Mitigating the scale effects of the MAUP in environmental health studies

Keywords: MAUP, scale effects, environment-health associations, lacunarity analysis, model averaging, exposome studies
Session Type: Virtual Paper Abstract
Day: Saturday
Session Start / End Time: 2/26/2022 08:00 AM (Eastern Time (US & Canada)) - 2/26/2022 09:20 AM (Eastern Time (US & Canada))
Room: Virtual 3

Abstract

Several studies found that environmental exposures such as greenspace benefits human health, while increased noise and air pollution levels are associated with the incidence of chronic diseases. Such associations are, however, not always consistent across studies. The conflicting results might be caused by the modifiable areal unit problem (MAUP) that arises when exposure contexts were delineated differently. Individual-based delineations are one emerging approach which represents the health-influencing environment by creating buffers that center on individual’s residential addresses. However, there is a lack of empirical guidance regarding the appropriate buffer distance for different exposures. Second, studies usually examine the joint effects of exposures by applying the same buffer size for different exposures in one model. Both practices are problematic because they are likely to be susceptible to the scale effects of the MAUP. Our research aims to fill these gaps. First, we seek to find the appropriate buffer sizes for assessing greenspace, noise, and PM2.5 exposures. Second, the obtained appropriate buffer size of each exposure will be applied in multi-exposure models to examine the effects of exposures. The proposed workflow consists of two steps. First, we assess the lacunarity, a scale-dependent measurement of heterogeneity, to define the scale where the spatial pattern of exposures becomes invariant. Buffer sizes smaller than the scale are regarded to be appropriate. Second, the obtained appropriate buffer sizes are then used within a Bayesian Model Averaging approach to assess exposure-health association. Our data-driven workflow contributes to mitigating scale effects of the MAUP in future exposome studies.