Among adolescents, overweight, obesity and metabolic syndrome are rapidly increasing in recent years as a consequence of unhealthy palatable diets. Animal models of diet-induced obesity have been developed, but little is known about the behavioural patterns produced by the consumption of such diets. The aim of the present study was to determine the behavioural and biochemical effects of a cafeteria diet fed to juvenile male and female rats, as well as to evaluate the possible recovery from these effects by administering standard feeding during the last week of the study. Two groups of male and female rats were fed with either a standard chow diet (ST) or a cafeteria (CAF) diet from weaning and for 8 weeks. A third group of males (CAF withdrawal) was fed with the CAF diet for 7 weeks and the ST in the 8th week. Both males and females developed metabolic syndrome as a consequence of the CAF feeding, showing overweight, higher adiposity and liver weight, increased plasma levels of glucose, insulin and triglycerides, as well as insulin resistance, in comparison with their respective controls. The CAF diet reduced motor activity in all behavioural tests, enhanced exploration, reduced anxiety-like behaviour and increased social interaction; this last effect was more pronounced in females than in males. When compared to animals only fed with a CAF diet, CAF withdrawal increased anxiety in the open field, slightly decreased body weight, and completely recovered the liver weight, insulin sensitivity and the standard levels of glucose, insulin and triglycerides in plasma. In conclusion, a CAF diet fed to young animals for 8 weeks induced obesity and metabolic syndrome, and produced robust behavioural changes in young adult rats, whereas CAF withdrawal in the last week modestly increased anxiety, reversed the metabolic alterations and partially reduced overweight.

Background: Physical activity (PA) is a key health behavior in people with stroke including risk reduction of recurrent stroke. Despite the beneficial effects of PA, many community-dwelling stroke survivors are physically inactive. Information and communication technologies are emerging as a possible method to promote adherence to PA. Objective: The aim of this study is to investigate the effectiveness of a mobile-health (mHealth) App in improving levels of PA. Methods: Forty-one chronic stroke survivors were randomized into an intervention group (IG) n=24 and a control group (CG) n=17. Participants in the IG were engaged in the Multimodal Rehabilitation Program (MMRP) that consisted on supervising adherence to PA through a mHealth app, participating in an 8-week rehabilitation program that included: aerobic, task-oriented, balance and stretching exercises. Participants also performed an ambulation program at home. The CG received a conventional rehabilitation program. Outcome variables were: adherence to PA, (walking and sitting time/day), walking speed (10MWT); walking endurance (6MWT); risk of falling (TUG); ADLs (Barthel); QoL (Eq-5D5L) and participant’s satisfaction. Results: At the end of the intervention, community ambulation increased more in IG (38.95 min; SD: 20.37) than in the CG (9.47 min; SD: 12.11) (p≤.05). Sitting time was reduced by 2.96 (SD 2.0) hours/day in the IG and by 0.53 (SD 0.24) hours in the CG (p≤.05). Conclusions: The results suggest that mHealth technology provides a novel way to promote adherence to home exercise programs post stroke. However, frequent support and guidance of caregiver is required to ensure the use of mobile devices.

Exercise enhances general health. However, its effects on neurodegeneration are controversial, and the molecular pathways in the brain involved in this enhancement are poorly understood. Here, we examined the effect of long-term moderate treadmill training on adult male rat cortex and hippocampus to identify the cellular mechanisms behind the effects of exercise. We compared three animal groups: exercised (30 min/day, 12 m/min, 5 days/wk, 36 wk), handled but nonexercised (treadmill handling procedure, 0 m/min), and sedentary (nonhandled and nonexercised). Moderate long-term exercise induced an increase in IGF-1 levels and also in energy parameters, such as PGC-1α and the OXPHOS system. Moreover, the sirtuin 1 pathway was activated in both the exercised and nonexercised groups but not in sedentary rats. This induction could be a consequence of exercise as well as the handling procedure. To determine whether the long-term moderate treadmill training had neuroprotective effects, we studied tau hyperphosphorylation and GSK3β activation. Our results showed reduced levels of phospho-tau and GSK3β activation mainly in the hippocampus of the exercised animals. In conclusion, in our rodent model, exercise improved several major brain parameters, especially in the hippocampus. These improvements induced the upregulation of sirtuin 1, a protein that extends life, the stimulation of mitochondrial biogenesis, the activation of AMPK, and the prevention of signs of neurodegeneration. These findings are consistent with other reports showing that physical exercise has positive effects on hormesis.

Objective: To systematically review the publications on ecological momentary assessment (EMA) relating to physical activity (PA) behavior in order to classify the methodologies, and to identify the main mHealth technology-based tools and procedures that have been applied during the first 10 years since the emergence of smartphones. As a result of this review, we want to ask if there is enough evidence to propose the use of the term “mEMA” (mobile-based EMA). Design: A systematic review according to PRISMA Statement (PROSPERO registration: CRD42018088136). Method: Four databases (PsycINFO, CINALH, Medline and Web of Science Core Collection) were searched electronically from 2008 to February 2018. Results: A total of 76 studies from 297 potential articles on the use of EMA and PA were included in this review. It was found that 71% of studies specifically used “EMA” for assessing PA behaviors but the rest used other terminology that also adjusted to the inclusion criteria. Just over half (51.3%) of studies (39) used mHealth technology, mainly smartphones, for collecting EMA data. The majority (79.5%) of these studies (31 out of 39) were published during the last 4 years. On the other hand, 58.8% of studies that only used paper-and-pencil were published during the first 3 years of the 10-year period analyzed. An accelerometer was the main built-in sensor used for collecting PA behavior by means of mHealth (69%). Most of the studies were carried out on young-adult samples, with only three studies in older adults. Women were included in 60% of studies, and healthy people in 82%. The studies lasted between 1 and 7 days in 57.9%, and between three and seven assessments per day were carried out in 37%. The most popular topics evaluated together with PA were psychological state and social and environmental context. Conclusions: We have classified the EMA methodologies used for assessing PA behaviors. A total of 71% of studies used the term “EMA” and 51.3% used mHealth technology. Accelerometers have been the main built-in sensor used for collecting PA. The change of trend in the use of tools for EMA in PA coincides with the technological advances of the last decade due to the emergence of smartphones and mHealth technology. There is enough evidence to use the term mEMA when mHealth technology is being used for monitoring real-time lifestyle behaviors in natural situations. We define mEMA as the use of mobile computing and communication technologies for the EMA of health and lifestyle behaviors. It is clear that the use of mHealth is increasing, but there is still a lot to be gained from taking advantage of all the capabilities of this technology in order to apply EMA to PA behavior. Thus, mEMA methodology can help in the monitoring of healthy lifestyles under both subjective and objective perspectives. The tendency for future research should be the automatic recognition of the PA of the user without interrupting their behavior. The ecological information could be completed with voice messages, image captures or brief text selections on the touch screen made in real time, all managed through smartphone apps. This methodology could be extended when EMA combined with mHealth are used to evaluate other lifestyle behaviors.