ArticleAdvanced biomedical research2015
Effect of age on the phenotype of metabolic syndrome in developing country.
Article in Advanced biomedical research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Selenium Homeostasis and Clustering of Cardiovascular Risk Factors: A Systematic Review.Acta bio-medica : Atenei Parmensis · 2017Pooled it
- Article
- A higher TyG index level is more likely to have enhanced incidence of T2DM and HTN comorbidity in elderly Chinese people: a prospective observational study from the reaction study.Diabetology & metabolic syndrome · 2024Article
- The levels and trends of metabolic risk factors in the elderly population at the national and sub-national scale in Iran from 1990 to 2016.Journal of diabetes and metabolic disorders · 2023Article
- Reported organic food consumption and metabolic syndrome in older adults: cross-sectional and longitudinal analyses.European journal of nutrition · 2022Article
- A high triglyceride glucose index is more closely associated with hypertension than lipid or glycemic parameters in elderly individuals: a cross-sectional survey from the Reaction Study.Cardiovascular diabetology · 2020Article
- Effect of single nucleotide polymorphisms in SEPS1 and SEPP1 on expression in the protein level in metabolic syndrome in subjects with cardiovascular disease.Molecular biology reports · 2019Article
- Application of Latent Class Analysis to Identify Metabolic Syndrome Components Patterns in adults: Tehran Lipid and Glucose study.Scientific reports · 2019Article
- Some facts about the Metabolic Syndrome in Iran.ARYA atherosclerosis · 2017Article
- The cut-off values of anthropometric indices for identifying subjects at risk for metabolic syndrome in Iranian elderly men.Journal of obesity · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aimed to determine how age groups effect on the phenotype of metabolic syndrome (MetS) among Iranian population. MATERIALS AND
methodsThis cross-sectional study was conducted as part of Isfahan Healthy Heart Program. Height, weight, waist circumference, and blood pressure were measured by trained health-care professionals. MetS was defined as having three or more of the National Cholesterol Education Program III criteria. The relation between different age groups and different phenotypes of MetS was examined using the multinomial logistic regression.
resultsWe found low high-density lipoprotein-cholesterol (HDL-c) was the most common feature, followed by hypertriglyceridemia (HTG), abdominal obesity (ABO), hypertension (HTN), and high fasting blood glucose in decreasing order of prevalence. The most prevalent combination of MetS components was hypertrigeceridemia, low HDL-c and ABO (50.7%) in all subjects and especially in younger age group (63.2%). In elder age group, the most prevalent three components combination was HTG, Low HDL-c and HTN (43.9%). Logistic regression analysis demonstrated that elder subjects were at approximately 12 times higher risk of having the combination HTG, ABO, low HDL-c, and HTN (P < 0.001) compared to the middle age subjects who had a lower risk for the same combination; (2 [1.49-3.49]) (P < 0.001).
conclusionThis study provides a nationally representative estimate of the prevalence of different phenotypes of MetS across different age groups. Regarding different phenotypes of MetS in various age groups need to have important implications in the clinical management of these patients and the implementation of public health.
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