ArticleBMJ open diabetes research & care2020
Effects of BMI and LDL-cholesterol change pattern on cardiovascular disease in normal adults and diabetics.
Article in BMJ open diabetes research & care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Weight variability and cardiovascular outcomes: a systematic review and meta-analysis.Cardiovascular diabetology · 2023Pooled it
- Lipid variability and risk of microvascular complications in Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial: A post hoc analysis.Journal of diabetes · 2022Trial
- Association of the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) with COPD prevalence and all-cause mortality: a population-based study based on NHANES 2007-2016.Frontiers in medicine · 2025Article
- Sarcosine, Trigonelline and Phenylalanine as Urinary Metabolites Related to Visceral Fat in Overweight and Obesity.Metabolites · 2024Article
- Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts.Scientific reports · 2024Article
- High Variability of Body Mass Index Is Independently Associated With Incident Heart Failure.Journal of the American Heart Association · 2024Article
- Is There a Relationship between Adverse Pregnancy Outcomes and Future Development of Atherosclerosis?Biomedicines · 2023Review
- Development of Data Mining Algorithms for Identifying the Best Anthropometric Predictors for Cardiovascular Disease: MASHAD Cohort Study.High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension · 2023Article
- Repercussions of absolute and time-rated BMI "yo-yo" fluctuations on cardiovascular stress-related morbidities within the vascular-metabolic CUN cohort.Frontiers in endocrinology · 2022Article
- Dietary Magnesium Intake Affects the Vitamin D Effects on HOMA-β and Risk of Pancreatic β-Cell Dysfunction: A Cross-Sectional Study.Frontiers in nutrition · 2022Article
- Associations of variability in body mass index with cardiovascular outcomes in the general population: A systematic review.JRSM cardiovascular diseaseReview
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionTo examine how the risk of cardiovascular disease changes according to degree of change in body mass index (BMI) and low-density lipoprotein (LDL)-cholesterol in patients with diabetes using the health medical examination cohort database of the National Health Insurance Service in Korea. In comparison, the pattern in a non-diabetic control group was also examined. RESEARCH DESIGN AND
methodsThe study samples were 13 800 patients with type 2 diabetes and 185 898 non-diabetic controls, and their baseline characteristics and repeatedly measured BMI and LDL-cholesterol until occurrence of cardiovascular disease were collected in longitudinal data. We used the variability model that is joint of mixed effects and regression model, then estimated parameters about variability by Bayesian methods.
resultsThe risk of cardiovascular disease was increased significantly with high average real variability (ARV) of BMI in the patients with diabetes, but the risk of cardiovascular disease was not increased according to degree of ARV in non-diabetic controls. The Bayesian variability model was used to analyze the effects of BMI and LDL-cholesterol change pattern on development of cardiovascular disease in diabetics, showing that variability did not have a statistically significant effect on cardiovascular disease. This shows the danger of the former simple method when interpreting only the mean of the absolute value of the variation.
conclusionsThe approach of simple SD in previous studies for estimation of individual variability does not consider the order of observation. However, the Bayesian method used in this study allows for flexible modeling by superimposing volatility assessments on multistage models.
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