Evidence map›Paper›PMID 31752854›Full record

ArticleInternational journal for equity in health2019

Measuring inequalities in the public health workforce at county-level Centers for Disease Control and Prevention in China.

Weiqin Cai, Chengyue Li, Mei Sun, Mo Hao

Abstract read
In one paragraph

Article in International journal for equity in health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Weiqin CaiResearch Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China.
Chengyue LiResearch Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China.
Mei SunResearch Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China.
Mo HaoResearch Institute of Health Development Strategies & Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, 177 box, 130 Dong'an Road, Shanghai, 200032, China. haomo03@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe public health workforce (PHW) is a key component of a country's public health system. Since the outbreak of SARS (severe acute respiratory syndrome) in 2003, the scale of PHW in China has been continuously expanding, but policymakers and researchers still focus on the distribution of public health personnel, especially the regional inequality in such distribution. We aimed to identify the root cause of PHW inequality by decomposing different geographical units in China.

methodsThis study was based on data from a nationwide survey, which included 2712 county-level data. The distribution of the PHW in geographical units was evaluated by the Gini coefficient and Theil T index, and inequalities at regional, provincial, and municipal levels were decomposed to identify the root causes of inequalities in the PHW. Additionally, the contextual factors affecting the distribution of the PHW were determined through regression analysis.

resultsThe overall inequality results show that health professional and field epidemiological investigators faced worse inequality than the staff. In particular, field epidemiological investigators had a Gini coefficient close to 0.4. Step decomposition showed that within-region inequalities accounted for 98.5% or more of overall inter-county inequality in the distribution of all PHW categories; provincial decomposition showed that at least 74% of inequality is still distributed within provinces; the overall contribution of within-municipal inequality and between-municipal inequality was basically the same. Further, the contextual factor that influenced between-municipality and within-municipality inequality for all three categories of PHWs was the agency building area per employee. Per capita GDP had a similar effect, except for between-municipality inequality of professionals and within-municipality inequality of field epidemiological investigators.

conclusionsThe successive decomposition showed that inequality is mainly concentrated in counties at the within-province and within-municipal levels. This study clearly suggests that the government, especially the municipal government at the provincial level, should increase financial investment in Centers for Disease Control and Prevention (CDCs) with worse resource allocation in their jurisdiction through various ways of compensation and incentives, enhance their infrastructure, and improve the salary of personnel in these institutions, to attract more public health professionals to these institutions.

Indexed as

Health WorkforcePublic HealthChinaCross-Sectional StudiesGovernment AgenciesHumansLocal GovernmentSocioeconomic FactorsCDCCounty-levelInequalities decompositionPublic health workforce

Identifiers

PMID31752854
PMCPMC6873429

What OpenQuestion holds

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LicenceCC BY
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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.