Abstract
Background
With growing numbers of migrants worldwide, accurate data are needed to assess the health of migrants and ethnic minorities, highlight inequalities and evaluate relevant policies and actions. To summarise and reveal the complexity of the findings, we developed data visualisation techniques based on epidemiological principles.
Methods
We used published results from the Scottish Health and Ethnicity Linkage Study (SHELS), a retrospective cohort of 4.62 million people linking census ethnicity data to health service and death records during 2001-2013. In tables mainly using rate ratios, we employed different colours to show health advantage, disadvantage or equivalence; different colour shades to represent degree of certainty, combining effect size and precision of estimate; and different font sizes for absolute rates, to highlight more common conditions. We ranked health conditions by age-adjusted rate within each ethnic group to show differences in burden of disease and disease priorities.
Results
Using 30 health outcomes for up to 11 ethnic groups, we show that ethnic differences vary greatly depending on outcome, sex and ethnic group. The patterns are complex with some ethnic groups showing strong advantages for some outcomes and strong disadvantages for others. Using absolute rates highlighted differences in common conditions such as myocardial infarction, COPD, and falls. Ranking conditions within ethnic groups showed that most ethnic groups have largely similar disease priorities.
Conclusions
Our approach helps reveal and interpret the complexity of ethnic health differences. Simplistic generalisations that the health of migrants or ethnic minorities is worse or better than majority populations are often misleading and best avoided. Using absolute rates and ranking conditions within ethnic groups are useful as large relative differences in disease rates between ethnic groups may not translate into different disease priorities.
Key messages
Statements that the health of migrants or ethnic minorities is worse or better than majority populations are often misleading and best avoided. Large relative differences in disease rates between ethnic groups may not translate into different disease priorities.
Visualising the complex relationships between ethnic group and health in Scotland: 2001-2013
