Racial Disparities in Mental Health

Printer Friendly version
Collapse open tabs

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:

  • How is race related to self-rated mental health?
  • How is race related to seeking medical treatment for mental health disorders?
  • Are racial differences in treatment of mental health disorders related to differences in insurance coverage?
  • To what extent can differences in mental health by race be explained by differences in income, education, and marital status?
  • To what extent can racial differences in mental health be explained by differences in experiences of discrimination?

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:

  • Frequency of feeling sad (V226)
  • Self-reported race (V118)
  • Highest grade of school completed (V1001)
  • Marital status (V107)
  • Ever treated unfairly because of race or ethnicity (V125)

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 distribution of responses to V226NEW. This will show you how many people chose each answer category. What percent of people said that they hardly ever felt sad and how many people was that?

In this survey, respondents were asked to identify the race that best describes them. Look at the distribution of responses to this variable (V118). As you can see, very few selected Asian, American Indian, Hispanic, or other. For this exercise we dropped these respondents in order to compare only Black and White respondents. V118NEW is the recoded where Black is coded as "1" and White is coded as "0".

To see whether Blacks and Whites report feeling sad with similar frequencies, look at a crosstab of V226new with V118new. What do you find? What percent of Whites report feeling sad very or fairly often? What percent of Blacks do? What about never feeling sad?

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):

  • Education level (V1001new) will be included in a measure of socioeconomic status. Previous studies have shown that depression rates may be higher among people with lower socioeconomic standing.
  • Marital status (V107new) will be included because research has shown that rates of depression tend to be higher among single people than married people.
  • Discrimination (V125new)

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 race and frequency of feeling sad in the regression. How would you interpret the outcome? How would you compare the regression results to the results of the crosstabulation you conducted? (Hint: to understand regression results, look at the B value and the Probability. The B value tells the strength and direction of the relationship and the probability tells you if the relationship is significant. If you need more help with the interpretation, see the Interpretation Guide on the next tab.

Next the control variables are added to the regression.

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.
  • Main Findings:
    • Rates of depression in the study were low. The majority of the respondents say they feel so sad that nothing could cheer them up hardly ever or never (71%), and less than 10% of respondents said they feel that sad very often or fairly often.
    • The crosstab indicates Black respondents report feeling sad more frequently than White respondents. Among the Black respondents, about 10% reported feeling sad very often or fairly often, compared to about 9% of Whites. At the other extreme, 44% of Black respondents said that they never feel that sad as compared to about 48% of the white respondents.
    • The bivariate regression shows a very slight relationship between race and depression. A positive coefficient of race means that, on average, Black respondents reported feeling sad more frequently than Whites (Because Blacks are coded the higher number [1] on the race variable and 4 represents feeling sad very often or fairly often). The coefficient of race was positive, but it was not statistically significant so we would say there is no significant relationship between race and depression.
    • The multivariate regression analysis added variables that might be related to both race and reports of depression (education, marital status, and experience of discrimination). In this model, the coefficient of race has changed direction (negative means Blacks reported feeling sad less than whites when education, marital status, and discrimination are taken into account), but still is not statistically significant.
    • The relationship between education level and feelings of depression is significant in the model. The negative coefficient of education tells us that as the level of education increases, the frequency of feeling sad decreases. However, we can not conclude that level of education causes fewer feelings of depression. It could also be the case that feelings of depression limit the amount of education individuals receive.
    • Experiences with discrimination are associated with significant differences in reports of feeling sad. On average, people who have experienced discrimination report feeling sad more often than people who have not experienced discrimination.
    • Taken together, these findings suggest that experiences of discrimination and lower education might account for the pattern of Blacks reporting feeling sad more often. (Further analyses indicate that Blacks have, on average, lower levels of education than Whites and are also far more likely to report experiencing discrimination (68% of Blacks compared to 16% of Whites).

    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.

CITATION: Inter-university Consortium for Political and Social Research. Racial Disparities in Mental Health: A Data-Driven Learning Guide. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2009-04-16. Doi: https://doi.org/10.3886/racementalhealth

Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial 3.0 United States License.