ArticleInternational journal of endocrinology and metabolism2013
Insulin-related biomarkers to predict the risk of metabolic syndrome.
Article in International journal of endocrinology and metabolism, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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3 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2021Pooled it
- Association of Serum Uric Acid with cardio-metabolic risk factors and metabolic syndrome in seafarers working on tankers.BMC public health · 2020Article
- Article
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1 author at 1 institution in 1 country.
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Abstract
backgroundThe predictive ability of insulin resistance or insulin sensitivity, in combination with traditional cardiovascular risk factors for metabolic syndrome (MetS), has not yet been clearly evaluated in Japanese male subjects.
objectivesA one-year follow-up study was conducted to determine the ability of the insulin-related biomarkers to predict the risk of MetS development. PATIENTS AND
methodsA total of 2642 male workers of a Japanese company free from MetS at the baseline were monitored. The homeostasis model assessment for insulin resistance (HOMA-IR), and quantitative insulin sensitivity check index (QUICKI) were selected as the insulin-related markers.
resultsThe incidence of metabolic syndrome after one year was 8.8%. A multiple logistic regression analysis identified regular physical activity, age (≥ 45 years old), serum uric acid (≥ 7 mg/dL), serum alanine aminotransferase (≥ 45 IU/L), serum C-reactive protein (≥ 0.1 mg/L) and HOMA-IR (≥ 2.5) as significant risk factors for the development of MetS, with odds ratios (95% confidence intervals) of 0.68 (0.50 - 0.92), 2.0 (1.5 - 2.6), 2.2 (1.6 - 3.0), 1.5 (1.02 - 2.2), 1.4 (1.01 - 2.0), and 2.3 (1.6 - 3.3), respectively. When QUICKI was used instead of HOMA-IR, age (≥ 45 years old), serum uric acid (≥ 7 mg/dL), serum gamma-glutamyl transferase (≥ 50 IU/L), and QUICKI (≤ 0.33) were identified as significant contributors to the risk of MetS, with odds ratios (95% confidence intervals) of 0.68 (0.51 - 0.93), 2.0 (1.5 - 2.6), 2.2 (1.6 - 3.0), 1.4 (1.01 - 2.0), and 2.5 (1.7 - 3.6), respectively.
conclusionsThe mathematical meaning of the two insulin-related biomarkers examined was the same, and the odds ratios of the two biomarkers were almost the same after adjustments for other independent variables.
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