Evidence map›Paper›PMID 31640629›Full record

ArticleBMC public health2019

Age moderates the effect of socioeconomic status on physical activity level among south Korean adults: cross-sectional analysis of nationally representative sample.

Harold H Lee, Ashley E Pérez, Don Operario

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Exploring novel determinants of exercise behavior: a lagged exposure-wide approach.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2025
    Article
  4. Article
  5. Article
  6. Physical Activity in Malaysia: Are We Doing Enough? Findings from the REDISCOVER Study.International journal of environmental research and public health · 2022
    Article
  7. Article
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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.

Harold H LeeDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 401 Park Dr., 428F, Boston, MA, 02115, USA. hhlee@hsph.harvard.edu.ORCID http://orcid.org/0000-0001-5778-3227
Ashley E PérezDepartment of Social and Behavioral Sciences, University of California San Francisco School of Nursing, 3333 California St., Suite 455, San Francisco, CA, 94118, USA.
Don OperarioDepartment of Behavioral and Social Sciences, Brown University School of Public Health, Box G-S121-3, Providence, RI, 02912, USA.

Funding

Training Program for Scientists Conducting Research to Reduce HIV Health DisparitR25MH067127 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Emily A Arnold, Torsten Brian Neilands · 2003 to 2026
$5.4M
Minority Populations Prevention Researcher TrainingR25HD045810 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NEILANDS, TORSTEN BRIAN · 2003 to 2018
$4.3M
Genetic effects of BDNF on physical activity adherence: Affective response to physical activity as a phenotypic mediatorF31HL140817 · NHLBI · BROWN UNIVERSITY · PI LEE, HAROLD H. · 2018 to 2019
$45k
NHLBI NIH HHS 1F31HL140817NHLBI NIH HHS F31 HL140817NICHD NIH HHS R25 HD045810NIMH NIH HHS R25 MH067127
6 · The paper itself

Abstract

backgroundIn a nationally representative sample of South Korean adults, we investigated the association between socioeconomic status (SES) and physical activity level, and whether this association varied by age group.

methodsWe used data from 5065 subjects aged ≥19 years who participated in the 6th Korea National Health and Nutrition Examination Survey. Weighted logistic regression examined the SES-physical activity association. Using the International Physical Activity Questionnaire short form, physical activity level was categorized into two groups: meeting the guideline (≥150 min/week of moderate intensity physical activity) and not meeting the guideline. Annual household income quartile (first quartile = highest income) and education (elementary, middle school, high school, and college graduates) were used as SES indicators. Sociodemographic covariates included in the adjusted models were marital status, town type (rural/urban), dwelling type, perceived health, federal allowance support (yes/no), and working- and sleeping-hours.

resultsIn unadjusted models, low income and low education were both associated with significantly lower odds of meeting the physical activity guideline. The income-physical activity association was moderated by age group in both unadjusted and adjusted models. Specifically, among those age < 45 years, those in the third quartile group had 41% higher odds (p < 0.01) of meeting the physical activity guideline compared with the first quartile group, after adjusting for covariates. In contrast, among those age ≥ 45 years, those in the third quartile group had 16% lower odds (p < 0.01) of meeting the physical activity guideline compared with the first quartile group, after adjusting for covariates. Furthermore, the education-physical activity association was moderated by age but only in the adjusted model. Specifically, among those age < 45 years, high school graduates had a 21% higher odds of meeting the physical activity guideline compared with college graduates (p = 0.08). In contrast, among those age ≥ 45 years, high school graduates had a 23% lower odds of meeting the physical activity guideline compared with college graduates (p = 0.01).

conclusionFuture policies that aim to address SES-related health disparities in physical activity among adults in South Korea should consider the different patterns of physical activity in accordance with SES and age.

Indexed as

ExerciseSocial ClassAdultAge FactorsCross-Sectional StudiesFemaleHumansMaleMiddle AgedRepublic of KoreaHealth disparitiesNoncommunicable diseasePhysical activitySouth Korea

Identifiers

PMID31640629
PMCPMC6805456

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Registered trials

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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.