Global burden of aflatoxin-induced liver cancer aflatoxin directly in food or reduce adverse health effects caused by aflatoxin. Materials and Methods To perform a quantitative cancer risk assess- ment for aflatoxin-related HCC, we ana- lyzed extensive data sets by nation or world region: food consumption patterns (of maize and peanuts), aflatoxin levels in maize and peanuts, HBV prevalence, and population size. Risk assessment is the process of esti- mating the magnitude and the probability of a harmful effect to individuals or popula- tions from certain agents or activities. Four steps are involved in estimation of the risk: hazard identification, dose–response analysis, exposure assessment, and risk characterization (National Research Council 1983). Hazard identification. Hazard iden- tification is the process of determining whether exposure to an agent can increase the incidence of a particular health condi- tion. Aflatoxin exposure is associated with an increase in incidence of HCC in humans and sensitive animal species (Groopman et al. 2008); in fact, IARC has classified AFB1 naturally occurring mixes of aflatoxins as a Group 1 carcinogen (IARC 2002). Dose–response analysis. This second risk assessment step involves characterizing the relationship between the dose of an agent—in this case, aflatoxin—and incidence of HCC. Because of the synergistic impact of aflatoxin and HBV in inducing HCC, the assessment must be done separately for populations with and without chronic HBV infection. Although chronic HCV infection may also have syner- gistic effects with aflatoxin in inducing HCC, we did not include this effect in the analyses for three reasons: a) there is much less overlap worldwide between aflatoxin and HCV expo- sures in general; b) chronic HCV infection usually occurs later in life, whereas chronic HBV infection occurs much earlier, thus the time of overlapped exposure is less significant for aflatoxin and HCV (Groopman J, per- sonal communication); and c) much less is known about the quantitative relationship of aflatoxin and HCV in inducing HCC. For cancer risk assessment, it is tradition- ally assumed that there is no threshold of exposure to a carcinogen below which there is no observable adverse effect (National Research Council 2008). Cancer potency fac- tors are estimated from the slope of the dose– response relationship, which is assumed to be linear, between doses of the carcinogen and cancer incidence in a population. The IPSC/ WHO aflatoxin risk assessment selected two different cancer potency factors for aflatoxin: 0.01 cases/100,000/year/nanogram/kilogram body weight per day aflatoxin exposure for individuals without chronic HBV infection, and 0.30 corresponding cases for individuals with chronic HBV infection. This was based on one cohort study that estimated can- cer potency in individuals positive for the HBV surface antigen (HBsAg; a biomarker of chronic HBV infection) and in HBsAg- negative individuals (Yeh et al. 1989), as well as other human studies that assessed cancer potency among either HBsAg-positive or HBsAg-negative individuals. We used these same potency factors for this risk assessment. Because only one of the studies (Yeh et al. 1989) specifically assessed cancer potency in both cohorts, considerable uncertainty may be associated with these potency factors. However, several epidemiological studies con- firm that aflatoxin’s cancer potency is about 30 times greater among HBV-positive than among HBV-negative individuals (Kirk et al. 2005, Ok et al. 2007; Qian et al. 1994). Exposure assessment. Exposure assess- ment involves estimating the intensity, fre- quency, and duration of human exposures to a toxic agent. Specifically, we sought to determine how individuals’ exposure to afla- toxin increases their risk of HCC. Aflatoxin exposure is a function not only of aflatoxin concentrations in maize and nuts but also of how much of these foodstuffs individuals consume in different parts of the world. Aflatoxin exposure assessment has evolved significantly over the past two decades, largely due to the characterization of biomarkers for both aflatoxin exposure and effect (Groopman et al. 2005, 2008). Before these biomarkers, the primary way to estimate aflatoxin expo- sure was to observe how much maize and nuts people consumed on average and to meas- ure or assume aflatoxin levels in these foods. By measuring biomarkers such as aflatoxin– albumin adducts in serum or aflatoxin-N7- guanine in urine, it is possible to improve estimations of aflatoxin exposure and how much has been biotransformed to increase cancer risk (Groopman et al. 2008). Because aflatoxin biomarker data worldwide are limited, we collected data on estimated HBV prevalence in these countries and on maize and nut consumption patterns in different world regions and estimated average aflatoxin expo- sure or contamination levels in the maize and nuts in different world regions. Where aflatoxin exposure data were not already estimated, we used food consumption patterns and aflatoxin contamination levels to estimate exposure. The studies estimating HBV prevalence were based on HBsAg detection among males and among females in both urban and rural settings across all age groups. Data on maize and peanut consump- tion in different world regions are adapted from the WHO Global Environment Monitoring System (GEMS)/Food Consumption Cluster Diets database (WHO 2006). We estimated aflatoxin exposure data in different nations from multiple sources through literature searches. Environmental Health Perspectives • volume 118 | number 6 | June 2010 Risk characterization. This final step of risk assessment integrates dose–response and exposure data to describe the overall nature and magnitude of risk. For our study, this final step consisted of quantifying, across the globe, the burden of aflatoxin-related liver cancer. For each nation, we estimated total number of individuals with or without chronic HBV by multiplying prevalence by population size. To estimate aflatoxin-induced HCC rates within these two populations (with and without chronic HBV infection), we multiplied the corresponding cancer potency factor by afla- toxin exposure estimates. Then we multiplied these values by each nation’s HBV-positive and HBV-negative population sizes to derive total number of aflatoxin-induced HCC cases in each nation. We summed across all world regions to arrive at an estimate for global bur- den of aflatoxin-induced HCC. Results Table 1 lists the prevalence of chronic HBV infection by world region, as measured by HBsAg in different parts of the world. Although these different estimates involve uncertainty and variability, all data are from literature published in or after 2000, to ensure that the HBV prevalence estimates are as cur- rent and as relevant as possible. Countries are grouped by WHO designated regions (WHO 2005): Africa, North America and Latin America, Eastern Mediterranean, Southeast Asia, Western Pacific, and Europe. Some regions were divided into subgroups because of significantly varied aflatoxin exposure and HBV prevalence within the region. Table 2 provides calculations of maize and peanut consumption in select countries of the world. The GEMS/Food Consumption Cluster Diets database divides countries of the world into 13 groups based on diets. For each group cluster, the GEMS food consumption database has estimated the amount of cereals, nuts, and oilseeds consumed. We thus estimated aver- age maize and nut consumption by individual country. There are limitations to these data because of the clustering into 13 groups (with potentially wide ranges among nations within a group), as well as variability in data quality regarding diet and aflatoxin exposure estimates. We estimated (based on Tables 1 and 2) or found in the literature the average afla- toxin exposure in different world regions and then calculated the estimated incidence of aflatoxin-induced HCC, with and without the synergistic impact with HBV, in the cor- responding populations of each nation and world region (Table 3). Within each WHO- designated region, we found aflatoxin expo- sures in the most populous nations. The “in general” rows in Table 3 represent a small proportion of each region: nations in which aflatoxin data were not available, or very 819