Two-Year Follow-up of a Multimodal Intervention on Functional Capacity and Muscle Power in Frail Patients With Type 2 Diabetes

Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.

Regular exercise improves glucose control in diabetes, but the association of different exercise training interventions on glucose control is unclear. To conduct a systematic review and meta-analysis of randomized controlled clinical trials (RCTs) assessing associations of structured exercise training regimens (aerobic, resistance, or both) and physical activity advice with or without dietary cointervention on change in hemoglobin A(1c) (HbA(1c)) in type 2 diabetes patients. MEDLINE, Cochrane-CENTRAL, EMBASE, ClinicalTrials.gov, LILACS, and SPORTDiscus databases were searched from January 1980 through February 2011. RCTs of at least 12 weeks' duration that evaluated the ability of structured exercise training or physical activity advice to lower HbA(1c) levels as compared with a control group in patients with type 2 diabetes. Two independent reviewers extracted data and assessed quality of the included studies. Of 4191 articles retrieved, 47 RCTs (8538 patients) were included. Pooled mean differences in HbA(1c) levels between intervention and control groups were calculated using a random-effects model. Overall, structured exercise training (23 studies) was associated with a decline in HbA(1c) level (-0.67%; 95% confidence interval [CI], -0.84% to -0.49%; I(2), 91.3%) compared with control participants. In addition, structured aerobic exercise (-0.73%; 95% CI, -1.06% to -0.40%; I(2), 92.8%), structured resistance training (-0.57%; 95% CI, -1.14% to -0.01%; I(2), 92.5%), and both combined (-0.51%; 95% CI, -0.79% to -0.23%; I(2), 67.5%) were each associated with declines in HbA(1C) levels compared with control participants. Structured exercise durations of more than 150 minutes per week were associated with HbA(1c) reductions of 0.89%, while structured exercise durations of 150 minutes or less per week were associated with HbA(1C) reductions of 0.36%. Overall, interventions of physical activity advice (24 studies) were associated with lower HbA(1c) levels (-0.43%; 95% CI, -0.59% to -0.28%; I(2), 62.9%) compared with control participants. Combined physical activity advice and dietary advice was associated with decreased HbA(1c) (-0.58%; 95% CI, -0.74% to -0.43%; I(2), 57.5%) as compared with control participants. Physical activity advice alone was not associated with HbA(1c) changes. Structured exercise training that consists of aerobic exercise, resistance training, or both combined is associated with HbA(1c) reduction in patients with type 2 diabetes. Structured exercise training of more than 150 minutes per week is associated with greater HbA(1c) declines than that of 150 minutes or less per week. Physical activity advice is associated with lower HbA(1c), but only when combined with dietary advice.

Fragala, MS, Cadore, EL, Dorgo, S, Izquierdo, M, Kraemer, WJ, Peterson, MD, and Ryan, ED. Resistance training for older adults: position statement from the national strength and conditioning association. J Strength Cond Res 33(8): 2019-2052, 2019-Aging, even in the absence of chronic disease, is associated with a variety of biological changes that can contribute to decreases in skeletal muscle mass, strength, and function. Such losses decrease physiologic resilience and increase vulnerability to catastrophic events. As such, strategies for both prevention and treatment are necessary for the health and well-being of older adults. The purpose of this Position Statement is to provide an overview of the current and relevant literature and provide evidence-based recommendations for resistance training for older adults. As presented in this Position Statement, current research has demonstrated that countering muscle disuse through resistance training is a powerful intervention to combat the loss of muscle strength and muscle mass, physiological vulnerability, and their debilitating consequences on physical functioning, mobility, independence, chronic disease management, psychological well-being, quality of life, and healthy life expectancy. This Position Statement provides evidence to support recommendations for successful resistance training in older adults related to 4 parts: (a) program design variables, (b) physiological adaptations, (c) functional benefits, and (d) considerations for frailty, sarcopenia, and other chronic conditions. The goal of this Position Statement is to a) help foster a more unified and holistic approach to resistance training for older adults, b) promote the health and functional benefits of resistance training for older adults, and c) prevent or minimize fears and other barriers to implementation of resistance training programs for older adults.