Can Financial Support Reduce Suicide Mortality Rates?

Abstract

After the launch of governmental financial support for the development of a regional suicide prevention programme, 'Emergency Fund to Enhance Community-Based Suicide Countermeasure' in 2009, suicide mortality rates in Japan have decreased from 25.7 (in 2009) to 16.5 (in 2018) per 100,000 population. Therefore, to explore the effects of governmental financial support on suicide mortality rates in Japan, the present study determined the relationship between the trends of empirical Bayes standardised Mobile Ratio of suicide mortality ratio in all 47 Japanese prefectures (EBSMR-RR) and the execution amounts of 10 sub-divisions of 'Emergency Fund to Enhance Community-Based Suicide Countermeasure' using stepwise multiple regression analysis. The female EBSMR-RR was only significantly/inversely related to the municipal 'development of listeners and leaders', whereas male EBSMR-RR was significantly/inversely related to prefectural 'enlightenment', and 'intervention models', but significantly/directly related to prefectural 'personal consultation support'. The present findings suggest the inverse relationship between financial support and the suicide mortality rates in Japan. Furthermore, the independent factors in the reduction of suicide mortality rates between males and females provide important information for planning a scientifically evidence-based and more cost-effective regional suicide prevention programmes.

Keywords: Japan; financial support; prefecture; suicide mortality.

Figure 1

(A) Trends of age-dependent Japanese suicide mortality rates and government budgets for comprehensive suicide prevention programmes. Left and right ordinates indicate suicide mortality rate (per 100,000 population/year) and budget amounts ($million/year), respectively. (B) Comparison of age-distribution between World Health Organisation (WHO) world standard population model and Japan. Ordinate indicates age-distribution rates (%). Japanese age distribution was significantly different from WHO world standard population model by Mantel–Haenszel test (χ² = 52.1, p < 0.05).

Figure 2

Trends of empirical Bayes standardized mobile ratio (EBSMR) of suicide mortality per 100,000 population between 2009 and 2018 for (A) total (male plus female), (B) males and (C) females in 47 Japanese prefectures, and national average (red). Ordinates: EBSMR of suicide mortality for each prefecture (per 100,000 population); abscissa: time (year).

Figure 3

Time-dependent trends of EBSMR (EBSMR-RR) of total (male plus female), male and female suicide mortality in 47 Japanese prefectures, including national average (red) between 2009 and 2018 calculated while using the least squares method.

Figure 4

Relationship between EBSMR-RR and regional execution amounts (REAs) in 47 prefectures: (A) prefectures plus municipalities, (B) prefectures and (C) municipalities. Ordinates indicate EBSMR-RR and abscissas indicate REAs (¥ per population). Sphere size indicates the population size of each prefecture. Brown, blue and red indicate EBSMR-RR of total (male plus female), male and female, respectively. Linear regression analysis indicates total EBSMR-RR = −0.010 × REA (prefectures plus municipalities) − 0.866, = −0.012 × REA (prefectures) − 0.932, and = −0.018 × REA (municipalities) − 0.987. Male EBSMR-RR = −0.017 × REA (prefectures plus municipalities) − 1.231, = −0.022 × REA (prefectures) − 1.321, and = −0.028 × REA (municipalities) − 1.432. Female EBSMR-RR = −0.011 × REA (municipalities) − 0.498.

Figure 5

Relationship between total (male plus female) EBSMR-RR and sub-divisions of REAs: (A) prefectural enlightenment programmes and (B) municipal development programmes of leaders and listeners. Ordinates indicate total EBSMR-RR and abscissas indicate sub-divisions of REAs (¥ per population). Sphere size indicates the population size of each prefecture. Light blue spheres indicate the population size of the nation. Total EBSMR-RR = −0.021 × (prefectural ELM) − 0.092 × (municipal DLL) − 0.873. There was no multicollinearity.

Figure 6

Relationship between male EBSMR-RR and sub-divisions of REAs: (A) prefectural personal consultation support programmes, (B) enlightenment programmes, and (C) intervention model programmes. Ordinates indicate male EBSMR-RR and abscissas indicate sub-divisions of REAs (¥ per population). Sphere size indicates the population size of each prefecture. Light blue spheres indicate the population size of the nation. Male EBSMR-RR = +0.065 × (prefectural PCS) − 0.043 × (prefectural ELM) − 0.039 × (prefectural IVM) − 1.347. There was no multicollinearity.

Figure 7

Relationship between female EBSMR-RR and ELM sub-division of REAs. Ordinate indicates female EBSMR-RR and abscissa indicates sub-division of REAs (¥ per population). Sphere size indicates the population size of each prefecture. Light blue spheres indicate the population size of the nation. Female EBSMR-RR = −0.083 × (municipal DLL) − 0.500. There was no multicollinearity.