Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Jiu-Chiuan Chen is active.

Publication


Featured researches published by Jiu-Chiuan Chen.


Neurotoxicology | 2014

Components of air pollution and cognitive function in middle-aged and older adults in Los Angeles

Nicole M. Gatto; Victor W. Henderson; Howard N. Hodis; Jan A. St. John; Fred Lurmann; Jiu-Chiuan Chen; Wendy J. Mack

While experiments in animals demonstrate neurotoxic effects of particulate matter (PM) and ozone (O3), epidemiologic evidence is sparse regarding the relationship between different constituencies of air pollution mixtures and cognitive function in adults. We examined cross-sectional associations between various ambient air pollutants [O3, PM2.5 and nitrogen dioxide (NO2)] and six measures of cognitive function and global cognition among healthy, cognitively intact individuals (n=1496, mean age 60.5 years) residing in the Los Angeles Basin. Air pollution exposures were assigned to each residential address in 2000-06 using a geographic information system that included monitoring data. A neuropsychological battery was used to assess cognitive function; a principal components analysis defined six domain-specific functions and a measure of global cognitive function was created. Regression models estimated effects of air pollutants on cognitive function, adjusting for age, gender, race, education, income, study and mood. Increasing exposure to PM2.5 was associated with lower verbal learning (β=-0.32 per 10 μg/m(3) PM2.5, 95% CI=-0.63, 0.00; p=0.05). Ambient exposure to NO2 >20 ppb tended to be associated with lower logical memory. Compared to the lowest level of exposure to ambient O3, exposure above 49 ppb was associated with lower executive function. Including carotid artery intima-media thickness, a measure of subclinical atherosclerosis, in models as a possible mediator did not attenuate effect estimates. This study provides support for cross-sectional associations between increasing levels of ambient O3, PM2.5 and NO2 and measures of domain-specific cognitive abilities.


Environmental Science & Technology | 2017

Constrained Mixed-Effect Models with Ensemble Learning for Prediction of Nitrogen Oxides Concentrations at High Spatiotemporal Resolution

Lianfa Li; Fred Lurmann; Rima Habre; Robert Urman; Edward B. Rappaport; Beate Ritz; Jiu-Chiuan Chen; Frank D. Gilliland; Jun Wu

Spatiotemporal models to estimate ambient exposures at high spatiotemporal resolutions are crucial in large-scale air pollution epidemiological studies that follow participants over extended periods. Previous models typically rely on central-site monitoring data and/or covered short periods, limiting their applications to long-term cohort studies. Here we developed a spatiotemporal model that can reliably predict nitrogen oxide concentrations with a high spatiotemporal resolution over a long time span (>20 years). Leveraging the spatially extensive highly clustered exposure data from short-term measurement campaigns across 1-2 years and long-term central site monitoring in 1992-2013, we developed an integrated mixed-effect model with uncertainty estimates. Our statistical model incorporated nonlinear and spatial effects to reduce bias. Identified important predictors included temporal basis predictors, traffic indicators, population density, and subcounty-level mean pollutant concentrations. Substantial spatial autocorrelation (11-13%) was observed between neighboring communities. Ensemble learning and constrained optimization were used to enhance reliability of estimation over a large metropolitan area and a long period. The ensemble predictions of biweekly concentrations resulted in an R2 of 0.85 (RMSE: 4.7 ppb) for NO2 and 0.86 (RMSE: 13.4 ppb) for NOx. Ensemble learning and constrained optimization generated stable time series, which notably improved the results compared with those from initial mixed-effects models.


Atmospheric Environment | 2018

Source characterization and exposure modeling of gas-phase polycyclic aromatic hydrocarbon (PAH) concentrations in Southern California

Shahir Masri; Lianfa Li; Andy Dang; Judith Chung; Jiu-Chiuan Chen; Zhi-Hua (Tina) Fan; Jun Wu

Airborne exposures to polycyclic aromatic hydrocarbons (PAHs) are associated with adverse health outcomes. Because personal air measurements of PAHs are labor intensive and costly, spatial PAH exposure models are useful for epidemiological studies. However, few studies provide adequate spatial coverage to reflect intra-urban variability of ambient PAHs. In this study, we collected 39-40 weekly gas-phase PAH samples in southern California twice in summer and twice in winter, 2009, in order to characterize PAH source contributions and develop spatial models that can estimate gas-phase PAH concentrations at a high resolution. A spatial mixed regression model was constructed, including such variables as roadway, traffic, land-use, vegetation index, commercial cooking facilities, meteorology, and population density. Cross validation of the model resulted in an R2 of 0.66 for summer and 0.77 for winter. Results showed higher total PAH concentrations in winter. Pyrogenic sources, such as fossil fuels and diesel exhaust, were the most dominant contributors to total PAHs. PAH sources varied by season, with a higher fossil fuel and wood burning contribution in winter. Spatial autocorrelation accounted for a substantial amount of the variance in total PAH concentrations for both winter (56%) and summer (19%). In summer, other key variables explaining the variance included meteorological factors (9%), population density (15%), and roadway length (21%). In winter, the variance was also explained by traffic density (16%). In this study, source characterization confirmed the dominance of traffic and other fossil fuel sources to total measured gas-phase PAH concentrations while a spatial exposure model identified key predictors of PAH concentrations. Gas-phase PAH source characterization and exposure estimation is of high utility to epidemiologist and policy makers interested in understanding the health impacts of gas-phase PAHs and strategies to reduce emissions.


American Journal of Epidemiology | 2018

Long-Term Ambient Temperature and Externalizing Behaviors in Adolescents

Diana Younan; Lianfa Li; Catherine Tuvblad; Jun Wu; Fred Lurmann; Meredith Franklin; Kiros Berhane; Rob McConnell; Anna H. Wu; Laura A. Baker; Jiu-Chiuan Chen

The climate-violence relationship has been debated for decades, and yet most of the supportive evidence has come from ecological or cross-sectional analyses with very limited long-term exposure data. We conducted an individual-level, longitudinal study to investigate the association between ambient temperature and externalizing behaviors of urban-dwelling adolescents. Participants (n = 1,287) in the Risk Factors for Antisocial Behavior Study, in California, were examined during 2000-2012 (aged 9-18 years) with repeated assessments of their externalizing behaviors (e.g., aggression, delinquency). Ambient temperature data were obtained from the local meteorological information system. In adjusted multilevel models, aggressive behaviors significantly increased with rising average temperatures (per 1°C increment) in the preceding 1, 2, or 3 years (respectively, β = 0.23, 95% confidence interval (CI): 0.00, 0.46; β = 0.35, 95% CI: 0.06, 0.63; or β = 0.41, 95% CI: 0.08, 0.74), equivalent to 1.5-3.0 years of delay in age-related behavioral maturation. These associations were slightly stronger among girls and families of lower socioeconomic status but greatly diminished in neighborhoods with more green space. No significant associations were found with delinquency. Our study provides the first individual-level epidemiologic evidence supporting the adverse association of long-term ambient temperature and aggression. Similar approaches to studying meteorology and violent crime might further inform scientific debates on climate change and collective violence.


Alzheimers & Dementia | 2018

ENVIRONMENTAL DETERMINANTS OF NEUROANATOMIC RISK FOR ALZHEIMER’S DISEASE IN OLDER WOMEN: ROLE OF FINE PARTICULATE MATTER

Diana Younan; Xinhui Wang; Andrew J. Petkus; Ramon Casanova; Ryan T. Barnard; Sarah A. Gaussoin; Santiago Saldana; Susan M. Resnick; Marc L. Serre; William Vizuete; Sally A. Shumaker; Margaret Gatz; Helena Chang Chui; Mark A. Espeland; Jiu-Chiuan Chen

in self-reported CA over time on global cognition in older adults without mild cognitive impairment or dementia. Methods: Participants were 742 older adults from the RushMemory and Aging Project, an ongoing epidemiological cohort study. Participants were recruited from Chicago communities, and agreed to annual clinical evaluations, including neurocognitive testing and wearing an accelerometer for 10 days. Exclusion criteria included diagnosis or symptoms of mild cognitive impairment or dementia. Longitudinal data with 3-5 time points were used, with the first time point being the first assessment with both accelerometer and neurocognitive data. A parallel growth model tested the interaction between change over time in PA (mean daily accelerometer counts) and change over time in CA (self-report of seven activities) on global cognition (index of 19 neurocognitive tests). Results:Higher levels of baseline PA (p<.001) and baseline CA (p<.001) were each related to higher global cognition at five years. Increases in CA over time were significantly related to higher global cognition (p<.001), but change in PA over time was unrelated to global cognition. The interaction between change in PA and change in CA over time was significantly related to higher global cognition (p<.001) such that the positive effects of changes in CAwere stronger among those who had increases in PA over time. Conclusions: These findings suggest the importance of considering changes in both PA and CA over time in order to prevent cognitive decline in older adults. PA and CA show evidence of synergistic effects on cognition, which should be further explored in trials with factorial designs of multi-domain interventions.


Alzheimers & Dementia | 2018

MEMORY RESERVE MODERATES THE ASSOCIATION BETWEEN A NEUROANATOMICAL MEASURE OF AD RISK AND GLOBAL COGNITIVE DECLINE IN THE WOMEN’S HEALTH INITIATIVE MEMORY STUDY

Andrew J. Petkus; Mark A. Espeland; Ramon Casanova; Xinhui Wang; Diana Younan; Stephen R. Rapp; Helena C. Chui; Kathleen M. Hayden; Margaret Gatz; Sarah A. Gaussoin; Ryan T. Barnard; Santiago Saldana; Sally A. Shumaker; Jiu-Chiuan Chen

Figure 1. Mod Impairment (M imaging patho graphic factors cise), and clin and cardiovasc split. RISK AND GLOBAL COGNITIVE DECLINE IN THE WOMEN’S HEALTH INITIATIVE MEMORY STUDY Andrew J. Petkus, Mark A. Espeland, Ramon Casanova, Xinhui Wang, Diana Younan, Stephen R. Rapp, Helena C. Chui, Kathleen M. Hayden, Margaret Gatz, Sarah A. Gaussoin, Ryan Barnard, Santiago Saldana, Sally A. Shumaker, Jiu-Chiuan Chen, University of Southern California, Los Angeles, CA, USA; Wake Forest School of Medicine, Winston-Salem, NC, USA; Keck School of Medicine at USC, Los Angeles, CA, USA; Bryan Alzheimer’s Disease Research Center, Duke University, Durham, NC, USA. Contact e-mail: [email protected]


PLOS ONE | 2017

Socioeconomic disparities and sexual dimorphism in neurotoxic effects of ambient fine particles on youth IQ: A longitudinal analysis

Pan Wang; Catherine Tuvblad; Diana Younan; Meredith Franklin; Fred Lurmann; Jun Wu; Laura A. Baker; Jiu-Chiuan Chen

Mounting evidence indicates that early-life exposure to particulate air pollutants pose threats to children’s cognitive development, but studies about the neurotoxic effects associated with exposures during adolescence remain unclear. We examined whether exposure to ambient fine particles (PM2.5) at residential locations affects intelligence quotient (IQ) during pre-/early- adolescence (ages 9–11) and emerging adulthood (ages 18–20) in a demographically-diverse population (N = 1,360) residing in Southern California. Increased ambient PM2.5 levels were associated with decreased IQ scores. This association was more evident for Performance IQ (PIQ), but less for Verbal IQ, assessed by the Wechsler Abbreviated Scale of Intelligence. For each inter-quartile (7.73 μg/m3) increase in one-year PM2.5 preceding each assessment, the average PIQ score decreased by 3.08 points (95% confidence interval = [-6.04, -0.12]) accounting for within-family/within-individual correlations, demographic characteristics, family socioeconomic status (SES), parents’ cognitive abilities, neighborhood characteristics, and other spatial confounders. The adverse effect was 150% greater in low SES families and 89% stronger in males, compared to their counterparts. Better understanding of the social disparities and sexual dimorphism in the adverse PM2.5–IQ effects may help elucidate the underlying mechanisms and shed light on prevention strategies.


Journal of the American Academy of Child and Adolescent Psychiatry | 2016

Environmental determinants of aggression in adolescents: role of urban neighborhood greenspace

Diana Younan; Catherine Tuvblad; Lianfa Li; Jun Wu; Fred Lurmann; Meredith Franklin; Kiros Berhane; Rob McConnell; Anna H. Wu; Laura A. Baker; Jiu-Chiuan Chen


Atmospheric Environment | 2017

Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

Lianfa Li; Anna H. Wu; Iona Cheng; Jiu-Chiuan Chen; Jun Wu


Journal of Abnormal Child Psychology | 2018

Longitudinal Analysis of Particulate Air Pollutants and Adolescent Delinquent Behavior in Southern California

Diana Younan; Catherine Tuvblad; Meredith Franklin; Fred Lurmann; Lianfa Li; Jun Wu; Kiros Berhane; Laura A. Baker; Jiu-Chiuan Chen

Collaboration


Dive into the Jiu-Chiuan Chen's collaboration.

Top Co-Authors

Avatar

Diana Younan

University of Southern California

View shared research outputs
Top Co-Authors

Avatar

Fred Lurmann

University of Southern California

View shared research outputs
Top Co-Authors

Avatar

Jun Wu

University of California

View shared research outputs
Top Co-Authors

Avatar

Lianfa Li

Chinese Academy of Sciences

View shared research outputs
Top Co-Authors

Avatar

Catherine Tuvblad

University of Southern California

View shared research outputs
Top Co-Authors

Avatar

Laura A. Baker

University of Southern California

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Meredith Franklin

University of Southern California

View shared research outputs
Top Co-Authors

Avatar

Margaret Gatz

University of Southern California

View shared research outputs
Top Co-Authors

Avatar

Xinhui Wang

University of Southern California

View shared research outputs
Researchain Logo
Decentralizing Knowledge