D pointed me to this great multilevel modeling example:

By living in a well-to-do neighborhood, poor people increase their risk of death, according to a new study by School of Medicine researchers to be published in the December issue of the American Journal of Public Health. . . researchers found that death rates were highest among people of low socioeconomic status who also lived in affluent neighborhoods. That finding surprised the researchers, but “every way we looked at the data, we found the same result” . . .

Previous studies have shown that neighborhood plays an important role in an individual’s health. Most studies have found that people fare better in high-income neighborhoods. The Stanford study is unique because it combined individual economic status with neighborhood status to produce a more detailed picture of the issue.

The researchers discovered the trend by analyzing data from another study that looked at the incidence of heart disease risk factors in California between 1979 and 1990. The study followed 8,200 men and women from 82 neighborhoods in Monterey, Modesto, Salinas and San Luis Obispo over 17 years.

The researchers used income and education to determine individual socioeconomic status. They then divided people into low, moderate or high socioeconomic groups. Similarly, the researchers classified neighborhoods as being of low, moderate or high socioeconomic status.

The study found that over time, the differences in death rates among the groups became more pronounced. After 17 years, 19 out of every 1,000 women of low socioeconomic status who lived in wealthier neighborhoods had died, compared with 11 of every 1,000 from poorer neighborhoods. The trend was similar, but less dramatic in men.

They found that age as well as a number of risk factors, such as obesity, hypertension and smoking, did not account for their results. There were also no differences in the causes of death, which were largely due to chronic diseases, the researchers said. They also found that access to neighborhood goods and services, such as health care, grocery stores, parks and gyms, did not explain their findings. . . .

The funny thing is that the graphs in the news article don’t fully tell the story. They should plot death rates vs. socioeconomic status, with three separate lines on the graph, one for each neighborhood. They can then use different-sized circles to show the number of people in each category (i.e., the “superplot,” as we did here).
(I also assume they controlled for age, although I didn’t see that mentioned in the news article.)