Evaluating Active U: an Internet-mediated physical activity program.

Background: Engaging in regular physical activity can be challenging, particularly during the winter months. To promote physical activity at the University of Michigan during the winter months, an eight-week Internet-mediated program (Active U) was developed providing participants with an online physical activity log, goal setting, motivational emails, and optional team participation and competition. Methods: This study is a program evaluation of Active U. Approximately 47,000 faculty, staff, and graduate students were invited to participate in the online Active U intervention in the winter of 2007. Participants were assigned a physical activity goal and were asked to record each physical activity episode into the activity log for eight weeks. Statistics for program reach, effectiveness, adoption, and implementation were calculated using the Re-Aim framework. Multilevel regression analyses were used to assess the decline in rates of data entry and goal attainment during the program, to assess the likelihood of joining a team by demographic characteristics, to test the association between various predictors and the number of weeks an individual met his or her goal, and to analyze server load. Results: Overall, 7,483 individuals registered with the Active U website (≈16% of eligible), and 79% participated in the program by logging valid data at least once. Staff members, older participants, and those with a BMI < 25 were more likely to meet their weekly physical activity goals, and average rate of meeting goals was higher among participants who joined a competitive team compared to those who participated individually (IRR = 1.28, P < .001). Conclusion: Internet-mediated physical activity interventions that focus on physical activity logging and goal setting while incorporating team competition may help a significant percentage of the target population maintain their physical activity during the winter months

Preventing type 2 diabetes mellitus in Qatar by reducing obesity, smoking, and physical inactivity: mathematical modeling analyses.

BACKGROUND: The aim of this study was to estimate the impact of reducing the prevalence of obesity, smoking, and physical inactivity, and introducing physical activity as an explicit intervention, on the burden of type 2 diabetes mellitus (T2DM), using Qatar as an example. METHODS: A population-level mathematical model was adapted and expanded. The model was stratified by sex, age group, risk factor status, T2DM status, and intervention status, and parameterized by nationally representative data. Modeled interventions were introduced in 2016, reached targeted level by 2031, and then maintained up to 2050. Diverse intervention scenarios were assessed and compared with a counter-factual no intervention baseline scenario. RESULTS: T2DM prevalence increased from 16.7% in 2016 to 24.0% in 2050 in the baseline scenario. By 2050, through halting the rise or reducing obesity prevalence by 10-50%, T2DM prevalence was reduced by 7.8-33.7%, incidence by 8.4-38.9%, and related deaths by 2.1-13.2%. For smoking, through halting the rise or reducing smoking prevalence by 10-50%, T2DM prevalence was reduced by 0.5-2.8%, incidence by 0.5-3.2%, and related deaths by 0.1-0.7%. For physical inactivity, through halting the rise or reducing physical inactivity prevalence by 10-50%, T2DM prevalence was reduced by 0.5-6.9%, incidence by 0.5-7.9%, and related deaths by 0.2-2.8%. Introduction of physical activity with varying intensity at 25% coverage reduced T2DM prevalence by 3.3-9.2%, incidence by 4.2-11.5%, and related deaths by 1.9-5.2%. CONCLUSIONS: Major reductions in T2DM incidence could be accomplished by reducing obesity, while modest reductions could be accomplished by reducing smoking and physical inactivity, or by introducing physical activity as an intervention

Application of the speed-duration relationship to normalize the intensity of high-intensity interval training

The tolerable duration of continuous high-intensity exercise is determined by the hyperbolic Speed-tolerable duration (S-tLIM) relationship. However, application of the S-tLIM relationship to normalize the intensity of High-Intensity Interval Training (HIIT) has yet to be considered, with this the aim of present study. Subjects completed a ramp-incremental test, and series of 4 constant-speed tests to determine the S-tLIM relationship. A sub-group of subjects (n = 8) then repeated 4 min bouts of exercise at the speeds predicted to induce intolerance at 4 min (WR4), 6 min (WR6) and 8 min (WR8), interspersed with bouts of 4 min recovery, to the point of exercise intolerance (fixed WR HIIT) on different days, with the aim of establishing the work rate that could be sustained for 960 s (i.e. 4×4 min). A sub-group of subjects (n = 6) also completed 4 bouts of exercise interspersed with 4 min recovery, with each bout continued to the point of exercise intolerance (maximal HIIT) to determine the appropriate protocol for maximizing the amount of high-intensity work that can be completed during 4×4 min HIIT. For fixed WR HIIT tLIM of HIIT sessions was 399±81 s for WR4, 892±181 s for WR6 and 1517±346 s for WR8, with total exercise durations all significantly different from each other (P&#60;0.050). For maximal HIIT, there was no difference in tLIM of each of the 4 bouts (Bout 1: 229±27 s; Bout 2: 262±37 s; Bout 3: 235±49 s; Bout 4: 235±53 s; P&#62;0.050). However, there was significantly less high-intensity work completed during bouts 2 (153.5±40. 9 m), 3 (136.9±38.9 m), and 4 (136.7±39.3 m), compared with bout 1 (264.9±58.7 m; P&#62;0.050). These data establish that WR6 provides the appropriate work rate to normalize the intensity of HIIT between subjects. Maximal HIIT provides a protocol which allows the relative contribution of the work rate profile to physiological adaptations to be considered during alternative intensity-matched HIIT protocols

Determinants of physical activity participation following traumatic brain injury

Aims The objective of the study described in this article was to establish the environmental, social, or personal determinants associated with physical activity participation in people with traumatic brain injury (TBI). Methods A multi-centre cross-sectional questionnaire survey using a convenience sample was used at eight community day centres for brain injured populations. The participants were 63 individuals with traumatic brain injury (51 male, 12 female). Physical activity participation was based on the proportion of participants achieving the level of physical activity recommended for health (30 mins moderate activity, most days of the week). Standardized measures were used to assess activities of daily living (Extended Activities of Daily Living Scale), self-efficacy (Self-Efficacy for Exercise Scale), social support (Social Support for Exercise Scale) and mood (General Health Questionnaire-12). Findings Over half the participants were not active enough for health benefit. Active participants were more independent in activities of daily living (t = -2.21, P < 0.05), had greater self-efficacy for exercise (t = -3.02, P < 0.05) and were more educated (χ2=5.61, P<0.05) than inactive participants. Logistic Regression showed self-efficacy for exercise to be the only significant predictor of physical activity participation (β = 0.32, OR 1.03, P < 0.05). Conclusions Self-efficacy predicted physical activity participation. Efforts to increase self-efficacy among brain injured participants may encourage activity participation in those who are able and this warrants further investigation

Statistical power considerations in genotype-based recall randomized controlled trials

Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for genemetformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design

The prevention of type 2 diabetes

Type 2 diabetes mellitus (T2DM) affects more than 7% of adults in the US and leads to substantial personal and economic burden. In prediabetic states insulin secretion and action—potential targets of preventive interventions—are impaired. In trials lifestyle modification (i.e. weight loss and exercise) has proven effective in preventing incident T2DM in high-risk groups, although weight loss has the greatest effect. Various medications (e.g. metformin, thiazolidinediones and acarbose) can also prevent or delay T2DM. Whether diabetes-prevention strategies also ultimately prevent the development of diabetic vascular complications is unknown, but cardiovascular risk factors are favorably affected. Preventive strategies that can be implemented in routine clinical settings have been developed and evaluated. Widespread application has, however, been limited by local financial considerations, even though cost-effectiveness might be achieved at the population level

Gestational weight gain and group prenatal care: A systematic review and meta-analysis

Abstract Background Group visits for chronic medical conditions in non-pregnant populations have demonstrated successful outcomes including greater weight loss compared to individual visits for weight management. It is plausible that group prenatal care can similarly assist women in meeting gestational weight gain goals. The purpose of this study was to evaluate the effect of group vs. traditional prenatal care on gestational weight gain. Methods A keyword search of Medline, Embase, Scopus, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Cochrane Central Register of Controlled Trials, clinicaltrials.gov, and Google Scholar was performed up to April 2017. Studies were included if they compared gestational weight gain in a group prenatal care setting to traditional prenatal care in either randomized controlled trials, cohort, or case-control studies. The primary and secondary outcomes were excessive and adequate gestational weight gain according to the Institute of Medicine guidelines. Heterogeneity was assessed with the Q test and I2 statistic. Pooled relative risks (RRs) and confidence intervals (CI) were reported with random-effects models from the randomized controlled trials (RCT) and cohort studies. Results One RCT, one secondary analysis of an RCT, one study with “random assignment”, and twelve cohort studies met the inclusion criteria for a total of 13,779 subjects. Thirteen studies used the CenteringPregnancy model, defined by 10 sessions that emphasize goal setting and self-monitoring. Studies targeted specific populations such as adolescents, African-Americans, Hispanics, active-duty military or their spouses, and women with obesity or gestational diabetes. There were no significant differences in excessive [7 studies: pooled rates 47% (1806/3582) vs. 43% (3839/8521), RR 1.09, 95% CI 0.97–1.23] or adequate gestational weight gain [6 studies: pooled rates 31% (798/2875) vs. 30% (1410/5187), RR 0.92, 95% CI 0.79–1.08] in group and traditional prenatal care among the nine studies that reported categorical gestational weight gain outcomes in the meta-analysis. Conclusions Group prenatal care was not associated with excessive or adequate gestational weight gain in the meta-analysis. Since outcomes were overall inconsistent, we propose that prenatal care models (e.g., group vs. traditional) should be evaluated in a more rigorous fashion with respect to gestational weight gain

The ARIC predictive model reliably predicted risk of type II diabetes in Asian populations

10.1186/1471-2288-12-48BMC Medical Research Methodology12

Enhanced physical health screening for people with severe mental illness in Hong Kong: results from a one-year prospective case series study

Background People with severe mental illness have significantly poorer physical health compared to the general population; previous health screening studies conducted outside Asian countries have demonstrated the potential in addressing this issue. This case series aimed to explore the effects and utility of integrating an enhanced physical health screening programme for community dwelling patients with severe mental illness into routine clinical practice in Hong Kong. Method This study utilises a consecutive prospective case series design. The serious mental illness Health Improvement Profile (HIP) was used as a screening tool at baseline and repeated at 12 months follow-up. Results A total of 148 community-based patients with severe mental illness completed the study. At one year follow-up analysis showed a significant improvement in self-reported levels of exercise and a reduction in the numbers of patients prescribed medications for diabetes However, mean waist circumference increased at follow-up. In addition to the statistically significant results some general trends were observed, including: a lack of deterioration in most areas of cardiovascular risk; a reduction in medicines prescribed for physical health problems; and general improvements in health behaviours over the 12 month period. Conclusions The findings demonstrate that using the HIP is feasible and acceptable in Hong Kong. The results of the enhanced physical health-screening programme are promising, but require further testing using a randomised controlled trial design in order to more confidently attribute the improvements in well-being and health behaviours to the HIP. Trial registration Clinical trial registration number: ISRCTN1258247

Discordance in glycemic categories and regression to normality at baseline in 10,000 people in a Type 2 diabetes prevention trial

The world diabetes population quadrupled between 1980 and 2014 to 422 million and the enormous impact of Type 2 diabetes is recognised by the recent creation of national Type 2 diabetes prevention programmes. There is uncertainty about how to correctly risk stratify people for entry into prevention programmes, how combinations of multiple ‘at high risk’ glycemic categories predict outcome, and how the large recently defined ‘at risk’ population based on an elevated glycosylated haemoglobin (HbA1c) should be managed. We identified all 141,973 people at highest risk of diabetes in our population, and screened 10,000 of these with paired fasting plasma glucose and HbA1c for randomisation into a very large Type 2 diabetes prevention trial. Baseline discordance rate between highest risk categories was 45.6 %, and 21.3 - 37.0 % of highest risk glycaemic categories regressed to normality between paired baseline measurements (median 40 days apart). Accurate risk stratification using both fasting plasma glucose and HbA1c data, the use of paired baseline data, and awareness of diagnostic imprecision at diagnostic thresholds would avoid substantial overestimation of the true risk of Type 2 diabetes and the potential benefits (or otherwise) of intervention, in high risk subjects entering prevention trials and programmes