scholarly journals Leveraging Genomic Associations in Precision Digital Care for Weight Loss: Cohort Study (Preprint)

2020 ◽  
Author(s):  
Ranjan Sinha ◽  
Dashyanng Kachru ◽  
Roshni Ray Ricchetti ◽  
Simitha Singh-Rambiritch ◽  
Karthik Marimuthu Muthukumar ◽  
...  
Keyword(s):  
Weight Loss ◽  
Regression Models ◽  
Genomic Data ◽  
Mobile App ◽  
Weight Loss Program ◽  
Behavioral Engagement ◽  
Average Weight ◽  
Loss Models ◽  
The Impact ◽  
Genomic Risk

BACKGROUND In this age of global COVID-19 pandemic, the urgency of addressing an epidemic of obesity and associated inflammatory illnesses has come to the fore. Studies have demonstrated that interactions between single nucleotide polymorphisms (SNPs) and lifestyle interventions like food and exercise may vary metabolic outcomes, contributing to obesity and therapeutic response. However, there is a paucity of research relating outcomes from digital therapeutics to inclusion of genetic data in care interventions. OBJECTIVE This study aims to describe and model weight loss of subjects enrolled in a precision digital weight loss program informed by machine learning analysis of subject data, including genomic. It was hypothesized that weight loss models would exhibit better fit when incorporating genomic data than utilizing demographic and engagement variables alone. METHODS A cohort of 393 participants enrolled in Digbi Health’s personalized digital care program for 120 days was analyzed retrospectively. Care protocol included the use of subject genomic and gut microbiome data informing precision coaching by mobile app and personal coach. Two linear regression models of weight loss in this cohort (pounds lost, percentage lost) as a function of demographic and behavioral engagement variables were fit. Genomic-enhanced models were built by adding 197 SNPs from subject genomic data as predictors, then refitting, employing Lasso regression on SNPs for variable selection. Success/failure logistic regression models were also fit, with and without genomic data. RESULTS 72% of subjects in this cohort lost weight, while 17% maintained stable weight. 142 subjects lost 5% within 120 days. Models describe the impact of demographic and clinical factors, behavioral engagement, and genomic risk on weight loss. The addition of genomic predictors improved the mean squared error of weight loss models (pounds lost and percent) from 70 to 60 and 16 to 13 respectively. The logistic model improved pseudo R2 from 0.193 to 0.285. Gender, engagement and specific SNPs were significantly associated with weight loss. SNPs within genes involved in metabolic pathways that process food and regulate storage of fat were associated with weight loss in this cohort. This included rs17300539_G (insulin resistance, monounsaturated fat metabolism), rs2016520_C (BMI, waist circumference, cholesterol metabolism), and rs4074995_A (calcium-potassium transport, serum calcium levels). Models described greater average weight loss for subjects having more of these risk alleles. Notably, coaching for dietary modification was personalized to these genetic risks. CONCLUSIONS Adding genomic information in modeling outcomes of a digital precision weight loss program greatly enhanced model accuracy. Interpretable weight loss models pointed to efficacy of coaching informed by subjects’ genomic risk, accompanied by active engagement of subjects in their own success. While large-scale validation is needed, our study preliminarily supports precision dietary interventions for weight loss utilizing genetic risk, with digitally delivered recommendations alongside health-coaching to improve intervention efficacy.

scholarly journals Does Personalized Nutrition Increase Weight Loss Self-Efficacy?

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1310-1310
Author(s):  
Lu Hu ◽  
Chan Wang ◽  
Huilin Li ◽  
Margaret Curran ◽  
Collin J Popp ◽  
...  
Keyword(s):  
Weight Loss ◽  
Real Time ◽  
Self Efficacy ◽  
Learning Algorithm ◽  
Mobile App ◽  
Small Sample ◽  
Dietary Counseling ◽  
Macronutrient Distribution ◽  
The Impact

Abstract Objectives We examined whether a diet personalized to reduce postprandial glycemic response (PPGR) to foods increases weight loss self-efficacy. Methods The Personal Diet Study is an ongoing clinical trial that aims to compare two weight loss diets: a one-size-fits-all, calorie-restricted, low-fat diet (Standardized) versus a diet having the same calorie restriction but utilizing a machine learning algorithm to predict and reduce PPGR (Personalized). Both groups receive the same behavioral counseling to enhance weight loss self-efficacy. Both groups self-monitor dietary intake using a mobile app, with Standardized receiving real-time feedback on calories and macronutrient distribution, and Personalized receiving real time feedback on calories, macronutrient distribution, and predicted PPGR. We examined changes in self-efficacy between baseline and 3 mos, using the 20-item Weight Efficacy Lifestyle questionnaire (WEL). Linear mixed models were used to analyze differences, adjusting for age, gender, and race. Results The analyses included the first 75 participants to complete 3-mos assessments (41 Personalized and 34 Standardized). The majority of the participants were white (69.3%), female (61.3%), with a mean age of 61.7 years (SD = 9.9) and BMI of 33.4 kg/m2 (SD = 4.8). At baseline, WEL scores were similar between the 2 groups [Standardized WEL: 118.8 (SD = 27.6); Personalized WEL: 124.9 (SD = 29.5), P = 0.47]. At 3 mos, the WEL score was significantly improved in both groups [16.0 (SD = 4.1) in the Standardized group (P < 0.001) and 7.4 (SD = 3.7) in the Personalized group (P = 0.048)], but the between group difference was not significant (P = 0.12). Conclusions Personalized feedback on predicted PPGRs does not appear to enhance weight loss self-efficacy at 3 mos. The lack of significance may be related to the short follow-up period in these preliminary analyses, the small sample accrued to date, or the fact that WEL is designed to assess confidence in various situations (e.g., depressed, anxious) that may not be impacted by personalization. These analyses will be replicated with a larger sample using data obtained through the 6-mos follow-up. New self-efficacy measures may be required to assess the impact of personalized dietary counseling. Funding Sources This research was supported by the American Heart Association.

The Impact of a Workplace-Based Weight Loss Program on Work-Related Outcomes in Overweight Male Shift Workers

2012 ◽  
Vol 54 (2) ◽  
pp. 122-127 ◽  
Author(s):  
Philip J. Morgan ◽  
Clare E. Collins ◽  
Ronald C. Plotnikoff ◽  
Alyce T. Cook ◽  
Bronwyn Berthon ◽  
...  
Keyword(s):  
Weight Loss ◽  
Weight Loss Program ◽  
Shift Workers ◽  
Work Related ◽  
The Impact

Psychological Well-Being, Health Behaviors, and Weight Loss Among Participants in a Residential, Kripalu Yoga-Based Weight Loss Program

2012 ◽  
Vol 22 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Tosca Braun ◽  
Crystal Park ◽  
Lisa Ann Conboy
Keyword(s):  
Weight Loss ◽  
Health Behaviors ◽  
Well Being ◽  
The United States ◽  
Overweight And Obesity ◽  
Weight Loss Program ◽  
Health Concern ◽  
Psychological Well Being ◽  
The Impact

The increasing prevalence of overweight and obesity in humans is a growing public health concern in the United States. Concomitants include poor health behaviors and reduced psychological well-being. Preliminary evidence suggests yoga and treatment paradigms incorporating mindfulness, self-compassion (SC), acceptance, non-dieting, and intuitive eating may improve these ancillary correlates, which may promote long-term weight loss. Methods: We explored the impact of a 5-day residential weight loss program, which was multifaceted and based on Kripalu yoga, on health behaviors, weight loss, and psychological well-being in overweight/obese individuals. Thirty-seven overweight/obese program participants (age 32-65, BMI<25) completed validated mind-fulness, SC, lifestyle behavior, and mood questionnaires at baseline, post-program, and 3-month follow-up and reported their weight 1 year after program completion. Results: Significant improvements in nutrition behaviors, SC, mindfulness, stress management, and spiritual growth were observed immediately post-program (n = 31, 84% retention), with medium to large effect sizes. At 3-month follow-up (n = 18, 49% retention), most changes persisted. Physical activity and mood disturbance had improved significantly post-program but failed to reach significance at 3-month follow-up. Self-report weight loss at 1 year (n = 19, 51% retention) was significant. Conclusion: These findings suggest a Kripalu yoga-based, residential weight loss program may foster psychological well-being, improved nutrition behaviors, and weight loss. Given the exploratory nature of this investigation, more rigorous work in this area is warranted.

scholarly journals Weight loss and usage of an online commercial weight loss program delivered in an everyday context: A 5-year evaluation of the CSIRO Total Wellbeing Diet Online (Preprint)

2020 ◽  
Author(s):  
Gilly A Hendrie ◽  
Danielle L Baird ◽  
Emily Brindal ◽  
Gemma Williams ◽  
Jennie Brand-Miller ◽  
...  
Keyword(s):  
Weight Loss ◽  
Body Weight ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Comprehensive Evaluation ◽  
Economic Benefits ◽  
Weight Loss Program ◽  
Average Weight ◽  
Global Public Health ◽  
Food Diary

BACKGROUND Obesity is a global public health challenge, and there is a need for more evidence-based self-management programs that support longer term, sustained weight loss. OBJECTIVE This study used data from the CSIRO Total Wellbeing Diet Online to determine the reach and weight loss results over its first five years. METHODS Participants were adults who joined the commercial weight loss program of their own volition between October 2014 and September 2019 (N=61,164). Information collected included year of birth, sex, height and weight, and usage data, for example entries into the food diary, views of the menu and program content. Weight loss and percentage of starting body weight lost were calculated. Members were divided into two groups for analysis: ‘Stayers’ were members who signed up to at least 12 weeks of the program and recorded a weight entry at baseline and at the end of the program; ‘Starters’ started the program but did not record a weight after 12 weeks. Descriptive statistics and multiple linear regression were used to describe weight loss and determine the member and program characteristics associated with weight loss. RESULTS Data were available from 59,686 members for analysis. Members were predominately female (n=48979/59686; 82%) with an average age of 50 years (SD=12.6). The average starting weight was 90.2kg (SD=19.7) and over half of all members were obese (n=34195/59688, 57%). At week-12, 95% of members had an active program membership which decreased to 41% at 24 weeks. At week 12, 52% of remaining members were actively using the platform, and by week 24, 27% were using the platform. The average weight loss for all members was 2.8kg or 3.1% of starting body weight. Stayers lost 4.9kg (5.3% of starting body weight), compared to starters who lost 1.6kg (1.7% of starting body weight). Almost half (49%) the members who stayed on the program lost 5% or more of their starting body weight, and 16% achieved a weight loss of 10% or more. Of members who were Class 1 obese when they joined the program, 41% who stayed on the program were no longer obese at the end, and across all categories of obesity 24% were no longer obese at the end of the program. Based on multiple linear regression, platform usage was the strongest predictor of weight loss (beta=.263; P<.001), with higher usage associated with greater weight loss. CONCLUSIONS This comprehensive evaluation of a commercial, online weight loss program showed that it was effective for weight loss, particularly for members who finished the program and were active in using the platform and tools provided. If the results demonstrated here can be achieved at an even greater scale, the potential social and economic benefits will be extremely significant. CLINICALTRIAL not applicable.

scholarly journals Estimation of Tomato Bruising by Mechanical Impact Force Using Multivariate Analysis

HortScience ◽  
2018 ◽  
Vol 53 (9) ◽  
pp. 1352-1359
Author(s):  
Jinshi Cui ◽  
Myongkyoon Yang ◽  
Daesik Son ◽  
Seongmin Park ◽  
Seong-In Cho
Keyword(s):  
Weight Loss ◽  
Multivariate Analysis ◽  
Regression Models ◽  
Impact Force ◽  
Tomato Fruit ◽  
Contact Forces ◽  
Impact Measurement ◽  
Mechanical Impact ◽  
Acceleration Sensors ◽  
The Impact

Fresh fruit bruising caused by mechanical impact is the most problematic effect of mechanical postharvest processing of tomatoes. The conventional postharvest process of tomato fruit (Solanum lycopersicum L.) handling was surveyed from harvest to shipping preparation at a farm in Toechon in the Republic of Korea. Acceleration sensors located on the harvest boxes and fruit skin showed that the most severe impact forces (>10 g) occurred while fruit was moved in and out of the harvest box. Next, multivariate analysis was used to evaluate nondestructively the susceptibility of tomatoes to bruising by developing five estimation models incorporating quality factors and the presence of bruising resulting from peak contact forces. Linear regression models, artificial neural network (ANN) regression models, and a logistic regression model were built; the primary dependent variables were the rates of weight loss and firmness loss, and impact-induced bruising. The impact force was controlled by using a pendulum, which produced four levels of impact force on tomato fruit. Increasing the relative humidity (RH) and firmness, and decreasing the temperature and degree of weight loss decreased tomato fruit bruise damage. In addition, the proposed drop–impact measurement technique, with multivariate analysis, can be used to evaluate tomato quality nondestructively.

scholarly journals The Impact of the COVID-19 Lockdown on Weight Loss and Body Composition in Subjects with Overweight and Obesity Participating in a Nationwide Weight-Loss Program: Impact of a Remote Consultation Follow-Up—The CO-RNPC Study

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2152
Author(s):  
Sébastien Bailly ◽  
Odile Fabre ◽  
Rémy Legrand ◽  
Laurent Pantagis ◽  
Monique Mendelson ◽  
...  
Keyword(s):  
Weight Loss ◽  
Body Composition ◽  
Overweight And Obesity ◽  
Weight Loss Program ◽  
Dose Effect ◽  
Remote Consultation ◽  
Consultation Group ◽  
The Impact ◽  
Remote Consultations

The aim of this study was to assess the impact of the nationwide total lockdown (LD) in France on weight loss and body composition modifications in subjects participating in a weight loss program and to evaluate the impact of remote consultations on participants’ adherence to the weight loss program. The CO-RNPC study was a prospective multicentre cohort study including participants undergoing a two to six months program. The rate of weight loss in kg/week was computed before (15 days), during (99 days) and after LD (15 days). In the 1550 completing participants, body weight decreased from 87.1 kg [IQR 77.0; 100.2] to 82.3 kg [72.1; 94.3] resulting in a difference of −4.79 kg [−4.48; −5.10] (p < 0.01), with a corresponding reduction in waist circumference by 4 cm ([0; 9], p < 0.01). The median weight loss was 4.4 kg [0.5; 9.4] in those who used remote consultations, and 1.4 kg [0.8; 5.7] in the no remote consultation group (p < 0.01). In this large prospective cohort, we observed that the rate of weight loss was reduced during LD. This reduction was counterbalanced in participants involved in a remote consultation follow-up with a dose-effect response based on the number of remote consultations.

scholarly journals The Impact of COVID-19 Lockdown on Weight Loss Program in Infertile Polycystic Ovary Syndrome Women with Obesity

Obesity Facts ◽  
2021 ◽  
pp. 1-8
Author(s):  
Ana Šuštaršič ◽  
Eda Vrtačnik Bokal ◽  
Tanja Burnik Papler
Keyword(s):  
Weight Loss ◽  
Polycystic Ovary Syndrome ◽  
Weight Reduction ◽  
Polycystic Ovary ◽  
Statistical Significance ◽  
Weight Loss Program ◽  
Pregnancy Rates ◽  
Ovary Syndrome ◽  
Spontaneous Pregnancy ◽  
The Impact

<b><i>Introduction:</i></b> Lockdown due to the COVID-19 pandemic has caused gym closures and adjustments to ongoing weight loss programs were needed in order to keep the programs running. Little is known whether adjustments affected the success of weight reduction. Weight reduction of at least 5% is related to improved fertility and better pregnancy outcomes in obese women. This study compared success of the weight loss program in infertile polycystic ovary syndrome women with obesity who attended the program before and during lockdown due to COVID-19 pandemic. Furthermore, we checked whether there were any differences in spontaneous pregnancy rates between both groups at the end of the program. <b><i>Methods:</i></b> Altogether, 27 women were prospectively included to the weight loss program. Twelve women attended the 8 – week program before COVID-19 pandemic. Fifteen women began the program before the lockdown and ended it during lockdown. Due to lockdown, the program was prolonged for 4 weeks and taken online. <b><i>Results:</i></b> On average, prior to lockdown women achieved a BMI reduction of 6.8% whereas women that attended the program during the lockdown reduced their BMI for 3.7%. This difference was not statistically significant. No significant differences were seen in other measured anthropometric and endocrine parameters between both groups. Furthermore, there were no differences in spontaneous pregnancy rates between both groups. In women who reduced their BMI for 5% or more, spontaneous pregnancy rate was 29.4%. <b><i>Discussion/Conclusions:</i></b> Although statistical significance has not been reached in the present study, we have shown that lockdown due to COVID-19 pandemic has led to almost half lower BMI reduction despite adaptations and longer duration of the weight loss program. On average, BMI in the group of women that attended the program during lockdown was 3.7% lower after the end of the weight loss program. This means they did not reach the wanted 5% reduction which is known to improve fertility. We have also shown that weight reduction is the correct approach for treating infertile women with obesity, as almost 30% of those who reduced their body weight by 5% or more conceived spontaneously.

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