Objective: The epidemiological evidence for the association between sleep duration and obesity in the elderly is inconsistent and has not been investigated with objective measures. Furthermore, the role of sleep fragmentation in this relationship is unknown. Our aim was to investigate the association of sleep measures with body mass index (BMI) and obesity in a normal elderly population. Design: Cross-sectional study. Subjects: A total of 983 community-dwelling elderly (mean age 68.4±6.9 years, range, 57-97). Measurements: Weight and height were measured, and sleep duration and fragmentation were assessed with on average six nights of actigraphy.Results: A quadratic model adequately described the association between continuous measures of sleep duration and BMI. Actigraphic sleep duration had a significant U-shaped relationship with BMI (b of quadratic term ¼ 0.30, 95% confidence interval (CI): 0.08, 0.52). Both short sleepers (o5 h: OR, 2.76 (95% CI: 1.38, 5.49), 5 to o6 h: OR, 1.97 (95% CI: 1.26, 3.08)) and long sleepers (X8 h: OR, 2.93 (95% CI: 1.39, 6.16)) were more likely to be obese, compared to participants who slept 7 to o8 h. BMI increased with 0.59 kg m À2 per standard deviation of sleep fragmentation (95% CI: 0.34, 0.84). After adjustment for sleep fragmentation, the association between short sleep and obesity was no longer significant. Exclusion of participants with probable sleep apnea only marginally changed these associations. Self-reported habitual sleep duration was not associated with BMI or obesity. Conclusions: Sleep duration, as measured with actigraphy, had a U-shaped relationship with BMI and obesity in an elderly population. A highly fragmented sleep is associated with a higher BMI and a higher risk of obesity, and may explain why short sleep is related to obesity. To preclude bias that can be introduced by self-report measures of sleep duration, using multiple measures of sleep parameters is recommended in future research.

Social isolation in community-dwelling older adults with dementia is a growing health issue that can negatively affect health and well-being. To date, little attention has been paid to the role of technology in improving their social participation. This systematic review aims to provide a systematic overview of the effects of technological interventions that target social participation in community-dwelling older adults with and without dementia. The scientific databases Medline (PubMed), PsycINFO, CINAHL, Web of Science, and the Cochrane Library were systematically searched and independently screened by two reviewers. Results were synthesized narratively. The methodological quality of included studies was independently assessed by two reviewers. In total, 36 studies of varying methodological quality were identified. Most studies evaluated social networking technology and ICT training programs. Three studies focused on people with dementia. Quantitative findings showed limited effects on loneliness, social isolation, and social support. Nevertheless, several benefits related to social participation were reported qualitatively. Social interaction, face-to-face contact, and intergenerational engagement were suggested to be successful elements of technological interventions in improving the social participation of community-dwelling older adults. Rigorous studies with larger sample sizes are highly needed to evaluate the long-term effects of technology on the multidimensional concept of social participation.

The combination of self-reported travel diaries and objective GPS loggers offered detailed information about the actual outdoor travel behaviour of PwMS, which was significantly changed in PwMS with EDSS greater than 4. Implications for Rehabilitation Activity and travel behaviour changes significantly in persons with multiple sclerosis (MS) with moderate to severe disability (EDSS greater than 4). Behavioural therapy could help to develop better coping and problem-solving skills to overcome anxiety in the making of trips by persons with MS with a mild severity. Enhancing community environments could serve as a promising approach to increase the outdoor participation of persons with (more severe) impairments.

In multiple sclerosis (MS), physical activity (PA) is most commonly measured as number of steps, while also walking intensity and walking activity duration are keys for a healthy lifestyle. The aim of this study was to investigate (1) the number of steps persons with MS (PwMS) take; (2) the number of steps they take at low and moderate intensity; and (3) their walking activity duration for 2, 3, 6, 10, 12 and 14 uninterrupted minutes; all related to the degree of disability. 64 PwMS participated, distinguished in a mild (n = 31) and moderate MS subgroup (n = 34) based on their ambulatory dysfunction (Disease Steps). Standardized clinical tests were performed, and step data from the StepWatch Activity Monitor were collected for seven consecutive days. The results showed that (1) step count in PwMS was lower than PA recommendations, and is negatively influenced by a higher disability degree. (2) No walking was registered during 77 % of the day. PwMS are making steps for 22 % at low and only 1 % at moderate intensity. (3) Both MS subgroups rarely walk for more than six uninterrupted minutes, especially not at moderate intensity. PwMS need to be encouraged to make steps at moderate intensity, and to make steps for longer periods of time (minimal ten uninterrupted minutes).

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Current cardiac rehabilitation programs intending to increase physical activity of patients suffer from a lack of knowledge about effective patient's activity profiles and their associated behavior. This leads to the fact that therapies are not completely tailored to the patient, causing non-adherence to the proposed treatment schedule. An important potential for increasing the physical activity level of patients is available in their daily travel behaviour that can be made more active. To validate this potential, we propose a Cardiac Travel Advice Support System (CTASS) digital framework for personalized travel behaviour advice to cardiac patients. The travel behaviour of the group of patients whose actual physical activity level is expected to be too low is monitored by a smartphone application that objectifies their daily activity schedules. The data from the schedules is analysed semi-automatically by the CTASS. Based on this analysis, the doctor can provide a treatment that is personalized to the specific contexts of the patient. In this way, we try to optimize their travel-related physical activity. Moreover, we predict the risk of non-adherence to the therapy taking into account the derived characteristics of the patient.

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