Weight rhythms: weight increases during weekends and decreases during weekdays.

BACKGROUND/AIMS: The week's cycle influences sleep, exercise, and eating habits. An accurate description of weekly weight rhythms has not been reported yet - especially across people who lose weight versus those who maintain or gain weight. METHODS: The daily weight in 80 adults (BMI 20.0-33.5 kg/m(2); age, 25-62 years) was recorded and analysed to determine if a group-level weekly weight fluctuation exists. This was a retrospective study of 4,657 measurements during 15-330 monitoring days. Semi-parametric regression was used to model the rhythm. RESULTS: A pattern of daily weight changes was found (p < 0.05), with higher weight early in the week (Sunday and Monday) and decreasing weight during the week. Increases begin on Saturday and decreases begin on Tuesday. This compensation pattern was strongest for those who lost or maintained weight and weakest for those who slowly gained weight. CONCLUSION: Weight variations between weekends and weekdays should be considered as normal instead of signs of weight gain. Those who compensate the most are most likely to either lose or maintain weight over time. Long-term habits may make more of a difference than short-term splurges. People prone to weight gain could be counselled about the importance of weekday compensation.

Active assistance technology reduces glycosylated hemoglobin and weight in individuals with type 2 diabetes: results of a theory-based randomized trial.

BACKGROUND: Type 2 diabetes is an individual health challenge requiring ongoing self-management. Remote patient reporting of relevant health parameters and linked automated feedback via mobile telephone have potential to strengthen self-management and improve outcomes. This research involved development and evaluation of a mobile telephone-based remote patient reporting and automated telephone feedback system, guided by health behavior change theory, aimed at improving self-management and health status in individuals with type 2 diabetes. SUBJECTS AND METHODS: This research comprised a randomized controlled trial. Inclusion criteria were diagnosis of type 2 diabetes, elevated glycosylated hemoglobin (HbA1c) levels (range, 6.5-11%) or use of oral diabetes medication, and 30-70 years of age. Intervention subjects (n=24) participated in remote patient reporting of health status parameters and linked health behavior change feedback. Control participants (n=24) received standard of care including diabetes education and healthcare provider counseling. Patients were followed for approximately 10 months. RESULTS: Intervention participants achieved, compared with controls and controlling for baseline, a significantly greater mean reduction in HbA1c of -0.40% (95% confidence interval [CI] -0.67% to -0.14%) versus 0.036% (95% CI -0.23% to 0.30%) (P<0.03) and significantly greater weight reduction of -2.1 kg (95% CI -3.6 to -0.6 kg) versus 0.4 kg (95% CI -1.1 to 1.9 kg). Nonsignificant trends for greater intervention compared with control improvement in systolic and diastolic blood pressure were observed. CONCLUSIONS: Sophisticated information technology platforms for remote patient reporting linked with theory-based health behavior change automated feedback have potential to improve patient outcomes in type 2 diabetes and merit scaled-up research efforts.

Personal health technologies in employee health promotion: usage activity, usefulness, and health-related outcomes in a 1-year randomized controlled trial.

BACKGROUND: Common risk factors such as obesity, poor nutrition, physical inactivity, stress, and sleep deprivation threaten the wellness and work ability of employees. Personal health technologies may help improve engagement in health promotion programs and maintenance of their effect. OBJECTIVE: This study investigated personal health technologies in supporting employee health promotion targeting multiple behavioral health risks. We studied the relations of usage activity to demographic and physiological characteristics, health-related outcomes (weight, aerobic fitness, blood pressure and cholesterol), and the perceived usefulness of technologies in wellness management. METHODS: We conducted a subgroup analysis of the technology group (114 subjects, 33 males, average age 45 years, average BMI 27.1 kg/m(2)) of a 3-arm randomized controlled trial (N=352). The trial was organized to study the efficacy of a face-to-face group intervention supported by technologies, including Web services, mobile applications, and personal monitoring devices. Technology usage was investigated based on log files and questionnaires. The associations between sustained usage of Web and mobile technologies and demographic and physiological characteristics were analyzed by comparing the baseline data of sustained and non-sustained users. The associations between sustained usage and changes in health-related outcomes were studied by repeated analysis of variance, using data measured by baseline and end questionnaires, and anthropometric and laboratory measurements. The experienced usability, usefulness, motivation, and barriers to using technologies were investigated by 4 questionnaires and 2 interviews. RESULTS: 111 subjects (97.4%) used technologies at some point of the study, and 33 (29.9%) were classified as sustained users of Web or mobile technologies. Simple technologies, weight scales and pedometer, attracted the most users. The sustained users were slightly older 47 years (95% CI 44 to 49) versus 44 years (95% CI 42 to 45), P=.034 and had poorer aerobic fitness at baseline (mean difference in maximal metabolic equivalent 1.0, 95% Cl 0.39 to 1.39; P=.013) than non-sustained users. They succeeded better in weight management: their weight decreased -1.2 kg (95% CI -2.38 to -0.01) versus +0.6 kg (95% CI -0.095 to 1.27), P=.006; body fat percentage -0.9%-units (95% CI -1.64 to -0.09) versus +0.3%-units (95% CI -0.28 to 0.73), P=.014; and waist circumference -1.4 cm (95% CI -2.60 to -0.20) versus +0.7 cm (95% CI -0.21 to 1.66), P=.01. They also participated in intervention meetings more actively: median 4 meetings (interquartile range; IQR 4-5) versus 4 meetings (IQR 3-4), P=.009. The key factors in usefulness were: simplicity, integration into daily life, and clear feedback on progress. CONCLUSIONS: Despite active initial usage, less than 30% of subjects continued using Web or mobile technologies throughout the study. Sustained users achieved better weight-related outcomes than non-sustained users. High non-usage attrition and modest outcomes cast doubt on the potential of technologies to support interventions.