Quantitative health risk analysis
NOTE: Article from the Geogenic Contamination Handbook
Risk assessment is the scientific evaluation of known or potential adverse health effects resulting from human exposure to environmental hazards. One of the more commonly used risk assessment paradigms, the Quantitative Health Risk Analysis (QHRA), is based on the U.S. National Academy of Science in Risk Assessment in the Federal Government: Managing the Process (NAS, 1983), colloquially known as the “Red Book”. In the Red Book, the four steps are:
Also shown in Figure 3.2 are the results of a study in Jilin province in China (Bo et al., 2003). The dose-response curves are encouragingly similar. Nevertheless, the nature of the relationship between dose and response remains contentious, and there are calls for more biologically-based risk assessments (Carlson-Lynch et al., 1994; Kitchin and Conolly, 2010). Great efforts have been made to evaluate the dose-response of arsenic-related diseases. Fewtrell et al. (2005) estimated the risk of developing skin lesions caused by elevated arsenic concentrations in drinking water using data from Bangladesh, Inner Mongolia (China) and West Bengal (India). The evaluation showed that at a drinking-water arsenic concentration of >350 mg/L, the age-adjusted prevalence of skin lesions is around 33%. The evaluation of cancer rates and mortality linked to arsenic exposure has also been the subject of many studies (for example Fig. 3.3) and evaluations (e.g. NRC 1999, 2001, 2014). Dose-response functions have been developed to predict incidence rates from arsenic exposure (usually in drinking water). The functions include available demographic parameters, such as gender and age (e.g. Yu et al., 2003). The determination of dose-response functions for both arsenic and fluoride is very much a field of development. As new data sets become available, the models will certainly be refined. One important factor is nutritional status, as malnutrition increases the likelihood of disease (NRC, 2001 and references therein). Differences in water consumption and diet, and the speciation of the contaminant in foodstuffs, have also been noted as factors that affect dose-response functions.
Exposure assessment: The determination of the size and nature of the population exposed, and the route, amount and duration of the exposure. The estimated daily intake (EDI) is the sum of all possible inputs, including water and foodstuffs, per unit body weight per unit time. More details can be found, for example, in Phan et al., 2010 or Erdal and Buchanan, 2005. The EDI can be simplified to contaminant intake via water, but ideally it should be demonstrated that other pathways can be excluded. This step is important, because in cases where contaminant concentration in water is not so high, other sources become important. Section 9.4 provides a good example of fluoride intake in Ethiopia.
Risk characterisation: An integration of steps 1–3 to estimate the magnitude of the public health problem, including information uncertainties. The units are the number of people affected, often per 100,000 people. With a QHRA, it is possible to estimate the number of people that are at risk in a particular population, but how can different health effects (i.e. skin lesions, cancer) be compared? How can death and/or disability be compared? Comparisons of risks on the same scale are a valuable aid in evaluating and planning interventions to improve health. The concept of disease burden is based on the need for such a tool.
Estimation of disease burden
One DALY can be thought of as one year of healthy life lost, and the overall disease burden can be thought of as a measure of the gap between current health status and ideal health status, where the individual lives to old age free from disease and disability. Fewtrell et al. (2005, 2006) assume a life expectancy of 80 years. The health burden (expressed in DALYs) is the sum of mortality (years of life lost, YLL, and years of life with disability, YLD). Disability levels are weighted (see Table 3.4). The weighting correlates to the degree of disability (WHO, 2014). DALY = YLL + YLD where YLL = N x L N: Number of deaths L: Standard life expectancy at age of death in years and YLD = P x DW P: Number of prevalent cases DW: Disability weighting
The weighting corresponds to the loss in quality of life. Fewtrell et al. (2006) give dental fluorosis a low weight of 0.0033 that remains constant with age. They base the weight for skeletal fluorosis on that of untreated rheumatoid arthritis with a weight of 0.24 for the age range 40–59 and of 0.5 for those aged 60 or above. A weighting of 0.1–0.2 is given for arsenic-related skin lesions, depending on the length of exposure (Fewtrell et al., 2005). The DALY can be used to compare different scenarios. For example, DALY estimates have been used to compare the health burden associated with water consumption from different arsenicosis mitigation options in Bangladesh considering both the potential decrease of arsenic intake and to the potential increase in microbial contamination (Howard et al., 2006, 2007), Due to the complexity of the calculations, no examples are given in this handbook. Seriously interested readers should consult the literature and guidelines and tools provided by the WHO on the estimation of the national burden of disease (WHO, 2001, 2014).
For references, please visit the page References - Geogenic Contamination Handbook.