Evidence map›Paper›PMID 29209972›Full record

ArticleEnvironmental science and pollution research international2018

PBPK/PD assessment for Parkinson's disease risk posed by airborne pesticide paraquat exposure.

Yi-Hsien Cheng, Wei-Chun Chou, Ying-Fei Yang, Chi-Wei Huang, Chun Ming How, Szu-Chieh Chen, Wei-Yu Chen, Nan-Hung Hsieh, Yi-Jun Lin, Shu-Han You and 1 more

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Article in Environmental science and pollution research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 26 citations in OpenAlex.

  1. Dose Optimization of Tilmicosin againstJournal of agricultural and food chemistry · 2026
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  5. Lanostane Triterpenoid Metabolites from aMolecules (Basel, Switzerland) · 2020
    Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 7 institutions in 2 countries.

Yi-Hsien ChengInstitute of Computational Comparative Medicine, Department of Anatomy and Physiology, Kansas State University, Manhattan, KS, 66506, USA.
Wei-Chun ChouNational Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli County, 35053, Taiwan, Republic of China.
Ying-Fei YangDepartment of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 10617, Taiwan, Republic of China.
Chi-Wei HuangDepartment of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 10617, Taiwan, Republic of China.
Chun Ming HowDepartment of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 10617, Taiwan, Republic of China.
Szu-Chieh ChenDepartment of Public Health, Chung Shan Medical University, Taichung, 40201, Taiwan, Republic of China.
Wei-Yu ChenDepartment of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, 80708, Taiwan, Republic of China.
Nan-Hung HsiehDepartment of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77845, USA.
Yi-Jun LinInstitute of Food Safety and Health Risk Assessment, National Yang-Ming University, Taipei, 11221, Taiwan, Republic of China.
Shu-Han YouNational Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli County, 35053, Taiwan, Republic of China.
Chung-Min LiaoDepartment of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, 10617, Taiwan, Republic of China. cmliao@ntu.edu.tw.
National Taiwan University · TWNational Health Research Institutes · TWChung Shan Medical University Hospital · TWKansas State University · USKaohsiung Medical University · TWNational Yang Ming Chiao Tung University · TWTexas A&M University · US

Funding

MOST of Science and Technology (ROC) MOST 105-2313-B-002-020-MY3
6 · The paper itself

Abstract

Exposure to several specific pesticides has led to an increase of Parkinson's disease (PD) risk. However, it is difficult to quantify the PD population risk related to certain pesticides in regions where environmental exposure data are scarce. Furthermore, the time trend of the prevalence and incidence of PD embedded in the background relationship between PD risk and pesticide exposures has not been well characterized. It has been convincingly identified that a key pesticide associated significantly with an increased risk trend of PD is paraquat (PQ). Here, we present a novel, probabilistic population-based exposure-response approach to quantify the contribution from PQ exposure to prevalence risk of PD. We found that the largest PQ exposure contributions occurred in its positive trend during 2004-2011, with the PQ contributing nearly 21 and 24%, respectively, to the PD prevalence rates among the age groups of 70-79 and ≥ 80 years in Taiwan. We also employed the present population risk model to predict the PQ-induced PD prevalence based on the projected rates of increase in PQ exposure associated with age-specific population. The predicted outcome can be used as an early warning signal for public health authorities. We suggest that a mechanistic understanding of the contribution of a specific pesticide exposure to PD risk trends is crucial to enhance our insights into the perspective on the impacts of environmental exposure on the neurodegenerative diseases.

Indexed as

AgedAged, 80 and overAir PollutantsEnvironmental ExposureHumansMiddle AgedParaquatParkinson DiseasePesticidesPrevalenceRisk FactorsTaiwanAir PollutantsParaquatPesticidesParaquatParkinson’s diseasePBPK/PDPesticidePopulation exposure-response functionProbabilistic risk assessment

Identifiers

PMID29209972
OpenAlexW2772591596

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.