Goal
This exercise will investigate racial disparities in mental illness, particularly differences in reports of depression between African American and White adults. Crosstabulation and linear regression will be used.
Concept
Race is a social category of people labeled and treated as similar because of some common traits, such as skin color, texture of hair, and shape of eyes. Racial categories are not natural, biological categories. Different societies identify different characteristics that distinguish one race from another. Racial categories are often reflected social rankings and access to resources.
Numerous disciplines study mental health and illness. The sociological approach to mental health focuses on the social conditions that influence psychological functioning as well as the processes linking social conditions and psychological well-being. Researchers might use measures such as self-reported mental health, medical diagnoses, scales representing symptoms of mental disorders, or number of work days missed due to mental illness.
Evidence shows that mental health disorders are not randomly distributed throughout society but tend to be higher among minority racial groups. Race can be an important predictor of exposure to stress, coping strategies, and social support and, in turn, mental health status. For example, experiences of discrimination are stressful events that place minorities at risk for depression and anxiety.
Examples of possible research questions about race and mental health:
Data for this exercise come from the Detroit Area Study, 1995: Social Influence on Health. Researchers at the University of Michigan conducted the survey of adults aged 18 and older residing in households located in the Michigan counties of Oakland, Macomb, and Wayne.
The Detroit Area Study was conducted nearly every year from 1951 through 2005. The 1995 survey explored the ways in which social influences such as stress and racism affected respondents' health and outlook on life. Respondents were asked about their physical and mental health status and the effects these had on daily activities. Respondents were also asked about their experiences with employment, crime, discrimination, alcohol and drug use, fears and phobias, and medical treatment. A final set of questions gathered demographic information such as highest level of education completed and total family income in 1994.
This exercise will use the following variables:
This exercise explores the relationship between race and reported levels of depression using crosstabulation and linear regression.
Crosstabulation
Depression was measured with the question, "how often do you feel so sad that nothing could cheer you up?" (V226) The response options were "very often," "fairly often," "not too often," "hardly ever," and "never." Fewer than 10 percent of respondents said "very often" or "fairly often," so we created a new variable (called V226NEW) that combined these two categories and reversed the coding so that higher numbers meant higher frequency of depression.
Begin by examining the
In this survey, respondents were asked to identify the race that best describes them.
Look at the
To see whether Blacks and Whites report feeling sad with similar frequencies, look at a
Multiple Regression
One concern when studying race and mental health is that the relationship between race and depression may be caused by a third factor. Next we will use multiple regression to control for potential confounding factors and isolate the relationship between race and reports of depression. In addition to race and depression, we will include the following measures (the links take you to frequency distributions of each):
Note, we recoded education (V1001) into V1001new which collapses the answers from specific years of schooling completed to categories that represent less than high school, high school degree, and so on. We recoded V107 so that respondents were considered either married or not married rather than retaining all categories of "not married" (divorced, single, etc.). Lastly, we removed the two people who answered "Don't know" to the question about discrimination, creating V125new.
Can you think of other factors that might confound the relationship between race and feelings of depression?
First, we start by including only
Next the
What do you find? How would you interpret the coefficient on race? How has the coefficient changed compared to the previous model without control variables? How would you interpret the coefficients on the other variables in the model? What can you say about the relationship between race and depression overall based on these models?
Think about your answers to the application questions before you click through to the interpretation guide for help in answering them.
What percent of people said that they hardly ever felt sad and how many people was that?
Did there appear to be a relationship between race and depression based on the crosstabulation? What percent of Whites report feeling sad very or fairly often? What percent of Blacks do? What about never feeling sad?
Can you think of other factors that might confound the relationship between race and feelings of depression?
How would you interpret the outcome regression with race as an independent variable and depression as the dependent? How would you compare the regression results to the results of the crosstabulation you conducted?
What about the results for the regression with controls? How would you interpret the coefficient on race? How has the coefficient changed compared to the previous model without control variables? How would you interpret the coefficients on the other variables in the model? What can you say about the relationship between race and depression overall based on these models?
Interpretation
Things to think about when interpreting the results:
It is important to look at the amount of missing data in each relationship and think about the ways in which that might affect the generalizability of the results. Most of these analyses have very small amounts of missing data so that would not be as much of a concern here. Because the survey was done with a probability sample and sample weights were included on the analyses, the results are likely to be fairly representative of people living in greater Detroit.
Reading the results: the numbers in each cell of the crosstabulation tables show the percent of the people who fall into the overlapping categories, followed by the actual number of people that represents in this sample. The coloring in the tables demonstrates how the observed numbers in each cell compares to the expected number if there were no association between the two variables. The accompanying bar charts display the patterns visually as well.
Regression is a statistical technique that tests for the effects of one variable on another. A bivariate regression includes the dependent variable and a single independent variable while a multiple regression includes the dependent variable and two or more independent or control variables. To quickly interpret regression results, look at the B value and the probability. The B value tells the amount and direction of change in the dependent variable caused by one unit increase in the value of the independent variable. The "p-value" or probability tells whether this change is likely due to change -- generally a probability of .05 or less is considered not due to chance.
Summary
The goal of this exercise was to examine the relationship between race and mental health as measured by feelings of sadness or depression. Taken together, the results show that, contrary to the pattern suggested in the initial crosstabulation table, there are no significant differences in reports of depression by race. However, having a lower level of education and experiences with discrimination are related to higher frequencies of feeling sad. The use of multivariate regression emphasizes about importance of confounding factors which could help explain an apparent relationship between race and depression.