scholarly journals Greater Average Meal Planning Frequency Predicts Greater Weight Loss Outcomes in a Worksite-Based Behavioral Weight Loss Program

2020 ◽  
Author(s):  
Jacqueline F Hayes ◽  
Katherine N Balantekin ◽  
Ellen E Fitzsimmons-Craft ◽  
Joshua J Jackson ◽  
Danielle R Ridolfi ◽  
...  
Keyword(s):  
Weight Loss ◽  
Random Effect ◽  
Fixed Effect Model ◽  
Behavioral Weight Loss ◽  
Growth Curve Models ◽  
Effect Model ◽  
Best Fitting ◽  
Weight Loss Outcomes ◽  
Meal Planning

Abstract Background Planning in behavioral weight loss (BWL) programs helps participants enact changes in eating and exercise, although the direct impact on weight loss is unclear. Purpose To examine how meal and exercise planning frequencies change in a BWL program and their relations to weight loss outcomes. Methods Participants (N = 139) in a 40 week worksite-based BWL program completed a questionnaire regarding meal and exercise planning frequency at Weeks 0, 10, 20, 30, and 40 and were weighed weekly. Growth curve models were used to determine trajectories in meal and exercise planning frequency and to assess the role of an individual’s average meal and exercise planning (between-person effect) and individual variation in planning (within-person effect) on body mass index (BMI). Results The best-fitting model, a linear random effect with a quadratic fixed-effect model, demonstrated that meal and exercise planning frequency increased over the course of the program with slowing growth rates. Between participants, higher average meal planning frequency (B = −0.029, t = −3.60), but not exercise planning frequency, was associated with greater weight loss. Within participants, exercise planning, but not meal planning, predicted a higher than expected BMI (B = 3.17, t = 4.21). Conclusions Frequent meal planning should be emphasized as a continued, as opposed to intermittent, goal in BWL programs to enhance weight loss. Average exercise planning frequency does not impact weight loss in BWL programs; however, acute increases in exercise planning frequency may be a popular coping strategy during a weight loss setback or, alternatively, may lead to increased calorie consumption and weight gain.

scholarly journals Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
The Tien Mai ◽  
Paul Turner ◽  
Jukka Corander
Keyword(s):  
Random Effect ◽  
Simulated Data ◽  
Fixed Effect Model ◽  
Accurate Estimate ◽  
Limited Attention ◽  
Effect Model ◽  
Generic Strategy ◽  
Multiple Sample ◽  
Inference Strategy ◽  
Resistance Data

Abstract Background Heritability is a central measure in genetics quantifying how much of the variability observed in a trait is attributable to genetic differences. Existing methods for estimating heritability are most often based on random-effect models, typically for computational reasons. The alternative of using a fixed-effect model has received much more limited attention in the literature. Results In this paper, we propose a generic strategy for heritability inference, termed as “boosting heritability”, by combining the advantageous features of different recent methods to produce an estimate of the heritability with a high-dimensional linear model. Boosting heritability uses in particular a multiple sample splitting strategy which leads in general to a stable and accurate estimate. We use both simulated data and real antibiotic resistance data from a major human pathogen, Sptreptococcus pneumoniae, to demonstrate the attractive features of our inference strategy. Conclusions Boosting is shown to offer a reliable and practically useful tool for inference about heritability.

Social Jetlag and Emerging Adults’ Performance in a Behavioral Weight Loss Trial

2020 ◽  
pp. 216769682098243
Author(s):  
Autumn Lanoye ◽  
Jessica Gokee LaRose
Keyword(s):  
Weight Loss ◽  
Emerging Adults ◽  
Life Transitions ◽  
Behavioral Weight Loss ◽  
Fat Percentage ◽  
Sleep Timing ◽  
Social Jetlag ◽  
Suboptimal Weight Loss ◽  
Weight Loss Outcomes ◽  
Program Engagement

Social jetlag (SJ)—the shift in sleep timing between workdays and free days—is linked to deleterious cardiometabolic outcomes. SJ is greatest among emerging adults, who are already at high risk for overweight/obesity and experience suboptimal weight loss outcomes. Goals of this ancillary study were to assess SJ among emerging adults enrolled in a 6-month behavioral weight loss trial and examine the association between SJ and treatment outcomes. Bedtime/waketime were self-reported at baseline, and program engagement was monitored throughout the intervention. Weight, waist circumference, and body fat percentage were measured at baseline and post-treatment. Participants (N = 282) reported 1.5 hours of SJ on average, with 30.5% reaching the threshold for clinical significance. There were no significant associations between SJ and program engagement nor between SJ and change in adiposity. Life transitions and chaotic schedules are common during emerging adulthood; thus, further research is needed to capture nuanced patterns of sleep disruption.

scholarly journals The Correlation of Glycemic Index, Glycemic Load, and Carbohydrates with the Risk of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

2021 ◽  
Author(s):  
Long-Shan Yang ◽  
Guang-Xiao Meng ◽  
Zi-Niu Ding ◽  
Lun-Jie Yan ◽  
Sheng-Yu Yao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Glycemic Index ◽  
Hepatitis Virus ◽  
Meta Analysis ◽  
Glycemic Load ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Case Control Studies ◽  
Effect Model

Abstract Background Glycemic index (GI), glycemic load (GL), and carbohydrates have been shown to be associated with a variety of cancers, but their correlation with hepatocellular carcinoma (HCC) remains controversial. The purpose of our study was to investigate the correlation of GI, GL and carbohydrate with risk of HCC.Methods Systematic searches were conducted in PubMed, Embase and Web of Science until November 2020. According to the size of heterogeneity, the random effect model or the fixed effect model was performed to calculate the pooled relative risks (RRs) and 95% confidence intervals (CIs) for the correlation of GI, GL, and carbohydrates with the risk of HCC.Results Seven cohort studies involving 1,193,523 participants and 1,004 cases, and 3 case-control studies involving 827 cases and 5,502 controls were eventually included. The pooled results showed no significant correlation of GI (RR=1.11, 95%CI 0.80-1.53, I2= 62.2%), GL (RR=1.09, 95%CI 0.76-1.55, I2 = 66%), and carbohydrate (RR=1.09, 95%CI 0.84-1.32, I2=0%) with the risk of HCC in general population. Subgroup analysis revealed that in hepatitis B virus (HBV) or/and hepatitis C virus (HCV)-positive group, GI was not correlated with the risk of HCC (RR=0.65, 95%CI 0.32-1.32, p=0.475, I2=0.0%), while GL was significantly correlated with the risk of HCC (RR=1.52, 95%CI 1.04-2.23, p=0.016, I2=70.9%). In contrast, in HBV and HCV-negative group, both GI (RR=1.23, 95%CI 0.88-1.70, p=0.222, I2=33.6%) and GL (RR=1.17, 95% CI 0.83-1.64, p=0.648, I2=0%) were not correlated with the risk of HCC. Conclusion A high GL diet is correlated with a higher risk of HCC in people with hepatitis virus. A low GL diet may be recommended for patients with viral hepatitis to reduce the risk of HCC.

scholarly journals Boosting Heritability: Estimating the Genetic Component of Phenotypic Variation With Multiple Sample Splitting

2021 ◽  
Author(s):  
The Tien Mai ◽  
Paul Turner ◽  
Jukka Corander
Keyword(s):  
Random Effect ◽  
Simulated Data ◽  
Fixed Effect Model ◽  
Limited Attention ◽  
Reliable Estimate ◽  
Effect Model ◽  
Generic Strategy ◽  
Multiple Sample ◽  
Inference Strategy ◽  
Resistance Data

Abstract Background: Heritability is a central measure in genetics quantifying how much of the variability observed in a trait is attributable to genetic differences. Existing methods for estimating heritability are most often based on random-effect models, typically for computational reasons. The alternative of using a fixed-effect model has received much more limited attention in the literature. Results: In this paper, we propose a generic strategy for heritability inference, termed as boosting heritability, by combining several advantageous features of different recent methods to produce an estimate of the heritability with a high-dimensional linear model. Boosting heritability uses in particular a multiple sample splitting strategy which leads to a more reliable estimate. We use both simulated data and real antibiotic resistance data from a major human pathogen, Sptreptococcus pneumoniae, to demonstrate the attractive features of our inference strategy. Conclusions: Compared with other methods, boosting heritability yields a more reliable estimate and allows one to make inference about heritability.

Analysis of Board Size and Firm Performance: Evidence from NSE Companies Using Panel Data Approach

2016 ◽  
Vol 9 (2) ◽  
pp. 148-172 ◽  
Author(s):  
Anjala Kalsie ◽  
Shikha Mittal Shrivastav
Keyword(s):  
Firm Performance ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Least Square ◽  
Empirical Literature ◽  
Board Size ◽  
Effect Model

This article seeks to examine the relationship between the board size and firm performance. Existing literature on board size is based on different theories of corporate governance. While agency theory and resource dependency theory suggest that the board size positively affects performance, stewardship theory favours smaller board size and argues that larger board size negatively impacts the firm performance. The present article adds to the empirical literature by employing panel data analysis of 145 non-financial companies listed in the NSE CNX 200 Index of India corresponding to 16 industries. The study is carried out for a period of five years from 2008 to 2012. The firm performance has been measured using Tobin’s Q and the market-to-book value ratio (MBVR) as market-based measures and return on assets (ROA) and return on capital employed (ROCE) as accounting-based measures. The fixed effect model, random effect model and feasible generalised least square (FGLS) regression models are applied to achieve the above-mentioned objectives. The results conclude that the board size has a positive and significant impact on the firm performance.

Racial disparity in OncotypeDX score in early stage, hormone receptor positive, HER-2 negative, node negative breast cancers: A systemic review and meta-analysis.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12555-e12555
Author(s):  
Yi Lee ◽  
Ruolin Liu ◽  
Alexis K. Bean ◽  
Madison J. Garshasebi ◽  
Qasim Jehangir ◽  
...  
Keyword(s):  
High Risk ◽  
Random Effects ◽  
Racial Disparity ◽  
Random Effect ◽  
Recurrence Score ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Random Effects Model ◽  
Effect Model ◽  
To Receive

e12555 Background: Oncotype DX Breast Recurrence Score (RS) is the currently used risk-assessment tool for early-stage, hormone receptor-positive, HER-2 negative, node-negative breast cancer in the US. Studies showed inconsistency in RS distribution and treatment among races. Causes may include variations in somatic mutations like Ki-67, which have been reported to express higher in African American (AA) and Asian populations than in Non-Hispanic White (NHW) population, germline mutations in BRCA and TP53, that are not in the RS algorithm, and financial burden of the testing. We analyzed data from different countries to investigate racial disparity in RS. Methods: We searched Medline, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials, indexed from January 2010 to January 2021. More than 85% of studies were conducted in the pre-TAILORx study phase. To include data that are available and better represent different races, we included studies that used the previous cutoff value, low-risk ( < 18), intermediate-risk (18-30), high-risk ( > 30). Retrospective studies using Surveillance, Epidemiology, and End Results or National Cancer Database were excluded to avoid overlap data. A total of 17 studies, 9789 patients from seven countries (US, Japan, China, Taiwan, Kuwait, UAE, Israel) were pooled. The Odds Ratio (OR) was extracted with a 95% confidence interval (CI) for RS distribution and post-RS treatment. Both fixed-effect and random-effect meta-analysis were performed. Results: Among AA and NHW, AA were 1.7 times more likely to have high recurrence score (OR = 1.75; 95% CI = 1.46 - 2.10; P < 0.0001), with no heterogeneity among studies (I2 = 0%, heterogeneity P = 0.59). Asian were 1.59 more likely than NHW to be high-risk using a random effects model (OR = 1.59; 95% CI = 1.06 - 2.40; P = 0.0259). High-risk Asian were two times more likely to receive adjuvant chemotherapy post-RS comparing to NHW (OR: 2.31, CI: 1.07 - 4.98, fixed effect model; OR: 2.85, CI: 0.48, 17.05, random effects model), while high-risk AA were less likely to receive chemotherapy comparing to NHW (OR: 0.74, CI: 0.54-1.01, fixed effect model; OR: 0.73, CI: 0.54-0.99, random effects model). Intermediate-risk Asian and AA were more likely to receive chemotherapy compared to NHW (Asian to NHW; OR: 1.68, CI: 1.16-2.43, with fixed effect model, OR: 1.68, CI: 0.94-3.02, with random effects model; AA to NHW; OR: 1.16, CI: 0.93-1.46 with fixed effect model; OR: 1.06, CI: 0.62-1.79 with random effect model). Conclusions: We identified racial disparity in RS and post-RS treatment. Future research is required to elucidate the causes for AA and Asian receiving higher recurrence scores, a need for tailoring RS cutoffs for different races, and the utilization in adequate post-RS treatment.

Effect of Dividend on Stock Price: A Case of Fuel and Power Industries in Bangladesh

2019 ◽  
Vol 9 (2) ◽  
pp. 87
Author(s):  
Mir Md Nazrul Islam
Keyword(s):  
Stock Price ◽  
Dividend Policy ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Return On Equity ◽  
Share Prices ◽  
Earnings Per Share ◽  
Effect Model

Dividend policy is an extensively researched topic in the arena of investments but still it remains an enigmatic that whether Dividend Policy affects the Stock Prices or not. The consequences of researches conducted in different stock markets are different. In Bangladesh, capital market investment is very essential and significant for the growth and market capitalization of domestic industry, trade and commerce. In current years Bangladesh had faced many precarious situations in its stock market. The Stock price reactions to the declaration of dividend of the fuel and power industry of Bangladesh are empirically examined. This study examines stock price reactions of listed dividend paying fuel and power industries in Dhaka stock exchange, Bangladesh for period of 11 years from of 2008-2018. This study will help us to make effective dividend decisions and effective implementation of dividend policies. In this study, Fixed Effect Model along with Random Effect Model have been used to estimate results. Both Models are implemented on panel data for explaining the association between dividend payments and share prices while controlling logarithm value of Profit after Tax, Earnings per Share and Return on Equity. The research is accompanied with a view to find whether the dividend announcement convey any evidence to the market that results a stock price volatility for adjusting the dividend announcement information while controlling the variables like Profit After Tax Earnings, Per Share and Return on Equity. The study also tested both the Models and found Random Effect Model is more significant than Fixed Effect Model. The result documented on the Random Effect Model shows that there are significant relationship with Retention Ratio, dividend per share and Return on Equity. In addition, Profit after tax shows the negative significant association and Earning per Shares insignificant with the share prices in Bangladesh Fuel and Power sector. 

Sign in / Sign up

Export Citation Format

Share Document