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Record W4412076865 · doi:10.3386/w33994

Health Spillovers: The Broad Impact of Spousal Health Shocks

2025· report· en· W4412076865 on OpenAlexfundno aff
Carolina Arteaga, Natalia Vigezzi, Pilar García-Gómez

Bibliographic record

VenueNational Bureau of Economic Research · 2025
Typereport
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Toronto
KeywordsHealth impact assessmentEconomicsEnvironmental scienceMedicinePublic health

Abstract

fetched live from OpenAlex

In this paper we provide new evidence on the health spillover effects of health shocks within couples.Using administrative data from the Netherlands and a matching event-study framework, we estimate the causal effect of experiencing a health shock within a couple on the health of the initially unaffected partner.Our findings reveal a significant deterioration in the partner's health outlook, characterized by substantial increases in hospital visits, overnight stays, and mortality.The health decline is broad in scope, encompassing higher risk of infections, accidents, and digestive and cardiovascular conditions.This deterioration is accompanied by substantial increases in stress, anxiety and depression for both men and women, as well as sleep disorders for women.These effects are not driven by a heavy caregiving load, financial distress or worsening of health behaviors.On the contrary, the adverse outcomes persist despite suggestive positive changes, including increased exercise for both men and women, and reduced alcohol consumption among women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.517
GPT teacher head0.699
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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