Evidence map›Paper›PMID 41843294›Full record

ArticleInternational journal of health economics and management2026

The impact of health literacy on healthcare spending: theory and evidence from China.

Yisong Wang, Xuezheng Qin

Abstract read
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Article in International journal of health economics and management, 2026. 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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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Yisong WangSchool of Economics, Peking University, No 5 Yiheyuan Road, Beijing, China.
Xuezheng QinSchool of Economics, Peking University, No 5 Yiheyuan Road, Beijing, China. xqin@pku.edu.cn.

Funding

National Natural Science Foundation of China 72074004
6 · The paper itself

Abstract

We develop a theoretical model where health literacy endogenously shapes healthcare spending decisions. The model predicts an inverted U-shaped relationship between literacy and spending, driven by two channels: the 'attention' effect, where increased health literacy enhances health awareness, and the 'productivity' effect, where health literacy improves health production efficiency. We empirically test these predictions based on an adult subsample of 2020 China Family Panel Studies, where individual-level health literacy is measured using a self-design questionnaire (the Chinese Health Literacy Survey) following internationally comparable and established instruments. To address the potential endogeneity, we apply Natural Language Processing on 2.16 million news articles to construct an instrumental variable for health literacy coverage.​ This instrument exploits province–month variation in news coverage of concepts related to understanding and navigating health information. Our quantitative analysis reveals that a 10% increase in health literacy correlates with a 5% reduction in healthcare expenditure. Through mechanism analysis, we provide evidence for the attention and the productivity effects, respectively. For robustness, we conduct alternative IV construction and use Double Machine Learning to control for observable and high-dimensional confounding. Our findings imply that improving health literacy can be an effective policy measure to curb the rising healthcare spending and promote efficient healthcare utilization around the globe.

Indexed as

Health ExpendituresHealth LiteracyChinaHumansModels, TheoreticalChinaHealthcare spendingHealth literacyHuman capitalNatural language processing

Identifiers

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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.