Evidence map›Paper›PMID 24349655›Full record

ArticleJournal of preventive medicine and public health = Yebang Uihakhoe chi2013

Social network characteristics and body mass index in an elderly Korean population.

Won Joon Lee, Yoosik Youm, Yumie Rhee, Yeong-Ran Park, Sang Hui Chu, Hyeon Chang Kim

Abstract read
In one paragraph

Article in Journal of preventive medicine and public health = Yebang Uihakhoe chi, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Social Network Analysis and Resilience in University Students: An Approach from Cohesiveness.International journal of environmental research and public health · 2018
    Article
  7. Article
  8. Article
  9. Article
  10. 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

6 authors.

Won Joon LeeDepartment of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea.
Yoosik YoumDepartment of Sociology, Yonsei University College of Social Sciences, Seoul, Korea.
Yumie RheeDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea.
Yeong-Ran ParkDivision of Silver Industry, Kangnam University, Yongin, Korea.
Sang Hui ChuDepartment of Clinical Nursing Science, Yonsei University College of Nursing, Seoul, Korea.
Hyeon Chang KimDepartment of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesResearch has shown that obesity appears to spread through social ties. However, the association between other characteristics of social networks and obesity is unclear. This study aimed to identify the association between social network characteristics and body mass index (BMI, kg/m(2)) in an elderly Korean population.

methodsThis cross-sectional study analyzed data from 657 Koreans (273 men, 384 women) aged 60 years or older who participated in the Korean Social Life, Health, and Aging Project. Network size is a count of the number of friends. Density of communication network is the number of connections in the social network reported as a fraction of the total links possible in the personal (ego-centric) network. Average frequency of communication (or meeting) measures how often network members communicate (or meet) each other. The association of each social network measure with BMI was investigated by multiple linear regression analysis.

resultsAfter adjusting for potential confounders, the men with lower density (<0.71) and higher network size (4-6) had the higher BMI (β=1.089, p=0.037) compared to the men with higher density (>0.83) and lower size (1-2), but not in the women (p=0.393). The lowest tertile of communication frequency was associated with higher BMI in the women (β=0.885, p=0.049), but not in the men (p=0.140).

conclusionsOur study suggests that social network structure (network size and density) and activation (communication frequency and meeting frequency) are associated with obesity among the elderly. There may also be gender differences in this association.

Indexed as

Body Mass IndexSocial NetworkingAgedAged, 80 and overComorbidityDepressionFemaleHumansMaleMiddle AgedRegression AnalysisRepublic of KoreaSelf ConceptSmokingAgedBody mass indexSocial support

Identifiers

PMID24349655
PMCPMC3859855

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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.