Effects of Suicide Rate

Introduction

Each case of suicide intimately effects at least 6 other people. So what causes people to want to commit suicide? What has the biggest effect on the suicide rate? Is it the poverty rate? Or possibly the population density? Maybe it's the percentage of sunny days? My research proposal is based on the question: What effect does the percentage of sunny days in each state have on that state's suicide rate? My hypothesis is the percentage of sunny days has a large effect on a state's suicide rate. I think that if a state is not very sunny then the suicide rate will be higher because of the depression that sets in from the lack of sun. I will also test the effect that the population density, poverty rate, divorce rate, and unemployment rate has on the suicide rate.

Literature Review

E.A. Deisenhammer did a study on the meteorological factors and effects on suicidal behaviors. The investigation included a statistical relationship between weather parameters with attempted and/ or completed suicides. In order to form data, Deisenhammer researched papers and other studies to find a relationship between the two. A total of 27 studies were found that included these parameters. It was found that most of these papers reported that suicidal acts were caused by at least one weather factor; however the results were contradictory and inconclusive. Deisenhammer concluded that it was not possible to identify a single weather condition that directly affected suicidal acts because there were also social effects that may have caused suicidal behavior.

My results were similar Deisenhammer's results, as I found that the percent of sunny days in a state was not the only factor on the suicide rate. Factors such as population density, unemployment rate, and divorce rate, also affected the suicide rate in each state.

Model

I believe that the percentage of sunny days in a state has the biggest effect on the suicide rate in that state because weather has such a high effect on most people's mood and mental state. Population density may affect suicide rate because when someone lives in a state that is not very dense, people do not have as much contact with other humans. Conversely, if the state has a density that is high, a person may feel cramped of their personal space. Poverty rate and unemployment rate could go hand in hand in affecting the suicide rate because when someone is living in a state where poverty surrounds them, it could have them feeling trapped and depressed that they cannot overcome the pressures of living without money. Divorce rate might affect suicide rate because once someone divorces their partner, they may feel like there is nothing else to live for.

Data

For this study, I used State Rankings 2010 to retrieve the data for each variable. I then used the PASW Statistics 18 software to run the data and formulate graphs.

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta

1 (Constant) 9.643 3.025 3.188 .003

%sunny .034 .042 .088 .824 .415

PopDens -.008 .002 -.559 -4.318 .000

PovRate -.154 .138 -.133 -1.113 .272

DivRate 1.197 .421 .337 2.843 .007

UnemRate -.030 .188 -.020 -.162 .872

a. Dependent Variable: SuiRate

The dependent variable is the suicide rate in each state (SuiRate). The independent variables are: percentage of sunny days in the state (%sunny), the state's population density (PopDens), poverty rate by state (PovRate), divorce rate (DivRate), and unemployment rate (UnemRate).

The estimated coefficient for the independent variable measuring the percentage of sunny days is .034. This means that as the percentage of sunny days increases, the suicide rate increased by an estimated 3.4%, holding everything else constant. I believe that the suicide rate should decrease as the percentage of sunny days increases, so the positive slope is unexpected. The standardized coefficient is 0.088, which means that the suicide rate changes by 0.088 standard deviations when the percentage of sunny days changes by one standard deviation. This is a very small response, and is the second smallest relative response for all the independent variables.

The estimated coefficient for the independent variable population density is -0.08. This means that as the population density increases, the suicide rate decreased by an estimated 8%, holding everything else constant. I believe that when the population density is at its extremes, the suicide rate would increase, so the negative slope is acceptable. The standardized coefficient is -0.559, which means the suicide rate changes by 0.559 standard deviations

...