Loading
Diabetes, Cardiovascular Risks, and Lipoproteins · Journal article
BMC Cardiovascular Disorders · September 4, 2026
Early or partial results. Treat as a signal, not a conclusion.
This longitudinal cohort study identified four latent dyslipidemia states in middle-aged to older Iranian adults and characterized 5-year transition probabilities between them. Higher BMI and diabetes were associated with transitions to less favourable lipid states, whilst lipid-lowering medication use was associated with transitions to more favourable states. The findings are observational and descriptive, suitable for hypothesis generation but not for inferring causal effects or changing clinical practice.
Longitudinal observational cohort study with latent Markov modeling. Adults aged 45–70 years from Shahroud, Iran enrolled in the Shahroud Eye Cohort Study (ShECS) at phases 2 and 3. n = 4,054. Shahroud, Iran.
Four latent dyslipidemia states were identified: normal (41.0%), HDL-predominant (32.0%), TG-predominant (17.0%), and TC/LDL-predominant (10.0%) TC/LDL-predominant state was least stable, with about two-thirds transitioning to normal or HDL-predominant states over 5 years Prevalence of normal state increased while other dyslipidemia states decreased over 5-year follow-up
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
Clinicians should recognize that dyslipidemia patterns are dynamic over time and that BMI, diabetes control, and lipid-lowering medication use correlate with transitions between states. However, observational associations do not establish causation, and findings require confirmation in other populations before informing treatment decisions.
Observational longitudinal cohort study using latent Markov modeling to identify dyslipidemia states and transition patterns; descriptive and associational findings without randomization or causal inference, suitable for hypothesis generation rather than clinical decision-making.
As stated by the source record.
Quoted from the source exactly as published.
Clinicians should recognize that dyslipidemia patterns are dynamic over time and that BMI, diabetes control, and lipid-lowering medication use correlate with transitions between states. However, observational associations do not establish causation, and findings require confirmation in other populations before informing treatment decisions.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Dyslipidemia is a multifactorial metabolic disorder associated with an increased risk of cardiovascular and other chronic diseases. This study investigated changes in dyslipidemia patterns over a 5-year period and factors associated with transitions across different dyslipidemia states in the adult population of Shahroud. This longitudinal study used data related to 4054 adults aged 45–70 years from the second (2014) and third (2019) phases of the Shahroud Eye Cohort Study (ShECS). The data included indicators (abnormalities in total cholesterol, triglycerides, LDL-C, and HDL-C levels) and covariates (age, sex, body mass index, economic status, diabetes, blood pressure status, tobacco use, and lipid-lowering medication use). Data analysis was performed using a latent Markov model to identify dyslipidemia states and to estimate 5-year transition probabilities between them. Four latent dyslipidemia states were identified: normal (41.0%), HDL-predominant (32.0%), TG-predominant (17.0%), and TC/LDL-predominant (10.0%). Over the 5-year follow-up, the prevalence of the normal state increased, whereas the prevalence of the other dyslipidemia states decreased. The TC/LDL-predominant state was the least stable, with about two-thirds of individuals in this state transitioning to the normal or HDL-predominant states. Higher body mass index and diabetes were associated with transitions toward less favourable dyslipidemia states, whereas lipid-lowering medications use was associated with transitions toward more favourable states; sex, age, economic status, blood pressure, and current smoking were also associated with transition patterns. Overweight, obesity and diabetes appear to play important roles in the persistence and progression of dyslipidemia, while lipid-lowering therapy is associated with transition to more favourable lipid states. Strategies for dyslipidemia control should combine risk-factor reduction with appropriate pharmacological management.
Taken from the source record, never inferred. Follow any of these and new work involving them reaches your briefing.