ABSTRACT
Introduction Financial literacy correlates with less debt and better retirement planning. Medical students, residents, and physicians often have poor financial literacy and large amounts of debt. We measured baseline financial literacy and whether it improved with the administration of a financial literacy course. Methods We created the Medical Mini-MBA,a six-week financial literacy course that targeted gaps in financial literacy among medical students and residents. Weekly topics included personal finance, investing, real estate and mortgage, physician billing and payment models, income and tax, and choosing a medical specialty. A 46-question financial literacy assessment was delivered to participants before and after the course. Results Of the 276 who participated in the course, 179 (64.86%) participated in the study. Participants who completed the course improved their financial literacy score by 10.10/46.00±5.12 (n=93, p<0.001). Self-assessment of financial literacy was positively correlated with financial literacy exam scores (r=0.366, p<0.001). Demographics such as gender, geography, education level, and first-degree relatives who are/were physicians had no effect on financial literacy scores. Conclusions The Medical Mini-MBA improved financial literacy at a Canadian medical school. Implementation of the coursemay equip medical students and residents for financial decisions. It avoids financial conflicts of interest and can supplement the medical curriculum.
ABSTRACT
Globally consistent measurements of airborne metal concentrations in fine particulate matter (PM2.5) are important for understanding potential health impacts, prioritizing air pollution mitigation strategies, and enabling global chemical transport model development. PM2.5 filter samples (N ~ 800 from 19 locations) collected from a globally distributed surface particulate matter sampling network (SPARTAN) between January 2013 and April 2019 were analyzed for particulate mass and trace metals content. Metal concentrations exhibited pronounced spatial variation, primarily driven by anthropogenic activities. PM2.5 levels of lead, arsenic, chromium, and zinc were significantly enriched at some locations by factors of 100-3000 compared to crustal concentrations. Levels of metals in PM2.5 and PM10 exceeded health guidelines at multiple sites. For example, Dhaka and Kanpur sites exceeded the US National Ambient Air 3-month Quality Standard for lead (150 ng m-3). Kanpur, Hanoi, Beijing and Dhaka sites had annual mean arsenic concentrations that approached or exceeded the World Health Organization's risk level for arsenic (6.6 ng m-3). The high concentrations of several potentially harmful metals in densely populated cites worldwide motivates expanded measurements and analyses.
ABSTRACT
Exposure to ambient fine particulate matter (PM2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM2.5 to interpret globally dispersed PM2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 µg/m3), mineral dust (1.9-14.7 µg/m3), residual/organic matter (2.1-40.2 µg/m3), and black carbon (1.0-7.3 µg/m3). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 µg/m3), industry (6.5 µg/m3), and power generation (5.6 µg/m3) are leading sources of outdoor global population-weighted PM2.5 concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM2.5 provides insight into sources and processes that influence the global spatial variation in PM2.5 composition.
