Evidence map›Paper›PMID 35309188›Full record

ArticleFrontiers in public health2022

Influence of Public Health Services on the Goal of Ending Tuberculosis: Evidence From Panel Data in China.

Yang Chen, Qingyu Zhou, Xinmei Yang, Peiwu Shi, Qunhong Shen, Zhaoyang Zhang, Zheng Chen, Chuan Pu, Lingzhong Xu, Zhi Hu and 8 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

18 authors at 6 institutions in 1 country.

Yang ChenResearch Institute of Health Development Strategies, Fudan University, Shanghai, China.
Qingyu ZhouResearch Institute of Health Development Strategies, Fudan University, Shanghai, China.
Xinmei YangResearch Institute of Health Development Strategies, Fudan University, Shanghai, China.
Peiwu ShiCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Qunhong ShenCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Zhaoyang ZhangCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Zheng ChenCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Chuan PuCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Lingzhong XuCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Zhi HuCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Anning MaCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Zhaohui GongCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Tianqiang XuCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Panshi WangCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Hua WangCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Chao HaoCollaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China.
Chengyue LiResearch Institute of Health Development Strategies, Fudan University, Shanghai, China.
Mo HaoResearch Institute of Health Development Strategies, Fudan University, Shanghai, China.
Fudan University · CNAnhui Medical University · CNChongqing Public Health Medical Center · CNShandong University · CNWeifang Medical University · CNZhejiang Academy of Medical Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The World Health Organization has proposed an initiative to "end tuberculosis (TB)." Unfortunately, TB continues to endanger the health of people worldwide. We investigated the impact of public health services (PHS) in China on TB incidence. In this way, we provided policy ideas for preventing the TB epidemic. Methods: We used the "New Public Management Theory" to develop two indicators to quantify policy documents: multisector participation (MP) and the Assessable Public Health Service Coverage Rate (ASCR). The panel data from 31 provinces in Chinese mainland were collected from 2005 to 2019 based on 1,129 policy documents and the China Statistical Yearbook. A fixed-effect model was used to determine the impact of MP and the ASCR on TB incidence. Results: From 2005 to 2019, the average MP increased from 89.25 to 97.70%, and the average ASCR increased from 53.97 to 78.40% in Chinese mainland. However, the development of ASCR between regions was not balanced, and the average level in the western region was lower than that in the eastern coastal provinces. With an increase in MP and the ASCR, the TB incidence had been decreasing gradually in recent years. The panel analysis results showed that MP (β = -0.76, Conclusions: Promoting the participation of multiple departments, as well as emphasizing the quality of PHS delivery, are important ways to alleviate the TB epidemic. The settings of evaluation indices for PHS provision should be strengthened in the future.

Indexed as

GoalsTuberculosisChinaHealth ServicesHumansWorld Health OrganizationChinamultisector participationpublic health servicesservices assessmenttuberculosis incidence

Identifiers

PMID35309188
PMCPMC8931334
OpenAlexW4214952032

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.