scholarly journals Understanding Time Series Patterns of Weight and Meal History Reports in Mobile Weight Loss Intervention Programs: Data-Driven Analysis

10.2196/17521 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e17521
Author(s):  
Junetae Kim ◽  
Hye Jin Kam ◽  
Youngin Kim ◽  
Yura Lee ◽  
Jae-Ho Lee
Keyword(s):  
Time Series ◽  
Weight Loss ◽  
Weight Reduction ◽  
Reduction Process ◽  
Weight Loss Intervention ◽  
Weight Loss Outcome ◽  
Weight Loss Outcomes ◽  
Reported Data ◽  
The Relationship ◽  
Over Time

Background Mobile apps for weight loss provide users with convenient features for recording lifestyle and health indicators; they have been widely used for weight loss recently. Previous studies in this field generally focused on the relationship between the cumulative nature of self-reported data and the results in weight loss at the end of the diet period. Therefore, we conducted an in-depth study to explore the relationships between adherence to self-reporting and weight loss outcomes during the weight reduction process. Objective We explored the relationship between adherence to self-reporting and weight loss outcomes during the time series weight reduction process with the following 3 research questions: “How does adherence to self-reporting of body weight and meal history change over time?”, “How do weight loss outcomes depend on weight changes over time?”, and “How does adherence to the weight loss intervention change over time by gender?” Methods We analyzed self-reported data collected weekly for 16 weeks (January 2017 to March 2018) from 684 Korean men and women who participated in a mobile weight loss intervention program provided by a mobile diet app called Noom. Analysis of variance (ANOVA) and chi-squared tests were employed to determine whether the baseline characteristics among the groups of weight loss results were different. Based on the ANOVA results and slope analysis of the trend indicating participant behavior along the time axis, we explored the relationship between adherence to self-reporting and weight loss results. Results Adherence to self-reporting levels decreased over time, as previous studies have found. BMI change patterns (ie, absolute BMI values and change in BMI values within a week) changed over time and were characterized in 3 time series periods. The relationships between the weight loss outcome and both meal history and self-reporting patterns were gender-dependent. There was no statistical association between adherence to self-reporting and weight loss outcomes in the male participants. Conclusions Although mobile technology has increased the convenience of self-reporting when dieting, it should be noted that technology itself is not the essence of weight loss. The in-depth understanding of the relationship between adherence to self-reporting and weight loss outcome found in this study may contribute to the development of better weight loss interventions in mobile environments.

scholarly journals Understanding Time Series Patterns of Weight and Meal History Reports in Mobile Weight Loss Intervention Programs: Data-Driven Analysis (Preprint)

2019 ◽  
Author(s):  
Junetae Kim ◽  
Hye Jin Kam ◽  
Youngin Kim ◽  
Yura Lee ◽  
Jae-Ho Lee
Keyword(s):  
Time Series ◽  
Weight Loss ◽  
Weight Reduction ◽  
Reduction Process ◽  
Weight Loss Intervention ◽  
Weight Loss Outcome ◽  
Weight Loss Outcomes ◽  
Reported Data ◽  
The Relationship ◽  
Over Time

BACKGROUND Mobile apps for weight loss provide users with convenient features for recording lifestyle and health indicators; they have been widely used for weight loss recently. Previous studies in this field generally focused on the relationship between the cumulative nature of self-reported data and the results in weight loss at the end of the diet period. Therefore, we conducted an in-depth study to explore the relationships between adherence to self-reporting and weight loss outcomes during the weight reduction process. OBJECTIVE We explored the relationship between adherence to self-reporting and weight loss outcomes during the time series weight reduction process with the following 3 research questions: “How does adherence to self-reporting of body weight and meal history change over time?”, “How do weight loss outcomes depend on weight changes over time?”, and “How does adherence to the weight loss intervention change over time by gender?” METHODS We analyzed self-reported data collected weekly for 16 weeks (January 2017 to March 2018) from 684 Korean men and women who participated in a mobile weight loss intervention program provided by a mobile diet app called Noom. Analysis of variance (ANOVA) and chi-squared tests were employed to determine whether the baseline characteristics among the groups of weight loss results were different. Based on the ANOVA results and slope analysis of the trend indicating participant behavior along the time axis, we explored the relationship between adherence to self-reporting and weight loss results. RESULTS Adherence to self-reporting levels decreased over time, as previous studies have found. BMI change patterns (ie, absolute BMI values and change in BMI values within a week) changed over time and were characterized in 3 time series periods. The relationships between the weight loss outcome and both meal history and self-reporting patterns were gender-dependent. There was no statistical association between adherence to self-reporting and weight loss outcomes in the male participants. CONCLUSIONS Although mobile technology has increased the convenience of self-reporting when dieting, it should be noted that technology itself is not the essence of weight loss. The in-depth understanding of the relationship between adherence to self-reporting and weight loss outcome found in this study may contribute to the development of better weight loss interventions in mobile environments.

scholarly journals Relationship Between Weekly Patterns of Caloric Intake and Reported Weight Loss Outcomes: Retrospective Cohort Study (Preprint)

2017 ◽  
Author(s):  
Christine Hill ◽  
Brian W Weir ◽  
Laura W Fuentes ◽  
Alicia Garcia-Alvarez ◽  
Danya P Anouti ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Weight Loss ◽  
Linear Regression ◽  
Mobile Phone ◽  
Body Mass ◽  
Caloric Intake ◽  
Body Mass Index Category ◽  
Obese Adults ◽  
Weight Loss Outcomes ◽  
The Relationship

BACKGROUND Although millions of overweight and obese adults use mobile phone apps for weight loss, little is known about the predictors of success. OBJECTIVE The objective of this study was to understand the relationship between weight loss outcomes and weekly patterns of caloric intake among overweight and obese adults using a mobile phone app for weight loss. METHODS We examined the relationship between weekly patterns of caloric intake and weight loss outcomes among adults who began using a weight loss app in January 2016 and continued consistent use for at least 5 months (N=7007). Unadjusted and adjusted linear regression analyses were used to evaluate the predictors of percentage of bodyweight lost for women and men separately, including age, body mass index category, weight loss plan, and difference in daily calories consumed on weekend days (Saturday and Sunday) versus Monday. RESULTS In adjusted linear regression, percentage of bodyweight lost was significantly associated with age (for women), body mass index (for men), weight loss plan, and differences in daily caloric intake on Mondays versus weekend days. Compared with women consuming at least 500 calories more on weekend days than on Mondays, those who consumed 50 to 250 calories more on weekend days or those with balanced consumption (±50 calories) lost 1.64% more and 1.82% more bodyweight, respectively. Women consuming 250 to 500 calories or more than 500 calories more on Mondays than on weekend days lost 1.35% more and 3.58% more bodyweight, respectively. Compared with men consuming at least 500 calories more on weekend days than on Mondays, those consuming 250 to 500 calories or more than 500 calories more on Mondays than on weekend days lost 2.27% and 3.42% less bodyweight, respectively. CONCLUSIONS Consistent caloric intake on weekend days and Mondays or consuming slightly fewer calories per day on Mondays versus weekend days was associated with more successful weight loss. CLINICALTRIAL ClinicalTrials.gov NCT03136692; https://clinicaltrials.gov/ct2/show/NCT03136692 (Archived by WebCite at http://www.webcitation.org/6y9JvHya4)

On the use of structured time-series to detect and test hypotheses about within-lakes relationships

1995 ◽  
Vol 52 (4) ◽  
pp. 799-803 ◽  
Author(s):  
Yves T. Prairie ◽  
C. Tara Marshall
Keyword(s):  
Time Series ◽  
Empirical Data ◽  
Single System ◽  
Empirical Relationships ◽  
Cross Sectional ◽  
Apparent Relationship ◽  
Field Season ◽  
The Relationship ◽  
Over Time ◽  
Chlorophyll Concentrations

Aquatic scientists using empirical relationships developed from point measurements or averages from different lakes often assume that these relationships also apply to individual lakes over time. However, this assumption is difficult to test because the extent of variation within a single system is generally much smaller and the relationship accordingly less defined than across a number of systems. We present a new method to extract empirical relationships from the internal structure of a time-series within a single lake. When we applied the method to an extreme simulation, we were able to recover accurately the parameters of the relationship in spite of the absence of any apparent relationship between the variables. When applied to empirical data for phosphorus and chlorophyll concentrations collected daily over one field season, the estimated structural relationship was nearly identical to that estimated from cross-sectional data even though the empirical trend appeared much shallower and very weak.

scholarly journals Cross-National Outcomes of a Digital Weight Loss Intervention in the United States, Canada, United Kingdom and Ireland, and Australia and New Zealand: A Retrospective Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Qiuchen Yang ◽  
Ellen Siobhan Mitchell ◽  
Annabell S. Ho ◽  
Laura DeLuca ◽  
Heather Behr ◽  
...  
Keyword(s):  
United States ◽  
Weight Loss ◽  
United Kingdom ◽  
New Zealand ◽  
Mixed Models ◽  
Linear Mixed Models ◽  
The United States ◽  
Weight Loss Intervention ◽  
The Us ◽  
Over Time

Mobile health (mHealth) interventions are ubiquitous and effective treatment options for obesity. There is a widespread assumption that the mHealth interventions will be equally effective in other locations. In an initial test of this assumption, this retrospective study assesses weight loss and engagement with an mHealth behavior change weight loss intervention developed in the United States (US) in four English-speaking regions: the US, Australia and New Zealand (AU/NZ), Canada (CA), and the United Kingdom and Ireland (UK/IE). Data for 18,459 participants were extracted from the database of Noom's Healthy Weight Program. Self-reported weight was collected every week until program end (week 16). Engagement was measured using user-logged and automatically recorded actions. Linear mixed models were used to evaluate change in weight over time, and ANOVAs evaluated differences in engagement. In all regions, 27.2–33.2% of participants achieved at least 5% weight loss by week 16, with an average of 3–3.7% weight loss. Linear mixed models revealed similar weight outcomes in each region compared to the US, with a few differences. Engagement, however, significantly differed across regions (P < 0.001 on 5 of 6 factors). Depending on the level of engagement, the rate of weight loss over time differed for AU/NZ and UK/IE compared to the US. Our findings have important implications for the use and understanding of digital weight loss interventions worldwide. Future research should investigate the determinants of cross-country engagement differences and their long-term effects on intervention outcomes.

Does craniofacial morphology relate to sleep apnea severity reduction following weight loss intervention? A patient-level meta-analysis

SLEEP ◽  
2020 ◽  
Author(s):  
Kate Sutherland ◽  
Julia L Chapman ◽  
Elizabeth A Cayanan ◽  
Aimee B Lowth ◽  
Camilla M Hoyos ◽  
...  
Keyword(s):  
Weight Loss ◽  
Sleep Apnea ◽  
Meta Analysis ◽  
Craniofacial Morphology ◽  
Apnea Hypopnea Index ◽  
Facial Morphology ◽  
Weight Loss Intervention ◽  
Obstructive Sleep ◽  
Intervention Trials ◽  
The Relationship

Abstract Study Objectives Obesity is a common and reversible risk factor for obstructive sleep apnea (OSA). However, there is substantial unexplained variability in the amount of OSA improvement for any given amount of weight loss. Facial photography is a simple, inexpensive, and radiation-free method for craniofacial assessment. Our aims were (1) to determine whether facial measurements can explain OSA changes, beyond weight loss magnitude and (2) whether facial morphology relates to how effective weight loss will be for OSA improvement. Methods We combined data from three weight loss intervention trials in which participants had standardized pre-intervention facial photography (N = 91; 70.3% male, mean ± SD weight loss 10.4 ± 9.6% with 20.5 ± 51.2% apnea–hypopnea index [AHI] reduction). Three skeletal-type craniofacial measurements (mandibular length, lower face height, and maxilla-mandible relationship angle) were assessed for relationship to AHI change following weight loss intervention. Results Weight and AHI changes were moderately correlated (rho = 0.3, p = 0.002). In linear regression, an increased maxilla-mandible relationship angle related to AHI improvement (β [95% CI] −1.7 [−2.9, −0.5], p = 0.004). Maxilla-mandible relationship angle explained 10% in the variance in AHI over the amount predicted by weight loss amount (20%). The relationship between weight change and AHI was unaffected by the maxilla–mandible relationship angle (interaction term p > 0.05). Conclusions Regardless of facial morphology, weight loss is similarly moderately predictive of OSA improvement. Increased maxilla-mandible relationship angle, suggestive of retrognathia, was weakly predictive of OSA response to weight loss. Although this is unlikely to be clinically useful, exploration in other ethnic groups may be warranted.

Abstract MP21: Better Sleep Health is Associated With Greater Weight Loss During a 12-month Behavioral Weight Loss Intervention

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Christopher E Kline ◽  
Zhadyra H Bizhanova ◽  
Susan M Sereika ◽  
Daniel Buysse ◽  
Christopher C Imes ◽  
...  
Keyword(s):  
Weight Loss ◽  
Weight Change ◽  
Apnea Hypopnea Index ◽  
Poor Sleep ◽  
Weight Loss Intervention ◽  
Behavioral Weight Loss ◽  
Sleep Health ◽  
Obstructive Sleep ◽  
Behavioral Weight Loss Intervention ◽  
The Relationship

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.

The effect of growth rate on muscle distribution in sheep

1975 ◽  
Vol 85 (1) ◽  
pp. 189-191 ◽  
Author(s):  
D. M. Murray ◽  
Olga Slezacek
Keyword(s):  
Growth Rate ◽  
Weight Loss ◽  
Growth Rates ◽  
Live Weight ◽  
High Growth ◽  
Growth Path ◽  
Merino Sheep ◽  
Reported Data ◽  
Relationship Of ◽  
The Relationship

There is little information available on the effect of growth rate on muscle distribution in sheep. Although Lohse, Moss & Butterfield (1971) and Lohse (1973) have reported data on muscle distribution of Merino sheep, the growth rates of animals in both these studies were neither controlled nor reported. In another experiment using Merino sheep, Lohse, Pryor & Butterfield (1973) studied the effect of a period of live-weight loss on the relationship of selected muscles to total side muscle during subsequent re-alimentation. They found that the interrupted growth path decreased the proportion of total side muscle formed by the weight of ten muscles which had previously been classified as muscles with a high growth impetus (Lohse, 1971). Data are presented herein for the muscle distribution of sheep grown along three growth paths.

scholarly journals Give it Time

2007 ◽  
Vol 129 (11) ◽  
pp. 28-31
Author(s):  
Jean Thilmany
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Data Acquisition ◽  
Cell Response ◽  
Preventive Maintenance ◽  
Failure Time ◽  
Living Systems ◽  
Macroscopic Level ◽  
The Relationship ◽  
Over Time

This article discusses that data acquisition techniques give researchers insights into fields outside the realm of machines. The methods that mechanical engineers most frequently call upon in their work have never been strictly confined to the province of machinery. Patterns may indicate the need for preventive maintenance or they may warn that a key piece of equipment is on the verge of failure. Time-series analysis has found uses in the important and potentially lucrative-intersection of engineering and medicine. Engineers commonly look at the relationship between time and response. But in biology that time relationship is not well characterized because it is hard to isolate and look at living systems over time. Currently, cell response is often studied on the macroscopic level.

scholarly journals Weight Bias Internalization and Long-Term Weight Loss in Patients With Obesity

2018 ◽  
Vol 53 (8) ◽  
pp. 782-787 ◽  
Author(s):  
Rebecca L Pearl ◽  
Thomas A Wadden ◽  
Ariana M Chao ◽  
Olivia Walsh ◽  
Naji Alamuddin ◽  
...  
Keyword(s):  
Weight Loss ◽  
Weight Change ◽  
Controlled Trial ◽  
Weight Loss Maintenance ◽  
Weight Bias ◽  
Change Over Time ◽  
Weight Bias Internalization ◽  
The Relationship ◽  
Over Time

Abstract Background The relationship between weight bias internalization (WBI) and long-term weight loss is largely unknown. Purpose To determine the effects of weight loss on WBI and assess whether WBI impairs long-term weight loss. Methods One hundred thirty-three adults with obesity completed the Weight Bias Internalization Scale (WBIS) at baseline, after a 14-week lifestyle intervention in which they lost ≥5 per cent of initial weight, and at weeks 24 and 52 of a subsequent randomized controlled trial (RCT) for weight-loss maintenance (66 weeks total). Linear mixed models were used to examine the effects of weight loss on WBIS scores and the effects of baseline WBIS scores on weight change over time. Logistic regression was used to determine the effects of baseline WBIS scores on achieving ≥5 and ≥10 per cent weight loss. Results Changes in weight did not predict changes in WBIS scores. Baseline WBIS scores predicted reduced odds of achieving ≥5 and ≥10 per cent weight loss at week 24 of the RCT (p values < .05). At week 52, the interaction between participant race and WBIS scores predicted weight loss (p = .046) such that nonblack (but not black) participants with higher baseline WBIS scores had lower odds of achieving ≥10 per cent weight loss (OR = 0.38, p = .01). Baseline WBIS scores did not significantly predict rate of weight change over time. Conclusions Among participants in a weight loss maintenance trial, WBI did not change in relation to changes in weight. More research is needed to clarify the effects of WBI on long-term weight loss and maintenance across race/ethnicity. Clinical trials registration ClinicalTrials.gov identifier NCT02388568.

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