Written by Patience Kunonga, Research Associate

Health inequality and inequity are major problems that impact how easily people can access healthcare and their overall health.  Inequality refers to differences in health between groups, while inequity points to unfair differences that could be avoided.

What if we could identify the inconsistencies that make it difficult for researchers and policymakers to understand how to close these health gaps? Our latest research takes an important step towards making this a reality. We recently published a study in the Journal of Clinical Epidemiology to explore how researchers in evidence synthesis approach these issues.

We looked at 62 studies and found that many researchers use tools like the PROGRESS-Plus framework, which considers factors such as where people live, their race, job, gender, religion, education, and income. Another tool, the PRISMA-Equity checklist, ensures that researchers think about fairness when reviewing studies. While these tools are helpful, they have some drawbacks. For instance, The PROGRESS-Plus framework highlights factors that can impact people’s health, but it doesn’t explain how those factors interact. This matters because unfair health differences often arise from a combination of things.

We also noticed that only 31% of the studies clearly defined what they meant by health inequality or inequity. Some studies even used the terms as if they meant the same thing, which made it harder to understand the real issues.

Our study suggests that researchers need better methods that consider how unfair differences change over time. This would help them, along with policymakers, create better strategies aimed at reducing unfair health differences.

For more details, you can read the full study here. You can read more about Patience’s work on developing a novel approach for consideration of health inequality/inequity in evidence synthesis here. The link to the Kunonga Framework can be found here.

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