Evidence map›Paper›PMID 33006619›Full record

Observational studyJAMA network open2020

Observational and Genetic Associations of Body Mass Index and Hepatobiliary Diseases in a Relatively Lean Chinese Population.

Yuanjie Pang, Christiana Kartsonaki, Jun Lv, Iona Y Millwood, Canqing Yu, Yu Guo, Yiping Chen, Zheng Bian, Ling Yang, Junshi Chen and 7 more

Open access · goldAbstract readComparative StudyObservational Study
In one paragraph

Observational study in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
1.6field-weighted citation impact, top 15% of its field
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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Determinants of abnormal liver-related biomarkers in adult COVID-19 patients.Frontiers in cellular and infection microbiology · 2025
    Article
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  12. Obesity and Gallstones.Visceral medicine · 2021
    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

17 authors at 6 institutions in 2 countries.

Yuanjie PangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Christiana KartsonakiClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Iona Y MillwoodClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yu GuoChinese Academy of Medical Sciences, Beijing, China.
Yiping ChenClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Zheng BianChinese Academy of Medical Sciences, Beijing, China.
Ling YangClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, China.
Robert ClarkeClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Robin WaltersClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Shukuan WuHaikou Meilan Disease Prevention and Control Center, Haikou, China.
Huimei LiHaikou Meilan Disease Prevention and Control Center, Haikou, China.
Michael V HolmesClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Zhengming ChenClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute University of Oxford, Oxford, United Kingdom.
Medical Research Council · GBPeking University · CNUniversity of Oxford · GBChinese Academy of Medical Sciences & Peking Union Medical College · CNHainan Center for Disease Control & Prevention · CNChina National Center for Food Safety Risk Assessment · CN

Funding

British Heart Foundation FS/18/23/33512Cancer Research UK 29186Medical Research Council MC_PC_13049Medical Research Council MC_PC_14135Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2Wellcome Trust 088158Wellcome Trust 088158/Z/09/ZWellcome Trust 104085Wellcome Trust 104085/Z/14/ZWellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

Importance: There is some support for the existence of genetic associations between adiposity and certain hepatobiliary diseases in Western populations. However, there is little evidence of such genetic associations in China, where the causes of these diseases may differ from those in Western populations and the mean body mass index (BMI) is much lower. Objectives: To compare the observational associations of BMI with hepatobiliary diseases and liver biomarkers with the genetic associations between BMI and these factors and to assess whether the genetic associations of BMI with liver diseases differed by hepatitis B virus infection status. Design, Setting, and Participants: This cohort study used data from the prospective China Kadoorie Biobank, including 473 938 adults aged 30 to 79 years without hepatobiliary diseases at baseline from 10 diverse areas in China from June 25, 2004, to July 15, 2008. A random sample of 75 736 participants with genotyping data was included in the Mendelian randomization analysis. Follow-up was completed January 1, 2017 (median [interquartile range] length of follow-up, 10.2 [9.2-11.1] years). Data were analyzed from January to October 2019. Exposures: Measured BMI obtained during the baseline survey and genetically instrumented BMI derived using 92 single-nucleotide variations. Main Outcomes and Measures: Incident cases of hepatobiliary diseases, liver enzymes, fatty liver index, and fibrosis score. Results: Among 473 938 individuals (276 041 [58.2%] women), the mean (SD) age was 52 (10.9) years and mean (SD) BMI was 23.8 (3.4). Baseline BMI was associated with higher risks of chronic liver disease (adjusted risk ratio per 1-SD increase, 1.14; 95% CI, 1.11 to 1.17) and gallbladder disease (adjusted risk ratio per 1-SD increase, 1.29; 95% CI, 1.27 to 1.31), with heterogeneity by disease subtype (P < .001). Genetically instrumented BMI was associated with higher risks of chronic liver disease (risk ratio per 1-SD increase, 1.55; 95% CI, 1.08 to 2.24) and gallbladder disease (risk ratio per 1-SD increase, 1.40; 95% CI, 1.11 to 1.76), with no heterogeneity between subtypes. A meta-analysis of the genetic associations in China Kadoorie Biobank and those calculated in UK Biobank gave a risk ratio of 1.55 (95% CI, 1.30 to 1.84) for chronic liver disease and 1.42 (95% CI, 1.22 to 1.64) for gallbladder disease. In the China Kadoorie Biobank study, there were positive genetic associations of BMI with liver enzymes, steatosis, and fibrosis scores, consistent with observational associations. The genetic associations of BMI with liver diseases and biomarkers did not differ by hepatitis B virus infection status. Conclusions and Relevance: In this cohort study of a relatively lean Chinese population, there were positive genetic associations of BMI with hepatobiliary diseases. These results suggest that maintaining a healthy weight through diet and physical activity may help prevent hepatobiliary diseases.

Indexed as

Body Mass IndexGenetic Predisposition to DiseaseAdultAgedAsian PeopleBiomarkersChinaDigestive System DiseasesFemaleHumansMaleMiddle AgedRisk FactorsThinnessBiomarkers

Identifiers

PMID33006619
PMCPMC7532388
OpenAlexW3089431965

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.