Madeleine Svensson

Older members perform better in an internet-based behavioral weight loss program compared to younger members.

Background: New technology offers increased opportunities for weight control. However, it is not clear whether older people with less computer training can make use of this tool. Our objective was to examine how members above the age of 65 years performed in an internet-based behavioral weight loss program, compared to younger members. Methods: Data from members (n = 23,233) of an internet-based behavioral weight loss program were analyzed. We restricted our study to active participants accessing the weight club, during a 6-month period (n = 4,440). The number of logins, food intake, and weight records were examined. Participants were divided into age tertiles separately for men and women. The oldest tertile was further subdivided into two groups: above and below the age of 65 years. Results: Participants aged 65 or older were more likely to remain active in the weight club for at least 6 months compared to younger age groups. They had the highest frequency of recordings of food intake and current weight. Among women, those older than 65 years had on average the highest percentage of weight loss (5.6 kg, 6.8%). Men above 65 years of age had the highest number of logins, on average 161 times during the 6-month period. Conclusion: Older participants are performing equally well or even better in an internet-based behavioral weight loss program than younger participants. Internet-based programs could be a promising and attractive option for older adults requiring assistance in losing weight.

Motivational technologies to promote weight loss—From Internet to gadgets

The growing obesity epidemic cannot go unnoticed. It is amajor concern leading to fatal health conditions and high socioeconomic costs. Methods for losing weight are continuously being proposed in themedia [1], in the pharmaceutical field [2], in research [3] and in the general healthcare setting [4] – the expanding communication sources in modern times make it possible to distribute health information at most settings. Concurrently, the promotion of unhealthy foods and beverages reaches similar heights. The uneven battle between science and industry creates counterprevailing messages about healthy behaviors. Despite competing health messages, the major key behind successful weight loss is still behavioral changes [5], or put differently, ‘‘lifestyle-medicine’’ according to Egger et al. [6]. Once the desired bodyweight has been achieved, weight maintenance becomes the primary challenge [6]. Previous research shows that frequent contacts and follow-ups significantly increase the chance ofmaintaining newbehaviors [7–9]. In addition, asweight changes impinge upon individuals’ daily life, a supportive and understanding environment is a vital component of sustaining weight. The use of modern technology in weight loss interventions is expanding. By taking advantage of the potentials of technology,

The Change in Eating Behaviors in a Web-Based Weight Loss Program: A Longitudinal Analysis of Study Completers

Background Eating behaviors are essential components in weight loss programs, but limited research has explored eating behaviors in Web-based weight loss programs. Objectives The aim was to evaluate an interactive Web-based weight loss program on eating behaviors using the 18-item Three-Factor Eating Questionnaire Revised (TFEQ-R18) which measures uncontrolled eating, emotional eating, and cognitive restrained eating. Our Web-based weight loss program is comprised of information about healthy lifestyle choices, weekly chats with experts, social networking features, databases for recipe searches, and features allowing members to self-report and track their weight, physical activity, and dietary intake on the website. Methods On registering for the weight loss program, 23,333 members agreed to take part in the research study. The participants were then asked to complete the TFEQ-R18 questionnaire at baseline and after 3 and 6 months of participation. All data collection was conducted online, with no face-to-face contact. To study changes in TFEQ-R18 eating behaviors we restricted our study to those members who completed all 3 TFEQ-R18 questionnaires. These participants were defined as “completers” and the remaining as “noncompleters.” The relationships between sex, change in eating behaviors, and total weight loss were studied using repeated measures ANOVA and Pearson correlation coefficient. Results In total, 22,800 individuals participated (females: 19,065/22,800, 83.62%; mean age 39.6, SD 11.4 years; BMI 29.0 kg/m2; males: 3735/22,800, 16.38%; mean age 43.2, SD 11.7 years; BMI 30.8 kg/m2). Noncompleters (n=22,180) were younger and reported a lower score of uncontrolled eating and a higher score of cognitive restrained eating. Over time, completers (n=620) decreased their uncontrolled eating score (from 56.3 to 32.0; P<.001) and increased their cognitive restrained eating (from 50.6 to 62.9; P<.001). Males decreased their emotional eating (from 57.2 to 35.9; P<.001), but no significant change was found among females. The baseline cognitive restrained eating score was significantly and positively associated with weight loss for completers in both men (P=.02) and women (P=.002). Conclusions To our knowledge, this is the largest TFEQ sample that has been documented. This Web-based weight loss intervention suggests that eating behaviors (cognitive restrained eating, uncontrolled eating, and emotional eating) measured by TFEQ-R18 were significantly changed during 6 months of participation. Our findings indicate differences in eating behaviors with respect to sex, but should be interpreted with caution because attrition was high.

An Interactive Internet-Based Plate for Assessing Lunchtime Food Intake: A Validation Study on Male Employees

Background Misreporting food intake is common because most health screenings rely on self-reports. The more accurate methods (eg, weighing food) are costly, time consuming, and impractical. Objectives We developed a new instrument for reporting food intake—an Internet-based interactive virtual food plate. The objective of this study was to validate this instrument’s ability to assess lunch intake. Methods Participants were asked to compose an ordinary lunch meal using both a virtual and a real lunch plate (with real food on a real plate). The participants ate their real lunch meals on-site. Before and after pictures of the composed lunch meals were taken. Both meals included identical food items. Participants were randomized to start with either instrument. The 2 instruments were compared using correlation and concordance measures (total energy intake, nutritional components, quantity of food, and participant characteristics). Results A total of 55 men (median age: 45 years, median body mass index [BMI]: 25.8 kg/m2) participated. We found an overall overestimation of reported median energy intake using the computer plate (3044 kJ, interquartile range [IQR] 1202 kJ) compared with the real lunch plate (2734 kJ, IQR 1051 kJ, P<.001). Spearman rank correlations and concordance correlations for energy intake and nutritional components ranged between 0.58 to 0.79 and 0.65 to 0.81, respectively. Conclusion Although it slightly overestimated, our computer plate provides promising results in assessing lunch intake.

SLEEP DURATION DOES NOT PREDICT MAJOR ADVERSE CARDIAC EVENTS IN THE SWEDISH NATIONAL MARCH COHORT STUDY

Introduction and Objectives: Experimental research suggests that sleep deprivation may alter physiological factors associated with an increased risk for cardiovascular diseases (CVDs). Prior observational studies examining the effects of sleep duration have focused on narrowly defined CVD outcomes, such as myocardial infarction or stroke only. A more comprehensive measure of CVDs is lacking. Therefore, we examined the relationship between sleep duration and Major Adverse Cardiac Events (MACE).Materials and Methods: In 1997, 39,047 Swedish residents (women: 64%, age: 18-94 years) were enrolled in the National March cohort study and asked to self-report their habitual sleep duration in a questionnaire. They were followed-up over approximately 7 years to study incidents of MACE. Events were defined as death from all CVDs, nonfatal myocardial infarction, stroke, or heart failure. The relationship between sleep duration and MACE was analyzed using Cox proportional hazards models.Results: A total of 1,730 events were observed during a median follow-up period of 7.25 years. We found 665 nonfatal myocardial infarctions, 641 nonfatal strokes, 212 nonfatal heart failures, and 198 deaths from all CVDs. Age- and sex-adjusted hazard ratios (95% confidence intervals) of MACE (with 7 hours of sleep/day as the reference group) for individuals reporting ≤5, 6, and ≥ 8 hours of sleep were 1.24 (1.05-1.47), 1.03 (0.91-1.16), and 1.09 (0.97-1.23), respectively. Adjusting for BMI and physical activity did not change the hazard ratios. When adjusting for additional confounders, e.g., depressive symptoms, sleep apnea, and smoking, the association between ≤5h of sleep and MACE was attenuated (HR: 1.22, 95% CI: 0.98-1.52).Conclusion: Sleep duration was not associated with the risk of Major Adverse Cardiac Events. Sleep duration, however, may not in itself explain the effects of inadequate sleep on cardiovascular diseases. Yet, it may serve as an essential component in the understanding of cardiovascular diseases. Copyright