Latent profiles of health insurance literacy, numeracy and supplementary voluntary health insurance enrollment

BACKGROUND: Low enrollment threatens the sustainability of China's voluntary health insurance system. Limited health insurance literacy and numeracy may create a cognitive barrier to informed decision-making regarding enrollment. This study aims to identify latent profiles of health insurance literacy and numeracy, and to evaluate their associations with Supplementary Voluntary Health Insurance (SVHI) enrollment. METHODS: A cross-sectional survey utilizing face-to-face computer-assisted personal interviews was conducted between July and August 2024 across three Chinese provinces (Shandong, Henan, and Sichuan). Using multistage stratified sampling, 1,326 valid responses were collected from residents aged 18 years or older (out of 1,359 approached). Health insurance literacy was assessed using a validated scale comprising self-rated abilities and an objective knowledge quiz, while numeracy was measured via an adapted 3-item General Numeracy Scale. Latent profile analysis identified unobserved cognitive subgroups. Multivariable logistic regression with robust standard errors evaluated the associations between latent profiles and SVHI enrollment, adjusting for relevant covariates. RESULTS: A total of 1,326 participants were included in the analysis, of whom 369 (27.8%) were male and 610 (46.0%) were aged between 18 and 44 years. Of the participants, 195 (14.7%) had an education level of elementary school or lower. Three distinct cognitive profiles were identified: Profile 1 ("High health insurance literacy, High numeracy", 32.9%), Profile 2 ("High health insurance literacy, Low numeracy", 52.0%), and Profile 3 ("Low health insurance literacy, Low numeracy", 15.1%). In multivariable logistic regression, participants in profile 1 (OR = 2.14; 95% CI, 1.23-3.70) and profile 2 (OR = 2.40; 95% CI, 1.43-4.02) were significantly more likely to enroll in SVHI than those in Profile 3. CONCLUSIONS: This study found that distinct cognitive profiles of health insurance literacy and numeracy were associated with SVHI enrollment. Individuals with low health insurance literacy and low numeracy were significantly less likely to enroll in SVHI than those with higher levels of both. These findings may inform targeted communication and support strategies to improve equitable access to SVHI among populations with lower health insurance literacy and numeracy.

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Publication Details

Journal
Health Economics Review
Published
2026-07-02
DOI
https://doi.org/10.1186/s13561-026-00814-z
Primary Topic
Healthcare Policy and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Latent profiles of health insurance literacy, numeracy and supplementary voluntary health insurance enrollment

Lei Liu, Chaofan Li, Lizheng Xu, Tong Liu
Health Economics Review
Healthcare Policy and Management
article

Latent profiles of health insurance literacy, numeracy and supplementary voluntary health insurance enrollment

Lei Liu, Chaofan Li, Lizheng Xu, Tong Liu
article en

Abstract

BACKGROUND: Low enrollment threatens the sustainability of China's voluntary health insurance system. Limited health insurance literacy and numeracy may create a cognitive barrier to informed decision-making regarding enrollment. This study aims to identify latent profiles of health insurance literacy and numeracy, and to evaluate their associations with Supplementary Voluntary Health Insurance (SVHI) enrollment. METHODS: A cross-sectional survey utilizing face-to-face computer-assisted personal interviews was conducted between July and August 2024 across three Chinese provinces (Shandong, Henan, and Sichuan). Using multistage stratified sampling, 1,326 valid responses were collected from residents aged 18 years or older (out of 1,359 approached). Health insurance literacy was assessed using a validated scale comprising self-rated abilities and an objective knowledge quiz, while numeracy was measured via an adapted 3-item General Numeracy Scale. Latent profile analysis identified unobserved cognitive subgroups. Multivariable logistic regression with robust standard errors evaluated the associations between latent profiles and SVHI enrollment, adjusting for relevant covariates. RESULTS: A total of 1,326 participants were included in the analysis, of whom 369 (27.8%) were male and 610 (46.0%) were aged between 18 and 44 years. Of the participants, 195 (14.7%) had an education level of elementary school or lower. Three distinct cognitive profiles were identified: Profile 1 ("High health insurance literacy, High numeracy", 32.9%), Profile 2 ("High health insurance literacy, Low numeracy", 52.0%), and Profile 3 ("Low health insurance literacy, Low numeracy", 15.1%). In multivariable logistic regression, participants in profile 1 (OR = 2.14; 95% CI, 1.23-3.70) and profile 2 (OR = 2.40; 95% CI, 1.43-4.02) were significantly more likely to enroll in SVHI than those in Profile 3. CONCLUSIONS: This study found that distinct cognitive profiles of health insurance literacy and numeracy were associated with SVHI enrollment. Individuals with low health insurance literacy and low numeracy were significantly less likely to enroll in SVHI than those with higher levels of both. These findings may inform targeted communication and support strategies to improve equitable access to SVHI among populations with lower health insurance literacy and numeracy.

Health Economics Review
Shandong University (CN), Shandong Management University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province
Quality Education
Openalex Percentile: Top 4%
Healthcare Policy and Management
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