Suicidal Behavior of Australian Males, From an Ethnicity Perspective

Abstract

Background

Suicide is the 10th leading cause of death among Australian males. Despite the cultural diversity in Australia, there is a significant research gap in knowledge of suicidal behavior among Australian males from ethnically and culturally diverse backgrounds. The study aimed to estimate the prevalence and risk of suicidal behaviors among Australian males based on ethnicity, with an emphasis on those from ethnic-minority backgrounds.

Methods

We used data from the first wave of the Australian Longitudinal Study on Male Health. Multiple logistic regression models were used to determine the risk of suicidal behavior (lifetime suicide attempt, lifetime suicidal ideation, recent suicidal ideation) by ethnicity.

Results

Among ethnic minority males, Pacific Islander males also had the highest prevalence of lifetime suicide attempts (12.2%), while Middle Eastern (2.3%) and South-/North-East Asian males (2.9%) had the lowest rates. South American males had the highest recent suicidal ideation (18.2%), followed by Pacific Islanders (14.2%). The highest prevalence of lifetime suicidal thoughts was reported among males of mixed ethnicity (23.0%), followed by South American (14.6%) and Pacific Islander (13.5%) males. Most ethnic-minority groups had a lower risk of lifetime suicidal ideation compared with Australian males. Evidence regarding differences in recent suicidal ideation and lifetime suicide attempts between ethnic-minority and Australian-background males was inconclusive.

Conclusion

Evidence was found of differences in suicidal behaviors among Australian males based on ethnicity. Future research should use inclusive methodologies to confirm these associations and explore the underlying factors contributing to higher rates of suicidal behavior in specific populations.

Keywords:

• Australia
• CALD
• ethnicity
• migrants
• suicidal behavior

INTRODUCTION

Suicide remains a public health concern worldwide, although the epidemiology and dynamics of suicide vary significantly across countries and across populations within countries. Culture plays a significant role in influencing suicide risk, acting as both a potential risk and protective factor, and can influence attitudes that affect how suicide is enacted and responded to. For example, cultures that deem suicide acceptable or honorable tend to exhibit higher suicide rates than cultures in which suicide is considered prohibited (Chu et al., 2018; Kuroki, 2018; Ratkowska & De Leo, 2013). With the phenomenon of ever-increasing global migration, critical questions are being asked about the risk of suicide experienced by migrant populations, particularly among ethnic minorities.

In multicultural settler countries in the Global North, there is mixed evidence about the risk of suicide and suicidal behavior experienced by ethnic minorities. While some studies reveal elevated numbers of suicide deaths and behaviors among ethnic minorities, such as Black African, Black Caribbean, and Pacific Islander (Forte et al., 2018), others show lower rates, such as males from South Asian backgrounds (Hunt et al., 2021). Two prominent theories offer insights into the varying rates of suicidal behavior among ethnic minorities. The first is the acculturation stress theory, which posits that individuals may experience psychological distress directly resulting from the process of acculturation. This distress can manifest as feelings of marginalization, alienation, psychosomatic symptoms, or identity confusion, all of which increase the risk of suicidal behavior among ethnic minorities (Haase et al., 2022; Hovey, 2000). In addition, their experiences of racism can hinder their successful integration into society (Liebkind & Jasinskaja‐Lahti, 2000).

Another theory is the “healthy migrant effect,” which is often used to explain the lower suicide rates observed among ethnic minorities, especially among first-generation migrants. The theory posits that certain selection factors, for example, their ability to make and act on the decision to migrate, reflect their resilient personalities (Elshahat et al., 2021). In most countries, migrants are required to undergo rigorous health assessments as a prerequisite for migration. Hence, at the time of migration, migrants typically possess better overall health compared to the general population. The combination of resilient personality traits and good physical health reduces their vulnerability to suicide, placing them at a significantly lower risk than the general population (Dhadda & Greene, 2018; Renzaho, 2016). However, it is important to note that the protectiveness of the healthy migrant effect tends to diminish over time, as migrants spend more years in host countries (Elshahat et al., 2021; Wu & Schimmele, 2005). In fact, there is evidence suggesting the deteriorating mental health of long-term migrants (those residing in the host country for more than 10 years) as this protective effect wanes.

Research has shown a range of risk and protective factors of suicide that are particularly important for ethnic-minority populations. Factors including family cohesion (Joel Wong et al., 2012) and religious affiliation (Al-Sharifi et al., 2015; Saunders et al., 2023) are associated with lower suicide risk, whereas racial discrimination (Baiden et al., 2022; Gaylord-Harden et al., 2023), unemployment (Hunt et al., 2021), social disconnection (Aran et al., 2023), and diagnosed mental illness (Al-Sharifi et al., 2015; Hunt et al., 2003; Joel Wong et al., 2012) are associated with a higher risk of suicidal behaviors. In Germany, male adolescents from migrant backgrounds reported a significantly higher lifetime prevalence of suicide attempts (4.7% vs. 3.1%) than native males (Donath et al., 2019). Among Black college students in the United States, experiences of racial discrimination were associated with suicidal thoughts. However, the same was not observed for other minority groups, including Latinx and Asian students (Polanco-Roman et al., 2022). Another study noted that among young Asian Americans, intergenerational cultural conflict and academic parental control are associated with an increased risk of suicidal behavior (Lee et al., 2023). On the other end of the age spectrum, among older adults (aged 60 years and older) from the United States, Latinx adults have higher odds of suicidal behavior and mental illness. In contrast, those from Asian backgrounds have higher odds of mild to severe depression symptoms compared to native white individuals (Jiménez et al., 2022).

Australia is one such settler society where this phenomenon can be examined, with large populations from various ethnicities. Each year, 65,000 Australians attempt suicide and more than 3,000 people die of suicide (Australian Bureau of Statistics [ABS], 2021a; Black Dog Institute, 2023). Suicide is the 10th leading cause of death among Australian males (ABS, 2021a). The National Suicide Prevention Strategy 2020–2023 in Australia (Department of Health and Human Services, 2020) has identified people from culturally diverse backgrounds as a priority group for suicide prevention. Considering the cultural diversity within Australia, where 48% of the population has a parent born overseas and 27% report a birthplace overseas, understanding suicide from ethnic and cultural perspectives is not just important but fundamental (ABS, 2021b). A recent study (Maheen & King, 2023) indicated that some migrant groups, such as those from Oceania and African countries, can be disproportionately affected by suicide mortality. However, similar evidence regarding nonfatal suicidal behavior is lacking.

We aimed to extend the existing literature using data from a large general population-based sample of Australian males that contain information on country of birth and parental country of birth. The study aimed to examine the prevalence of suicidal behaviors among Australian males, with an emphasis on males from ethnic-minority backgrounds, to investigate whether odds of suicidal behavior varied by ethnicity.

MATERIALS AND METHODS

Data Source

We used data from the first wave of the Australian Longitudinal Study on Male Health, also called the Ten to Men Study. The survey was administered in three waves (2013–2014, 2015–2016, and 2020–2021). In the first wave (2013–2014), Ten to Men collected health and lifestyle information from 16,021 males aged 10–55 nationwide through surveys and interviews. A random sampling technique that ensured a broad range of backgrounds, life experiences, and representation across all Australian states and territories was applied to select the study participants (Currier et al., 2016; Pirkis et al., 2017). In the subsequent waves, the number of participants dropped to 10,729 and 7,919, respectively, with a notable decline in participation among ethnic minorities by 66%. For this reason, we only used the first wave of the survey. The Ten to Men study received ethical clearance from the Human Ethics Sub-Committee of the University of Melbourne (HREC 1237897 and 1237376).

Study Variables and Measurements

Exposure variable: Our exposure variable is country of origin, which we used to define ethnic background. The Ten to Men survey uses the Standard Australian Classification of Countries (SACC) classification system to code countries of birth up to two digits. The ABS endorses SACC classification for collecting, aggregating, and disseminating data related to birthplace and has previously been used in studies measuring suicide outcomes in the Australian population.

To determine a person’s ethnic background, we considered both the individual’s birthplace (based on SACC two-digit geographic origin) and the birthplace of their parents. This is also consistent with one of the ABS definitions of ethnicity as a “common geographic origin” (ABS, 2019). For example, if the individual and their parents were born in a South-East Asian country, we classify their ethnic background as South-East Asian. Similarly, if the individual was born in Australia but both parents originated from a South-East Asian country, we designate their ethnic origin as South-East Asian. In cases where an individual was born in Australia and their parents were from two different geographic regions, we categorize them as having a mixed ethnicity. Including parents’ and the individual’s birthplace is a practical approach for assigning ethnic origin when the question about ethnicity or culture was not asked. We employed SACC codes to create 12 specific ethnic group categories for the study’s purposes. Appendix 1 shows the categories used to create ethnic groups.

Outcome variables: The primary outcome variables of interest were lifetime suicidal ideation, lifetime suicidal attempt, and recent suicide ideation. The questions that were used to measure these outcomes were as follows:

1. Lifetime suicide thoughts: Have you seriously thought about killing yourself (ever in your life)?

2. Lifetime suicide attempts: Have you seriously considered attempting suicide ever in your life?

3. Recent suicide ideation: Over the past 2 weeks, how often have you been bothered by any of the following problems? (Item 9, Thoughts that you would be better off dead, or of hurting yourself).

Covariates: Time-variant covariates considered in this study were age group (15–24, 25–34, 35–44, 45–54, 55–64, or 65 and older), marital status (single, married, or divorced/widowed/separated), highest educational qualification (year 12 and below, certificate/diploma, bachelor degree, postgraduate, or others), annual household income (<$40,000, $40,000 to $79,999, or $80,000 and above), employment status (employed, unemployed, not in the labor force), remoteness of residence (major cities, inner regional, or outer regional), and born overseas (yes or no).

Data analysis

We used Stata 17 for data analysis (StataCorp, 2021). We accounted for the complex multistage sampling design and unequal probability of selection in determining the weighted prevalence of suicidal behavior outcomes using a sampling weights (Spittal et al., 2016). We assessed the cross-sectional association between country of birth and lifetime suicidal ideation and attempt using multiple logistic regression models. We presented prevalence and odds ratios (ORs) with 95% confidence intervals (CIs). We considered the effect size, confidence interval, and p value <0.05 to draw meaningful and reliable conclusions (Vittinghoff et al., 2006).

RESULTS

Characteristics of Study Participants

The analysis included 11,603 males. This included 55.3% Australian background, 14.1% mixed ethnic backgrounds, and 30.6% other ethnic backgrounds. Among the sample, 67% were married, 86% reported being employed, and 59% had an annual household income of more than $80,000. The average age of study participants was 39.1 ± 10.1, with 31% older than 45 years and 13% younger than 24 years (see Table 1). Appendix 2 provides the demographic characteristics of the analytical sample by ethnic background.

TABLE 1. Demographic characteristics of the sample (n = 11,603).

Participant characteristics	Percentage, 95% confidence interval
Age (years)
15–24	13.5 (12.6–14.4)
25–34	26.5 (25.4–27.6)
35–44	28.9 (27.9–30)
45–57	31.1 (30.1–32.2)
Highest education qualification
Year 12 and below	24.6 (23.6–25.7)
Certificate or diploma	44.9 (43.7–46.1)
Bachelor degree	18 (17.1–19)
Postgraduate	10.7 (9.9–11.5)
Others	1.8 (1.5–2.1)
Marital status
Single/never married	26.9 (25.8–28)
Divorced/separated/widowed	6.6 (6.1–7.2)
Married	66.5 (65.4–67.7)
Household income (annual Australian dollars)
Less than $40,000	12.6 (11.8–13.5)
$40,000 to $79,999	28.1 (27.1–29.2)
$80,000 and above	59.3 (58.1–60.4)
Employment status
Employed	86.3 (85.4–87.1)
Unemployed	8.0 (7.3–8.7)
Not in the labor force	5.7 (5.2–6.3)
Remoteness
Major cities	58.3 (57.1–59.4)
Inner regional	22.6 (21.7–23.5)
Outer regional	19.2 (18.2–20.2)
Country of origin
Australia	55.3 (54.1–56.5)
New Zealand	3.2 (2.8–3.7)
Pacific Islands	0.5 (0.3–0.7)
UK and Ireland	6.8 (6.2–7.4)
Western Europe	1.5 (1.3–1.8)
Southern and South-Eastern Europe	4.1 (3.6–4.6)
Southern and East Africa	1.6 (1.4–2)
Middle East	1.2 (1–1.5)
South and North East Asia	5.6 (5–6.2)
Southern Asia	5.0 (4.4–5.6)
North America	0.6 (0.5–0.9)
South America	0.5 (0.3–0.7)
Mixed	14.1 (13.3–15)
Overseas born
Yes	24.0 (23.0–25.0)
No	76.0 (75.0%–77.0%)

Prevalence of Suicidal Thoughts and Attempts

Table 2 displays the weighted prevalence of suicidal behaviors by ethnic background. Participants with mixed ethnic backgrounds had the highest percentage of lifetime suicidal thoughts at 23.0%, followed by Australians (22.2%). Migrants from New Zealand, the United Kingdom and Ireland, and Western European regions demonstrated a prevalence of lifetime suicide thoughts similar to their Australian counterparts. Among ethnic minorities, those from the Pacific Islander background (13.5%) and South American background (14.6%) reported a higher percentage of lifetime suicidal thoughts.

TABLE 2. Weighted prevalence, 95% confidence interval.

Countries of origin	Lifetime suicide ideation	Lifetime suicide attempt	Recent suicide ideation (PHQ), last 2 weeks
Australia	22.2 (20.9,23.5)	5.5 (4.8–6.3)	9.4 (8.6–10.4)
New Zealand	20.8 (15.7–27.0)	4.5 (2.6–7.9)	7.8 (5.1–11.7)
Pacific Islands	13.5 (5.0–31.4)	12.2 (4.2–30.7)	14.2 (5.8–30.3)
UK and Ireland	20.6 (16.9–24.8)	5.9 (4.2–8.5)	8.9 (6.3–12.3)
Western Europe	19.3 (12.7–28.2)	4.5 (1.6–11.7)	11.9 (6.4–21.1)
Southern and South-Eastern Europe	11.6 (8.7–15.4)	4.3 (2.5–7.3)	8.3 (5.7–12.1)
Southern and East Africa	12.4 (7.6–19.6)	6.0 (2.6–13.2)	10.3 (5.7–17.9)
Middle East	7.4 (3.5–15.0)	2.3 (0.83–6.2)	9.5 (4.9–17.6)
South and North East Asia	11.1 (7.7–15.6)	2.9 (1.4–6.3)	9.4 (6.5–13.3)
Southern Asia	6.8 (4.3–10.3)	6.2 (3.9–9.8)	7.6 (4.9–11.6)
North America	17.7 (9.3–31.1)	8.6 (3.1–22.36)	4.6 (1.6–12.3)
South America	14.6 (6.5–29.8)	5.5 (1.3–21.4)	18.2 (6.8–40.2)
Mixed	23.0 (20.5–25.8)	6.3 (4.9–8.0)	10.7 (8.8–12.8)

PHQ = Patient Health Questionnaire (PHQ).

The highest percentage of lifetime suicide attempts was found in males from the Pacific Islands (12.2%). Among other ethnic-minority groups, males from African (6.0%) and South Asian (6.2%) backgrounds were also noted to have a higher prevalence of lifetime suicide attempts, whereas those from Middle Eastern (2.3%) and South- and North-East Asian (2.9%) backgrounds had the lowest percentages of lifetime suicidal attempts.

The prevalence of recent suicidal ideation was more common in ethnic minorities, with South American males (18.2%) having the highest prevalence, followed by males from the Pacific Islander (14.2%) and African backgrounds (10.3%). Among other groups, those from Western European backgrounds (11.9%) were also reported to have a higher prevalence of recent suicide ideation.

ASSOCIATION BETWEEN SUICIDAL BEHAVIOR AND COUNTRY OF ORIGIN

In Table 3, the odds ratios for males from various ethnic backgrounds regarding lifetime suicidal ideation, recent suicide ideation, and lifetime suicidal attempts are presented. The model was adjusted for covariates, and Australian background was used as the reference group. Results indicate that many ethnic-minority groups had significantly lower odds of reporting lifetime suicidal thoughts, such as males from South and Eastern European (OR, 0.5; 95% CI, 0.35–0.71), Middle Eastern (OR, 0.27; 95% CI, 0.12–0.63), South- and North-East Asian (OR, 0.48; 95% CI, 0.27–0.86), and Southern Asian (OR, 0.32; 95% CI, 0.17–0.59) backgrounds.

TABLE 3. Risk of suicide behaviors by ethnic backgrounds (logistic regression).

Countries of origin	Lifetime suicide ideation	Lifetime suicide attempt	Recent suicide ideation (PHQ), last 2 weeks
Australia	1.00	1.00	1.00
New Zealand	1.19 (0.72–1.96)	0.91 (0.4–2.2)	0.82 (0.43–1.57)
Pacific Islands	0.68 (0.22–2.16)	2.89 (0.8–11.0)	1.78 (0.61–5.21)
UK and Ireland	1.13 (0.77–1.66)	1.14 (0.6–2.1)	0.88 (0.53–1.47)
Western Europe	1.04 (0.59–1.81)	1.04 (0.4–3.0)	1.27 (0.63–2.56)
Southern and South-Eastern Europe	0.50 (0.35–0.71)	0.83 (0.4–1.5)	0.77 (0.48–1.23)
Southern and East Africa	0.61 (0.31–1.18)	1.11 (0.3–3.6)	1.02 (0.45–2.33)
Middle East	0.27 (0.12–0.63)	0.32 (0.1–1.0)	0.83 (0.37–1.84)
South and North East Asia	0.48 (0.27–0.86)	0.53 (0.2–1.3)	0.91 (0.52–1.61)
Southern Asia	0.32 (0.17–0.59)	1.43 (0.6–3.3)	0.82 (0.43–1.56)
North America	1.12 (0.49–2.53)	2.92 (0.8–10.4)	0.53 (0.16–1.78)
South America	0.86 (0.33–2.26)	1.73 (0.3–10.1)	2.94 (0.82–10.5)
Mixed	1.02 (0.85–1.22)	1.14 (0.8–1.6)	1.16 (0.92–1.47)

PHQ = Patient Health Questionnaire (PHQ).

*Model adjusted for age, educatoin, marital status, household income, employment status, remoteness, born overseas.

While no ethnic groups demonstrated statistically significantly different odds of lifetime suicide attempts, there was some indication that this may be a problem for males from the Pacific Islander (OR, 2.89; 95% CI, 0.76–11.0) and North American (OR, 2.92; 95% CI, 0.83–10.4) backgrounds.

Across all ethnic groups, there was insufficient evidence to reject the null hypothesis that the odds of recent suicide ideation among males from different ethnic backgrounds were similar to those from an Australian background. While this finding was not statistically significant, those from Pacific Islander (OR, 1.78; 95% CI, 0.61–5.21) and South American (OR, 2.94; 95% CI, 0.82–10.5) backgrounds tended more strongly toward having higher odds of recent suicidal ideation. A more inclusive sample of the diverse Australian population is needed to confirm these associations.

DISCUSSION

Our study examines suicidal thoughts and attempts among Australian males according to their ethnic backgrounds. We found that compared to Australians, males from ethnic-minority backgrounds reported having a lower risk of suicidal behaviors. The prevalence of suicidal behaviors, however, varies across different groups, and the highest prevalence of recent suicide ideation and lifetime suicide attempt was reported by males with South American and Pacific Islander backgrounds, respectively. Males from South Asian, North American, UK and Ireland, and mixed ethnic backgrounds have been reported to have some elevated parameters of lifetime suicide behaviors, but a more inclusive sample is needed to confirm these associations. Our findings emphasize the need for further investigation into how ethnicity and migrant generation intersect to affect suicidal behaviors in ethnic minority males and identify risk and protective factors contributing to suicidal behavior within diverse populations.

Our study identifies certain minority groups, including those from the Pacific Islands and South America, as emerging populations at risk for suicidal behaviors because of their elevated rates of either recent suicide ideation or lifetime suicide attempts. Some of the countries in these regions have been noted as having a higher risk of hospital presentation of self-harm (Pham et al., 2023) and suicide mortality (Maheen & King, 2023) in recent Australian studies. Indigenous status, for example, is a significant predictor of suicidal behavior in South America (Azuero et al., 2017; Graafsma et al., 2006) and Pacific Island countries (De Leo et al., 2009). While it is not possible to conclude that in Australia, males from South American backgrounds are at higher risk for suicidal behaviors given its elevated parameters, future research is warranted to better understand suicidality within this group.

Similar to our study, another Australian study investigating suicide mortality among migrant groups has identified male migrants from Pacific countries to be a high-risk group for suicide deaths (Maheen & King, 2023). Not only do they exhibit higher suicide rates compared to other ethnic-minority groups, but they have also exhibited no change in suicide rates over a 13-year period (2006–2019; Maheen & King, 2023). It is possible that the suicidal behaviors noted in this study may be associated with cultural backgrounds or countries of origin, given that Pacific Island countries have one of the highest rates of self-harm and suicide globally (De Leo et al., 2009). The cultural expression of suicide in this region, often characterized by impulsivity and driven by anger, contrasts with Western views, where suicide is typically associated with depression (Mathieu et al., 2021). While our study does not delve into the specific circumstances or reasons behind participants’ suicidal behaviors or help-seeking behaviors, further research is warranted to identify the stressors leading to suicidal behaviors and coping mechanisms in this group. This includes understanding the cultural significance of these stressors; exploring their impact on suicidal behaviors, including psychological pain thresholds; and examining help-seeking behaviors.

The finding that ethnic-minority groups have a lower lifetime suicide risk is consistent with existing studies in which migrants demonstrated lower suicide risk. Considering that 24% of our study population are first-generation migrants, the observed lower rate can be attributed to the “healthy migrant effect” (Kõlves & De Leo, 2015). This effect suggests that recent migrants, particularly those arriving through skilled migrant programs, come with higher education levels, advanced English proficiency, married, and high employability and may exhibit protective factors (such as employability or resilient personalities) against suicidal behavior. This trend was evident in our sample, with 80% of the participants being employed and 75% being married, both of which are associated with a decreased risk of suicidal behavior. However, patterns can change quickly across generations of migrant families, and presumptions of lifetime lower suicide risk among certain ethnic-minority groups could well be misguided. Further research with more inclusive data is needed to confirm these associations and understand future patterns.

It is possible that suicidal ideation in our study is underreported, as has been observed in other studies, wherein the cultural stigma surrounding suicide is associated with hidden suicide ideation. The stigma associated with suicide in certain cultural backgrounds can deter individuals from disclosing their suicidal thoughts, even if they are experiencing them (Akouri-Shan et al., 2022; Money & Batterham, 2021; Özen‐Dursun et al., 2023). Chu et al. (2018) noted hidden suicidal ideation as more of a concern for ethnic minorities (Chu et al., 2018). Hidden suicide ideation is strongly associated with greater severity of suicidal distress than disclosed suicide ideation (Chu et al., 2018). The authors further argue that if left unaddressed, hidden ideation could result in the underdetection of suicide risk and subsequent mismanagement.

In the context of general population surveys similar to the one used in our study, there is a need to adapt culturally appropriate tools for assessing suicide risk. One such example is the Cultural Assessment Risk for Suicide (CARS) tool (Chu et al., 2013), a validated instrument sensitive to determining suicide risk in ethnic minorities and the general population. Future research should focus on the viability of similar validated instruments in the Australian context to assess suicidal behavior across diverse populations. Such instruments will be valuable for identifying the underlying causes of distress that contribute to suicidal behaviors within minority groups, such as acculturation stress, minority stress, and cultural sanctions. Understanding these factors is crucial, especially for men, who are at a heightened risk for fatal outcomes of their initial suicide attempts. These instruments should also be inclusive of a wide range of risk factors associated with suicidal behavior in diverse populations and should consider language and content differences to account for the cultural variations in how suicide or suicidal behaviours are percieved, expressed, or experienced by individuals from diverse backgrounds (Chu et al., 2013). Including such tools in general population surveys would enhance the detection of suicidal behavior by ethnicity and enable suicide-prevention initiatives to better address the specific needs of diverse communities.

STRENGTHS AND LIMITATIONS

A key strength of our study is that it is based on a large general population survey including people from outside Australia. Our findings are based on a cross-sectional survey; hence, it may not account for individuals’ changing circumstances over time and whether they may have affected their suicidal behaviors. Furthermore, the survey was administered to males younger than 55 years; hence, suicidal behaviors among males aged 55 years and older are not captured in this study. The survey attrition rate for ethnic minorities was substantial from waves 1 through 3, so restricting it to wave 1 was necessary. We acknowledge that our study may have overlooked certain groups at high risk for suicidal behaviors, such as ethnic-minority males with limited English language proficiency or those with insecure visa statuses (e.g., temporary residents or asylum-seekers), due to survey selection criteria for participants (Currier et al., 2016). We recognize that these groups may be disproportionately affected by self-harm and suicidal behaviors and are not represented in our study sample.

In addition, using an individual’s country of birth and their parents’ country of birth to determine ethnicity may not be as accurate as self-reported ethnicity data, and it may lead to individuals being assigned to groups they do not self-identify with. In the absence of such data, this was the best way to determine ethnic backgrounds, and this approach is also consistent with ABS standards. Having said that, there may be a misclassification for some Australians (third-generation and beyond) who may have identified with a different ethnicity. While this could be considered a classification error, their suicidal behaviors are likely more aligned with Australian culture than with their ethnic backgrounds; as noted in the literature, this should not affect our results substantially. We stress the importance of collecting self-reported ethnicity data to minimize these errors in population-level surveys.

CONCLUSION

This is the first Australian study investigating suicidal behavior by detailed ethnic groups using a national-level sample. The study underscores the importance of using an intersectionality lens to understand male suicide in Australia, particularly from ethnic and cultural perspectives. It also underscores the importance of inclusive research designs to better grasp the underlying factors contributing to higher rates of suicidal behavior in specific populations. This understanding can inform prevention efforts and strategies to reduce suicide rates in vulnerable communities.

AUTHOR STATEMENT

HM, TH, and GA conceptualized the research question and study design. TH and HM undertook the statistical analyses. HM wrote the first draft of the paper, whereas GA revised the manuscript and contributed toward the final draft. All authors contributed toward the revised manuscript. All authors approved the submitted version of the article.

ACKNOWLEDGEMENTS

The research on which this paper is based was conducted as part of the Australian Longitudinal Study on Male Health (Ten to Men) by the University of Melbourne. We are grateful to the Australian Government Department of Health for funding and to the boys and men who provided the data. Ten to Men is managed by the Australian Institute of Family Studies. Ten to Men research data are the intellectual property of the Commonwealth."

DISCLOSURE STATEMENT

The authors declare no conflicts of interest or competing interests with this article.

AVAILABILITY OF DATA

The data (Ten to Men: The Australian Longitudinal Study for Male Health) that support the findings of this study are available from the Australian Institute of Family Studies via a request and review process. Information on data access, wave 1 surveys, data books, and the data user’s manual are available at https://aifs.gov.au/research_programs/ten-men.

Additional information

Funding

HM is a recipient of a postdoctoral fellowship funded by Suicide Prevention Australia. GA is funded by a National Health and Medical Research Council Investigator Grant (GNT2016501).

Notes on contributors

Humaira Maheen

Humaira Maheen, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.

Tilahun Haregu

Tilahun Haregu and Gregory Armstrong, Nossal Institute of Global Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.

Gregory Armstrong

Tilahun Haregu and Gregory Armstrong, Nossal Institute of Global Health, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.

APPENDIX 1:

COUNTRIES OR BIRTH ORIGIN, CATEGORIES USED IN THE STUDY

Table

SACC^a 2-digit code as reported in the Ten to Men survey	Country of birth—geographical region
11 Australia	Australia
12 New Zealand	New Zealand
15 Polynesia (excludes Hawaii)	Pacific Islands
21 United Kingdom, Channel Islands, Isle of Man 22 Ireland	UK and Ireland
23 Western Europe	Western Europe
31 Southern Europe 32 South Eastern Europe	Southern and South-Eastern Europe
42 Middle East	Middle East
51 Mainland South-East Asia 52 Maritime South-East Asia 61 Chinese Asia (includes Mongolia)	South and North East Asia
71 Southern Asia	Southern Asia
81 North America	North America
82 South America	South America
92 Southern and East Africa	Southern and East Africa

^a Standard Australian Classification of Countries.

APPENDIX 2:

ANALYTICAL SAMPLE CHARACTERISTICS BY ETHNIC BACKGROUNDS

Table

Demographics	Australia			Pacific Islanders			Africans			Middle East			Mixed
Age (years)	%	%		%	95% CI					%	95% CI		%	95% CI
15–24	15.3	14.1	16.5	3.7	0.8	14.9	11.2	6.5	18.8	14.0	8.2	22.8	18.4	15.6	21.6
25–34	25.6	24.2	27.1	22.0	10.5	40.4	21.4	15.4	29.0	23.5	15.6	33.8	29.0	26.0	32.1
35–44	27.2	25.9	28.5	45.2	30.1	61.1	32.1	24.0	41.4	38.7	27.8	50.8	28.8	26.2	31.6
45–57	31.9	30.5	33.3	29.1	17.7	44.1	35.2	27.3	44.0	23.8	16.3	33.4	23.8	21.3	26.5
Highest educational qualification
Year 12 and below	26.6	25.2	28.0	33.4	19.4	51.2	14.8	9.6	22.1	31.8	22.3	43.1	27.0	24.0	30.3
Certificate or diploma	50.2	48.6	51.7	48.3	32.7	64.3	35.7	27.6	44.8	19.8	13.4	28.3	45.0	41.7	48.3
Bachelor degree	14.3	13.2	15.5	12.4	5.2	26.7	26.7	19.7	35.2	21.8	13.9	32.5	17.0	14.7	19.5
Postgraduate	7.2	6.4	8.1	5.8	2.2	14.3	21.1	13.9	30.8	25.7	16.0	38.7	8.0	6.5	9.9
Others	1.7	1.4	2.2	–	–	–	1.6	0.6	4.5	0.8	0.2	3.8	3.0	2.1	4.3
Marital status
Single/never married	29.0	27.6	30.6	6.2	2.2	16.0	19.2	12.5	28.4	21.4	13.6	32.1	32.7	29.5	36.0
Divorced/separated/widowed	6.7	6.0	7.5	6.3	2.5	15.2	6.8	3.4	13.3	4.7	1.9	11.4	6.0	4.8	7.4
Married	64.2	62.7	65.7	87.5	76.4	93.7	74.0	64.6	81.6	73.9	63.0	82.4	61.4	58.1	64.6
Household income
Less than $40,000	12.5	11.5	13.6	8.4	3.1	21.1	13.1	7.4	21.9	22.3	14.9	32.0	12.6	10.6	14.9
$40,000 to $79,999	28.1	26.7	29.5	41.4	26.4	58.1	21.5	15.6	28.9	32.7	22.5	44.8	27.7	24.9	30.6
$80,000 and above	59.4	57.9	61.0	50.2	34.6	65.8	65.5	56.5	73.5	45.0	34.3	56.2	59.7	56.5	62.8
Employment status
Employed	87.0	85.9	88.1	93.0	78.6	98.0	81.7	72.4	88.4	73.9	61.9	83.1	84.9	82.1	87.4
Unemploy	7.5	6.7	8.5	5.8	1.4	21.2	9.0	5.2	15.2	18.7	10.5	31.3	7.2	5.8	9.0
NILF	5.4	4.8	6.2	1.3	0.2	8.9	9.3	4.3	19.1	7.4	3.9	13.7	7.9	5.9	10.5
Remoteness
Major Cities	46.7	45.2	48.3	91.5	82.3	96.2	73.9	65.9	80.5	89.9	82.4	94.5	60.7	57.5	63.9
Inner Regional	29.2	27.9	30.6	6.1	2.4	14.7	15.0	10.0	21.9	8.3	4.1	15.8	20.3	18.0	22.8
Outer Regioal	24.1	22.8	25.5	2.3	0.5	9.8	11.1	7.0	17.2	1.8	0.7	4.9	19.0	16.4	22.0
Born overseas
Yes	99.8	99.6	99.9	8.7	3.6	19.8	8.9	4.7	16.0	25.9	17.3	36.9	98.4	97.3	99.1
No	0.2	0.1	0.4	91.3	80.2	96.4	91.1	84.1	95.3	74.1	63.1	82.7	1.6	0.9	2.7
Demographics	New Zealand			South Asia			South and Northeast Asia			Southern and Eastern Europe			UK and Ireland
Age (years)	%	95% CI		%	95% CI		%	95% CI		%	95% CI		%	95% CI
15–24	10.0	6.2	15.9	5.1	3.2	8.1	14.3	10.5	19.2	3.0	1.6	5.5	5.9	3.9	8.8
25–34	25.3	19.7	31.9	46.4	40.7	52.2	37.9	32.3	43.9	14.8	10.5	20.3	16.6	13.3	20.4
35–44	33.6	27.5	40.3	35.7	30.3	41.4	29.4	24.8	34.5	30.7	25.6	36.3	28.9	24.9	33.2
45–57	31.1	25.5	37.4	12.8	9.5	17.0	18.3	14.9	22.3	51.5	45.5	57.4	48.7	44.2	53.2
Highest educational qualification
Year 12 and below	30.2	24.2	36.8	8.1	5.6	11.7	22.0	17.4	27.4	26.0	21.1	31.7	20.1	16.9	23.8
Certificate or diploma	46.3	39.4	53.2	20.0	15.7	25.2	21.7	17.2	27.0	42.3	36.5	48.3	49.8	45.2	54.4
Bachelor degree	18.1	12.4	25.7	35.5	30.1	41.4	39.0	33.5	44.7	16.5	12.7	21.2	17.6	14.4	21.4
Postgraduate	3.7	2.0	7.1	35.4	29.8	41.3	16.8	13.1	21.3	12.0	8.0	17.5	11.1	8.6	14.1
Others	1.7	0.7	4.3	1.0	0.3	2.8	0.5	0.2	1.4	3.3	1.3	7.7	1.4	0.8	2.4
Marital status
Single/Never married	24.8	18.7	32.1	15.8	12.0	20.6	32.5	27.2	38.2	15.0	11.4	19.6	16.2	12.7	20.3
Divorced/separated/widowed	6.6	4.1	10.5	2.7	1.3	5.6	3.3	2.1	5.3	10.5	7.3	14.9	10.2	7.5	13.6
Married	68.6	61.4	75.0	81.4	76.4	85.6	64.2	58.5	69.6	74.4	69.0	79.2	73.7	69.1	77.8
Household income
Less than $40,000	8.1	5.3	12.2	17.7	13.9	22.4	17.6	13.9	22.2	7.8	5.4	11.2	11.3	8.2	15.2
$40,000 to $79,999	30.1	24.5	36.4	39.0	33.4	44.9	29.9	24.8	35.5	31.0	25.6	37.0	19.5	16.2	23.3
$80,000 and above	61.8	55.2	68.0	43.3	37.7	49.0	52.5	46.8	58.1	61.2	55.2	66.9	69.2	64.7	73.4
Employment status
Employed	90.0	85.0	93.4	89.6	85.5	92.7	80.8	76.0	84.9	87.5	83.1	90.8	84.3	80.2	87.7
Unemploy	5.4	3.0	9.8	8.2	5.6	12.0	12.2	8.8	16.6	8.0	5.4	11.9	9.4	6.7	12.9
NILF	4.6	2.5	8.3	2.1	0.9	5.0	7.0	4.8	10.0	4.5	2.7	7.4	6.3	4.2	9.4
Remoteness
Major Cities	66.4	59.9	72.4	86.0	81.5	89.6	85.5	81.1	89.0	82.1	77.1	86.2	71.1	67.1	74.8
Inner Regional	15.8	11.9	20.7	6.8	4.6	10.1	5.2	3.4	7.8	9.4	6.6	13.3	17.5	14.4	21.0
Outer Regioal	17.8	13.1	23.6	7.2	4.5	11.1	9.3	6.4	13.4	8.5	5.6	12.7	11.4	9.1	14.1
Born overseas
Yes	7.1	4.0	12.4	2.2	1.2	4.1	18.1	13.6	23.7	66.9	60.8	72.4	24.3	20.5	28.5
No	92.9	87.6	96.0	97.8	95.9	98.8	81.9	76.3	86.4	33.1	27.6	39.2	75.7	71.5	79.5
Demographics	Western Europe			South America
Age (years)	%	95% CI		%	95% CI
15–24	4.9	4.9	2.4	3.7	0.8	14.9
25–34	13.6	13.6	8.0	22.0	10.5	40.4
35–44	30.1	30.1	22.8	45.2	30.1	61.1
45–57	51.4	51.4	42.3	29.1	17.7	44.1
Highest educational qualification
Year 12 and below	10.0	10.0	6.2	33.4	19.4	51.2
Certificate or diploma	42.8	42.8	33.8	48.3	32.7	64.3
Bachelor degree	16.9	16.9	10.7	12.4	5.2	26.7
Postgraduate	30.1	30.1	21.6	5.8	2.2	14.3
Others	0.3	0.3	0.0	33.4	19.4	51.2
Marital status
Single/never married	18.4	18.4	12.1	14.9	6.3	31.2
Divorced/separated/widowed	6.8	6.8	4.0	5.1	1.9	13.1
Married	74.8	74.8	66.1	80.0	64.0	90.0
Household income
Less than $40,000	10.7	10.7	6.0	2.7	0.5	13.4
$40,000 to $79,999	24.4	24.4	16.7	26.7	13.7	45.3
$80,000 and above	65.0	65.0	55.3	70.6	52.1	84.2
Employment status
Employed	88.1	88.1	80.1	96.4	88.7	98.9
Unemploy	7.4	7.4	3.6	3.6	1.1	11.3
NILF	4.6	4.6	1.9
Remoteness
Major Cities	59.3	59.3	50.1	91.0	79.8	96.3
Inner Regional	21.7	21.7	15.5	5.8	2.0	15.7
Outer Regioal	19.0	19.0	12.6	3.2	0.7	13.2
Born overseas
Yes	41.9	41.9	33.6	22.0	9.1	44.2
No	58.1	58.1	49.3	78.0	55.8	90.9

NILF = Not in the Labour Force.