Evidence map›Paper›PMID 35643944›Full record

ArticleActa diabetologica2022

Association between cardiovascular health metrics and risk of incident type 2 diabetes mellitus: the Rural Chinese Cohort Study.

Pei Qin, Dechen Liu, Yifei Feng, Xingjin Yang, Yang Li, Yuying Wu, Huifang Hu, Jinli Zhang, Tianze Li, Xi Li and 7 more

Abstract read
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In one paragraph

Article in Acta diabetologica, 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

17 authors.

Pei QinShenzhen Qianhai Shekou Free Zone Hospital, No. 36 Gongye 7th Road, Luohu District, Shenzhen, Guangdong, 518001, People's Republic of China.
Dechen LiuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, No. 1066 Xueyuan Avenue, 30 Nanshan District, Shenzhen, Guangdong, 518060, People's Republic of China.
Yifei FengDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Xingjin YangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Yang LiShenzhen Qianhai Shekou Free Zone Hospital, No. 36 Gongye 7th Road, Luohu District, Shenzhen, Guangdong, 518001, People's Republic of China.
Yuying WuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, No. 1066 Xueyuan Avenue, 30 Nanshan District, Shenzhen, Guangdong, 518060, People's Republic of China.
Huifang HuShenzhen Qianhai Shekou Free Zone Hospital, No. 36 Gongye 7th Road, Luohu District, Shenzhen, Guangdong, 518001, People's Republic of China.
Jinli ZhangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Tianze LiDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Xi LiShenzhen Qianhai Shekou Free Zone Hospital, No. 36 Gongye 7th Road, Luohu District, Shenzhen, Guangdong, 518001, People's Republic of China.
Yang ZhaoDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Chuanqi ChenDepartment of Endocrinology, Shenzhen Qianhai Shekou Free Trade Zone Hospital, Shenzhen, Guangdong, People's Republic of China.
Fulan HuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, No. 1066 Xueyuan Avenue, 30 Nanshan District, Shenzhen, Guangdong, 518060, People's Republic of China.
Ming ZhangDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, No. 1066 Xueyuan Avenue, 30 Nanshan District, Shenzhen, Guangdong, 518060, People's Republic of China.
Yu LiuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, No. 1066 Xueyuan Avenue, 30 Nanshan District, Shenzhen, Guangdong, 518060, People's Republic of China.
Xizhuo SunDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, No. 1066 Xueyuan Avenue, 30 Nanshan District, Shenzhen, Guangdong, 518060, People's Republic of China.
Dongsheng HuShenzhen Qianhai Shekou Free Zone Hospital, No. 36 Gongye 7th Road, Luohu District, Shenzhen, Guangdong, 518001, People's Republic of China. hud@szu.edu.cn.ORCID http://orcid.org/0000-0002-9998-8041

Funding

National Natural Science Foundation of China 81402752National Natural Science Foundation of China 81673260National Natural Science Foundation of China 82103940Natural Science Foundation of Guangdong Province 2019A1515011183
6 · The paper itself

Abstract

aimsThe evidence for association between cardiovascular health (CVH) metrics and type 2 diabetes mellitus (T2DM) in Chinese population is limited. We explored the association between the number of ideal CVH metrics and risk of incident T2DM in a rural Chinese population. MATERIALS AND

methodsA total of 12,150 rural Chinese participants (median age 51 years) were enrolled. A Cox proportional-hazards model was used to assess the association between the number of ideal CVH metrics and risk of incident T2DM by using hazard ratios (HRs) and 95% confidence intervals (CIs). We another conducted multiplicative and additive interaction effect between the number of ideal CVH metrics and sex or age on incident T2DM, and subgroup analyses of the association were also conducted by sex and age.

resultsDuring a median of 6.01 years of follow-up, 840 incident cases of T2DM occurred. The number of ideal CVH metrics was negatively associated with risk of incident T2DM (per unit increase: HR = 0.76, 95% CI 0.70-0.82). We also observed both multiplicative and additive interaction effect between lower number of ideal CVH metrics and sex on incident T2DM, and multiplicative interaction effect between lower number of ideal CVH metrics and age on incident T2DM was observed. The association remained statistically significant for both men and women, or participants with age < 65 years.

conclusionsIncreasing number of ideal CVH metrics was associated with reduced risk of incident T2DM, which presented age- and sex-related differential associations.

Indexed as

Cardiovascular DiseasesCardiovascular SystemDiabetes Mellitus, Type 2AgedChinaCohort StudiesFemaleHealth StatusHumansMaleMiddle AgedQuality Indicators, Health CareRisk FactorsAge and sex differencesCardiovascular healthCohort studyType 2 diabetes mellitus

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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.