Public health outcomes are affected by multiple, intersecting social determinants, yet dominant regression-based approaches often struggle to analyse such causal complexity. This paper illustrates the value of fuzzy-set Qualitative Comparative Analysis (fsQCA) as a viable method for public health research by applying it to the social determinants of health in Aberdeen, Dundee and Glasgow, which we use as illustrative examples for teaching the utility of fsQCA. Using indicator-level Scottish Index of Multiple Deprivation data, we demonstrate how fsQCA identifies necessary conditions and multiple sufficient configurations linking combinations of income, employment, education and training, housing, crime and access-related deprivation to area-level health outcomes. The analysis shows that fsQCA can accommodate equifinality and causal asymmetry, revealing recurring constellations of disadvantage associated with poor health and distinct configurations linked to better health. Rather than estimating average net effects, fsQCA makes explicit the specific combinations of conditions most consistently associated with health outcomes. The study demonstrates how configurational methods can complement existing quantitative approaches and offers a practical template for incorporating fsQCA into applied public health and health policy research.