State-level working memory and dysregulated eating in children and adolescents: An exploratory ecological momentary assessment study.

BACKGROUND: Children with loss of control (LOC) eating and overweight/obesity have relative deficiencies in trait-level working memory (WM), which may limit adaptive responding to intra- and extra-personal cues related to eating. Understanding of how WM performance relates to eating behavior in real-time is currently limited. METHODS: We studied 32 youth (ages 10-17 years) with LOC eating and overweight/obesity (LOC-OW; n = 9), overweight/obesity only (OW; n = 16), and non-overweight status (NW; n = 7). Youth completed spatial and numerical WM tasks requiring varying degrees of cognitive effort and reported on their eating behavior daily for 14 days via smartphone-based ecological momentary assessment. Linear mixed effects models estimated group-level differences in WM performance, as well as associations between contemporaneously completed measures of WM and dysregulated eating. RESULTS: LOC-OW were less accurate on numerical WM tasks compared to OW and NW (ps < .01); groups did not differ on spatial task accuracy (p = .41). Adjusting for between-subject effects (reflecting differences between individuals in their mean WM performance and its association with eating behavior), within-subject effects (reflecting variations in moment-to-moment associations) revealed that more accurate responding on the less demanding numerical WM task, compared to one's own average, was associated with greater overeating severity across the full sample (p = .013). There were no associations between WM performance and LOC eating severity (ps > .05). CONCLUSIONS: Youth with LOC eating and overweight/obesity demonstrated difficulties mentally retaining and manipulating numerical information in daily life, replicating prior laboratory-based research. Overeating may be related to improved WM, regardless of LOC status, but temporality and causality should be further explored. PUBLIC SIGNIFICANCE STATEMENT: Our findings suggest that youth with loss of control eating and overweight/obesity may experience difficulties mentally retaining and manipulating numerical information in daily life relative to their peers with overweight/obesity and normal-weight status, which may contribute to the maintenance of dysregulated eating and/or elevated body weight. However, it is unclear whether these individual differences are related to eating behavior on a moment-to-moment basis.

An explanation for the accuracy of sensor-based measures of energy intake: Amount of food consumed matters more than dietary composition.

Understanding and intervening on eating behavior often necessitates measurement of energy intake (EI); however, commonly utilized and widely accepted methods vary in accuracy and place significant burden on users (e.g., food diaries), or are costly to implement (e.g., doubly labeled water). Thus, researchers have sought to leverage inexpensive and low-burden technologies such as wearable sensors for EI estimation. Paradoxically, one such methodology that estimates EI via smartwatch-based bite counting has demonstrated high accuracy in laboratory and free-living studies, despite only measuring the amount, not the composition, of food consumed. This secondary analysis sought to further explore this phenomenon by evaluating the degree to which EI can be explained by a sensor-based estimate of the amount consumed versus the energy density (ED) of the food consumed. Data were collected from 82 adults in free-living conditions (51.2% female, 31.7% racial and/or ethnic minority; Mage = 33.5, SD = 14.7) who wore a bite counter device on their wrist and used smartphone app to implement the Remote Food Photography Method (RFPM) to assess EI and ED for two weeks. Bite-based estimates of EI were generated via a previously validated algorithm. At a per-meal level, linear mixed effect models indicated that bite-based EI estimates accounted for 23.4% of the variance in RFPM-measured EI, while ED and presence of a beverage accounted for only 0.2% and 0.1% of the variance, respectively. For full days of intake, bite-based EI estimates and ED accounted for 41.5% and 0.2% of the variance, respectively. These results help to explain the viability of sensor-based EI estimation even in the absence of information about dietary composition.

Association of weight and shape concern with weight change and weight-related behaviors in behavioral weight loss treatment.

Weight and shape concern (WSC) is a facet of negative body image that is common among individuals with overweight/obesity seeking behavioral weight loss treatment (BWL), but remains understudied. This secondary analysis evaluates associations between WSC, weight change, and weight-related behaviors among individuals in a 24-week BWL. Adults (n = 32) with body mass index 25-50 kg/m2 completed a baseline WSC questionnaire, measured weight at 12 and 24 weeks, measured physical activity via accelerometer, and completed 24-hour dietary recalls. Adherence to self-monitoring dietary intake and weight were assessed. A series of linear mixed models were used to evaluate associations between baseline WSC and weight change, as well as weight-related behaviors. Results revealed no significant effect of WSC on weight change. There were significant WSC x time interactions, such that those rating WSC "very important" decreased self-weighing and the "low importance" group decreased their caloric intake during treatment. The "pretty important" group had greater minutes of activity than the "low importance" group. Findings indicated that WSC may impact weight-related behaviors that contribute to BWL success. This trial was pre-registered on ClinicalTrials.gov (NCT03739151).

Physical activity changes during an automated online weight loss program.

Evidence-based online behavioral weight loss (BWL) treatment targets a combination of diet, physical activity, and behavioral skills training. While weight loss outcomes are well documented, little is known about changes in physical activity. This study examined changes in objectively measured physical activity across the energy expenditure spectrum during a fully automated, online BWL program. Adults with overweight or obesity (n = 63) completed a 12-week, online BWL program. Participants wore an accelerometer for 7 days and body weight was measured in-clinic at pre- and post-treatment. At post-treatment, mean daily moderate-to-vigorous physical activity increased by about 4 min (SE = 1.59, p = 0.01). There were no statistically significant changes in light physical activity or time spent sedentary (p's > 0.05). Despite only minimal changes in moderate-to-vigorous physical activity overall, larger increases correlated with greater weight loss (r = - 0.28, p = 0.02), which averaged 6.1% of baseline weight at post-treatment. Though achieving important weight loss outcomes, online programs may fail to produce clinically relevant improvements in physical activity, which can put weight loss maintenance at risk.

Association of Migraine and Blood Pressure-Does Obesity Severity Have a Moderating Role?

BACKGROUND: The relationship between migraine and blood pressure (BP) is equivocal, warranting exploration of potential moderators. Obesity associates with both migraine and BP in a dose-dependent fashion, although its role as a moderator has not been evaluated. We examined the relation between migraine and BP in women with comorbid migraine and obesity, and whether this relation was influenced by obesity severity. METHODS: Women with migraine and obesity (n = 134) completed a 28-day headache diary before randomization to lifestyle intervention or migraine education. BP (systolic (SBP)/diastolic (DBP)), body mass index (BMI), and waist circumference (WC) were measured before diary completion. Hierarchical linear regression assessed associations between BP and migraine characteristics (headache frequency, duration, and pain intensity), and obesity severity (both total (BMI) and abdominal (WC)) as moderators of these associations. RESULTS: Participants (BMI = 35.4 ± 6.5 kg/m2; WC = 105.4 ± 15.6 cm, SBP = 113.1 ± 12.1/DPB = 68.1 ± 8.0 mmHg) reported 8.4 ± 4.5 migraine days that lasted 20.2 ± 15.9 h with mean pain intensity of 5.9 ± 1.6 on a 10-point scale. DBP inversely related to migraine days in both total (ß = - 0.226, p = .010) and abdominal (ß = 0.214, p = .015) obesity severity models. SBP and obesity severity did not relate to migraine characteristics. Obesity severity did not moderate relations between migraine characteristics and BP (p's > .05). CONCLUSION: Among women with comorbid migraine and obesity, DBP inversely related to migraine frequency; however, obesity severity did not affect the strength of this or other examined associations. Future studies including healthy weight controls and men and women with continuous BP measures are needed to confirm these findings and identify mechanisms and moderators.

Characterizing emotional eating: Ecological momentary assessment with person-specific modeling.

Emotional eating is a topic of clinical importance, with links to weight regulation and wellness. However, issues of concept clarity and measurement can interfere with efforts to understand and intervene on emotional eating. One explanation for prior difficulties in defining emotional eating may be that this construct is not uniform across individuals. The current study critically examined emotional eating by combining ecological momentary assessment (EMA) with an idiographic analytic approach. The study examined the heterogeneity in the emotions and dysregulated eating behaviors often thought to underlie emotional eating, by establishing and comparing latent factor profiles across individuals. Ten community adults with overweight or obesity completed a 21-day EMA protocol, with 5 daily prompts to report on relevant emotions and eating behaviors. P-technique factor analysis was used to examine the data. Results suggested variability across individuals in the number of factors that emerged, the items that loaded on each factor, and the strength of loadings. Dysregulated eating was not found to covary with affective states strongly enough to produce a distinct "emotional eating" factor for any individual, nor did the correlations between factors suggest strong relationships between emotions and dysregulated eating for most participants, even in this sample with 90% of participants self-identifying as "emotional eaters." Findings are consistent with a growing body of literature questioning the validity of the "emotional eating" construct as currently defined and measured, and supports conceptualizing emotional eating as a locally heterogenous construct that varies between people. Combining EMA with an intra-individual modeling technique appears to be a promising approach for understanding emotional eating. Additional work with larger samples is needed to capture the full range in individual profiles.

Ecological momentary assessment of changes in eating behaviors, appetite, and other aspects of eating regulation in Roux-en-Y gastric bypass and sleeve gastrectomy patients.

Bariatric surgery can have profound impacts on eating behaviors and experiences, yet most prior research studying these changes has relied on retrospective self-report measures with limited precision and susceptibility to bias. This study used smartphone-based ecological momentary assessment (EMA) to evaluate the trajectory of change in eating behaviors, appetite, and other aspects of eating regulation in 71 Roux-en-Y gastric bypass and sleeve gastrectomy patients assessed preoperatively and at 3, 6, and 12-months postoperative. For some outcomes, results showed a consistent and similar pattern for SG and RYGB where consumption of sweet and high-fat foods and hunger, desire to eat, ability to eat right now, and satisfaction with amount eaten all improved from pre-to 6-months post-surgery with some degree of deterioration at 12-months post-surgery. By contrast, other variables, largely related to hedonic hunger and craving and desire for specific foods, showed less consistent patterns that differed by surgery type. While the findings suggest an overall pattern of improvement in eating patterns following bariatric surgery, they also highlight how a return to preoperative habits may begin as early as 6 months after surgery. Additional research is needed to understand mechanisms that promote changes in eating behavior after surgery, and how best to intervene to preserve beneficial effects.

Preliminary evidence of contextual factors' influence on weight loss treatment outcomes: implications for future research.

BACKGROUND/OBJECTIVES: Behavioral health interventions, including behavioral obesity treatment, typically target psychosocial qualities of the individual (e.g., knowledge, self-efficacy) that are largely treated as persistent, over momentary contextual factors (e.g., affect, environmental conditions). The variance in treatment outcomes that can be attributable to these two sources is rarely quantified but may help inform future research and treatment development efforts. SUBJECTS/METHODS: The intraclass correlation coefficient (ICC) for weekly weight loss was calculated in three studies involving 10-12 weeks of behavioral obesity treatment delivered to adults via in-person group sessions, mobile application, or website. The ICC explains the proportion of variance between vs. within individuals, and was used to infer the contribution of individual vs. contextual factors to weekly weight loss. The analytic approach involved unconditional linear mixed effect models with a random effect for subject. RESULTS: The ICCs were very low, ranging from 0.01 to 0.06, suggesting that momentary contextual factors may influence obesity treatment outcomes to a substantial degree. CONCLUSIONS: This study yielded preliminary evidence that the influence of contextual factors in behavioral obesity treatment may be underappreciated. Future research is needed to simultaneously identify and quantify sources of within- and between-subjects variance to optimize treatment approaches.

Optimizing relapse prevention and changing habits (REACH+) in anorexia nervosa.

INTRODUCTION: Relapse rates in anorexia nervosa (AN) are high, even after full weight restoration. This study aims to develop a relapse prevention treatment that specifically addresses persistent maladaptive behaviors (habits). Relapse Prevention and Changing Habits (REACH+) aims to support patients in developing routines that promote weight maintenance, encourage health, and challenge habits that perpetuate illness. The clinical trial design uses the Multiphase Optimization STrategy (MOST) framework to efficiently identify which components of treatment contribute to positive outcomes. METHODS: Participants will be 60 adults with AN who have achieved weight restoration in an inpatient setting. Treatment will consist of 6 months of outpatient telehealth sessions. REACH+ consists of behavior, cognitive, and motivation components, as well as food monitoring and a skill consolidation phase. A specialized online platform extends therapy between sessions. Participants will be randomly assigned to different versions of each component in a fractional factorial design. Outcomes will focus on maintenance of remission, measured by rate of weight loss and end-of-trial status. Interventions that contribute to remission will be included in an optimized treatment package, suitable for a large-scale clinical trial of relapse prevention in AN.

Combining passive eating monitoring and ecological momentary assessment to characterize dietary lapses from a lifestyle modification intervention.

Dietary lapses (i.e., specific instances of nonadherence to recommended dietary goals) contribute to suboptimal weight loss outcomes during lifestyle modification programs. Passive eating monitoring could enhance lapse measurement via objective assessment of eating characteristics that could be markers for lapse (e.g., more bites consumed). The purpose of this study was to evaluate if passively-inferred eating characteristics (i.e., bites, eating duration, and eating rate), measured via wrist-worn device, could distinguish dietary lapses from non-lapse eating. Adults (n = 25) with overweight/obesity received a 24-week lifestyle modification intervention. Participants completed ecological momentary assessment (EMA; repeated smartphone surveys) biweekly to self-report on dietary lapses and non-lapse eating episodes. Participants wore a wrist device that captured continuous wrist motion. Previously-validated algorithms inferred eating episodes from wrist data, and calculated bite count, duration, and rate (seconds per bite). Mixed effects logistic regressions revealed no simple effects of bite count, duration, or eating rate on the likelihood of dietary lapse. Moderation analyses revealed that eating episodes in the evening were more likely to be lapses if they involved fewer bites (B = -0.16, p < .05), were shorter (B = -0.54, p < .05), or had a slower rate (B = 1.27, p < .001). Statistically significant interactions between eating characteristics (Bs = -0.30 to -0.08, ps < .001) revealed two distinct patterns. Eating episodes that were 1. smaller, slower, and shorter than average, or 2. larger, quicker, and longer than average were associated with increased probability of lapse. This study is the first to use objective eating monitoring to characterize dietary lapses throughout a lifestyle modification intervention. Results demonstrate the potential of sensors to identify non-adherence using only patterns of passively-sensed eating characteristics, thereby minimizing the need for self-report in future studies. CLINICAL TRIALS REGISTRY NUMBER: NCT03739151.

Traditional versus developmental measures of weight suppression: Exploring their relationships with bulimic psychopathology.

OBJECTIVE: Weight suppression (WS) is related to a wide variety of eating disorder characteristics. However, individuals with eating disorders usually reach their highest premorbid weight while still developing physically. Therefore, a more sensitive index of individual differences in highest premorbid weight may be one that compares highest premorbid z-BMI to current z-BMI (called developmental weight suppression [DWS] here). METHOD: In this exploratory study, we compared the relationships between traditional weight suppression (TWS) and DWS and a variety of measures related to bulimic psychopathology in 91 females (M age, 25.2; 60.5% White), with clinical or sub-clinical bulimia nervosa. RESULTS: TWS and DWS were correlated (r = 0.40, p < 0.001). TWS was only significantly related to a measure of physical activity whereas DWS was related to 14 outcomes. DWS showed consistent positive relations with behavioural outcomes (e.g., binge eating) but consistent negative relations with cognitive/affective outcomes (e.g., weight concerns). CONCLUSIONS: Findings indicated much more consistent relationships between the novel DWS measure and bulimic characteristics than with the TWS measure. DWS showed both positive and negative relations with bulimic symptoms, though these findings require replication to confirm their validity. Consistent evidence indicated that the two WS measures served as mutual suppressor variables.

Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach.

OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to generate personalized predictions of symptom trajectories among patients receiving treatment for EDs, and compared model performance to a simpler logistic regression prediction model. METHOD: Participants were adolescent girls and adult women (N = 333) presenting for residential ED treatment. Self-report progress assessments were completed at admission, discharge, and weekly throughout treatment. Latent growth mixture modeling previously identified three latent treatment response trajectories (Rapid Response, Gradual Response, and Low-Symptom Static Response) and assigned a trajectory type to each patient. Machine learning models (support vector, k-nearest neighbors) and logistic regression were applied to these data to predict a patient's response trajectory using data from the first 2 weeks of treatment. RESULTS: The best-performing machine learning model (evaluated via area under the receiver operating characteristics curve [AUC]) was the radial-kernel support vector machine (AUCRADIAL = 0.94). However, the more computationally-intensive machine learning models did not improve predictive power beyond that achieved by logistic regression (AUCLOGIT = 0.93). Logistic regression significantly improved upon chance prediction (MAUC[NULL] = 0.50, SD = .01; p <.001). DISCUSSION: Prediction of ED treatment response trajectories is feasible and achieves excellent performance, however, machine learning added little benefit. We discuss the need to explore how advance knowledge of expected trajectories may be used to plan treatment and deliver individualized interventions to maximize treatment effects.

Identifying behavioral types of dietary lapse from a mobile weight loss program: Preliminary investigation from a secondary data analysis.

Success in behavioral weight loss (BWL) programs depends on adherence to the recommended diet to reduce caloric intake. Dietary lapses (i.e., deviations from the BWL diet) occur frequently and can adversely affect weight loss outcomes. Research indicates that lapse behavior is heterogenous; there are many eating behaviors that could constitute a dietary lapse, but they are rarely studied as distinct contributors to weight outcomes. This secondary analysis aims to evaluate six behavioral lapse types during a 10-week mobile BWL program (eating a large portion, eating when not intended, eating an off-plan food, planned lapse, being unaware of caloric content, and endorsing multiple types of lapse). Associations between weekly behavioral lapse type frequency and weekly weight loss were investigated, and predictive contextual characteristics (psychological, behavioral, and environmental triggers for lapse) and individual difference (e.g., age, gender) factors were examined across lapse types. Participants (N = 121) with overweight/obesity (MBMI = 34.51; 84.3% female; 69.4% White) used a mobile BWL program for 10 weeks, self-weighed weekly using Bluetooth scales, completed daily ecological momentary assessment of lapse behavior and contextual characteristics, and completed a baseline demographics questionnaire. Linear mixed models revealed significant negative associations between unplanned lapses and percent weight loss. Unplanned lapses from eating a large portion, eating when not intended, and having multiple "types" were significantly negatively associated with weekly percent weight loss. A lasso regression showed that behavioral lapse types share many similar stable factors, with other factors being unique to specific lapse types. Results add to the prior literature on lapses and weight loss in BWL and provide preliminary evidence that behavioral lapse types could aid in understanding adherence behavior and developing precision medicine tools to improve dietary adherence.

Consistent Morning Exercise May Be Beneficial for Individuals With Obesity.

This review explores the hypothesis that a consistent exercise time, especially consistent morning exercise, improves exercise adherence and weight management for individuals with overweight or obesity. We discuss data supporting this premise, identify limitations of current research, and outline directions for future research on exercise timing to more robustly evaluate our thesis.

Anxiety sensitivity and intentional avoidance of physical activity in women with probable migraine.

INTRODUCTION: Avoidance of physical activity is a common migraine management strategy. Anxiety sensitivity (i.e. fear of anxiety and bodily sensations due to physical, cognitive, or social consequences) is a potential correlate of physical activity avoidance and may strengthen beliefs about physical activity's detrimental effect on migraine. METHOD: Women (n = 100) with probable migraine diagnosis completed an online survey about migraine and physical activity, which included the Anxiety Sensitivity Index-3. RESULTS: Anxiety sensitivity was associated with significantly increased odds of avoiding moderate- and vigorous-intensity physical activity. Anxiety sensitivity, particularly cognitive concerns, was associated with more frequent vigorous and moderate physical activity avoidance. Social concerns about anxiety sensitivity were associated with stronger expected likelihood of vigorous-intensity physical activity as a triggering and worsening factor in migraine. DISCUSSION: Preliminary findings indicate that anxiety sensitivity may contribute to avoidance of moderate and vigorous physical activity and fear-based cognitions about exercise.

The Association of Changes in Pain Acceptance and Headache-Related Disability.

BACKGROUND: Migraine accounts for substantial suffering and disability. Previous studies show cross-sectional associations between higher pain acceptance and lower headache-related disability in individuals with migraine, but none has evaluated this association longitudinally during migraine treatment. PURPOSE: This study evaluated whether changes in pain acceptance were associated with changes in headache-related disability and migraine characteristics in a randomized controlled trial (Women's Health and Migraine) that compared effects of behavioral weight loss (BWL) treatment and migraine education (ME) on headache frequency in women with migraine and overweight/obesity. METHODS: This was a post hoc analysis of 110 adult women with comorbid migraine and overweight/obesity who received 16 weeks of either BWL or ME. Linear and nonlinear mixed effects modeling methods were used to test for between-group differences in change in pain acceptance, and also to examine the association between change in pain acceptance and change in headache disability. RESULTS: BWL and ME did not differ on improvement in pain acceptance from baseline across post-treatment and follow-up. Improvement in pain acceptance was associated with reduced headache disability, even when controlling for intervention-related improvements in migraine frequency, headache duration, and pain intensity. CONCLUSIONS: This study is the first to show that improvements in pain acceptance following two different treatments are associated with greater reductions in headache-related disability, suggesting a potential new target for intervention development. CLINICAL TRIALS INFORMATION: NCT01197196.

Anxiety Sensitivity as a Risk Indicator for Anxiety, Depression, and Headache Severity in Women With Migraine.

OBJECTIVE: The primary aim of this exploratory study was to assess the relationship between anxiety sensitivity and emotional disorders, migraine characteristics, and migraine-related fear and avoidance behaviors in women with probable migraine. BACKGROUND: Anxiety and depressive disorders are the most frequent comorbid psychiatric conditions in migraine, particularly in women; however, the underlying reasons for these comorbidities are uncertain. Anxiety sensitivity, the tendency to catastrophically appraise anxiety and bodily sensations in terms of their physical, social, or cognitive consequences, is a psychological factor that may contribute to the comorbidity of anxiety and depressive disorders and migraine. It was hypothesized that anxiety sensitivity would be associated with greater migraine severity and psychiatric symptoms. METHOD: Participants were women (n = 100) who screened positive for migraine on the validated IDMigraine Screener participated in an anonymous single-session online survey-based study on migraine. The Anxiety Sensitivity Index-3 total and subscales scores were used to assess anxiety sensitivity. Anxiety and depression symptoms were assessed with the brief Patient Health Questionnaire. RESULTS: On average, anxiety sensitivity was clinically elevated (mean ± SD: 24.0 ± 15.2). Anxiety sensitivity cognitive and social concerns were most strongly correlated with severity of anxiety (r's = .38-.46) and depressive symptoms (r = .35-.39, P's < .001), and all anxiety sensitivity facets were related to fear of head pain (r's = .35-.38, P's < .001). Anxiety sensitivity cognitive concern facet was uniquely related to headache patterns, including longer migraine attack duration (r = .22, P = .029) and pain intensity (r = .24, P = .029), pain-related avoidance, including avoiding movement and more frequent misuse of prescribed or non-prescribed pain medication (r's = .20-.21, P's < .01). CONCLUSIONS: These novel findings indicate that anxiety sensitivity, specifically fearful appraisal of bodily sensations, are linked to both psychiatric symptoms and migraine severity in women. In this cross-sectional study, causal sequence cannot be determined. If anxiety sensitivity leads to more severe pain and psychiatric distress, targeting anxiety sensitivity could lead to better headache outcomes.

Topical Review: Design Considerations When Creating Pediatric Mobile Health Interventions: Applying the IDEAS Framework.

OBJECTIVE: To present a guiding framework from the perspective of psychologists and technologists to develop effective mobile health (mHealth) interventions for pediatric populations. METHODS: This topical review uses the IDEAS framework as an organizational method to summarize current strategies to conceptualize, design, evaluate, and disseminate mHealth interventions. RESULTS: Incorporating theories of behavior change and feedback from target populations are essential when developing mHealth interventions. Following user-centered approaches that fully incorporate end users into design and development stages increases the likelihood that the intervention will be acceptable. Iterative design cycles and prototyping are important steps to gather user feedback to optimize an mHealth intervention. Broad sharing of knowledge and products generated during intervention development also is recommended. Assessment of behavioral principles, intervention components, or a full intervention package should be conducted to evaluate usability and efficacy. CONCLUSIONS: Pediatric health-care researchers and clinicians are increasingly using mHealth technology to target health behaviors and improve related outcomes. Pediatric psychologists should consider applying the design strategies outlined in the IDEAS framework to produce and disseminate mHealth interventions tailored to the specific needs of pediatric populations.

Examining the pattern of new foods and beverages consumed during obesity treatment to inform strategies for self-monitoring intake.

Maintaining dietary self-monitoring during obesity treatment may improve outcomes. As dietary variety is associated with energy intake, understanding the pattern of when new foods and beverages are consumed may assist with identifying when self-monitoring should occur. This study examined dietary variety (total number of differing foods and beverages consumed) from the first 40 days of self-monitoring records reporting ≥ 3 eating occasions and >600 kcal/day from 60 adults (55.9 ±â€¯9.1 yrs, 35.1 ±â€¯5.3 kg/m2, 80.0% female, 95.0% white) participating in a smartphone-based, lifestyle intervention. Dietary variety was coded using an ingredient-based approach. Additionally, new flavors of previously consumed items, and modified and non-modified items contributed to variety. Total number of different foods and beverages consumed over 40 coded days (cumulative variety [cv40]); number of days to reach 50%, 75%, and 100% of cv40; cv40 by eating occasions; and mean number of new items consumed on weekdays and weekend days were calculated. CV40 was 145.4 ±â€¯33.5. Number of coded days to consume 50%, 75%, and 100% of cv40 was 12.7, 25.1, and 40.0, respectively. Dinner was greater (p < 0.0001) in cv40 (58.6 ±â€¯18.5 different items) than other eating occasions, and lunch was greater (p < 0.0001) (38.8 ±â€¯10.7 different items) than breakfast and snack. Weekend days had a greater mean number of new items consumed than weekdays, (3.8 ±â€¯1.0 items vs. 3.6 ±â€¯0.9 items, p = 0.035). Variety of items consumed during obesity treatment is high, and to capture the majority of differing items consumed, at least 4 weeks of detailed recording is needed. After this, to capture new foods and beverages consumed, self-monitoring dinners, lunch, and weekend days may be helpful.

Pain worsening with physical activity during migraine attacks in women with overweight/obesity: A prospective evaluation of frequency, consistency, and correlates.

Background Migraine is a neurological disease involving recurrent attacks of moderate-to-severe and disabling head pain. Worsening of pain with routine physical activity during attacks is a principal migraine symptom; however, the frequency, individual consistency, and correlates of this symptom are unknown. Given the potential of this symptom to undermine participation in daily physical activity, an effective migraine prevention strategy, further research is warranted. This study is the first to prospectively evaluate (a) frequency and individual consistency of physical activity-related pain worsening during migraine attacks, and (b) potential correlates, including other migraine symptoms, anthropometric characteristics, psychological symptoms, and daily physical activity. Methods Participants were women (n = 132) aged 18-50 years with neurologist-confirmed migraine and overweight/obesity seeking weight loss treatment in the Women's Health and Migraine trial. At baseline, participants used a smartphone diary to record migraine attack occurrence, severity, and symptoms for 28 days. Participants also completed questionnaires and 7 days of objective physical activity monitoring before and after diary completion, respectively. Patterning of the effect of physical activity on pain was summarized within-subject by calculating the proportion (%) of attacks in which physical activity worsened, improved, or had no effect on pain. Results Participants reported 5.5 ± 2.8 (mean ± standard deviation) migraine attacks over 28 days. The intraclass correlation (coefficient = 0.71) indicated high consistency in participants' reports of activity-related pain worsening or not. On average, activity worsened pain in 34.8 ± 35.6% of attacks, had no effect on pain in 61.8 ± 34.6% of attacks and improved pain in 3.4 ± 12.7% of attacks. Few participants (9.8%) reported activity-related pain worsening in all attacks. A higher percentage of attacks where physical activity worsened pain demonstrated small-sized correlations with more severe nausea, photophobia, phonophobia, and allodynia (r = 0.18 - 0.22, p < 0.05). Pain worsening due to physical activity was not related to psychological symptoms or total daily physical activity. Conclusions There is large variability in the effect of physical activity on pain during migraine attacks that can be accounted for by individual differences. For a minority of participants, physical activity consistently contributed to pain worsening. More frequent physical activity-related pain worsening was related to greater severity of other migraine symptoms and pain sensitivity, which supports the validity of this diagnostic feature. Study protocol ClinicalTrials.govIdentifier: NCT01197196.