Human monitoring analysis calculation

Human monitoring analysis computes internal substance concentration estimates based on 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 contain measurements below the limit of reporting and similar to concentrations modelling in foods, human monitoring analysis addresses these non-detects and replaces them with imputed concentration values. Two approaches are available:

1. Replace non-detects by zero.

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

In Figure 70, the human monitoring concentrations data for three bisphenols are imputed with a factor * LOR and the summary statistics are visualized.

Figure 70 Boxplots for imputed concentration data for bisphenols BPA, BPS and BPF. Lower whiskers indicate the p5 and p10 percentiles, upper whiskers the p90 and p95. The edges of the box indicate the p25 and p75 percentiles with the median in the centre of the box.

Imputation of missing values

For missing concentration measurements, two imputation methods are available:

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 used. E.g., when for a given day multiple samples are available and one is missing, then this sample might be neglected in the computation of an average exposure. Also, when samples have been taken at different time-slots, impute the missing records using samples 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. For a given substance, compartment, and sampling type, the acute individual-day concentration \(c_{ij}\) for individual \(i\) on day \(j\) is:

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

\(n_{\mathtt{samples}}\) 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 correction factor, respectively, of the \(k\)-th sample of the individual day \(j\).

Note

Currently, acute concentrations are computed as the mean concentration of multiple samples on a day. In acute scenarios, the interest may be in peak concentrations, i.e., the highest concentration during a day.

Calculation of chronic human monitoring concentrations

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

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

\(n_{\mathtt{days}}\) 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 in the analysis of human monitoring data is to compare the concentrations with modelled exposures obtained from dietary (and optionally non-dietary) exposure assessments. The comparison provides insight in the coherence between modelled exposures and the measured reality. It is required that monitoring data and dietary/non-dietary exposure data are available for the same individual or individual-day. In Figure 71, an example is shown.

Figure 71 Monitoring versus modelled concentrations for bisphenol BPA

In Figure 72, summary statistics are visualised for the monitoring and modelled concentrations for bisphenols BPA, BPS and BPF.

Figure 72 Boxplots for monitoring and modelled concentrations for bisphenols BPA, BPS and BPF. Lower whiskers indicate the p5 and p10 percentiles, upper whiskers the p90 and p95. The edges of the box indicate the p25 and p75 percentiles with the median in the centre of the box.