Wen-Chi Pan

Dr. Wen-Chi Pan

National Yang-Ming University
orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2017 in Environmental Pollution
Verified
Journal Article
Closed access
Chih-Da WuChih-Da Wu
Chih-Da Wu
YCYu-Cheng Chen
Yu-Cheng Chen
Wen-Chi PanWen-Chi Pan
Wen-Chi Pan
YZYu-Ting Zeng
Yu-Ting Zeng
MCMu-Jean Chen
Mu-Jean Chen
Shih-Chun Candice LungShih-Chun Candice Lung
Shih-Chun Candice Lung

HLHsiao-Yun Lee
Hsiao-Yun Lee
CYChia-Pin Yu
Chia-Pin Yu
Chih-Da WuChih-Da Wu
Chih-Da Wu
Wen-Chi PanWen-Chi Pan
Wen-Chi Pan
Previous studies have confirmed that activity participation is beneficial to mental health, but few studies focus on older adults’ depression. Based on the theory of social integration, this study examined the effects of leisure activity diversity and exercise time on depression in late adulthood. Subjects in the 2011 Survey of Health and Living Status of the Middle-Aged and Elderly in Taiwan were extracted. A series of logistic regressions were conducted to discern factors related to the odds of having depression. Among study subjects (N = 3727; age ≥ 58), 20.9% indicated an inclination of having depression (CESD-10 score ≥ 8). This study found that participating in diverse leisure activities and longer exercise time decreases older adults’ risk of having depression. Additionally, the results confirmed that depression is positively correlated with chronic diseases. Consequently, efforts should be continually spent on encouraging older adults’ participation in activities to reduce the prevalence of depression.

THTao Huang
Tao Huang
TCTa-Chien Chan
Ta-Chien Chan
YHYing-Jhen Huang
Ying-Jhen Huang
Wen-Chi PanWen-Chi Pan
Wen-Chi Pan
Metabolic syndrome is becoming more common worldwide. Studies suggest environmental pollution, including traffic noise, might be linked with metabolic syndrome. This study sought to evaluate how noise exposure is linked to the development of metabolic syndrome and its components in Taiwan. Using data from a cohort of 42,509 participants and Cox proportional hazards regression models, the effects of noise exposure on metabolic syndrome and its components were quantified. After adjustment for covariates (age, gender, body mass index, and physical activity), the hazard ratio for metabolic syndrome was 1.13 (95% CI: 1.04–1.22) for medium noise exposure and 1.24 (95% CI: 1.13–1.36) for high noise exposure. Noise exposure was also positively associated with all of metabolic syndrome’s components. This finding suggests noise exposure might contribute to metabolic syndrome and its components. Policies aiming to reduce noise pollution might reduce the risks of metabolic syndrome and its components.

HTHui-Ju Tsai
Hui-Ju Tsai
CLChia-Ying Li
Chia-Ying Li
Wen-Chi PanWen-Chi Pan
Wen-Chi Pan
TYTsung-Chieh Yao
Tsung-Chieh Yao
HSHuey-Jen Su
Huey-Jen Su
JSJohn Spengler
John Spengler
This study determines whether surrounding greenness is associated with the incidence of type 2 diabetes Mellitus (T2DM) in Taiwan. A retrospective cohort study determines the relationship between surrounding greenness and the incidence of T2DM during the study period of 2001–2012 using data from the National Health Insurance Research Database. The satellite-derived normalized difference vegetation index (NDVI) from the global MODIS database in the NASA Earth Observing System is used to assess greenness. Cox proportional hazard models are used to determine the relationship between exposure to surrounding greenness and the incidence of T2DM, with adjustment for potential confounders. A total of 429,504 subjects, including 40,479 subjects who developed T2DM, were identified during the study period. There is an inverse relationship between exposure to surrounding greenness and the incidence of T2DM after adjustment for individual-level covariates, comorbidities, and the region-level covariates (adjusted HR = 0.81, 95% CI: 0.79–0.82). For the general population of Taiwan, greater exposure to surrounding greenness is associated with a lower incidence of T2DM.

HLHsiao-Yun Lee
Hsiao-Yun Lee
Chih-Da WuChih-Da Wu
Chih-Da Wu
YCYi-Tsai Chang
Yi-Tsai Chang
YCYinq-Rong Chern
Yinq-Rong Chern
Shih-Chun Candice LungShih-Chun Candice Lung
Shih-Chun Candice Lung
Wen-Chi PanWen-Chi Pan
Wen-Chi Pan
Exposure to surrounding greenness is associated with reduced mortality in Caucasian populations. Little is known however about the relationship between green vegetation and the risk of death in Asian populations. Therefore, we opted to evaluate the association of greenness with mortality in Taiwan. Death information was retrieved from the Taiwan Death Certificate database between 2006 to 2014 (3287 days). Exposure to green vegetation was based on the normalized difference vegetation index (NDVI) collected by the Moderate Resolution Imagine Spectroradiometer (MODIS). A generalized additive mixed model was utilized to assess the association between NDVI exposure and mortality. A total of 1,173,773 deaths were identified from 2006 to 2014. We found one unit increment on NDVI was associated with a reduced mortality due to all-cause (risk ratio [RR] = 0.901; 95% confidence interval = 0.862–0.941), cardiovascular diseases (RR = 0.892; 95% CI = 0.817–0.975), respiratory diseases (RR = 0.721; 95% CI = 0.632–0.824), and lung cancer (RR = 0.871; 95% CI = 0.735–1.032). Using the green land cover as the alternative green index showed the protective relationship on all-cause mortality. Exposure to surrounding greenness was negatively associated with mortality in Taiwan. Further research is needed to uncover the underlying mechanism.

CHChin-Yu Hsu
Chin-Yu Hsu
JWJhao-Yi Wu
Jhao-Yi Wu
Yu-Cheng ChenYu-Cheng Chen
Yu-Cheng Chen
NCNai-Tzu Chen
Nai-Tzu Chen
MCMu-Jean Chen
Mu-Jean Chen
Chih-Da WuChih-Da Wu
Chih-Da Wu
This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O3 concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency’s (EPA) data of O3 concentrations from 2000 and 2013 were used to develop this model, while observations from 2014 were used as the external data verification to assess model reliability. The distribution of temples, cemeteries, and crematoriums was included for a potential predictor as an Asian culturally specific source for incense and joss money burning. We used stepwise regression for the LUR model development, and applied 10-fold cross-validation and external data for the verification of model reliability. With the overall model R2 of 0.74 and a 10-fold cross-validated R2 of 0.70, this model presented a mid-high prediction performance level. Moreover, during the stepwise selection procedures, the number of temples, cemeteries, and crematoriums was selected as an important predictor. By using the long-term monitoring data to establish an LUR model with culture specific predictors, this model can better depict O3 concentration variation in Asian areas.