Acceptability of early childhood obesity prediction models to New Zealand families

The care of infants with rapid weight gain: Should we be doing more?

Rapid weight gain (RWG) during infancy is a known risk factor for later childhood obesity. It can be measured using a range of definitions across various time periods in the first 2 years of life. In recent years, some early childhood obesity prevention trials have included a focus on preventing RWG during infancy, with modest success. Overall, RWG during infancy remains common, yet little work has examined whether infants with this growth pattern should receive additional care when it is identified in health-care settings. In this viewpoint, we contend that RWG during infancy should be routinely screened for in health-care settings, and when identified, viewed as an opportunity for health-care professionals to instigate non-stigmatising discussions with families about RWG and general healthy practices for their infants. If families wish to engage, we suggest that six topics from early life obesity prevention studies (breastfeeding, formula feeding, complementary feeding, sleep, responsive parenting, and education around growth charts and monitoring) could form the foundations of conversations to help them establish and maintain healthy habits to support their infant's health and well-being and potentially lower the risk of later obesity. However, further work is needed to develop definitive guidelines in this area, and to address other gaps in the literature, such as the current lack of a standardised definition for RWG during infancy and a clear understanding of the time points over which it should be measured.

"We'd be really motivated to do something about it": a qualitative study of parent and clinician attitudes towards predicting childhood obesity in practice

ISSUE ADDRESSED

In Australia, one-in-four (24.9%) children live with overweight or obesity (OW/OB). Identifying infants at-risk of developing childhood OW/OB is a potential preventive pathway but its acceptability is yet to be investigated in Australia. This study aimed to (1) investigate acceptability of predicting childhood OW/OB with parents of infants (aged 0-2 years) and clinicians and (2) explore key language to address stigma and maximise the acceptability of predicting childhood OW/OB in practice.

METHODS

Cross-sectional and qualitative design, comprising individual semi-structured interviews. Participants were multidisciplinary paediatric clinicians (n=18) and parents (n=13) recruited across public hospitals and health services in Queensland, Australia. Data were analysed under the Framework Method using an inductive, thematic approach.

RESULTS

Five main themes were identified: (1) Optimism for prevention and childhood obesity prediction (2) Parent dedication to child's health (3) Adverse parent response to risk for childhood obesity (4) Language and phrasing for discussing weight and risk (5) Clinical delivery. Most participants were supportive of using a childhood OW/OB prediction tool in practice. Parents expressed dedication to their child's health that superseded potential feelings of judgment or blame. When discussing weight in a clinical setting, the use of sensitive (i.e. 'overweight', 'above average', 'growth' versus 'obesity') and positive, health-focused language was mostly supported.

CONCLUSIONS

Multidisciplinary paediatric clinicians and parents generally accept the concept of predicting childhood OW/OB in practice in Queensland, Australia. SO WHAT?: Clinicians, public health and health promotion professionals and policymakers can act now to implement sensitive communication strategies concerning weight and obesity risk.

A prediction model for childhood obesity in New Zealand

Several early childhood obesity prediction models have been developed, but none for New Zealand's diverse population. We aimed to develop and validate a model for predicting obesity in 4-5-year-old New Zealand children, using parental and infant data from the Growing Up in New Zealand (GUiNZ) cohort. Obesity was defined as body mass index (BMI) for age and sex ≥ 95th percentile. Data on GUiNZ children were used for derivation (n = 1731) and internal validation (n = 713). External validation was performed using data from the Prevention of Overweight in Infancy Study (POI, n = 383) and Pacific Islands Families Study (PIF, n = 135) cohorts. The final model included: birth weight, maternal smoking during pregnancy, maternal pre-pregnancy BMI, paternal BMI, and infant weight gain. Discrimination accuracy was adequate [AUROC = 0.74 (0.71-0.77)], remained so when validated internally [AUROC = 0.73 (0.68-0.78)] and externally on PIF [AUROC = 0.74 [0.66-0.82)] and POI [AUROC = 0.80 (0.71-0.90)]. Positive predictive values were variable but low across the risk threshold range (GUiNZ derivation 19-54%; GUiNZ validation 19-48%; and POI 8-24%), although more consistent in the PIF cohort (52-61%), all indicating high rates of false positives. Although this early childhood obesity prediction model could inform early obesity prevention, high rates of false positives might create unwarranted anxiety for families.

See How They Grow: Testing the feasibility of a mobile app to support parents' understanding of child growth charts

BACKGROUND

Mobile devices provide new opportunities for the prevention of overweight and obesity in children. We aimed to co-create and test an app that offered comprehensible feedback to parents on their child's growth and delivered a suite of age-specific information about nutrition and activity.

METHODS

A two-phased approach was used to co-create the digital growth tool-See How They Grow-and test its feasibility. Phase one used focus groups (parents and professionals such as paediatricians and midwives) and a national on-line survey to gather requirements and build the app. Phase two involved testing the app over 12-weeks, with parents or carers of children aged ≤ 2-years. All research activities were undertaken exclusively through the app, and participants were recruited using social media and hard copy materials given to patents at a child health visit.

FINDINGS

Four focus groups and 101 responses to the national survey informed the features and functions to include in the final app. Two hundred and twenty-five participants downloaded the app, resulting in 208 eligible participants. Non-Māori/Non-Pacific (78%) and Māori (14%) had the highest downloads. Fifty-four per cent of participants were parents of children under 6-months. These participants were more likely to regularly use the app than those with children older than 6-months (64% vs 36%, P = 0.011). Over half of the participants entered three measures (n = 101, 48%). Of those that completed the follow-up survey (n = 101, 48%), 72 reported that the app helped them better understand how to interpret growth charts.

CONCLUSION

The app was acceptable and with minor modifications, has the potential to be an effective tool to support parents understanding of growth trajectories for their children. A larger trial is needed to evaluate if the app can have a measurable impact on increasing knowledge and behaviour, and therefore on preventing childhood overweight and obesity.

Systematic review of randomised controlled trials to improve dietary intake for the prevention of obesity in infants aged 0-24 months

Improving dietary intake early in life is a common behavioural target in obesity prevention trials. We undertook a systematic review of randomised controlled trials aiming to improve dietary intake of complementary foods during infancy (0-24 months). PubMed, Cochrane Library, EMBASE, Medline, and PsycInfo were searched for trials focussed on obesity prevention conducted between January 2000 and August 2019 where dietary intake was an outcome. Two reviewers screened studies and extracted data from selected articles. Risk of bias was assessed using the Cochrane Collaboration Risk of Bias 2 tools. The protocol was registered on Open Science Framework (https://osf.io/6srg7/). Seventeen articles from 12 trials were selected for data extraction. Statistically significant group differences in outcomes were observed in 36 of 165 (21.8%) of dietary variables examined. Measurement and analysis of outcomes varied between studies. Overall risk of bias was rated as high, primarily due to missing outcome data. Improving dietary intake at this age appears challenging based on a relatively limited number of studies. Future research could consider dietary pattern analyses, which may provide more meaningful outcomes for this age group. Opportunities exist for further exploration of maternal-focussed interventions, responsive feeding interventions, and interventions delivered outside of homes.