Goal & Concept
Goal
The goal of this exercise is to explore the ways in which health status, health care access, and health care utilization differ between social classes. Crosstabulation will be used.
Concept
Social class is a measure of relative power, privilege, and opportunity in a society. Individuals in higher social classes generally have greater power and access to resources than individuals in lower social classes. Researchers may assign individuals to social classes on the basis of criteria such as occupation, education, income, wealth, and place of residence.
Health can be generally defined as physical, mental, and social well-being. Like social class, an individual's health can be measured in many different ways, depending on the needs and preferences of the researcher. Researchers may measure self-reported health, medical diagnoses, number or frequency of medical visits, number of work days missed due to illness, receipt of government disability payments, and many more.
Social class is consistently linked with health outcomes in the United States and other countries. This is due to factors such as differences between social classes in food quality and eating habits, housing quality, stress, affordability of health care, occupational hazards, and knowledge of healthy behaviors.
Examples of possible research questions about social class and health:
- How are income and education related to self-rated health?
- How are income and education related to frequency of medical visits?
- How are income and education related to health insurance coverage?
- Do people of different social classes have different medical problems?
- Is there a relationship between social class and work-related injuries?
Dataset
Data for this exercise come from the 2004 National Health Interview Survey (NHIS). NHIS is collected by The United States Department of Health and Human Services and the National Center for Health Statistics. Its main purpose is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive.
The NHIS sample is designed to represent the civilian, non-institutionalized population of the 50 states and the District of Columbia. Data are collected about individuals and families. The person-level file, used in this exercise, includes information on sex, age, race and Hispanic origin, marital status, education, veteran status, family income, family size, major activities, health status, activity limits, and employment status, along with industry and occupation.
This exercise will use the following variables:
- Total combined family income (INCGRP)
- Self-reported health status (PHSTAT)
- Family member in hospital overnight in the last 12 months (FHOSPYN)
- Health insurance coverage (NOTCOV)
- Health insurance offered at workplace (HIEMPOF)
- Employment status (EMPSTAT)
Application
For this exercise, you will be exploring the relationship between income and different measures of health using crosstabulation.
In this dataset, total combined family income group is divided into 11 categories--too many for a useful crosstabulation. So, we recoded it into four categories and called the new variable NEWINC.
Self-Reported Health Status
Next, we recoded self-reported health status (PHSTAT) to exclude those answering "don't know (DK)," "refused (RF)," and "not ascertained (NA)" and called the new variable PHSTAT1.
Run a crosstab to examine the relationship between income and health status. Do those with higher levels of income rate their health status in the same way as those with lower levels?
Family Member in Hospital in Last 12 Months
Next take a look at the variable FAMHOSP, which contains answers to the question, "was anyone in the family in the hospital overnight in the last 12 months?" Answers to this question are coded 1 for "yes" and 2 for "no." (We recoded FHOSPYN to exclude DK/RF as above.)
Now look at the crosstab of FAMHOSP with NEWINC. What do you find?
Health Insurance Coverage
To examine health insurance coverage (NOTCOV), we ran a crosstab with our income variable Are people with lower incomes as likely as those with higher to have health insurance? Look in particular at the bar chart. What does it show?
Health Insurance Offered at Workplace
Now consider whether respondents are offered health insurance though the workplace. We again recoded HIEMPOF to exclude DK/RF/NA and called the new variable INSWORK.
Look at the relationship between income and having insurance through work. For this analysis, we want to limit our sample to only those people who are employed.
What do you find? Are the people who are less likely to have insurance through work those who are more or less likely to be able to afford to purchase it on their own?
Interpretation & Summary
Think about your answers to the application questions before you click through to the interpretation guide for help in answering them.
Self-Reported Health Status
Do those with higher levels of income rate their health status in the same way as those with lower levels?
Family Member in Hospital in Last 12 Months
How is income related to family member hospitalization?
Health Insurance Coverage
Are people with lower incomes as likely as those with higher to have health insurance? What does the bar chart tell you?
Health Insurance Offered at Workplace
Looking at those who are employed, what do you find out about health insurance coverage at work? Are the people who are less likely to have insurance through work those who are more or less likely to be able to afford to purchase it on their own?
Interpretation
Things to think about in 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 - some crosstabulation tables have relatively little missing data, others have a great deal because the questions were only asked of people with particular characteristics (e.g., employed). In general, results from this dataset should be fairly representative of the general population because it is a national probability sample.
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. This dataset is very large, so the actual number is often in the millions. 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.
The use of column percentages, as shown in these tables, allows for the comparison of answers to the "outcome" of interest across values of the grouping variable. For example, only 23.4% of those earning under $20,000/year reported that their health was excellent, compared to 46.3% of those who earn $55,000/year or more. Conversely, those with lower incomes were much more likely to report poor health than those with higher incomes.
The analyses show the following:
Those with higher reported incomes are less likely to have had someone in their family hospitalized over the past 12 months than those with lower reported incomes. Overall, however, the majority (at least 77%) of all groups did not experience hospitalization.
As would be expected, those who earn more each year are much more likely to be covered by some sort of health insurance than are those earning less. About a quarter of those earning less than $35,000/year are uncovered (24.3% and 22.1%) whereas only 6% of those earning $55,000 or more are not covered.
The table examining the relationship between income and insurance through work only includes those who were working for pay at a job or business during the last week. Just over 1/3 (36.8%) of those who earn less than $20,000/year have health insurance through work whereas almost 80% of those who earn $55,000 or more do. Overall, about 70% of the sample report having insurance through their jobs, but the difference in percent between each of the income groups is substantial.
Summary
The goal of this exercise was to demonstrate the concept of Social Class as measured by income and how it is related to health. We examine the ways in which income is related to variables tied to health - subjective health status, hospital visits, and insurance coverage. Taken together, the results show that the higher the income respondents report, the more likely they are to also report being in excellent or good health, avoiding hospitalization of themselves or family members, and being covered by insurance whether it is through work or on their own. The disparities between income groups can easily be seen as the analyses depict fairly linear relationships in all cases. The collapsing of income into four categories allows patterns to be easily identified without having to be concerned with small cell counts or tables that are unwieldy.
Bibliography
The references presented here represent resources that might be useful to instructors and students wishing to further explore this topic. All were chosen because they relate to the topic of study, whether or not they use the specific dataset that was used in this exercise. Some relate directly to the concepts as defined by the exercise, others explore the topic more broadly either conceptually or empirically. Most can be found in the ICPSR bibliography, though some outside sources were added if they were particularly relevant.
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Crespo, C.J.; Ainsworth, Barbara E.; Keteyian, S.J.; Heath, G.W.; Smit, E., "Prevalence of physical inactivity and its relation to social class in U.S. adults: results from the Third National Health and Nutrition Examination Survey, 1988-1994." Medicine and Science in Sports and Exercise. Dec 1999, 31, (12), 1821 - 1827.
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Duncan, Greg J.; Hofferth, Sandra L.; Stafford, Frank P., "Evolution and Change in Family Income, Wealth and Health: The Panel Study of Income Dynamics, 1968-2000 and Beyond." Jun 2000.
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Gresenz, Carole R.; Sturm, Roland; Tang, L., "Income and mental health: Unraveling community and individual level relationships." Journal of Mental Health Policy and Economics. 2001, 4, 197 - 203.
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McDonough, Peggy; Duncan, Greg J.; Williams, David; House, James S., "Income Dynamics and Health in the United States, 1972-1989." American Journal of Public Health. 1997, 87, 1 - 8.
Mellor, J.M.; Milyo, J., "Is exposure to income inequality a public health concern? Lagged effects of income inequality on individual and population health." Health Services Research. Feb 2003, 38, (1 Pt. 1), 153 - 167.
Mellor, Jennifer M.; Milyo, Jeffrey, "Income Inequality and Health Status in the United States: Evidence from the Current Population Survey." Journal of Human Resources. Sum 2002, 37, (3), 510 - 539.
Miech, Richard A.; Hauser, Robert M., "Social Class Indicators and Health at Midlife." CDE Working Paper 98-06. Madison, WI: Center for Demography and Ecology, Mar 1998.
Newacheck, Paul W.; Jameson, W.J./ Halfon. N., "Health status and income: the impact of poverty on child health." Journal of School Health. Aug 1994, 64, (6), 229 - 233.
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