Dataset Information

Trends, composition and distribution of nurse workforce in China: a secondary analysis of national data from 2003 to 2018

ABSTRACT:

Objectives

Given the increased ageing population and frequent epidemic challenges, it is vital to have the nurse workforce of sufficient quantity and quality. This study aimed to demonstrate the trends, composition and distribution of nurse workforce in China.

Design

Secondary analysis using national public datasets in China from 2003 to 2018.

Setting/participants

National population, nurse workforce and physician workforce.

Primary and secondary outcome measures

Frequency and proportion were used to demonstrate: (1) the longitudinal growth of nurse workforce; (2) the diversity of nurse workforce in gender, age, work experience and education level; and (3) the distribution of nurse workforce among provinces, rural–urban areas and hospital/community settings. The Gini coefficient and Theil L index were used to measure the inequality trends of nurse workforce.

Results

The total number of nurses increased from 1.3 million to 4.1 million and the density increased from 1 to 2.94 per 1000 population over 2003–2018. The nurses to physician ratio changed from 0.65:1 to 1.14:1. The majority of the nurse workforce was female, under 35 years old, with less than 30 years of work experience, with an associate’s degree and employed within hospitals. Central and eastern regions had more nurses and there were 5.08 nurses per 1000 population in urban areas while less than two in rural areas in 2018. The Gini coefficient and between-provincial Theil index experienced a consistent decline. Within-province inequality accounted for overall inequality has risen from 52.38% in 2010 to 71.43% in 2018 suggested that the differences of distribution are mainly reflected in urban and rural areas.

Conclusion

Chinese nurse workforce has been changed significantly in the past 15 years that may be associated with the reformations of policy, nursing education in China. Our study suggests current features in the nurse workforce and can be used to strengthen future health services.

SUBMITTER: Lu H

PROVIDER: S-EPMC8552175 | biostudies-literature |

REPOSITORIES: biostudies-literature

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