ArticleScientific reports2020
A cross-sectional study on diabetes epidemiology among people aged 40 years and above in Shenyang, China.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The worldwide trend in diabetes awareness, treatment, and control from 1985 to 2022: a systematic review and meta-analysis of 233 population-representative studies.Frontiers in public health · 2024Pooled it
- Systematic literature review and meta-analysis of cardiovascular risk factor management in selected Asian countries.Journal of comparative effectiveness research · 2023Pooled it
- Cumulative estimated glucose disposal rate predicts frailty progression in Chinese adults with diabetes: a 9-year follow-up cohort study.Frontiers in medicine · 2025Article
- Prevalence, awareness, treatment and control of type 2 diabetes in southeast China: A population-based study.Journal of diabetes investigation · 2024Article
- Mortality and Years of Life Lost in Diabetes Mellitus and Its Subcategories in China and Its Provinces, 2005-2020.Journal of diabetes research · 2022Article
- Prevalence and potential risk factors of self-reported diabetes among elderly people in China: A national cross-sectional study of 224,142 adults.Frontiers in public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed at understanding the diabetic prevalence, awareness, treatment and control rates and their influencing factors among people aged ≥ 40 years in Shenyang, China. A face-to-face cross-sectional epidemiological survey was conducted on the respondents using the national unified questionnaire. A total of 3922 respondents were enrolled, including 609 cases of diabetes. The diabetic prevalence rate was 15.5%, and was higher in rural areas than that in urban areas (17.7% vs. 14.2%, p = 0.004), while no difference was observed between men and women (14.8% vs. 16.1%, p = 0.242). Advanced age, hypertension and dyslipidemia were the diabetes influencing factors. Among the 609 respondents with diabetes, the diabetic awareness and treatment rates, and the control rate of fasting plasma glucose were 82.3%, 36.6% and 17.1%, respectively. In different age groups, the diabetic awareness rate was higher in men than that in women, and the treatment rate was higher in women than that in men. The diabetic patients, who consumed fruit for ≥ 5 days a week, accounted for 16.3%, and their diabetic treatment (28.1%) and control rates (44.1%) were lower. Shenyang people aged ≥ 40 years have higher diabetic prevalence and awareness rates, and lower diabetic treatment and control rates. Finally, it is necessary to enhance awareness and education about diabetes, to improve its treatment and control rates.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.