Nationwide Analysis of the Causes of Death in Males and Females for the Year 2010: A Comparative Study

Abstract

The top ten causes of death for males and females in the Northeastern, Southern, Midwestern, and Western regions were gathered from the Center for Disease Control to assess if causes of death differ between males and females for all age groups according to statistics for the year 2010. Based upon the frequency distribution, and the z-scores for each age group for both males and females in the four nation regions, the findings indicate the following.

Introduction

Within this paper, the variability between men and women’s top ten causes of death will be examined within the framework of statistics gathered from the Center for Disease Control. A complete picture of the United States’ men and women’s mortality rates was garnered from data reflecting the causes of death for the people within the Northeastern, Southern, Midwestern, and Western regions for the year 2010. A review of the literature will reveal how the statistics for the disparity between men and women in the causes of death is used in the field of psychology to understand non-death issues associated with the cause of death. The method used to gather the data will be discussed, followed by the results of the statistical analysis and the discussion. Since it was requested for this particular assignment that specific statistical results are included in the Discussion section rather than the Results section, I have combined the Results and Discussion sections to answer the assigned questions and complete this assignment as requested. 

A review of the literature in the study of the difference in causes of death between men and women in the field of psychology reveals a wide array of research questions to illuminate non-disease factors, such as personal habits and lifestyle, and how they contribute to the cause of death, with the intention of improving quality of life and increasing life expectancy. Moreover, the period of time one studies in causes of death makes a difference in the factors observable and inferred from the data.

Causes of death for men and women are often assessed to correlate the diseases or other non-disease causes to more intangible, quality of life issues (Case and Paxon, 2004, p. 1). For example, Case and Paxon (2004, p. 1) determined the causes of death in men and women in light of self-perceived quality of life for identical illnesses. In terms of identical illnesses for both sexes, Case and Paxon (2004, p. 7) found in studying the morbidity data and rates of men and women suffering from identical illnesses, the mortality rates were the same, while their perceived quality of life differed. 

According to some researchers, the differing causes of death between genders can be used to understand the quality of life issues associated with the causes of death, as well as solve other puzzles, such as explaining the widening gap between the life expectancy of men and women. Wong, Chung, Boscardin, Li, Hsieh, Ettner, and Shapiro (2006, p. 747) stated observing the difference of causes of death in men and women can help clarify the growing trend of women living longer than men. For instance, at the turn of the 20th century, women lived two years longer than men, whereas one hundred years later, the gap has grown to five years. Wong et al. (2006, p. 747) stated that studying the difference in causes of death between genders is a great starting point to help address the factors contributing to chronic illnesses, such as heart disease, and sudden death scenarios, such as violent acts or suicide.

In many studies in this area, researchers might consider a block of time to discover if the data reveals any trends over a period of years, sometimes even decades, as Hoyert (2012, p. 1) explained. Year to year analysis of causes of death are less fruitful than seeking trends in data over a matter of decades, specifically when it comes to the study of the differences between cause of death in males and females (Hoyert, 2012, p. 4). For instance, Hoyert (2012, p. 1) observed for both genders, while the number of deaths increased over a period of seventy-five years ranging from 1935 to 2010 because of the growing population, the percentage of deaths for the total population fell as an overall trend. Along with longer life spans, the trend of a decline in the risk of dying decreased overall for that period for both men and women. While considering the death rates for a specific year can be enlightening, to observe real trends in causes of death for men and women, one must look to a longer length of time, Hoyert (2012, p. 4) explained.  At times, the causes of death for each gender might simply reflect higher rates for one cause for a period of time than others. Depicting trends in the data can point to areas that need to be further researched in understanding the difference in causes of death between genders, Hoyert (2012, p. 4) stated.   

For the purposes of this study, nationwide data for the causes of death for men and women was collected and analyzed to understand which diseases were most prominent in both men and women for the year 2010, as explained in the Method section. The Results section will reveal whether or not there was a difference in causes of death for men and women for the year 2010, followed by a discussion of the findings.   

Method

To assess whether or not the causes of death differed for men and women in 2010, statistics for the nation were gathered from the Center for Disease Control (CDC) WONDER database (n. d.). The top ten causes of death for all races and age groups were gathered for males and females across the nation in the four geographical regions; Northeastern, Southern, Midwestern, and Western regions. Since gender is a nominal variable in this study (Howell, 2011, p. 24-25), a comparison of the central tendencies in the men and women data were computed to highlight the differences in causes of death between the genders.

Results and Discussion

As stated in the introduction for this study, the unique aspect of the assignment requires a discussion centered around six questions: The discussion will address six questions in particular, describing the hypothesis and null hypothesis of this study, the type of research design, depicting the independent variable and dependent variables, the frequency distribution of the causes of death for men and women in the four regions, a computation of the mean number of “unintentional injury” deaths for each gender, which inferential statistic is most appropriate to determine whether males and females differed in causes of death, whether or not the null hypothesis was accepted or rejected, and determining if there is a difference between the genders for each of the top ten causes. Because of the unique nature of the required discussion, and because of the request to include statistical results in the Discussion section, I have combined the Results and Discussion section to complete the requirements of this assignment. The required results and the discussion are listed and answered in turn below.

Question 1

What is the research hypothesis(es) and what type research (of) question does it represent (descriptive, relationship, difference)?

The hypothesis and null hypothesis for this study are as follows:

H1: The causes of death differ between all males and females in the nation in 2010.

H0: The causes of death do not differ between males and females in the nation in 2010.

The research design is to determine the difference between males and females. According to Howell (2011), a research question that centers upon the difference in data between two groups is a difference research question.

Question 2

What is the independent variable? What are the dependent variables?

According to Howell (2011), the independent variable is the variable the researcher is testing, and the dependent variable is the variable that stays constant. Gender in this study is the dependent variable because it is the constant. The independent variable is the causes of death data. The independent variable is the variable under examination, the causes of death data for both males and females, which vary according to gender, the dependent variable.

If the researcher were to consider all the four geographical regions separately (Northeast, South, Midwest, and West), as well as take into consideration the combined statistics reflecting cause of death for the entire nation, the four regions would be another dependent variable because it is constant and does not fluctuate (Howell, 2011). The death rates for men and women by region would be the independent variable. In other words, we can assess whether or not men and women’s cause of death data differ by nation and by regions within the nation. In both cases, gender differences are the data we are experimenting with; therefore, it is going to be the independent variable in both cases.

Question 3

Construct a frequency distribution, based upon the data set provided.

(Table 1 omitted for preview. Available via download)

According to Table 1, nationwide data for cause of death in males were higher than females in Diabetes, Heart Disease, Malignant Neoplasms, and Unintentional Injuries. Moreover, Suicide was in the top ten causes of death for men, and not for women. The frequency for causes of death in females was higher in Alzheimer’s Disease, Cerebrovascular Disease, Chronic low, Respiratory Disease, Influenza and Pneumonia, and Nephritis. In addition, a top ten cause for females and not males were Septimia, and Suicide was not in the top ten causes of death for females.

Question 4

Compute the mean number of “unintentional injury” deaths for females and for males.

Mean of Unintentional Injury deaths for females: 11235

Mean of Unintentional Injury deaths for males: 18980

To obtain the mean for males and females within this group, I added together the statistics from the four regions together and divided the total by four (Howell, 2011).

Question 5

Which inferential statistic is most appropriate to determine whether males and females differed along the research conditions?

According to Howell (2011), an analysis where two groups of data are compared is called a bivariate analysis. The bivariate analysis is for the nominal variable of gender, the differences between males and females.

Question 6

Based upon either accepting or rejecting the null hypothesis: Is there a difference between males and females for each of the top ten causes?

According to Howell (2011), when one needs to compare the data for nominal variables, one needs to measure the central tendency. One could measure the mode, median, and mean to compare the central tendencies for each category. 

In order to compare the overall data of the two groups, it can be a bit more complicated. Howell (2011) stated the t-statistic is most appropriate when comparing the central tendency of two groups, such as male versus female. However, the t-test is used, stated Howell (2011), when two samples of a population of an unknown size is measured. The most appropriate measurement for the two groups would be the z score. The z score stated Howell (2011) is the most appropriate measurement for two groups when the population is known. Since it is possible to gain the total population of males and females through the United States 2010 census, z scores can be calculated for a realistic determination of the differences of all the causes of death for males and females.

As depicted in Table 1, the frequency distribution for males and females varies quite a bit, noticeable just by the fact that the top ten causes of death are not exactly the same for men as they are for women. Based upon this fact, we can accept the hypothesis and reject the null hypothesis that there are differences in causes of death between males and females based upon nationwide figures.

The differences between causes of death for men and women in 2010 were examined. Upon studying the variances in frequency of the top ten causes of death for men and women, there were a significant number of differences between the dependent variable of gender. As highlighted in the review of literature, this basic data can be used in the field of psychology to illuminate possible causes for death, which can in turn increase longevity and quality of life. 

References

Case, A. & Paxson, C. (2004). Sex differences in morbidity and mortality. Retrieved from the Center for Health and Wellbeing: Princeton University, 1-44, http://www.princeton.edu/rpds/papers/pdfs/case_paxson_morbidity.pdf

Center for Disease Control (CDC). CDC WONDER database: Underlying cause of death, 1999-2010 request. Retrieved from http://wonder.cdc.gov/controller/datarequest/D76

Howell, D. C. (2011). Fundamental statistics for the behavioral sciences. Belmont, CA: Wadsworth Cengage Learning. 

Hoyert, D. L. (2012). 75 Years of Mortality in the United States, 1935–2010. NCHS (National Center for Health Statistics) Data Brief, 88, 1-7. Retrieved from http://www.cdc.gov/nchs/data/databriefs/db88.pdf

Wong, M. D., Chung, A. K., Boscardin, J. W., Li, M., Hsieh, H. J., Ettner, S. L., & Shapiro, M. F. (2006).  The contribution of specific causes of death to sex differences in mortality. Public Health Reports, 121(6), 746–754. doi: PMCID: PMC1781916