地球環境研究,Vol.11(2009)

Influences of the Weather on Mental Status in
Okayama and Tottori, Japan
YAMATO Keiko＊, FUKUOKA Yoshitaka＊＊, HOPPE
Peter＊＊＊

Keywords: suicide, meteorological factor, regression analysis
Tottori in winters is only a half time long in

1. Introduction

Okayama. (See the Table in next page.)

Weather sensitivity (Wetterfuhligkeit)Anyone is weather-reacting. According to a survey(von Mackensen and Hoppe,
2001) to 55％ of population is afflicted by weather condition in Germany.

Data Source
We have got monthly data (January 2001 -The results show, 19.2％ of the asked think that theirDecember 2006 per month) on:

health in strong measure on the weather depends.

・suicides from Ministry of Health, Labour andPurpose of this Study

Welfare of Japan and Okayama and Tottori Prefec-

We got started this study because Yamato is also ature'weather-sensitive' person. In this thesis we aim to・crimes and traffic accidents from National Police

find relationships between the weather condition

Agency and Okayama and Tottori Prefectural(temperature, relative humidity, air pressure, andPolicesunshine duration) and human emotions (suicides,
crimes, and traffic accidents) based on statistics.

・meteorologicalfactors(temperature,

relative

humidity, air pressure, sunshine duration, andweather) from Japan Meteorological Agency
・population from Statistics Bureau, Ministry of

2. Materials and Methods

Internal Affairs and Communications

We will compare climate of 2 southwestern Japa-

We wanted to gather daily data because it is better

nese cities-Okayama and Tottori-, because Okayama

to verify a hypothesis -correlation between the humanis my hometown.

emotion and the weather-, but I could not get them on
2

Tottori (35°29.2' N, 134°14.2' E; 3507km ) lies on thenorth side of Okayama (34 °39.6' N, 133 °55.0' E;

account of privacy problems, especially on the field ofsuicide deaths.

27009km ) in Japan. They are relative warm andhumid Japanese cities. But they have a little different

3.5. Hypothesis

climate by reason of the Sea of Japan and big moun-Suicidestains.
Okayama has a population of about 1955 thousand
and Tottori 604 thousand.

We think there is a relationship of suicides especially with sunshine duration. In my opinion where
the sun shines short, there are more suicide deaths. In

Here are tables of weather of Okayama and Tottori.

the respect that person gets depressed when it is

They show the relative humidity in Tottori is rela-cloudy or rainy. So I will show the distribution maps

tively higher than Okayama throughout the years.

of sunshine duration and suicide deaths in Japan. As

What we should say is that the sunshine duration of

the maps show, my hypothesis might be right.

＊

Meteorological Institute,Ludwig-Maximilians-University of Munich
Department of Environmental Systems, Rissho University＊＊＊
Munich Reinsurance Company, Germany＊＊

201

Influences of the Weather on Mental Status in Okayama and Tottori, Japan (Yamato, Fukuoka, Hoppe)
Fig.3-7: Sunshine duration (Japan Meteorological Agency, Normals 1970 - 2000) and suicides (Ministry of Health,Labour and Welfare of Japan, 2006) in Japan.

Fig.3-8: Mean temperature and relative humidity (Japan Meteorological Agency, Normals 1970 - 2000) and crimes
and traffic accidents (National Police Agency of Japan, 2006) in Japan.

202

地球環境研究,Vol.11(2009)

Crimes and Traffic Accidents

at each year. Comparing of Okayama and Tottori, it

On crimes and traffic accidents there are relation-is higher in Tottori throughout the year, especially inships with temperature and relative humidity. Crimes

winter because of snow. In June we have the rainy

and traffic accidents occur oftener at high tempera-

season and we can see the relative humidity is high.

ture and humidity, We think. That is because person

Sunshine Duration

gets impatient when it is hot and humid. Here are

Sunshine duration in h is long in spring to summer,

distribution maps of mean temperature, relativeand particularly short in winter. In Tottori it is al-

humidity, crimes, and traffic accidents. We can notmost a half time of it in Okayama in winter. Because

exactly mention that crimes and traffic accidentsof the rainy season the sunshine duration is short in

relate with the temperature and relative humidity.

June. There are different trends at each year. In 2003
there is no great difference in each season.
Air Pressure

Methods

Air pressure in hPa is low in June to August (sum-First we made graphs from the statistics and gave
careful consideration to a tendency. Then we did regression analyses with excel and got correlation coefficients of them.

mer) and high in winter. No difference appears
between both cities and in each year.
The weather in Okayama and in Tottori is shown in
the Table 4-1. It is similar in spring, summer, andautumn, but in winter is changeable in Tottori and it
has more snowfalls. Okayama has apparently more

3. Results

sunny days than Tottori. So we say in Japan,

3.1. Trends of Statistical Data

Okayama is sunny land. In Okayama it dose not often

3.1.1. Meteorological Data

snow. In spring (March to May) it is sunny or cloudy(See also tables in page XX.)in the both cities. They have more cloudy days in sum-

We have got the meteorological monthly data onmer (June to August). In autumn (September to No-

sunshine duration, mean temperature, and air pres-vember) there are many sunny days. In Okayama it issure from January 2001 to December 2006 (sixalmost fair weather, on the other hand it snows some-years＝72 months) and normals from 1971 to 2000

times in Tottori in winter (December to February).

and seasonally statistics from Spring 2001 to Winter2005 (5 years＝20 seasons, spring: March to May,
summer: June to August, autumn: September toNovember,

winter:DecembertoFebruary)

3.1.2. Emotional Data
- Suicides, Crimes, and Traffic Accidents -ofTo easily compare the two cities - Okayama andOkayama and Tottori, and the data of all Japanese

Tottori -, we convert these all data into per 100 thou-cities from Japan Meteorological Agency.

sand population.

Mean Temperature

Statistics of Suicides

As mentioned in the chapter 3, the monthly andWe have got the monthly data on suicides in 2001 -seasonally mean temperature in ℃ is high in July and2006 from Ministry of Health, Labour and Welfare

August (summer) and low in December to February(MHLW) of Japan and Okayama and Tottori Prefec-(winter). There are no different trends between

ture. Honestly said, we wanted get them from the

Tottori and Okayama, or each year.

police, because the statistics from the Police Agency
covers total population (including foreigners in

Relative Humidity

Japan), while MHLW covers only Japanese living in

Relative humidity in ％ is relatively high in sum-

Japan. But the Police Agency has disadvantage former and low in spring, but there are some differences

me or for my study too. It counts numbers based203

Influences of the Weather on Mental Status in Okayama and Tottori, Japan (Yamato, Fukuoka, Hoppe)on the time of discovery of corps (more precisely

offenses, violent offenses, larceny offenses, intellec-"recognition"), while MHLW dose so based on thetual offenses, moral offenses, and other offenses. We

time of death and the living place ("Overview ofhave got the statistics of total number cases known to

Suicides"In

the police, total cases cleared up, and total arrestees

Okayama Prefectural Police dose not count and haveand all kinds of the crimes in 2001 - 2006 from theany monthly data on suicides.

Okayama and Tottori Prefectural Police. In this

by

the

National

PoliceAgency).

thesis we will take only the total number cases known
In Japan more 30000 people commit suicide andto the police, because we think total cases cleared upthey are 3 times more than deaths by traffic accidents

and total arrestees are not related with the weather(Ministry of Health, Labour and Welfare of Japan,

condition or human emotions. But there is an interest2003).

survey that the rates of total cleared up in Tottori(more than 50％) are higher than in Okayama (ca.
30％). Person says offenders escape to a northern city
and will be arrested because it is a small country.

Throughout the year total cases of crimes arehigher in Okayama. In winter are the crimes relative
less than in summer, but we can not say exactly.
It appears that suicide death rates in Tottori arehigher than in Okayama. We think it because of theshorter sunshine duration in Tottori. But at thepresent time we can not mention in which season they
have the peak.
In the figures below, we can see the suicides bysexual. In both cities the suicide death rates by maleare almost always higher than by female. It is because
the men are psychic weaker than the women or there

Data on Traffic Accidents

are the causes of suicides, not only meteorological

We have got the data on traffic accidents in 2001 -factors but also social, financial factors etc., we think.

2006 and partly by the weather 1997 - 2006 from the
Okayama and Tottori Prefectural Police.

The traffic accidents have the peak in December in
the almost all year. In Okayama the traffic accidents
occur more than 2 times often in Tottori. Okayama
has 5th many traffic accidents and Tottori 44th of all
47 Japanese cities. we heard, in the respect that people
in Okayama are more aggressive than those in
Tottori because of the climate.

Data on Crimes
There are many kinds of crimes, e.g. felonious

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地球環境研究,Vol.11(2009)

In the Table 4-2 traffic accidents on a sunny,would be more careful on cloudy or rainy days, there-

cloudy, rainy, foggy, or snowy day are shown. Eachfore it happens less. In Okayama there are more traf-

value is divided by the days of the weather (see Table

fic accidents in snowy days than in Tottori. That is

3-1 and 4-1). We can see that many traffic accidents

because, we think, Okayama does not often snow.

mostly happen on sunny days. In our opinion, people

3.2. Results of Regression Analysis
Table 4-3: Correlation coefficient R from the data
72 Months

Year 01

Year 02

Year 03

Year 04

Year 05

Year 06

SeasonSample Size N

72

12

12

12

12

12

12

20

4 Parameters

0.443

0.409

0.609

0.685

0.632

0.599

0.717

0.695

2 Parameters

0.249

0.341

0.577

0.500

0.315

0.301

0.231

0.595

Temperature

0.077

0.242

0.448

0.106

0.211

−0.003−0.2140.325

Rel. Humidity−0.193−0.177−0.222−0.349−0.074−0.2830.004−0.329Sunshine Dur.

0.283

0.372

0.594

0.344

0.508

0.393

−0.057

0.556

Air Pressure−0.248−0.301−0.446−0.333−0.244−0.296−0.017−0.530

4 Parameters

0.381

0.757

0.675

0.657

0.664

0.895

0.673

0.353

2 Parameters

0.279

0.597

0.547

0.348

0.507

0.853

0.359

0.336

Temperature

0.193−0.005

0.547

0.330

0.489

0.842

0.314

0.260

Rel. Humidity

0.257

0.579

0.145

0.274

0.164

0.165

0.276

0.298

Sunshine Dur.

0.073

0.003

0.249

0.224

0.328

0.363

0.378

−0.021

Air Pressure−0.0750.344−0.362−0.146−0.411−0.637−0.149−0.1624 Parameters

0.659

0.887

0.650

0.335

0.714

0.562

0.699

0.698

2 Parameters

0.415

0.728

0.582

0.096

0.506

0.235

0.124

0.635

Temperature

0.220

0.531

0.400

0.068

0.138

−0.091

0.114

0.360

Rel. Humidity

0.407

0.610

0.519

0.093

0.480

0.171

−0.0050.622

Sunshine Dur.

0.133

0.500

0.039

0.095

−0.116

0.051

0.448

−0.145

Air Pressure−0.058−0.204−0.282

0.064

0.127

0.045

−0.093−0.1634 Parameters

0.327

0.253

0.514

0.593

0.700

0.771

0.500

0.759

2 Parameters

0.292

0.226

0.388

0.405

0.495

0.350

0.495

0.598

Okayama

SuicidesCrimesTraff.Acc.

Tottori

SuicidesCrimesTraff.Acc.

＊

Temperature

0.222

0.196

0.095

−0.041

0.427

0.288

0.388

0.222

Rel. Humidity−0.198−0.111−0.387−0.396−0.195−0.2520.321−0.580Sunshine Dur.

0.327

0.228

0.325

0.470

0.360

0.547

0.152

0.634

Air Pressure−0.213−0.152−0.2320.091−0.627−0.059−0.266−0.205

4 Parameters

0.542

0.768

0.829

0.774

0.320

0.890

0.864

0.740

2 Parameters

0.502

0.741

0.585

0.624

0.145

0.810

0.737

0.574

Temperature

0.491

0.739

0.585

0.608

−0.094

0.809

0.613

0.571

Rel. Humidity−0.1230.059−0.191

0.050

0.098

−0.194−0.387−0.022Sunshine Dur.

0.373

0.620

0.402

0.576

−0.225

0.637

0.664

0.285

Air Pressure−0.339−0.532−0.306−0.4790.162−0.575−0.790−0.3434 Parameters

0.354

0.636

0.641

0.749

0.404

0.489

0.860

0.548

2 Parameters

0.104

0.434

0.402

0.230

0.391

0.317

0.306

0.272

Temperature−0.0790.410−0.268−0.067−0.370−0.2820.085−0.271

Rel. Humidity

0.069

0.147

0.372

−0.230

0.078

0.198

−0.291

0.057

Sunshine Dur.

0.025

0.361

−0.4570.084−0.252−0.1390.471−0.061

Air Pressure

0.216−0.254

0.449

0.397

0.389

0.278

0.166

0.323

4 parameters: temp., rel. humidity, sunshine duration, air pressure; 2 parameters: temp., rel. humidity

205

Influences of the Weather on Mental Status in Okayama and Tottori, Japan (Yamato, Fukuoka, Hoppe)With excel calculated correlative coefficients R are

In general the correlations of suicides with the rela-

shown on the Table 4-3 and what significant at thetive humidity and the air pressure are negative, while

5％ risk are written in boldface and what in randomsuicide deaths are positive correlated with the mean

relationship are in italic. The acceptable coefficients

temperature and the sunshine duration.

are more than R＝0.576, 0.444, and 0.233 at the 5％

We thought the suicide death rates increase withsignificance level for the sample size N＝12, 20, and 72.

decreasing sunshine duration. And it is shown in the

Many correlation coefficients are significant by
four

distinct

parameters(temperature,

relativeassociation

betweenthesuicidesandsunshineduration in all 47 Japanese cities (See figure below).

humidity, sunshine duration, and air pressure) or
two parameters (temperature and relative humidity).
But it is difficult to say which meteorologicalfactor(s) or which weather condition(s) is/arestrongly correlated with the human emotions bysuicide death, crimes, and traffic accidents at thepresent.
We can also see that the suicide deaths are positive

The correlation coefficient: R＝ − 0.383 (More than
0.289 is significant at N＝47 cities.)

associated with the mean temperature and thesunshine duration and negative with relative humid-

But in our results, as we mentioned before, we canity and the air pressure in both cities. The crimes are

see the positive correlation. It means a man can

positive correlated with the mean temperature,commit suicides while sun shines. In Japan person

relative humidity and sunshine duration in Okayama,

also says that suicides increase in the springs, espe-

positive with the temperature and sunshine duration

cially under continuation of warm sunny days.

in Tottori, and negative with the air pressure in both

According to a statistic (Eto, 1990), those whocities. The traffic accidents are positive correlated

commit suicide increase by durations of sunshinewith the temperature, the relative humidity andlong.

sunshine duration and negative with air pressure in
Okayama, and positive with the relative humidity andair pressure and negative with the temperature andsunshine duration in Tottori.

3.3. Meteorology and Suicides
According to the results on the Table 4-3, multiple
regressions of the suicides with four parameters(temperature, relative humidity, sunshine duration,

Suicides and Temperature

and air pressure) are positive and relatively high in

Now we enlarge the results with figures.

both cities (Okayama and Tottori). But we can not

The relationship of suicides with the mean tempera-

say what it means because of its complexity. With

ture alone is not so high in our results. We were

two parameters (temperature and relative humidity)

honestly surprised, but we can also image that it

are shown relatively strong positive correlations.

could be indifferent to someone who will commit

Thus we might mention that a person could suicide

suicide whether it is hot or cold.

himself in the hot (or warm) and humid weather. We
can see also that there is the relationship between
suicidesOkayama.

206

andsunshineduration

especiallyin

Suicides and Relative Humidity
As we said, there is the negative correlation
between suicides and relative humidity. It means that

地球環境研究,Vol.11(2009)a person could be murdered by himself. According to
the results however, the relation is not so strong.
In the figure below we can see a sample correlation

In the next two figures are given seasonally datefrom 2001 to 2005. We can see the correlation coefficients and also the values of R2 are relatively high.

of suicides with the relative humidity. They areseasonally data, these mean spring, summer, autumn,
and winter from 2001 to 2005. The value of R2 is also
relatively high.

The correlation coefficient: R＝＋0.556 (More than
0.444 is significant at N＝20 seasons in both cities.)

The correlation coefficient: R＝ − 0.580 (More than
0.444 is significant at N＝20 seasons.)

Suicides and Sunshine Duration
We can see the relative strong and positive relationship of suicides with the sunshine duration. Accord-

The correlation coefficient: R＝＋0.634

ing to the results, we could say that the correlation isa little stronger in Tottori than in Okayama. That is
because, as we mentioned, there are more suicides in
Tottori and duration of the sunshine in winter is ahalf in Okayama.
The two figures below are monthly data of suicides
from 2001 to 2006.
The correlation coefficient: R＝＋0.594 (More than
0.576 is significant at N＝12 months.)
We can see in the figure on the preceding page themonthly data in 2002 in Okayama. There is a weakcorrelation between the suicides and the sunshine duration. We might say the value of R2 is relativelyhigh.
The correlation coefficient: R＝＋0.283 (More than
0.233 is significant at N＝72 months)

Suicides and Air Pressure
From the Table 4-3

we can read that the monthly

and seasonally relationship in Okayama is stronger
compared with that in Tottori from 2001 to 2006.
Here in the figures are shown that suicides arenegative correlated with the air pressure, as mentioned above. In 2004 we had a strong correlation in
Tottori. The value of R2 is also high.
The correlation coefficient: R＝＋0.327

207

Influences of the Weather on Mental Status in Okayama and Tottori, Japan (Yamato, Fukuoka, Hoppe)
cities. With four parameters (temperature, relative
humidity, sunshine duration, and air pressure) andwith two parameters (temperature and relative
humidity) are shown relatively strong positive
relationships. The correlations with the mean temperature and the sunshine duration are especially in
Tottori very significant.
The correlation coefficient: R＝ − 0.248 (More than
0.233 is significant at N＝72 months.)

Our hypothesis was that there is a relationship ofcrimes with temperature and relative humidity.
According to the results we can mention that it might
be right.
Now we will see the results in detail.

Crimes and Mean Temperature
As mentioned above, the correlation between crimes
and the mean temperature is positive. We can see
The correlation coefficient: R＝ − 0.530 (More than
0.444 is significant at N＝20 seasons.)strongercorrelationofTottori

than

that

of

Okayama. A Policeman in Tottori meant there arefewer (less) crimes in winter because it is very cold
and the ground is covered with snow. In Okayama is
not so colder than Tottori and there is mostly notcovered with snow.

The correlation coefficient: R＝ − 0.627 (More than
0.576 is significant at N＝12 months.)

The correlation coefficient: R＝＋0.491 (More than
0.233 is significant at N＝72 months.)

In both cities we can see positive R＝0.391(Okayama) and negative R＝−0.400 (Tottori). The
values are relatively high, we think. It means that in
Okayama people commit suicides on not-sunny days
und in Tottori on sunny days.

The correlation coefficient: R＝＋0.571 (More than
0.444 is significant at N＝20 seasons.)

3.4. Meteorology and Crimes

We can see in the figures below the significant

When we see the Table 4-3 we can know that thecrimes are negative correlated with the relative
humidity in Tottori and with the air pressure in both

208

results in each year, and the values R2 of those arealso higher than the others.
In Okayama the correlation was significant only in地球環境研究,Vol.11(2009)2005. But we think it is the best result of all.

The correlation coefficient: R＝＋0.613
The correlation coefficient: R＝＋0.842 (More than
0.576 is significant at N＝12 months.)

Crimes and Relative Humidity
The results in the Table 4-3 (see page XX) are
shown that crimes are generally positive correlatedwith the relative humidity in Okayama and negativein Tottori. But the relationship is not so strong. Especially in Tottori we can see no significant results.

The correlation coefficient: R＝＋0.739

The correlation coefficient: R＝＋0.257 (more than
0.233 is significant at N＝72 months)

The correlation coefficient: R＝＋0.585

The correlation coefficient: R＝＋0.579 (More than
0.576 is significant at N＝12 months.)
The correlation coefficient: R＝＋0.608
Crimes and Sunshine Duration
In opposite we can see the correlation of crimes
with the sunshine duration only in Tottori. We canmention why. In any case it is not strong by the long
periods (72 months and 20 seasons).

The correlation coefficient: R＝＋0.809

209

Influences of the Weather on Mental Status in Okayama and Tottori, Japan (Yamato, Fukuoka, Hoppe)


Crimes and Air PressureWith the Air Pressure we can read the negative
relationship of crimes. A person often commits crimes
under the low pressure. It sometimes means it is nota fine weather.
In general the results are not significant. But thefigure of 2005 in Okayama and that of 2006 in Tottori
The correlation coefficient: R＝＋0.373 (More than
0.233 is significant at N＝72 months.)

show the good correlation between crimes and the airpressure.

The correlation coefficient: R＝＋0.620 (More than
0.576 is significant at N＝12 months.)

The correlation coefficient: R＝ − 0.339 (More than
0.233 is significant at N＝72 months.)

The correlation coefficient: R＝＋0.576

The correlation coefficient: R＝ − 0.637 (More than
0.576 is significant at N＝12 months.)

In 2005 and 2006 we can see the higher correlation
coefficients and R2.

The correlation coefficient: R＝−0.790
The correlation coefficient: R＝＋0.637
3.5. Meteorology and Traffic Accidents
In the Table 4-3 (see page XX) it is shown that
traffic accidents are not particularly associated withthe meteorological factors. Only with four or two
parameters we can see the correlation of traffic accidents. These are surprising results for us.
The relationships between traffic accidents and the
The correlation coefficient: R＝＋0.664

210

individual factors (the mean temperature, the relative

地球環境研究,Vol.11(2009)

humidity, the sunshine duration, and the air pressure) are weak, and we do not exactly know whether
the association is positive or negative.

4. Conclusion
Heretofore we have tried to analyze and consider
the influences of the weather on the human emotions.

There are a few significant results with the relative
humidity in Okayama.

We really wondered that there are relatively big influences of the weather. There are certainly not only theweather influences, but also the social influences, e.g.

Traffic Accidents and Relative Humidity
In the next figures we can read the positive correlation between traffic accidents and the relative humid-

human relations, financial problems, etc. In our
opinion, the weather is one of the stressers that cause
the suicide deaths, crimes, and traffic accidents.

ity. The correlations coefficients of the long-term
periods (72 months and 20 seasons) show are rela-Temperature, relative humidity, and sunshine

tively high. Maybe we could mention that the values

durations are meteorological factors on the feeling of2of R are also high in 20 seasons and the year 2001.

warm or cold. Human bodies are controlled by the
homeostasis that keeps the temperature constant.
When the body temperature rises or sinks 2℃, humancan become sick. Compare with the human body themeteorological environments surrounded us changevery fast. Then the homeostasis controls our body,but the changes of the weather could be stress for us.

The correlation coefficient: R＝＋0.407 (More than
0.233 is significant at N＝72 months.)

Human bodies have seasonal changes. On autonomic nervous system parasympathetic tense in summer and sympathetic in winter. Human bodies are
responsive to stimulations as reflex though the nervous system. When the stimulations continue it change
physiological reaction of internal secretion and thenhabituation. On an uncomfortable day a person could
be emotional instable because the change of the system is big. People who have argy, problems with auto-

The correlation coefficient: R＝＋0.622 (More than
0.444 is significant at N＝20 seasons.)

nomic

nervoussystem,internal

secretion,or

psychological problem can excessively react tostimulations. Then their autonomic nervous systemor hormones can not smoothly respond to it and theircondition or mind are harmful influenced by meteorological changes. That is why seasonal disease andmeteorological disease exist. It is closely related
between health and psychology. On healthy people
also the system can change with meteorological
The correlation coefficient: R＝＋0.610 (More than
0.576 is significant at N＝12 months.)changes.

5. Problems of the Survey
We took the statistics of two cities in Japan. But we

211Influences of the Weather on Mental Status in Okayama and Tottori, Japan (Yamato, Fukuoka, Hoppe)
also wanted to compare with Germany because weReferences

study there.

Hick, C. and Hick, A. (2006): Intensive course of physiology. Elsevier, Munich. (in German)

The data were too scarce for the survey. We could
send out questionnaires to people or we could be thereagent of the survey myself.

Hoppe,
P. (1997): Aspects of human biometeorology in past,
present and future. Int J Biometeorol 40: 19-23
Kagami, M. (1991):Weather and Healthm Kodansha (inJapanese)
Yoshino, M. and Fukuoka, Y. (2002): Medical weather fore-

We wanted to have the daily statistics of suicides,

cast. Kadokawa, Tokyo. (inbecause it could be deeply analyzed the humanemotions with the weather conditions. But in Japanthe data are not released because of privacy problems.

Influences of the Weather on Mental Status in
Okayama and Tottori, Japan
YAMATO Keiko＊, FUKUOKA Yoshitaka＊＊, HOPPE
Peter＊＊＊
＊

Meteorological Institute,Ludwig-Maximilians-University of Munich＊＊
Department of Environmental Systems, Rissho University＊＊＊
Munich Reinsurance Company, Germany

keywords: suicide, meteorological factor, regression analysis

212