Evidence map›Paper›PMID 24259387›Full record

ArticleBMJ open2013

A cross-sectional study of factors associated with uptake of vaccination against influenza among older residents in the postpandemic season in Beijing, China.

Yang Zheng, Peng Yang, Shuangsheng Wu, Chunna Ma, Holly Seale, C Raina Macintyre, Quanyi Wang

Abstract read
In one paragraph

Article in BMJ open, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Monitoring influenza vaccination coverage among older adults: a rural cohort study, Rio Grande, 2017-2022.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 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

7 authors.

Yang ZhengInstitute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control (CDC), Beijing, China.
Peng Yang
Shuangsheng Wu
Chunna Ma
Holly Seale
C Raina Macintyre
Quanyi Wang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAnnually, influenza epidemics are associated with high mortality rates, notably among elderly persons. The aim of the study was to examine the level of influenza vaccine coverage among Chinese residents aged 60 years and older and to examine the demographic, behavioural and lifestyle health factors associated with vaccine receipt.

designCross-sectional study.

settingBeijing, China.

participantsStratified sampling was used to recruit participants for this study. A total of 2578 people aged 60 years and older consented to participate in this study. Questionnaires from 2481 participants were valid and were included in the final analysis. OUTCOME MEASURES: Influenza vaccination status and factors associated with vaccination.

methodsIn late 2010, a survey was conducted with residents from three urban and three rural districts in Beijing, China. Multivariate logistic regression was performed to detect the factors associated with influenza vaccination.

results2481 older people (aged ≥60 years) were included in the final analysis. In 2010, 44% had received the annual influenza vaccine. Lower education level, poor health status of the participant, regular taking exercises and considering that vaccine is the best measure for preventing influenza were associated with influenza vaccination coverage.

conclusionsInfluenza vaccine coverage in Beijing still remains suboptimal. Further work needs to be undertaken to ascertain whether the methods used to distribute the vaccine are adequate and whether health professionals are appropriately promoting the vaccine.

Identifiers

PMID24259387
PMCPMC3840337

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Registered trials

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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.