Evidence map›Paper›PMID 35762391›Full record

ArticleJournal of diabetes2022

Comprehensive risk profiles of family history and lifestyle and metabolic risk factors in relation to diabetes: A prospective cohort study.

Chaojie Ye, Yiying Wang, Lijie Kong, Zhiyun Zhao, Mian Li, Yu Xu, Min Xu, Jieli Lu, Shuangyuan Wang, Hong Lin and 5 more

Abstract read
In one paragraph

Article in Journal of diabetes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

15 authors.

Chaojie YeDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yiying WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lijie KongDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhiyun ZhaoDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0001-5950-2732
Mian LiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0001-6514-2729
Yu XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Min XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0003-3930-8718
Jieli LuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0003-1317-0896
Shuangyuan WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hong LinDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuhong ChenDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-6506-2283
Weiqing WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guang NingDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yufang BiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tiange WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0003-0723-489X

Funding

Chinese Academy of Medical Sciences 2018PT32017, 2019PT330006National Natural Science Foundation of China 81730023, 82088102National Natural Science Foundation of China 81941017National Natural Science Foundation of China 81970706National Natural Science Foundation of China 81970728National Natural Science Foundation of China 82022011Ruijin Hospital 2018CR002Shanghai Jiao Tong University School of Medicine DLY201801"Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support" from Shanghai Jiao Tong University School of Medicne 20171901 Round 2Shanghai Shenkang Hospital Development Center SHDC12019101Shanghai Shenkang Hospital Development Center SHDC12019101, SHDC2020CR1001A, SHDC2020CR3064B
6 · The paper itself

Abstract

backgroundFamily history of diabetes, unhealthy lifestyles, and metabolic disorders are individually associated with higher risk of diabetes, but how different combinations of the three risk categories are associated with incident diabetes remains unclear. We aimed to estimate the associations of comprehensive risk profiles of family history and lifestyle and metabolic risk factors with diabetes risk.

methodsThis study included 5290 participants without diabetes at baseline with a mean follow-up of 4.4 years. Five unhealthy lifestyles and five metabolic disorders were each allocated a score, resulting in an aggregated lifestyle and metabolic risk score ranging from 0 to 5. Eight risk profiles were constructed from combinations of three risk categories: family history of diabetes (yes, no), lifestyle risk (high, low), and metabolic risk (high, low).

resultsCompared with the profile without any risk category, other profiles exhibited incrementally higher risks of diabetes with increasing numbers of categories: the hazard ratio (HR, 95% confidence interval [CI]) for diabetes ranged from 1.34 (1.01-1.79) to 2.33 (1.60-3.39) for profiles with one risk category, ranged from 2.42 (1.45-4.04) to 4.18 (2.42-7.21) for profiles with two risk categories, and was 4.59 (2.85-7.39) for the profile with three risk categories. The associations between the numbers of risk categories and diabetes risk were more prominent in women (p

conclusionsThis study delineated associations between comprehensive risk profiles with diabetes risk, with stronger associations observed in women and slightly stronger associations in adults younger than 55 years.

Indexed as

Diabetes MellitusLife StyleAdultFemaleHumansProportional Hazards ModelsProspective StudiesRisk Factorsdiabetesfamily historylifestylemetabolic disorderrisk profile代谢紊乱家族史生活方式糖尿病风险特征

Identifiers

PMID35762391
PMCPMC9366567

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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.