Evidence map›Paper›PMID 29215812›Full record

ArticleJournal of Korean medical science2018

Prevalence of Overweight and Income Gaps in 245 Districts of Korea: Comparison Using the National Health Screening Database and the Community Health Survey, 2009-2014.

Ikhan Kim, Jinwook Bahk, Yeon Yong Kim, Jeehye Lee, Hee Yeon Kang, Juyeon Lee, Sung Cheol Yun, Jong Heon Park, Soon Ae Shin, Young Ho Khang

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

10 authors.

Ikhan KimDepartment of Health Policy and Management, Seoul National University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-6428-4159
Jinwook BahkInstitute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, Korea.ORCID https://orcid.org/0000-0002-7715-9955
Yeon Yong KimBig Data Steering Department, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0003-2179-8931
Jeehye LeeDepartment of Health Policy and Management, Seoul National University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-9522-1919
Hee Yeon KangInstitute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, Korea.ORCID https://orcid.org/0000-0001-8530-8087
Juyeon LeeThe People's Health Institute, Seoul, Korea.ORCID https://orcid.org/0000-0001-6235-6043
Sung Cheol YunDepartment of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea.ORCID https://orcid.org/0000-0001-8503-109X
Jong Heon ParkBig Data Steering Department, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0002-4749-5878
Soon Ae ShinBig Data Steering Department, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0001-8858-0801
Young Ho KhangDepartment of Health Policy and Management, Seoul National University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-9585-8266

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe compared age-standardized overweight prevalence and their income gaps at the level of district in Korea using the National Health Screening Database (NHSD) and the Community Health Survey (CHS).

methodsWe analyzed 39,093,653 subjects in the NHSD and 926,580 individuals in the CHS between 2009 and 2014. For the comparison of body mass index (BMI) distributions, data from 26,100 subjects in the Korea National Health and Nutrition Examination Survey (KNHANES) were also analyzed. We calculated the age-standardized overweight prevalence and its interquintile income gap at the district level. We examined the magnitudes of the between-period correlation for age-standardized overweight prevalence. The differences in overweight prevalence and its income gap between the NHSD and the CHS were also investigated.

resultsThe age-adjusted mean BMI from the CHS was lower than those from the NHSD and the KNHANES. The magnitudes of the between-period correlation for overweight prevalence were greater in the NHSD compared to the CHS. We found that the district-level overweight prevalence in the NHSD were higher in all districts of Korea than in the CHS. The correlation coefficients for income gaps in overweight prevalence between the two databases were relatively low. In addition, when using the NHSD, the district-level income inequalities in overweight were clearer especially among women than the inequalities using the CHS.

conclusionThe relatively large sample size for each district and measured anthropometric data in the NHSD are more likely to contribute to valid and reliable measurement of overweight inequality at the district level in Korea.

Indexed as

Health SurveysNutrition SurveysAdultBody HeightBody Mass IndexBody WeightDatabases, FactualFemaleHumansIncomeMaleMiddle AgedOverweightPrevalenceRepublic of KoreaSurveys and QuestionnairesHealth SurveysIncomeOverweightRepublic of KoreaSample SizeSocioeconomic Factors

Identifiers

PMID29215812
PMCPMC5729638

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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.