ArticleDiabetology & metabolic syndrome2024
The synergistic effect of obesity and dyslipidemia on hypertension: results from the STEPS survey.
Article in Diabetology & metabolic syndrome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Effectiveness and safety of intermittent fasting on blood pressure in adults with overweight or obesity: a systematic review.International journal of obesity (2005) · 2025Pooled it
- Non-laboratory-based cardiovascular risk assessment: 10-year absolute risk, predicted heart age and intervention requirements in a Nigerian population.BMC cardiovascular disorders · 2026Article
- Integrative Multi-Omics Profiling of Dynamic Body Mass Index-Systolic Blood Pressure Trajectories in Obesity for Precision Risk Stratification of Heart Failure Subtypes.Biomedicines · 2026Article
- Prevalence and associated factors of obesity-related hypertension among Malaysian adults: findings from the National Health and Morbidity Survey 2023.BMC public health · 2026Article
- Clustering metabolic and behavioral risk factors for hypertension: evidence from a longitudinal cohort in western Iran.Scientific reports · 2026Article
- The role of chrysanthemum phytochemicals in neural tube development: a narrative review of underlying mechanisms.Frontiers in cell and developmental biology · 2026Review
- Nutrition Patterns, Metabolic and Psychological State Among High-Weight Young Adults: A Network Approach.Nutrients · 2026Article
- Hypertension Types and Associated Cardiovascular Risk Factors in Lithuanians Aged 50-54 Years.Journal of clinical medicine · 2025Article
- The association between obesity indicators and mortality among individuals with hyperlipidemia: evidence from the NHANES 2003-2018.Lipids in health and disease · 2025Article
- Patterns of general and abdominal obesity and their association with hypertension control in the iranian hypertensive population: insights from a nationwide study.BMC public health · 2025Article
- Joint Association of Remnant Cholesterol and Body Mass Index with Hypertension: A National Cohort Study in Chinese Adults.Journal of multidisciplinary healthcare · 2025Article
- Observational
- Comparative analysis of three BMI cutoffs for five metabolic abnormalities in the population of Western Guangdong, China.Frontiers in nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundObesity and dyslipidemia are important risk factors for hypertension (HTN). When these two conditions coexist, they may interact in a synergistic manner and increase the risk of developing HTN and its associated complications. The aim of this study was to investigate the synergistic effect of general and central obesity with dyslipidemia on the risk of HTN.
methodData from 40,387 individuals aged 25 to 64 years were obtained from a repeated cross-sectional study examining risk factors for non-communicable diseases (STEPS) in 2007, 2011 and 2016. Body mass index (BMI) was calculated as a measure of general obesity and waist circumference (WC) as a measure of central obesity. Dyslipidemia was defined as the presence of at least one of the lipid abnormalities. Hypertension was defined as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg or current use of antihypertensive medication. To analyze the synergistic effect between obesity and dyslipidemia and HTN, the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (SI) were calculated. A weighted logistic regression model was performed to estimate the odds ratios (ORs) for the risk of HTN.
resultsThe results showed an association between obesity, dyslipidemia and hypertension. The interaction between obesity and dyslipidemia significantly influences the risk of hypertension. In hypertensive patients, the presence of general obesity increased from 14.55% without dyslipidemia to 64.36% with dyslipidemia, while central obesity increased from 13.27 to 58.88%. This interaction is quantified by RERI and AP values of 0.15 and 0.06 for general obesity and 0.24 and 0.09 for central obesity, respectively. The corresponding SI of 1.11 and 1.16 indicate a synergistic effect. The OR also show that the risk of hypertension is increased in the presence of obesity and dyslipidemia.
conclusionObesity and dyslipidemia are risk factors for HTN. In addition, dyslipidemia with central obesity increases the risk of HTN and has a synergistic interaction effect on HTN. Therefore, the coexistence of obesity and lipid abnormalities has many clinical implications and should be appropriately monitored and evaluated in the management of HTN.
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.