Globalisation and suicide: An empirical investigation in 35 countries over the period 1980–2006

Globalisation and suicide: An empirical investigation in 35 countries over the period 1980–2006

Health & Place 17 (2011) 996–1003 Contents lists available at ScienceDirect Health & Place journal homepage: www.elsevier.com/locate/healthplace Gl...

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Health & Place 17 (2011) 996–1003

Contents lists available at ScienceDirect

Health & Place journal homepage: www.elsevier.com/locate/healthplace

Globalisation and suicide: An empirical investigation in 35 countries over the period 1980–2006 Allison Milner n, Rod McClure, Jing Sun, Diego De Leo Griffith University, Brisbane QLD 4011, Australia

a r t i c l e i n f o

a b s t r a c t

Article history: Received 22 October 2010 Received in revised form 14 March 2011 Accepted 14 March 2011 Available online 24 March 2011

Background: Globalisation is mediated through a variety of flows including persons, information and ideas, capital, and goods. The process is increasingly recognised as a potential mediator of changes in attitudes and habits around the globe. Aim: This research investigated the relationship between globalisation and suicide rates in 35 countries over the period 1980–2006. Methods: The association between a globalisation ‘‘index’’ and suicide rates was tested using a fixedeffects regression model. The model also tested the influence of eleven other socio-economic variables on male and female suicide rates. Results: Overall, high levels of the globalisation index were associated with higher male and female suicide rates; however, the significance of this association dropped when assessed alongside other social and economic variables. Conclusions: While the nature of these findings should be regarded as exploratory, this paper highlights the need for researchers to consider the influence of world-changing phenomena like globalisation on suicide, which might deeply upset the traditional structure of societies with mixed types of impact. Crown Copyright & 2011 Published by Elsevier Ltd. All rights reserved.

Keywords: Social change Economic change Suicide Globalisation

1. Introduction The idea that suicide is influenced by social factors was popularised by Durkheim, who argued that changes associated with modernisation were related to an increase in suicide within European nations (Durkheim, 1897). Following on from his work, researchers have identified a number of population-level correlates of suicide, including divorce, fertility rates, education, religion, migration, and location of residence (e.g., rural versus urban areas) (Stack, 2000a; Yip et al., 2000). Suicide rates have also been related to trends in national economies (Yang and Lester, 2001) and employment (e.g., female labour force participation, unemployment, and type of employment) (Andersen et al., 2010; Blakely et al., 2003; Stack, 2000b), as well as income and health care expenditures (Neumayer, 2003; Zimmerman, 2002). While changes consequent to modernisation (as described by Durkheim at the end of 19th century) have been absorbed, societies around the world are now witnessing new transformations due to a phenomenon known as ‘‘globalisation’’. Despite variations in how different theoretical paradigms conceptualise it (as described later), globalisation can be broadly described as

n

Corresponding author. Tel.: þ61 7 3735 3338; fax: þ 61 7 3735 3450. E-mail address: a.milner@griffith.edu.au (A. Milner).

‘‘the process of creating networks among actors at multi-continental distances, mediated through a variety of flows including people, information and ideas, and capital and goods’’ (Dreher et al., 2008, p. 43). Globalisation is manifested in greater economic and political links between countries, faster and more efficient means of travel, instant forms of communication, adoption of technologies such as the internet, and changes to the type and location of employment (Held et al., 1999). In addition to influencing economic, social, political, and cultural structures within countries, health researchers argue that global processes can be important, contextual determinants of health and mortality (Huynen et al., 2005; Kawachi and Wamala, 2006). These global processes are likely to operate at multiple levels of a society and produce both positive and negative outcomes for human wellbeing (see Huynen et al., 2005 for a wider examination of this topic). While there has been increasing interest in health-related outcomes of globalisation, only a small amount of research has speculated about its potential effects on suicide (Arnett, 2002; Chenhall and Senior, 2009; Gilchrist et al., 2007; Gunnell et al., 2009) or mental health (Bhavsar and Bhugra, 2008; Bhugra and Mastrogianni, 2004; Kelly, 2003; Nizamie and Desarkar, 2005). Some researchers have discussed globalisation in the context of recent turbulence in the global economic market, which is thought to have increased suicide rates in a number of countries

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A. Milner et al. / Health & Place 17 (2011) 996–1003

(Ahmad, 1999; Gunnell et al., 2009). Others have drawn attention to problems associated with disruptions in social relationships, cultural values, and identities (Arnett, 2002; Lam et al., 2004). Aside from these pathways, globalisation may heighten the possibility for suicide by increasing the availability of risk factors, such as alcohol and drugs (Chenhall and Senior, 2009). Thus far, all published articles on the possible effects of globalisation on suicide have not been validated in empirical research. A possible reason for the limited amount of research in this area could be constituted by the different conceptualisations and lack of measurement of globalisation. In recognition of this gap in research, we developed a globalisation ‘‘index’’, which was used to measure the relationship between globalisation and rates of suicide. In addition, we controlled the influences of a number of other possible social and economic factors.

2. Conceptualising globalisation There is a multitude of economic, sociological, and cultural perspectives on globalisation and when it actually ‘‘began’’. Hirst and Thompson (1999) conceptualise globalisation in terms of international trade relations between countries and argue that the process began over 150 years ago. Sociological approaches have tended to view globalisation as a multi-dimensional process that brings people and societies closer together. For example, Giddens (1990) defines globalisation as ‘‘the intensification of worldwide social relations which link distant localities in such a way that local happenings are shaped by events occurring many miles away and vice versa’’ (p. 21). Sociologists have been inclined to consider globalisation as a rather recent phenomenon; Guillen (2001) identifies the genesis of globalisation after World War II, concurrent with the ‘‘nuclear age’’, the end of Western European imperialisation, the dramatic increase in trade and foreign investments, and the rising influence of Asian countries in the international economic arena. Cultural perspectives characterise globalisation as a gradual transformation of symbolic forms, cultural practices, and lifestyle (Sklair, 1999). Within this approach, researchers have predicted that globalisation will either lead to increasing uniformity and homogenisation (Barber, 1996) or cultural hybridisation (Appundurai, 1990). Despite conceptual differences, there is general consensus that globalisation is multi-dimensional, and occurs at various levels in societies around the world. Most theoretical positions also acknowledge the possibility that globalisation has historical precedents, such as modernisation or earlier periods of industrial development (Held et al., 1999).

3. Measuring globalisation Globalisation ‘‘indices’’ have been developed to provide a proxy measure of the process over time and between countries (Andersen and Herbertsson, 2005; Dreher et al., 2008; Foreign Policy and A. T. Kearney, 2001; Lockwood and Redoano, 2005; Martens and Zywietz, 2006; Raab et al., 2008). The KOF index (Dreher et al., 2008) is one of the most commonly used globalisation measures in research on human wellbeing. Some of the outcome variables studied using the KOF index include ‘‘helping behaviours’’ (Koster, 2007; Koster, 2009), life satisfaction (Bjørnskov et al., 2008), and human wellbeing (using the Human Development Index) (Tsai, 2007). However, thus far, no research using globalisation indices has examined suicide mortality. Inspired by past research, the authors of this paper decided to develop a new measure of globalisation. One of the main reasons for this was that past indices have attempted to provide a

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measure of cultural globalisation using proxy variables such as the number of ‘‘IKEAs’’ and ‘‘McDonalds’’ in a country. However, these variables are more likely to describe an outcome of globalisation, rather than processes. Aside from this, these variables are unlikely to reflect actual cultural change; rather, they are more likely to provide information on the expansion of specific multinational corporations.

4. Methodology 4.1. Sample Two main criteria were used to select sample countries for this project. First, we examined the availability of suicide data on males and females among all countries that report information to the World Health Organization (WHO). We then selected those with data available for the social–ecological variables used in the study (see below). The final sample included 35 countries (see Table 1). The time period under study was 1980–2006. 4.2. Outcome variable Male and female age-standardised suicide rates were calculated using the WHO World Standard Population (Ahmad et al., 2001).

Table 1 Male and female age-standardised suicide rates and the globalisation index in 35 countries, 1980–2006, in alphabetical order. Country

Male Female suicide rate suicide rate Mean Mean

Globalisation index score Mean

Australia Austria Brazil Bulgaria Canada China Costa Rica Czech Republic Denmark El Salvador Estonia Finland France Greece Hong Kong Hungary Italy Japan Latvia Lithuania Mexico Norway New Zealand Poland Portugal Republic of Korea Russian Federation Slovenia Spain Sweden Switzerland Ukraine United Kingdom United States of America Uruguay Mean (n ¼35 countries) Difference 1980 and 2006 (n ¼35 countries)

18.4 33.9 5.4 22.4 20.4 13.9 9.6 28.8 30.5 13.3 47 39.8 29.2 5.5 16 56 11.4 18.2 52.5 64.1 4.7 19.3 18.9 23.6 12.4 19.7 59.6 45.5 10.9 22.7 31 42.7 11.7 18.9 18.7 26.2 þ 1.2

4.5 4.3 3.1 3.2 4.0 3.1 2.7 3.1 3.8 2.0 2.7 3.9 4.1 3.4 3.3 3.0 4.1 6.2 2.9 2.9 3.2 4.0 3.7 3.3 3.3 3.5 3.2 3.1 3.7 4.3 4.2 3.0 4.3 5.0 2.1 3.5 þ 4.1

5.1 12.3 1.7 8.9 5.6 17.4 1.7 8.6 15.5 5.5 13.3 10.9 10.7 1.7 11 19.1 4.2 12.7 12.5 13 0.9 6.9 5.8 4.5 4.2 8 12.1 13.2 3.6 9.5 12.6 9 4.3 4.7 4.4 8.3  2.2

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As in past research (Chang et al., 2009, Minoiu and Andre´s, 2008), log transformation (to base) was applied to suicide rates to reduce possible heteroskedasticity within country and time effects. The data were sourced from the detailed data files of the WHO Mortality Database (World Health Organization, 2009). 4.3. Methodological details of the index The index developed for this study sought to investigate the processes of globalisation, rather than its outcomes, and therefore used a different conceptual approach and variables compared to other globalisation indices. As mentioned previously, the index explicitly excluded a measurement of cultural globalisation. Further, although globalisation is likely to have historical precedents, the process was measured from the year 1980 onwards due to less availability of data before this time. A country’s total score on the globalisation index represented the average of the three ‘‘sub-indices’’. These sub-indices were developed based on the results of a principal components analysis, which found three main factors: economic globalisation (defined as a country’s integration into the world market economy), social movement and contact (the expanding scale of human interaction and information flows, as shown by the movement of people between countries), and social development (all processes occurring that display active engagement in globalisation, such as computer ownership, expenditures on information and technology, and telephone coverage in the countries). The choice of variables used in the index was driven by a conceptual model developed by Held et al., (2009) and past globalisation indices (e.g., Andersen and Herbertsson, 2005; Dreher et al., 2008; Foreign Policy and A. T. Kearney, 2001; Lockwood and Redoano, 2005; Martens and Zywietz, 2006; Raab et al., 2008). Variable choice was also influenced by the quality of completeness of data (the list of variables used in each sub-index can be seen in Appendix A). Following methods used in past globalisation indices (e.g., Dreher et al., 2008), the data were transformed according to the percentiles of the original distribution using the formula [(Vi–Vmin)/(Vmax– Vmin)n10, where V refers to each variable used in the calculation of the index], so as to be comparable between countries and over time. Variables were weighted using statistically optimal weights, as determined by a principal components analysis. The indices represented the averaged weighted variables. The sub-sample of countries used in this paper was drawn from a larger sample of 73 countries. A high score on the index (e.g., 6.2 in Japan) indicates a high level of globalisation. A low score (e.g., 2.0 in El Salvador) indicates a low level of globalisation. 4.4. Other independent variables Aside from the globalisation index discussed above, 11 other variables were implemented to control for existing sociological influences on suicide. Most of these have been used in past research (see the introduction section of this paper). Variables were selected only if they were available at the country-level and over time. The final list of variables included: divorce (as a proportion of the total population), fertility (the number of births per woman in the country), expenditure on health per capita (USD), expenditure on tertiary education (as a proportion of GDP per capita in USD), agricultural employment (as a proportion of the total employed workforce), rural population (as a proportion of the total population), international migrants (as a proportion of the total population), female labour force participation (as a proportion of the total employed workforce), unemployment (as a proportion of the total workforce), and religious book production (the number of titles published in the total population, including both first and

subsequent editions). We have long hesitated before accepting this variable as an indicator of religiosity. The influence of religious beliefs and practices is of paramount important in the social life of a given country (as well as changes within it); however, a credible measurement of religiosity should not necessarily rely on official religious affiliations data, because these seldom represent the intensity or support of the ‘‘communal’’ aspects of religiosity (Stack, 1983). Following past research (Fernquist, 2007; Fernquist and Cutright, 1998), we have preferred a more reliable index, the diffusion of religious books, accepting the limitations involved in this choice. The proportion of the population over 65 years was included as a control for the age-distribution of a population. GDP per capita (USD) was implemented as a proxy of individual income, as distinct from GDP, which provides an indication of the overall wealth in the country. Linear interpolation accounted for missing data, based on the assumption of a linear development of the variable (Twisk and de Vente, 2002). Independent variables were standardised to have a mean of ‘‘0’’ and a standard deviation of ‘‘1’’. The sources of data for independent variables can be seen in Appendix B. 4.5. Statistical approach A Least-Square Dummy Variable (LSDV) fixed-effects regression model was used to control for country-specific effects on suicide rates. This technique controls for country effects by treating them as fixed parameters to be estimated. The model therefore accounts for unobserved heterogeneity within each country cluster. Fixed-effects models have been used in a number of past studies of suicide using time-series cross-sectional data (Andre´s, 2005; Brainerd, 2001; Chen et al., 2009; Minoiu and Andre´s, 2008; Neumayer, 2003; Noh, 2009). The fixed-effects model was tested against a Generalised Least Squares (GLS) ‘‘random-effects’’ model, using the Hausman postestimation test. As in past research (e.g., Noh, 2009), five-year dummy variables were added to estimate the possible effects due to time and to account for secular trends in suicide rates. Robust standard errors were implemented to control for possible heteroskedasticity (Gutierrez and Drukker, 2007). The basic estimation model was logðSRti Þ ¼ b0 þ b1 Xti þ b2 Gti þ b3 ct þ b4 timei þ mti

ð1Þ

where SRti is the suicide rate for each country and year (calculated for males and females); Xti represents the vector of independent variables; Gti is the globalisation index for each country and year; ct is the country-specific effect; timei represents the five-year time effects; and mti is the residual term. b0, b1, b2, b3, and b4 are the coefficients to be estimated. All analyses were conducted using Stata version 10.

5. Results 5.1. Descriptive results Table 1 shows the mean rates of male and female suicide in the sample. The highest rate of suicide for males over the period 1980– 2006 was in Lithuania (64.1 per 100,000), while the lowest was in Mexico (4.7 per 100,000). The highest rate of suicide for females was in Hungary (19.1 per 100,000) and the lowest was again in Mexico (0.9 per 100,000) (World Health Organization, 2009). Table 1 also shows the mean for the globalisation index (expressed as raw scores, or the summed average of the subindices) over the period 1980–2006 in 35 countries. The countries with the highest scores of globalisation over the time period were Japan (6.2), the United States (5.0), Australia (4.5), Austria (4.3),

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the United Kingdom (4.3), and Sweden (4.3). Countries with the lowest score in the globalisation index were El Salvador (2.0), Uruguay (2.1), and Costa Rica (2.0). Table 2 shows basic descriptive information for the other independent variables used in the project. Variation within the independent variables can be seen in the minimum and maximum scores. Those with the greatest disparity between countries and over time were divorce (proportion in the population), unemployment (as a proportion of the total employed workforce), and international migrants (proportion in the population). Those most similar across countries and over time included female labour force participation

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(as a percentage of the employed workforce), the rural population (proportion in the population), and tertiary education spending (as a proportion of GDP per capita).

5.2. Globalisation, ecological risk and protective factors and suicide The Variance Inflation Factors (VIF) test was used to measure multi-collinearity among the variables in the regression model. Multi-collinearity did not appear to be a problem as none of the scores exceeded the value of 3, although it should be noted that

Table 2 Summary statistics of variables, 35 countries, 1980–2006.

Globalisation index Male suicide rate Female suicide rate Divorce (per 10,000 persons in the pop.) Rural population (% in the pop.) Unemployment (% employed pop.) Agricultural employ (% employed pop.) Female labour force (% employed pop.) International migrants (% pop.) Religion book production (% pop.) Fertility rate (per female in the pop.) Expenditure on health (per capita) Tertiary education (% GDP per capita) Population over 65 years (% pop.) GDP per capita

Mean

SD

Minimum

Maximum

3.5 26.2 8.3 12.63 29.10 5.58 11.94 41.19 1.83 0.04 1.81 1548.62 32.49 11.91 13,113.5

0.80 16.10 4.70 10.27 2.24 3.61 2.76 1.63 3.80 0.12 0.26 275.14 6.06 1.24 2231.07

2.1 4.7 0.90 0.002 25.65 0.596 7.82 38.33 0.001 0.008 1.47 1217.07 27.44 10.19 9843.77

6.2 64.1 19.10 26.31 33.02 12.57 16.66 43.67 11.50 0.37 2.30 1847.58 34.96 14.01 17,116.14

Note: SD refers to standard deviation.

Table 3 The globalisation index, social-ecological variables, and male and female suicide rates, 1980–2006. Male suicide Model 1a Std. coef. a Divorce (% pop) Rural population (% pop) Unemployment (% workforce) Employed in agriculture (% employed pop.) Females in the labour force (% employed pop.) International migrants (% pop.) Religious book production (% pop.) Fertility rate (per female in the pop.) Expend. on health (per capita) Expend. on tertiary edu. (GDP per capita) Pop. over 65 years (% pop) GDP per capita Globalisation index 1980–84 1985–89 1990–1994 1995–99 2000–2004 Constant R2 (within) R2 (overall) F(18.34) p value

0.02nn  0.10nn  0.03  0.03 0.05 0.00 2.94nnn 0.0742 0.0011 11.61 p o 0.001

Female suicide Model 2a Std. err.b

0.01 0.03 0.03 0.03 0.03 0.03 0.06

Std. coef.a

0.01nnn 0.18nnn 0.16nnn 0.10nnn 0.12nnn 0.03 1.53nnn 0.1068 0.0109 17.27 po 0.001

Notes: Coefficients country specific dummies not shown. a

‘‘Std. coef.’’ refers to the standardised coefficient term. ‘‘Std. err.’’ refers to the robust standard error of the standardised coefficient term. nnn Represents significance at a 99% level. nn Represents significance at a 95% level. n Represents significance at a 90% level. b

Male suicide Model 1b Std. err.b

0.00 0.03 0.03 0.03 0.03 0.03 0.07

Female suicide Model 2b

Std. coef. a

Std. err.b

Stand. coef. a

Std. err.b

 0.01 0.07 0.03n 0.03 0.26nnn 0.01 –0.01 –0.05 –0.09nn –0.02 0.06nnn –0.01n 0.01n –0.11 –0.03 –0.05 0.01 –0.04 2.15nnn 0.4170 0.3362 9.69 p o 0.001

0.02 0.14 0.01 0.02 0.07 0.01 0.01 0.05 0.04 0.02 0.02 0.01 0.01 0.13 0.11 0.09 0.09 0.05 0.27

–0.03 –0.20 0.06nn 0.04 0.17 0.01 –0.02n –0.05 –0.10 0.03 0.05nn –0.01 0.01 0.10 0.10 0.04 0.08 –0.02 0.90nn 0.3138 0.1805 2.64 p o0.001

0.03 0.20 0.02 0.02 0.14 0.01 0.01 0.07 0.06 0.03 0.02 0.01 0.01 0.15 0.13 0.12 0.10 0.07 0.40

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there is no agreed ‘‘gold standard’’ regarding critical VIF values (O’Brien, 2007). Table 3 shows the fixed-effects regression analyses for male (Models 1a and 1b) and female (Models 2a and 2b) suicide. All models controlled for time (through the use of five-year proxy variables) and country effects. Model 1a shows the association between globalisation and male suicide before adjusting for independent variables. As can be seen in the first column in Table 3, the globalisation index is associated with a rise in suicide rates (coefficient¼0.02, po0.05). Results from Model 1b (which includes the other independent variables) indicate that unemployment (coefficient¼0.03, p o0.10), the population over 65 years (coefficient¼0.06, p o0.001), and the female workforce (coefficient¼0.26, po0.001) were related to an increase in male suicide rates. Expenditure on health (coefficient¼  0.09, p o0.05) and GDP per capita (coefficient¼  0.01, p o0.10) were associated with a decrease in male suicide. Model 1b also shows that increasing globalisation, as measured by the ‘‘globalisation index’’, was related to a rise in male suicide rates; this relationship fell just outside the 95% significance level (coefficient¼0.01, p o0.10). However, it should be noted that the relationship between globalisation and suicide described in Model 1b continues to be significant at 95% when the use of robust standard errors is disengaged. Regardless of this, robust errors are retained in the analysis in order to provide a more reliable indication of the relationship. Results of the estimation of the fixed-effects analysis for females (Model 2a) shows that the globalisation index was significantly associated with an increase in female suicide rates (coefficient¼0.01, po0.001). As seen in Model 2b, the globalisation index had a positive, but non-significant, effect on female suicide after adjusting for the effect of other social and economic variables. Model 2b also shows that unemployment (coefficient¼0.06, po0.05), and the population over 65 years (coefficient¼0.05, po0.05) were associated with an increase in female suicide rates. Religious book production (coefficient¼  0.02, po0.10) was associated with a decrease in female rates. The finding that the globalisation index drops out of significance after adjustment indicates that the effect of globalisation may be influenced by the other social and economic factors included in the fixed-effects regression.

6. Discussion This study sought to investigate the possible association between a globalisation index and suicide mortality after controlling for country and time effects (through five-year dummy variables). The analysis also tested the relationship between social and economic variables and male and female suicide rates. Results suggest that an increase in unemployment and the elderly population were associated with a rise in suicide rates for both males and females. In contrast, health spending was associated with lower suicide rates. There were also some significant gender differences, as male suicide rates increased when associated with female labour force participation. These findings support Stack’s (1998) suggestion that men are more sensitive to labour market shifts than women. Per capita GDP was associated with a reduction in male suicide, endorsing the idea that economic variables are related to male wellbeing in a population (Leo, 2006; Neumayer, 2003). Results for females suggest that religious book production was associated with a decrease in suicide rates, which confirmed the protective effect of this variable found in past research (Fernquist, 2007; Fernquist and Cutright, 1998). However, the validity of the religious indicator variable is problematic, as it measures number of books produced, rather than

number of religious books sold. Another problem with this indicator is that it fails to provide information on the types of religious books published. The integrative measure of globalisation developed for this study explicitly sought to involve social, economic, and technological aspects of the process. This reflects the premise that globalisation may influence suicide through multiple and different pathways. Results of the fixed-effect analysis indicated that globalisation was associated with an increase in male and female suicide when assessed without the contribution of other independent variables. However, the significance of this association dropped after adjusting for social and economic factors. One inference arising from these results is that the independent variables account for some of the effect globalisation has on suicide. Variables such as employment, female-labour force participation, and income may therefore constitute some of the possible ‘‘pathways’’ through which globalisation could affect suicide rates. In high-income countries, there is already some evidence that recent labour market shifts toward the outsourcing of jobs and part-time and contract employment have adversely affected mental health and wellbeing (Burgard et al., 2009; D’Souza et al., 2003; Kim et al., 2008; Lewchuk et al., 2008). Global economic change, unemployment, and downturns in household income are also seen as factors associated with increasing male suicide rates in several Asian countries (Chang et al., 2009). Aside from economic adversities, researchers have discussed globalisation in the context of changing access to lethal suicide methods, demonstrated by the increased use of agricultural pesticides in rural suicides in India and China (Bose et al., 2009; Gunnell and Eddleston, 2003; Zhang et al., 2009). Technological globalisation, as seen in the growing reliance on the internet, is noted as contributing to increased knowledge about other lethal suicide methods, such as charcoal burning deaths in Hong Kong (Lee et al., 2005). Globalisation may also indirectly affect suicide by producing identity confusion and shifting value structures in society (Arnett, 2002; Berry, 2006; Tseng et al., 2001). This has been noted to be particularly relevant for migrant and minority groups, many of whom have to contend with greater cultural, social, and economic pressures (Berry, 2006). Aside from these issues, it is necessary to consider the role of globalisation in changing the quality of human relationships and communication styles. This especially refers to the movement from face-to-face to ‘‘virtual’’ interactions through the use of the internet and other technologies (DiMaggio et al., 2001). Global migratory patterns, rapid social change, and changing labour market conditions may also contribute to greater social isolation and create higher risk of suicide (Bhavsar and Bhugra, 2008; Patel and Kleinman, 2003). Kelly (2003) suggests that widespread social change driven by globalisation produces ‘‘anomie’’, a term which describes societal normlessness following a breakdown in social order (Thorlindsson and Bjarnason, 1998). As far back as the 1800s, researchers have argued that there is a link between anomic social and economic conditions and increasing suicide rates (Durkheim, 1897). More recently, anomie has been invoked to explain rising rates of suicide in countries of Asia undergoing rapid economic change (as noted in Zhang et al., 2010, p. 162). It is unlikely that it is simply one aspect of globalisation that influences the risk of suicide. Rather, it is more probable that suicide is subject to the combined effect of changes to the economy and labour market, transitory living circumstances, modes of communication, and shifts in cultural identity. It is also highly likely that the influence of globalisation on suicide differs across regions of the world due to variation in economic, political, social, and cultural backgrounds.

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7. Limitations

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Table A1 (continued )

We acknowledge that the index developed to measure globalisation has yet to be validated and was used for the first time in this study. Because of this, the index needs to be further tested in research studies using different samples, time periods, and methodologies. Another limitation is that the index did not weight countries’ scores by population; however, this is a criticism that could be true of many of the established indices. This study attempted to control for confounders by utilising a wide range of known social and contextual ecological factors associated with suicide. Despite this, it is possible that there are still unmeasured variables which may affect results, such as alcohol or measured mental illness in a given population. Further, despite the adoption of a model able to control for issues arising from using correlated data, it is likely that there is still measurement error due to time and country differences. Data quality and missing data affected both the sample size and the number of independent variables used in this study. The distal nature of independent variables was a further limitation, as selected proxies could only provide country-level accounts, and thereby ignored possible within-country variations. We also acknowledge potential issues in the reliability of suicide data, which may be influenced by death reporting practices and stigma around suicide within countries (Douglas, 1967; Pescosolido and Mendelsohn, 1986).

Sub-index

Variable

Social movement and contact Data sources: United Nations Data Retrieval System World Development Indicators

Imports of services, balance of payments (USD)

Social development Data source: World Development Indicators

Passenger cars (per 1000 people) Personal computers (per 100 people) Research and development expenditure (% of GDP) Information and Communication Technology expenditure (USD) Telephone mainlines (per 100 people) Official development assistance (ODA) and official aid

Exports of services, balance of payments (USD) International aviation, number of passenger flown (thousands) Daily newspapers: total average circulation per 1000 people) Internet users (per 100 people) Fixed-line and mobile phone subscribers (per 100 people) International tourism and expenditures (USD) International voice traffic (out and in, minutes) Workers’ remittances and compensation of employees (USD) Mobile phone subscribers (per 100 people)

International Monetary Fund (2009); International Telecommunication Union (2009); United Nations Educational Scientific and Cultural Organization (2009); United Nations Statistics Division (2009); World Bank (2009).

8. Conclusions Appendix B The globalisation index was related to increasing rates of male and female suicide, although these relationships decreased in significance when assessed alongside other potential social and economic variables. This may indicate that globalisation operates through variables already present at the country level, such as the labour market. Considering the far-reaching effects of globalisation on societies around the world, this study highlights the need for researchers to broaden current understandings of suicide prevention from individual or community-level perspectives to a global perspective. Consequently, increased awareness of the effects of global processes on employment, relationships, and living circumstances would be of importance. However, as this study provides only one perspective of globalisation, more investigations are needed before any definitive conclusions can be drawn about the effect of the process on suicide. Regardless, we feel that this study may fill an important gap in literature, as it is the first of its kind in suicide research.

Appendix A See Table A1. Table A1 Variables used in the calculation of the globalisation index. Sub-index

Variable

Economic globalisation Data sources: United Nations Data Retrieval System World Development Indicators International Monetary Fund

GDP, constant prices (USD) Total imports, millions (USD) Total exports, millions (USD) Net direct investment, balance of payments (USD) Net portfolio investment, balance of payments (USD) Foreign direct investment, net inflows (USD) High-technology exports (USD)

See Table B1.

Table B1 Sources of data for independent variables. Variable

Data source

Divorce (per 100,000 persons in the United Nations Gender Database population) Rural population (% in the population) United Nations Data Retrieval System and the World Development Indicators Unemployment (% of workforce) World Development Indicators Employment in agriculture International Labour Organization (% of workforce) (2009) Female workforce (% in the employed World Development Indicators population) International migrant population World Development Indicators (% in the population) Religious book production United Nations Educational Scientific (% in the population) and Cultural Organization Fertility rate (per female in the World Development Indicators population) Expenditure on health per capita World Development Indicators (constant USD) Tertiary education expenditure United Nations Data Retrieval System (proportion of GDP per capita and the World Development Indicators Proportion of the population over the WHO Statistical Information System age of 65 years (% in the population) GDP per capita (constant USD) World Development Indicators

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