 127–135.

Hirsch

J. K.

Duberstein

P. R.

Unutzer

(2009). Chronic medical problems and distressful thoughts of suicide in primary care patients: Mitigating role of happiness. International Journal of Geriatric Psychiatry, 24(7), 671–679.

Joiner

T. E.

(2005). Why people die by suicide. Cambridge, MA: Harvard University Press.

Koivumaa-Honkanen

Honkanen

Koskenvuo

Kaprio

(2003). Self-reported happiness in life and suicide in ensuing 20 years. Social Psychiatry & Psychiatric Epidemiology, 38(5), 244–248.

Kuznets

(1955). Economic growth and income inequality. American Economic Review, 45(1), 1–28.

10.

Lester

(1989). Suicide from a sociological perspective. Springfield, IL: Charles C. Thomas.

11.

Lester

(2002). National ratings of happiness, suicide, and homicide. Psychological Reports, 91(3), 758–758.

12.

Rogers

J. R.

Bromley

J. L.

Mcnally

C. J.

Lester

(2011). Content analysis of suicide notes as a test of the motivational component of the existential-constructivist model of suicide. Journal of Counseling & Development, 85(2), 182–188.

13.

Sha

Yip

P. S. F.

Law

Y. W.

(2017). Decomposing change in China’s suicide rate, 1990-2010: Ageing and urbanization. Injury Prevention, 23(1), 40–45.

14.

Shafik

(1994). Economic development and environmental quality: An econometric analysis. Oxford Economic Papers, 46(Supplement), 757–773.

15.

Shneidman

E. S.

(1987). A psychological approach to suicide. In VandenBos

G. R.

(Ed.), Cataclysms, crises, and catastrophes: Psychology in action. Master lectures series (pp. 147–183). Washington, DC: American Psychological Association.

16.

Soares

M. J.

Bos

Pereira

A. T.

Marques

Maia

Macedo

(2016). Clinical morbidity at pregnancy: The role of previous suicidal attempts and repetition. European Psychiatry, 33, S605–S605.

17.

United Nations Development Programme. (2010). Human development report 2010. The real wealth of nations: Pathways to human development, 20th anniversary edition. New York, NY: Palgrave Macmillan.

18.

Van Orden

K. A.

Witte

T. K.

Cukrowicz

K. C.

Braithwaite

S. R.

Selby

E. A.

Joiner

T. E.

(2010). The interpersonal theory of suicide. Psychological Review, 117(2), 575–600.

19.

Voracek

(2009). National intelligence, suicide rate, and subjective well-being. Perceptual & Motor Skills, 109(3), 718–720.

20.

Wang

C.-W.

Chan

C. L. W.

Yip

P. S. F.

(2014). Suicide rates in China from 2002 to 2011: An update. Social Psychiatry and Psychiatric Epidemiology, 49(6), 929–941.

21.

World Health Organization. (2016). World Health Statistics 2016: Monitoring health for the SDGs. Geneva, Switzerland: Author.

22.

World Health Organization. (2019). Suicide. Retrieved from https://www.who.int/en/news-room/fact-sheets/detail/suicide

23.

Värnik

Tooding

L. M.

Värnik

Kasearu

(2014). Suicide among older people in relation to their subjective and objective well-being in different European regions. European Journal of Ageing, 11(2), 131–140.

24.

Yao

Y. S.

Chang

W. W.

Jin

Y. L.

Chen

L. P.

Zhang

(2014). Life satisfaction, coping, self-esteem and suicide ideation in Chinese adolescents: A school-based study. Child Care Health & Development, 40(5), 747–752.

25.

You

Song

Qin

Zhou

(2014). Effects of life satisfaction and psychache on risk for suicidal behaviour: A cross-sectional study based on data from Chinese undergraduates. BMJ Open, 4(3), e004096.