Resistance training in the treatment of the metabolic syndrome: a systematic review and meta-analysis of the effect of resistance training on metabolic clustering in patients with abnormal glucose metabolism

Abstract

Over the last decade, investigators have given increased attention to the effects of resistance training (RT) on several metabolic syndrome variables. The metabolic consequences of reduced muscle mass, as a result of normal aging or decreased physical activity, lead to a high prevalence of metabolic disorders. The purpose of this review is: (i) to perform a meta-analysis of randomized controlled trials (RCTs) regarding the effect of RT on obesity-related impaired glucose tolerance and type 2 diabetes mellitus; and (ii) to investigate the existence of a dose-response relationship between intensity, duration and frequency of RT and the metabolic clustering. Thirteen RCTs were identified through a systematic literature search in MEDLINE ranging from January 1990 to September 2007. We included all RCTs comparing RT with a control group in patients with abnormal glucose regulation. For data analysis, we performed random effects meta-analyses to determine weighted mean differences (WMD) with 95% confidence intervals (CIs) for each endpoint. All data were analysed with the software package Review Manager 4.2.10 of the Cochrane Collaboration. In the 13 RCTs included in our analysis, RT reduced glycosylated haemoglobin (HbA(1c)) by 0.48% (95% CI -0.76, -0.21; p = 0.0005), fat mass by 2.33 kg (95% CI -4.71, 0.04; p = 0.05) and systolic blood pressure by 6.19 mmHg (95% CI 1.00, 11.38; p = 0.02). There was no statistically significant effect of RT on total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglyceride and diastolic blood pressure. Based on our meta-analysis, RT has a clinically and statistically significant effect on metabolic syndrome risk factors such as obesity, HbA(1c) levels and systolic blood pressure, and therefore should be recommended in the management of type 2 diabetes and metabolic disorders.