ArticleBMC public health2024
Implications for household health expenditure in China's ageing population: based on Red Herring hypothesis.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Article
- The role of dominant handgrip strength in fall occurrence possibility and frequency.BMC public health · 2026Article
- Improving patients' satisfaction through service digitalization: a cross-sectional study based on the theory of psychological empowerment.BMC health services research · 2025Article
- Impact of environmental regulation, energy technology innovation on population health.BMC public health · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rising healthcare costs due to population aging present a complex issue, with debate centering on whether these costs are driven by aging or end-of-life care. This study examines healthcare expenditures in Chinese households using data from the 2005 and 2018 Chinese Longitudinal Healthy Longevity Survey. By applying the Heckman select model and a two-part model, the research innovatively includes time to death, income, social security and health level in the benchmark regression in order to validate the recent some new Red Herring hypothesis. The findings show that time to death is the primary determinant of healthcare expenditures, while the effect of aging is minimal. Income, social security, and health status also significantly influence health expenditure, but they do not function as Red Herring variables.
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Registered trials
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.