Behavioral Treatment of Obesity

Dietary lapses (i.e., instances of dietary non-adherence) are common during weight loss attempts, and compromise success in two ways: increasing caloric intake and demoralizing the participant, sometimes leading them to abandon their weight control goals altogether. Efforts to understand and prevent demoralization have received almost no research attention. Self-compassion has high potential to promote adaptive responses to these setbacks because it reframes “failure” and promotes self-improvement. Past research shows that when participants experience a lapse, those practicing higher self-compassion report higher self-efficacy and intentions to continue dieting. The current study extended this literature to examine whether self-compassion in response to a lapse would predict lower likelihood of a subsequent same-day lapse and greater reports of perceived control over weight management behaviors. We also examined whether the individual facets of self-compassion, including self-kindness (treating oneself the way one would a friend); common humanity (the understanding that everyone has struggles); and mindfulness (non-judgmental awareness of thoughts and feelings) are associated with these outcomes. Participants (N = 140) enrolled in a behavioral weight loss trial completed 6 ecological momentary assessment (EMA) surveys a day for seven days. Total self-compassion and each facet of self-compassion individually were all associated with less negative affect after a lapse. None of the self-compassion variables predicted the likelihood of participants reporting a lapse again that day. However, higher total self-compassion and higher self-kindness after a lapse were both associated with greater perceived self-control over weight management behaviors in the hours following. Common humanity and mindfulness, respectively, were not associated with reports of perceived control. Results suggest that self-compassion following dieting setbacks may prevent goal disengagement, and that self-kindness is the facet most strongly associated with adaptive responses to these setbacks.

Behaviour change interventions for weight management have found varied effect sizes and frequent weight re-gain after weight loss. There is interest in exploring whether differences in eating behaviour can be used to develop tailored weight management programs. This secondary analysis of an 18-month weight maintenance randomised controlled trial (RCT) aimed to investigate the association between individual variability in weight maintenance success and change in eating behaviour traits (EBT). Data was analysed from the NoHoW trial (Scott et al., 2019), which was designed to measure processes of change after weight loss of ≥5% body weight in the previous year. The sample included 1627 participants (mean age = 44.0 years, SD = 11.9, mean body mass index (BMI) = 29.7 kg/m², SD = 5.4, gender = 68.7% women/31.3% men). Measurements of weight (kg) and 7 EBTs belonging to domains of reflective, reactive, or homeostatic eating were taken at 4 time points up to 18-months. Increases in measures of ‘reactive eating’ (binge eating, p < .001), decreases in ‘reflective eating’ (restraint, p < .001) and changes in ‘homeostatic eating’ (unlimited permission to eat, p < .001 and reliance on hunger and satiety cues, p < .05) were significantly and independently associated with concomitant weight change. Differences in EBT change were observed between participants who lost, maintained, or re-gained weight for all EBTs (p < .001) except for one subscale of intuitive eating (eating for physical reasons, p = .715). Participants who lost weight (n = 322) exhibited lower levels of reactive eating and higher levels of reflective eating than participants who re-gained weight (n = 668). EBT domains can identify individuals who need greater support to progress in weight management interventions. Increasing reflective eating and reducing reactive eating may enhance weight management success.

The population worldwide is getting older as a result of advances in public health, medicine, and technology. Older individuals are living longer with a higher prevalence of subclinical and clinical cardiovascular disease (CVD). In 2010, the American Heart Association introduced a list of key prevention targets, known as “Life’s Simple 7’’ to increase CVD-free survival, longevity, and quality of life. In 2022, sleep health was added to expand the recommendations to “Life’s Essential 8’’ (eat better, be more active, stop smoking, get adequate sleep, manage weight, manage cholesterol, manage blood pressure, and manage diabetes). These prevention targets are intended to apply regardless of chronologic age. During this same time, the understanding of aging biology and goals of care for older adults further enhanced the relevance of prevention across the range of functions. From a biological perspective, aging is a complex cellular process characterized by genomic instability, telomere attrition, loss of proteostasis, inflammation, deregulated nutrient-sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. These aging hallmarks are triggered by and enhanced by traditional CVD risk factors leading to geriatric syndromes (eg, frailty, sarcopenia, functional limitation, and cognitive impairment) which complicate efforts toward prevention. Therefore, we review Life’s Essential 8 through the lens of aging biology, geroscience, and geriatric precepts to guide clinicians taking care of older adults.

Binge-type eating disorders (EDs; i.e., bulimia nervosa, binge eating disorder) are common among young adults with high body weight, yet few interventions target both conditions. This study tested an online guided self-help intervention that provided cognitive behavioral therapy (CBT) tools for EDs and behavioral weight loss (BWL) content to young adults with binge-type EDs and high body weight.

60 adults aged 18–39 with clinical/subclinical binge-type EDs and high body weight were randomized to a combined condition or a CBT-only condition. Participants received self-help content for 8 weeks and self-reported ED attitudes, frequency of binge eating and compensatory behaviors, and weight at baseline, 4-weeks, and 8-weeks. Linear mixed models and negative binomial models compared changes between conditions in ED attitudes, ED behaviors, and weight at each timepoint. Chi-square test and independent samples t-test compared program completion and session engagement between conditions.

No significant differences in weight change or ED symptom change emerged between the conditions. Both conditions achieved significant reductions in ED attitudes, binge episodes, and compensatory behaviors from baseline to 8-weeks (ps < .05). Neither condition demonstrated significant weight loss from baseline to 8-weeks. Program completion (47 %) and session engagement (57 %) were equally high across conditions.

Both conditions achieved ED symptom change; however, neither condition was associated with weight change. Research is needed to identify the types of strategies and doses of BWL that promote clinically significant weight and ED symptom change in young adults.

In adults, behavioral-based interventions support prevention of Type 2 diabetes; less is known in children. The aim of this systematic review was to examine the impact of behavioral-based interventions on cardiometabolic outcomes among children at risk for diabetes.

PubMed, CINAHL Plus with Full Text, PsycINFO, and Web of Science were searched between September 2011 and September 2021. RCTs in children aged 6−12 years at risk for Type 2 diabetes that implemented a behavioral-based intervention and included ≥1 cardiometabolic outcome were eligible. If reported, dietary quality data were extracted. Risk of bias was assessed using the revised Cochrane risk-of-bias tool.

Of the 2,386 records identified, 4 met the inclusion criteria. Study length ranged from 10 weeks to 24 months, with sample sizes ranging from 53 to 113 participants. Among the 4 studies, there were 5 behavioral-based arms. All studies included weight status outcomes, with 3 finding significant between-group differences. Four studies assessed fasting glucose, and 3 assessed HbA1c; none found significant changes between groups. Of the 4 studies reporting blood pressure outcomes, 1 found a significant between-group difference for systolic blood pressure. Three studies assessed cholesterol and found no changes. No studies reported measures of dietary quality. All studies had some concerns about risk of bias.

Behavioral-based interventions improved weight status and supported the maintenance of cardiometabolic parameters. Stronger consideration of the most important risk factors in children along with intermediate outcomes (e.g., diet quality) may help to elucidate the relationship between behavioral-based interventions and cardiometabolic outcomes.

A growing interest exists among behavior analysts to apply their training, expand their scope of competence, and practice in areas that fall under the umbrella of health, sport, and fitness (HSF). While the opportunities are vast, this chapter focuses on applications outside of the formal healthcare system that serve to improve health and fitness through diet, physical activity, and exercise modification, as well as to enhance athletic and sport performance. Our intent was to provide information to guide aspiring practitioners toward an HSF-focused career, as well as to assist seasoned practitioners looking to expand or pivot their practice. The chapter is organized into three primary sections: health, fitness, and sport. Within each section, you will find an overview of the topic, common assessment and measurement tools for frequently targeted behaviors for change, a summary of research-supported interventions, and major implications based on research outcomes. The chapter concludes with training-related recommendations to increase both scope of competence and scope of practice and interprofessional collaboration.