Objectives: Dropout and weight regain are common problems in most obesity treatments. The purpose of this study was to review previously published study results of the predictive factors associated with dropout during weight loss treatment and weight loss maintenance after successful weight loss. Methods: Authors searched for the articles related to dropout and weight loss maintenance, published from 2007 to 2016 found on Pubmed, Scopus, RISS, and KISS. A total of 19 articles were finally selected. From the study results, unchangeable and changeable predictors were extracted, and these predictors were examined according to dropout and weight loss maintenance categories. Results: The unchangeable predictors of dropout were younger age, lower education level and female, whereas the changeable predictors of dropout were lower initial weight loss, symptoms of depression and body dissatisfaction. The strongest factor for predicting the dropout was initial weight loss. The unchangeable predictors of weight loss maintenance were old age, male and family history of obesity, whereas the changeable predictors of weight loss maintenance were regular exercise, dietary restraint, self-weighing and low depressive symptoms. Initial weight loss, depressive symptoms, body image, dietary restraint, physical activity, weight loss expectation and social support were considered to be dominant factors for weight loss treatments. Conclusions: Our review results suggest that unchangeable and changeable predictors of dropout and weight loss maintenance should be carefully examined during treatments of obesity.
Objectives: People often fail to reduce or maintain their weight despite trying to lose weight. The purpose of this study was to review previously published study results of the predictive factors associated with weight loss in obesity treatment. Methods: Authors searched for the articles related to weight loss, published from 2007 to 2017 found on PubMed, Scopus, Research Information Sharing Service (RISS), and Koreanstudies Information Service System (KISS). A total of 43 articles were finally selected. From the study results, unchangeable and changeable predictors were extracted, and these predictors were examined according to detailed categories. Results: Predictors of weight loss in obesity treatment included genetic and physiological factors, demographic factors, history of treatment on obesity related factors, behavioral factors, psychological factors and treatment process related factors. The main factors of weight loss were unchangeable predictors such as high initial degree of obesity and younger age, and changeable predictors such as dietary restraint, regular exercise, self-efficacy, initial weight loss and attendance. Especially dietary restraint, regular exercise, successful initial weight loss and high attendance were considered to be dominant factors for weight loss treatments. Conclusions: Our review results suggest that unchangeable and changeable predictors of weight loss should be carefully examined during treatments of obesity.
Objectives: People often fail to maintain their weight even though they have succeeded in weight loss. The purpose of this study was to review previously published study results with regards to the predictive factors associated with weight loss maintenance after successful weight loss. Methods: The authors searched for the articles related to weight loss maintenance after successful weight loss, published up until June 2019 on PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Embase, Research Information Sharing Service (RISS), and Koreanstudies Information Service System (KISS). A total of 76 articles were finally selected. From the study results, changeable and unchangeable predictors were extracted, and these predictors were examined according to detailed categories. Results: The changeable predictors of weight loss maintenance included behavioral factors, psychological factors and treatment process-related factors, whereas the unchangeable predictors included genetic and physiological factors, demographic factors, history of treatment on obesity-related factors. The main factors of weight loss maintenance were changeable predictors such as healthy eating habits, dietary intake control, binge eating control, regular exercise and physical activity, depression and stress control, social supports, self-regulation, self-weighing and initial weight loss and unchangeable predictors such as low initial weight and maximum lifetime weight. Conclusions: The results of our review results suggest that changeable and unchangeable predictors of weight loss maintenance should be carefully examined during treatments of obesity.
Objectives: The purpose of this study was to review predictive factors associated with weight loss in moderate to severe obesity treatment. The direction of the treatment for moderate to severe obesity will be suggested in consideration of various factors. Methods: Authors searched the articles published from 2018 to 2023 in three international databases (PubMed, Embase and the Cochrane Central Register of Controlled Trials) and two domestic databases (Research Information Sharing Service, Korean studies Information Service System). Studies including treatment with moderate to severe obese patients were selected. Results: A total of 43 studies were included. The main factors of weight loss were unchangeable predictors such as low initial degree of obesity, younger age, non-diabetes and high resting energy expenditure with changeable predictors such as increase in protein, physical activity, self-efficacy, initial weight loss and attendance of the treatment. Conclusions: Our review results suggest that based on the characteristics of moderate to severe obese patients, predictors of weight loss can be used to determine treatment and prognosis in various aspects.
Objectives: Acceptability of patients towards obesity treatment program is associated with better weight loss outcomes. The purpose of this study was to review previously published study results of the predictive factors associated with patients' acceptability in obesity treatment. Methods: Authors searched for the articles related to acceptability reported as continuation, attendance and adherence, published from 2011 to 2018 found on Pubmed, Scopus, Research Information Sharing Service, and Koreanstudies Information Service System. A total of 23 articles were finally selected. From the study results, unchangeable and changeable predictors were extracted, and these predictors were examined according to detail categories. Results: Regarding the continuation of the treatment, unchangeable factors such as younger age, lower educational level, male sexuality and lower accessibility to physical activity predicted lower continuation. Furthermore, changeable factors such as early and half weight loss, better accessibility to the treatment and financial incentives for retention predicted higher continuation rate. Greater degree of attendance was predicted by unchangeable factors such as economical affordability, and changeable predictors such as half weight loss and proximity to the clinic. Main factors of adherence to the recommendation were unchangeable predictors such as weight loss experience, and changeable predictors such as more physical activity and appropriate dietary habits. Negative psychological state predicted lower continuation, attendance and adherence rate. Conclusions: Our review results suggest that unchangeable and changeable predictors of acceptability of patients should be carefully examined during treatments of obesity.
Leung, Alice Wai Yi;Chan, Ruth Suk Mei;Sea, Mandy Man Mei;Woo, Jean
Nutrition Research and Practice
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제13권5호
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pp.415-424
/
2019
BACKGROUND/OBJECTIVES: Existing evidence on lifestyle modification programs for weight loss is limited by the high attrition rate of such programs. Identifying predictors of adherence to a lifestyle modification program could result in program improvement. However, little is known about behavior-specific adherence and its psychological predictors. This study aimed to examine the psychological predictors of adherence after one-month participation in a community-based lifestyle modification program among Chinese overweight and obese adults in Hong Kong. SUBJECTS/METHODS: A total of 205 Chinese overweight and obese adults aged $38.9{\pm}10.5years$ completed the study. Data were collected at baseline and after one month using self-reported questionnaires, which assessed knowledge (self-developed scale), motivation (Treatment Self-Regulation Questionnaire), stage of change (Stage of Exercise Scale) and self-efficacy (Self-Rated Abilities for Health Practices Scale). At one month, a 4-day dietary recall and the International Physical Activity Questionnaire-Short Form were used to assess dietary and physical activity (PA) adherence. Food and PA diaries were examined to indicate self-monitoring. Program attendance was tracked between baseline and one-month follow-up. RESULTS: After one month, participants reported high dietary adherence, attendance, and adherence to self-monitoring but low PA adherence. Multiple regression analyses suggested that diet self-efficacy (baseline) and nutrition knowledge (one-month change) were independent predictors of dietary adherence score at one month, whereas autonomous PA motivation (baseline) and PA self-efficacy (both baseline and one-month change) were independent predictors of PA adherence score at one month. No significant psychological predictor was identified for attendance or self-monitoring. CONCLUSIONS: The results suggest that the effect of psychological factors on adherence differs between diet and PA adherence outcomes. To promote adherence, practitioners should assess self-efficacy, knowledge, and motivation at the beginning of a weight-loss program and explore behavior-specific strategies to improve knowledge and self-efficacy. The results of this study have direct implications for program improvements.
Objectives: The purpose of this study was to analyze the factors affecting weight loss effect of Gamitaeumjowee-tang and to see if weight loss could be predicted using influence factors and weight loss progress. Methods: From September 2016 to March 2017, we retrospectively reviewed the medical records of 139 patients who were visited to the Korean Oriental Clinic for 3 months. We conducted a regression analysis to determine whether age, gender, initial weight, patient health questionnaire-9, heart rate variability (HRV), sleep quality, drinking habit and the medication history of weight loss affect weight loss. We found weight loss prediction equations using multiple regression analysis applying significant factors and weight loss progress. Results: Gender and initial weight had a significant effect on weight loss in all periods (P<0.001). HRV had a significant effect on primary weight loss (P<0.01). Other factors did not have any significant effect on weight loss. Using the significant factors, weight loss of each period could be predicted from 23.9% to 44.6%, and tertiary weight loss could be predicted with 76.6% using factors, primary weight loss and secondary weight loss (P<0.001). Conclusions: This study suggests that weight loss effect of Gamitaeumjowee-tang maybe be affected by influence factors and that weight loss prediction equations using them can be used for obesity treatment.
Background: Little IS known about predictors of lifestyle modification in overweight or obese patients with acute myocardial infarctions. Methods: Between October 2005 and May 2007, 311 overweight or obese patients with an AMI visited Kyungpook National University Hospital. Among them, 216 patients ($63{\pm}11$ years old, 144 males) with ${\geq}1$ year of follow-up were included. Results: Body weight of all patients showed a significant decrease and 20% showed a >3% weight reduction at 1 year of follow-up. Ninety-six (44%) patients were smoking at baseline, and 52% of them had quit by 1 year of follow-up. Only six smokers were successful with both a >3% weight reduction and smoking cessation. In multivariate analysis, age (OR 1.084, 95% CI 1.028-1.144, p=0.003) and smoking cessation (OR 0.167, 95% CI 0.048-0.575, p=0.005) were independent predictors of weight reduction. Abdominal circumference was a negative predictor of smoking cessation (OR 0.903, 95% CI 0.820-0.994, p=0.037). Conclusions: Mean body weight of all patients showed a significant decrease at follow-up. Smoking cessation and age were independent predictors of weight reduction, and abdominal circumference was a negative predictor of smoking cessation.
BACKGROUND/OBJECTIVES: Malnutrition during hospitalization is linked to increased morbidity and mortality, but there are insufficient studies observing clinical factors contributing to weight loss during hospitalization in Indonesia. This study was therefore undertaken to determine the rate of weight loss during hospitalization and the contributing factors. SUBJECTS/METHODS: This was a prospective study involving hospitalized adult patients aged 18-59 yrs, conducted between July and September 2019. Body weight measurement was taken at the time of admission and on the last day of hospitalization. The factors studied were malnutrition at admission (body mass index < 18.5 kg/m2), immobilization, depression (Beck Depression Inventory-II Indonesia), polypharmacy, inflammatory status (neutrophil-lymphocytes ratio; NLR), comorbidity status (Charlson Comorbidity Index; CCI), and length of stay. RESULTS: Totally, 55 patients were included in the final analysis, with a median age of 39 (18-59 yrs) yrs. Of these, 27% had malnutrition at admission, 31% had a CCI score > 2, and 26% had an NLR value of ≥ 9. In all, 62% presented with gastrointestinal symptoms, and depression was documented in one-third of the subjects at admission. Overall, we recorded a mean weight loss of 0.41 kg (P = 0.038) during hospitalization, with significant weight loss observed among patients hospitalized for 7 days or more (P = 0.009). The bivariate analysis revealed that inflammatory status (P = 0.016) was associated with in-hospital weight loss, while the multivariate analysis determined that the contributing factors were length of stay (P < 0.001) and depression (P = 0.019). CONCLUSIONS: We found that inflammatory status of the patient might influence the incidence of weight loss during hospitalization, while depression and length of stay were independent predictors of weight loss during hospitalization.
Wipfli, Brad;Hanson, Ginger;Anger, Kent;Elliot, Diane L.;Bodner, Todd;Stevens, Victor;Olson, Ryan
Safety and Health at Work
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제10권1호
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pp.95-102
/
2019
Background: In a cluster-randomized trial, the Safety and Health Involvement For Truck drivers intervention produced statistically significant and medically meaningful weight loss at 6 months (-3.31 kg between-group difference). The current manuscript evaluates the relative impact of intervention components on study outcomes among participants in the intervention condition who reported for a post-intervention health assessment (n = 134) to encourage the adoption of effective tactics and inform future replications, tailoring, and enhancements. Methods: The Safety and Health Involvement For Truck drivers intervention was implemented in a Web-based computer and smartphone-accessible format and included a group weight loss competition and body weight and behavioral self-monitoring with feedback, computer-based training, and motivational interviewing. Indices were calculated to reflect engagement patterns for these components, and generalized linear models quantified predictive relationships between participation in intervention components and outcomes. Results: Participants who completed the full program-defined dose of the intervention had significantly greater weight loss than those who did not. Behavioral self-monitoring, computer-based training, and health coaching were significant predictors of dietary changes, whereas behavioral and body weight self-monitoring was the only significant predictor of changes in physical activity. Behavioral and body weight self-monitoring was the strongest predictor of weight loss. Conclusion: Web-based self-monitoring of body weight and health behaviors was a particularly impactful tactic in our mobile health intervention. Findings advance the science of behavior change in mobile health intervention delivery and inform the development of health programs for dispersed populations.
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