P/S 06 · Social determinants of health and study design
Income, Stress and Blood Pressure
Read three tables on a health gradient: prevalence, relative risk, adjustment and correlation.
Passage
Epidemiologists study how health and disease are distributed in populations and which factors explain the patterns. Researchers have found that people with lower income and less education tend to have worse health. This relationship is often described as a gradient, because health improves at each step up the social ladder and not only at the extremes. Possible explanations include differences in health behaviors such as smoking, in access to healthy food and health care, and in exposure to chronic stress. Researchers must also consider reverse causation, in which poor health lowers income, and confounding by other variables.
Part 1. A research team surveys 8,000 adults in one metropolitan area, selected from a list of patients registered at community health clinics. Each participant has a blood pressure measurement taken during the visit, and is classified as having hypertension if the average of two readings is above a standard cutoff or if they are taking medication for high blood pressure. The participants are divided into four equal groups by household income (quartiles). Table 1 shows the percentage of each group with hypertension.
Table 1. Prevalence of hypertension by household income quartile.
| Income quartile | Number of participants | Percentage with hypertension |
|---|---|---|
| Lowest (Q1) | 2000 | 38 |
| Second (Q2) | 2000 | 32 |
| Third (Q3) | 2000 | 27 |
| Highest (Q4) | 2000 | 22 |
Prevalence is the proportion of people who have a condition at a given time, while incidence is the proportion who develop it during a period. Because Part 1 counts people who already have hypertension, it measures prevalence. When a statistical model is adjusted for a variable, it estimates the association between income and hypertension among people who are similar on that variable.
Part 2. The researchers then compare the lowest and highest income groups using relative risk, the ratio of the prevalence in one group to the prevalence in the other. They calculate the relative risk before and after adjusting for other variables in a statistical model. Table 2 shows the results.
Table 2. Relative risk of hypertension in the lowest compared with the highest income quartile.
| Model | Adjusted for | Relative risk (Q1 vs. Q4) |
|---|---|---|
| 1 | Nothing | 1.7 |
| 2 | Smoking and body mass index | 1.5 |
| 3 | Smoking, body mass index, neighborhood food access and a measure of chronic stress | 1.2 |
Part 3. In a separate survey of 800 adults, the researchers ask participants to complete a questionnaire about how often they experience unfair treatment in daily life, which produces a score. They also record each participant’s systolic blood pressure. The correlation between the score and systolic blood pressure is r = 0.30.
The researchers note that income was measured only once, at the time of the survey, and that participants who did not have a recorded income were not included in the analysis. They also point out that the clinics serve communities with a wide range of incomes, but that people who have no regular access to a clinic could not be included.
Questions
Question 1 of 6
Which description of the pattern in Table 1 is most accurate?
The second and third groups also have higher prevalence than the highest group (32% and 27% versus 22%).
The prevalence changes consistently across the groups, from 38% to 22%.
Prevalence is highest in the lowest income group and falls as income rises.
Why the answer is what it is
Each step up in income is associated with a lower prevalence (38, 32, 27, 22). A relationship that continues across the whole range, not just at one end, is a social gradient in health.
Review: Social Structure, Inequality, Health, & Research Methods · Equations: Data & Statistics
Question 2 of 6
What is the relative risk of hypertension in Q1 compared with Q4, based on Table 1?
This is the inverse, 22 ÷ 38. The relative risk of the lowest group is the Q1 prevalence divided by the Q4 prevalence.
This is the difference in percentage points (38 − 22), which is an absolute difference and not a ratio.
This would require a Q1 prevalence of 55% or a Q4 prevalence of about 15%.
Why the answer is what it is
Relative risk = 38 ÷ 22, which is about 1.7. People in the lowest income quartile are about 1.7 times as likely to have hypertension as those in the highest.
Review: Social Structure, Inequality, Health, & Research Methods · Equations: Data & Statistics
Question 3 of 6
The relative risk falls from 1.7 to 1.2 across the models in Table 2. What is the most reasonable conclusion?
A relative risk of 1.2 is still above 1, which means there is a remaining association between income and hypertension.
The adjustment shows how much of the income association these variables can account for. It does not prove that they cause hypertension.
The models answer different questions. The change between them is informative.
Why the answer is what it is
Adjusting for variables that lie on the path between income and blood pressure reduces the association from 1.7 to 1.2. This suggests that these factors explain part of it, but an association of 1.2 remains.
Review: Social Structure, Inequality, Health, & Research Methods · Equations: Data & Statistics
Question 4 of 6
Why does the cross-sectional design of Part 1 limit the conclusions that can be drawn about cause and effect?
Cross-sectional studies include both healthy and unhealthy participants.
Large samples improve precision. They do not cause problems with the design.
Observational studies can find associations. The lack of random assignment limits causal claims, not the finding of an association.
Why the answer is what it is
A cross-sectional study measures exposure and outcome at one time. It cannot show their order, and reverse causation (for example, hypertension reducing a person’s ability to work and earn) is a possible explanation of the association.
Review: Social Structure, Inequality, Health, & Research Methods · Equations: Data & Statistics
Question 5 of 6
Participants were selected from patients registered at community health clinics. Which concern does this raise?
The passage does not say that the staff knew the purpose, and the blood pressure was measured in a standard way.
The groups are all the same size. Group size does not cause confounding.
Taking the average of two readings improves reliability.
Why the answer is what it is
If the sample comes only from clinic patients, people who do not use clinics are not represented, and they may differ in income and health. That is a selection bias that limits generalization to the whole population.
Review: Social Structure, Inequality, Health, & Research Methods · Equations: Data & Statistics
Question 6 of 6
The correlation between the unfair-treatment score and systolic blood pressure is r = 0.30. What is the best interpretation?
Correlation alone does not show causation. A third variable could influence both.
The proportion of variance explained is r², which is 0.09, or 9%, not 30%.
The coefficient is positive: higher scores go with higher blood pressure.
Why the answer is what it is
The positive sign means higher scores go with higher blood pressure. The proportion of variance accounted for is r² = 0.09, so the association is modest, and correlation does not prove cause.
Review: Social Structure, Inequality, Health, & Research Methods · Equations: Data & Statistics
Built from these lessons