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

Abstract

Background: The 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.

Methods: This 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.

Results: The 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.

Conclusions: The 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.

Keywords: CDC; County-level; Inequalities decomposition; Public health workforce.

Fig. 1

Box plots of the density of three types of workforce per 10,000 population by county share in province. Note: X axis = 31 provinces. Y axis = density of workforce per 10,000 population. Panel A = description for staff. Panel B = description for health professionals. Panel C = description for field epidemiological investigators. Because of the confidentiality of the data, we have hidden the names of the provinces and used the region code to represent them: E for the eastern provinces, C for the central provinces, and W for the western provinces. According to the range between maximum county density and minimum county density in each province, the provinces are sorted from large to small

Fig. 2

Distribution of the contribution of “within-municipality” inequalities in all 31 provinces by inner-county share. Different colors represent different contributions. Note: Panel A = contribution for staff. Panel B = contribution for health professionals. Panel C = contribution for field epidemiological investigators