The analyses detected 5 statistically significant clusters over the 8-year study period. Overall, the age-adjusted incidence rates and the relative risk of lung cancer decreased from 2010 to 2017 with no statistically significant space and time interaction. Demographics obtained from the 2011–2015 American Community Survey and health variables obtained from 2020 CDC PLACES database were compared between census tracts that were part of clusters versus those that were not. Spatio-temporal clusters with high incidence were identified using scan statistics. Relative risks over the expected case counts at the census tract level were estimated using a log-linear Poisson model that allowed for spatial and temporal effects. We geocoded the residential addresses at the time of diagnosis for lung cancer cases in the Pennsylvania Cancer Registry diagnosed between 20. The objectives of this study were to examine spatio-temporal patterns of lung cancer incidence in Pennsylvania, to identify geographic clusters of high incidence, and to compare demographic characteristics and general physical and mental health characteristics in those areas. It is known that geographic location plays a role in developing lung cancer.
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