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HOME Study FAQ
Disparities in exposure along racial/ethnic and socioeconomic lines may be key drivers of environmental health disparities (EHDs) in the United States. Most individuals spend 80-90% of their day indoors; therefore, it is important to study disparities in indoor microenvironmental exposures. Indoor exposures to chemical and non-chemical stressors are influenced by ambient conditions, housing characteristics, and in-home activities. While spatiotemporal variability in ambient chemical and non-chemical stressors can be substantial, the modifying effects of housing attributes and in-home activities can further differentiate exposures along significant within-neighborhood socioeconomic gradients. Most importantly, housing factors may not only modify personal exposures, but may also be a direct stressor with independent effects on health. Therefore, the combined effects of these housing-related exposures are likely to be highly influential in shaping EHDs.
In the Home-based Observation and Monitoring Exposure (HOME) study (Project 2), we aim to develop and implement innovative methods to provide improved estimates for between-household variability in exposures. We are identifying the key determinants of indoor exposure to chemical stressors as:
- activity patterns
- source usage
- ambient pollutant concentrations
- air exchange rates
We are studying these determinants within small spatial scales to best characterize drivers of exposure disparities and to directly inform targets for future mitigation at the household level. In addition, we are characterizing variability in non-chemical stressors (noise, thermal comfort) to understand the distribution of these key modifiers and their socio-demographic and structural predictors. We focus our intensive exposure monitoring study on CRESSH’s two partner communities of Chelsea and Dorchester, Massachusetts (MA).
1) Use portable, real-time monitoring devices to estimate indoor exposure to multiple chemical stressors, noise and the thermal comfort within 200 homes in Chelsea and Dorchester, MA.
2) Determine how resident behavior and housing characteristics affect indoor-outdoor associations of chemical stressors, noise, and thermal comfort in our study population, including associations with publicly available geospatial covariates from CRESSH: MAP-EHD.
3) Use community-based crowdsourcing approaches to assess housing and household characteristics to develop season-specific determinants that predict ventilation characteristics for residence in Chelsea and Dorchester.
Contact: Gary Adamkiewicz, Project Lead: email@example.com