Okan U. Elci

The Effect of Electronic Self-Monitoring on Weight Loss and Dietary Intake: A Randomized Behavioral Weight Loss Trial

Technology may improve self‐monitoring adherence and dietary changes in weight loss treatment. Our study aimed to investigate whether using a personal digital assistant (PDA) with dietary and exercise software, with and without a feedback message, compared to using a paper diary/record (PR), results in greater weight loss and improved self‐monitoring adherence. Healthy adults (N = 210) with a mean BMI of 34.01 kg/m2 were randomized to one of three self‐monitoring approaches: PR (n = 72), PDA with self‐monitoring software (n = 68), or PDA with self‐monitoring software and daily feedback messages (PDA+FB, n = 70). All participants received standard behavioral treatment. Self‐monitoring adherence and change in body weight, waist circumference, and diet were assessed at 6 months; retention was 91%. All participants had a significant weight loss (P < 0.01) but weight loss did not differ among groups. A higher proportion of PDA+FB participants (63%) achieved ≥5% weight loss in comparison to the PR group (46%) (P < 0.05) and PDA group (49%) (P = 0.09). Median percent self‐monitoring adherence over the 6 months was higher in the PDA groups (PDA 80%; PDA+FB 90%) than in the PR group (55%) (P < 0.01). Waist circumference decreased more in the PDA groups than the PR group (P = 0.02). Similarly, the PDA groups reduced energy and saturated fat intake more than the PR group (P < 0.05). Self‐monitoring adherence was greater in the PDA groups with the greatest weight change observed in the PDA+FB group.

SMART trial: A randomized clinical trial of self-monitoring in behavioral weight management-design and baseline findings

BACKGROUNDnThe primary form of treatment for obesity today is behavioral therapy. Self-monitoring diet and physical activity plays an important role in interventions targeting behavior and weight change. The SMART weight loss trial examined the impact of replacing the standard paper record used for self-monitoring with a personal digital assistant (PDA). This paper describes the design, methods, intervention, and baseline sample characteristics of the SMART trial.nnnMETHODSnThe SMART trial used a 3-group design to determine the effects of different modes of self-monitoring on short- and long-term weight loss and on adherence to self-monitoring in a 24-month intervention. Participants were randomized to one of three conditions (1) use of a standard paper record (PR); (2) use of a PDA with dietary and physical activity software (PDA); or (3), use of a PDA with the same software plus a customized feedback program (PDA + FB).nnnRESULTSnWe screened 704 individuals and randomized 210. There were statistically but not clinically significant differences among the three cohorts in age, education, HDL cholesterol, blood glucose and systolic blood pressure. At 24 months, retention rate for the first of three cohorts was 90%.nnnCONCLUSIONSnTo the best of our knowledge, the SMART trial is the first large study to compare different methods of self-monitoring in a behavioral weight loss intervention and to compare the use of PDAs to conventional paper records. This study has the potential to reveal significant details about self-monitoring patterns and whether technology can improve adherence to this vital intervention component.

Adherence to a behavioral weight loss treatment program enhances weight loss and improvements in biomarkers

Objectives: To describe participants’ adherence to multiple components (attendance, energy intake, fat gram, exercise goals, and self-monitoring eating and exercise behaviors) of a standard behavioral treatment program (SBT) for weight loss and how adherence to these components may influence weight loss and biomarkers (triglycerides, low density lipoproteins [LDL], high density lipoprotein, and insulin) during the intensive and less-intensive intervention phases. Methods: A secondary analysis of a randomized clinical trial consisting of a SBT with either fat-restricted standard or lacto-ovo vegetarian diet. The 12-month intervention was delivered in 33 group sessions. The first six months reflected the intensive phase; the second six months, the less-intensive intervention phase. We conducted the analysis without regard to treatment assignment. Eligible participants included overweight/obese adults (N = 176; mean body mass index = 34.0 kg/m2). The sample was 86.9% female, 70.5% White, and 44.4 ± 8.6 years old. The outcome measures included weight and biomarkers. Results: There was a significant decline in adherence to each treatment component over time (P < 0.0001). In the first six months, adherence to attendance, self-monitoring and the energy goal were significantly associated with greater weight loss (P < 0.05). Adherence to attendance and exercise remained significantly associated with weight loss in the second six months (P < 0.05). Adherence to attendance, self-monitoring and exercise had indirect effects through weight loss on LDL, triglycerides, and insulin (P < 0.05). Conclusions: We observed a decline in adherence to each treatment component as the intervention intensity was reduced. Adherence to multiple treatment components was associated with greater weight loss and improvements in biomarkers. Future research needs to focus on improving and maintaining adherence to all components of the treatment protocol to promote weight loss and maintenance.

Locally Advanced Squamous Cell Carcinoma of the Head and Neck: CT Texture and Histogram Analysis Allow Independent Prediction of Overall Survival in Patients Treated with Induction Chemotherapy

PURPOSEnTo determine if computed tomographic (CT) texture and histogram analysis measurements of the primary mass are independently associated with overall survival in patients with locally advanced squamous cell carcinoma of the head and neck who were previously treated with cisplatin, 5-fluorouracil, and docetaxel (TPF) induction chemotherapy.nnnMATERIALS AND METHODSnThis institutional review board-approved retrospective study included 72 patients with locally advanced squamous cell carcinoma of the head and neck who were treated with induction TPF chemotherapy in 2004-2010. CT texture and histogram analysis of the primary mass on the pretherapy CT images were performed by using TexRAD software before and after application of spatial filters at different anatomic scales ranging from fine detail to coarse features. Cox proportional hazards models were used to examine the association between overall survival and the baseline CT imaging measurements and clinical variables.nnnRESULTSnPrimary mass entropy and skewness measurements with multiple spatial filters were associated with overall survival. Multivariate Cox regression analysis incorporating clinical and imaging variables indicated that primary mass size (hazard ratio [HR], 1.58 for each 1-cm increase; P = .018), N stage (HR, 8.77 for N3 vs N0 or N1; P = .002; HR, 4.99 for N3 vs N2; P = .001), and primary mass entropy (HR, 2.10 for each 0.5-unit increase; P = .036) and skewness (HR, 3.67 for each 1.0-unit increase; P = .009) measurements with the 1.0 spatial filter were independently associated with overall survival.nnnCONCLUSIONnIndependent of tumor size, N stage, and other clinical variables, primary mass CT texture and histogram analysis parameters are associated with overall survival in patients with locally advanced squamous cell carcinoma of the head and neck who were treated with induction TPF. Online supplemental material is available for this article.

Physical Activity Self-Monitoring and Weight Loss: 6-Month Results of the SMART Trial

INTRODUCTIONnWeight loss has been associated with higher physical activity (PA) levels and frequent dietary self-monitoring. Less is known about how PA self-monitoring affects adherence to PA goals, PA levels, and weight change.nnnMETHODSnThe SMART Trial is a clinical weight loss trial in which 210 overweight adults were randomized equally to one of three arms: 1) paper record (PR), 2) personal digital assistant with self-monitoring software (PDA), and 3) PDA with daily tailored feedback message (PDA + FB). PA self-monitoring and adherence to PA goals were based on entries in weekly submitted diaries. PA levels were measured via self-report by the past 6-month Modifiable Activity Questionnaire at baseline and 6 months.nnnRESULTSnData are presented on 189 participants with complete 6-month PA data (84% female, 77% white, mean age = 47.3 ± 8.8 yr, mean body mass index = 34.1 ± 4.5 kg·m(-2)). Median PA level was 7.96 MET·h·wk(-1) at baseline and 13.4 MET·h·wk(-1) at 6 months, with significant PA increases in all three arms. PDA + FB arm had a higher mean number of weekly self-monitoring entries than the PR arm (3.4 vs 2.4, P = 0.003) and were more likely to maintain high (i.e., 100%) adherence to PA goals over time than the PDA (P = 0.02) or PR arms (P = 0.0003). Both PA self-monitoring and adherence to PA goals were related to higher PA levels at 6 months. A higher mean rate of PA self-monitoring was associated with a greater percentage of weight decrease (ρ = -0.49, P < 0.0001) at 6 months.nnnCONCLUSIONSnPA self-monitoring and adherence to PA goals were more likely in participants in the PDA + FB arm and in turn predicted higher PA levels and weight loss.

Self-Monitoring as a Mediator of Weight Loss in the SMART Randomized Clinical Trial

BackgroundIntegral components of behavioral weight-loss treatment include self-monitoring of diet and physical activity along with feedback to participants regarding their behaviors. While providing feedback has been associated with weight loss, no studies have examined the impact of feedback frequency on weight loss or the mediating role of self-monitoring adherence in this relationship.PurposeThis study examined the effect of participant feedback frequency on weight loss and determined if this effect was mediated by adherence to self-monitoring in a behavioral weight-loss trial conducted in the USA.MethodParticipants (Nu2009=u2009210) were randomly assigned to one of three self-monitoring methods with either no-daily feedback messages or daily feedback messages: (1) paper diary (PD), no-daily feedback; (2) personal digital assistant (PDA), no-daily feedback; and (3) PDA, daily tailored feedback messages (PDA + FB). The Sobel test via bootstrapping examined the direct effect of feedback frequency on weight loss and the indirect effect through self-monitoring adherence.ResultsReceiving daily feedback messages significantly increased participants self-monitoring adherence. A significant effect of feedback frequency on weight loss was noted; however, after adjusting for self-monitoring adherence, the effect of feedback frequency on weight loss was no longer significant. Feedback frequency had a significant indirect effect on weight loss through self-monitoring adherence.ConclusionSelf-monitoring adherence mediated the effect of feedback frequency on weight loss. Increasing the frequency with which participants receive feedback could enhance self-monitoring adherence, a critical component of behavioral weight-loss treatment.

The impact of self-reported psychological stress levels on changes to peripheral blood immune biomarkers in recreational marathon runners during training and recovery.

Objective: Marathon training is both physically and psychologically stressful, both of which can lead to altered immunity. The purpose of this study was to determine if the overall immunoregulatory changes associated with the physical stress of marathon training are affected by psychological stress. Methods: Nineteen recreational marathoners completed the Perceived Stress Scale (PSS), State-Trait Anxiety Inventory (STAI) and Penn State Worry Questionnaire (PSWQ), and had levels of T cell subpopulations and cytokine (IFNγ, IL4 and IL10) production determined 4 weeks before (baseline), 24-48 h before (prerace) and 1 week after (recovery) participation in a marathon. Results: PSS scores decreased at the prerace visit compared to baseline and remained low at recovery. Compared to baseline, there were significant changes to numerous immune measures at the prerace visit, including decreases in Th1/Th2 ratio, Tc1/Tc2 ratio, Tr1 and Th3 cell populations as well as decreases in IFNγ/IL4 cytokine ratio and IL10 production. Most immune parameters had returned to near baseline values at the recovery visit. Higher levels of perceived stress, anxiety and worry exacerbated many of the alterations in immunity that were observed at the prerace visit. Higher levels of perceived stress and worry had significant effects on changes to Treg, IL4 production and the IFNγ/IL4 cytokine ratio. Stress had an additional impact on changes in IL10 production. High anxiety levels resulted in significant changes to Treg, Tr1 and Th3. Conclusion: These data suggest that recreational marathon runners with higher levels of psychological stress may be more at risk for the immune alterations that are common during periods of prolonged physical training.

Variability in Laboratory Immune Parameters Is Associated with Stress Hormone Receptor Polymorphisms

Objectives: Interpretation of laboratory immune data in healthy human subjects is often challenging due to wide inter-subject variability. Since endocrine and immune mediators have been mutually interlinked, a potential explanation for the significant variability seen in immune data even when controlled for technical variability and demographics is differences in the binding affinity of ligand with hormone receptors on the surface of immune cells, which can be associated with single nucleotide polymorphisms (SNP). Methods: We categorized immunoregulatory cellular profiles from PBMC of 207 healthy volunteers according to glucocorticoid receptor (GR: Bcl1, TthIIII, and A3669G) and β2-adrenergic receptor (β2AR: Gly16Arg and Gln27Glu) polymorphisms. Subjects were genotyped for each SNP, and Th1, Th2, Th1/Th2 ratio, regulatory T cell (Treg), Tr1, and Th3 cell numbers were assessed. Immune parameters in the SNP groups were compared to the wild type (WT). Results: Significant differences were observed in Th2 and the Th1/Th2 ratio for the β2AR SNP Gly16Arg. Th1, the Th1/Th2 ratio, and Tr1 differed significantly by SNP of Gln27Glu. In addition, the effect of age on Th2 and the effect of the body mass index on the Th1/Th2 ratio significantly differed across subtypes of the Gly16Arg SNP. Significant differences based on allergic status and gender were also seen for Treg, Th1, and Th2 across Gly16Arg, Gln27Glu, and TthIIII SNP. Conclusions: These data suggest that SNP from various components of the stress-immune network may be useful for subgrouping of immune responses to more accurately categorize psychoneuroimmunological components of stress risk in individual subjects. This approach may have significant research and clinical potential.

Longitudinal relationship between physical activity and cardiometabolic factors in overweight and obese adults

Few studies have reported longitudinal relationships between physical activity (PA) and cardiometabolic risk factors over time using repeated assessments in overweight or obese adults. We conducted a longitudinal study in 127 participants (81% with body mass indexxa0>xa030xa0kg/m2) who completed a 12-month behavioral intervention for weight loss between 2003 and 2005 in Pittsburgh, PA, USA. Using absolute change scores from baseline to each time point (i.e., 6 and 12xa0months) for all studied variables (Δxa0=xa0time pointxa0−xa0baseline), we performed mixed effects modeling to examine relationships between PA and cardiometabolic risk factors, after adjusting for body weight, energy intake and other covariates (i.e., age, gender, and ethnicity). PA was assessed as energy expenditure (kcal/week) using the Paffenbarger activity questionnaire. Over the 12-month period, energy expenditure increased (Δ1,370xa0kcal/week at 6xa0months vs. Δ886xa0kcal/week at 12xa0months); body weight decreased (Δ8.9xa0kg at 6xa0months vs. Δ8.4xa0kg at 12xa0months). The average increase in energy expenditure over 12xa0months was significantly and independently related to reductions in total cholesterol (Fxa0=xa06.25, pxa0=xa00.013), low-density lipoprotein cholesterol (LDL-C) (Fxa0=xa05.08, pxa0=xa00.025) and fasting blood glucose (Fxa0=xa05.10, pxa0=xa00.025), but not to other risk factors (i.e., fasting insulin, high-density lipoprotein cholesterol, triglycerides, and waist circumference). In conclusion, among overweight and obese adults undergoing a weight loss intervention, increased energy expenditure over 12xa0months may improve total cholesterol and LDL-C, important coronary risk factors, and fasting blood glucose, a metabolic risk factor.

Associations between cytokine receptor polymorphisms and variability in laboratory immune parameters in normal humans

In every study involving human immune parameters, large inter-subject variability occurs which can make interpretation of results difficult. The aim of this study was to evaluate whether genetic variants in cytokine receptors could associate with variability in laboratory immune measures. A total of 207 normal volunteers were recruited in this study. Immunoregulatory profiles were measured by flow cytometry and genotyping assays were performed by allelic discrimination real-time PCR. Immunoregulatory profiles were categorized according to various single nucleotide polymorphisms (SNPs) of cytokine receptors including T-56C and G-611A of IFN-γ receptor 1 (IFNGR1); Q64R of IFNGR2; and Ile50Val, Q576R and S503P of IL4R. Results reveal that Th1 levels were significantly higher in the heterozygous of the IFNGR1 T-56C polymorphism (minor allele) compared to wild-type (WT, major allele) (p = 0.006). For the Q576R of IL4R, Th1/Th2 ratio was significantly lower for the homozygous SNP (Arg/Arg) compared to the WT (Gln/Gln) (p = 0.035). In addition, the significant interaction effects of demographic characteristics on SNP-immune parameter associations were reported as well. We conclude that cytokine receptor polymorphisms might associate with variability in laboratory immune measures. Approach of SNP analysis of cytokine receptors can be useful in categorizing baseline immune responses to more accurately evaluate clinical immune data.