Human monitoring analysis calculation

Human monitoring analysis computes internal substance concentration estimates based on provided human monitoring data. These estimates are specified at the level of long term average concentrations for individuals in case of chronic assessments, or the average concentrations for individual-days in case of acute assessments. The internal concentrations are computed independently for each substance, compartment, and sampling type.

The main steps for computing the human monitoring concentration estimates are:

1. Imputation of non-detects.

2. Imputation of missing values.

3. Calculation of individual concentrations (chronic) or individual day concentrations (acute).

4. Comparison of monitoring versus modelled exposures by substance and compartment (optional).

Imputation of non-detects

Similar to concentrations measurements in food, human monitoring measurements can also contain measurements below the limit of reporting and similar to concentrations modelling in foods, human monitoring analysis needs to address these non-detects and replace them with imputed concentration values. For this, two approaches are available:

1. Replace non-detects by zero.

2. Replace non-detects by a factor times LOR, in which the factor is set between zero and one.

Imputation of missing values

Concentration measurements may be missing. The following imputation methods are available for imputation of missing values:

1. Replace missing values by zero.

2. For each substance, sampling type, and compartment, replace missing values by a random other sample of this substance, sampling type, and compartment.

Note

For the second imputation method, more refined methods could be useful as well. E.g., when for a given day multiple samples are available, of which one is missing, then it may alternatively be sensible to leave this sample out when computing an average exposure. Also, when samples have been taken at different times during the day, it may be better to impute missing records using samples approximately from the same time-slot.

Calculation of acute human monitoring concentrations

For acute assessments, the monitoring concentrations are computed for each substance, compartment, and sampling type as average individual-day concentrations. That is, for a given substance, compartment, and sampling type, the acute individual-day concentration \(c_{ij}\) for individual \(i\) on day \(j\) is:

\[c_{ij} = \frac{\sum_{k = 1}^{n_{\mathtt{samples}}} c_{ijk} \cdot \mathit{sg}_{ijk}}{n_{\mathtt{samples}}} ,\]

where \(n_{\mathtt{samples}}\) is the number of samples available for individual \(i\) on day \(j\), and \(c_{ijk}\) and \(\mathit{sg}_{ijk}\) denote the concentration and specific gravity, respectively, of the \(k\)-th sample of the individual day.

Note

Note that currently, the acute concentrations are computed as mean concentrations when multiple samples are available for one day. In acute scenarios, one may be more interested in peak concentrations. I.e., the highest concentration of a day.

Calculation of chronic human monitoring concentrations

Note

The implementation for chronic is not yet available. Below is a description of the foreseen implementation.

For chronic assessments, the monitoring concentrations are computed as the average monitoring concentrations of multiple individual-days for each substance, compartment, and sampling type. That is, for a given substance, compartment, and sampling type, the chronic concentration \(c_{i}\) for individual \(i\) is:

\[c_{i} = \frac{\sum_{j = 1}^{n_{\mathtt{days}}} c_{ij}}{n_{\mathtt{days}}} ,\]

where \(n_{\mathtt{days}}\) is the number of days that individual \(i\) was monitored, and \(c_{ij}\) denotes the average monitoring concentration of individual \(i\) on day \(j\).

Compare measured and modelled exposures

An optional step of the human monitoring analysis is to compare the monitoring concentrations with modelled exposures that were obtained from dietary (and optionally non-dietary) exposure assessments. This comparison may provide insight in the coherence between modelled exposures and the measured reality. A requirement is that both monitoring data and dietary/non-dietary use data is available for the same individuals or individual-days. An example of a graphical output of these comparison is given in Figure 67.

Figure 67 Measured exposures from monitoring versus modelled exposures