Cost/variance optimization for human exposure assessment studies

Abstract

The National Human Exposure Assessment Survey (NHEXAS) field study in EPA Region V (one of three NHEXAS field studies) provides extensive exposure data on a representative sample of 249 residents of the Great Lakes states. Concentration data were obtained for both metals and volatile organic compounds (VOCs) from multiple environmental media and from human biomarkers. A variance model for the logarithms of concentration measurements is used to define intraclass correlations between observations within primary sampling units (PSUs) (nominally counties) and within secondary sampling units (SSUs) (nominally Census blocks). A model for the total cost of the study is developed in terms of fixed costs and variable costs per PSU, SSU, and participant. Intraclass correlations are estimated for media and analytes with sufficient sample sizes. We demonstrate how the intraclass correlations and variable cost components can be used to determine the sample allocation that minimizes cost while achieving pre-specified precision constraints for future studies that monitor environmental concentrations and human exposures for metals and VOCs.

Cost-efficient assessment of biomechanical exposure in occupational groups, exemplified by posture observation and inclinometry

“…Thus, a 2010 systematic review of literature focusing on cost-efficient collection of exposure data (18) found only nine studies dealing with the trade-off between statistical performance and monetary resources invested in obtaining that performance, even if some studies have appeared after 2010 (19)(20)(21). Only some of the publications identified in the 2010 review dealt specifically with occupational or environmental exposures (7,(22)(23)(24)(25)(26); only two of these included empirical data to illustrate cost and efficiency (24,26), and none were devoted to assessment of biomechanical exposure. In the context of study design, the trade-off between cost and statistical performance appears in the form of either one of two questions: (i) for a given research budget, which measurement method and sampling strategy delivers the highest statistical performance with respect to producing unbiased and precise data?…”

Optimizing cost-efficiency in mean exposure assessment - cost functions reconsidered

“…This cost function presents a generalisation of previously suggested linear cost functions [43,44,46] by permitting both linear and non-linear relationships between the sample size at different stages of data collection and the cost of obtaining data. With ( α, β, γ ) = (1,1,1), equation (2) takes the customary linear form used in previous studies.…”

“…A few studies take on the more challenging task of determining the optimally cost-efficient strategy at a certain budget, on the basis of specified costs for collecting data at different stages, and specified sizes of the corresponding variance components. The general significance of examining cost-efficiency in data collection is illustrated by previous studies appearing in a variety of research areas, including occupational hygiene [38], environmental medicine [39,42,43], clinical chemistry [44], and nutrition [45]. …”

“…Previous optimization studies have addressed hierarchical models with two [45-47] or three [43,44,47] stages, as well as the optimal allocation of measurements between two alternative yet correlated instruments for data collection [42,48,49]. All these studies have, however, assumed that the price of one measurement unit at each stage is constant, implying that costs increase in a linear fashion at that stage, proportionally to the number of samples.…”

Economic Decisions on Proposed Work Environmental Studies – a Theory for Cost and Value of Information

“…A purely efficient assessment of an exposure cannot be the basis for evaluation of the output if, for instance, the critical occupational exposures in the work environment (i. e. the exposures to disorders that are behind the social costs) are omitted in the study. By considering statistical efficiency as the actual output and not as a criterion for evaluation, resources have been allocated optimally between different stages of statistical production to approach the true average value of a single exposure variable [19][20][21][22][23][24]. Moreover, taking as an output the statistical efficiency in terms of precision and accuracy has led to obscurity in the costoutput relationship and unclear economic evaluations, as the output was not related to the social cost of work-related disorders caused by the exposure, and was also measured with different measurement units than the costs [18].…”