Evidence map›Paper›PMID 39639892›Full record

ArticleFrontiers in public health2024

Configurational analysis of ovarian cancer incidence in 30 provinces of China and its policy implications: a fuzzy-set qualitative comparative analysis approach.

Ying Shen, Zhenyu Huang, Chan Li

Abstract readComparative Study
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ying ShenDepartment of Obstetrics and Gynecology, Heilongjiang University of Chinese Medicine, Harbin, China.
Zhenyu HuangSchool of Humanities and Social Sciences, Harbin Engineering University, Harbin, China.
Chan LiDepartment of Obstetrics and Gynecology, Heilongjiang University of Chinese Medicine, Harbin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Ovarian cancer is one of the three most common gynecological cancers, with the highest mortality rate among gynecological malignancies. Previous studies on the environmental and socioeconomic (ESE) factors that affect ovarian cancer incidence (OCI) have generally only considered the net effects of single variables, while the synergistic effects among multiple factors have yet to be explored. Methods: Based on a sample of 30 provinces in Mainland China, an ESE configuration model was constructed in this study, using a fuzzy-set qualitative comparative analysis approach to empirically explore the configuration effects of multiple ESE factors on OCI. Results: (1) Education, marriage, income, insurance, urbanization, and environment alone do not constitute the necessary conditions for high or low OCI, indicating a need to comprehensively consider the configuration effects of these six conditions. (2) There are two configurations for high OCI: "configuration of environmental pollution under low socioeconomic development" and "configuration of insurance deficiency under high socioeconomic development." (3) There are two configurations for low OCI: "configuration of insurance adequacy under low socioeconomic development" and "configuration of insurance adequacy under low urbanization." Conclusion: The main contribution of this study is its focus on the configuration mechanism of ESE factors, enhancing understanding of the synergistic effects among the multiple factors that affect OCI. The study also provides valuable policy implications for decision-makers to formulate comprehensive health policies for the prevention and treatment of ovarian cancer.

Indexed as

Fuzzy LogicOvarian NeoplasmsSocioeconomic FactorsChinaFemaleHealth PolicyHumansIncidenceQualitative Researchconfiguration effectenvironmental-socioeconomic factorsESE modelFuzzySet qualitative comparative analysisovarian cancer incidence

Identifiers

PMID39639892
PMCPMC11617518

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