Evidence map›Paper›PMID 33069235›Full record

ArticleBMC public health2020

Public awareness and knowledge of factors associated with dementia in China.

Yong-Bo Zheng, Le Shi, Yi-Miao Gong, Xiao-Xiao Wang, Qing-Dong Lu, Jian-Yu Que, Muhammad Zahid Khan, Yan-Ping Bao, Lin Lu

Abstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
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  4. Gaps in dementia knowledge: a nationwide study of public awareness and misconceptions in Bulgaria.Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society · 2025
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  9. Review
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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

9 authors.

Yong-Bo ZhengPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Le ShiPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Yi-Miao GongPeking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
Xiao-Xiao WangResearch Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China.
Qing-Dong LuNational Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
Jian-Yu QuePeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Muhammad Zahid KhanNational Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
Yan-Ping BaoNational Institute on Drug Dependence and Beijing Key Laboratory of Drug Dependence, Peking University, Beijing, China.
Lin LuPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China. linlu@bjmu.edu.cn.

Funding

Beijing Natural Science Foundation 7194336Natural Science Foundation of China 31900805
6 · The paper itself

Abstract

backgroundDementia is a global public health priority. Many modifiable factors have been shown to influence the development of dementia, but these factors are not adequately known by the general public. This study aimed to assess public awareness of the factors that are associated with dementia in China.

methodsA cross-sectional study was conducted from May to October 2019 using an Internet-based questionnaire. Data on basic sociodemographic characteristics were collected, and the knowledge of risk and protective factors for dementia was investigated. Logistic regression analysis was performed to compare levels of the knowledge of factors associated with dementia across populations with different demographic characteristics.

resultsData from 3338 respondents were analyzed. The percentages of participants who accurately identified the risk factors of dementia were follows: 84.24% for negative affect, 65.07% for alcohol use, 56.68% for smoking, 48.74% for hypertension, and 42.66% for diabetes. The percentages of participants who accurately identified the protective factors for dementia were follows: 90.00% for exercise, 84.69% for social activity, 80.92% for intelligence games, 74.45% for reading, and 6.14% for antihypertensive or hypolipidemic drugs. The majority of Chinese people correctly recognized the role of lifestyle factors in the development of dementia but not medical factors. The levels of knowledge of the factors associated with dementia were significantly distinct across populations with different characteristics. The following sociodemographic characteristics were associated with more comprehensive knowledge of dementia risk and protective factors: women, young age, high education levels, nonmanual jobs, and contact with patients with dementia.

conclusionsPublic awareness and knowledge of risk and protective factors for dementia in China are still insufficient. More efforts are needed to publicize information to reduce the risk of dementia.

Indexed as

DementiaAwarenessChinaCross-Sectional StudiesFemaleHealth Knowledge, Attitudes, PracticeHumansRisk FactorsChinaDementiaFactorsPublic awarenessUnderstanding

Identifiers

PMID33069235
PMCPMC7568826

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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.