Effectiveness of a paediatric weight management intervention for rural youth (iAmHealthy): Primary outcomes of a cluster randomised control trial.

BACKGROUND: Youth in rural areas are disproportionally affected by obesity. Given the unique barriers rural populations face, tailoring and increasing access to obesity interventions is necessary. OBJECTIVE: This paper evaluates the effectiveness of iAmHealthy, a family-based paediatric obesity intervention delivered to rural children, compared to a Newsletter Control. METHODS: Participating schools (n = 18) were randomly assigned to iAmHealthy or Newsletter Control. iAmHealthy consists of individual health coaching and group sessions delivered via televideo to a participant's home. The child and parent's body mass index (BMI), child physical activity and child dietary intake were assessed at baseline, post-treatment (8 months) and follow-up (20 months). Multilevel modeling estimated the effect of treatment at both time points. RESULTS: Parent and child dyads were recruited (n = 148) and randomised to iAmHealthy (n = 64) or the Control group (n = 84). The Control group had significant increases in child BMIz from baseline to follow-up. iAmHealthy youth had no significant changes in BMIz from baseline to post or follow-up. Child dietary intake, physical activity and parent BMI results are also discussed. CONCLUSIONS: This trial extends previous paediatric obesity work by simultaneously increasing convenience and dose of treatment. Results suggest iAmHealthy resulted in a change in BMIz trajectories and long-term health behaviour for youth.

Family Rules and Routines During the Early Phases of Pediatric Cancer Treatment: Associations With Child Emotional and Behavioral Health.

OBJECTIVE: Consistent family rules and routines promote positive adaptation to stress and may be protective to child emotional and behavioral functioning. Few studies have quantified family engagement in these behaviors during pediatric cancer treatment or examined associations with child emotional and behavioral health. METHODS: In this cross-sectional observational study, 86 primary caregivers of youth ages 2-14 years (M = 7.9) with an initial diagnosis of cancer within 16 weeks reported on their frequency of engagement in family rules and routines (e.g., sleep, schoolwork, and meal routines) before their child's cancer diagnosis and their current frequency of engagement in the same routines. Caregivers also reported demographics, psychosocial distress, and child emotional and behavioral health outcomes. Analyses examined demographic and psychosocial factors associated with engagement in rules and routines during cancer treatment, and associations with child emotional and behavioral health. RESULTS: Families reported a lower frequency of engagement in rules and routines during cancer treatment, compared to before treatment (mean difference 0.8 SDs [95% confidence interval 0.7-1.1 SDs]). Caregiver factors associated with lower engagement in rules and routines during treatment included being married, having lower educational attainment, and higher levels of psychosocial distress. Families who engaged in higher levels of rules and routines during treatment reported fewer child externalizing and behavioral challenges. There was limited evidence of association between family rules and routines and child internalizing outcomes. CONCLUSIONS: Results found that engaging in family rules and routines during cancer treatment was associated with fewer child behavioral challenges during treatment. Future directions include longitudinal examinations of family rules, routines, and child emotional/behavioral outcomes to examine directional impact over time.

Prevalence of Parent Mental Health Problems in an Interdisciplinary Feeding Clinic: Short Communication.

Parents of children with pediatric feeding disorder (PFD) often experience high stress and may be at advanced risk for mental health conditions. We conducted a retrospective chart review of 413 parents who completed intake surveys at an interdisciplinary feeding clinic to determine the prevalence and types of mental health conditions among parents; 41.8% of parents reported a mental health diagnosis among the mother and/or father. Of the parents with mental health conditions, the most prevalent conditions reported were anxiety (71.1% for mothers, 50% for fathers) and mood disorders (62.7% for mothers, 40.9% for fathers). For mothers, 21.1% indicated their mental health disorder had a postpartum onset. Parents of children with birth complications were more likely to have a mental health condition (50.9%) than parents of children without a birth complication (38.7%), and parents reporting mental health conditions had children with significantly more co-occurring medical conditions. Since parent stress and mental health can influence parent-child interactions during mealtime, this study suggests the importance of addressing both parent mental health factors and child factors when treating children for PFD. Future studies are needed to develop novel interventions that support the specific mental health needs of parents of children with PFD.

Recruitment and reach in a school-based pediatric obesity intervention trial in rural areas.

Introduction: The purpose of this study is to evaluate two recruitment strategies on schools and participant participation rates and representativeness (reach) within a pediatric obesity treatment trial tailored for families who live in rural areas. Methods: Recruitment of schools was evaluated based on their progress toward enrolling participants. Recruitment and reach of participants were evaluated using (1) participation rates and (2) representativeness of demographics and weight status of participants compared to eligible participants (who did not consent and enroll) and all students (regardless of eligibility). School recruitment, as well as participant recruitment and reach, were evaluated across recruitment methods comparing opt-in (i.e., caregivers agreed to allow their child to be screened for eligibility) vs. screen-first (i.e., all children screened for eligibility). Results: Of the 395 schools contacted, 34 schools (8.6%) expressed initial interest; of these, 27 (79%) proceeded to recruit participants, and 18 (53%) ultimately participated in the program. Of schools who initiated recruitment, 75% of schools using the opt-in method and 60% of schools using the screen-first method continued participation and were able to recruit a sufficient number of participants. The average participation rate (number of enrolled individuals divided by those who were eligible) from all 18 schools was 21.6%. This percentage was higher in schools using the screen-first method (average of 29.7%) compared to schools using the opt-in method (13.5%). Study participants were representative of the student population based on sex (female), race (White), and eligibility for free and reduced-price lunch. Study participants had higher body mass index (BMI) metrics (BMI, BMIz, and BMI%) than eligible non-participants. Conclusions: Schools using the opt-in recruitment were more likely to enroll at least 5 families and administer the intervention. However, the participation rate was higher in screen-first schools. The overall study sample was representative of the school demographics.

Rationale and design of integrating a parents first obesity intervention with a pediatric weight management intervention for rural families - Evaluating the ripple effect.

Rural families are disproportionately affected by obesity. Obesity often runs in families and is impacted by hereditary components, the shared home environment, and parent modeling/child observational learning. Moreover, parent changes in weight predict child changes in weight. Thus, targeting the family unit has the potential to enhance outcomes for adults and children simultaneously. Additionally, engaging rural nurses in medical clinics and schools may be important in determining whether rural telehealth programs are successfully implemented and sustained. This paper describes the rationale and design of a randomized control trial (RCT) evaluating the effectiveness of an integrated adult- and child-focused obesity treatment tailored for rural participants. Outcomes of this study include participant weight loss from baseline to 9-months, device-measured physical activity, and dietary intake. This project will additionally compare reach between clinic and school settings and evaluate the impact of nurse engagement. This study will include 240 participants from eight rural communities who will be randomized to either a Parent +Family-based group or a Newsletter +Family-based group. Parents in the Parent +Family-based group will receive a 3-month adult obesity treatment designed for adult behavior change as a first step. Then, parents and children together will enter the family-based program (iAmHealthy), allowing for potential enhancement of a theorized ripple effect. Parents in the Newsletter +Family-based group will receive 3 monthly newsletters and then participate in the 6-month family-based intervention designed for child behavior change. This study is the first RCT to examine the effectiveness of an integrated adult- and child-focused obesity treatment program. Registered with ClinicalTrials.gov NCT ID NCT05612971.

The impact of COVID-19 on rural treatment-seeking families with children with overweight or obesity.

To examine the early impact of the COVID-19 pandemic on rural parental stress and family behaviors, parents who participated in a 2nd-4th grade pediatric obesity intervention completed a survey in May 2020. Parents (N=77) experienced 7.8±2.7 events on the COVID-19 Exposure and Family Impact Scales (CEFIS) with an average impact of 2.5±0.5, with many parents reporting moderate stress (73%). Parental stress was predictive of personal well-being getting 'worse' while loss of income events were predictive of family routines getting 'better.' Professionals working with rural families may want to assess for these factors when promoting positive changes in family health behaviors.

Validation of remote height and weight assessment in a rural randomized clinical trial.

BACKGROUND: The purpose of this study is to describe and assess a remote height and weight protocol that was developed for an ongoing trial conducted during the SARS COV-2 pandemic. METHODS: Thirty-eight rural families (children 8.3 ± 0.7 years; 68% female; and caregivers 38.2 ± 6.1 years) were provided detailed instructions on how to measure height and weight. Families obtained measures via remote data collection (caregiver weight, child height and weight) and also by trained staff. Differences between data collection methods were examined. RESULTS: Per absolute mean difference analyses, slightly larger differences were found for child weight (0.21 ± 0.21 kg), child height (1.53 ± 1.29 cm), and caregiver weight (0.48 ± 0.42 kg) between school and home measurements. Both analyses indicate differences had only minor impact on child BMI percentile (- 0.12, 0.68) and parent BMI (0.05, 0.13). Intraclass coefficients ranged from 0.98 to 1.00 indicating that almost all of the variance was due to between person differences and not measurement differences within a person. CONCLUSION: Results suggest that remote height and weight collection is feasible for caregivers and children and that there are minimal differences in the various measurement methods studied here when assessing group differences. These differences did not have clinically meaningful impacts on BMI. This is promising for the use of remote height and weight measurement in clinical trials, especially for hard-to reach-populations. TRIAL REGISTRATION: Clinical. Registered in clinicaltrials.gov ( NCT03304249 ) on 06/10/2017.

Utilization of machine learning for identifying symptom severity military-related PTSD subtypes and their biological correlates.

We sought to find clinical subtypes of posttraumatic stress disorder (PTSD) in veterans 6-10 years post-trauma exposure based on current symptom assessments and to examine whether blood biomarkers could differentiate them. Samples were males deployed to Iraq and Afghanistan studied by the PTSD Systems Biology Consortium: a discovery sample of 74 PTSD cases and 71 healthy controls (HC), and a validation sample of 26 PTSD cases and 36 HC. A machine learning method, random forests (RF), in conjunction with a clustering method, partitioning around medoids, were used to identify subtypes derived from 16 self-report and clinician assessment scales, including the clinician-administered PTSD scale for DSM-IV (CAPS). Two subtypes were identified, designated S1 and S2, differing on mean current CAPS total scores: S2 = 75.6 (sd 14.6) and S1 = 54.3 (sd 6.6). S2 had greater symptom severity scores than both S1 and HC on all scale items. The mean first principal component score derived from clinical summary scales was three times higher in S2 than in S1. Distinct RFs were grown to classify S1 and S2 vs. HCs and vs. each other on multi-omic blood markers feature classes of current medical comorbidities, neurocognitive functioning, demographics, pre-military trauma, and psychiatric history. Among these classes, in each RF intergroup comparison of S1, S2, and HC, multi-omic biomarkers yielded the highest AUC-ROCs (0.819-0.922); other classes added little to further discrimination of the subtypes. Among the top five biomarkers in each of these RFs were methylation, micro RNA, and lactate markers, suggesting their biological role in symptom severity.

iKanEat: protocol for a randomized controlled trial of megestrol as a component of a pediatric tube weaning protocol.

BACKGROUND: Although tube feeding routinely saves the lives of children who do not eat by mouth, chronic tube feeding can be a burden to patients, caregivers, and families. Very few randomized trials exist regarding the best methods for weaning children from their feeding tubes. METHODS: The current paper describes a randomized controlled trial of an empirically supported outpatient treatment protocol for moving children from tube to oral eating called iKanEat. Specifically, we describe the methods of randomized double-blind, placebo-controlled trial which includes a 4-week course of megestrol, the only medication used in the iKanEat protocol, to determine whether the addition of megestrol results in improved child outcomes. The primary and secondary aims are to assess the safety and efficacy of megestrol as part of the iKanEat protocol. The third aim is to provide critical information about the impact of the transition from tube to oral feeding on parent stress and parent and child quality of life. DISCUSSION: This trial will provide data regarding whether megestrol is a safe and effective component of the iKanEat tube weaning protocol, as well as important data on how the tube weaning process impacts parent stress and parent and child quality of life. TRIAL REGISTRATION: ClinicalTrials.gov NCT#03815019 . Registered on January 17, 2019.

Investigating associations between physical activity-related neighborhood built environment features and child weight status to inform local practice.

Despite evidence of the importance of neighborhood built environment features in relation to physical activity and obesity, research has been limited in informing localized practice due to small sample sizes and limited geographic coverage. This demonstration study integrated data from a local pediatric health system with nationally available neighborhood built environment data to inform local decision making around neighborhood environments and childhood obesity. Height/weight from clinic visits and home neighborhood measures from the U.S. Environmental Protections Agency and WalkScore were obtained for 15,989 6-17 year olds. Multilevel models accounted for the nested data structure and were adjusted for neighborhood income and child sociodemographics. In 9-17 year olds, greater street connectivity and walkability were associated with a 0.01-0.04 lower BMIz (Ps = .009-.017) and greater residential density, street connectivity, and walkability were associated 5-7% lower odds of being overweight/obese (Ps = .004-.044) per standard deviation increase in environment variable. 45.9% of children in the lowest walkability tertile were overweight or obese, whereas 43.1% of children in the highest walkability tertile were overweight or obese. Maps revealed areas with low walkability and a high income-adjusted percent of children overweight/obese. In the Kansas City area, data showed that fewer children were overweight/obese in more walkable neighborhoods. Integrating electronic health records with neighborhood environment data is a replicable process that can inform local practice by highlighting the importance of neighborhood environment features locally and pointing to areas most in need of interventions.

Epigenetic biotypes of post-traumatic stress disorder in war-zone exposed veteran and active duty males.

Post-traumatic stress disorder (PTSD) is a heterogeneous condition evidenced by the absence of objective physiological measurements applicable to all who meet the criteria for the disorder as well as divergent responses to treatments. This study capitalized on biological diversity observed within the PTSD group observed following epigenome-wide analysis of a well-characterized Discovery cohort (N = 166) consisting of 83 male combat exposed veterans with PTSD, and 83 combat veterans without PTSD in order to identify patterns that might distinguish subtypes. Computational analysis of DNA methylation (DNAm) profiles identified two PTSD biotypes within the PTSD+ group, G1 and G2, associated with 34 clinical features that are associated with PTSD and PTSD comorbidities. The G2 biotype was associated with an increased PTSD risk and had higher polygenic risk scores and a greater methylation compared to the G1 biotype and healthy controls. The findings were validated at a 3-year follow-up (N = 59) of the same individuals as well as in two independent, veteran cohorts (N = 54 and N = 38), and an active duty cohort (N = 133). In some cases, for example Dopamine-PKA-CREB and GABA-PKC-CREB signaling pathways, the biotypes were oppositely dysregulated, suggesting that the biotypes were not simply a function of a dimensional relationship with symptom severity, but may represent distinct biological risk profiles underpinning PTSD. The identification of two novel distinct epigenetic biotypes for PTSD may have future utility in understanding biological and clinical heterogeneity in PTSD and potential applications in risk assessment for active duty military personnel under non-clinician-administered settings, and improvement of PTSD diagnostic markers.

Pre-deployment risk factors for PTSD in active-duty personnel deployed to Afghanistan: a machine-learning approach for analyzing multivariate predictors.

Active-duty Army personnel can be exposed to traumatic warzone events and are at increased risk for developing post-traumatic stress disorder (PTSD) compared with the general population. PTSD is associated with high individual and societal costs, but identification of predictive markers to determine deployment readiness and risk mitigation strategies is not well understood. This prospective longitudinal naturalistic cohort study-the Fort Campbell Cohort study-examined the value of using a large multidimensional dataset collected from soldiers prior to deployment to Afghanistan for predicting post-deployment PTSD status. The dataset consisted of polygenic, epigenetic, metabolomic, endocrine, inflammatory and routine clinical lab markers, computerized neurocognitive testing, and symptom self-reports. The analysis was computed on active-duty Army personnel (N = 473) of the 101st Airborne at Fort Campbell, Kentucky. Machine-learning models predicted provisional PTSD diagnosis 90-180 days post deployment (random forest: AUC = 0.78, 95% CI = 0.67-0.89, sensitivity = 0.78, specificity = 0.71; SVM: AUC = 0.88, 95% CI = 0.78-0.98, sensitivity = 0.89, specificity = 0.79) and longitudinal PTSD symptom trajectories identified with latent growth mixture modeling (random forest: AUC = 0.85, 95% CI = 0.75-0.96, sensitivity = 0.88, specificity = 0.69; SVM: AUC = 0.87, 95% CI = 0.79-0.96, sensitivity = 0.80, specificity = 0.85). Among the highest-ranked predictive features were pre-deployment sleep quality, anxiety, depression, sustained attention, and cognitive flexibility. Blood-based biomarkers including metabolites, epigenomic, immune, inflammatory, and liver function markers complemented the most important predictors. The clinical prediction of post-deployment symptom trajectories and provisional PTSD diagnosis based on pre-deployment data achieved high discriminatory power. The predictive models may be used to determine deployment readiness and to determine novel pre-deployment interventions to mitigate the risk for deployment-related PTSD.

Divergence in aerobic capacity impacts bile acid metabolism in young women.

Liver adaptations may be critical for regular exercise and high aerobic capacity to protect against metabolic disease, but mechanisms remain unknown. Bile acids (BAs) synthesized in the liver are bioactive and can putatively modify energy metabolism. Regular exercise influences BA metabolism in rodents, but effects in humans are unknown. This study tested whether female subjects screened for high aerobic capacity (Hi-Fit, n = 19) [peak oxygen consumption (V̇o2peak) ≥45 mL·kg-1·min-1] have increased hepatic BA synthesis and different circulating BA composition compared with those matched for age and body mass with low aerobic capacity (Lo-Fit, n = 19) (V̇o2peak ≤35 mL·kg-1·min-1). Diet patterns, activity level, stool, and blood were collected at baseline before participants received a 1-wk standardized, eucaloric diet. After the 1-wk standardized diet, stool and blood were again collected and an oral glucose tolerance test (OGTT) was performed to assess insulin sensitivity and postprandial BA response. Contrary to our hypothesis, serum 7α-hydroxy-4-cholesten-3-one (C4), a surrogate of BA synthesis, was not different between groups, whereas Hi-Fit women had lower fecal BA concentrations compared with Lo-Fit women. However, Lo-Fit women had a higher and more sustained rise in circulating conjugated BAs during the OGTT. Hi-Fit women showed a significant post-OGTT elevation of the secondary BA, lithocholic acid (a potent TGR5 agonist), in contrast to Lo-Fit women where no response was observed. A 1-wk control diet eliminated most differences in circulating BA species between groups. Overall, the results emphasize the importance of using a standardized diet when evaluating BAs and indicate that regular exercise and aerobic capacity modulate BA metabolism under postprandial conditions.NEW & NOTEWORTHY Women with contrasting exercise and aerobic capacity levels show clear differences in bile acid (BA) metabolism. Women with low aerobic capacity (Lo-Fit) have increased circulating conjugated BAs post oral glucose tolerance test (OGTT), whereas women with high aerobic capacity (Hi-Fit) display a transient increase. Hi-Fit women show an increase in the secondary BA, lithocholic acid, during the OGTT not seen in Lo-Fit women. Differences in circulating BA species between Hi- and Lo-Fit women possibly contribute to differences in insulin sensitivity and energy regulation via different signaling mechanisms.

Automated High-Frequency Observations of Physical Activity Using Computer Vision.

PURPOSE: To test the validity of the Ecological Video Identification of Physical Activity (EVIP) computer vision algorithms for automated video-based ecological assessment of physical activity in settings such as parks and schoolyards. METHODS: Twenty-seven hours of video were collected from stationary overhead video cameras across 22 visits in nine sites capturing organized activities. Each person in the setting wore an accelerometer, and each second was classified as moderate-to-vigorous physical activity or sedentary/light activity. Data with 57,987 s were used to train and test computer vision algorithms for estimating the total number of people in the video and number of people active (in moderate-to-vigorous physical activity) each second. In the testing data set (38,658 s), video-based System for Observing Play and Recreation in Communities (SOPARC) observations were conducted every 5 min (130 observations). Concordance correlation coefficients (CCC) and mean absolute errors (MAE) assessed agreement between (1) EVIP and ground truth (people counts+accelerometry) and (2) SOPARC observation and ground truth. Site and scene-level correlates of error were investigated. RESULTS: Agreement between EVIP and ground truth was high for number of people in the scene (CCC = 0.88; MAE = 2.70) and moderate for number of people active (CCC = 0.55; MAE = 2.57). The EVIP error was uncorrelated with camera placement, presence of obstructions or shadows, and setting type. For both number in scene and number active, EVIP outperformed SOPARC observations in estimating ground truth values (CCC were larger by 0.11-0.12 and MAE smaller by 41%-48%). CONCLUSIONS: Computer vision algorithms are promising for automated assessment of setting-based physical activity. Such tools would require less manpower than human observation, produce more and potentially more accurate data, and allow for ongoing monitoring and feedback to inform interventions.

Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD.

Metabolomic analysis of male combat veterans with post traumatic stress disorder.

Posttraumatic stress disorder (PTSD) is associated with impaired major domains of psychology and behavior. Individuals with PTSD also have increased co-morbidity with several serious medical conditions, including autoimmune diseases, cardiovascular disease, and diabetes, raising the possibility that systemic pathology associated with PTSD might be identified by metabolomic analysis of blood. We sought to identify metabolites that are altered in male combat veterans with PTSD. In this case-control study, we compared metabolomic profiles from age-matched male combat trauma-exposed veterans from the Iraq and Afghanistan conflicts with PTSD (n = 52) and without PTSD (n = 51) ('Discovery group'). An additional group of 31 PTSD-positive and 31 PTSD-negative male combat-exposed veterans was used for validation of these findings ('Test group'). Plasma metabolite profiles were measured in all subjects using ultrahigh performance liquid chromatography/tandem mass spectrometry and gas chromatography/mass spectrometry. We identified key differences between PTSD subjects and controls in pathways related to glycolysis and fatty acid uptake and metabolism in the initial 'Discovery group', consistent with mitochondrial alterations or dysfunction, which were also confirmed in the 'Test group'. Other pathways related to urea cycle and amino acid metabolism were different between PTSD subjects and controls in the 'Discovery' but not in the smaller 'Test' group. These metabolic differences were not explained by comorbid major depression, body mass index, blood glucose, hemoglobin A1c, smoking, or use of analgesics, antidepressants, statins, or anti-inflammatories. These data show replicable, wide-ranging changes in the metabolic profile of combat-exposed males with PTSD, with a suggestion of mitochondrial alterations or dysfunction, that may contribute to the behavioral and somatic phenotypes associated with this disease.

iAmHealthy: Rationale, design and application of a family-based mHealth pediatric obesity intervention for rural children.

Children in rural areas are disproportionately affected by pediatric obesity. Poor access to healthcare providers, lack of nutrition education, lower socioeconomic status, and fewer opportunities to be physically active are all unique barriers that contribute to this growing health concern. There are very few pediatric obesity interventions that have been developed that target this unique population. iAmHealthy is a family-based behavioral, nutrition and physical activity intervention developed with input from rural children and families that capitalizes on the innovative use of mobile health applications (mHealth). iAmHealthy is a 25-contact hour multicomponent intervention delivered over an 8-month period targeting 2nd-4th grade school children and their families. This paper describes the rationale, design, participant/school enrollment, and planned implementation of a randomized controlled trial of the iAmHealthy intervention in comparison to a monthly newsletter delivered through rural elementary schools. Child Body Mass Index z-score (BMIz) is the primary outcome, along with child 24-hour dietary recall, and child accelerometer-determined physical activity and sedentary behavior as secondary outcomes. The study will include 18 schools (with 8 children each) resulting in a final planned sample size of 144 children. This project also has a strong focus on dissemination and implementation science, and thus includes many measures related to the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance). Data collection is completed at baseline, end of intervention (8 months), and follow-up (20 months). This study is the first randomized controlled trial to deliver a rurally tailored, empirically supported, family-based behavioral intervention for pediatric obesity solely over mHealth. Registered with ClinicalTrials.gov NCT ID 03304249.

Adherence With Multiple National Healthy Lifestyle Recommendations in a Large Pediatric Center Electronic Health Record and Reduced Risk of Obesity.

OBJECTIVE: To evaluate the utility of a routine assessment of lifestyle behaviors incorporated into the electronic health record (EHR) to quantify lifestyle practices and obesity risk at a pediatric primary care center. PATIENTS AND METHODS: Participants included 24,255 patients aged 2 to 18 years whose parent/caregiver completed a self-report lifestyle assessment during a well-child examination (January 1, 2013, through June 30, 2016). Cross-sectional analyses of age, race/ethnicity, body mass index, and lifestyle assessment responses were performed. Outcome measures included prevalence of patients meeting consensus recommendations for physical activity; screen time; and dairy, water, and fruit/vegetable consumption and the odds of obesity based on reported lifestyle behaviors. RESULTS: Prevalence of meeting recommendations for lifestyle behaviors was highest for physical activity (84%), followed by screen time (61%) and consumption of water (51%), dairy (27%), and fruits/vegetables (10%). Insufficient physical activity was the strongest predictor of obesity (odds ratio [OR], 1.65; 95% CI, 1.51-1.79), followed by excess screen time (OR, 1.36; 95% CI, 1.27-1.45). Disparities existed across ages, races/ethnicities, and sexes for multiple lifestyle habits. Youth who met 0 or 1 lifestyle recommendation were 1.45 to 1.71 times more likely to have obesity than those meeting all 5 recommendations. CONCLUSION: Healthy behaviors vary in prevalence, as does their association with obesity. This variation is partially explained by age, sex, and race/ethnicity. Meeting national recommendations for specific behaviors is negatively associated with obesity in a dose-dependent manner. These findings support the assessment of lifestyle behaviors in primary care as one component of multilevel initiatives to prevent childhood obesity.

Clinical-Community Collaboration: A Strategy to Improve Retention and Outcomes in Low-Income Minority Youth in Family-Based Obesity Treatment.

BACKGROUND: Clinical-community collaboration is a promising strategy for pediatric obesity treatment, but current research is limited. This study examined the effect of a family-based treatment program embedded in a primary care clinic on retention and changes in child weight status at 1 year. METHODS: Children (2-16 years, BMI ≥85th percentile, 87.0% Hispanic) and their parents were recruited from a single pediatric clinic for Healthy Hawks Primary Plus (HHP+). Children were referred by physicians and enrolled by a bilingual clinic-based recruitment coordinator. Participants received 12 weekly 2-hour sessions focused on lifestyle modification and health behavior change and then received bimonthly follow-up visits with their clinic-based physician through 1-year follow-up. Child body mass index (BMI) percentage of the 95th percentile (%BMIp95) was measured as the primary outcome at baseline, postintervention, and 1-year follow-up. Random effect multilevel models assessed changes in child weight status over time accounting for clustering by family. To further evaluate the impact, HHP+ retention and changes in child weight status were compared to a standard 12-week treatment program only. RESULTS: HHP+ participants had significantly better retention at 1 year (73.9%, p ≤ 0.001) compared to the standard treatment program (38.3%). In HHP+, physician visit attendance was significantly correlated with retention at 1 year (r = 0.69, p ≤ 0.001), and HHP+ completers had significant reductions in %BMIp95 between baseline and 1-year follow-up (p = 0.03). CONCLUSION: Clinical-community partnerships might be a promising strategy to improve retention and reduce child weight status in populations currently underrepresented in obesity treatment.

Automated Ecological Assessment of Physical Activity: Advancing Direct Observation.

Technological advances provide opportunities for automating direct observations of physical activity, which allow for continuous monitoring and feedback. This pilot study evaluated the initial validity of computer vision algorithms for ecological assessment of physical activity. The sample comprised 6630 seconds per camera (three cameras in total) of video capturing up to nine participants engaged in sitting, standing, walking, and jogging in an open outdoor space while wearing accelerometers. Computer vision algorithms were developed to assess the number and proportion of people in sedentary, light, moderate, and vigorous activity, and group-based metabolic equivalents of tasks (MET)-minutes. Means and standard deviations (SD) of bias/difference values, and intraclass correlation coefficients (ICC) assessed the criterion validity compared to accelerometry separately for each camera. The number and proportion of participants sedentary and in moderate-to-vigorous physical activity (MVPA) had small biases (within 20% of the criterion mean) and the ICCs were excellent (0.82-0.98). Total MET-minutes were slightly underestimated by 9.3-17.1% and the ICCs were good (0.68-0.79). The standard deviations of the bias estimates were moderate-to-large relative to the means. The computer vision algorithms appeared to have acceptable sample-level validity (i.e., across a sample of time intervals) and are promising for automated ecological assessment of activity in open outdoor settings, but further development and testing is needed before such tools can be used in a diverse range of settings.