One-year caloric restriction and 12-week exercise training intervention in obese adults with type 2 diabetes: emphasis on metabolic control and resting metabolic rate

Zurlo, F.; Trevisan, Caterina; Vitturi, Nicola; Ravussin, Éric; Salvo, Carmelo Di; Carraro, Samuela; Siffi, M.; I, Iob; Saller, Alois; Previato, L.; Sergi, Giuseppe; Kreutzenberg, Saula de; Maran, Alberto; Avogaro, Angelo

doi:10.1007/s40618-019-01090-x

Cited by 5 publications

(3 citation statements)

References 42 publications

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“…A few studies have investigated the effects of CR and exercise on cardiometabolic health [ 25 , 26 , 27 ]. Despite the inconsistent results and the vastly differently designed interventions that were in those studies, a few studies reported that an appropriate amount of exercise improved the cardiometabolic health in individuals with normal-weight, overweight, obesity, metabolic syndrome, or diabetes mellitus [ 28 , 29 ].…”

Section: Discussionmentioning

confidence: 99%

Effects of Caloric Restriction and Rope-Skipping Exercise on Cardiometabolic Health: A Pilot Randomized Controlled Trial in Young Adults

Tang

Ming

et al. 2021

Nutrients

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The aim of this study is to investigate the effects of calorie restriction (CR), rope-skipping (RS) exercise, and their joint effects on cardiometabolic health in young adults. An 8-week randomized trial was conducted on 46 undergraduates aged 19–21 y from South China. The participants were randomized into the following three groups: Calorie restriction (CR) group (n = 14), Rope-skipping (RS) group (n = 14), and CR plus RS (CR–RS) group (n = 12). At both allocation and the end of the intervention, data on anthropometry, serum metabolic, and inflammatory markers were collected. A total of 40 participants completed the intervention and were included in the analysis. After the 8-week intervention, the participants from the CR group and the CR–RS group reduced in body weight (−1.1 ± 1.7 kg, −1.3 ± 2.0 kg), body mass index (−0.4 ± 0.6 kg/m2, −0.5 ± 0.7 kg/m2), body fat percentage (−1.2 ± 1.6%, −1.7 ± 1.8%), and body fat mass (−1.1 kg (−2.2, −0.3), −1.1 kg (−2.5, −0.4)) compared to the baseline (p < 0.05 or p = 0.051). For metabolic and inflammatory factors, the participants in the CR–RS group showed significant decreases in low density lipoprotein cholesterol (−0.40 mmol/L) and interleukin-8 (−0.73 mmol/L). While all the above markers showed no significant difference among the groups after intervention, in the subgroup of overweight/obese participants (n = 23), the CR–RS group had significantly lower blood pressure, fasting insulin, homeostatic model assessment of insulin resistance, tumor necrosis factor-α, and interleukin-8 levels than the CR or RS groups (p < 0.05). In conclusion, both CR and CR–RS could reduce weight and improve body composition in young adults. More importantly, in those with overweight or obesity, CR–RS intervention might be superior to either CR or RS in improving cardiometabolic health.

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Section: Discussionmentioning

confidence: 99%

Effects of Caloric Restriction and Rope-Skipping Exercise on Cardiometabolic Health: A Pilot Randomized Controlled Trial in Young Adults

Tang

Ming

et al. 2021

Nutrients

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“…56,57 And also, the combined intervention of supervised structured exercise training and caloric restriction are effective in improving metabolic health and decreasing an excess weight in obese patients with T2DM. 58 The PA could result in an improved health status of T2DM patients and also decrease a burden of health professionals. 59 Besides, rising a PA may also decrease the risk of progression from GDM to T2DM.…”

Section: Management Of T2dmmentioning

confidence: 99%

<p>Antidiabetic Effects of Physical Activity: How It Helps to Control Type 2 Diabetes</p>

Wake¹

2020

DMSO

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Despite the improvements in clinical care of the patients, research updates, and public health interventions, there is still an increase in the prevalence, incidence, and mortality because of diabetes mellitus (DM). DM is a public health problem in both developed and developing countries. It has increased alarmingly, putting this disease in the dimension of an epidemic. Diabetes is associated with several complications which increase the risk of many serious health problems on the other side. Therefore, this review was aimed to discuss the antidiabetic effects of physical activity (PA) on type 2 DM (T2DM) by summarizing the significant studies on this topic. This review found that several studies have recommended the utilization of PA for the effective management of T2DM. PA is a non-pharmacologic therapy which is a significant strategy for the management of T2DM and is an appropriate lifestyle modification approach to be practiced by these patients. The studies showed that PA has antidiabetic effects which are evidenced by its substantial role in improving the blood glucose (BG) levels of the individuals with T2DM where it helps them to control their levels of glucose in the blood. It plays a significant role in glycemic control of this disease by lowering the BG levels through possible mechanisms such as decreasing insulin resistance, increasing production of glucose transporter type 4 (GLUT-4), lowering visceral adipose tissue (VAT), increasing pancreatic β-cell functions, using glucose for energy, and so on. In turn, the controlled glycemia helps to prevent the complications associated with uncontrolled T2DM and this would further improve the overall health of the patients and the burden on the health professionals as well. Finally, this review concludes that PA is the cornerstone in the management of T2DM. It also suggests that more attention is needed to its significance in the prevention, glycemic control, and its role in the management of the morbidity and mortality associated with T2DM. Practical PA recommendations and suggestions for the future direction of research in this area are also provided.

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“…It follows and explores user behavior to identify and affect significant variables for the purpose of obtaining the objective of the process [13,14]. The IoB can become a strong marketing facility for businesses all around the world since it has the potential to provide them with in-detail personalized breakdowns of the perception of their users [15,16]. In terms of personal healthcare, the IoB can efficiently deliver customized services [17].…”

Section: Introductionmentioning

confidence: 99%

The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors

Amiri,

Heidari,

Darbandi

et al. 2023

Sustainability

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With the swift pace of the development of artificial intelligence (AI) in diverse spheres, the medical and healthcare fields are utilizing machine learning (ML) methodologies in numerous inventive ways. ML techniques have outstripped formerly state-of-the-art techniques in medical and healthcare practices, yielding faster and more precise outcomes. Healthcare practitioners are increasingly drawn to this technology in their initiatives relating to the Internet of Behavior (IoB). This area of research scrutinizes the rationales, approaches, and timing of human technology adoption, encompassing the domains of the Internet of Things (IoT), behavioral science, and edge analytics. The significance of ML in medical and healthcare applications based on the IoB stems from its ability to analyze and interpret copious amounts of complex data instantly, providing innovative perspectives that can enhance healthcare outcomes and boost the efficiency of IoB-based medical and healthcare procedures and thus aid in diagnoses, treatment protocols, and clinical decision making. As a result of the inadequacy of thorough inquiry into the employment of ML-based approaches in the context of using IoB for healthcare applications, we conducted a study on this subject matter, introducing a novel taxonomy that underscores the need to employ each ML method distinctively. With this objective in mind, we have classified the cutting-edge ML solutions for IoB-based healthcare challenges into five categories, which are convolutional neural networks (CNNs), recurrent neural networks (RNNs), deep neural networks (DNNs), multilayer perceptions (MLPs), and hybrid methods. In order to delve deeper, we conducted a systematic literature review (SLR) that examined critical factors, such as the primary concept, benefits, drawbacks, simulation environment, and datasets. Subsequently, we highlighted pioneering studies on ML methodologies for IoB-based medical issues. Moreover, several challenges related to the implementation of ML in healthcare and medicine have been tackled, thereby gradually fostering further research endeavors that can enhance IoB-based health and medical studies. Our findings indicated that Tensorflow was the most commonly utilized simulation setting, accounting for 24% of the proposed methodologies by researchers. Additionally, accuracy was deemed to be the most crucial parameter in the majority of the examined papers.

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One-year caloric restriction and 12-week exercise training intervention in obese adults with type 2 diabetes: emphasis on metabolic control and resting metabolic rate

Cited by 5 publications

References 42 publications

Effects of Caloric Restriction and Rope-Skipping Exercise on Cardiometabolic Health: A Pilot Randomized Controlled Trial in Young Adults

Effects of Caloric Restriction and Rope-Skipping Exercise on Cardiometabolic Health: A Pilot Randomized Controlled Trial in Young Adults

<p>Antidiabetic Effects of Physical Activity: How It Helps to Control Type 2 Diabetes</p>

The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors

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