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Adverse Childhood Experiences (ACEs) affect almost half of youth in the U.S. and are linked to a host of deleterious medical and psychosocial outcomes. The current study examines the relationships among ACEs, childhood obesity, and modifiable lifestyle behaviors to inform clinical care, future research, and policy. Using data from the 2016-2018 National Survey of Children's Health (NSCH), associations between children's ACEs, weight status, and health behaviors that may influence the link between ACEs and obesity were examined. In the NSCH data, 25.3% of youth aged 10-17 years experienced one ACE with another 25.9% experiencing two or more ACEs. Having ACEs was related to excess screen time and inadequate sleep, and independently associated with obesity. Findings highlight the importance of providers screening and finding ways to intervene on behalf of youth with obesity. The present provides guidelines for providers on intervening with youth experiencing ACEs.

Blood pressure (BP) assessment and management are important aspects of care for youth with obesity. This study evaluates data of youth with obesity seeking care at 35 pediatric weight management (PWM) programs enrolled in the Pediatric Obesity Weight Evaluation Registry (POWER). Data obtained at a first clinical visit for youth aged 3-17 years were evaluated to: (1) assess prevalence of BP above the normal range (high BP); and (2) identify characteristics associated with having high BP status. Weight status was evaluated using percentage of the 95

BackgroundAdherence to dietary interventions is a significant barrier in the treatment of childhood obesity. Time-limited eating (TLE) is a simple dietary approach that limits food intake to a given number of consecutive hours per day, but parental and youth acceptability of TLE in youth with obesity is unknown. This study explored the feasibility of utilizing TLE among parents and youth attending pediatric weight management (PWM).MethodsMembers of COMPASS (Childhood Obesity Multi-Program Analysis and Study System) developed a survey to assess the acceptability of TLE in families attending PWM, which included patient characteristics, current diet and sleep schedules, and interests in trying TLE. The survey was administered electronically via REDCap or manually to parents of patients between the ages of 8-17 years old and to patients 11-17 years old attending one of five PWM practices in the COMPASS network.ResultsPatients (n=213) were 13.0 ± 2.5 years old, 58% female, 52% White, 22% Black, 17% Hispanic/Latino, and 47% reported a diagnosed psychological disorder. On average, parents reported their child’s daily eating spanned 12.5 ± 1.9 hours (7:35am - 8:05pm) and included 5.6 ± 1.6 eating bouts (meals + snacks). Most parents reported being likely to try TLE ≤12 hours/d (TLE12: 66%), which was similar to the likelihood of following a nutrient-balanced diet (59%). Likelihood was lower for TLE ≤10 hours/d (TLE10: 39%) or ≤8 hours/d (TLE8: 26%) (pConclusionsTwo-thirds of parents with children attending PWM programs report interest in TLE ≤12 hours/d regardless of demographic characteristics, but interest wanes when limiting eating to ≤10 or ≤8 hours per day. Time-limited eating appears to be a feasible option in PWM settings provided treatment options are individualized based on the interests and barriers of patients and their families.

Background: The prevalence of severe obesity and electronic game use among youth has increased over time. Methods: We administered a survey assessing gaming and psycho-demographic characteristics to youth aged 11–17 attending five weight management programs. We conducted chi-square and logistic regression analyses to describe the association between class 3 severe obesity and gaming characteristics. Results: Four hundred twelve youth (51% female, 26% Black, 25% Hispanic, 43% White, and 44% with class 3 severe obesity) completed the survey. There was a stepwise relationship between time spent gaming and class 3 severe obesity, with 28% of those playing 2 to

Early-onset severe obesity in childhood presents a significant clinical challenge signaling an urgent need for effective and sustainable interventions. A large body of literature examines overweight and obesity, but little focuses specifically on the risk factors for severe obesity in children ages 5 and younger. This narrative review identified modifiable risk factors associated with severe obesity in children ages 5 and younger: nutrition (consuming sugar sweetened beverages and fast food), activity (low frequency of outdoor play and excessive screen time), behaviors (lower satiety responsiveness, sleeping with a bottle, lack of bedtime rules, and short sleep duration), and socio-environmental risk factors (informal child care setting, history of obesity in the mother, and gestational diabetes). The lack of literature on this topic highlights the need for additional research on potentially modifiable risk factors for early-onset severe obesity.

Summary Youth with obesity are at increased risk of psychosocial symptoms; however, little is known regarding the impact of paediatric weight management (PWM) on psychosocial health. The aim of the study was to investigate changes in psychosocial health among children who completed a 7-week PWM program. Participants aged 5 to 16 years with a BMI ≥85th percentile completed a 7-week, family-centred PWM program focused on health behaviour education, exercise and mentored goal setting. The Paediatric Symptom Checklist (PSC) was assessed via parent report to evaluate psychosocial symptoms before and after the program, and subscales were calculated for internalizing (PSC-IS), externalizing (PSC-ES) and attention symptoms (PSC-AS). At baseline, positive screen rates for psychosocial symptoms among the 317 patients included 16.1% for PSC, 14.1% for PSC-ES, 18.6% for PSC-IS and 12.3% for PSC-AS. Among program completers, total PSC scores improved in those with normal (p = 0.010) and elevated p < .001 psychosocial symptoms at baseline. Youth with positive screens for elevated PSC subscales improved their subscale scores, on average, and the majority reduced scores to below elevated levels for PSC (54.2%), PSC-ES (64.7%), PSC-IS (78.3%) and PSC-AS (64.7%). Improvements in PSC remained significant after adjusting for BMI changes during treatment, but BMI differed across PSC-change groups, including BMI increases among participants with PSC deterioration (0.33 ± 0.64 kg m−2) (P = 0.035) and BMI decreases among patients with no reliable PSC change (−0.26 ± 1.04 kg m−2) (P = 0.038) or reliable PSC improvement (−0.22 ± 0.74 kg m−2) (P = 0.025). Youth with positive screens for psychosocial symptoms can improve emotional and behavioural functioning during short-term PWM. Future research is needed to elucidate mechanisms and long-term outcome durability.

The Family Nutrition and Physical Activity Screening Tool (FNPA) evaluates family behavioural and environmental factors associated with pediatric obesity, but it is unknown if FNPA scores differ among youth across obesity severities. Our aim was to determine the association between the FNPA and obesity severity in youth referred to weight management.Upon initiating treatment, height, weight, and the FNPA were collected according to standard procedures. Cut-points for overweight/obesity, severe obesity (SO) class 2, and SO class 3 were calculated. FNPA scores were compared across weight status groups using analysis of covariance, and odds of SO across FNPA quartiles were evaluated with multiple logistic regression.Participants included 564 5-18year old who initiated treatment and completed the FNPA. After adjustment, FNPA scores differed by weight status with higher/healthier scores in youth with overweight/obesity (56.6±8.5) when compared to those with SO class 2 (55.0±7.1; p=0.015) or SO class 3 (53.6±9.0; p0.001). Compared to those in the highest FNPA quartile, youth in the 2nd quartile had 1.8 (95% CI: 1.1, 2.9) times higher odds of SO, and those in the lowest FNPA quartile had 2.1 (95% CI: 1.3, 3.4) times higher odds of SO. Youth with SO had unhealthier subscale scores among 6 of 10 constructs, including nutritional, physical activity, sedentary, and sleep behaviours.Results suggest a consistent inverse relationship between the FNPA and adiposity among youth presenting for weight management. The FNPA is a useful metric for programs and clinicians targeting family behaviours and the home environment to combat obesity.

Attrition in pediatric weight management negatively impacts treatment outcomes. A potentially modifiable contributor to attrition is unmet family expectations. This study aimed to evaluate the association between adolescent and parent/guardian treatment expectations and attrition.A prospective, nonrandomized, uncontrolled, single-arm pilot trial was conducted among 12 pediatric weight management programs in the Children's Hospital Association's FOCUS on a Fitter Future collaborative. Parents/guardians and adolescents completed an expectations/goals survey at their initial visit, with categories including healthier food/drinks, physical activity/exercise, family support/behavior, and weight management goals. Attrition was assessed at 3 months.From January to August 2013, 405 parents/guardians were recruited and reported about their children (203 adolescents, 202 children12 years). Of the 203 adolescents, 160 also self-reported. Attrition rate was 42.2% at 3 months. For adolescents, greater interest in family support/behavior skills was associated with decreased odds of attrition at 3 months [odds ratio (OR) 0.75, 95% confidence interval (CI) 0.57-0.98, p = 0.04]. The more discordant the parent/adolescent dyad responses in this category, the higher the odds of attrition at 3 months (OR 1.36, 95% CI 1.04-1.78, p = 0.02). Weight loss was an important weight management goal for both adolescents and parents. For adolescents with this goal, the median weight-loss goal was 50 pounds. Attrition was associated with adolescent weight-loss goals above the desired median (50% above the median vs. 28% below the median, p = 0.02).Assessing initial expectations may help tailor treatment to meet families' needs, especially through focus on family-based change and realistic goal setting.Clinicaltrials.gov NCT01753063.

Liguori, G, Schuna, JM Jr, Tucker, J, and Fountaine, CM. Impact of prescribed exercise on physical activity compensation in young adults. J Strength Cond Res 31(2): 503-508, 2017-Army Reserve Officers' Training Corps cadets present a unique subpopulation because they are required to participate in regular physical activity (PA). This study describes PA patterns of cadets and attempts to identify evidence of nonexercise PA compensation (activitystat) as a result of prescribed PA (pPA) by comparing differences between training and nontraining days for (a) autonomous PA among cadets and (b) PA between cadets and noncadets. Participants included 84 university students (33 cadets and 51 noncadets) who each wore an accelerometer for 5 consecutive days to estimate moderate and vigorous physical activity (MVPA). A 2×2 mixed model analysis of variance was used to examine within- and between-group differences in MVPA on training and nontraining days. This analysis was repeated after removing the cadet's pPA. Cadets had lower-body fat than noncadets (p = 0.044), but all other characteristics were similar. Overall, moderate PA (MPA) and vigorous PA (VPA) were significantly greater among cadets (p = 0.048 and p < 0.001), because of greater weekend MPA (p = 0.021) and greater weekday VPA (p < 0.001). Cadets accumulated more MVPA on training days than nontraining days (p < 0.001) and accumulated more MVPA than noncadets on training days (p = 0.004). However, after accounting for pPA, cadet MVPA did not differ between training and nontraining days (within 1.2Â ± 18.4 min·d) and was similar between cadets and noncadets (within 1.5Â ± 5.9 min·d). These results suggest that cadets were significantly more active than noncadets due mainly to pPA. When controlling for pPA, cadets were similarly active across all days, and were as active as noncadets, indicating no evidence of activitystat in this population.

Prior studies show seven percent to nine percent of children demonstrate gaming behaviors that affect a child's ability to function (e.g., problem gaming), but none have examined the association between problem gaming and weight status. The objective of this study was to determine the prevalence of problem gaming among children enrolled in tertiary weight management programs. We administered a computer-based survey to a convenience sample of children aged 11-17 years enrolled in five geographically diverse pediatric weight management (PWM) programs in the COMPASS (Childhood Obesity Multi-Program Analysis and Study System) network. The survey included demographics, gaming characteristics, and a problem gaming assessment. The survey had 454 respondents representing a diverse cohort (53 percent females, 27 percent black, 24 percent Hispanic, 41 percent white) with mean age of 13.7 years. A total of 8.2 percent of respondents met criteria for problem gaming. Problem gamers were more likely to be white, male, play mature-rated games, and report daily play. Children in PWM programs reported problem gaming at the same rate as other pediatric populations. Screening for problem gaming provides an opportunity for pediatricians to address gaming behaviors that may affect the health of children with obesity who already are at risk for worsened health and quality of life.

BACKGROUND We tested the effectiveness of the Go Wild With Fruits and Veggies! (GWWFV) Extension curriculum on increasing fruit and vegetable (FV) intake of third graders. METHODS An intervention study was used testing self-reported FV intake pre/post GWWFV. Recruited schools were randomized to control (12 schools, N = 369, third grade children) or intervention (14 schools, N = 378, third grade children). Measures included items from a validated FV food frequency survey. Access to the federal Fresh Fruit and Vegetable Snack Program (FFVSP), and taste testing within GWWFV were also measured. Between-group differences in FV intake were evaluated using 1-way ANOVA for unadjusted models and 1-way ANCOVA for baseline adjusted models. The Tukey-Kramer test was employed for post hoc comparisons. RESULTS Students with access to the FFVSP consumed more fruits (p

OBJECTIVE This study aimed to examine whether 1-month BMI improvement is predictive of superior 6- and 12-month BMI changes in a national sample of youth in pediatric weight management treatment. METHODS Participants were 4- to 18-year-olds from the Pediatric Obesity Weight Evaluation Registry, a prospective study collecting data from 31 pediatric weight management programs across the United States. Response at 1 month was defined as ≥ 3% BMI reduction; success at 6 and 12 months was defined as ≥ 5% BMI reduction from baseline. Analyses used linear and logistic regression with robust variance estimation. RESULTS Primary analyses were completed with 687 participants (mean age 12.2 years). One-month responders demonstrated significant improvements in BMI compared with nonresponders at 6 months (BMI, -2.05 vs. 0.05; %BMI, -5.81 vs. 0.23; P

BACKGROUND AND OBJECTIVES As a distinct group, 2- to 5-year-olds with severe obesity (SO) have not been extensively described. As a part of the Expert Exchange Workgroup on Childhood Obesity, nationally-representative data were examined to better characterize children with SO. METHODS Children ages 2 to 5 (N = 7028) from NHANES (1999–2014) were classified as having normal weight, overweight, obesity, or SO (BMI ≥120% of 95th percentile). Sociodemographics, birth characteristics, screen time, total energy, and Healthy Eating Index 2010 scores were evaluated. Multinomial logistic and linear regressions were conducted, with normal weight as the referent. RESULTS The prevalence of SO was 2.1%. Children with SO had higher (unadjusted) odds of being a racial and/or ethnic minority (African American: odds ratio [OR]: 1.7; Hispanic: OR: 2.3). They were from households with lower educational attainment (OR: 2.4), that were single-parent headed (OR: 2.0), and that were in poverty (OR: 2.1). Having never been breastfed was associated with increased odds of obesity (OR: 1.5) and higher odds of SO (OR: 1.9). Odds of >4 hours of screen time were 1.5 and 2.0 for children with obesity and SO. Energy intake and Healthy Eating Index 2010 scores were not significantly different in children with SO. CONCLUSIONS Children ages 2 to 5 with SO appear to be more likely to be of a racial and/or ethnic minority and have greater disparities in social determinants of health than their peers and are more than twice as likely to engage in double the recommended screen time limit.

In this article, we describe a protocol used to test the functional capacity of the obese pediatric patient and describe the peak oxygen consumption (VO2peak) of patients seeking treatment at a pediatric weight management center.One hundred eleven (mean age, 12.5 ± 3.0 years) patients performed a multistage exercise test on a treadmill, of which 90 (81%) met end-test criteria and provided valid VO2peak data. Peak VO2 was expressed: (1) in absolute terms (L·min(-1)); (2) as the ratio of the volume of oxygen consumed per minute relative to total body mass (mL·kg(-1)·min(-1)); and (3) as the ratio of the volume of oxygen consumed per minute relative to fat-free mass (mL·FFM·kg(-1)·min(-1)).Mean BMI z-score was 2.4 ± 0.3 and the mean percent body fat was 36.5 ± 9.7%. Absolute VO2peak (L·min(-1)) was significantly different between sexes; however, relative values were similar between sexes. Mean VO2peak was 25.7 ± 4.8 mL·kg(-1)·min(-1) with a range of 13.5-36.7 mL·kg(-1)·min(-1).Obese youth seeking treatment at a stage 3 pediatric weight management center exhibit low VO2peak. The protocol outlined here should serve as a model for similar programs interested in the submaximal and peak responses to exercise in obese pediatric patients.

BACKGROUND AND OBJECTIVES: As a distinct group, 2- to 5-year-olds with severe obesity (SO) have not been extensively described. As a part of the Expert Exchange Workgroup on Childhood Obesity, nationally-representative data were examined to better characterize children with SO. METHODS: Children ages 2 to 5 (N = 7028) from NHANES (1999–2014) were classified as having normal weight, overweight, obesity, or SO (BMI ≥120% of 95th percentile). Sociodemographics, birth characteristics, screen time, total energy, and Healthy Eating Index 2010 scores were evaluated. Multinomial logistic and linear regressions were conducted, with normal weight as the referent. RESULTS: The prevalence of SO was 2.1%. Children with SO had higher (unadjusted) odds of being a racial and/or ethnic minority (African American: odds ratio [OR]: 1.7; Hispanic: OR: 2.3). They were from households with lower educational attainment (OR: 2.4), that were single-parent headed (OR: 2.0), and that were in poverty (OR: 2.1). Having never been breastfed was associated with increased odds of obesity (OR: 1.5) and higher odds of SO (OR: 1.9). Odds of >4 hours of screen time were 1.5 and 2.0 for children with obesity and SO. Energy intake and Healthy Eating Index 2010 scores were not significantly different in children with SO. CONCLUSIONS: Children ages 2 to 5 with SO appear to be more likely to be of a racial and/or ethnic minority and have greater disparities in social determinants of health than their peers and are more than twice as likely to engage in double the recommended screen time limit.

We compared the diagnostic accuracy of CT performed without and with oral contrast for suspected appendicitis in children. In this retrospective cohort study, we reviewed abdomen/pelvis CT scans with IV contrast performed between 2011 and 2015 for suspected appendicitis. Oral contrast was used routinely before August 2013 and eliminated from the CT protocol thereafter. Diagnostic accuracy of CT was compared with operative/pathology reports, and included a 30-day follow-up period for non-surgical patients. For a secondary analysis, the oral contrast group was subdivided into “complete” (contrast extending into the cecum) or “partial” contrast. We also compared groups for CT turnaround time, the frequency of appendiceal perforation and abscess, and the potential influence of a prior appendix ultrasound. Five hundred fifty-eight patients were included: 51.6% (n = 288) without oral contrast and 48.4% (n = 270) with oral contrast (of which 52% (n = 140/270) had “complete” contrast). There was no difference in diagnostic accuracy between the oral contrast and non-contrast groups (p = 0.903), with sensitivity/specificity of 93.8% (95% CI 84.8–98.3)/98.5% (CI 95.8–99.7) and 94.6% (CI 84.9–98.9)/98.3% (CI 95.7–99.5), respectively. Similarly, there was no difference in accuracy when comparing only “complete” contrast vs. non-contrast groups (p = 0.755). CT turnaround time for the non-contrast group was significantly faster (43.8 ± 37.6 min), on average, than the oral contrast group (137.4 ± 47.5 min). For children evaluated by CT with IV contrast for suspected appendicitis, administering oral contrast increased wait time by > 90 min, did not reach the cecum in 48% of cases, and did not improve diagnostic accuracy. Oral contrast for pediatric CT appendicitis evaluation is not warranted.

Children classified as overweight or obese and those with disabilities are at a greater risk of not meeting the minimum recommendation of 60 min a day of moderate to vigorous physical activity (PA). Youth with Prader-Willi Syndrome (PWS) appear to participate in less PA compared to nonsyndromal children, likely due to syndrome-related factors. However, description of PA patterns in youth with PWS is lacking. The purpose of this study was to characterize PA in youth with PWS and to compare it to PA in children with nonsyndromal obesity. Twenty-four youth with PWS (ages 8-16 years) and 40 obese children without PWS (OB) (ages 8-11 years) wore accelerometers for eight consecutive days. Data were screened for compliance and classified into PA intensities: sedentary behavior (SED), light (LPA), moderate (MPA), vigorous (VPA) and moderate plus vigorous (MVPA). Youth with PWS spent 19.4% less time in weekly LPA (p=0.007) and 29.8% less time in weekly VPA compared to OB controls (p=0.036). All other intensities were similar between groups. In addition, PWS participated in less LPA and VPA during the weekends compared to OB, and less LPA on weekdays when compared to OB. There was also a trend towards PWS participating in less MVPA during the weekends and less VPA during the weekends than OB controls. There was a trend towards PWS participating in less VPA on weekends compared to weekdays, while OB participated similarly in VPA on weekdays and weekend days. On average, neither PWS nor OB children met minimum MVPA recommendations. The results suggest there is a need to design exercise programs for PWS youth that focus on integrating vigorous intensity activities, especially during the weekends when structured PA may not be available.

Purpose. Examine the extent to which meat consumption influences risk of weight gain in women during a 20-month period. Additionally, to determine the extent to which demographic, lifestyle, and dietary factors influence the meat-weight gain association. Design. Prospective cohort. Setting. Two metropolitan areas of the Mountain West. Subjects. Two hundred thirty-seven middle-aged women. Measures. Diet was assessed by using 7-day weighed food records, and physical activity was measured by using accelerometers. Other potential confounders included age; initial body weight; energy intake; percentage of energy from fat, protein, and carbohydrate; dietary fiber intake per 1000 kcal; and time in the investigation. Two meat variables were studied: very lean meat (VLM) and other meat (Meat). Analysis. Multiple regression, partial correlation, and relative risk. Results. Each additional serving (1 ounce) of Meat consumed at baseline per 1000 kcal was associated with a 1.19-kg gain in weight over time (F = 7.3, p = .0073). Controlling for physical activity, fiber, and macronutrient intake, individually, strengthened the relationship. Servings of VLM per 1000 kcal were not predictive of weight change (F= .00, p = .9576). With all potential confounders controlled, the relative risk of gaining weight (>5 pounds) for women with Low Meat intake was .36 (95% confidence interval = .17–.76) compared to women with High Meat intake. Conclusion. Consuming meats other than those in the VLM category is associated with increased risk of weight gain over time.

Context: Ingesting high-sodium drinks pre-exercise can improve thermoregulation and performance. Athletic trainers (19%) give athletes pickle juice (PJ) prophylactically for cramping. No data exist on whether this practice affects aerobic performance or thermoregulation. Objective: To determine if drinking 2 mL/kg body mass of PJ, hypertonic saline, or deionized water (DIW) pre-exercise affects aerobic performance or thermoregulation. Design: Crossover study. Setting: Controlled laboratory study. Patients or Other Participants: Nine euhydrated men (age = 22 ± 3 years, height = 184.0 ± 8.2 cm, mass = 82.6 ± 16.0 kg) completed testing. Intervention(s): Participants rested for 65 minutes. During this period, they ingested 2 mL/kg of PJ, hypertonic saline, or DIW. Next, they drank 5 mL/kg of DIW. Blood was collected before and after ingestion of all fluids. Participants were weighed and ran in the heat (temperature = 38.3°C ± 1°C, relative humidity = 21.1% ± 4.7%) at increasing increments of maximal heart rate (50%, 60%, 70%, 80%, 90%, 95%) until exhaustion or until rectal temperature exceeded 39.5°C. Participants were weighed postexercise so we could calculate sweat volume. Main Outcome Measure(s): Time to exhaustion, rectal temperature, changes in plasma volume, and sweat volume. Results: Time to exhaustion did not differ among drinks (PJ = 77.4 ± 5.9 minutes, hypertonic saline = 77.4 ± 4.0 minutes, DIW = 75.7 ± 3.2 minutes; F2,16 = 1.1, P = .40). Core temperature of participants was similar among drinks (PJ = 38.7°C ± 0.3°C, hypertonic saline = 38.7°C ± 0.4°C, DIW = 38.8°C ± 0.4°C; P = .74) but increased from pre-exercise (36.7°C ± 0.2°C) to postexercise (38.7°C ± 0.4°C) (P < .05). No differences were observed for changes in plasma volume or sweat volume among drinks (P > .05). Conclusions: Ingesting small amounts of PJ or hypertonic saline with water did not affect performance or select thermoregulatory measures. Drinking larger volumes of PJ and water may be more effective at expanding the extracellular space.

Background: Primary care offers a promising setting for promoting parenting practices that shape healthy eating and physical activity behaviors of young children. This study assessed the impact of a parent-based, primary care intervention on the feeding habits, health behaviors, and body mass index (BMI) of 2&ndash, 5 year olds with elevated or rapidly-increasing BMI. Methods: Four private pediatric offices in West Michigan were assigned as control (n = 2) or intervention (n = 2) sites based on patient load and demographics. Treatment families were recruited at well-child visits to receive physician health-behavior counseling and four visits with a registered dietitian nutritionist (RDN) over a 6-month period. Intervention outcomes were age- and sex-specific BMI metrics, including BMI z-scores and percent of the 95th percentile (%BMIp95), the Family Nutrition and Physical Activity survey (FNPA), and the Feeding Practices and Structure Questionnaire (FPSQ). Results: Of 165 enrolled families, 127 completed follow-up measures (77% retention). Mean (&plusmn, SD) FNPA scores improved in treatment vs. control (4.6 &plusmn, 4.6 vs. 0.1 &plusmn, 4.2, p &lt, 0.001), and screen time (h/day) decreased (&minus, 0.9 &plusmn, 1.8 vs. 0.3 &plusmn, 1.1, 0.001). Non-responsive feeding practices (i.e., reward for behavior (p = 0.006) and distrust in appetite (p &lt, 0.015)) and structure-related feeding practices (structured meal timing (p &lt, 0.001)) improved in treatment parents vs. controls. Reductions in child BMI measures did not differ between groups. Conclusions: Families with preschool children participating in a low-intensity, primary care intervention improved obesogenic health behaviors, parent feeding habits, and child screen time, but not child adiposity. Future research should assess the sustainability of these family lifestyle improvements, and evaluate their future impact on the health and development of the children.

Objective Research indicates that risk of obesity increases as physical activity (PA) decreases; however, the reciprocal effect has been rarely studied. The present investigation was conducted to determine the contribution of obesity on objectively measured PA over 20 months. Design and Methods A prospective cohort design with 254 middle-aged women was employed. Body fat percentage (BF%) was measured using Bod Pod, and obesity was defined as BF% ≥32%. PA was assessed objectively using 7-day accelerometry at baseline and ∼20 months later at follow-up. Results Of the 254 subjects, 124 were obese (49%) at baseline. Mean BF% was 32.1 ± 7.8 and average age was 41.7 ± 3.1 years. Mean weekly PA was 2.79 ± 0.85 million activity counts for all participants. Over the 20-month period, PA decreased significantly more in obese women (−8.1% ± 27.1%) than in nonobese women (0.3% ± 31.7%) after adjusting for confounders (F = 5.3, P = 0.022). Moderate plus vigorous PA levels also decreased more in obese women (−28.1 ± 73.6 min/week) than in nonobese women (−5.9 ± 66.8 min/week), after adjusting for covariates (F = 7.84; P = 0.0055). Conclusions It appears that obese women tend to reduce PA over time at a faster rate than nonobese women. Evidently, obesity is a risk factor for decreasing PA over time in middle-aged women.

Prospective patient registries have been successfully utilized in several disease states with a goal of improving treatment approaches through multi-institutional collaboration. The prevalence of youth with severe obesity is at a historic high in the United States, yet evidence to guide effective weight management is limited. The Pediatric Obesity Weight Evaluation Registry (POWER) was established in 2013 to identify and promote effective intervention strategies for pediatric obesity.Sites in POWER provide multicomponent pediatric weight management (PWM) care for youth with obesity and collect a defined set of demographic and clinical parameters, which they regularly submit to the POWER Data Coordinating Center. A program profile survey was completed by sites to describe characteristics of the respective PWM programs.From January 2014 through December 2015, 26 US sites were enrolled in POWER and had submitted data on 3643 youth with obesity. Ninety-five percent were 6-18 years of age, 54% female, 32% nonwhite, 32% Hispanic, and 59% publicly insured. Over two-thirds had severe obesity. All sites included a medical provider and used weight status in their referral criteria. Other program characteristics varied widely between sites.POWER is an established national registry representing a diverse sample of youth with obesity participating in multicomponent PWM programs across the United States. Using high-quality data collection and a collaborative research infrastructure, POWER aims to contribute to the development of evidence-based guidelines for multicomponent PWM programs.

Background: This investigation evaluated seasonal changes in preschoolers’ (3-5 years) sedentary time and physical activity (PA) during childcare. Methods: Sixty-two children from 4 preschools in Fargo, North Dakota had their sedentary behavior and PA objectively assessed during 2 separate weeks of childcare. Children wore accelerometers for 5 consecutive days, once each in the fall (October/November) and winter (January/February). Separate analyses were conducted to evaluate seasonal changes in full-day, indoor only, and outdoor only sedentary time and PA during childcare. Results: When expressed relative to accelerometer wear time, the full-day rate of sedentary time accumulation (minutes/hour) increased significantly from fall to winter (p < 0.001), while accumulation rates for all other PA variables (light PA, moderate PA, moderate-to-vigorous PA, and activity counts) significantly declined during this period (all p’s < 0.001). No significant changes in accumulation rates for sedentary time or PA (light PA, moderate PA, moderate-tovigorous PA, and activity counts) were noted for either indoor or outdoor time between seasons. Conclusions: Childcare-related sedentary time and PA can dramatically vary across seasons., {"references":["Ogden, C. and M. Carroll. Prevalence of obesity among children and adolescents: United States, trends 1963-1965 through 2007-2008. 2010 [cited 2011 September 19th]; Available from: http://www.cdc.gov/nchs/data/hestat/ obesity_child_07_08/obesity_child_07_08.htm","Must A, Anderson SE. Effects of obesity on morbidity in children and adolescents. Nutr Clin Care 2003; 6: 4-12","Francis SL, Stancel MJ, Sernulka-George FD, Broffitt B, Levy SM, Janz KJ. Tracking of TV and video gaming during childhood: Iowa Bone Development Study. Int J Behav Nutr Phys Act 2011; 8: 100. http://dx.doi.org/10.1186/1479-5868-8-100"]}

The purpose was to determine the relationship between insulin resistance (IR) and risk of gaining body fat percentage (BF%), body weight, and abdominal fat over 18 months. A prospective cohort study was conducted using a sample of 226 women. IR was assessed using fasting blood insulin and glucose levels to calculate homeostatic model assessment (HOMA). Participants were divided into High (4th quartile) Moderate (2nd and 3rd quartiles), and Low (1st quartile) HOMA categories. BF% was estimated using plethysmography (Bod Pod), weight was measured in a standard swimsuit, and abdominal fat was indexed using the average of two circumferences taken at the umbilicus. Participants wore accelerometers and completed weighed food logs for 7 consecutive days to control for the effect of physical activity (PA) and energy intake, respectively. On average, women in the High HOMA group decreased in BF% (-0.48 ± 3.60), whereas those in the Moderate (0.40 ± 3.66) and Low HOMA (1.17 ± 3.15) groups gained BF% (F = 5.4, P = 0.0211). Changes in body weight showed a similar dose-response relationship (F = 4.7, P = 0.0317). However, baseline IR was not predictive of changes in abdominal fat (F = 0.8, P = 0.3635). Controlling for several covariates had little effect on gains in BF% and weight, but adjusting for initial BF% and/or initial weight nullified changes in BF% and weight across the IR groups. In conclusion, women with High HOMA tend to gain significantly less BF% and weight than women with low or moderate HOMA. The decreased risk appears unrelated to several covariates, except initial BF% and weight levels, which seem to play key roles in the relationships.

Background To date, no study has objectively measured physical activity levels among U.S. adults according to the 2008 Physical Activity Guidelines for Americans (PAGA). Purpose The purpose of this study was to assess self-reported and objectively measured physical activity among U.S. adults according to the PAGA. Methods Using data from the NHANES 2005–2006, the PAGA were assessed using three physical activity calculations: moderate plus vigorous physical activity ≥150 minutes/week (MVPA); moderate plus two instances of vigorous physical activity ≥150 minutes/week (M2VPA); and time spent above 3 METs ≥500 MET-minutes/week (METPA). Self-reported physical activity included leisure, transportation, and household activities. Objective activity was measured using Actigraph accelerometers that were worn for 7 consecutive days. Analyses were conducted in 2009–2010. Results U.S. adults reported 324.5±18.6 minutes/week (M±SE) of moderate physical activity and 73.6±3.9 minutes/week of vigorous physical activity, although accelerometry estimates were 45.1±4.6 minutes/week of moderate physical activity and 18.6±6.6 minutes/week of vigorous physical activity. The proportion of adults meeting the PAGA according to M2VPA was 62.0% for self-report and 9.6% for accelerometry. Conclusions According to the NHANES 2005–2006, fewer than 10% of U.S. adults met the PAGA according to accelerometry. However, physical activity estimates vary substantially depending on whether self-reported or measured via accelerometer.

The purpose of this study was to determine the joint association of fatness and physical activity on resting blood pressure in children. Subjects included 157 children (age 5.5–9.5 years). Moderate-to-vigorous physical activity (MVPA, min/day), body fatness, and resting blood pressure were measured. Four categories were created by cross tabulation of high/normal levels of fatness and high/low levels of MVPA. There were significant differences in systolic blood pressure and mean arterial pressure across the fat/MVPA groups (p < .05). Regardless of participating in an acceptable level of MVPA, overfat children had higher resting systolic blood pressure than normal fat children. MVPA did not significantly attenuate blood pressure within a fat category.

Background:This study was designed to develop a prediction algorithm that would allow the Previous Day Physical Activity Recall (PDPAR) to be equated with temporally matched data from an accelerometer.Methods:Participants (n = 121) from a large, school-based intervention wore a validated accelerometer and completed the PDPAR for 3 consecutive days. Physical activity estimates were obtained from PDPAR by totaling 30-minute bouts of activity coded as ≥4 METS. A regression equation was developed in a calibration sample (n = 91) to predict accelerometer minutes of moderate to vigorous physical activity (MVPA) from PDPAR bouts. The regression equation was then applied to a separate, holdout sample (n = 30) to evaluate the utility of the prediction algorithm.Results:Gender and PDPAR bouts accounted for 36.6% of the variance in accelerometer MVPA. The regression model showed that on average boys obtain 9.0 min of MVPA for each reported PDPAR bout, while girls obtain 4.8 min of MVPA per bout. When applied to the holdout sample, predicted minutes of MVPA from the models showed good agreement with accelerometer minutes (r = .81).Conclusions:The prediction equation provides a valid and useful metric to aid in the interpretation of PDPAR results.

BACKGROUND The aim of the study was to determine if physical activity (PA) is associated with bone health in children with Prader-Willi syndrome (PWS). METHODS Participants included 23 children with PWS (age: 11.0±2.0 years). PA, measured by accelerometry, was categorized into light, moderate, vigorous and moderate plus vigorous intensities. Hip, total body minus the head (body), bone mineral content (BMC), bone mineral density (BMD) and BMD z-score (BMDz) were measured by dual X-ray absorptiometry. Separate hierarchical regression models were completed for all bone parameters, PA intensity and select covariates. RESULTS Moderate PA and select covariates explained the most variance in hip BMC (84.0%), BMD (61.3%) and BMDz (34.9%; p

Physical activity (PA) is essential for youth weight management. FOCUS on a Fitter Future (FFF), a group of health care professionals from 25 children's hospitals, sponsored by the Children's Hospital Association, examined current care practices for overweight and obese youth with the goal of building consensus on outcome measurements and quality improvement for pediatric weight management programs (WMPs). WMPs completed a survey regarding PA practices, including testing, assessment and intervention. Consistency in general treatment practices was noted with variability in implementation. All programs included PA assessment and counseling. A majority of programs measured aerobic fitness, and more than half evaluated muscular fitness. Most offered group exercise sessions. Programs differed in availability of resources, assessment tools, interventions and outcome measures. Based on current practice and research, the FFF PA subgroup recommends key components for inclusion in a pediatric WMP: exercise testing, body composition assessment, PA and sedentary behaviors measures, individual exercise counseling, and group exercise programming.

There are no existing multisite national data on obese youth presenting for pediatric weight management. The primary aim was to describe BMI status and comorbidities among youth with obesity presenting for pediatric weight management (PWM) at programs within the Pediatric Obesity Weight Evaluation Registry (POWER).Data were collected from 2009-2010 among 6737 obese patients ages 2-17. Patients were classified in three groups by BMI (kg/m(2)) cutoffs and percent of the 95th percentile for BMI: (1) obesity; (2) severe obesity class 2; and (3) severe obesity class 3. Weighted percentages are presented for baseline laboratory tests, blood pressure, and demographics. Generalized logistic regression with clustering was used to examine the relationships between BMI status and comorbidities.Study youth were 11.6 ± 3.4 years of age, 56% female, 31% black, 17% Hispanic, and 53% publicly insured. Twenty-five percent of patients had obesity (n = 1674), 34% (2337) had severe obesity class 2, and 41% (2726) had severe obesity class 3. Logistic regression revealed that males (odds ratio [OR], 1.8; 95% confidence interval [CI], 1.5-2.0), blacks (OR, 1.7; 95% CI, 1.5-2.0), age6 years (OR, 2.0; 95% CI, 1.5-2.6), and public insurance (OR, 1.8; 95% CI, 1.5-2.0) had a higher odds of severe obesity class 3. Severe obesity class 3 was associated with higher odds of laboratory abnormalities for hemoglobin A1c (OR, 1.7; 95% CI, 1.3-2.2), alanine aminotransferase ≥40 U/L (OR, 1.9; 95% CI, 1.3-2.6), and elevated systolic blood pressure (OR, 2.5; 95% CI, 2.0-3.0).Youth with obesity need earlier access to PWM given that they are presenting when they have severe obesity with significant comorbidities.

Purpose. To assess the relationship between self-reported and objectively measured physical activity (PA) and metabolic syndrome and its risk factors in U.S. adults. Design. A cross-sectional design was used for this study. Setting. The study was set among a nationally representative sample of U.S. adults. Subjects. Adults, ages 20 years and older, from the National Health and Nutrition Examination Survey (NHANES) 2003–2006 (n = 5580) participated in the study. Measures. PA measures included minutes per week of moderate plus vigorous PA estimated by self-report (MVPAsr), total 7-day accelerometry (MVPAa), and accelerometer-based MVPA performed in 10-minute bouts (MVPAb). Risk factors for metabolic syndrome included blood pressure, high-density lipoprotein cholesterol, triglycerides, glucose, and waist circumference. Analysis. Odds ratios (ORs) for having metabolic syndrome were calculated for men and women who met the Physical Activity Guidelines for Americans compared to those who did not. Results. Women who did not meet the PA guidelines had significantly greater odds of having metabolic syndrome according to MVPAsr (OR = 2.20; 95% confidence interval [CI] = 1.65–2.94), MVPAa (OR = 4.40; 95% CI= 2.65–7.31), and MVPAb (OR= 2.91; 95% CI= 1.42–5.96). Men had significantly higher odds of having metabolic syndrome according to MVPAa (OR = 2.57; 95% CI= 1.91–3.45) and MVPAb (OR = 2.83; 95% CI = 1.55–5.17), but not MVPAsr. These ORs remained significant after adjusting for all potential confounders except body mass index, after which only MVPAsr in women and MVPAb in men remained significant. Conclusion. Individuals who do not meet the PA guidelines exhibited greater odds of having metabolic syndrome. This relationship tended to be stronger for objective PA measures than for self-report.

Purpose: Emerging evidence suggests that infancy and early childhood may present a “window of opportunity” in which characteristics and lifestyle habits are still being formed and are therefore more malleable. Primary care offers a promising setting for obesity prevention and treatment given our established relationship with families and regular access to most children during well-child visits. The purpose of this study was to assess the impact of a primary care obesity prevention and treatment program in 2-5 year olds on parental feeding habits and child …

Purpose: to assess the impact of a primary care obesity prevention program in 0-2 year olds on dietary intake, active and sedentary behaviors, and parental feeding styles. Methods: Newborn infants presenting for well-child care were enrolled into either the control group or intervention group based on which of the 4 offices provided their care. Two offices were pre-determined control groups and two were intervention groups. The intervention included obesity-prevention specific physician training, newly developed handouts for ages newborn to 5 years, and 3 structured nutritionist …

Purpose.To identify independent patterns of diet using factor analysis to determine the extent to which dietary patterns account for differences in body fat percentage (BF%) and body mass index (BMI). Also, to ascertain the extent to which the associations are influenced by age, education, menopause, energy intake, and physical activity.Design.Study design was cross-sectional.Setting.Study setting was approximately 20 cities in the Mountain West.Subjects.The study included 281 apparently healthy female nonsmokers.Measures.Diet was assessed using 7-day weighed food records, and foods were categorized using the American Diabetes and American Dietetic Associations Exchange Lists and expressed as servings per 1000 kcal. BF% was measured using the Bod Pod, and physical activity was estimated using accelerometers worn for 1 week.Analysis.We used factor analysis, general linear models, and partial correlations.Results.Three dietary patterns were identified: (1) Prudent Pattern, (2) Low-fat Milk, and (3) Meat. Higher consumption of the Prudent Pattern corresponded with significantly lower BF% (F = 8.5, p = .0038) and BMI (F = 4.4, p = .0363). The Low-fat Milk pattern was inversely related to BF% (F= 5.4, p = .0207) and BMI (F= 9.5, p = .0023). Higher intake of the Meat pattern was related to higher levels of BF% (F= 4.5, p= .0346) and BMI (F= 4.2, p = .0418).Conclusion.These findings support an association between dietary patterns and body composition. Dietary patterns reflect the complex interrelationships inherent in day-to-day eating and are strongly related to differences in BF% and BMI in women.

Purpose. Examine the association between soft drink consumption and risk of weight gain over 4 years. Also, determine if the relationship between soft drink intake and weight gain is a result of differences in calorie intake or physical activity (PA), or other potential mediating factors. Design. Four-year prospective cohort. Setting. Approximately 20 cities in Utah and Wyoming. Subjects. One hundred seventy nonsmoking, apparently healthy women. Measures. At baseline, soft drink consumption and menopause status were measured using a questionnaire; calorie intake was estimated using 7-day, weighed food records; and PA was assessed using 7-day accelerometer data. Weight was assessed using an electronic scale at baseline and follow-up. Analysis. Multiple regression and partial correlation. Results. Four-year weight gain in participants who, at baseline, consumed sugar-sweetened soft drinks (2.7 ± 5.1 kg) was greater than in participants who consumed artificially sweetened soft drinks (–.1 ± 4.4 kg) or no soft drinks (.5 ± 5.1 kg) (F = 5.4, p = .022). Adjusting for objectively measured PA had no effect on risk of weight gain. However, controlling statistically for differences in calorie intake significantly weakened the relationship between soft drink consumption and weight gain by 28%. Conclusion. Consuming artificially sweetened soft drinks or no soft drinks instead of sugar-sweetened soft drinks may help to reduce risk of weight gain in women. The relationship appears to be partly a function of differences in calorie intake, but not differences in PA.

Individuals with Prader-Willi Syndrome (PWS) present hypotonia, low lean mass and a fairly low amount of spontaneous ambulatory physical activity (PA), possibly influencing bone mineral density (BM...

Objective To determine the relationship between adherence to the 2010 Dietary Guidelines for Americans and adiposity in young women with and without statistical adjustment for physical activity (PA). Methods Participants included 324 young women (aged 17–25 years). The researchers measured dietary intake using the Dietary History Questionnaire and determined diet quality using the 2010 Healthy Eating Index (HEI-2010). BOD POD (Cosmed, Rome, Italy, 2006) and accelerometry were used to assess body fat and PA, respectively. Results Women in the top quartile of HEI-2010 had significantly lower percent body fat than women in the lowest 3 quartiles (F = 3.36; P = .03). Controlling for objectively measured PA weakened this relationship by 20%. These young women (top quartile of HEI-2010) also had 0.37 odds (95% confidence interval, 0.16–0.85) of having body fat > 32%. Conclusions and Implications Young women whose diets most closely meet the 2010 Dietary Guidelines for Americans have lower adiposity.

This paper describes FitKids360, a stage 2 pediatric weight management program. FitKids360 is a physician-referred, multicomponent, low-cost healthy lifestyle program for overweight and obese youth 5–16 years of age and their families. FitKids360 provides an evidence-based approach to the treatment of pediatric overweight by targeting patients’ physical activity, screen time, and dietary behaviors using a family-centered approach. The intervention begins with a two-hour orientation and assessment period followed by six weekly sessions. Assessments include lifestyle behaviors, anthropometry, and the Family Nutrition and Physical Activity (FNPA) survey, which screens for obesogenic risk factors in the home environment. Outcomes are presented from 258 patients who completed one of 33 FitKids360 classes. After completing FitKids360, patients increased moderate to vigorous physical activity by 14 minutes (P=0.019), reduced screen time by 44 minutes (P<0.001), and improved key dietary behaviors. Overall, FNPA scores increased by 9% (P<0.001) and 69% of patients with “high risk” FNPA scores at baseline dropped below the “high risk” range by followup. Patients also lowered BMIs (P=0.011) and age- and sex-adjusted BMIz-scores (P<0.001) after completing the 7-week program. We hope this report will be useful to medical and public health professionals seeking to develop stage 2 pediatric obesity programs.