- Industry: Academic, Healthcare
- Product(s): @RISK
- Application: Lifetime Excess Cancer Risk
Researchers at the University of Victoria used @RISK to model the differences in Lifetime Excess Cancer Risk (LECR) for Canadians based on contaminants found in food and beverages. The results revealed notable differences in cancer risks for several different demographics.
I really appreciated how easy @RISK was to use – I didn’t need to be a statistician to understand it. Plus I loved the instantaneous flexibility. If I needed to run a new simulation, the results were immediately visible – and easily understandable – in a graph or chart.Roslyn Cheasley, Master’s student, Department of Geography, University of Victoria
The University of Victoria (UVic), a national and international leader in many areas of critical research, participated in a study funded by Health Canada that looked at the human exposure to carcinogens in various demographics. The UVic team used @RISK, Palisade’s risk analysis software, to model the differences in Lifetime Excess Cancer Risk (LECR) for Canadians based on contaminants found in food and beverages. The results revealed notable differences in cancer risks for several different demographics, and are detailed in the thesis, Geographic Exposure and Risk Assessment for Food Contaminants in Canada, by Roslyn Cheasley, a Master’s student with the Department of Geography at UVic.
The University of Victoria is a public research university in British Columbia, Canada. Ranked one of the top 250 universities in the world, UVic is a national and international leader in many areas of critical research, offering students education that is complemented by applied, clinical and work-integrated learning opportunities. The University participated in a study funded by Health Canada that looked at the human exposure to carcinogens in various demographics.
While news headlines regularly report on acute health issues relating to food and beverages, such as E. coli outbreaks and salmonella poisoning, very little is known about the adverse health issues caused by the longer-term intake of contaminants in those foods and beverages – including carcinogens. The CAREX Canada Project, funded by the Canadian Partnership Against Cancer, was launched to better understand the environmental and occupational exposures to substances associated with cancer, and subsequently provide support for exposure reduction strategies and cancer prevention programs. "The goal of the Project was to analyze all publicly available data and build a website that provided local and regional communities with tools to help determine if their geographic areas were at risk," explains Roslyn Cheasley, a Master’s student with the Department of Geography at the University of Victoria. "While the site was launched in 2012, they were concerned that by 2014, the data was already out of date. The University of Victoria made up part of the team that undertook a new study to update the information, and ensure that health officials and other decision makers had all the information they might need to indicate if there could be future health problems."
The UVic team focused on the environmental aspects of the study, looking at potential exposure to carcinogens via air, dust, water, food and beverages. They reviewed 92 different substances that were considered carcinogenic, probably carcinogenic, or potentially carcinogenic. These were then narrowed down to five substances specifically for the food and beverage study: arsenic, benzene, lead, PCB (polychlorinated biphenyls) and PERC (tetrachloroethylene). "Up to this point in time, all analysis had been done from a deterministic point of view, which wasn’t particularly helpful as it didn’t enable us to understand the full range of potential contamination and which populations were more or less at risk," said Cheasley. "We decided to take things up a notch when we updated the data, and upgrade to a probabilistic analysis model based on Monte Carlo simulation. We wanted to estimate the range and frequency of possible daily contaminant intakes for Canadians, as well as associate these intake levels with lifetime excess cancer risk. This is where @RISK came into the equation."
Palisade’s @RISK enabled the team to easily and effectively determine the concentration of carcinogenic elements in the identified food and beverage products, as well as learn if certain demographics were more at risk from dietary patterns than others.
Building the Model
The first challenge to building the new model was pulling together all existing information, as elements of the data were in different formats (e.g. Excel, Access and Stata), as well as in different physical (offline) locations. Then the team had to manage the vast quantity of that information: the resulting 1.5 million rows of data was too much to easily manipulate, sort and manage without corrupting the results.
The next challenge related to the data for the food and beverage types. The team had analyzed the dietary patterns of approximately 35 thousand Canadians, using three different categories: geographic location, gender and income levels. They’d also identified 60 whole foods for the model, from eight food groups: meat, fish, dairy, fruit, vegetables, rice/cereals, grain/nuts and beverages. However, the data for these specified foods came from three different sources, with each using a different form of measurement. According to Cheasley, “The problem we had was how to bring all of these components together in a way that would provide a comprehensive but usable outcome. We needed to be able to filter the data into different dietary patterns as well as different demographics, then marry it each time with the five different carcinogenic substances."
Palisade's @RISK software solved these problems, enabling the team to use PERT distributions to easily determine the minimum, mean and maximum concentration of the five carcinogenic elements in the identified food and beverage products. They were also able to see the output of the different dietary patterns and determine if certain demographics were more at risk than others. “I really appreciated how easy @RISK was to use – I didn’t need to be a statistician to understand it," said Cheasley. "Plus I loved the instantaneous flexibility. If I needed to run a new simulation, the results were immediately visible – and easily understandable – in a graph or chart.” For this study, each of the 125 different simulations was run 50 thousand times, to ensure the most accurate results (and smoothest possible graphs).
The outputs of the @RISK model revealed to the UVic team that of the five tested contaminants, arsenic showed the greatest difference between urban and rural estimated Lifetime Excess Cancer Risk (LECR). In addition, LECR was estimated to be higher for men vs. women in Canada for all five contaminants, with an emphasis on males in British Columbia from the dietary intake of arsenic. When based on income level, the model predicted LECR being higher for low and middle incomes from the dietary intake of arsenic, benzene, lead and PERC. However, high-income populations were more likely to have higher LECR from the dietary intake of PCBs.
"I hope that local health officials will be able to use the results of this model to determine if they should do a more detailed study in their own particular regions. For example, what are males eating in British Columbia that impacts their dietary intake of arsenic, and is there a real risk of arsenic in specific foods," added Cheasley.