Keumji Jung

Dr. Keumji Jung

orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2016 in The Lancet
Verified
Journal Article
Open access
EAEmanuele Di Angelantonio
Emanuele Di Angelantonio
SBShilpa N Bhupathiraju
Shilpa N Bhupathiraju
DWDavid Wormser
David Wormser
PGPei Gao
Pei Gao
SKStephen Kaptoge
Stephen Kaptoge
FHFrank B Hu
Frank B Hu
Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up. Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4-14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5-<25·0 kg/m(2). All-cause mortality was minimal at 20·0-25·0 kg/m(2) (HR 1·00, 95% CI 0·98-1·02 for BMI 20·0-<22·5 kg/m(2); 1·00, 0·99-1·01 for BMI 22·5-<25·0 kg/m(2)), and increased significantly both just below this range (1·13, 1·09-1·17 for BMI 18·5-<20·0 kg/m(2); 1·51, 1·43-1·59 for BMI 15·0-<18·5) and throughout the overweight range (1·07, 1·07-1·08 for BMI 25·0-<27·5 kg/m(2); 1·20, 1·18-1·22 for BMI 27·5-<30·0 kg/m(2)). The HR for obesity grade 1 (BMI 30·0-<35·0 kg/m(2)) was 1·45, 95% CI 1·41-1·48; the HR for obesity grade 2 (35·0-<40·0 kg/m(2)) was 1·94, 1·87-2·01; and the HR for obesity grade 3 (40·0-<60·0 kg/m(2)) was 2·76, 2·60-2·92. For BMI over 25·0 kg/m(2), mortality increased approximately log-linearly with BMI; the HR per 5 kg/m(2) units higher BMI was 1·39 (1·34-1·43) in Europe, 1·29 (1·26-1·32) in North America, 1·39 (1·34-1·44) in east Asia, and 1·31 (1·27-1·35) in Australia and New Zealand. This HR per 5 kg/m(2) units higher BMI (for BMI over 25 kg/m(2)) was greater in younger than older people (1·52, 95% CI 1·47-1·56, for BMI measured at 35-49 years vs 1·21, 1·17-1·25, for BMI measured at 70-89 years; pheterogeneity<0·0001), greater in men than women (1·51, 1·46-1·56, vs 1·30, 1·26-1·33; pheterogeneity<0·0001), but similar in studies with self-reported and measured BMI. The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations. UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.

10 April 2014 in BMC Medicine
Verified
Journal Article
Open access
PDF file
WNWei Nie
Wei Nie
YZYi Zhang
Yi Zhang
SJSun Ha Jee
Sun Ha Jee
KJKeumji Jung
Keumji Jung
BLBing Li
Bing Li
QXQingyu Xiu
Qingyu Xiu
It is unclear whether an ‘obesity survival paradox’ exists for pneumonia. Therefore, we conducted a meta-analysis to assess the associations between increased body mass index (BMI), pneumonia risk, and mortality risk.

21 May 2014 in BMJ Open
Verified
Journal Article
Open access
PDF file
SJSun Ha Jee
Sun Ha Jee
YJYangsoo Jang
Yangsoo Jang
DODong Joo Oh
Dong Joo Oh
BOByung-Hee Oh
Byung-Hee Oh
SLSang Hoon Lee
Sang Hoon Lee
MWMark Woodward
Mark Woodward
Objective The objectives of this study were to develop a coronary heart disease (CHD) risk model among the Korean Heart Study (KHS) population and compare it with the Framingham CHD risk score. Design A prospective cohort study within a national insurance system. Setting 18 health promotion centres nationwide between 1996 and 2001 in Korea. Participants 268 315 Koreans between the ages of 30 and 74 years without CHD at baseline. Outcome measure Non-fatal or fatal CHD events between 1997 and 2011. During an 11.6-year median follow-up, 2596 CHD events (1903 non-fatal and 693 fatal) occurred in the cohort. The optimal CHD model was created by adding high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol and triglycerides to the basic CHD model, evaluating using the area under the receiver operating characteristic curve (ROC) and continuous net reclassification index (NRI). Results The optimal CHD models for men and women included HDL-cholesterol (NRI=0.284) and triglycerides (NRI=0.207) from the basic CHD model, respectively. The discrimination using the CHD model in the Korean cohort was high: the areas under ROC were 0.764 (95% CI 0.752 to 0.774) for men and 0.815 (95% CI 0.795 to 0.835) for women. The Framingham risk function predicted 3–6 times as many CHD events than observed. Recalibration of the Framingham function using the mean values of risk factors and mean CHD incidence rates of the KHS cohort substantially improved the performance of the Framingham functions in the KHS cohort. Conclusions The present study provides the first evidence that the Framingham risk function overestimates the risk of CHD in the Korean population where CHD incidence is low. The Korean CHD risk model is well-calculated alternations which can be used to predict an individual's risk of CHD and provides a useful guide to identify the groups at high risk for CHD among Koreans.

1 April 2019 in Gastroenterology
Verified
Journal Article
Closed access
YLYingchang Lu
Yingchang Lu
SKSun-Seog Kweon
Sun-Seog Kweon
CTChizu Tanikawa
Chizu Tanikawa
WJWei-Hua Jia
Wei-Hua Jia
YXYong-Bing Xiang
Yong-Bing Xiang
WZWei Zheng
Wei Zheng

21 February 2017 in Human Molecular Genetics
Verified
Journal Article
Open access
PDF file
CSCassandra N. Spracklen
Cassandra N. Spracklen
PCPeng Chen
Peng Chen
YKYoung Jin Kim
Young Jin Kim
XWXu Wang
Xu Wang
Hui CaiHui Cai
Hui Cai
XSXueling Sim
Xueling Sim
Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10−8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10−9), NCOA2 (P = 1.6 × 10−8), and NID2-PTGDR (P = 4.2 × 10−8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10−10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10−5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets.

1 September 2015 in Atherosclerosis
Verified
Journal Article
Closed access
KJKeumji Jung
Keumji Jung
YJYangsoo Jang
Yangsoo Jang
DODong Joo Oh
Dong Joo Oh
BOByung-Hee Oh
Byung-Hee Oh
SLSang Hoon Lee
Sang Hoon Lee
SJSun Ha Jee
Sun Ha Jee