Evidence map›Paper›PMID 31152186›Full record

ArticleDiabetologia2019

Sex differences in the association between socioeconomic status and diabetes prevalence and incidence in China: cross-sectional and prospective studies of 0.5 million adults.

Hongjiang Wu, Fiona Bragg, Ling Yang, Huaidong Du, Yu Guo, Caroline A Jackson, Shankuan Zhu, Canqing Yu, Andrea O Y Luk, Juliana C N Chan and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Diabetologia, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
4.7field-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

32 citing papers in PubMed, 58 citations in OpenAlex.

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  8. [Adaptive Regulation of Glucose Metabolism and Diseases in High-Altitude Areas].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2024
    Review
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  20. Sex differences in factors associated with prediabetes in Korean adults.Osong public health and research perspectives · 2022
    Article
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

14 authors at 7 institutions in 4 countries.

Hongjiang WuUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK.ORCID 0000-0003-2193-1114
Fiona BraggNuffield Department of Population Health, University of Oxford, Oxford, UK.
Ling YangNuffield Department of Population Health, University of Oxford, Oxford, UK.
Huaidong DuNuffield Department of Population Health, University of Oxford, Oxford, UK.
Yu GuoChinese Academy of Medical Sciences, Beijing, China.
Caroline A JacksonUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK.
Shankuan ZhuSchool of Public Health, Zhejiang University, Hangzhou, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Andrea O Y LukDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China.
Juliana C N ChanDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China.
Danijela GasevicUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK.
Liming LiChinese Academy of Medical Sciences, Beijing, China.
Zhengming ChenNuffield Department of Population Health, University of Oxford, Oxford, UK.
Sarah H WildUsher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, UK. sarah.wild@ed.ac.uk.
University of Oxford · GBUniversity of Edinburgh · GBChinese Academy of Medical Sciences & Peking Union Medical College · CNChinese University of Hong Kong · HKMonash University · AUPeking University · CNZhejiang University · CN

Funding

British Heart FoundationCancer Research UKMedical Research Council MC_PC_14135Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2Wellcome Trust 088158/Z/09/ZWellcome Trust 104085/Z/14/ZWellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

aims/hypothesisChina has undergone rapid socioeconomic transition accompanied by lifestyle changes that are expected to have a profound impact on the health of its population. However, there is limited evidence from large nationwide studies about the relevance of socioeconomic status (SES) to risk of diabetes. We describe the associations of two key measures of SES with prevalent and incident diabetes in Chinese men and women.

methodsThe China Kadoorie Biobank study included 0.5 million adults aged 30-79 years recruited from ten diverse areas in China during 2004-2008. SES was assessed using the highest educational level attained and annual household income. Prevalent diabetes was identified from self-report and plasma glucose measurements. Incident diabetes was identified from linkage to disease and death registries and national health insurance claim databases. We estimated adjusted ORs and HRs for prevalent and incident diabetes associated with SES using logistic and Cox regression models, respectively.

resultsAt baseline, 30,066 (5.9%) participants had previously diagnosed (3.1%) or screen-detected (2.8%) diabetes among 510,219 participants included for cross-sectional analyses. There were 480,153 people without prevalent diabetes at baseline, of whom 9544 (2.0%) had new-onset diabetes during follow-up (median 7 years). Adjusted ORs (95% CIs) for prevalent diabetes, comparing highest vs lowest educational level, were 1.21 (1.09, 1.35) in men and 0.69 (0.63, 0.76) in women; for incident diabetes, the corresponding HRs were 1.27 (1.07, 1.51) and 0.80 (0.67, 0.95), respectively. For household income, the adjusted ORs for prevalent diabetes, comparing highest vs lowest categories, were 1.45 (1.34, 1.56) in men and 1.26 (1.19, 1.34) in women; for incident diabetes, the HRs were 1.36 (1.19, 1.55) and 1.06 (0.95, 1.17), respectively. CONCLUSIONS/

interpretationAmong Chinese adults, the associations between education and diabetes prevalence and incidence differed qualitatively between men and women, whereas higher household income was positively associated with diabetes prevalence and incidence in both sexes, with a stronger relationship in men than in women.

Indexed as

Sex FactorsSocial ClassAdultAgedBlood GlucoseChinaCross-Sectional StudiesDiabetes MellitusEducational StatusFemaleFollow-Up StudiesHealth EquityHealth Status DisparitiesHumansIncidenceInsurance Claim ReviewBlood GlucoseDiabetesEducational levelHealth inequalityHousehold incomeSocioeconomic status

Identifiers

PMID31152186
PMCPMC6647183
OpenAlexW2947201571

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.