The Association between Long-term PM2.5 Exposure and Risk for Pancreatic Cancer: An Application of Social Informatics.

There is a profound need to identify modifiable risk factors to screen and prevent pancreatic cancer. Air pollution, including fine particulate matter (PM2.5), is increasingly recognized as a risk factor for cancer. We conducted a case-control study using data from the electronic health record (EHR) of Duke University Health System, 15-year residential history, NASA satellite fine particulate matter (PM2.5) and neighborhood socioeconomic data. Using deterministic and probabilistic linkage algorithms, we linked residential history and EHR data to quantify long term PM2.5 exposure. Logistic regression models quantified the association between a one interquartile range (IQR) increase in PM2.5 concentration and pancreatic cancer risk. The study included 203 cases and 5027 controls (median age of 59 years, 62% female, 26% Black). Individuals with pancreatic cancer had higher average annual exposure (9.4 µg/m3) as compared to IQR increase in average annual PM2.5 was associated with greater odds of pancreatic cancer (OR=1.20; 95% CI: 1.00-1.44). These findings highlight the link between elevated PM2.5 exposure and increased pancreatic cancer risk. They may inform screening strategies for high-risk populations and guide air pollution policies to mitigate exposure.

The impact of climate change on the prevalence of mental illness symptoms.

BACKGROUND: The repercussions of climate change threaten the population with an increased prevalence of extreme climate events. We explored the impact of climate change induced sea level rise (SLR) and tropical cyclone (TC) exposure on mental illness symptom prevalence. METHODS: Using three datasets, TC exposure scores were calculated for each subject to determine how exposure affects posttraumatic stress disorder (PTSD), anxiety, and major depressive disorder (MDD) symptom prevalence. Inundation mapping of various SLR and storm surge (SS) scenarios were performed for the susceptible region of Miami-Dade and Broward counties to determine the population impact of flooding. RESULTS: We found an elevated risk of mental illness symptoms from exposure to more high- intensity TCs and identified demographic variables that may contribute to this risk. Furthermore, inundation mapping demonstrated severe and widespread impact of SLR and SS on the mental health of communities. LIMITATIONS: This study did not include data directly measuring comorbidity, resilience, preparedness, or ability to adapt to climate change. Also, multiple imputation using chained equations may have been imperfect. Furthermore, there is uncertainty in predicting and mapping SLR and TC intensity, which limits complete confidence in our SS predictions. CONCLUSION: The impacts of climate change have been frequently studied in terms of physical health, natural disaster prevalence, and economic impacts, but rarely on mental health burden. However, it is vital that national, state, and local governments develop and deploy plans to address mental health needs along with expenditures for protecting infrastructure, the economy, and physical health from the combined effects of SLR and climate change-induced natural disasters.