Bidirectional Relationships Between Weight Change and Sleep Apnea in a Behavioral Weight Loss Intervention

Introduction: Sleep is consistently associated with obesity risk, but minimal research has examined its relationship with attempted weight loss. Most of the available evidence has focused on sleep duration, which fails to recognize the multidimensional nature of sleep. Purpose: To examine the relationship between a composite measure of sleep health and weight change in a sample of adults who participated in a 12-month behavioral weight loss intervention. Methods: 125 adults with overweight or obesity enrolled in the EMPOWER study (50.3±10.6 years, 91% female, 81% white) were included in analyses. All individuals participated in a 12-month behavioral weight loss intervention, with assessments at baseline, 6 months, and 12 months. Six dimensions of sleep were included in our operationalization of sleep health: regularity, satisfaction, alertness, timing, efficiency, and duration. Sleep dimensions were assessed using validated questionnaires and actigraphy, with values dichotomized into ‘good’ and ‘poor’ sleep. A composite sleep health score was calculated based upon the sum of the ‘good’ individual dimensions (range: 0-6), with higher scores indicating better sleep health. Obstructive sleep apnea (OSA) was assessed in a subset of participants (n=117) with a portable home sleep testing device, using the apnea-hypopnea index (AHI) as a marker of OSA severity. Linear mixed modeling was used to examine the relationship between sleep health and weight change during the subsequent 6-month interval with adjustment for age, gender, bed partner, and race. An additional model adjusted for AHI along with the previously noted covariates. Results: Mean sleep health was 4.5±1.1 at baseline and 4.5±1.2 at 6 months, and mean % weight change from 0 to 6 months and 6 to 12 months was -9.3±6.1% and 0.4±4.8%, respectively. In the adjusted model, greater sleep health was associated with greater weight loss (b=-0.77, SE=0.32; P=.02). Following additional adjustment for AHI, the relation between sleep health and weight loss was no longer significant (b=-0.53, SE=0.34; P=.12). Among individual sleep dimensions, only regularity and satisfaction showed trends to be associated with weight change (b=-1.28, SE=0.72 [P=.08] and b=-1.67, SE=0.86 [P=.06], respectively); however, these marginal associations were not retained after AHI adjustment (each P=.15). Conclusions: Better sleep health was associated with greater weight loss, but this association did not persist after accounting for OSA severity. Because OSA negatively impacts sleep health, future research should address whether improving sleep health, OSA, and/or the combination leads to better weight loss.

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Sociodemographic Characteristics Associated with Pretreatment Weight Change in a Behavioral Weight Loss Intervention

10.21203/rs.2.506/v1 ◽

2019 ◽

Author(s):

Margaret Fahey ◽

Robert C. Klesges ◽

Mehmet Kocak ◽

Gerald W. Talcott ◽

Rebecca A. Krukowski

Keyword(s):

Weight Loss ◽

Treatment Outcome ◽

Racial Differences ◽

Weight Change ◽

Sociodemographic Characteristics ◽

Weight Loss Intervention ◽

Behavioral Weight Loss ◽

Baseline Visit ◽

Intervention Protocol ◽

Behavioral Weight Loss Intervention

Abstract Background. Three previous studies found that participants commonly experienced significant weight change before beginning a behavioral weight loss intervention. However, these findings are conflicting in regard to how pretreatment weight change is associated with eventual treatment outcome. Further, these studies measured weight loss outcomes only up to six-months. Thus, the current study aims to examine pretreatment weight change among a diverse sample of active duty military personnel engaged in a behavioral weight loss intervention. Additionally, this study will investigate potential sociodemographic characteristics that influence the relationship between pretreatment change and treatment outcome up to 12-months, as well as how pretreatment weight change is related to intervention adherence. Methods. Using secondary analysis of data from a behavioral weight loss intervention, pretreatment (i.e., screening to baseline visit) weight categories [loss (> 1.15% decrease), stable, or gain (> 1.15% increase)] were compared to % weight change from both screening and baseline visits to four and 12-months. Results. During pretreatment, 59.4% remained weight stable, 24.4% lost and 16.1% gained; and racial differences in group classification were found. In regression models, pretreatment weight categories did not predict baseline to four or 12-month outcomes; however, interactions with age were observed (p = 0.038; p = 0.051, respectively). Weight change category predicted screening to 4-month outcome (p = .0005); specifically, those who lost pretreatment weight were more likely to lose weight from screening to 4-months compared to those who gained or remained weight stable. Pretreatment weight loss was related to consuming more meal replacements by four (p = .025) and 12-months (p = .012) but was not associated with adherence to other intervention protocol. Conclusions. Current results suggest that sociodemographic differences might influence pretreatment weight change and its relationship to 12-month treatment success. Given that many individuals (40.5%) in the current sample experienced significant weight change before the intervention, results extend previous findings suggesting that weight loss trials should account for both screening and baseline visit weights when examining treatment results. Trial Registration: NCT02063178. Registered February 14, 2014. https://clinicaltrials.gov/ct2/show/NCT02063178?term=dissemination+of+look+ahead&rank=1

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

Circulation ◽

10.1161/circ.137.suppl_1.p338 ◽

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.

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The association between sleep health and weight change during a 12-month behavioral weight loss intervention

International Journal of Obesity ◽

10.1038/s41366-020-00728-8 ◽

2021 ◽

Author(s):

Christopher E. Kline ◽

Eileen R. Chasens ◽

Zhadyra Bizhanova ◽

Susan M. Sereika ◽

Daniel J. Buysse ◽

...

Keyword(s):

Weight Loss ◽

Weight Change ◽

Weight Loss Intervention ◽

Behavioral Weight Loss ◽

Sleep Health ◽

Behavioral Weight Loss Intervention

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Sociodemographic Characteristics Associated with Pretreatment Weight Change in a U.S. Military Behavioral Weight Loss Intervention

Military Behavioral Health ◽

10.1080/21635781.2020.1750512 ◽

2020 ◽

Vol 8 (3) ◽

pp. 327-332

Author(s):

Margaret C. Fahey ◽

Robert C. Klesges ◽

Mehmet Kocak ◽

Gerald W. Talcott ◽

Rebecca A. Krukowski

Keyword(s):

Weight Loss ◽

Weight Change ◽

Sociodemographic Characteristics ◽

Weight Loss Intervention ◽

Behavioral Weight Loss ◽

Behavioral Weight Loss Intervention

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Abstract P249: A Behavioral Weight Loss Intervention is Effective for Change in CVD Risk Factors in Young Adults: The IDEA Study

Circulation ◽

10.1161/circ.131.suppl_1.p249 ◽

2015 ◽

Vol 131 (suppl_1) ◽

Author(s):

John M Jakicic ◽

Kelliann K Davis ◽

Bethany Barone Gibbs ◽

Diane Helsel ◽

Wendy C King ◽

...

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Weight Loss ◽

Young Adults ◽

Disease Risk ◽

Cardiovascular Disease Risk ◽

Cardiovascular Disease Risk Factors ◽

Weight Loss Intervention ◽

Behavioral Weight Loss ◽

Behavioral Weight Loss Intervention

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)

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