We assessed time-location patterns and the role of individual- and residential-level characteristics on these patterns within the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) cohort and also investigated the impact of individual-level time-location patterns on individual-level estimates of exposure to outdoor air pollution. Reported time-location patterns varied significantly by demographic factors such as age, gender, race/ethnicity, income, education, and employment status. On average, Chinese participants reported spending significantly more time indoors and less time outdoors and in transit than White, Black, or Hispanic participants. Using a tiered linear regression approach, we predicted time indoors at home and total time indoors. Our model, developed using forward-selection procedures, explained 43% of the variability in time spent indoors at home, and incorporated demographic, health, lifestyle, and built environment factors. Time-weighted air pollution predictions calculated using recommended time indoors from USEPA overestimated exposures as compared with predictions made with MESA Air participant-specific information. These data fill an important gap in the literature by describing the impact of individual and residential characteristics on time-location patterns and by demonstrating the impact of population-specific data on exposure estimates.
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http://dx.doi.org/10.1038/jes.2015.26 | DOI Listing |
Heliyon
December 2024
School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Investigating hidden hazards and implementing closed-loop management are essential strategies for accident prevention in the mining industry. This study tackles a key challenge in applying association rule mining to the development of hazard management plans for underground mines. The current approach mainly focuses on hazard description data, often underutilizing critical information such as hazard time and location.
View Article and Find Full Text PDFPrev Vet Med
December 2024
Department of Population Health and Pathobiology, North Carolina State University College of Veterinary Medicine, Raleigh, NC 27606, USA.
Empirical data on livestock contact networks are scarce but digital technologies are increasingly used to characterize animal behavior and describe the dynamics of contact networks. The objective of this study was to use contact network analysis to quantify contacts within three pens of feedlot cattle across three consecutive years at varying temporal resolutions to better inform the construction of network-based disease transmission models for cattle within confined-housing systems. We also aimed to describe the influence of the variation in Real-Time Location System (RTLS) average tag read rates and the effect of increasing minimum contact duration (MCD) on the contact networks of feedlot cattle.
View Article and Find Full Text PDFBMC Infect Dis
December 2024
Department of Population, Family and Reproductive Health, School of Public Health, University of Ghana, Legon, Ghana.
Background: There is currently limited knowledge about HIV prevention and treatment cascades among female sex workers (FSW) in Ghana. This study sought to use the 2020 bio-behavioural survey (BBS) among FSWs to identify gaps and priorities in HIV treatment and prevention cascades to help achieve the 95-95-95 fast track targets.
Method: The study used a cross-sectional design with Time Location Sampling (TLS) technique in all regions of Ghana.
Am J Epidemiol
November 2024
Center for Public Health Research, San Francisco Department of Public Health, San Francisco, CA, USA.
During the COVID-19 pandemic, the sampling method for the National HIV Behavioral Surveillance (NHBS) in San Francisco changed from physical venue time-location sampling (TLS) to online or virtual venue TLS for men who have sex with men (MSM). We present differences in the samples of MSM recruited using physical venue TLS in 2017 and virtual venue TLS in 2021. We further assess changes in preventive and risk behaviors from 2017 to 2021 after controlling for differences in the sample compositions with multivariable Poisson models using GLM with robust standard errors.
View Article and Find Full Text PDFJDS Commun
November 2024
Department of Animal Biosciences, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden.
Dairy cattle are frequently housed in freestalls with limited space, affecting social interactions between individuals. Social behavior in dairy cattle is gaining recognition as a valuable tool for identifying sick animals, but its application is hampered by the complexities of analyzing social interactions in intensive housing systems. In this context, precision livestock technologies present the opportunity to continuously monitor dyadic spatial associations on dairy farms.
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