Evidence map›Paper›PMID 39093840›Full record

ArticlePloS one2024

Adult-onset asthma morbidity and related economic costs in middle age due to intentional chronic absenteeism in high school: An epidemiologic study using the national longitudinal survey of youth 1979 data.

Zongqiang Liao, Neville Francis, Kevin Brooks

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
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

3 authors.

Zongqiang LiaoInstitute for Health Policy, Michigan State University, East Lansing, Michigan, United States of America.ORCID 0009-0009-0399-8703
Neville FrancisDepartment of Economics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
Kevin BrooksInstitute for Health Policy, Michigan State University, East Lansing, Michigan, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMany authors examined the individual and societal impact of school absenteeism. Nevertheless, no empirical study has looked at the potential direct correlation between deliberate school absences and chronic illnesses in mid-adulthood. Our goal is to investigate any potential direct links between purposeful school absences and adult-onset asthma in middle age, as well as measure any associated costs of asthma.

methodsData were sourced from the National Longitudinal Survey of Youth 1979, a nationally representative survey. The outcome measure was self-reported asthma in mid-adulthood. School records of absenteeism from grades nine through twelve were the key explanatory variables. Logistic regressions were performed with controls for demographic, economic and health variables. Predicted probabilities from the regressions were used to quantify costs of adult-onset asthma in middle age due to intentional high school absenteeism.

resultsMore years of chronic absenteeism in high school were associated with higher risk of adult-onset asthma in middle age. Four years of chronic absenteeism in high school during the late 1970s through the early 1980s could potentially have incurred between $817 million to $1 billion of asthma related costs in 2002, when these students were in their mid-adulthood. These potential asthma related costs due to high school absenteeism are sizeable considering that this high school cohort only accounted for six percent of the U.S. population.

conclusionsReducing high school absenteeism could lower the incidence of adult-onset asthma in middle age, and its associated future economic burden.

Indexed as

AbsenteeismAsthmaAdolescentAdultAge of OnsetCost of IllnessFemaleHumansLongitudinal StudiesMaleMiddle AgedSchoolsUnited States

Identifiers

PMID39093840
PMCPMC11296655

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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.