Conducting studies on sharp particulate matter (PM) gradients in Asian residential communities is difficult due to their complex building arrangements and various emission sources, particularly road traffic. In this study, a synthetic methodology, combining numerical simulations and minor field observations, was set up to investigate the dispersion of traffic-related PM in a typical Asian residential community and its contribution to PM exposure. A Lagrangian particle model (GRAL) was applied to estimate the spatiotemporal variation of the traffic-related PM increments within the community. A detailed topography dataset with 5 m horizontal resolution was used to simulate a micro-scale flow field. The model performance was comprehensively validated using both in-situ and mobile observations. The coefficient of determination (R) of the simulated vs. observed PM reached 0.81 by an artery road, and 0.85 in alleys without significant road traffic. The maximum increments of kerbside PM exposure concentration contributed by road traffic during rush hour were found to be 38% (PM) and 40% (PM). This synthetic method was used to assess the impact of synoptic wind and canyon orientation on residents' PM exposure related to traffic exhaust. Perfect exponential decay curves of traffic-related PM were found within canyons. The decrease of road-traffic PM on five different floor levels, compared with that on kerbside levels, ranged between 42% and 100%. The results demonstrated that in complex Asian communities, Lagrangian particle models such as GRAL can simulate the spatial distribution of PM and PM and assess the residents' outdoor exposure.
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http://dx.doi.org/10.1016/j.envpol.2020.115046 | DOI Listing |
J Racial Ethn Health Disparities
January 2025
Valleywise Health, Phoenix, AZ, USA.
Background: Missed clinic appointments disproportionately affect Medicaid-insured patients and residents of socioeconomically deprived neighborhoods. The role of the recent telemedicine expansion in reducing these disparities is unclear. We analyzed the relationship between census tract (CT) poverty level, residential segregation, missed appointments, and the role of telemedicine.
View Article and Find Full Text PDFJ Am Med Dir Assoc
January 2025
The Gleen Biggs Institute for Alzheimer's & Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
Objectives: To assess recent trends in antipsychotic use among older adults with Alzheimer's disease and related dementias (ADRDs) according to their residential status and determine the factors associated with the use of antipsychotics.
Design: Population-based, cross-sectional study using Texas Medicare Fee-for-Service data.
Setting And Participants: Individuals ≥ 65 years of age with ADRDs who had at least 3 months of Medicare Part A and B, and Part D for prescription drug coverage, in any year between 2015 and 2020.
Int J Ment Health Nurs
February 2025
School of Nursing and Midwifery, University College Cork, Cork, Ireland.
China is the country with the largest population of older persons. Depression is the most common mental health issue among older adults, a trend expected to increase as societies continue to age. With the global increase in depression and depressive symptoms among this demographic, the resulting disease burden poses a significant challenge to health and social care systems in China.
View Article and Find Full Text PDFBMC Public Health
January 2025
School of Nursing and Midwifery, Griffith University, Brisbane, QLD, Australia.
Background: The Health Literacy Questionnaire (HLQ) is an increasingly used health literacy instrument that has been translated into many languages. The HLQ has 44 items and comprises 9 scales assessing the multidimensional construct of health literacy. This study reports the HLQ reliability and construct validity tested in people with chronic diseases living in Vietnam.
View Article and Find Full Text PDFJ Racial Ethn Health Disparities
January 2025
Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA, USA.
Recent research shows a significant link between race-ethnicity and income concentration and premature death rates in the U.S. However, most studies focus on Black-White residential concentration, overlooking racial-ethnic diversity.
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