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Received date: 29/05/2014 Revised date: 20/10/2014 Accepted date: 06/11/2014
Analysis of the impact of geographical characteristics on the suicide rate and visualization of the result by GIS (Geographic Information System) 1
Running title: Geographical factors & suicide rate
Mayumi Oka, Ph.D. 1,*, Takafumi Kubota, Ph.D. 2 , Hiroe Tsubaki, Ph.D. 3 , Keita
Yamauchi, Ph.D. 4
1
School of Health and Nursing Science, Wakayama Medical University, Wakayama
Prefecture, Japan 2
School of Management and Information Sciences, Tama University, Tokyo, Japan
3
The Institute of Statistical Mathematics, Tokyo, Japan
4
Keio University, Faculty of Nursing and Medical Care, Kanagawa, Japan
This article has been accepted for publication and undergone full peer review but has not been through the opyediting, typesetting, pagination and proofreading proces s, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/pcn.12254
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*Corresponding Author: Mayumi Oka School of Health and Nursing Science, Wakayama Medical Unive rsity 580 Mikazura, Wakayama City, Wakayama Prefecture 641 -0011, Japan Phone: 81-73-446-6700 E-mail: [email protected]
Number of figures: 2
Number of tables: 2
Number of words in the manuscript: 3039
Number of words in the abstract: 163 Field: Social psychiatry and epidemiology
Running Title: Geographical factors and suicide rate
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ABSTRACT Aim
The aim of our study is to understand the geographical characteristics of the
communities to raise or to restrain suicide rate. Methods
We calculated the standardized mortality ratio from suicide statistics of 3,318
municipalities from 1972 to 2002. Correlation analysis, multi -regression analysis and generalized additive model were used to find the relationship between topographic and climatic variables and suicide rate. We visualized the relation between geographical characteristics and suicide rate on
the map of Wakayama Prefecture, using GIS (Geographic Information System) Results
Our study showed that the geographical characteristics of each community are
related with its suicide rate. The strongest factor among geographical characteristics to raise suicide rate was slope of habitable land. Conclusions It is necessary to take the characteristics of each community into consideration,
when we work out measures of suicide prevention.
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Visualization of the findings on the local map should be helpful to promote
understanding of problem and share the information among various parties in charge of suicide prevention.
Key words Suicide, geographic characteristics, communit y, risk factors for suicide, protective
factors for suicide
INTRODUCTION
In Japan, nearly 30000 persons had committed suicide since 1998 for 14 years in a
row. 1 The ratio of suicide to a population of 100 thousand persons of Japan had been
around 25.0, and it is the worst among seven industrial democracies. Although the number has gradually decreased owing to unceasing effort of
Japanese Government, this figure is nearly six times larger than the number of people who were killed in traffic accidents in Japan. 2
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Suicide is still one of the most urgent problems to be solved in Japanese society.
Among the numerous social factors that could induce suicide, the characteristics of a community, a basis of people’s living, are an important key to suicide prevention. Regional studies on suicide have accumulated in Japan. However, they mostly cover areas with high suicide incidence. We started studying the protective factors for suicide in the areas with low suicide incidence because basing our study on a viewpoint that is different from existing ones would provide new implications. Since 2008, we have conducted study in former Kaifu Town of Tokushima
prefecture (hereinafter “Kaifu Town”), one of the areas with low suicide incidence in
Japan. In 2009, another study was started in the former Village P (hereinafter “Village P”) located in the same prefecture. 3-6 Village P is categorized as one of the areas with highest suicide incidence in Japan. The two different studies were conducted simultaneously for the purpose of
comparing their regional characteristics. There was not any specific gap in their population distribution, in state of habitants’ health or in economic situation. The large difference is topography. Kaifu Town, a small town facing the Pacific
Ocean, is densely packed with communities and has good accessibility to resources necessary in everyday life. On the other hand, Village P is located at a high elevation, rather deserted and dotted with small settlements in a mountainous area that is sharply
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sloped. Geographically, the village has large obstacles in everyday life. T here were found to be apparently different in character of the habitants and their behavioral pattern.
Concerning the relationship between suicide rate and topography, previous
overseas studies analyzed population density, elevation and the accessibility to social resources. 7-16 According to these studies, population density and elevation are negatively and positively correlated with suicide rate, respectively. Poor accessibility to social resources (e.g. medical institutions) and suicide rate are positively correlated. Regarding the relationship between suicide rate and climate, s ome previous studies
analyzed the factors such as season, temperature, rainfall, length of daylight hours
and snow accumulation. 17,18 Results of these analyses are not necessarily self-consistent. For example, some reports say the length of daylight hours and suicide rate are positively correlated. 19,20 while other reports say the opposite. 21,22 Even in the same country, arguments are clearly split. Berry reviewed literature on relationships between climate and mental health, and derived a view that climatic conditions influence happiness levels in a community and thus might indirectly influence mental health of residents via the community. 23
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Based on these points, Oka et al analyzed the correlation between suicide rate and 9
topographic variables using the suicide statistics of 3,318 municipalities of Japan. 24
As a result, many of areas with low suicide incidence are flat land with high population density of habitable land in coastal area, facing the Pacific Ocean or Seto
Inland Sea. As an additional analysis, we extracted and overviewed 33 municipalities with 1% lower suicide rate throughout the country. On the basis of our findings, we are to advance this study by using added variables
and analysis methods, and discuss how topography and climate influence the suicide rate of municipalities in Japan. Then, we are to visualize the result of analysis on the Japanese map , using GIS,
Geographic Information System so that we can verify the relation between geographical characteristics and suicide rate. GIS is a system to analyze relation between various spatial information and other valuables or to display them visually overlaying them. Though GIS used to be for some specialists, recently the range of use has expanded to our daily-life issue and is utilized in the field of mental health and environment as well. 25-27 The aim of our study is to understand the geographical characteristics of the
communities to raise or to restrain suicide rate.
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METHODS
Data used for analysis
1. Index of suicide rate We used data from “Regional statistics on suicide deaths” (hereinafter “regional
statistics”) 28 published by the National Institute of Mental Health. The data are about
suicide rate in a total of 3318 municipalities in a 30-year period from 1973 to 2002. Based on the mortality sheet for the demographic survey conducted by the Ministry of Health,
Traditionally, many statistical documents used as reference in discussing suicide
issues on a national level are divided into 47 different prefectures and the use of statistic documents by municipalities is not much. However, many different attributes such as coasts, mountains, urban areas, farms and fishing villages coexist in a prefecture. Therefore, this study covers the areas that were formerly municipalities in and before 2002, right before the great municipal merger of Heisei Era. This is because the merger was followed by a tendency to lump together living areas with
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different topography, history and culture, making it difficult to identify characteristics of each of the traditional communities. Suicide often occurs from age-related factors. To facilitate comparisons among
municipalities with different age distribution, we calculated the standardized mortality ratio of suicide deaths by municipalities. In a municipality with small population, even a slight increase or decrease in the
number of suicide causes significant variation. So the 30 years average of SMR (Standardized Mortality Ration) was calculated to minimize the influence of the
increase/decrease. We consider the values obtained from the above calculation as the index of
municipal suicide rate in this analysis. This index is hereinafter referred to as “Suicide-SMR” by municipalities.
2. Topographic data Topographic variables were chosen with consideration of previous studies and
results of field survey we had conducted. We chose “population,” “area,” “population density,” “population density of habitable land” (hereinafter “population
density-HL”), “elevation of habitable land” (hereinafter “elevation-HL”), “slope of
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habitable land” (hereinafter “slope-HL”), “coastal area attributes” and “island attributes” as topographic variables. For the “population”, “area”, “population density” and “population density of
habitable land”, we referred to the database (year of 2000) of Geographical Survey Institute of Japan. Besides existing and disclosed data, this study uses topographic
and climatic variables that were processed with the use of existing data. The following is a simple explanation about those variables. We sought elevation of the locations of local government offices because we needed to grasp the elevation-HL in accordance with the objective of this study. We named the variables “elevation-HL”. For the same reason, we calculated the slope of the ground on which all buildings such as houses and public institutions (approx. 3.5 million records nationwide) stand,
referring the resources of Japanese Geospatial Information Authority and found a mean value for each municipality. We named the variables “slope-HL.”
3. Climatic data We chose “average temperature,” “rainfall,” “daylight hours” and “ snow
accumulation” as climatic variables. Referring the resources of Japanese Meteorological Business Support Center, normal value for observations in a 30-year
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period between 1971 and 2000 was added to the locations of each municipal government office.
Analysis procedure Correlation analysis, multi-regression analysis with weighted least-squares method
and generalized additive model were used to find the positive/negative relationship between topographic and climatic variables and suicide rate, as well as its strength. Among the variables used for correlation analysis, continuous variables such as “population,” “area” and “population density” have widely-scattered values. Equally-spaced division was performed on these values so that five-staged category variables could be obtained for the purpose of reducing the effect of outliers. With consideration of multicollinearity, explanatory variables for multi-regression
analysis were determined to be “population density-HL,” “slope-HL,” “coastal area attributes,” “island attributes,” “daylight hours” and “snow accumulation.” Logarithmic conversion was performed on continuous variables of positive numbers, and dummy variables were created for coastal area attributes and island attributes. Standard error of CI of Suicide-SMR was used for weighting, before performing a multi-regression analysis with the use of weighted least-squares method.
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We decided to use a nonlinear model to review in detail the influence of
“elevation-HL” and “slope” on Suicide-SMR, and applied the smoothing spline for
the generalized additive model. IBM SPSS Statistics 19.0 and R Ver2.13.1 were used for the analysis.
Visualization of the result Based on the above results, we visualized the relation between geographical
characteristics and suicide rate on the local map of Wakayama prefecture. In Wakayama, there are both coastal and steep mountain areas containing
industrial, agricultural, forestry and fishery zones. Through the field surveys we have conducted, we found that there are big gaps in geographical features which cause various socio-cultural characteristics in this prefecture. We validated the hypothesis that geographical characteristics of community influence suicide rate as well in Wakayama, and by visualizing the facts on the map, we aimed to share the information among the parties in charge of suicide presentation. Arc GIS.Ver.10.0 was used for the analysis.
RESULTS
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Correlation analysis Our analysis showed a low to moderate degree of significant correlation between
Suicide-SMR and the following: “population,” “area,” “population density,” “population density-HL,” “elevation-HL,” “slope-HL,” “average temperature,” “daylight hours” and “snow accumulation.” The correlation with “rainfall” was significant, though its correlation coefficient was low at 0.112. A low to moderate degree of negative correlation was found with “population,”
“population density,” “population density-HL,” “average temperature” and “daylight hours.” A low degree of positive correlation was found with “area,” “elevation-HL,” “slope-HL” and “snow accumulation.” Correlation coefficient was highest with “population density-HL,” followed by “population density” (Table 1).
Multiple regression analysis The analysis showed that all variables except “island attributes” were significant.
The standardized coefficient of explanatory variables was highest with “slope-HL,” followed by “population density-HL,” “snow accumulation,” “daylight hours,” and “coastal area attributes” in the same order. “Population density-HL,” “daylight hours” and “coastal area attributes” exerted negative influence on Suicide-SMR, while
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“slope-HL” and “snow accumulation” gave positive influence. The coefficient of determination was 0.256 (Table 2).
Generalized additive model As a result of analysis about “elevation-HL” and “slope-HL,” the intercept with
Suicide-SMR was 110.8 at a significance level of less than 1% (Figure 1). The graduation of Y axis of the graph indicates increase and decrease of Suicide-SMR with the intercept value as the starting point. The dashed line indicates the upper and lower limits of confidence interval. The higher elevation-HL is, the more Suicide-SMR rises as long as the
elevation-HL is nearly 300 meters or less. Suicide-SMR drops at elevation-HL higher than 300 meters and remains unchanged at elevations higher than 700 meters. The greater a slope-HL is, the higher Suicide-SMR grows. In particular, the ascending curve becomes steeper above 15 degrees. With slopes below 20 degrees, Suicide-SMR reaches more than 200, indicating a great deal of influence. Concerning both “elevation” and “slope-HL,” the larger the value is, the less
frequent suicide occurs. This leads to greater range of confidence interval. For “slope-HL,” however, the range of confidence interval is relatively small even if the value reaches the maximum level.
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Visualization of geographical characteristics and suicide rate We visualized the distribution of suicide rate of Wakayama prefecture on the local
map (Figure 2). Difference of suicide rate was expressed by color. The darker the color is, the higher suicide rate is. Furthermore, we visualized the distribution of “slope-HL,” of Wakayama prefecture on the local map, and verified the relation
between geographical characteristics and suicide rate (Figure 2). The darker the color
is, the higher “slope-HL,” is. The color distribution of the map of suicide rate showed
resemblance with the one of “slope-HL.” The village with the highest suicide-SMR 248.8 has also the highest “slope HL”
15.4, and suicide-SMR 248.8 situates at highest level of suicide incidence in Japan.
DISCUSSION
While many previous regional studies of suicide are available, ours is the first
study discussing suicide rates related with topographic and climatic characteristics using 30-year suicide statistics for all of the 3318 municipalities in Japan.
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Our analysis showed that areas with low suicide incidence are generally less-sloped
flat land with high population density-HL in coastal area. These areas are with longer daylight hours and smaller snow accumulation. Many of the municipalities that have coastal area attributes and are categorized as areas with low suicide incidence have island attributes more than other regions do.
Influence of coastal area attributes on suicide rate In analyzing the influence of coastal area attributes on a community, the first thing
you need to know about is the development of social infrastructure such as transportation, distribution, commerce, medical welfare and educational facilities. In Japan, the development of social infrastructure tends to be facilitated more in coastal areas than in mountainous areas. According to WHO’s report 29 and previous studies, 30-33 the poor accessibility to healthcare, welfare and other social resources is
considered a risk factor that could induce suicide. Such risk factors would be fewer in coastal municipalities with well-developed social infrastructure. The finding from this analysis, that many of the municipalities with coastal area attributes are categorized into areas with low suicide incidence, may be considered as supporting the results of
previous studies.
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Influence of population density-HL on suicide rate It is suggested that the following two factors lie behind the relationship between
population density-HL and suicide rate. As shown by the abovementioned previous studies, poor accessibility to healthcare,
welfare and other social resources is one of the risk factors for suicide. In the areas with high population density-HL, however, the distance to social resources and the time necessary for obtaining the resources may be shorter. The finding from this
analysis, that many of the municipalities with high population density-HL are categorized into areas with low suicide incidence, may be considered as supporting the results of previous studies. Previous studies also specify as risk factors for suicide the lack of social support in
a community, poor network, lack of information and isolation and loneliness of local people. 34-38 These risk factors may also be correlated with distance to social resources,
time necessary for obtaining the resources and distance between neighbors, whereas the risk factors may be fewer in areas with high population density-HL. The finding
from this analysis, that many of the municipalities with high population density-HL are categorized into areas with low suicide incidence, may be considered as agreeing with the results of previous studies about social support in a community.
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Influence of elevation-HL and slope-HL on suicide rate Municipalities with higher elevation-HL and more sloped land are mostly located in
steeply-mountainous areas. Since the availability of transportation is limited in these areas, it often takes much time for people in these areas to attain social resources indispensable for their everyday life. Due to the limited availability of flat land, private houses and public organizations
have no choice but to be located far from one another. This results in low population density in a community and growing obstacles to neighbors’ exchanges and distribution of information. These areas suffer from a twofold suicide risk factor, namely the poor accessibility to social resources and the obstacles to social support. The result showed that the more the land is sloped, the more Suicide-SMR is
influenced. In particular, the spline curve rapidly ascends for slope-HL above 15 degrees. Despite of smaller frequency of occurrence, the confidence interval is relatively small and represents a high level of risk and its multiplication. As explained so far, elevation is not necessarily a risk factor. However, the degree of risk factor may rapidly increase if a factor of steep slope is added.
Influence of climate on suicide rate
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An analysis of climatic conditions showed that many of the areas with low suicide
incidence are municipalities with longer daylight hours and smaller snow accumulation. Relations between climatic conditions and suicide have been reported
by numerous previous studies both domestically and internationally. However, results of the analyses are not self-consistent. According to a review by Ajdacic-Gross et al in 2010, it would be impossible to universally grasp the influence of climate on suicide. 16 The finding from this study, that the areas with low suicide incidence have long daylight hours and less snow, may be dependent on coastal area attributes and other factors that are unique to areas with low suicide incidence. It remains to be seen how this is elucidated. The finding agrees with the discussion on indirect influence of geographical
characteristics on suicide rate, which will be mentioned later.
Effectiveness of visualization of the result of analysis We could review the knowledge obtained from this research by visualizing the
result of analysis on the map of Wakayama prefecture. Although there is largely different distribution of suicide rate in the same prefecture, it had not been recognized for long time.
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We could also gain clearer understanding that the areas with high suicide incidence
tend to exist in the areas with steep slopes in the prefecture. That supported our hypothesis and result of the analysis. The map colored by GIS (Geographic Information System) is a material easy to
understand the problems, and should be quite helpful to share the information among various parties in charge of suicide prevention.
Conclusions Our study showed that the strongest factor among geographical characteristics to
raise suicide rate is slope of habitable land. It is necessary to take the characteristics of each community into consideration, when we work out measures of suicide prevention. In this study, we focused on the relation between geographical characteristics and
local suicide rate. We have not done research on the other factors to influence mental
health of the local people, such as quality of medical services, deterioration of social network or decreasing birthrate and aging of the population. The results from our questionnaire survey conducted in Tokushima prefecture
showed that people living under severe circumstances tend to acquire patience and self-restrained behavior and the habitants in steep mountain area with poor
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accessibility felt stronger resistance to seek for help, compared with them in coastal area with good accessibility. Though we have not conducted the questionnaire survey in Wakayama, as far a s we
interviewed the local habitants and the persons in charge of health and welfare
services, our impression coincides with the previous study. That is f uture topics of discussion.
ACKNOWLEDGMENTS The study did not receive any specific grants.
CONFLICT OF INTEREST STATEMENT The authors have no conflict of interest to declare.
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TABLES Table 1. Analysis of correlation between Suicide-SMR and topographic and climatic variables
P opulation
Ar e a
Sui cid e SM R
P opulation
P opulation
El e va tion
Slop e o f
Ave r a ge
den sit y
den sit y o f
of
habi t abl e
te mp er a tur e
habi t abl e
habi t abl e
land
land
land
Ra in fa ll
D a yli gh t
Sno w
hours
a cc u mu l atio n
Cor re l atio n -.302
.314
-.456
-.473
.276
.267
-.321
.122
-.323
.263
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
co e ffi ci en t Si gn i fi c an ce proba bil it y (both sid e s )
SMR: standardized mortality ratio
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Table 2. Multi-regression analysis with Suicide-SMR as dependent variable
(Constant)
Non-standardized coefficient
B
Standardized
Diagnosis of collinearity
coefficient
Standard
Beta
t-value
Significance
VIF
probability error 197.808
10.627
18.613
.000
2.844
.201
.240
14.121
.000
1.288
habitable land
-16.658
1.440
-.201
-11.572
.000
1.349
Deepest snow
.194
.023
.173
8.526
.000
1.837
Daylight hours
-.028
.005
-.105
-5.265
.000
1.770
Coastal area attributes
-7.675
1.835
-.072
-4.182
.000
1.322
Island attributes
-5.393
3.163
-.029
-1.705
.088
1.262
Slope
Population density of
Dependent variable: suicide standardized mortality ratio (SMR). Weighted least square method with standard error of suicide SMR Conditioned R2 = 0.256 n = 3318 VIF: variance inflation factor
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FIGURE LEGENDS Figure 1. Influence of elevation-HL and slope-HL on Suicide-SMR Figure 2. Visualization of relation between slope of habitable land and suicide rate on the map of Wakayama Prefecture
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Received date: 29/05/2014 Revised date: 20/10/2014 Accepted date: 06/11/2014
Analysis of the impact of geographical characteristics on the suicide rate and visualization of the result by GIS (Geographic Information System) 1
Running title: Geographical factors & suicide rate
Mayumi Oka, Ph.D. 1,*, Takafumi Kubota, Ph.D. 2 , Hiroe Tsubaki, Ph.D. 3 , Keita
Yamauchi, Ph.D. 4
1
School of Health and Nursing Science, Wakayama Medical University, Wakayama
Prefecture, Japan 2
School of Management and Information Sciences, Tama University, Tokyo, Japan
3
The Institute of Statistical Mathematics, Tokyo, Japan
4
Keio University, Faculty of Nursing and Medical Care, Kanagawa, Japan
This article has been accepted for publication and undergone full peer review but has not been through the opyediting, typesetting, pagination and proofreading proces s, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/pcn.12254
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*Corresponding Author: Mayumi Oka School of Health and Nursing Science, Wakayama Medical Unive rsity 580 Mikazura, Wakayama City, Wakayama Prefecture 641 -0011, Japan Phone: 81-73-446-6700 E-mail: [email protected]
Number of figures: 2
Number of tables: 2
Number of words in the manuscript: 3039
Number of words in the abstract: 163 Field: Social psychiatry and epidemiology
Running Title: Geographical factors and suicide rate
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ABSTRACT Aim
The aim of our study is to understand the geographical characteristics of the
communities to raise or to restrain suicide rate. Methods
We calculated the standardized mortality ratio from suicide statistics of 3,318
municipalities from 1972 to 2002. Correlation analysis, multi -regression analysis and generalized additive model were used to find the relationship between topographic and climatic variables and suicide rate. We visualized the relation between geographical characteristics and suicide rate on
the map of Wakayama Prefecture, using GIS (Geographic Information System) Results
Our study showed that the geographical characteristics of each community are
related with its suicide rate. The strongest factor among geographical characteristics to raise suicide rate was slope of habitable land. Conclusions It is necessary to take the characteristics of each community into consideration,
when we work out measures of suicide prevention.
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Visualization of the findings on the local map should be helpful to promote
understanding of problem and share the information among various parties in charge of suicide prevention.
Key words Suicide, geographic characteristics, communit y, risk factors for suicide, protective
factors for suicide
INTRODUCTION
In Japan, nearly 30000 persons had committed suicide since 1998 for 14 years in a
row. 1 The ratio of suicide to a population of 100 thousand persons of Japan had been
around 25.0, and it is the worst among seven industrial democracies. Although the number has gradually decreased owing to unceasing effort of
Japanese Government, this figure is nearly six times larger than the number of people who were killed in traffic accidents in Japan. 2
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Suicide is still one of the most urgent problems to be solved in Japanese society.
Among the numerous social factors that could induce suicide, the characteristics of a community, a basis of people’s living, are an important key to suicide prevention. Regional studies on suicide have accumulated in Japan. However, they mostly cover areas with high suicide incidence. We started studying the protective factors for suicide in the areas with low suicide incidence because basing our study on a viewpoint that is different from existing ones would provide new implications. Since 2008, we have conducted study in former Kaifu Town of Tokushima
prefecture (hereinafter “Kaifu Town”), one of the areas with low suicide incidence in
Japan. In 2009, another study was started in the former Village P (hereinafter “Village P”) located in the same prefecture. 3-6 Village P is categorized as one of the areas with highest suicide incidence in Japan. The two different studies were conducted simultaneously for the purpose of
comparing their regional characteristics. There was not any specific gap in their population distribution, in state of habitants’ health or in economic situation. The large difference is topography. Kaifu Town, a small town facing the Pacific
Ocean, is densely packed with communities and has good accessibility to resources necessary in everyday life. On the other hand, Village P is located at a high elevation, rather deserted and dotted with small settlements in a mountainous area that is sharply
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sloped. Geographically, the village has large obstacles in everyday life. T here were found to be apparently different in character of the habitants and their behavioral pattern.
Concerning the relationship between suicide rate and topography, previous
overseas studies analyzed population density, elevation and the accessibility to social resources. 7-16 According to these studies, population density and elevation are negatively and positively correlated with suicide rate, respectively. Poor accessibility to social resources (e.g. medical institutions) and suicide rate are positively correlated. Regarding the relationship between suicide rate and climate, s ome previous studies
analyzed the factors such as season, temperature, rainfall, length of daylight hours
and snow accumulation. 17,18 Results of these analyses are not necessarily self-consistent. For example, some reports say the length of daylight hours and suicide rate are positively correlated. 19,20 while other reports say the opposite. 21,22 Even in the same country, arguments are clearly split. Berry reviewed literature on relationships between climate and mental health, and derived a view that climatic conditions influence happiness levels in a community and thus might indirectly influence mental health of residents via the community. 23
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Based on these points, Oka et al analyzed the correlation between suicide rate and 9
topographic variables using the suicide statistics of 3,318 municipalities of Japan. 24
As a result, many of areas with low suicide incidence are flat land with high population density of habitable land in coastal area, facing the Pacific Ocean or Seto
Inland Sea. As an additional analysis, we extracted and overviewed 33 municipalities with 1% lower suicide rate throughout the country. On the basis of our findings, we are to advance this study by using added variables
and analysis methods, and discuss how topography and climate influence the suicide rate of municipalities in Japan. Then, we are to visualize the result of analysis on the Japanese map , using GIS,
Geographic Information System so that we can verify the relation between geographical characteristics and suicide rate. GIS is a system to analyze relation between various spatial information and other valuables or to display them visually overlaying them. Though GIS used to be for some specialists, recently the range of use has expanded to our daily-life issue and is utilized in the field of mental health and environment as well. 25-27 The aim of our study is to understand the geographical characteristics of the
communities to raise or to restrain suicide rate.
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METHODS
Data used for analysis
1. Index of suicide rate We used data from “Regional statistics on suicide deaths” (hereinafter “regional
statistics”) 28 published by the National Institute of Mental Health. The data are about
suicide rate in a total of 3318 municipalities in a 30-year period from 1973 to 2002. Based on the mortality sheet for the demographic survey conducted by the Ministry of Health,
Traditionally, many statistical documents used as reference in discussing suicide
issues on a national level are divided into 47 different prefectures and the use of statistic documents by municipalities is not much. However, many different attributes such as coasts, mountains, urban areas, farms and fishing villages coexist in a prefecture. Therefore, this study covers the areas that were formerly municipalities in and before 2002, right before the great municipal merger of Heisei Era. This is because the merger was followed by a tendency to lump together living areas with
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different topography, history and culture, making it difficult to identify characteristics of each of the traditional communities. Suicide often occurs from age-related factors. To facilitate comparisons among
municipalities with different age distribution, we calculated the standardized mortality ratio of suicide deaths by municipalities. In a municipality with small population, even a slight increase or decrease in the
number of suicide causes significant variation. So the 30 years average of SMR (Standardized Mortality Ration) was calculated to minimize the influence of the
increase/decrease. We consider the values obtained from the above calculation as the index of
municipal suicide rate in this analysis. This index is hereinafter referred to as “Suicide-SMR” by municipalities.
2. Topographic data Topographic variables were chosen with consideration of previous studies and
results of field survey we had conducted. We chose “population,” “area,” “population density,” “population density of habitable land” (hereinafter “population
density-HL”), “elevation of habitable land” (hereinafter “elevation-HL”), “slope of
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habitable land” (hereinafter “slope-HL”), “coastal area attributes” and “island attributes” as topographic variables. For the “population”, “area”, “population density” and “population density of
habitable land”, we referred to the database (year of 2000) of Geographical Survey Institute of Japan. Besides existing and disclosed data, this study uses topographic
and climatic variables that were processed with the use of existing data. The following is a simple explanation about those variables. We sought elevation of the locations of local government offices because we needed to grasp the elevation-HL in accordance with the objective of this study. We named the variables “elevation-HL”. For the same reason, we calculated the slope of the ground on which all buildings such as houses and public institutions (approx. 3.5 million records nationwide) stand,
referring the resources of Japanese Geospatial Information Authority and found a mean value for each municipality. We named the variables “slope-HL.”
3. Climatic data We chose “average temperature,” “rainfall,” “daylight hours” and “ snow
accumulation” as climatic variables. Referring the resources of Japanese Meteorological Business Support Center, normal value for observations in a 30-year
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period between 1971 and 2000 was added to the locations of each municipal government office.
Analysis procedure Correlation analysis, multi-regression analysis with weighted least-squares method
and generalized additive model were used to find the positive/negative relationship between topographic and climatic variables and suicide rate, as well as its strength. Among the variables used for correlation analysis, continuous variables such as “population,” “area” and “population density” have widely-scattered values. Equally-spaced division was performed on these values so that five-staged category variables could be obtained for the purpose of reducing the effect of outliers. With consideration of multicollinearity, explanatory variables for multi-regression
analysis were determined to be “population density-HL,” “slope-HL,” “coastal area attributes,” “island attributes,” “daylight hours” and “snow accumulation.” Logarithmic conversion was performed on continuous variables of positive numbers, and dummy variables were created for coastal area attributes and island attributes. Standard error of CI of Suicide-SMR was used for weighting, before performing a multi-regression analysis with the use of weighted least-squares method.
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We decided to use a nonlinear model to review in detail the influence of
“elevation-HL” and “slope” on Suicide-SMR, and applied the smoothing spline for
the generalized additive model. IBM SPSS Statistics 19.0 and R Ver2.13.1 were used for the analysis.
Visualization of the result Based on the above results, we visualized the relation between geographical
characteristics and suicide rate on the local map of Wakayama prefecture. In Wakayama, there are both coastal and steep mountain areas containing
industrial, agricultural, forestry and fishery zones. Through the field surveys we have conducted, we found that there are big gaps in geographical features which cause various socio-cultural characteristics in this prefecture. We validated the hypothesis that geographical characteristics of community influence suicide rate as well in Wakayama, and by visualizing the facts on the map, we aimed to share the information among the parties in charge of suicide presentation. Arc GIS.Ver.10.0 was used for the analysis.
RESULTS
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Correlation analysis Our analysis showed a low to moderate degree of significant correlation between
Suicide-SMR and the following: “population,” “area,” “population density,” “population density-HL,” “elevation-HL,” “slope-HL,” “average temperature,” “daylight hours” and “snow accumulation.” The correlation with “rainfall” was significant, though its correlation coefficient was low at 0.112. A low to moderate degree of negative correlation was found with “population,”
“population density,” “population density-HL,” “average temperature” and “daylight hours.” A low degree of positive correlation was found with “area,” “elevation-HL,” “slope-HL” and “snow accumulation.” Correlation coefficient was highest with “population density-HL,” followed by “population density” (Table 1).
Multiple regression analysis The analysis showed that all variables except “island attributes” were significant.
The standardized coefficient of explanatory variables was highest with “slope-HL,” followed by “population density-HL,” “snow accumulation,” “daylight hours,” and “coastal area attributes” in the same order. “Population density-HL,” “daylight hours” and “coastal area attributes” exerted negative influence on Suicide-SMR, while
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“slope-HL” and “snow accumulation” gave positive influence. The coefficient of determination was 0.256 (Table 2).
Generalized additive model As a result of analysis about “elevation-HL” and “slope-HL,” the intercept with
Suicide-SMR was 110.8 at a significance level of less than 1% (Figure 1). The graduation of Y axis of the graph indicates increase and decrease of Suicide-SMR with the intercept value as the starting point. The dashed line indicates the upper and lower limits of confidence interval. The higher elevation-HL is, the more Suicide-SMR rises as long as the
elevation-HL is nearly 300 meters or less. Suicide-SMR drops at elevation-HL higher than 300 meters and remains unchanged at elevations higher than 700 meters. The greater a slope-HL is, the higher Suicide-SMR grows. In particular, the ascending curve becomes steeper above 15 degrees. With slopes below 20 degrees, Suicide-SMR reaches more than 200, indicating a great deal of influence. Concerning both “elevation” and “slope-HL,” the larger the value is, the less
frequent suicide occurs. This leads to greater range of confidence interval. For “slope-HL,” however, the range of confidence interval is relatively small even if the value reaches the maximum level.
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Visualization of geographical characteristics and suicide rate We visualized the distribution of suicide rate of Wakayama prefecture on the local
map (Figure 2). Difference of suicide rate was expressed by color. The darker the color is, the higher suicide rate is. Furthermore, we visualized the distribution of “slope-HL,” of Wakayama prefecture on the local map, and verified the relation
between geographical characteristics and suicide rate (Figure 2). The darker the color
is, the higher “slope-HL,” is. The color distribution of the map of suicide rate showed
resemblance with the one of “slope-HL.” The village with the highest suicide-SMR 248.8 has also the highest “slope HL”
15.4, and suicide-SMR 248.8 situates at highest level of suicide incidence in Japan.
DISCUSSION
While many previous regional studies of suicide are available, ours is the first
study discussing suicide rates related with topographic and climatic characteristics using 30-year suicide statistics for all of the 3318 municipalities in Japan.
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Our analysis showed that areas with low suicide incidence are generally less-sloped
flat land with high population density-HL in coastal area. These areas are with longer daylight hours and smaller snow accumulation. Many of the municipalities that have coastal area attributes and are categorized as areas with low suicide incidence have island attributes more than other regions do.
Influence of coastal area attributes on suicide rate In analyzing the influence of coastal area attributes on a community, the first thing
you need to know about is the development of social infrastructure such as transportation, distribution, commerce, medical welfare and educational facilities. In Japan, the development of social infrastructure tends to be facilitated more in coastal areas than in mountainous areas. According to WHO’s report 29 and previous studies, 30-33 the poor accessibility to healthcare, welfare and other social resources is
considered a risk factor that could induce suicide. Such risk factors would be fewer in coastal municipalities with well-developed social infrastructure. The finding from this analysis, that many of the municipalities with coastal area attributes are categorized into areas with low suicide incidence, may be considered as supporting the results of
previous studies.
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Influence of population density-HL on suicide rate It is suggested that the following two factors lie behind the relationship between
population density-HL and suicide rate. As shown by the abovementioned previous studies, poor accessibility to healthcare,
welfare and other social resources is one of the risk factors for suicide. In the areas with high population density-HL, however, the distance to social resources and the time necessary for obtaining the resources may be shorter. The finding from this
analysis, that many of the municipalities with high population density-HL are categorized into areas with low suicide incidence, may be considered as supporting the results of previous studies. Previous studies also specify as risk factors for suicide the lack of social support in
a community, poor network, lack of information and isolation and loneliness of local people. 34-38 These risk factors may also be correlated with distance to social resources,
time necessary for obtaining the resources and distance between neighbors, whereas the risk factors may be fewer in areas with high population density-HL. The finding
from this analysis, that many of the municipalities with high population density-HL are categorized into areas with low suicide incidence, may be considered as agreeing with the results of previous studies about social support in a community.
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Influence of elevation-HL and slope-HL on suicide rate Municipalities with higher elevation-HL and more sloped land are mostly located in
steeply-mountainous areas. Since the availability of transportation is limited in these areas, it often takes much time for people in these areas to attain social resources indispensable for their everyday life. Due to the limited availability of flat land, private houses and public organizations
have no choice but to be located far from one another. This results in low population density in a community and growing obstacles to neighbors’ exchanges and distribution of information. These areas suffer from a twofold suicide risk factor, namely the poor accessibility to social resources and the obstacles to social support. The result showed that the more the land is sloped, the more Suicide-SMR is
influenced. In particular, the spline curve rapidly ascends for slope-HL above 15 degrees. Despite of smaller frequency of occurrence, the confidence interval is relatively small and represents a high level of risk and its multiplication. As explained so far, elevation is not necessarily a risk factor. However, the degree of risk factor may rapidly increase if a factor of steep slope is added.
Influence of climate on suicide rate
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An analysis of climatic conditions showed that many of the areas with low suicide
incidence are municipalities with longer daylight hours and smaller snow accumulation. Relations between climatic conditions and suicide have been reported
by numerous previous studies both domestically and internationally. However, results of the analyses are not self-consistent. According to a review by Ajdacic-Gross et al in 2010, it would be impossible to universally grasp the influence of climate on suicide. 16 The finding from this study, that the areas with low suicide incidence have long daylight hours and less snow, may be dependent on coastal area attributes and other factors that are unique to areas with low suicide incidence. It remains to be seen how this is elucidated. The finding agrees with the discussion on indirect influence of geographical
characteristics on suicide rate, which will be mentioned later.
Effectiveness of visualization of the result of analysis We could review the knowledge obtained from this research by visualizing the
result of analysis on the map of Wakayama prefecture. Although there is largely different distribution of suicide rate in the same prefecture, it had not been recognized for long time.
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We could also gain clearer understanding that the areas with high suicide incidence
tend to exist in the areas with steep slopes in the prefecture. That supported our hypothesis and result of the analysis. The map colored by GIS (Geographic Information System) is a material easy to
understand the problems, and should be quite helpful to share the information among various parties in charge of suicide prevention.
Conclusions Our study showed that the strongest factor among geographical characteristics to
raise suicide rate is slope of habitable land. It is necessary to take the characteristics of each community into consideration, when we work out measures of suicide prevention. In this study, we focused on the relation between geographical characteristics and
local suicide rate. We have not done research on the other factors to influence mental
health of the local people, such as quality of medical services, deterioration of social network or decreasing birthrate and aging of the population. The results from our questionnaire survey conducted in Tokushima prefecture
showed that people living under severe circumstances tend to acquire patience and self-restrained behavior and the habitants in steep mountain area with poor
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accessibility felt stronger resistance to seek for help, compared with them in coastal area with good accessibility. Though we have not conducted the questionnaire survey in Wakayama, as far a s we
interviewed the local habitants and the persons in charge of health and welfare
services, our impression coincides with the previous study. That is f uture topics of discussion.
ACKNOWLEDGMENTS The study did not receive any specific grants.
CONFLICT OF INTEREST STATEMENT The authors have no conflict of interest to declare.
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TABLES Table 1. Analysis of correlation between Suicide-SMR and topographic and climatic variables
P opulation
Ar e a
Sui cid e SM R
P opulation
P opulation
El e va tion
Slop e o f
Ave r a ge
den sit y
den sit y o f
of
habi t abl e
te mp er a tur e
habi t abl e
habi t abl e
land
land
land
Ra in fa ll
D a yli gh t
Sno w
hours
a cc u mu l atio n
Cor re l atio n -.302
.314
-.456
-.473
.276
.267
-.321
.122
-.323
.263
.000
.000
.000
.000
.000
.000
.000
.000
.000
.000
co e ffi ci en t Si gn i fi c an ce proba bil it y (both sid e s )
SMR: standardized mortality ratio
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Table 2. Multi-regression analysis with Suicide-SMR as dependent variable
(Constant)
Non-standardized coefficient
B
Standardized
Diagnosis of collinearity
coefficient
Standard
Beta
t-value
Significance
VIF
probability error 197.808
10.627
18.613
.000
2.844
.201
.240
14.121
.000
1.288
habitable land
-16.658
1.440
-.201
-11.572
.000
1.349
Deepest snow
.194
.023
.173
8.526
.000
1.837
Daylight hours
-.028
.005
-.105
-5.265
.000
1.770
Coastal area attributes
-7.675
1.835
-.072
-4.182
.000
1.322
Island attributes
-5.393
3.163
-.029
-1.705
.088
1.262
Slope
Population density of
Dependent variable: suicide standardized mortality ratio (SMR). Weighted least square method with standard error of suicide SMR Conditioned R2 = 0.256 n = 3318 VIF: variance inflation factor
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FIGURE LEGENDS Figure 1. Influence of elevation-HL and slope-HL on Suicide-SMR Figure 2. Visualization of relation between slope of habitable land and suicide rate on the map of Wakayama Prefecture
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