Evidence map›Paper›PMID 31974579›Full record

ArticleThe American journal of clinical nutrition2020

Genetic risk, adherence to a healthy lifestyle, and type 2 diabetes risk among 550,000 Chinese adults: results from 2 independent Asian cohorts.

Haoxin Li, Chiea-Chuen Khor, Junning Fan, Jun Lv, Canqing Yu, Yu Guo, Zheng Bian, Ling Yang, Iona Y Millwood, Robin G Walters and 9 more

Open access · hybridAbstract read
In one paragraph

Article in The American journal of clinical nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
5.7field-weighted citation impact, top 4% 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

37 citing papers in PubMed, 2 syntheses or guidelines pooled it, 72 citations in OpenAlex.

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  5. [Health education preferences in patients with type 2 diabetes mellitus based on Big Five personality traits].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2026
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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

19 authors at 9 institutions in 4 countries.

Haoxin LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Chiea-Chuen KhorGenome Institute of Singapore, Singapore.
Junning FanDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Yu GuoChinese Academy of Medical Sciences, Beijing, China.
Zheng BianChinese Academy of Medical Sciences, Beijing, China.
Ling YangClinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Iona Y MillwoodClinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Robin G WaltersClinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Yiping ChenClinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Jian-Min YuanDivision of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, PA, USA.
Yan YangHuixian People's Hospital, Huixian, Henan, China.
Chen HuNCDs Prevention and Control Department, Huixian CDC, Huixian, Henan, China.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, China.
Zhengming ChenClinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Woon-Puay KohHealth Services and Systems Research, Duke-NUS Medical School, Singapore.
Tao HuangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Peking University · CNUniversity of Oxford · GBChinese Academy of Medical Sciences & Peking Union Medical College · CNChina National Center for Food Safety Risk Assessment · CNCixian People's Hospital · CNNational University of Singapore · SGSingapore Eye Research Institute · SGUniversity of Pittsburgh · USXian Center for Disease Control and Prevention · CN

Funding

Prospective studies of cancer etiology and prevention in Shanghai and SingaporeR01CA144034 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI YUAN, JIAN-MIN · 2010 to 2014
$7.0M
THE SINGAPORE COHORT STUDY OF DIET AND CANCERR01CA080205 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI YUAN, JIAN-MIN · 1999 to 2009
$5.3M
Cancer epidemiology cohorts in Shanghai and Singapore UM1CA182876 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI YUAN, JIAN-MIN · 2014 to 2018
$4.3M
Cancer Research UK 29186Medical Research Council MC_PC_13049Medical Research Council MC_PC_14135Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2NCI NIH HHS R01 CA080205NCI NIH HHS R01 CA144034NCI NIH HHS UM1 CA182876Wellcome Trust 088158/Z/09/ZWellcome Trust 104085/Z/14/ZWellcome Trust 202922/Z/16/ZWellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

backgroundWhether genetic susceptibility to type 2 diabetes is modified by a healthy lifestyle among Chinese remains unknown.

objectivesThe aim of the study was to determine whether genetic risk and adherence to a healthy lifestyle contribute independently to the risk of developing type 2 diabetes.

methodsWe defined a lifestyle score using BMI, alcohol intake, smoking, physical activities, and diets in 461,030 participants from the China Kadoorie Biobank and 38,434 participants from the Singapore Chinese Health Study. A genetic risk score was constructed based on type 2 diabetes loci among 100,175 and 16,172 participants in each cohort, respectively. A Cox proportional-hazards model was used to estimate the interaction between genetic and lifestyle factors on the risk of type 2 diabetes.

resultsIn 2 independent Asian cohorts, we consistently found a healthy lifestyle (the bottom quintile of lifestyle score) was associated with a substantially lower risk of type 2 diabetes than an unhealthy lifestyle (the top quintile of lifestyle score) regardless of genetic risk. In those at a high genetic risk, the risk of type 2 diabetes was 57% lower among participants with a healthy lifestyle than among those with an unhealthy lifestyle in the pooled cohorts. Among participants at high genetic risk, the standardized 10-y incidence of type 2 diabetes was 7.11% in those with an unhealthy lifestyle vs. 2.45% in those with a healthy lifestyle.

conclusionsIn 2 independent cohorts involving 558,302 Chinese participants, we did not observe an interaction between genetics and lifestyle with type 2 diabetes risk, but our findings provide replicable evidence to show lifestyle factors and genetic factors were independently associated with the risk of type 2 diabetes. Within any genetic risk category, a healthy lifestyle was associated with a significantly lower risk of type 2 diabetes among the Chinese population.

Indexed as

Healthy LifestyleAdultAgedAsian PeopleChinaCohort StudiesDiabetes Mellitus, Type 2FemaleHumansMaleMiddle AgedPolymorphism, Single NucleotideRisk FactorsSingaporeChinesegene–environment interactiongeneticslifestyletype 2 diabetes

Identifiers

PMID31974579
PMCPMC7049535
OpenAlexW3001541216

What OpenQuestion holds

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LicenceCC BY
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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.