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

Lowe, Michael R.; Feig, Emily H.; Winter, Samantha; Stice, Eric

doi:10.3945/ajcn.115.115402

Cited by 29 publications

(47 citation statements)

References 29 publications

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“…These predictors, especially the higher baseline BMI, have been previously noted (11,12). Lowe et al (31,32) found that weight variability over a 6-month period predicted weight gain over 2 years in college females. Weight suppression has also been predictive of weight gain.…”

Section: Clinical Trials and Investigationsmentioning

confidence: 64%

Examining Heterogeneity of Outcomes in a Weight Gain Prevention Program for Young Adults

Wing

Russell

Tate

et al. 2020

Obesity

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Objective This study aimed to characterize young adults who experienced significant weight gains (> 10%) over 3 years in a weight gain prevention program. Methods Secondary data analysis from the Study of Novel Approaches to Weight Gain Prevention (SNAP), a randomized trial comparing two self‐regulation interventions and a control arm in young adults (18‐35 years; BMI 21‐30.9 kg/m2), was used. Large Gainers (≥ 10% of their body weight; n = 48), Small Gainers (2.6%‐9.9%; n = 149), and Weight Stable participants (± 2.5%; n = 143) were compared on dimensions affecting weight gain. Results Differences in weight gain among the three groups were significant by year 1 and subsequently increased. Those who became Large Gainers were heavier at baseline and further below their highest weight, and they reported more weight cycling than Weight Stable, with Small Gainers intermediate. Neither study arm nor pregnancy explained weight change differences among the three groups. Large Gainers reported more depressive symptoms than Weight Stable at years 1 and 2. Large Gainers were less likely to weigh themselves at least weekly at 4 months, before differences in weight gain emerged, and at years 1 and 2. Conclusions Large Gainers (representing almost 10% of participants) could be identified early by greater weight issues at baseline and lower use of weight gain prevention strategies.

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Section: Clinical Trials and Investigationsmentioning

confidence: 64%

Examining Heterogeneity of Outcomes in a Weight Gain Prevention Program for Young Adults

Wing

Russell

Tate

et al. 2020

Obesity

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“…First, increased weight variability might represent some sort of early marker that is ultimately associated with a chronic positive energy balance and weight gain (1). The magnitude of the neural response that predicts weight variability in the current study reflects the potential utility of weight variability in addition to weight gain in the understanding of eating and weight regulation.…”

Section: Figurementioning

confidence: 82%

“…Because of missing weights at the 3-y follow-up, 127 total participants were analyzed in the supplementary analysis with the BMI change controlled for. BMI variability was selected as the outcome of interest in analyses because all of the extant literature on weight variability has used either BMI or raw weights (16,17). However, some studies that used the same or similar paradigms used body fat as the outcome of interest (18).…”

Section: Fmri Paradigmmentioning

confidence: 99%

“…Over periods of months or years, a person's body weight may increase, decrease, or show little absolute change, but the variability in body weight over that time period could vary independently of the degree of the overall change in body weight. When assessed repeatedly over time, these individual differences in body weight may, themselves, convey important information about people's current or future ability to regulate their body weights (1). Therefore, it is important to understand the processes that predict weight variability independent of the total weight change.…”

Section: Introductionmentioning

confidence: 99%

“…First, there has been preliminary evidence that an elevated weight variability in healthy-weight individuals increases risk of future weight gain (1). Therefore, it may be important to understand individual differences in weight variability in healthy-weight individuals, because weight variability may predate an increase in weight and, ultimately, the development of overweight or obesity.…”

Section: Introductionmentioning

confidence: 99%

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Elevated reward response to receipt of palatable food predicts future weight variability in healthy-weight adolescents

Winter

Yokum

Stice

et al. 2017

The American Journal of Clinical Nutrition

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Background: Both an elevated brain-reward-region response to palatable food and elevated weight variability have been shown to predict future weight gain. Objective: We examined whether the brain-reward response to food is related to future weight variability. Design: A total of 162 healthy-weight adolescents, who were aged 14-18 y at baseline, were enrolled in the study and were assessed annually over a 3-y follow-up period with 127 participants completing the final 3-y follow-up assessment. With the use of functional magnetic resonance imaging, we tested whether the neural responses to a cue that signaled an impending milkshake receipt and the receipt of the milkshake predicted weight variability over the follow-up period. Weight variability was modeled with a root mean squared error method to reflect fluctuations in weight independent of the net weight change. Results: Elevated activation in the medial prefrontal cortex and supplementary motor area, cingulate gyrus, cuneus and occipital gyrus, and insula in response to milkshake receipt predicted greater weight variability. Greater activation in the precuneus and middle temporal gyrus predicted lower weight variability. Conclusions: From our study data, we suggest that the elevated activation of reward and emotional-regulation brain regions (medial prefrontal cortex, cingulate cortex, and insula) and lower activation in self-reference regions (precuneus) in response to milkshake receipt predict weight variability over 3 y of follow-up. The fact that the reward response in the current study emerged in response to high-calorie palatable food receipt suggests that weight variability may be a measure of propensity periods of a positive energy balance and should be examined in addition to measures of the net weight change. With our collective results, we suggest that weight variability and its brain correlates should be added to other variables that are predictive of weight gain to inform the design of obesity-preventive programs in adolescents. This trial was registered at clinicaltrials.gov as NCT01807572.Am J Clin Nutr 2017;105:781-9.

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Within‐subject weight variability in bulimia nervosa: Correlates and consequences

Chen

Singh

Lowe

2021

Intl J Eating Disorders

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Objective The oscillations between binge eating, purging, and dieting in bulimia nervosa (BN) may produce substantial within‐subject weight variability. Although weight variability has been predictive of eating‐ and weight‐related variables in community samples, it has not been empirically examined in eating disorders. The current study examined cross‐sectional and prospective associations between weight variability and BN pathology. Method Four weights were collected over an average of 42.02 days, and weight variability was calculated as the root mean square error around each individual's weight trajectory regression line. Linear regressions were performed to examine the association between weight variability and eating disorder psychopathology, cross‐sectionally at baseline and prospectively at 6‐month follow‐up, adjusting for baseline BMI. Results Weight variability was cross‐sectionally associated with eating pathology, but these relationships became non‐significant after adjusting for BMI. However, at 6‐month follow‐up, greater baseline weight variability predicted increases in body dissatisfaction, shape and weight concerns, and global eating pathology, even after adjusting for baseline BMI. Discussion These findings demonstrate, for the first time, that within‐subject weight variability predicts greater eating disorder pathology over time in BN. The results add to evidence that weight history variables contribute to BN psychopathology above and beyond well‐documented psychological dysfunction in BN.

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

Cited by 29 publications

References 29 publications

Examining Heterogeneity of Outcomes in a Weight Gain Prevention Program for Young Adults

Examining Heterogeneity of Outcomes in a Weight Gain Prevention Program for Young Adults

Elevated reward response to receipt of palatable food predicts future weight variability in healthy-weight adolescents

Within‐subject weight variability in bulimia nervosa: Correlates and consequences

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