Cost-effectiveness of a behavioral weight loss intervention for low-income women: The Weight-Wise Program

2009 ◽  
Vol 49 (5) ◽  
pp. 390-395 ◽  
Author(s):  
Alison Gustafson ◽  
Olga Khavjou ◽  
Sally C. Stearns ◽  
Thomas C. Keyserling ◽  
Ziya Gizlice ◽  
...  
Obesity ◽  
2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
Carmen D. Samuel-Hodge ◽  
Beverly A. Garcia ◽  
Larry F. Johnston ◽  
Ziya Gizlice ◽  
Andy Ni ◽  
...  

Obesity ◽  
2009 ◽  
Vol 17 (10) ◽  
pp. 1891-1899 ◽  
Author(s):  
Carmen D. Samuel-Hodge ◽  
Larry F. Johnston ◽  
Ziya Gizlice ◽  
Beverly A. Garcia ◽  
Sara C. Lindsley ◽  
...  

2018 ◽  
Vol 2 (2) ◽  
pp. e18 ◽  
Author(s):  
Valerie J Silfee ◽  
Andrea Lopez-Cepero ◽  
Stephenie C Lemon ◽  
Barbara Estabrook ◽  
Oanh Nguyen ◽  
...  

Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 39
Author(s):  
Stephanie L. Orstad ◽  
Lauren Gerchow ◽  
Nikhil R. Patel ◽  
Meghana Reddy ◽  
Christina Hernandez ◽  
...  

Despite the popularity of commercially available wearable activity monitors (WAMs), there is a paucity of consistent methodology for analyzing large amounts of accelerometer data from these devices. This multimethod study aimed to inform appropriate Fitbit wear thresholds for physical activity (PA) outcomes assessment in a sample of 616 low-income, majority Latina patients with obesity enrolled in a behavioral weight-loss intervention. Secondly, this study aimed to understand intervention participants’ barriers to Fitbit use. We applied a heart rate (HR) criterion (≥10 h/day) and a step count (SC) criterion (≥1000 steps/day) to 100 days of continuous activity monitor data. We examined the prevalence of valid wear and PA outcomes between analytic subgroups of participants who met the HR criterion, SC criterion, or both. We undertook qualitative analysis of research staff notes and participant interviews to explore barriers to valid Fitbit data collection. Overall, one in three participants did not meet the SC criterion for valid wear in Weeks 1 and 13; however, we found the SC criterion to be more inclusive of participants who did not use a smartphone than the HR criterion. Older age, higher body mass index (BMI), barriers to smartphone use, device storage issues, and negative emotional responses to WAM-based self-monitoring may predict higher proportions of invalid WAM data in weight-loss intervention research.


Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
John M Jakicic ◽  
Kelliann K Davis ◽  
Bethany Barone Gibbs ◽  
Diane Helsel ◽  
Wendy C King ◽  
...  

Introduction: Few studies have examined behavioral weight loss interventions with respect to change in cardiovascular disease risk factors in young adults (aged 18 to 35 years). Hypothesis: We tested the hypothesis that a 6 month behavioral weight loss intervention resulted in significant improvements in selective cardiovascular disease risk factors in young adults. Methods: Data are presented as median [25 th , 75 th percentiles]. 470 participants (age: 30.9 [27.8, 33.7] years); BMI: 31.2 [28.4, 34.3] kg/m 2 ) were enrolled in a 6 month behavioral weight loss intervention that included weekly group sessions and prescribed an energy restricted diet and moderate-to-vigorous physical activity. Assessments included weight using a standardized protocol, resting blood pressure, and fasting lipids, glucose, and insulin. Statistical significance of change was according to tests of symmetry or the Wilcoxon matched pairs signed ranks test. Results: The primary outcome (weight) was available for 424 of the 470 participants (90.2%). Weight significantly decreased (-7.8 kg [-12.2, -3.7]) (p<0.0001). Systolic (-4.0 mmHg [-8.5, 0.5] and diastolic blood pressure (-3.0 mmHg [-6.5, 1.0]) decreased (p<0.0001). Total cholesterol (-13 mg/dl [-28.0, 2.0]), LDL cholesterol (-9.5 mg/dl [-21.7, 2.0]), triglycerides (-8.5 mg/dl [-44.0, 9.0]), glucose (-4.0 mg/dl [-8.0, 1.0]), and insulin (-2.6 mIU/L [-5.9, 0.7]) decreased (p<0.0001, n=416). There was not a significant change in HDL cholesterol (p=0.72). Conclusions: In conclusion, after 6 months, weight loss was observed in young adults assigned to this behavioral intervention that focused on physical activity and diet modification. They tended to also have improved cardiovascular disease risk factors. This may demonstrate an approach to reducing cardiovascular disease risk in young adults. Supported by NIH (U01HL096770) and AHA (12BGIA9410032)


2012 ◽  
Vol 39 (3) ◽  
pp. 397-405 ◽  
Author(s):  
Lisa M. McAndrew ◽  
Melissa A. Napolitano ◽  
Leonard M. Pogach ◽  
Karen S. Quigley ◽  
Kerri Leh Shantz ◽  
...  

Obesity ◽  
2017 ◽  
Vol 26 (1) ◽  
pp. 81-87 ◽  
Author(s):  
Dale S. Bond ◽  
J. Graham Thomas ◽  
Richard B. Lipton ◽  
Julie Roth ◽  
Jelena M. Pavlovic ◽  
...  

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Laura P Svetkey ◽  
Stephen S Intille ◽  
Bryan C Batch ◽  
Leonor Corsino ◽  
Crystal C Tyson ◽  
...  

Background: Obesity affects young adults, leading to future morbidity and mortality. Early behavioral intervention may promote long-term weight control. Mobile technology-based (mHealth) interventions may be particularly effective in young adults. We compared both an mHealth behavioral weight loss intervention and a personal coaching weight loss intervention to no intervention (and to each other) in overweight/obese young adults. Methods: We randomized 365 generally healthy adults age 18-35 years with BMI > 25 kg/m2 (overweight or obese) to 24-months of intervention delivered primarily via investigator-designed cell phone (CP) or intervention delivered primarily via in-person (6 weekly) and by phone (23 monthly) coaching (PC), compared to usual care control group (Control). Primary outcome was weight change from baseline to 24 months. This study was conducted as part of the Early Adult Reduction of weight through LifestYle (EARLY) cooperative trials. Results: Randomized participants (N=365) had mean BMI 35 kg/m2, mean age 29yrs, were 70% women, 36% African American, 6% Latino. Final weight was obtained in 86%; missing weight was multiply imputed. At 24 months, weight loss was not different in either PC or CP vs Control (see Figure). Weight loss in PC was significantly greater than Control at 6 months. From baseline to 24 months, clinically significant weight loss (> 3% per national guidelines) occurred in 40% of PC, 34% of CP, and 30% of Control. Conclusions: mHealth alone may not be sufficient for weight loss in young adults but mHealth-enhanced contact with an interventionist has a modest short-term effect. Future interventions should maximize the complementarity of mHealth and personal contact to achieve larger and more sustained effect.


Sign in / Sign up

Export Citation Format

Share Document