Evidence map›Paper›PMID 41803874›Full record

ArticleBMC public health2026

Can presenteeism predict future absenteeism? Evidence from the Korean Health Panel Study.

Yoonjung Ji, Wonhee Baek, Ari Min

Abstract read
In one paragraph

Article in BMC public health, 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yoonjung JiCollege of Nursing, Research Institute of AI and Nursing Science, Gachon University, Incheon, South Korea.
Wonhee BaekCollege of Nursing, Gyeongsang National University, Jinju, South Korea.
Ari MinDepartment of Nursing, Chung-Ang University, Seoul, South Korea. amin@cau.ac.kr.

Funding

National Research Foundation of Korea RS-2025-00521630
6 · The paper itself

Abstract

backgroundPresenteeism, the act of working while ill, is increasingly recognized as a key occupational health challenge with significant consequences for productivity and future work incapacity. Yet, longitudinal evidence on its temporal interplay with absenteeism remains scarce. We aimed to examine the lagged and bidirectional relationships between presenteeism and absenteeism using nationally representative multi-wave panel data from Korean wage workers.

methodsWe analyzed four waves (2019–2022) of longitudinal survey data from 4,180 baseline participants, with follow-up rates of 76.8% (wave 2), 66.6% (wave 3), and 58.4% (wave 4). Mixed-effects logistic regression models estimated the effect of prior-wave presenteeism on subsequent absenteeism, adjusting for covariates measured at the preceding wave. Bidirectional cross-lagged panel models were used to assess reciprocal relationships over time.

resultsPresenteeism prevalence ranged 12.7–25.0%, exceeding absenteeism prevalence (8.6–12.3%) across all waves. In mixed-effects models, prior-wave presenteeism predicted 30% higher odds of absenteeism at the next wave (odds ratio = 1.30, 95% confidence interval: 1.08–1.56, p = .005). The bidirectional model showed significant cross-lagged effects from presenteeism to absenteeism in two of three intervals, but absenteeism did not predict future presenteeism. Strong autoregressive effects were observed for presenteeism and absenteeism.

conclusionsPresenteeism is consistently associated with subsequent absenteeism among Korean workers and may serve as a useful risk marker for future absence; however, results should be interpreted as longitudinal associations as within-person effects were attenuated in a random-intercept sensitivity analysis. These findings highlight the potential importance of coordinated policy and organizational approaches—such as statutory paid sick leave, supportive sick leave cultures, and proactive health monitoring—in addressing problematic presenteeism.

Indexed as

AbsenteeismPresenteeismAdultFemaleForecastingHumansLongitudinal StudiesMaleMiddle AgedRepublic of KoreaAbsenceKorean workersLongitudinal studyOccupational healthWork while sick

Identifiers

PMID41803874
PMCPMC13085347

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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.