Recent weight changes and weight cycling as predictors of subsequent two year weight change in a middle-aged cohort

Long-Term Body Mass Index Variability and Adverse Cardiovascular Outcomes

Importance

Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is a commonly used estimate of obesity, which is a complex trait affected by genetic and lifestyle factors. Marked weight gain and loss could be associated with adverse biological processes.

Objective

To evaluate the association between BMI variability and incident cardiovascular disease (CVD) events in 2 distinct cohorts.

Design, Setting, and Participants

This cohort study used data from the Million Veteran Program (MVP) between 2011 and 2018 and participants in the UK Biobank (UKB) enrolled between 2006 and 2010. Participants were followed up for a median of 3.8 (5th-95th percentile, 3.5) years. Participants with baseline CVD or cancer were excluded. Data were analyzed from September 2022 and September 2023.

Exposure

BMI variability was calculated by the retrospective SD and coefficient of variation (CV) using multiple clinical BMI measurements up to the baseline.

Main Outcomes and Measures

The main outcome was incident composite CVD events (incident nonfatal myocardial infarction, acute ischemic stroke, and cardiovascular death), assessed using Cox proportional hazards modeling after adjustment for CVD risk factors, including age, sex, mean BMI, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking status, diabetes status, and statin use. Secondary analysis assessed whether associations were dependent on the polygenic score of BMI.

Results

Among 92 363 US veterans in the MVP cohort (81 675 [88%] male; mean [SD] age, 56.7 [14.1] years), there were 9695 Hispanic participants, 22 488 non-Hispanic Black participants, and 60 180 non-Hispanic White participants. A total of 4811 composite CVD events were observed from 2011 to 2018. The CV of BMI was associated with 16% higher risk for composite CVD across all groups (hazard ratio [HR], 1.16; 95% CI, 1.13-1.19). These associations were unchanged among subgroups and after adjustment for the polygenic score of BMI. The UKB cohort included 65 047 individuals (mean [SD] age, 57.30 (7.77) years; 38 065 [59%] female) and had 6934 composite CVD events. Each 1-SD increase in BMI variability in the UKB cohort was associated with 8% increased risk of cardiovascular death (HR, 1.08; 95% CI, 1.04-1.11).

Conclusions and Relevance

This cohort study found that among US veterans, higher BMI variability was a significant risk marker associated with adverse cardiovascular events independent of mean BMI across major racial and ethnic groups. Results were consistent in the UKB for the cardiovascular death end point. Further studies should investigate the phenotype of high BMI variability.

Changes in Macronutrients during Dieting Lead to Weight Cycling and Metabolic Complications in Mouse Model

Weight cycling is a major challenge in obesity management. Caloric restriction is known to promote this phenomenon, but the impact of macronutrient changes during dieting remains unclear. This study aimed to determine the role of macronutrient changes in weight maintenance without caloric restriction by alternating between two hypercaloric diets: a high-carbohydrate, high-fat Western diet (WD) and a low-carbohydrate, high-fat diet (LCHDF). Obesity was induced in 8-week-old C57BL/6 male mice by 10 weeks of WD feeding. Then, the mice were subjected to 12 weeks of LCHFD interspersed with WD (I-WD), 3 periods of 2-week LCHFD followed by 2 periods of 3-week WD, or 12 weeks of continuous WD (C-WD). C-WD and I-WD mice were compared to standard diet (SD) mice. In the I-WD group, each LCHFD period decreased weight gain, but mice regained weight after WD resumption. I-WD mice exhibited obesity, dyslipidemia, and glucose intolerance, similarly to the C-WD mice. I-WD mice also developed nonalcoholic steatohepatitis, associated with an increase in type-III collagen gene expression and a decrease in FGF21 protein levels, in comparison with SD. I-WD mice developed weight cycling despite maintaining a high caloric consumption, suggesting that changes in macronutrients during dieting are also a trigger of weight regain.

A Longitudinal Analysis of Weight Changes before and after Total Knee Arthroplasty: Weight Trends, Patterns, and Predictors

Longitudinal data on patient trends in body mass index (BMI) and the proportion that gains or loses significant weight before and after total knee arthroplasty (TKA) are scarce. This study aimed to observe patients longitudinally for a 2-year period and determine (1) clinically significant BMI changes during the 1 year before and 1 year after TKA and (2) identify factors associated with clinically significant weight changes.A prospective cohort of 5,388 patients who underwent primary TKA at a tertiary health care institution between January 2016 and December 2019 was analyzed. The outcome of interests was clinically significant weight changes, defined as a ≥5% change in BMI, during the 1-year preoperative and postoperative periods, respectively. Patient-specific variables and demographics were assessed as potential predictors of weight change using multinomial logistic regression.Overall, 47% had a stable weight throughout the study period (preoperative: 17% gained, 15% lost weight; postoperative: 19% gained, 16% lost weight). Patients who were older (odds ratio [OR] = 0.95), men (OR = 0.47), overweight (OR = 0.36), and Obese Class III (OR = 0.06) were less likely to gain weight preoperatively. Preoperative weight loss was associated with postoperative weight gain 1 year after TKA (OR = 3.03). Preoperative weight gain was associated with postoperative weight loss 1 year after TKA (OR = 3.16).Most patients maintained a stable weight before and after TKA. Weight changes during the 1 year before TKA were strongly associated with reciprocal rebounds in BMI postoperatively, emphasizing the importance of ongoing weight management during TKA and the recognition of patients at higher risk for weight gain.Level of evidence II (prospective cohort study).

Weight management behaviours mediate the relationship between weight cycling, BMI and diet quality among US Army Soldiers

Weight cycling is prevalent in sports/professions with body composition standards, and has been associated with weight management behaviours that may contribute to suboptimal diet quality and weight gain. US Army Soldiers may be at increased risk of weight cycling relative to civilians due to mandated body composition standards. However, the relationship between weight cycling, weight management behaviours, BMI and diet quality among Soldiers is unknown. In this cross-sectional study, 575 Soldiers (89 % enlisted, 90 % male, 23 ± 4 years) at Army installations at Joint Base Elmendorf-Richardson, AK, Joint-Base Lewis McChord, WA, and Fort Campbell, KY completed questionnaires on food frequency, health-related behaviours and history of weight cycling (≥ 3 weight fluctuations ≥ 5 % body weight). Weight cycling was reported by 33 % of Soldiers. Those who reported weight cycling reported higher BMI (27 ± 4 v. 25 ± 3 kg/m², P < 0·001) and higher prevalence of engaging in weight management behaviours prior to body weight screening but did not report lower dietary quality (Healthy Eating Index-2015 (HEI) scores 59 ± 10 v 59 ± 11, P = 0·46) relative to those who did not report weight cycling. Results of mediation analyses suggested that weight cycling may affect BMI both directly (c' = 1·19, 95 % CI: 0·62, 1·75) and indirectly (ab = 0·45, 95 % CI: 0·19, 0·75), and HEI scores indirectly (ab = 0·69, 95 % CI: 0·20, 1·35) through the adoption of weight management behaviours. Weight cycling is common in Soldiers and is associated with higher BMI and higher prevalence of engaging in weight management behaviours that mediate associations between weight cycling, BMI and diet quality.

History of Weight Cycling Is Prospectively Associated With Shorter and Poorer-Quality Sleep and Higher Sleep Apnea Risk in Diverse US Women

BACKGROUND

Poor sleep and history of weight cycling (HWC) are associated with worse cardiovascular health, yet limited research has evaluated the association between HWC and poor sleep patterns.

METHODS

The American Heart Association Go Red for Women Strategically Focused Research Network cohort at Columbia University (n = 506; mean age, 37 ± 15.7 years; 61% racial/ethnic minority) was used to evaluate the cross-sectional associations of HWC and sleep at baseline and the prospective associations of HWC from baseline with sleep at the 1-year visit. History of weight cycling, defined as losing and gaining 10 lb or more at least once (excluding pregnancy), was self-reported. Sleep duration, sleep quality, insomnia severity, and obstructive sleep apnea risk were assessed using the validated Pittsburgh Sleep Quality Index, Insomnia Severity Index, and Berlin questionnaires. Linear and logistic regression models, adjusted for age, race/ethnicity, education, health insurance status, pregnancy history, and menopausal status, were used to evaluate the relation of HWC with sleep.

RESULTS

Most women reported 1 or more episodes of weight cycling (72%). In linear models of cross-sectional and prospective data, each additional weight cycling episode was related to shorter sleep duration, poorer sleep quality, longer sleep onset latency, greater insomnia severity, more sleep disturbances, lower sleep efficiency, and higher sleep medication use frequency. In the logistic models, HWC (≥1 vs 0 episodes) was associated with greater odds for short sleep, poor sleep quality, long sleep onset latency (≥26 minutes), high obstructive sleep apnea risk, and sleep efficiency lower than 85%.

CONCLUSION

History of weight cycling predicted poor sleep among women, suggesting that weight maintenance may represent an important strategy to promote sleep health. The potential bidirectional relationship between HWC and sleep requires further investigation.

Exceeding body composition standards is associated with a more negative body image and increased weight cycling in active duty U.S. soldiers

Negative body image is more often identified in individuals with overweight or obesity. More than 65% of U.S. soldiers have a body mass index (BMI) that classifies them with overweight or obesity. Additionally, all soldiers must meet body composition and physical fitness standards which may increase the risk of negative body image. This cross-sectional study aimed to identify associations between compliance with body composition standards, body image, and weight cycling through surveying 969 active-duty soldiers (86% male, 24.0 ± 5.5 years of age, BMI 26.0 ± 3.6 kg/m²). Compliance with body composition standards was measured by whether a soldier had ever taken and failed the circumference-based body fat assessment. Weight cycling was self-reported as ≥3 weight fluctuations of ≥5% of body weight during their military career. Multivariate linear and logistic regression models were used to examine the relationship between compliance with body composition standards, body image, weight cycling, and sociodemographic characteristics while controlling for BMI. Failing the circumference-based body fat assessment was associated with increased concern with conforming to military image. Negative body image was associated with higher odds of weight cycling. Further examination is warranted to understand the effects of body composition standards on soldiers' body image and weight cycling.

Association between BMI variability and risk of fracture among Korean men and women: a population based study

In Korean adults aged 50 years and older, the overall risk of fractures increased with greater BMI variability among both men and women, specifically, spinal fractures for men and both spinal and hip fractures for women.

PURPOSE

The bone-health-related outcome, such as fractures due to BMI fluctuation, has been understudied within Asian populations. In this large-scale, population-based cohort study in Korea, we aimed to investigate the relationship between variability in body mass index (BMI) and the risk of fractures.

METHODS

The study included 166,932 subjects aged ≥ 50 years from the National Health Insurance Service-Health Screening Cohort. The BMI variability value from three follow-up examinations during 2002-2007 was categorized into quartiles. The hazard ratios (HRs) with 95% confidence intervals (CIs) for the effects of BMI variability on the risk of admission from hip, spine, and upper extremity fractures during 2008-2015 were evaluated using a Cox proportional hazards regression analysis.

RESULTS

Compared to those in the lowest BMI variability (1st quartile), men in the highest BMI variability (4th quartile) showed an increased risk of spinal fractures (aHR 1.21, 95% CI 1.07-1.36) with a significant linear trend (P for trend = 0.021). Compared to those in the lowest BMI variability (1st quartile), women in the highest BMI variability (4th quartile) showed an increased risk of hip and spinal fractures (aHR 1.35, 95% CI 1.05-1.69; aHR 1.16, 95% CI 1.05-1.28) with significant linear trends (P for trend = 0.021; P for trend = 0.003, respectively). There was no association between BMI variability and incidents of upper extremity fractures for men or women.

CONCLUSION

Association between BMI variability and increased fracture risk depended on sex and fracture types. BMI maintenance, instead of high BMI fluctuation, may be beneficial in terms of lowering the overall fracture risk for Korean adults over 50 years old.

Weight cycling practices in sport: A risk factor for later obesity?

Weight cycling, repeated cycles of weight loss and weight regain over time, is commonplace amongst many population groups. Although the effect of weight cycling on future obesity and cardiometabolic risk is still hotly debated, evidence does indicate that individuals who were normal weight prior to weight cycling are more susceptible to its adverse consequences than those who were overweight or with obesity. Athletes, and particularly those who compete in the so-called weight-sensitive sports, are prone to dieting and weight cycling practice owing to the competitive advantage to be gained from manipulating their body weight. However, in comparison with the general population, athletes tend to be leaner and weight loss phases more rapid and superimposed on a background of a high level of physical activity. In this context, it can be questioned whether weight cycling in this subpopulation will indeed increase risk for future obesity. It is perhaps surprising that despite recognition that athletes commonly partake in weight cycling during their career, studies are scarce and firm conclusions regarding the effect of this practice on future cardiometabolic risk remain to be drawn. In this review, we examine weight cycling prevalence and strategies in athletes and the current evidence relating to its short- and long-term consequences. In addition, a conceptual framework relating the dynamics of weight loss and recovery to athlete characteristics will be discussed, highlighting the need for well-controlled, prospective studies in this specific subpopulation.

Physiological Responses of Post-Dietary Effects: Lessons from Pre-Clinical and Clinical Studies

Dieting regimens such as calorie restriction (CR) are among the most commonly practiced interventions for weight management and metabolic abnormalities. Due to its independence from pharmacological agents and considerable flexibility in regimens, many individuals turn to dieting as a form of mitigation and maintenance of metabolic health. While metabolic benefits of CR have been widely studied, weight loss maintenance and metabolic benefits are reported to be lost overtime when the diet regimen has been terminated—referred to as post-dietary effects. Specifically, due to the challenges of long-term adherence and compliance to dieting, post-dietary repercussions such as body weight regain and loss of metabolic benefits pose as major factors in the efficacy of CR. Intermittent fasting (IF) regimens, which are defined by periodic energy restriction, have been deemed as more flexible, compliant, and easily adapted diet interventions that result in many metabolic benefits which resemble conventional CR diets. Many individuals find that IF regimens are easier to adhere to, resulting in fewer post-dietary effects; therefore, IF may be a more effective intervention. Unfortunately, there is a severe gap in current research regarding IF post-dietary effects. We recognize the importance of understanding the sustainability of dieting; as such, we will review the known physiological responses of CR post-dietary effects and its potential mechanisms through synthesizing lessons from both pre-clinical and clinical studies. This review aims to provide insight from a translational medicine perspective to allow for the development of more practical and effective diet interventions. We suggest more flexible and easily practiced dieting regimens such as IF due to its more adaptable and practical nature.

The impact of early body-weight variability on long-term weight maintenance: exploratory results from the NoHoW weight-loss maintenance intervention

BACKGROUND

Weight-loss programmes often achieve short-term success though subsequent weight regain is common. The ability to identify predictive factors of regain early in the weight maintenance phase is crucial.

OBJECTIVE

To investigate the associations between short-term weight variability and long-term weight outcomes in individuals engaged in a weight-loss maintenance intervention.

METHODS

The study was a secondary analysis from The NoHoW trial, an 18-month weight maintenance intervention in individuals who recently lost ≥5% body weight. Eligible participants (n = 715, 64% women, BMI = 29.2 (SD 5.0) kg/m², age = 45.8 (SD 11.5) years) provided body-weight data by smart scale (Fitbit Aria 2) over 18 months. Variability in body weight was calculated by linear and non-linear methods over the first 6, 9 and 12 weeks. These estimates were used to predict percentage weight change at 6, 12, and 18 months using both crude and adjusted multiple linear regression models.

RESULTS

Greater non-linear weight variability over the first 6, 9 and 12 weeks was associated with increased subsequent weight in all comparisons; as was greater linear weight variability measured over 12 weeks (up to AdjR² = 4.7%). Following adjustment, 6-week weight variability did not predict weight change in any model, though greater 9-week weight variability by non-linear methods was associated with increased body-weight change at 12 (∆AdjR² = 1.2%) and 18 months (∆AdjR² = 1.3%) and by linear methods at 18 months (∆AdjR² = 1.1%). Greater non-linear weight variability measured over 12 weeks was associated with increased weight at 12 (∆AdjR² = 1.4%) and 18 (∆AdjR² = 2.2%) months; and 12-week linear variability was associated with increased weight at 12 (∆AdjR² = 2.1%) and 18 (∆AdjR² = 3.6%) months.

CONCLUSION

Body-weight variability over the first 9 and 12 weeks of a weight-loss maintenance intervention weakly predicted increased weight at 12 and 18 months. These results suggest a potentially important role in continuously measuring body weight and estimating weight variability.

Have Our Attempts to Curb Obesity Done More Harm Than Good?

Dieting is a common method for weight loss, maintenance, and prevention of weight gain, but the harmful outcomes of dieting are understudied. Dieting is typically advised for obese patients for the sake of their health, though this does not account for the many complicated factors surrounding obesity. We conducted a search through the PubMed database on obesity, dieting, and eating disorders and did not limit the study by population or year. We found studies showing that although dieting may cause short-term weight loss, it is associated with weight gain in the long-term. We also found studies assessing the negative psychological and physical outcomes of dieting. Though there are many studies that emphasize the negative psychological impact of dieting, few studies have explored how dieting may contribute to the development of eating disorders in the obese. Studies on the physical impact of dieting were less conclusive but warrant further study. While it is difficult to draw any substantial conclusions from the data, our results showed that dieting may carry more risks than benefits as a means to lose weight.

Psychological and weight history variables as predictors of short-term weight and body fat mass loss

OBJECTIVE

Identifying predictors of early weight loss may have value in predicting longer-term success in weight loss programmes. This study examined if weight history variables (ie, weight cycling history [WCH], age of onset of obesity [AOO]), and preintervention Three-Factor Eating Questionnaire (TFEQ) and Power of Food Scale (PFS) scores predicted weight loss (WL) and fat mass loss (FML) following a 3-week calorie restriction intervention.

METHODS

Thirty-two participants (19-60 y; body mass index [BMI] 30-39.9 kg/m2) participated in a 3-week calorie restriction intervention (1120 kcal/d) as part of a larger clinical trial with 28 completers included in the current analyses. Preintervention WCH, AOO, TFEQ, and PFS subscale scores were collected, and WL and FML were measured. Multiple linear regression analyses were performed to predict WL and FML for relevant covariates in this study.

RESULTS

WCH, AOO, preintervention TFEQ subscale scores, and PFS subscale scores did not predict WL (all Ps > .08) or FML (Ps > .06) except, PFS-food tasted scores significantly predicted WL (r = -0.40, P = .03).

CONCLUSION

Although these variables were not robust predictors, results for at least the PFS suggest there may be value in further exploring this measure using larger sample sizes.

How dieting might make some fatter: modeling weight cycling toward obesity from a perspective of body composition autoregulation

The notion that dieting makes some people fatter has in the past decade gained considerable interest from both epidemiological predictions and biological plausibility. Several large-scale prospective studies have suggested that dieting to lose weight is associated with future weight gain and obesity, with such predictions being stronger and more consistent among dieters who are in the normal range of body weight rather than in those with obesity. Furthermore, the biological plausibility that dieting predisposes people who are lean (rather than those with overweight or obesity) to regain more body fat than what had been lost (referred to as fat overshooting) has recently gained support from a re-analysis of data on body composition during weight loss and subsequent weight recovery from the classic longitudinal Minnesota Starvation Experiment. These have revealed an inverse exponential relationship between the amount of fat overshot and initial adiposity, and have suggested that a temporal desynchronization in the recoveries of fat and lean tissues, in turn residing in differences in lean-fat partitioning during weight loss vs. during weight recovery (with fat recovery faster than lean tissue recovery) is a cardinal feature of fat overshooting. Within a conceptual framework that integrates the relationship between post-dieting fat overshooting with initial adiposity, the extent of weight loss and the differential lean-fat partitioning during weight loss vs. weight recovery, we describe here a mathematical model of weight cycling to predict the excess fat that could be gained through repeated dieting and multiple weight cycles from a standpoint of body composition autoregulation.

Predicting 2-year weight loss through temporally specific earlier losses, relevant behaviors, and their psychological correlates: Implications for behavioral treatment architectures

Maintaining loss of weight beyond an initial 6-9 months remains problematic, with research indicating little recent progress. A poor understanding of how and when prior weight loss, behavioral changes, and psychosocial predictors are associated with long-term weight changes persists. To better-inform behavioral treatments for long-term success with weight loss, women with obesity (N = 86; M_age  = 48.6 years) volunteered for research incorporating community-based weight-management treatments. They were assessed at months 6, 12, and 24 on theory-based psychosocial and behavioral factors, and over 24 months on weight. Considering the included times and temporal ranges, it was found that change in weight from month 6-24 was the strongest predictor of 24-month weight change, and physical activity and fruit/vegetable intake at month 24 best predicted that change in weight. Self-regulation, self-efficacy, and mood at month 24 best predicted both physical activity and fruit/vegetable intake at month 24, with body satisfaction also a significant predictor of physical activity. From these data, mediation analyses found that the predictions of long-term weight loss by scores of self-regulation, self-efficacy, body satisfaction, and mood at month 24 were significantly mediated by fruit/vegetable intake and physical activity in separate equations. Findings indicated both psychosocial and behavioral targets, and timing for those targets, most indicative of long-term success with weight loss.

Weight variability during self-monitored weight loss predicts future weight loss outcome

BACKGROUND

Obesity treatments often do not produce long-term results. It is therefore critical to better understand biological and behavioral correlates or predictors of future weight change.

OBJECTIVE

We tested the hypothesis that greater weight variability, independent of total body weight change, during early weight loss would predict degree of long-term success.

SUBJECTS/METHODS

We included 24,009 American users of the Withings smart scale with over a year's worth of self-monitored weight data. Multilevel modeling was used to calculate weight variability as the root mean square error around participants' weight trajectory regression line, using weekly average weights from the first 12 weeks of weight loss. Linear regressions were then used to examine whether weight variability predicted weight change from week 12 to week 48, 72, and 96.

RESULTS

Greater weight variability predicted less weight loss/more weight regain at week 48 (b ± SE: 1.18 ± 0.17, p < 0.001), week 72 (b ± SE: 1.45 ± 0.21, p < 0.001), and week 96 (b ± SE: 1.45 ± 0.23, p < 0.001), controlling for baseline BMI and overall weight change during the first 12 weeks. An interaction effect was found between weight variability and baseline BMI such that the relationship between weight variability and later weight change was stronger in individuals with lower baseline BMI.

CONCLUSIONS

This study found that in a large population sample, weight variability early on during weight loss significantly predicted longer term weight loss outcomes. The results provide further support that weight variability be considered an important predictor of future weight change. Research is needed to understand the mechanisms underlying this effect.

Effects of multiple cycles of weight loss and regain on the body weight regulatory system in rats

We studied the effects of multiple cycles of weight loss and regain on the defended body weight in rats. Thirty-six male Wistar rats were divided into three weight-matched groups: weight cyclers (n = 18), ad libitum-fed controls (n = 9), and maturity controls (n = 9). Cyclers underwent four rounds of 20% weight loss from 50% caloric restriction, each cycle followed by recovery to stable plateau weight on ad libitum feeding. Controls ate ad libitum. Maturity controls ate ad libitum and then weight cycled the final two rounds to evaluate the effect of age in later cycles. Cyclers' postdiet plateau weight became progressively lower than that of controls. With each weight loss, ghrelin increased, while insulin and leptin decreased; the magnitude of these changes did not differ across cycles. After four rounds, cyclers' weight (504 ± 7 vs. 540 ± 22 g; P < 0.05) and percent body fat (11.7 vs. 15.2%; P < 0.05) were lower than in controls. After a 4-mo follow-up period of ad libitum feeding, cyclers maintained a lower total fat-pad mass versus controls (8.6 ± 0.5 vs. 15.9 ± 3.6 g; P < 0.01) and a lower glucose area-under-the-curve on oral glucose tolerance tests (P < 0.05). Repeated weight-loss cycles exerted positive effects, durably lowering defended levels of body adiposity and improving glucose tolerance.

Differing Impact of Weight Cycling on Ambulatory Blood Pressure versus Conventional Blood Pressure Assessment: A Possible Explanation to Controversy

Background

Weight cycling (WC) is a widespread behavior associated with elevated laboratory blood pressure (BP). The impact WC may have on ambulatory BP (ABP) is unknown.

Methods

Impact of self-reported WC history on ABP was assessed via cross-sectional nonexperimental design. Sixty-five women completed the Weight and Lifestyle Inventory (WALI) questionnaire. The WALI has been shown to be a reliable index of WC (r=0.87, P<0.001). Data were analyzed looking at WC both as a continuous and criterion variable, and subjects were dichotomized as either WC or non-WC (NWC).

Results

WC (n=31) were older (39.7±8.9 vs. 33.1±11.3 years), had a higher percent body fat (47.1%±6.2% vs. 41.4%±7.8%), and were less fit (21.2±5.4 vs. 26.7±7.6 mL/kg/min) than NWC (n=34). No significant correlation between laboratory systolic BP (SBP, P=0.830) or diastolic BP (DBP, P=0.997) and WC was observed. A significant correlation between the number of WC and systolic ABP (r=0.326, P=0.010) and trend for diastolic ABP (r=0.238, P=0.065) was found. SBP (23% vs. 17%, P<0.001) and DBP (13% vs. 9%, P<0.001) load was higher for WC compared to NWC women.

Conclusion

WC may deleteriously affect BP outcomes that might only be observed when ABP monitoring is used.

Effects of weight-neutral approaches compared with traditional weight-loss approaches on behavioral, physical, and psychological health outcomes: a systematic review and meta-analysis

Context

Weight-neutral approaches for health are emerging therapeutic alternatives to traditional weight-loss approaches. The existing literature base comparing these approaches has not yet been systematically evaluated by a meta-analysis.

Objective

This review aims to determine if weight-neutral approaches are valid alternatives to weight-loss approaches for improving physical, psychological, and behavioral health outcomes.

Data Sources

Embase, Scopus, PsycINFO, PubMed, CINAHL, and the University of Queensland Library databases were searched.

Study Selection

Peer-reviewed, experimental, or quasi-experimental studies that included weight-neutral and weight-loss arms and reported physical, psychological, or behavioral outcomes were eligible. A total of 525 studies were identified through initial database searches, with 10 included in the final analysis after exclusion criteria were applied.

Data Extraction

Screening and eligibility assessment of studies followed the PRISMA protocol. The following outcomes were extracted: weight, body mass index, lipid and glucose variables, blood pressure, eating behavior, self-esteem, depression, quality of life, physical activity, and diet quality.

Data Analysis

Studies were graded per the National Health and Medical Research Council (NHMRC) level-of-evidence tool and the Academy of Nutrition and Dietetics quality-evaluation tool. Effect sizes were examined as a meta-analysis of standardized and mean differences using a random-effects inverse-variance model with 95%CIs. Practice recommendations for each outcome were graded per NHMRC body-of-evidence guidelines.

Conclusions

Weight-neutral approaches resulted in greater improvement in bulimia (P = 0.02), but no significant differences were observed for any other outcome. Weight-neutral approaches may be as effective as weight-loss methods for improving physical, psychological, and behavioral outcomes. Limitations include inconsistent definitions of both approaches and variable time frames of follow-up.

Self-report dieting and long-term changes in body mass index and waist circumference

OBJECTIVE

This prospective study explores whether dieting attempts and previous changes in weight predict changes in body mass index (BMI) and waist circumference (WC).

METHODS

The study was based on the representative Finnish Health 2000 Survey and on its follow-up examination 11 years later. The sample included 2,785 participants, aged 30-69. BMI and WC were determined at health examinations. Information on dieting attempts and previous changes in weight was collected using a questionnaire including questions on whether participant had tried to lose weight (no/yes), gained weight (no/yes) or lost weight (no/yes) during the previous year.

RESULTS

At baseline, 32.8% were dieters. Of these, 28.4% had lost weight during the previous year. Dieters had higher BMI and WC than non-dieters. During the follow-up, the measures increased more in dieters and in persons with previous weight loss. The mean BMI changes in non-dieters versus dieters were 0.74 (standard deviation [SD] 2.13) kg/m2 and 1.06 (SD 2.77) kg/m2 (P = 0.002), respectively. The corresponding numbers for those with no previous weight change versus those who had lost weight were 0.65 (SD 2.07) kg/m2 and 1.52 (SD 2.61) kg/m2. The increases in BMI and WC were most notable in dieters with initially normal weight.

CONCLUSIONS

The increases in BMI and WC were greater in dieters than in non-dieters, suggesting dieting attempts to be non-functional in the long term in the general population.

Metabolic dysfunction following weight regain compared to initial weight gain in a high-fat diet-induced obese mouse model

Diet-induced weight loss and regain leads to physiological and metabolic changes, some of which are potentially harmful. However, the specific metabolic processes and dysfunctions associated with weight regain, and how they differ from initial weight gain, remain unclear. Thus, we examined the metabolic profiles of mice following weight regain compared to initial weight gain. Mice were fed a normal diet or a high-fat diet or were cycled between the two diets to alternate between obese and lean states. Liver samples were collected and hepatic metabolites were profiled using nuclear magnetic resonance (NMR). The identified metabolites associated with weight regain were quantified using gas chromatography/mass spectrometry (GC/MS) and lipid profiles were assessed using ultra-high-performance liquid chromatography-quadrupole time-of-flight MS (UPLC-QTOF-MS). In addition, changes in expression of pro-inflammatory cytokines and gluconeogenic enzymes were investigated using polymerase chain reaction (PCR) and western blotting, respectively. Hepatic levels of several amino acids were reduced in mice during weight regain compared with initial weight gain. In addition, gluconeogenic enzyme levels were increased following weight regain, indicating an up-regulation of gluconeogenesis. Lipidomic profiling revealed that levels of ceramide and sphingomyelin, which are related to obesity-induced inflammation, were significantly increased during weight regain compared to initial weight gain. Moreover, tumor necrosis factor-α (TNF-α) and transforming growth factor-β1 (TGF-β1) levels were significantly up-regulated during weight regain. In this study, weight regains lead to an up-regulation of gluconeogenesis and aggravated inflammation. Additionally, weight regain can worsen the metabolic dysfunction associated with obesity.

Trajectories of body mass index among active-duty U.S. Army soldiers, 2011-2014

Establishing the shape and determinants of trajectories of body mass index (BMI) among Soldiers is critical given the importance of weight management to military service requirements. To establish the shape and determinants of BMI trajectories among Soldiers, we aimed to (1) model the overall BMI trajectory of Soldiers, (2) find the most common trajectory groups among Soldiers, (3) investigate the relationship between BMI trajectories and sociodemographic and military-specific characteristics, and (4) determine if there were Soldiers with large fluctuations in BMI. The study population included all US Army Soldiers on active-duty between 2011 and 2014 who were age 17–62 (n = 827,126). With longitudinal data from the Stanford Military Data Repository, we used group-based trajectory modeling to identify the BMI trajectories of Soldiers and multinomial logistic regression to estimate associations between Soldier characteristics and trajectory membership. Four distinct BMI trajectory groups were found: increasing, decreasing, constant, and inconstant. The constant, increasing, and decreasing trajectories were similar in shape and percentage between men and women. The constant trajectory had the fewest Soldiers who exceeded weight standards or had duty limitations. The increasing trajectory was associated with marriage and fewer service years. The decreasing trajectory was associated with more service years and higher educational attainment. The inconstant trajectory differed in shape between men and women. Over 6% of men and 12% of women had fluctuations in BMI indicative of weight cycling. Understanding the characteristics associated with BMI trends may assist the Army in targeting resources aimed to improve Soldier health and combat readiness.

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Four BMI trajectory groups were found: increasing, decreasing, constant, inconstant.

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The constant trajectory had the fewest Soldiers who exceeded weight standards.

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The increasing trajectory was associated with marriage and fewer service years.

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The decreasing trajectory was associated with more service years and education.

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6% of men and 12% of women had fluctuations in BMI indicative of weight cycling.

Fatness and Fluctuating Body Weight: Effect on Central Vasculature

Weight Cycling (WC) is a prevalent behavior associated with adverse cardiovascular (CV) health. However, a 2010 review on the effects of WC and blood pressure (BP) determined that there was not enough evidence to draw definitive conclusions. Central BP is the principal predictor of CV risk compared to peripheral BP. The influence that WC may have specifically on central BP is unknown. Cross-sectional observation of self-reported history of WC on measures of CV health was undertaken. Seventy-five women completed a Weight and Lifestyle Inventory questionnaire, which is considered a reliable index of WC (r = 0.87, p < 0.001). Measures of visceral fat, BP, arterial stiffness, and VO2peak were taken. Regression equations were used to assess primary predictors of these outcomes. Seventy-five middle aged (39 ± 11 years), obese (32 ± 7 kg/m2), and relatively unfit (24 ± 8 ml·kg-1 min-1) women completed the study. Visceral fat was the strongest predictor of brachial systolic blood pressure (SBP; r2 = 0.283), brachial diastolic blood pressure (DBP; r2 = 0.176), central SBP (r2 = 0.375), and augmentation index (AIx; r2 = 0.535, all p < 0.001). VO2peak was the strongest predictor of central DBP (r2 = 0.062, p = 0.036) and augmentation pressure (AP; r2 = 0.491, p < 0.001). Weight cycling index was associated with visceral fat (r = 0.521, p < 0.001). Visceral fat was a mediator between WC and central SBP (confidence interval [CI] = 0.0053-0.0602), AP (CI = 0.0507-0.4915), AIx (CI = 0.0025-0.0699), and carotid-femoral pulse wave velocity (CI = 0.0115-0.1227; all p < 0.05). WC may increase visceral fat accumulation, which was associated with increased central SBP and measures of arterial stiffness.

Is weight cycling associated with adverse health outcomes? A cohort study

Evidence about the health effects of weight cycling is not consistent, with some studies suggesting it is harmful for health. Here we investigated whether weight cycling was associated with weight change and mental health outcomes in 10,428 participants in the mid-age cohort of The Australian Longitudinal Study of Women's Health (ALSWH) over 12years. In 1998 the women were asked how many times they had ever intentionally lost at least 5kg and how many times had they regained this amount. Women were categorised into four weight pattern groups: frequent weight cyclers (FWC, three or more weight cycles), low frequency weight cyclers (LFWC, one or two weight cycles), non-weight cyclers (NWC), and weight loss only (WL). We used generalised linear modelling to investigate relationships between weight pattern group, weight change and mental health outcomes. In 1998, 15% of the women were FWC, 24% LFWC, 46% NWC and 15% were WL. Weight change was similar across weight pattern groups in women with obesity, however healthy weight and overweight FWC gained more weight than women who did not weight cycle. We found no difference in overall mental health scores between groups, but both LFWC and FWC had higher odds of depressive symptoms (adjusted OR 1.5, 95%CI: 1.1 to 1.9 and 1.7, 95%CI: 1.1 to 2.4, respectively) than NWC. Our results suggest that, although weight cycling is not associated with greater weight gain in women with obesity, it may increase depressive symptoms.

Weight change and 15 year mortality: results from the European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) cohort study

Studies have reported a higher mortality risk associated with weight loss, particularly in middle-aged and older adults, although some of these studies did find that gaining weight was also associated with an increased mortality risk. We examined changes in weight in relation to mortality in a prospective population-based cohort study of men and women, resident in Norfolk, UK. Participants were assessed at baseline (1993–1997) and at a second examination (1998–2000), as part of the European Prospective Investigation into Cancer and Nutrition (EPIC-Norfolk) study, and followed up to 2015 for mortality. Participants with a self-reported history of cancer or cardiovascular disease, body mass index < 18.5 kg/m² or missing data on adjustment variables, at either time-point were excluded, leaving 12,580 participants, aged 39–78 in 1993–1997, eligible for analyses. Cox proportional hazards models were used to determine Hazard Ratios (HRs) for all-cause (2603 deaths), cardiovascular (749 deaths), cancer (981 deaths), respiratory (226 deaths) and other causes of mortality (647 deaths) by categories of weight change. After multivariate adjustment, the HRs (95% CIs) for all-cause mortality for men and women who lost more than 5 kg were 1.85 (1.48–2.31) and 1.64 (1.31–2.05) respectively. Higher hazards were also found for specific causes of mortality and weight loss > 5 kg. Similar associations were observed after excluding deaths in the first 5 years of follow-up. Results for weight gain were inconclusive. We conclude that objectively measured weight loss, but not weight gain, was associated with subsequent higher mortality risk in this population-based study of middle-aged and elderly men and women. However, undiagnosed, pre-existing disease and the inability to account for weight cycling need to be remembered when interpreting these results. Unravelling the causal pathways underlying this association will require more detailed studies, including that of changes in body composition.

Irregular Patterns in the Daily Weight Chart at Night Predict Body Weight Regain

This study examined whether charting daily weight patterns can predict weight regain in obese patients. The subjects were 98 moderately obese Japanese women aged 23 to 66 years who were obliged to precisely record their daily weights during the initial 4-month education period, but not thereafter. The patients were followed up at 8, 12, and 16 months. Abdominal fat areas and blood samples were assessed in the outpatient clinic at 0, 4, and 16 months. The standard deviations (SDs) of the differences in body weight between “after waking up” and “after breakfast” (SDa), “after dinner” (SDb), and “before going to bed” (SDc) were calculated, which were parameters reflecting the fluctuations in the daily weight patterns during the first 4 months. SDc, but not SDa or SDb, was correlated positively with weight regain at 8, 12, and 16 months (P = 0.049, P = 0.002, and P = 0.001, respectively). There were significant differences in temporal change in body weight and abdominal visceral fat between the small SDc group (SDc ≤25th percentile) and the large SDc group (SDc >75th percentile), but not for subcutaneous abdominal fat or the serum concentrations of glucose, insulin, or lipids. The results indicate that fluctuation of body weight immediately before going to bed is useful for predicting the rebound in body weight.

Psychosocial predictors of decay in healthy eating and physical activity improvements in obese women regaining lost weight: translation of behavioral theory into treatment suggestions

Regain of lost weight is a universal problem for behavioral treatments. An increased understanding of theory-based psychosocial predictors of decay in behavioral correlates of weight loss might improve treatments. Data were derived from a previous weight loss investigation of 110 women with obesity. A subsample from the experimental treatment who lost ≥3 % body weight and regained at least one third of that over 24 months (N = 36) was assessed. During months 6 through 24, there were unfavorable changes in behavioral (fruit/vegetable and sweet intake; physical activity) and psychosocial variables. Mood change predicted change in fruit/vegetable and sweet intake, with emotional eating change mediating the latter relationship. Change in self-regulation predicted changes in sweet and fruit/vegetable intake and physical activity, with self-efficacy mediating the self-regulation-fruit/vegetable intake and self-regulation-physical activity relationships. Findings suggest that after treatment-induced weight loss, addressing indicated theory-based psychosocial variables might mitigate decay in behavioral predictors of healthier weight.

Ideals versus reality: Are weight ideals associated with weight change in the population?

OBJECTIVE

To quantify weight ideals of young adults and to examine whether the discrepancy between actual and ideal weight is associated with 10-year body mass index (BMI) change in the population.

METHODS

This study comprised 4,964 adults from the prospective population-based FinnTwin16 study. They reported their actual and ideal body weight at age 24 (range 22-27) and 10 years later (attrition 24.6%). The correlates of discrepancy between actual and ideal body weight and the impact on subsequent BMI change were examined.

RESULTS

The discrepancy between actual and ideal weight at 24 years was on average 3.9 kg (1.4 kg/m(2) ) among women and 1.2 kg (0.4 kg/m(2) ) among men. On average, participants gained weight during follow-up irrespective of baseline ideal weight: women ¯x = +4.8 kg (1.7 kg/m(2) , 95% CI 1.6-1.9 kg/m(2) ), men ¯x = +6.3 kg (2.0 kg/m(2) , 95% CI 1.8-2.1 kg/m(2) ). Weight ideals at 24 years were not correlated with 10-year weight change. At 34 years, just 13.2% of women and 18.9% of men were at or below the weight they had specified as their ideal weight at 24 years. Women and men adjusted their ideal weight upward over time.

CONCLUSIONS

Irrespective of ideal weight at baseline, weight gain was nearly universal. Weight ideals were shifted upward over time.

Weight Loss and the Prevention of Weight Regain: Evaluation of a Treatment Model of Exercise Self-Regulation Generalizing to Controlled Eating

CONTEXT

For decades, behavioral weight-loss treatments have been unsuccessful beyond the short term. Development and testing of innovative, theoretically based methods that depart from current failed practices is a priority for behavioral medicine.

OBJECTIVE

To evaluate a new, theory-based protocol in which exercise support methods are employed to facilitate improvements in psychosocial predictors of controlled eating and sustained weight loss.

METHODS

Women with obesity were randomized into either a comparison treatment that incorporated a print manual plus telephone follow-ups (n = 55) or an experimental treatment of The Coach Approach exercise-support protocol followed after 2 months by group nutrition sessions focused on generalizing self-regulatory skills from an exercise support to a controlled eating context (n = 55). Repeated-measures analysis of variance contrasted group changes in weight, physical activity, fruit and vegetable intake, mood, and exercise- and eating-related self-regulation and self-efficacy over 24 months. Regression analyses determined salient interrelations of change scores over both the weight-loss phase (baseline-month 6) and weight-loss maintenance phase (month 6-month 24).

RESULTS

Improvements in all psychological measures, physical activity, and fruit and vegetable intake were significantly greater in the experimental group where a mean weight loss of 5.7 kg (6.1% of initial body weight) occurred at month 6, and was largely maintained at a loss of 5.1 kg (5.4%) through the full 24 months of the study. After establishing temporal intervals for changes in self-regulation, self-efficacy, and mood that best predicted improvements in physical activity and eating, a consolidated multiple mediation model suggested that change in self-regulation best predicted weight loss, whereas change in self-efficacy best predicted maintenance of lost weight.

CONCLUSIONS

Because for most participants loss of weight remained greater than that required for health benefits, and costs for treatment administration were comparatively low, the experimental protocol was considered successful. After sufficient replication, physician referral and applications within health promotion and wellness settings should be considered.

The relationship between night work and involuntary weight change: data from the fifth Korea National Health and Nutrition Examination Survey (KNHANES 2010-2012)

Background

Previous studies on the association between shift or night work and weight change have been focused on finding the risk of weight gain caused by shift or night work. In this study, we aimed to reveal the risk of weight gain and weight loss associated with night work by using a nationwide representative data.

Methods

This study was performed on 1605 full-time wage workers between the age of 20 and 69 based on the fifth Korea National Health and Nutrition Examination Survey (KNHANES 2010–2012). The association between night work and involuntary weight change in the previous year was divided into the categories of weight gain and weight loss and studied with modifications in socio-demographic variables, health behavior-related variables, and occupational characteristic variables.

Results

The participants working in night work accounted for 10.6 % of total study participants (male; 11.9 %, female 7.4 %). Workers who worked more than 48 hours per week on average accounted for 41.6 % of the total study participants (male; 46.3 %, female 29.1 %).

Odds ratio (OR) of weight loss associated with night work in male workers was 0.34 (95 % confidence interval (CI) 0.16–0.76) after controlling for several related factors. OR of weight loss associated with night work in female workers with long working hours was 1.95 (95 % CI 0.47–80.86) and that of weight gain was 2.83 (95 % CI 0.12–69.83) after adjusting associated factors.

Conclusions

In this cross-sectional study with national representative sample, night work may lower the risk of weight loss in male workers and induce weight change (weight loss or weight gain) in female workers with long working hours. Therefore, future studies with cohort study design for night workers are needed to reveal the mechanisms and health effects of weight change associated with night work and establish proper management solutions with health and labor policies for Korean night workers.

Short-term variability in body weight predicts long-term weight gain

BACKGROUND

Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation.

OBJECTIVE

In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo.

DESIGN

A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later.

RESULTS

Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting.

CONCLUSIONS

Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131.

Weight cycling and cancer incidence in a large prospective US cohort

Weight cycling, which consists of repeated cycles of intentional weight loss and regain, is common among individuals who try to lose weight. Some evidence suggests that weight cycling may affect biological processes that could contribute to carcinogenesis, but whether it is associated with cancer risk is unclear. Using 62,792 men and 69,520 women enrolled in the Cancer Prevention Study II Nutrition Cohort in 1992, we examined the association between weight cycling and cancer incidence. Weight cycles were defined by using baseline questions that asked the number of times ≥10 pounds (4.54 kg) was purposely lost and later regained. Multivariable-adjusted hazard ratios and 95% confidence intervals for all cancer and 15 individual cancers were estimated by using Cox proportional hazards regression. During up to 17 years of follow-up, 15,333 men and 9,984 women developed cancer. Weight cycling was not associated with overall risk of cancer in men (hazard ratio = 0.96, 95% confidence interval: 0.83, 1.11 for ≥20 cycles vs. no weight cycles) or women (hazard ratio = 0.96, 95% confidence interval: 0.86, 1.08) in models that adjusted for body mass index and other covariates. Weight cycling was also not associated with any individual cancer investigated. These results suggest that weight cycling, independent of body weight, is unlikely to influence subsequent cancer risk.

Weight changes following the diagnosis of type 2 diabetes: the impact of recent and past weight history before diagnosis. results from the Danish Diabetes Care in General Practice (DCGP) study

Aims

The association between recent and more distant weight changes before and after the diagnosis of type 2 diabetes has been little researched. The aim of this study is to determine the influence of patients’ weight history before diabetes diagnosis on the observed 6-year weight changes after diagnosis.

Methods

A clinical cohort study combined with self-reported past weight history. In total 885 patients aged ≥40 years and newly diagnosed with clinical type 2 diabetes were included. Body weight was measured immediately after diabetes diagnosis and again at the 6-year follow up examination (median, 5.7 years). At diagnosis patients reported their weight 1 year and 10 years previously, and also at the age of 20. Multivariate linear regression analyses controlled for 20 baseline patient characteristics.

Results

The median (interquartile range) age at diagnosis was 63.2 (53.9; 71.4) years. Median body weight was 80.0 (72.0; 90.0) kg 10 years before diagnosis, 85.0 (75.0; 95.0) kg 1 year before diagnosis, 82.4 (72.0; 94.0) kg at diagnosis, and 80.0 (70.0; 91.1) kg at 6-year follow up. Each kg of weight gain during the year preceding the diagnosis was associated with a weight change (95% CI) of -0.20 (-0.28; -0.13) kg during the follow up period. In all models age and body mass index at diagnosis predicted future weight changes, while the weight at age 20 (-0.01 (-0.06; 0.03) kg/kg), and the weight change from 10 years to 1 year before diagnosis (-0.01 (-0.06; 0.04) kg/kg), did not predict weight change after diagnosis.

Conclusions

During the first on average 5.7 years after diagnosis of type 2 diabetes, patients generally follow a course of declining average weight, and these weight developments are related primarily to recent weight changes, body mass index, and age, but not to the more distant weight history.

How dieting makes the lean fatter: from a perspective of body composition autoregulation through adipostats and proteinstats awaiting discovery

Whether dieting makes people fatter has been a subject of considerable controversy over the past 30 years. More recent analysis of several prospective studies suggest, however, that it is dieting to lose weight in people who are in the healthy normal range of body weight, rather than in those who are overweight or obese, that most strongly and consistently predict future weight gain. This paper analyses the ongoing arguments in the debate about whether repeated dieting to lose weight in normal-weight people represents unsuccessful attempts to counter genetic and familial predispositions to obesity, a psychosocial reaction to the fear of fatness or that dieting per se confers risks for fatness and hence a contributing factor to the obesity epidemic. In addressing the biological plausibility that dieting predisposes the lean (rather than the overweight or obese) to regaining more body fat than what had been lost (i.e. fat overshooting), it integrates the results derived from the re-analysis of body composition data on fat mass and fat-free mass (FFM) losses and recoveries from human studies of experimental energy restriction and refeeding. These suggest that feedback signals from the depletion of both fat mass (i.e. adipostats) and FFM (i.e. proteinstats) contribute to weight regain through the modulation of energy intake and adaptive thermogenesis, and that a faster rate of fat recovery relative to FFM recovery (i.e. preferential catch-up fat) is a central outcome of body composition autoregulation in lean individuals. Such a temporal desynchronization in the restoration of the body's fat vs. FFM results in a state of hyperphagia that persists beyond complete recovery of fat mass and interestingly until FFM is fully recovered. However, as this completion of FFM recovery is also accompanied by fat deposition, excess fat accumulates. In other words, fat overshooting is a prerequisite to allow complete recovery of FFM. This confers biological plausibility for post-dieting fat overshooting - which through repeated dieting and weight cycling would increase the risks for trajectories from leanness to fatness. Given the increasing prevalence of dieting in normal-weight female and male among young adults, adolescents and even children who perceive themselves as too fat (due to media, family and societal pressures), together with the high prevalence of dieting for optimizing performance among athletes in weight-sensitive sports, the notion that dieting and weight cycling may be predisposing a substantial proportion of the population to weight gain and obesity deserves greater scientific scrutiny.

Dieting: proxy or cause of future weight gain?

The relationship between dieting and body mass has a long and controversial history. This paper aims to help resolve this issue by making two key distinctions. The first is between dieting as a cause of weight gain/regain and as a proxy risk factor for identifying non-obese individuals prone to weight gain for reasons other than dieting. The second is between the body mass that is attained following one or more weight loss/regain cycles and the body mass that might have been reached had dieting never been undertaken. Evidence is reviewed on the relation between recent diet-induced weight loss and sustained weight loss (weight suppression), on the one hand, and weight regain, on the other hand. Furthermore, the reason that a history of dieting in non-obese individuals reflects a susceptibility to future weight gain is explained. It is concluded that (i) diet-induced weight loss hastens weight regain but a history of weight loss diets does not cause weight gain beyond that which would occur in the absence of dieting, and (ii) weight loss dieting in non-obese individuals does not cause future weight gain but is simply a proxy risk factor reflecting a personal vulnerability to weight gain and living in an obesogenic environment.

Dieting and weight cycling as risk factors for cardiometabolic diseases: who is really at risk?

Despite the poor prognosis of dieting in obesity management, which often results in repeated attempts at weight loss and hence weight cycling, the prevalence of dieting has increased continuously in the past decades in parallel to the steadily increasing prevalence of obesity. However, dieting and weight cycling are not limited to those who are obese or overweight as substantial proportions of the various population groups with normal body weight also attempt to lose weight. These include young and older adults as well as children and adolescents who perceive themselves as too fat (due to media, parental and social pressures), athletes in weight-sensitive competitive sports (i.e. mandatory weight categories, gravitational and aesthetic sports) or among performers for whom a slim image is professionally an advantage. Of particular concern is the emergence of evidence that some of the potentially negative health consequences of repeated dieting and weight cycling are more readily seen in people of normal body weight rather than in those who are overweight or obese. In particular, several metabolic and cardiovascular risk factors associated with weight cycling in normal-weight individuals have been identified from cross-sectional and prospective studies as well as from studies of experimentally induced weight cycling. In addition, findings from studies of experimental weight cycling have reinforced the notion that fluctuations of cardiovascular risk variables (such as blood pressure, heart rate, sympathetic activity, blood glucose, lipids and insulin) with probable repeated overshoots above normal values during periods of weight regain put an additional stress on the cardiovascular system. As the prevalence of diet-induced weight cycling is increasing due to the opposing forces of an 'obesigenic' environment and the media pressure for a slim figure (that even targets children), dieting and weight cycling is likely to become an increasingly serious public health issue.

Gaining weight after taking orlistat: A qualitative study of patients at 18-months follow-up

Orlistat is currently the only prescribed form of pharmacological management for obesity and functions by reducing the amount of fat absorbed from food eaten. Although frequently prescribed, there is marked variability in outcomes. A total of 10 participants’ experiences of gaining weight after taking orlistat were analysed using thematic analysis. Participants attributed their failed weight loss to mechanisms of the medication, emphasised a medical model of obesity with barriers to their weight loss and other weight-loss methods which had also failed. Overall, their weight gain was considered an inevitable part of their self-identity, reflecting their self-fulfilling prophecy of being a perpetual dieter.

Weight cycling promotes fat gain and altered clock gene expression in adipose tissue in C57BL/6J mice

Repeated attempts to lose weight by temporary dieting may result in weight cycling, eventually further gain of body fat, and possible metabolic adaptation. We tested this with a controlled experiment in C57BL/6J mice subjected to four weight cycles (WC), continuous hypercaloric feeding (HF), or low-fat feeding (LF). To search for genes involved in an adaptive mechanism to former weight cycling and avoid acute effects of the last cycle, the last hypercaloric feeding period was prolonged by an additional 2 wk before euthanization. Total energy intake was identical in WC and HF. However, compared with HF, the WC mice gained significantly more total body mass and fat mass and showed increased levels of circulating leptin and lipids in liver. Both the HF and WC groups showed increased adipocyte size and insulin resistance. Despite these effects, we also observed an interesting maintenance of circulating adiponectin and free fatty acid levels after WC, whereas changes in these parameters were observed in HF mice. Global gene expression was analyzed by microarrays. Weight-cycled mice were characterized by a downregulation of several clock genes (Dbp, Tef, Per1, Per2, Per3, and Nr1d2) in adipose tissues, which was confirmed by quantitative PCR. In 3T3-L1 cells, we found reduced expression of Dbp and Tef early in adipogenic differentiation, which was mediated via cAMP-dependent signaling. Our data suggest that clock genes in adipose tissue may play a role in metabolic adaptation to weight cycling.

Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women

Background

Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population.

Methods

We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample).

Results

Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63–0.65) in the derivation sample and 0.57 (95% CI  = 0.56–0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥200 points were 9% and 96%, respectively.

Conclusion

The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

Clinically important body weight gain following knee arthroplasty: a five-year comparative cohort study

OBJECTIVE

The impact of knee arthroplasty on body weight has not been fully explored. Clinically important weight gain following knee arthroplasty would pose potentially important health risks.

METHODS

We used one of the largest US-based knee arthroplasty registries and a population-based control sample from the same geographic region to determine whether knee arthroplasty increases the risk of clinically important weight gain of ≥5% of baseline body weight over a 5-year postoperative period.

RESULTS

Of the persons in the knee arthroplasty sample, 30.0% gained ≥5% of baseline body weight 5 years following surgery as compared to 19.7% of the control sample. The multivariable-adjusted (age, sex, body mass index, education, comorbidity, and presurgical weight change) odds ratio (OR) was 1.6 (95% confidence interval [95% CI] 1.2-2.2) in persons with knee arthroplasty as compared to the control sample. Additional arthroplasty procedures during followup further increased the risk for weight gain (OR 2.1, 95% CI 1.4-3.1) relative to the control sample. Specifically, among patients with knee arthroplasty, younger patients and those who lost greater amounts of weight in the 5-year preoperative period were at greater risk for clinically important weight gain.

CONCLUSION

Patients who undergo knee arthroplasty are at an increased risk of clinically important weight gain following surgery. The findings potentially have broad implications to multiple members of the health care team. Future research should develop weight loss/maintenance interventions particularly for younger patients who have lost a substantial amount of weight prior to surgery, as they are most at risk for substantial postsurgical weight gain.

No effect of weight cycling on the post-career BMI of weight class elite athletes

Background

Repetitions of pre-competition weight-loss diets done by athletes participating in weight class sports can be regarded as periods of weight cycling. The aim of the present study is to identify the long term post-career (22 years) evolutionary profile of athletes’ BMI after such weight cycling.

Methods

One hundred and thirty-six retired French athletes who participated in major international competitions in weight class sports (rowers, wrestlers, boxers, and judokas) were included. Former and current body mass, height, dietary characteristics during the career (annual frequency, amount of weight lost), current physical activity, and answers on the eating-attitude test were collected by phone interview (consistency was tested by comparison with measured weight). We performed ANOVA tests for comparison between groups (sport, dieting), post-hoc tests (Bonferroni test) to identify differences within groups. BMI’s changes were treated using a mixed model.

Results

The recorded weight changes did not depend upon time since retirement. Between 18 y and 50 y, athletes’ BMI increased by 3.2 kg/m² compared to the 4.2 kg/m² increase in the general population. This increase was independent of the number of diets during the career. Retired athletes declared a mean weekly physical activity of 4.8 h ± 4.3. The eating-attitude test showed low scores for all sports without any correlation to diet characteristics.

Conclusion

Weight cycling during an athletic career does not induce a massive weight gain after retirement, probably due to the high level of physical activity still practiced after retirement by these athletes.

Macronutrient composition of the diet and prospective weight change in participants of the EPIC-PANACEA study

BACKGROUND

The effect of the macronutrient composition of the usual diet on long term weight maintenance remains controversial.

METHODS

373,803 subjects aged 25-70 years were recruited in 10 European countries (1992-2000) in the PANACEA project of the EPIC cohort. Diet was assessed at baseline using country-specific validated questionnaires and weight and height were measured at baseline and self-reported at follow-up in most centers. The association between weight change after 5 years of follow-up and the iso-energetic replacement of 5% of energy from one macronutrient by 5% of energy from another macronutrient was assessed using multivariate linear mixed-models. The risk of becoming overweight or obese after 5 years was investigated using multivariate Poisson regressions stratified according to initial Body Mass Index.

RESULTS

A higher proportion of energy from fat at the expense of carbohydrates was not significantly associated with weight change after 5 years. However, a higher proportion of energy from protein at the expense of fat was positively associated with weight gain. A higher proportion of energy from protein at the expense of carbohydrates was also positively associated with weight gain, especially when carbohydrates were rich in fibre. The association between percentage of energy from protein and weight change was slightly stronger in overweight participants, former smokers, participants ≥60 years old, participants underreporting their energy intake and participants with a prudent dietary pattern. Compared to diets with no more than 14% of energy from protein, diets with more than 22% of energy from protein were associated with a 23-24% higher risk of becoming overweight or obese in normal weight and overweight subjects at baseline.

CONCLUSION

Our results show that participants consuming an amount of protein above the protein intake recommended by the American Diabetes Association may experience a higher risk of becoming overweight or obese during adult life.

History of weight cycling does not impede future weight loss or metabolic improvements in postmenopausal women

OBJECTIVE

Given that the repetitive loss and regain of body weight, termed weight cycling, is a prevalent phenomenon that has been associated with negative physiological and psychological outcomes, the purpose of this study was to investigate weight change and physiological outcomes in women with a lifetime history of weight cycling enrolled in a 12-month diet and/or exercise intervention.

METHODS

439 overweight, inactive, postmenopausal women were randomized to: i) dietary weight loss with a 10% weight loss goal (N=118); ii) moderate-to-vigorous intensity aerobic exercise for 45 min/day, 5 days/week (n=117); ii) both dietary weight loss and exercise (n=117); or iv) control (n=87). Women were categorized as non-, moderate- (≥3 losses of ≥4.5 kg), or severe-cyclers (≥3 losses of ≥9.1 kg). Trend tests and linear regression were used to compare adherence and changes in weight, body composition, blood pressure, insulin, C-peptide, glucose, insulin resistance (HOMA-IR), C-reactive protein, leptin, adiponectin, and interleukin-6 between cyclers and non-cyclers.

RESULTS

Moderate (n=103) and severe (n=77) cyclers were heavier and had less favorable metabolic profiles than non-cyclers at baseline. There were, however, no significant differences in adherence to the lifestyle interventions. Weight-cyclers (combined) had a greater improvement in HOMA-IR compared to non-cyclers participating in the exercise only intervention (P=.03), but no differences were apparent in the other groups.

CONCLUSION

A history of weight cycling does not impede successful participation in lifestyle interventions or alter the benefits of diet and/or exercise on body composition and metabolic outcomes.

Clinically important body weight gain following total hip arthroplasty: a cohort study with 5-year follow-up

OBJECTIVE

Literature examining the effects of total hip arthroplasty (THA) on subsequent body weight gain is inconclusive. Determining the extent to which clinically relevant weight gain occurs following THA has important public health implications.

DESIGN

We used multi-variable logistic regression to compare data from one of the largest US-based THA registries to a population-based control sample from the same geographic region. We also identified factors that increased risk of clinically important weight gain specifically among persons undergoing THA. The outcome measure of interest was weight gain of ≥5% of body weight up to 5 years following surgery.

RESULTS

The multi-variable adjusted [age, sex, body mass index (BMI), education, comorbidity and pre-surgical weight change] odds ratio for important weight gain was 1.7 [95% confidence interval (CI), 1.06, 2.6] for a person with THA as compared to the control sample. Additional arthroplasty procedures during the 5-year follow-up further increased odds for important weight gain (OR = 2.0, 95% CI, 1.4, 2.7) relative to the control sample. A patient with THA had increased risk of important post-surgical weight gain of 12% (OR = 1.12, 95% CI, 1.08, 1.16) for every kilogram of pre-operative weight loss.

CONCLUSIONS

While findings should be interpreted with caution because of missing follow-up weight data, patients with THA appear to be at increased risk of clinically important weight gain following surgery as compared to peers. Patients less than 60 years and who have lost a substantial amount of weight prior to surgery appear to be at particularly high risk of important post-surgical weight gain.

Does recalled dieting increase the risk of non-vertebral osteoporotic fractures? The Tromsø Study

The risk of non-vertebral osteoporotic fractures increased by increasing recalled amount of weight loss when dieting in women aged ≥ 46 years and in those with BMI < 25 kg/m(2) participating in the Tromsø Study (1994/1995-2009). The increased risk was present both in women with few and several episodes of recalled dieting.

INTRODUCTION

The influence of repeated dieting on bone health is uncertain. This study aims to investigate whether recalled dieting is a risk factor for non-vertebral osteoporotic fractures.

METHODS

In 1994/1995 weight and height were measured in all participants aged 25-69 years in the population-based Tromsø Study. Information about socioeconomic background, diseases and lifestyle factors was collected by questionnaires-including number of recalled dieting episodes and largest amount of weight loss when dieting. The participating 20,745 women and men were followed for 15 years, fractures were registered from X-ray archives and analysed by Cox's proportional hazards models.

RESULTS

Among those who recalled dieting, 975 women and 364 men suffered a non-vertebral osteoporotic fracture during follow-up. Compared to women without recalled weight loss when dieting, women who reported their largest weight loss of 11 kg or more had a hazard ratio (HR) = 1.48 (95% CI 1.13-1.94) for osteoporotic fracture, adjusted for age, marital status, body mass index, height, education, physical activity, smoking, alcohol intake, history of cardiovascular disease and psychological distress. The increased risk was statistically significant only in women aged ≥ 46 years and in those with BMI < 25 kg/m(2). Women who recalled ≥ 11 dieting episodes had HR = 1.73 (CI 1.11-2.68) for osteoporotic fracture compared to those with no recalled episodes. Dieting was not associated with risk of fractures in men, but the number of fractures was low.

CONCLUSIONS

The increased risk of non-vertebral osteoporotic fractures by recalled dieting in women indicates that maintenance of a stable weight may have beneficial effects on fracture risk.

Reliability and internal consistency of questionnaire for evaluating weight cycling in Southern Brazil

AIMS AND OBJECTIVES

To determine the reliability and internal consistency of a questionnaire that was designed to assess weight cycling.

BACKGROUND

A large part of the obese population attempt to lose weight. Of those who had lost at least 10% of their initial weight, 33·5% regained weight. This weight loss and regain is termed 'weight cycling'. So far, no available validated instruments exist that are capable of identifying these patients.

DESIGN

A quantitative study for the validation of a questionnaire.

METHODS

The selected patients received a phone call from the researchers. On that occasion, they answered a questionnaire that contained eight questions about their current weight, their weight at 18 years of age and their history of weight cycling over the past two years. Approximately 20 days after the first phone call, the patients were re-contacted and asked to respond again to the proposed questionnaire. The internal consistency and reliability were examined through a kappa index and a chi-squared test. The questions that showed evidence of reliability and consistency composed the final questionnaire.

RESULTS

The final questionnaire consisted of six questions. An analysis of the test-retest kappa coefficient was moderate or greater for four of the six objective questions. One of the two quantitative questions showed a strong correlation for the test/retest reliability, and the other showed a strong correlation with the gold standard. An analysis of the internal consistency between a composition of questions 5 and 6 with question 4 showed moderate agreement, which increased when it was adjusted for the same cut-off point. The agreement between patients classified as 'weight cyclers' was higher than 80% in both tests.

CONCLUSIONS

The Questionnaire to Assess Weight Cycling provided evidence of reliability and internal consistency.

RELEVANCE TO CLINICAL PRACTICE

Evaluating weight cycling.

Repeated Weight Loss is Associated with the Metabolic Syndrome and Diabetes: Results of a 28 Year Re-screening of Men in the Oslo Study

OBJECTIVE

We investigated whether weight loss episodes were associated with the metabolic syndrome and diabetes in elderly men.

DESIGN AND SUBJECTS

Men residing in Oslo and born in 1923-32 (n = 16,209) were screened for cardiovascular diseases and risk factors in 1972-73. Those who resided in the same area in the year 2000 were invited to a repeat physical and laboratory examination, attended by 6 410 men (mean age 72.5 years). Weight, height and blood pressure were measured both times, and a non-fasting measurements of total serum cholesterol, triglycerides and glucose were obtained. Weight loss, leisure time physical activity, smoking habits, and educational attendance were self-reported.

RESULTS

The proportion that reported one or more episodes of weight loss at age 25-50 years was 15.6% (n = 3,564 respondents) while 26.8% reported weight loss after age 50 (n = 3,473 respondents). Age-specific weight loss scores based on the number of the episodes of weight loss or on the total amount of weight loss were strongly associated with the presence of obesity, the metabolic syndrome and diabetes in the year 2000. The risk of the metabolic syndrome and diabetes in 2000 increased with increasing number of weight loss episodes also adjusted for BMI in 1972-73 and other potential confounders. The odds ratio for the metabolic syndrome for one standard deviation change in the number of weight loss episodes after age 50 was 1.43 (95% confidence limits 1.30-1.57). The corresponding odds ratio for diabetes was 1.25 (95% confidence limits 1.14-1.37). Similar results were found using a score for the total amount of weight loss.

CONCLUSION

Among elderly men the number of episodes or amount of weight loss after age 50 was associated with the metabolic syndrome and diabetes, but this study cannot establish the causality of the association.