<p>Estimates after adding city covariates.</p>

Huan He's dataset on figshare contains estimates from a study linking air pollution to catastrophic health expenditure in China. The analysis uses four waves of the China Health and Retirement Longitudinal Study matched with PM2.5 and meteorological data, involving 24,004 participants aged 45 and above. The dataset was last updated on 2026-04-21.

Use Cases

• Modeling the relationship between PM2.5 exposure and catastrophic health expenditure based on longitudinal survey data.
• Analyzing subgroup heterogeneity in health expenditure risk based on urban/rural location, age, education, and chronic conditions.
• Evaluating the mitigating effect of social health insurance types on pollution-related health costs.
• Investigating the mechanisms linking air pollution to financial burden through direct disease costs and labor supply.

Strengths

• Dataset is based on a large longitudinal survey with 24,004 participants.
• Data integrates health survey responses with external PM2.5 and meteorological data.
• Analysis employs statistical methods like random effects logit and instrumental variable estimation.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 5.5 KB, indicating it likely contains summary estimates rather than raw survey data.

Provenance

Source

China Health and Retirement Longitudinal Study (CHARLS) data matched with PM2.5 and meteorological data.

Collection Method

Analysis using a random effects logit model and instrumental variable estimation.

Time Range

Covers four waves of the CHARLS survey; specific years are not provided.

Freshness

Last updated 2026-04-21 17:48:43; freshness should be verified.

Geography

China, focusing on middle-aged and older adults.