Spatiotemporal analysis of lung cancer disparity in Wisconsin, USA

Thesis presentation of Mathew Ugwuanyi: Studies over the United States has shown that disparity still exists in lung cancer mortality. Such disparity has been greatly attributed to several risk factors such as genetics, socio-economic status, comorbidities, amongst others. Primarily, this study aims to examine spatiotemporal variation in lung cancer mortality rates in the State of Wisconsin, U.S.A. The study also seeks to explore the relationship between socio-economic, environmental variables and lung cancer mortality. For this study, lung cancer mortality county level data from the United States Center for Disease Control (CDC) and, the National Cancer Institute’s Surveillance, Epidemiology and End Results (SEER), which is aggregated and age-adjusted according to the 2000 U.S standard million population were used. Also, county level socio-economic data like education attainment, median household income, unemployment and PM 2.5 data were gathered from the American Community Survey (ACS) and the Environmental Protection Agency (EPA) respectively. Scan statistics (SaTScan) will be used to analyze the spatiotemporal pattern of mortality clusters. In addition, regression analysis will be used to assess statistical significance and measure the relationship between lung cancer mortality and county level socio-economic and environmental factors in Wisconsin. This study hopes to show potential cluster patterns in lung cancer mortality in the study area, which might suggest uneven spatial temporal mortality risk. Also, through findings, we hope to suggest interventions to help ameliorate lung cancer mortality.