Physicians' attitudes about obesity and their associations with competency and specialty: A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Physicians frequently report negative attitudes about obesity which is thought to affect patient care. However, little is known about how attitudes toward treating obese patients are formed. We conducted a cross-sectional survey of physicians in order to better characterize their attitudes and explore the relationships among attitudes, perceived competency in obesity care, including report of weight loss in patients, and other key physician, training, and practice characteristics.</p> <p>Methods</p> <p>We surveyed all 399 physicians from internal medicine, pediatrics, and psychiatry specialties at one institution regarding obesity care attitudes, competency, including physician report of percent of their patients who lose weight. We performed a factor analysis on the attitude items and used hierarchical regression analysis to explore the degree to which competency, reported weight loss, physician, training and practice characteristics explained the variance in each attitude factor.</p> <p>Results</p> <p>The overall response rate was 63%. More than 40% of physicians had a negative reaction towards obese patients, 56% felt qualified to treat obesity, and 46% felt successful in this realm. The factor analysis revealed 4 factors–<it>Physician Discomfort/Bias, Physician Success/Self Efficacy, Positive Outcome Expectancy</it>, and <it>Negative Outcome Expectancy</it>. Competency and reported percent of patients who lose weight were most strongly associated with the <it>Physician Success/Self Efficacy </it>attitude factor. Greater skill in patient assessment was associated with less <it>Physician Discomfort/Bias</it>. Training characteristics were associated with outcome expectancies with newer physicians reporting more positive treatment expectancies. Pediatric faculty was more positive and psychiatry faculty less negative in their treatment expectancies than internal medicine faculty.</p> <p>Conclusion</p> <p>Physician attitudes towards obesity are associated with competency, specialty, and years since postgraduate training. Further study is necessary to determine the direction of influence and to explore the impact of these attitudes on patient care.</p

Unpacking the behavioural components and delivery features of early childhood obesity prevention interventions in the TOPCHILD Collaboration: a systematic review and intervention coding protocol.

INTRODUCTION: Little is known about how early (eg, commencing antenatally or in the first 12 months after birth) obesity prevention interventions seek to change behaviour and which components are or are not effective. This study aims to (1) characterise early obesity prevention interventions in terms of target behaviours, delivery features and behaviour change techniques (BCTs), (2) explore similarities and differences in BCTs used to target behaviours and (3) explore effectiveness of intervention components in preventing childhood obesity. METHODS AND ANALYSIS: Annual comprehensive systematic searches will be performed in Epub Ahead of Print/MEDLINE, Embase, Cochrane (CENTRAL), CINAHL, PsycINFO, as well as clinical trial registries. Eligible randomised controlled trials of behavioural interventions to prevent childhood obesity commencing antenatally or in the first year after birth will be invited to join the Transforming Obesity in CHILDren Collaboration. Standard ontologies will be used to code target behaviours, delivery features and BCTs in both published and unpublished intervention materials provided by trialists. Narrative syntheses will be performed to summarise intervention components and compare applied BCTs by types of target behaviours. Exploratory analyses will be undertaken to assess effectiveness of intervention components. ETHICS AND DISSEMINATION: The study has been approved by The University of Sydney Human Research Ethics Committee (project no. 2020/273) and Flinders University Social and Behavioural Research Ethics Committee (project no. HREC CIA2133-1). The study's findings will be disseminated through peer-reviewed publications, conference presentations and targeted communication with key stakeholders. PROSPERO REGISTRATION NUMBER: CRD42020177408

Transforming Obesity Prevention for CHILDren (TOPCHILD) Collaboration: protocol for a systematic review with individual participant data meta-analysis of behavioural interventions for the prevention of early childhood obesity.

INTRODUCTION: Behavioural interventions in early life appear to show some effect in reducing childhood overweight and obesity. However, uncertainty remains regarding their overall effectiveness, and whether effectiveness differs among key subgroups. These evidence gaps have prompted an increase in very early childhood obesity prevention trials worldwide. Combining the individual participant data (IPD) from these trials will enhance statistical power to determine overall effectiveness and enable examination of individual and trial-level subgroups. We present a protocol for a systematic review with IPD meta-analysis to evaluate the effectiveness of obesity prevention interventions commencing antenatally or in the first year after birth, and to explore whether there are differential effects among key subgroups. METHODS AND ANALYSIS: Systematic searches of Medline, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycInfo and trial registries for all ongoing and completed randomised controlled trials evaluating behavioural interventions for the prevention of early childhood obesity have been completed up to March 2021 and will be updated annually to include additional trials. Eligible trialists will be asked to share their IPD; if unavailable, aggregate data will be used where possible. An IPD meta-analysis and a nested prospective meta-analysis will be performed using methodologies recommended by the Cochrane Collaboration. The primary outcome will be body mass index z-score at age 24±6 months using WHO Growth Standards, and effect differences will be explored among prespecified individual and trial-level subgroups. Secondary outcomes include other child weight-related measures, infant feeding, dietary intake, physical activity, sedentary behaviours, sleep, parenting measures and adverse events. ETHICS AND DISSEMINATION: Approved by The University of Sydney Human Research Ethics Committee (2020/273) and Flinders University Social and Behavioural Research Ethics Committee (HREC CIA2133-1). Results will be relevant to clinicians, child health services, researchers, policy-makers and families, and will be disseminated via publications, presentations and media releases. PROSPERO REGISTRATION NUMBER: CRD42020177408

Unpacking the behavioural components and delivery features of early childhood obesity prevention interventions in the TOPCHILD Collaboration: a systematic review and intervention coding protocol

Introduction Little is known about how early (e.g., commencing antenatally or in the first 12 months after birth) obesity prevention interventions seek to change behaviour and which components are or are not effective. This study aims to 1) characterise early obesity prevention interventions in terms of target behaviours, delivery features, and behaviour change techniques (BCTs), 2) explore similarities and differences in BCTs used to target behaviours, and 3) explore effectiveness of intervention components in preventing childhood obesity

Transforming Obesity Prevention for CHILDren (TOPCHILD) Collaboration: protocol for a systematic review with individual participant data meta-analysis of behavioural interventions for the prevention of early childhood obesity

Introduction Behavioural interventions in early life appear to show some effect in reducing childhood overweight and obesity. However, uncertainty remains regarding their overall effectiveness, and whether effectiveness differs among key subgroups. These evidence gaps have prompted an increase in very early childhood obesity prevention trials worldwide. Combining the individual participant data (IPD) from these trials will enhance statistical power to determine overall effectiveness and enable examination of intervention-covariate interactions. We present a protocol for a systematic review with IPD meta-analysis to evaluate the effectiveness of obesity prevention interventions commencing antenatally or in the first year after birth, and to explore whether there are differential effects among key subgroups

Correction: Predicting childhood obesity using electronic health records and publicly available data.

[This corrects the article DOI: 10.1371/journal.pone.0215571.]

Predicting childhood obesity using electronic health records and publicly available data.

BackgroundBecause of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. The ability to predict obesity before age five could be a useful tool, allowing prevention strategies to focus on high risk children. The few existing prediction models for obesity in childhood have primarily employed data from longitudinal cohort studies, relying on difficult to collect data that are not readily available to all practitioners. Instead, we utilized real-world unaugmented electronic health record (EHR) data from the first two years of life to predict obesity status at age five, an approach not yet taken in pediatric obesity research.Methods and findingsWe trained a variety of machine learning algorithms to perform both binary classification and regression. Following previous studies demonstrating different obesity determinants for boys and girls, we similarly developed separate models for both groups. In each of the separate models for boys and girls we found that weight for length z-score, BMI between 19 and 24 months, and the last BMI measure recorded before age two were the most important features for prediction. The best performing models were able to predict obesity with an Area Under the Receiver Operator Characteristic Curve (AUC) of 81.7% for girls and 76.1% for boys.ConclusionsWe were able to predict obesity at age five using EHR data with an AUC comparable to cohort-based studies, reducing the need for investment in additional data collection. Our results suggest that machine learning approaches for predicting future childhood obesity using EHR data could improve the ability of clinicians and researchers to drive future policy, intervention design, and the decision-making process in a clinical setting

Characteristics Associated With Adding Cereal Into the Bottle Among Immigrant Mother–Infant Dyads of Low Socioeconomic Status and Hispanic Ethnicity

ObjectiveDetermine maternal and infant characteristics associated with adding cereal into the bottle.DesignSecondary data analysis.ParticipantsStudy participants were immigrant, low-income, urban mother-infant dyads (n&nbsp;=&nbsp;216; 91% Hispanic, 19% US-born) enrolled in a randomized controlled trial entitled the Bellevue Project for Early Language, Literacy and Education Success.Main outcome measuresMaternal characteristics (age, marital status, ethnicity, primary language, country of origin, education, work status, income, depressive symptoms, and concern about infant's future weight) and infant characteristics (gender, first born, and difficult temperament).AnalysisFisher exact test, chi-square test, and simultaneous multiple logistic regression of significant (P&nbsp;&lt;&nbsp;.05) variables identified in unadjusted analyses.ResultsTwenty-seven percent of mothers added cereal into the bottle. After adjusting for confounding variables identified in bivariate analyses, mothers who were single (P&nbsp;=&nbsp;.02), had moderate to severe depressive symptoms (P&nbsp;=&nbsp;.01) and perceived their infant had a difficult temperament (P&nbsp;=&nbsp;.03) were more likely to add cereal into the bottle. Conversely, mothers who expressed concern about their infants becoming overweight were less likely to add cereal (P&nbsp;=&nbsp;.02).Conclusions and implicationsHealth care providers should screen for adding cereal in infant bottles. Further research is needed to investigate the impact of adding cereal into the bottle on weight trajectories over time. Causal associations also need to be identified to effectively prevent this practice

Maternal Antibiotic Use During Pregnancy and Childhood Obesity at Age 5 Years

Objective The benefits of antibiotic treatment during pregnancy are immediate, but there may be long-term risks to the developing child. Prior studies show an association between early life antibiotics and obesity, but few have examined this risk during pregnancy. Subjects To evaluate the association of maternal antibiotic exposure during pregnancy on childhood BMI-z at 5 years, we conducted a retrospective cohort analysis. Using electronic health record data from seven health systems in PCORnet, a national distributed clinical research network, we included children with same-day height and weight measures who could be linked to mothers with vital measurements during pregnancy. The primary independent variable was maternal outpatient antibiotic prescriptions during pregnancy (any versus none). We examined dose response (number of antibiotic episodes), spectrum and class of antibiotics, and antibiotic episodes by trimester. The primary outcome was child age- and sex-specific BMI-z at age 5 years. Results The final sample was 53,320 mother–child pairs. During pregnancy, 29.9% of mothers received antibiotics. In adjusted models, maternal outpatient antibiotic prescriptions during pregnancy were not associated with child BMI-z at age 5 years (β = 0.00, 95% CI −0.03, 0.02). When evaluating timing during pregnancy, dose-response, spectrum and class of antibiotics, there were no associations of maternal antibiotics with child BMI-z at age 5 years. Conclusion In this large observational cohort, provision of antibiotics during pregnancy was not associated with childhood BMI-z at 5 years