ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2020
The Impact of BMI Categories on Metabolic Abnormality Development in Chinese Adults Who are Metabolically Healthy: A 7-Year Prospective Study.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 5 citations in OpenAlex.
- Cross-sectional analysis of the association between physical activity and metabolic syndrome in the elderly.Frontiers in endocrinology · 2026Article
- Residual cholesterol inflammatory index and its prognostic role in mortality among individuals with cardiovascular-kidney-metabolic syndrome stages 0-3 based on U.S. and Chinese national cohorts.European journal of medical research · 2025Article
- Risk identification and improvement strategies for BMI and physical fitness and health grade cross-classification: a cross-sectional study based on Chinese college students.Frontiers in public health · 2025Article
- Short-Term Changes in Metabolically Healthy Overweight/Obesity Status Impact the Susceptibility to Type 2 Diabetes in Chinese Adults.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo determine what metabolic abnormalities develop frequently among metabolically healthy adults over time according to different baseline body mass index (BMI) categories. PATIENTS AND
methodsA prospective cohort study was performed on 10,805 adults, who were metabolically healthy at the time of the 2008 survey. Participants were divided into four groups: metabolically healthy obese (MHO), metabolically healthy overweight (MHOW), metabolically healthy normal-weight (MHN), and metabolically healthy underweight (MHU). Modified Poisson regression models were used to evaluate the relationship of BMI with the development of metabolic abnormalities. Association rule mining was used to identify the most frequent abnormalities that developed over time.
resultsCompared with the MHN group, the adjusted relative risks of the MHO group were 1.57 (95% CI: 1.09-2.27) and 2.08 (95% CI: 1.59-2.73) for developing elevated fasting glucose and elevated blood pressure, respectively, after adjusting for lifestyle behaviours and dietary factors. At the end of follow-up, 33 (19.1%) MHO subjects and 342 (16.6%) MHOW subjects had elevated blood pressure as the predominant metabolic syndrome component, whereas 236 (9.0%) MHU subjects had elevated plasma glucose. The results were similar after stratification by sex.
conclusionMHO and MHOW subjects developed elevated blood pressure most frequently, and MHU subjects developed elevated blood glucose most commonly, regardless of sex.
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.