Gait impairment is common in Parkinson's disease (PD) and may result in greater energy expenditure, poorer walking economy, and fatigue during activities of daily living. Auditory cueing is an effective technique to improve gait; but the effects on energy expenditure are unknown.To determine whether energy expenditure differs in individuals with PD compared with healthy controls and if auditory cueing improves walking economy in PD.Twenty participants (10 PD and 10 controls) came to the laboratory for three sessions. Participants performed two, 6-minute bouts of treadmill walking at two speeds (1.12 m·sec-1 and 0.67 m·sec-1). One session used cueing and the other without cueing. A metabolic cart measured energy expenditure and walking economy was calculated (energy expenditure/power).PD had worse walking economy and higher energy expenditure than control participants during cued and non-cued walking at the 0.67 m·sec-1 speed and during non-cued walking at the 1.12 m·sec-1. With auditory cueing, energy expenditure and walking economy worsened in both participant groups.People with PD use more energy and have worse walking economy than adults without PD. Walking economy declines further with auditory cuing in persons with PD.
There has been an explosion in the use of wearable physical activity (PA) monitors, but we do not fully understand who wears them and why. PURPOSE: To describe sociodemographics, PA behaviors, reasons for device use, and compare across genders. METHODS: PA monitor users (N=579) recruited through online forums completed a web-based survey. Sociodemographics, health information, PA and monitor use were queried. Descriptives are reported as means and standard deviations (SD), and frequencies. Independent t-tests and chi-square analysis were used to compare across genders. RESULTS: Table 1 shows the descriptive data. Respondents were 18-72 years old with 73.9% women. Men were older, had higher BMI and were less educated than women. Men and women had similar PA. More men purchased the device themselves, while more women received the device as a gift. A greater proportion of men used the device because of an interest in its technology or for training for a sport. A larger proportion of women used the device as a weight loss aid or because friends or family recommended its use. CONCLUSION: Activity monitor users in this sample were affluent, highly educated, and physically active. Men and women differed in their reasons for device adoption and use.TABLE 1: RESULTS (*= p<0.05)
The potential for long-term neurotoxic effects of anesthetics on the developing human brain has led to intensified research in this area. To date, the human evidence has been inconclusive, but a large body of animal evidence continues to demonstrate cause for concern. On April 14 and 15, 2018 the sixth biennial Pediatric Anesthesia and Neurodevelopmental Assessment (PANDA) study symposium was held at Morgan Stanley Children’s Hospital of New York. This symposium brought together clinicians and researchers and served as a platform to review preclinical and clinical data related to anesthesia and neurotoxicity in developing brains. The program participants included many active investigators in the field of anesthesia neurotoxicity as well as stakeholders from different backgrounds with the common interest of potential anesthetic neurotoxicity in children. The moderated poster session included presentations of preclinical animal research studies. These studies focused on defining the anesthetic-induced neurotoxicity phenotype, understanding the mechanism of injury and discovering potential inhibitors of neurotoxic effects.
PURPOSE: The purpose of this study was to evaluate trends in stage of change for physical activity. METHODS: A random sample of adult residents of Rhode Island was surveyed during the years 1998 and 2000, and stage of change for physical activity was determined. We compared the trends for stage of change over the two-year period. A subgroup analysis to determine trends according to demographic and socioeconomic characteristics was also performed. RESULTS: Persons were less likely to be in maintenance in 2000 compared with 1998, but a somewhat higher proportion of persons were in action. Compared with 1998, a positive, forward shift in the distribution of persons in the pre-action stages occurred, such that a smaller proportion of persons were in precontemplation and a greater proportion in contemplation and preparation. This shift to contemplation and preparation was most pronounced in men, older adults, whites and blacks. There was a relatively high proportion of persons who believed they met the physical activity recommendations of the US Surgeon General in both years surveyed. CONCLUSIONS: The proportion of persons in maintenance declined, and a forward shift in persons in the pre-action stages occurred over the two-year period. More people were in contemplation, preparation and action in 2000 compared with 1998. These shifts were most pronounced in older persons, men and persons of minority status, and support the efficacy of public health efforts to improve physical activity.
Wearable activity monitors (AM) have been well accepted in some randomized controlled trials and have contributed to an increase in levels of physical activity (PA) in some, but not all participants. The sociodemographic profiles of users may be associated with the length of time (number of months) they wear the device, and how they perceive it impacts their PA behavior. PURPOSE: To assess whether sociodemographic characteristics of AM users are related to 1) duration of device use, and 2) perceived changes in PA behavior. METHODS: Current (n = 1355) and former (n = 590) AM users from across the United States were recruited online and completed a web-based survey. Sociodemographics, health information, and AM use were queried. Moderate to vigorous PA (MVPA) score was calculated using the Godin Leisure Time PA Questionnaire. Respondents also reported how AM use influenced their PA. Descriptive statistics are reported as medians, means ± standard deviations, and frequencies. AM users were categorized based on the median use time: AM use for > 6 months or ≤ 6 months. Age, income and MPVA score were categorized by quartiles. Chi-squared analyses were used to compare groups for all categorical variables. RESULTS: Respondents were 18-81 years old (33.0 ± 12.2) with 73.1% women. A majority were current AM users (69.7%) and BMI was 26.7 ± 6.6. The number of months of AM use among current users was 10.1 ± 11.6, and 6.8 ± 6.4 among former users. Age (χ2 (3) = 38.8), income (χ2 (3) = 22.0), MVPA (χ2 (3) = 22.4) and relationship status (partnered vs single; χ2 (1) = 14.7) were all significantly different across the device-use categories (p < 0.001). A majority of current (76%) and former (53.2%) users perceived that the AM contributed to increased PA. Across all respondents, purchasing an AM themselves, as opposed to receiving it as a gift, was associated with a perceived increase in PA after device use (p < 0.05). CONCLUSION: Duration of activity monitor use was associated with the sociodemographic characteristics of users, with a majority perceiving an increase in their physical activity as a result of use. This supports the need for further research to explore how sociodemographic data can be used to tailor interventions to specific populations using technology-based objective monitoring.
