A Mobile Health Lifestyle Program for Prevention of Weight Gain in Young Adults (TXT2BFiT): Nine-Month Outcomes of a Randomized Controlled Trial

BACKGROUND: The unprecedented rise in obesity among young adults, who have limited interaction with health services, has not been successfully abated. OBJECTIVE: The objective of this study was to assess the maintenance outcomes of a 12-week mHealth intervention on prevention of weight gain in young adults and lifestyle behaviors at 9 months from baseline. METHODS: A two-arm, parallel, randomized controlled trial (RCT) with subjects allocated to intervention or control 1:1 was conducted in a community setting in Greater Sydney, Australia. From November 2012 to July 2014, 18- to 35-year-old overweight individuals with a body mass index (BMI) of 25-31.99 kg/m2 and those with a BMI ≥ 23 kg/m2 and a self-reported weight gain of ≥ 2 kg in the past 12 months were recruited. A 12-week mHealth program "TXT2BFiT" was administered to the intervention arm. This included 5 coaching calls, 96 text messages, 12 emails, apps, and downloadable resources from the study website. Lifestyle behaviors addressed were intake of fruits, vegetables, sugar-sweetened beverages (SSBs), take-out meals, and physical activity. The control group received 1 phone call to introduce them to study procedures and 4 text messages over 12 weeks. After 12 weeks, the intervention arm received 2 further coaching calls, 6 text messages, and 6 emails with continued access to the study website during 6-month follow-up. Control arm received no further contact. The primary outcome was weight change (kg) with weight measured at baseline and at 12 weeks and self-report at baseline, 12 weeks, and 9 months. Secondary outcomes were change in physical activity (metabolic equivalent of task, MET-mins) and categories of intake for fruits, vegetables, SSBs, and take-out meals. These were assessed via Web-based surveys. RESULTS: Two hundred and fifty young adults enrolled in the RCT. Intervention participants weighed less at 12 weeks compared with controls (model β=-3.7, 95% CI -6.1 to -1.3) and after 9 months (model β=- 4.3, 95% CI - 6.9 to - 1.8). No differences in physical activity were found but all diet behaviors showed that the intervention group, compared with controls at 9 months, had greater odds of meeting recommendations for fruits (OR 3.83, 95% CI 2.10-6.99); for vegetables (OR 2.42, 95% CI 1.32-4.44); for SSB (OR 3.11, 95% CI 1.47-6.59); and for take-out meals (OR 1.88, 95% CI 1.07-3.30). CONCLUSIONS: Delivery of an mHealth intervention for prevention of weight gain resulted in modest weight loss at 12 weeks with further loss at 9 months in 18- to 35-year-olds. Although there was no evidence of change in physical activity, improvements in dietary behaviors occurred, and were maintained at 9 months. Owing to its scalable potential for widespread adoption, replication trials should be conducted in diverse populations of overweight young adults. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry (ANZCTR): ACTRN12612000924853; (Archived by WebCite at http://www.webcitation.org/6i6iRag55)

Effectiveness of a mHealth Lifestyle Program With Telephone Support (TXT2BFiT) to Prevent Unhealthy Weight Gain in Young Adults: Randomized Controlled Trial

BACKGROUND: Weight gained in young adulthood often persists throughout later life with associated chronic disease risk. Despite this, current population prevention strategies are not specifically designed for young adults. OBJECTIVE: We designed and assessed the efficacy of an mHealth prevention program, TXT2BFiT, in preventing excess weight gain and improving dietary and physical activity behaviors in young adults at increased risk of obesity and unhealthy lifestyle choices. METHODS: A two-arm, parallel-group randomized controlled trial was conducted. Subjects and analyzing researchers were blinded. A total of 250 18- to 35-year-olds with a high risk of weight gain, a body mass index (BMI) of 23.0 to 24.9 kg/m(2) with at least 2 kg of weight gain in the previous 12 months, or a BMI of 25.0 to 31.9 kg/m(2) were randomized to the intervention or control group. In the 12-week intervention period, the intervention group received 8 text messages weekly based on the transtheoretical model of behavior change, 1 email weekly, 5 personalized coaching calls, a diet booklet, and access to resources and mobile phone apps on a website. Control group participants received only 4 text messages and printed dietary and physical activity guidelines. Measured body weight and height were collected at baseline and at 12 weeks. Outcomes were assessed via online surveys at baseline and at 12 weeks, including self-reported weight and dietary and physical activity measures. RESULTS: A total of 214 participants—110 intervention and 104 control—completed the 12-week intervention period. A total of 10 participants out of 250 (4.0%)—10 intervention and 0 control—dropped out, and 26 participants (10.4%)—5 intervention and 21 control—did not complete postintervention online surveys. Adherence to coaching calls and delivery of text messages was over 90%. At 12 weeks, the intervention group were 2.2 kg (95% CI 0.8-3.6) lighter than controls (P=.005). Intervention participants consumed more vegetables (P=.009), fewer sugary soft drinks (P=.002), and fewer energy-dense takeout meals (P=.001) compared to controls. They also increased their total physical activity by 252.5 MET-minutes (95% CI 1.2-503.8, P=.05) and total physical activity by 1.3 days (95% CI 0.5-2.2, P=.003) compared to controls. CONCLUSIONS: The TXT2BFiT low-intensity intervention was successful in preventing weight gain with modest weight loss and improvement in lifestyle behaviors among overweight young adults. The short-term success of the 12-week intervention period shows potential. Maintenance of the behavior change will be monitored at 9 months. TRIAL REGISTRATION: Trial Registration: The Australian New Zealand Clinical Trials Registry ACTRN12612000924853; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12612000924853 (Archived by WebCite at http://www.webcitation.org/6Z6w9LlS9)

The use of Control Charts by Laypeople and Hospital Decision-Makers for Guiding Decision Making

Graphs presenting healthcare data are increasingly available to support laypeople and hospital staff's decision making. When making these decisions, hospital staff should consider the role of chance—that is, random variation. Given random variation, decision-makers must distinguish signals (sometimes called special-cause data) from noise (common-cause data). Unfortunately, many graphs do not facilitate the statistical reasoning necessary to make such distinctions. Control charts are a less commonly used type of graph that support statistical thinking by including reference lines that separate data more likely to be signals from those more likely to be noise. The current work demonstrates for whom (laypeople and hospital staff) and when (treatment and investigative decisions) control charts strengthen data-driven decision making. We present two experiments that compare people's use of control and non-control charts to make decisions between hospitals (funnel charts vs. league tables) and to monitor changes across time (run charts with control lines vs. run charts without control lines). As expected, participants more accurately identified the outlying data using a control chart than using a non-control chart, but their ability to then apply that information to more complicated questions (e.g., where should I go for treatment?, and should I investigate?) was limited. The discussion highlights some common concerns about using control charts in hospital settings

Hyponatremia: a new predictor of mortality in patients with Shiga toxin-producing Escherichia coli hemolytic uremic syndrome

(1) Evaluate mortality rate in patients with Shiga toxin-producing Escherichia coli hemolytic uremic syndrome, (2) determine the leading causes of death, and (3) identify predictors of mortality at hospital admission. We conducted a multicentric, observational, retrospective, cross-sectional study. It included patients under 18 years old with Shiga toxin-producing Escherichia coli hemolytic uremic syndrome hospitalized between January 2005 and June 2016. Clinical and laboratory data were obtained from the Argentine National Epidemiological Surveillance System of Hemolytic Uremic Syndrome. Clinical and laboratory variables were compared between deceased and non-deceased patients. Univariate and multivariate analyses were performed. ROC curves and area under the curve were obtained. Seventeen (3.65%) out of the 466 patients died, being central nervous system involvement the main cause of death. Predictors of death were central nervous system involvement, the number of days since the beginning of diarrhea to hospitalization, hyponatremia, high hemoglobin, high leukocyte counts, and low bicarbonate concentration on admission. In the multivariate analysis, central nervous system involvement, sodium concentration, and hemoglobin were independent predictors. The best cut off for sodium was ≤ 128 meq/l and for hemoglobin ≥ 10.8 g/dl. Mortality was low in children with Shiga toxin-producing Escherichia coli hemolytic uremic syndrome, being central nervous system involvement the main cause of death. The best mortality predictors found were central nervous system involvement, hemoglobin, and sodium concentration. Hyponatremia may be a new Shiga toxin-producing Escherichia coli hemolytic uremic syndrome mortality predictor.Facultad de Ciencias Veterinaria