Evidence map›Paper›PMID 35527564›Full record

ArticleJournal of Parkinson's disease2022

Independent and Joint Associations of Tea Consumption and Smoking with Parkinson's Disease Risk in Chinese Adults.

Jia Nie, Chunyu Liu, Canqing Yu, Yu Guo, Pei Pei, Ling Yang, Yiping Chen, Huaidong Du, Kaifei Zhu, Danile Schmidt and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of Parkinson's disease, 2022. 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
1.4field-weighted citation impact, top 18% 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, 11 citations in OpenAlex.

  1. Lifestyle medicine for neuroprotection: evidence and implementation in Asian contexts.Journal of neural transmission (Vienna, Austria : 1996) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 4 institutions in 2 countries.

Jia NieDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China.
Chunyu LiuDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China.
Canqing YuDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China.
Yu GuoFuwai hospital, Chinese Academy of Medical Sciences, Beijing, China.
Pei PeiChinese Academy of Medical Sciences, Beijing, China.
Ling YangMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom.
Yiping ChenMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom.
Huaidong DuMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom.
Kaifei ZhuNCDs Prevention and Control Department, Wuzhong Center for Disease Control and Prevention, China.
Danile SchmidtClinical Trial ServiceUnit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom.
Daniel AveryClinical Trial ServiceUnit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, China.
Zhengming ChenClinical Trial ServiceUnit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, United Kingdom.
Jun LvDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China.
Liming LiDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China.
China Kadoorie Biobank (CKB) Collaborative Group
Peking University · CNUniversity of Oxford · GBChinese Academy of Medical Sciences & Peking Union Medical College · CNChinese Center For Disease Control and Prevention · CN

Funding

Cancer Research UK 29186Medical Research Council MC_UU_00017/1Wellcome Trust
6 · The paper itself

Abstract

backgroundExisting limited evidence suggests that smoking and tea consumption may be associated with a lower risk of Parkinson's disease (PD). However, less is known about the independent and joint roles of these two habits, which are often clustered among Chinese, on PD risk.

objectiveTo prospectively examine the independent and joint association of tea consumption and smoking with the risk of PD.

methodsThe China Kadoorie Biobank (CKB) study recruited 512,725 participants aged 30 to 79 years from ten areas across China since 2004. Information on smoking and tea consumption was collected at baseline, and PD cases were ascertained by linkage to the national health insurance system and death registry. Cox proportional hazards models were used to estimate the multivariable-adjusted hazard ratios (HRs) and corresponding 95%confidence intervals (CIs).

resultsDuring a median of 10.8 years of follow-up, 922 PD cases were recorded. Compared with participants who never consumed tea, the HR (95%CI) for daily consumers was 0.68 (0.55, 0.84). Compared with participants who never or occasionally smoked, the HR (95%CI) for current smokers was 0.66 (0.53, 0.82). Those who had a clustering habit of smoking and tea consumption had a 38%(HR = 0.62; 95%CI: 0.49, 0.79) lower PD risk than those who consumed none. However, there were no statistically significant multiplicative or additive interaction for tea consumption and smoking on PD risk.

conclusionWe found that smoking and daily tea consumption were independently inversely associated with the risk of PD.

Indexed as

Parkinson DiseaseAdultChinaHumansProspective StudiesRisk FactorsSmokingTeaTeaChineseParkinson’s diseaseprospective studysmokingtea consumption

Identifiers

PMID35527564
PMCPMC9398092
OpenAlexW4225314474

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.