East Asian Arch Psychiatry 2023;33:79-88 | https://doi.org/10.12809/eaap2326

ORIGINAL ARTICLE

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Philip Harford, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
Madelyn Agaciak, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
Jeffrey CL Looi, Academic Unit of Psychiatry and Addiction Medicine, The Australian National University School of Medicine and Psychology, Canberra Hospital, Canberra, ACT, Australia; Consortium of Australian-Academic Psychiatrists for Independent Policy Research and Analysis (CAPIPRA), Canberra, ACT, Australia
David Smith, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
Stephen Allison, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia; Consortium of Australian-Academic Psychiatrists for Independent Policy Research and Analysis (CAPIPRA), Canberra, ACT, Australia
Sherry Kit Wa Chan, Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
Tarun Bastiampillai, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia; Consortium of Australian-Academic Psychiatrists for Independent Policy Research and Analysis (CAPIPRA), Canberra, ACT, Australia; Department of Psychiatry, Monash University, Melbourne, VIC, Australia

Submitted: 30 May 2023; Accepted: 14 September 2023

Suicide is a global problem.1 Three decades ago, 300 000 Chinese people were estimated to die by suicide annually, accounting for 40% of all global suicides.² The suicide rate in China was previously higher among females.^3-6 The decline in China’s suicide rates since 2000s has been most marked among females.^1-4,6 Urbanisation is considered to have a protective effect against suicide in China.⁷

It is estimated that by 2050, 6.4 billion people, or 68% of the world’s population, will be urbanised.⁸ Economic growth in China has lifted 700 million people out of poverty, with 450 million people moving to urban areas^2,9,10 — the largest internal migration in the history of mankind. In 1990, 26.4% of the population lived in urban areas, compared with 58% in 2017.⁸ Urbanised migrants comprise 220 million people, or 17% of the population of China.⁸ However, urban development varies widely. Beijing and Shanghai have the highest levels of urbanisation, whereas Tibet and Guizhou have the lowest.⁸

In the United States, the risk of suicide is lower in more densely populated (ie, urbanised) areas.11 In China, the reduction in suicide rates may be a result of rapid urbanisation.¹² From 1978 to 2017, China’s gross domestic product (GDP) increased at an annualised rate of 9.5%,9 reaching US$14.3 trillion in 2019.¹³ From 1990 to 2017, China’s suicide rate decreased by 66%,¹⁴ accounting for 35.1% of the worldwide reduction in suicide (from 15.4 to 10 per 100 000 people).^14,15 This decline may be due to economic growth, increased urbanicity, improved healthcare, and restricted access to pesticides (as a means of suicide).^15,16

We investigated the associations between suicide rates and urbanicity in 31 provinces, municipalities, and autonomous regions of China, which vary widely in population, income, and urbanicity. Potential disparities in the effect of urbanisation on males and females were examined, as was whether the effect of urbanisation was independent of economic growth.

Suicide data were obtained from the Global Burden of Disease databases¹⁴ and the supplementary dataset of the study by Zhou et al.¹⁷ Urbanisation data were obtained from Chinese Yearbooks from 2005 to 2017 (such data were unavailable prior to 2005).¹² Gross regional product (GRP) data, which is a metric of the value of goods and services produced within a particular region or province of a country were also obtained from Chinese Yearbooks.

Statistical analyses were conducted using Stata 17.0 (StataCorp LLC, College Station [TX], USA).¹⁸ Associations between suicide rates, urbanicity, and economic indicators were determined. Urbanicity was defined as the proportion of urban residents in the population, despite wide variations in the interpretation of urbanisation.¹⁹ Poisson random intercept models were used to determine province- specific associations, compared with the overall average, as differences in suicide rates across regions are related to aetiologically important cultural, social, and psychological characteristics of the populations being compared.²⁰ As suicide rates were non-integer outcomes, a robust variance estimation was used to determine standard errors. GRP was used as an economic indicator, and its effect on urbanicity and suicide rates was examined. The function of sex as a potential modifier of any association between urbanicity and suicide rates was also investigated.

In China, the age-adjusted suicide rate per 100 000 people per year decreased from 20.9 in 1990 to 7.2 in 2017 and the corresponding rates decreased from 19.7 to 8.8 among males and from 22.5 to 5.7 among females. The male- to-female ratio of suicide rates reversed from a female- dominant ratio of 0.9 in 1990 to a male-dominant ratio of 1.6 in 2017. From 2005 to 2017 (when province-level data were available), the overall, male, and female suicide rates decreased by 35.2%, 24.5%, 41.0% respectively, whereas the urbanicity increased from 26.4% in 1990 to 58% in 2017 (Figure 1 and Table 1). The GDP per capita increased from US$318 in 1990 to US$8759 in 2017, and the urban population increased by 15.5% during this period.

From 2005 to 2017, in all 31 provinces, municipalities, and autonomous regions, the suicide rates decreased and urbanicity increased (Figure 2). The most urbanised and populous cities (Beijing, Shanghai, Tianjin) had the lowest suicide rates. Overall, the mean urbanicity increased from 42.5% in 2005 to 58.0% in 2017, which corresponded with decreases in suicide rates (55% for males and 75% for females since 1990 and 24.5% for males and 41% for females since 2005). Hubei was an outlier, as it ranked 15th in urbanicity but had the highest suicide rate of 23.6 per 100 000 people (Table 2).

In the unadjusted Poisson random intercept model, a 1% increase in urbanicity was associated with a 2.2% decrease in the suicide rate over 13 years per 100 000 people (incidence rate ratio = 0.978, 95% confidence interval [CI] = 0.974-0.981, p < 0.001, Figure 3), with significant province- specific random effects (σ̑ 2 ) = 0.097, 95% CI = 0.038- 0.248, p < 0.05). After adjusting for GRP, a 1% increase in urbanicity was associated with a 1.4% decrease in the suicide rate over 13 years per 100 000 people (incidence rate ratio = 0.986, 95% CI = 0.978-0.994, p = 0.001). After adjusting for urbanicity, a GRP per capita increase of US$5000 was associated with a 2% decrease in the suicide rate over 13 years per 100 000 people (incidence rate ratio = 0.980, 95% CI = 0.966-0.994, p = 0.006).

Increase in urbanicity was associated with greater decrease in suicide rates in females than in males (Figures 4 and 5). In the Poisson random intercept model, a 1% increase in urbanicity was associated with 0.8% fewer female suicide rate, compared with male suicide rate, over 13 years per 100 000 people (incidence rate ratio = 0.992, 95% CI = 0.988-0.994, p = 0.001). After adjusting for GRP, a 1% increase in urbanicity remained to be associated with 0.8% fewer female suicide rate, compared with male suicide rate, over 13 years per 100 000 people (incidence rate ratio = 0.992, 95% CI = 0.987-0.997, p = 0.001). However, after adjusting for urbanicity, the sex difference in suicide rates over 13 years per 100 000 people was not significant (p = 0.855).

The urbanisation of China is the world’s largest contributor to ‘turning the tide’ of suicide.²¹ Urbanisation refers to the change in size, density, and heterogeneity of cities and depends on a variety of factors including migration rate, birth and death rates, and economic growth.²² The definitions of urbanisation vary among nations and therefore comparison is difficult. However, the effect of urbanisation on health is important. It is estimated that 70% of the world will be urbanised by 2050, and the rate will be faster in low- and middle-income countries.²² In the present study, urbanisation is defined as the proportion of urban residents in the population.²

The sociologist Émile Durkheim opined that economic development and urbanisation would increase suicide mortality²³ and result in reduction in social cohesion, integration, and control.^1,23,24 However, in the present study, urbanicity and economic prosperity were protective against suicide in China, despite evidence of the social and mental health issues associated with urbanisation. Findings from international studies,^1,2,11,25 including those from Japan from 1970 to 1990,²⁶ have supported the contention that urbanisation is associated with a reduction in suicide mortality.

The decrease in suicide rates in China is more marked in females than in males.^27,28 The suicide rate used to be unusually high in Chinese females in rural areas, compared with Chinese males, or females in other countries. The suicide rates in China were previously higher among females; other countries with similar sex differences in suicide rates were Morocco, Uganda, and Pakistan.⁵ In China, urbanisation was associated with a 74% decrease in the female suicide rate from 1990 to 2017. This may be due to improvements in opportunities and living conditions.^2,27-29 Urbanisation may also confer increased financial freedom, social networking, education, and employment access, which act as protective factors against suicide.^1,2,27,28 It may also reduce psychological strain, as postulated by the strain theory of suicide.^27,29 With fewer conflicting values, psychological strain becomes less prevalent, particularly for females in rural areas.^27-30 This, in part, explains the overall decrease in suicide rates, even in rural areas.

Studies in the United States^11,25 and Australia³¹ also highlight the protective effect of urbanisation on suicide rates. In the present study, a 1% increase in urbanicity was associated with a 2.2% decrease in suicide rates. Suicide rates were lower in more urbanised municipalities (Beijing, Shanghai, Tianjin) than in less-urbanised rural provinces.

However, Hubei was an outlier. It had the highest suicide rate, despite being the 15th most urbanised province in China. The aetiology of Hubei’s high self-harm and suicide burden remains unclear.^32,33 Suicide mortality in Hubei is twice the national and global rates.³² This may be due to the change in family structures in Hubei in which families have become smaller and more nuclear, thereby values such as provision for elderly relatives diminish.³² There is a “cultural phenomenon” in Hubei that suicide has become “normalised, particularly in deprived areas,” and males suffer a higher burden of self-harm.³² Risk factors for suicide in Hubei include alcohol use (for males) and intimate partner violence (for females).³² In Hubei, 60% of suicides were due to poisoning between 1990 and 2015.³² Reducing access to the means of suicide, particularly pesticides, is a prevention strategy in rural areas.

Urbanisation is an independent protective factor against suicide after adjusting for GRP.34 In the present study, a 1% increase in urbanicity yielded a 1.4% decrease in suicide rates, and the decrease in suicide rates was 0.8% greater among females. Increases in GRP per capita also demonstrated a positive effect on suicide rates. Further studies are warranted to investigate the effects of other measures of wellbeing on suicide rates. Studies in high- income countries have reported consistently increased suicide risks in rural areas than urban areas.³⁵

The reduction in China’s suicide rate from 1990 to 2017 was accompanied by increased anxiety and depression rates.^36,37 China-specific data showed an increasing prevalence of depressive disorders and poor rates of evidence-based treatment.^38,39 In China, depressive disorders remain the second-highest cause for years lived with disability.³⁹ The prevalence of depression in China is estimated to be 6.8% and is increasing.⁴⁰ However, most people with depression were not diagnosed, and there is an “unacceptably high” treatment gap.⁴⁰ The prevalence of depressive disorder did not significantly differ between rural and urban areas, although people living in urban areas had greater access to treatment. Depressive disorders are a major cause for disability-adjusted lived years in China.³⁹ In 2020, the Chinese National Health Commission developed the first action plan for the prevention and management of depression, including regular and routine screening for depression within the population.⁴⁰

The United Nations forecasts that China’s population will be <800 million by 2100.⁴¹ There are concerns of increased mental health burden and suicide rates among rural-to-urban migrant workers.^42,43 The concept of the “heathy migrant effect” should be considered, particularly given the large migrant population in China.^42,44 There remain challenges in access to mental health care, particularly in rural areas, and integration and acceptance of mental health services.⁴⁵ Improved access to mental health and other healthcare services may arise from increased urbanisation, although higher rates of mental illness may coexist with increased availability of effective treatments.² In addition, mental health education to improve uptake and reduce stigma as well as financial support for mental health prevention strategies are crucial.⁴⁵ Future trends are difficult to predict; ongoing economic prosperity and urbanisation may give rise to worsening mental health outcomes through income inequality, divorce, and family separation secondary to migration and poor job security.² Further government action is required.

One limitation to the present study is that only economic factors were considered. Confounders such as divorce, educational attainment, and access to healthcare and mental health services and treatments were not accounted for. In addition, suicide rates were not analysed by age group. Furthermore, inferring risks at the individual level based on the group (ie, sex and province) may have introduced bias. There may have been periodic trends in the data according to age-related cohort effects. The quality of China’s suicide data was scored as 3, with 1 indicating comprehensive high-quality data and 4 indicating low- quality data.⁴⁶ This may have negatively affected the analyses and any conclusions drawn. Urbanisation was defined as the proportion of the population living in urban areas, but this reflects only part of the extent of urbanisation. Further research could focus on suicide rates among at-risk populations (such as migrant workers and rural residents), suicide rates by age group, the effect of COVID-19 on suicide rates, and the relative accessibility of mental health services and treatments.

Increased urbanisation is associated with decreased suicide rates in China from 1990 to 2017. This protective effect of urbanisation is independent of GRP. However, other health, psychological, and socioeconomic factors may have also mediated the association between urbanisation and decreased suicide rates.

All authors designed the study, acquired the data, analysed the data, drafted the manuscript, and critically revised the manuscript for important intellectual content. All authors had full access to the data, contributed to the study, approved the final version for publication, and take responsibility for its accuracy and integrity.

As an editor of the journal, SKWC was not involved in the peer review process. All other authors have disclosed no conflicts of interest.

This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

All data generated or analysed during the present study are available from the corresponding author on reasonable request.

Ethics approval was not required because the supplementary dataset of the study by Zhou et al was de-identified and data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 were an open access collaboration.

We would like to thank Associate Professor Haidong Wang at the University of Washington, Seattle, USA for providing the supplementary dataset for analysis.

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