scholarly journals Defining Valid Activity Monitor Data: A Multimethod Analysis of Weight-Loss Intervention Participants’ Barriers to Wear and First 100 Days of Physical Activity

Informatics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 39
Author(s):  
Stephanie L. Orstad ◽  
Lauren Gerchow ◽  
Nikhil R. Patel ◽  
Meghana Reddy ◽  
Christina Hernandez ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Low Income ◽  
Activity Monitor ◽  
Accelerometer Data ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Behavioral Weight Loss Intervention ◽  
Monitor Data

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.

The Impact of Self-monitoring of Blood Glucose on a Behavioral Weight Loss Intervention for Patients With Type 2 Diabetes

2012 ◽  
Vol 39 (3) ◽  
pp. 397-405 ◽  
Author(s):  
Lisa M. McAndrew ◽  
Melissa A. Napolitano ◽  
Leonard M. Pogach ◽  
Karen S. Quigley ◽  
Kerri Leh Shantz ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Weight Loss ◽  
Blood Glucose ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Self Monitoring ◽  
Behavioral Weight Loss Intervention ◽  
The Impact

scholarly journals Translation of a behavioral weight loss intervention for mid-life, low-income women in local health departments

Obesity ◽  
2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
Carmen D. Samuel-Hodge ◽  
Beverly A. Garcia ◽  
Larry F. Johnston ◽  
Ziya Gizlice ◽  
Andy Ni ◽  
...  
Keyword(s):  
Weight Loss ◽  
Low Income ◽  
Local Health ◽  
Weight Loss Intervention ◽  
Health Departments ◽  
Local Health Departments ◽  
Behavioral Weight Loss ◽  
Behavioral Weight Loss Intervention ◽  
Low Income Women

Abstract P338: Adults With Obstructive Sleep Apnea Have Lower Adherence to Weight Loss Behaviors in a Behavioral Weight Loss Intervention

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Christopher E Kline ◽  
Lora E Burke ◽  
Yaguang Zheng ◽  
Susan M Sereika ◽  
Christopher C Imes ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Caloric Intake ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Obstructive Sleep ◽  
Behavioral Weight Loss Intervention ◽  
Lower Adherence

Introduction: Obesity is a primary risk factor for obstructive sleep apnea (OSA), and weight loss is a common recommendation for adults with OSA. However, we previously found that adults with OSA lost less weight than those without OSA during a 12-month behavioral weight loss intervention. The potential mechanisms underlying the blunted weight loss among those with OSA are currently unclear; however, one potential explanation may be lower adherence to the intervention and its prescribed behaviors. Purpose: These analyses examined whether measures of adherence to a behavioral weight loss intervention differed between adults with and without OSA. Methods: The sample was comprised of adults who were overweight or obese (N=114; 50.4±10.5 y, body mass index [BMI]: 34.0±4.6 kg/m 2 ; 90.4% female, 82.5% white) who participated in a 12-mo behavioral weight loss intervention study. Participants wore a home sleep testing device (ResMed ApneaLink Plus) for one night at baseline (BL), 6 mo (6M), and 12 mo (12M). Those with an apnea-hypopnea index ≥ 5 were categorized as having OSA. Adherence to the intervention was assessed by: 1) attendance at group intervention sessions over 12 mo; 2) frequency of meeting daily caloric intake goals over 12 mo; 3) objectively-measured changes from BL in physical activity (steps/day, sedentary time, moderate-vigorous physical activity [MVPA]). Linear mixed models estimated the impact of OSA on these measures of intervention adherence following adjustment for sex, age, race, marital status, smoking status, and baseline BMI, while considering participant to be a random effect. Results: About half (52%) of the participants had OSA at BL, while 41 % had OSA at 6M. Attendance at group sessions did not differ between those with and without OSA over 12 mo (74.5 vs. 75.7%; P=.72). However, adults with OSA met their caloric intake goal less frequently than those without OSA (25.2 vs. 34.8%; P=.006), and adults with OSA increased their steps/day (+378.3 vs. 1060.1; P=.047) and MVPA min/day (+2.1 vs. +6.4; P=.056) less than those without OSA. Reductions in sedentary behavior (min/day) did not differ between those with and without OSA (-7.1 vs. -9.1; P=.81). Conclusions: These data suggest that the blunted weight loss observed among adults with OSA may be at least partially attributable to lower levels of adherence to prescribed goals for caloric intake and physical activity. Additional strategies (e.g., OSA screening and treatment referral, supplemental sessions on diet and MVPA) may be needed to achieve improved adherence to the lifestyle behaviors that lead to weight loss among adults with OSA.

12 Month Behavioral Weight Loss Intervention With Varying Doses Of Physical Activity

2016 ◽  
Vol 48 ◽  
pp. 155
Author(s):  
Renee J. Rogers ◽  
Erik B. Schelbert ◽  
Bethany Barone Gibbs ◽  
Meghan R. McGuire ◽  
Seth A. Creasy ◽  
...  
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Behavioral Weight Loss Intervention

scholarly journals Changes in Dietary Intake with Varying Doses of Physical Activity Within a Weight Loss Intervention: The Heart Health Study

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1759-1759
Author(s):  
Carli Liguori ◽  
Renee Rogers ◽  
John Jakicic
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Dietary Intake ◽  
Health Study ◽  
High Dose ◽  
Fat Intake ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Behavioral Weight Loss Intervention ◽  
Successful Weight Loss

Abstract Objectives Successful weight loss interventions often require a multipronged approach. The need for interventions that incorporate both physical activity and dietary methodologies is apparent. The present study aimed to assess whether there were differential effects on dietary change within the context of a behavioral weight loss intervention that included different doses of physical activity. Methods Participants (N = 383; Age = 44.7 ± 8.2 years, BMI = 32.4 ± 3.8 kg/m2) were randomized to a reduced calorie diet (DIET, N = 127), diet plus a moderate dose of physical activity (MOD-EX, N = 129), or diet plus a high dose of physical activity (HIGH-EX, N = 127). All groups received weekly in-person intervention sessions for months 1–6, with combined in-person and telephonic sessions for months 7–12. Diet was prescribed at 1200–1800 kcal/day. MOD-EX was prescribed physical activity that progressed to 150 min/wk and HIGH-EX progressed to 250 min/wk. Physical activity, weight, and dietary intake were assessed. Dietary intake was assessed using the DHQII questionnaire. Results Retention at 12 months was 86.6% in DIET, 80.6% in MOD-EX, and 83.5% in HIGH-EX. Physical activity at 0 and 12 months was 65.4 ± 73.8 and 88.2 ± 104.3 min/wk in DIET; 68.7 ± 93.8 and 179.1 ± 125.3 min/wk in MOD-EX; and 71.5 ± 84.4 and 228.8 ± 148.3 min/wk in HIGH-EX (Group X Time P < 0.001). Weight decreased at 12 months (DIET: −9.9 ± 8.3 kg, MOD-EX: −10.8 ± 8.2 kg, HIGH-EX: −9.5 ± 7.3 kg) (P < 0.001), with no difference between groups. Energy intake decreased from baseline in all groups (6 mo: −495 ± 25.8 kcal/day, 12 mo: −502 ± 25.0 kcal/day) (P < 0.001). Percent dietary fat intake decreased (6 mo: −5.0 ± 0.4%, 12 mo: −3.8 ± 0.4%) (P < 0.001), whereas there was a non-significant increase in % carbohydrate intake (6 mo: 3.5 ± 0.4%, 12 mo: 3.0 ± 0.5%) and % protein intake (6 mo: 1.3 ± 0.2%, 12 mo: 1.0 ± 0.2%), with no difference between groups. Conclusions Weight loss was observed in all the interventions and physical activity did not enhance the weight loss that was observed. Also, the changes in diet that included reducing calories and fat intake were not impacted by the addition of physical activity. These findings have implications for interventions for weight loss in adults with obesity. Funding Sources National Institutes of Health.

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 ◽  
...  
Keyword(s):  
Weight Loss ◽  
Cost Effectiveness ◽  
Low Income ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Behavioral Weight Loss Intervention ◽  
Low Income Women
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