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Objective: Screen use at mealtimes is associated with poor dietary and psychosocial outcomes in children and is disproportionately prevalent among families of low socio-economic position (SEP). This study aimed to explore experiences of reducing mealtime screen use in mothers of low SEP with young children. Design: Motivational interviews, conducted via Zoom or telephone, addressed barriers and facilitators to reducing mealtime screen use. Following motivational interviews, participants co-designed mealtime screen use reduction strategies and trialled these for 3–4 weeks. Follow-up semi-structured interviews then explored maternal experiences of implementing strategies, including successes and difficulties. Transcripts were analysed thematically. Setting: Australia. Participants: Fourteen mothers who had no university education and a child between six months and six years old. Results: A range of strategies aimed to reduce mealtime screen use were co-designed. The most widely used strategies included changing mealtime location and parental modelling of expected behaviours. Experiences were influenced by mothers' levels of parenting self-efficacy and mealtime consistency, included changes to mealtime foods and an increased value of mealtimes. Experiences were reportedly easier, more beneficial and offered more opportunities for family communication, than anticipated. Change required considerable effort. However, effort decreased with consistency. Conclusions: The diverse strategies co-designed by mothers highlight the importance of understanding why families engage in mealtime screen use and providing tailored advice for reduction. Although promising themes were identified, in this motivated sample, changing established mealtime screen use habits still required substantial effort. Embedding screen-free mealtime messaging into nutrition promotion from the inception of eating will be important. [ABSTRACT FROM AUTHOR]

Objective: To describe environmentally sustainable (ES) and healthy food provision practices in childcare services in Victoria, Australia. Design: Cross-sectional study. Setting: Childcare services providing food onsite. Participants: Staff completed an online survey that explored ES food provision practices including purchasing seasonal/local food, food waste awareness/management, and food cost/child/d. A purposively sampled subgroup conducted weighed audits to determine compliance with guidelines and total waste, serving waste (prepared, not served) and plate waste. Results: Survey results found 8 % of services (n 129) had previously conducted food waste audits. Service audits (n 12) found 27 % total food waste (range: 9 % - 64 %). Statistically significant differences in plate waste were found between services who had previously conducted food waste audits (7 %) and those who had not (17 %) (P = 0·04). The most common ES practice was 'providing seasonal food'; the least common was 'maintaining a compost system' and 'less packaged foods'. Most services (95 %) purchased foods from supermarkets with 23 % purchasing from farmers' markets. This was statistically lower for regional/rural services (8 %), compared to metropolitan services (27 %) (P = 0·04). Twenty-seven per cent of services spent AUD2·50 or less per child per day on food. Only one audited service provided a menu compliant with childcare food provision guidelines. Conclusions: Childcare settings procure and provide large volumes of food; however, food waste awareness appears limited, and environmentally sustainable food procurement practices may be less affordable and difficult to achieve. Understanding the impact of food waste awareness on food waste practices and food costs across time merits further research. [ABSTRACT FROM AUTHOR]

This study describes engagement in and stability of physical activity and sedentary behaviours in early life, and assesses associations with sex, maternal education and developmental stage. Maternal-report data at child age 4, 9 and 20 months were collected from 542 families in the Melbourne Infant Feeding Activity and Nutrition Trial Program. Parents estimated average time per day their child spent in active pursuits or pursuits that restricted movement. With increasing age, children generally spent more time in active pursuits and watching television, and less time in situations that restrict movement. Associations were found with age of developmental milestone attainment but not sex or maternal education. Stability over time was strongest for television viewing (ß?=?0.34-0.38) and time spent outdoors (ß?=?0.27-0.33). Contrary to guidelines, television viewing increased and showed stability, suggesting a need to target this behaviour very early in life to achieve optimal longer term outcomes.

Objective: Behavioural patterns are important in understanding the synergistic effect of multiple health behaviours on childhood adiposity. Most previous evidence assessing associations between patterns and adiposity were cross-sectional and investigated two or three behaviour domains within patterns. This study aimed to identify behavioural patterns comprising four behaviour domains and investigate associations with adiposity risk in children. Design: Parent-report and accelerometry data were used to capture daily dietary, physical activity, sedentary behaviour and sleep data. Variables were standardised and included in the latent profile analysis to derive behavioural patterns. Trained researchers measured children's height, weight and waist circumference using standardised protocols. Associations of patterns and adiposity measures were tested using multiple linear regression. Setting: Melbourne, Australia. Participants: A total of 337 children followed up at 6–8 years (T2) and 9–11 years (T3). Results: Three patterns derived at 6–8 years were broadly identified to be healthy, unhealthy and mixed patterns. Patterns at 9–11 years were dissimilar except for the unhealthy pattern. Individual behaviours characterising the patterns varied over time. No significant cross-sectional or prospective associations were observed with adiposity at both time points; however, children displaying the unhealthy pattern had higher adiposity measures than other patterns. Conclusion: Three non-identical patterns were identified at 6–8 and 9–11 years. The individual behaviours that characterised patterns (dominant behaviours) at both ages are possible drivers of the patterns obtained and could explain the lack of associations with adiposity. Identifying individual behaviour pattern drivers and strategic intervention are key to maintain and prevent the decline of healthy patterns. [ABSTRACT FROM AUTHOR]

Breakfast is considered a healthy dietary habit which can track over time from childhood to adulthood. The breakfast meal has the potential to improve daily dietary quality, particularly if it includes a range of food groups and adequate nutrient intakes. However, research on breakfast consumption trends among young Australian children aged up to 5 years is currently limited. This study assessed children's usual breakfast food group and nutrient intakes at ages 1.5 (n = 369), 3.5 (n = 242), and 5.0 (n =240) years using three 24-hour dietary recalls from the Melbourne InFANT program. Tracking of food groups at breakfast across the three ages was assessed by Pearson correlation of energy-adjusted food intake residuals. The main food groups consumed at breakfast were grains, milk/alternatives and discretionary items, with vegetables rarely consumed at any age. Our study found that while breakfast contributed about 20% of total daily energy, this provided 20%-29.1% of total daily intake across all ages for carbohydrates, total sugars, calcium and potassium. For the contribution to daily recommendations, breakfast contributed more than about a third of daily recommended intakes for some micronutrients (e.g., iron, calcium and zinc), and a large proportion (over 40%) of sodium intake. Children consumed 11.9% -15.2% of their energy at breakfast from saturated fat, which is higher than the recommended total energy contribution of saturated fat (no more than 10% from saturated fat). For tracking of most food groups and nutrients, tracking was found to be low or moderate over time. Given the contribution that breakfast can make to ensure children achieve their daily dietary intakes, early interventions for young Australian children should focus on practical strategies to increase vegetable intake while reducing sodium and saturated fat intake at breakfast. [ABSTRACT FROM AUTHOR]

BackgroundThe first year of life is an important window to initiate healthy infant feeding practices to promote healthy growth. Interventions delivered by mobile phone (mHealth) provide a novel approach for reaching parents; however, little is known about the effectiveness of mHealth for child obesity prevention. ObjectiveThe objective of this study was to determine the feasibility and effectiveness of an mHealth obesity prevention intervention in terms of reach, acceptability, and impact on key infant feeding outcomes. MethodsA quasi-experimental study was conducted with an mHealth intervention group (Growing healthy) and a nonrandomized comparison group (Baby’s First Food). The intervention group received access to a free app and website containing information on infant feeding, sleep and settling, and general support for parents with infants aged 0 to 9 months. App-generated notifications directed parents to age-and feeding-specific content within the app. Both groups completed Web-based surveys when infants were less than 3 months old (T1), at 6 months of age (T2), and 9 months of age (T3). Survival analysis was used to examine the duration of any breastfeeding and formula introduction, and cox proportional hazard regression was performed to examine the hazard ratio for ceasing breast feeding between the two groups. Multivariate logistic regression with adjustment for a range of child and parental factors was used to compare the exclusive breastfeeding, formula feeding behaviors, and timing of solid introduction between the 2 groups. Mixed effect polynomial regression models were performed to examine the group differences in growth trajectory from birth to T3. ResultsA total of 909 parents initiated the enrollment process, and a final sample of 645 parents (Growing healthy=301, Baby’s First Food=344) met the eligibility criteria. Most mothers were Australian born and just under half had completed a university education. Retention of participants was high (80.3%, 518/645) in both groups. Most parents (226/260, 86.9%) downloaded and used the app; however, usage declined over time. There was a high level of satisfaction with the program, with 86.1% (143/166) reporting that they trusted the information in the app and 84.6% (170/201) claiming that they would recommend it to a friend. However, some technical problems were encountered with just over a quarter of parents reporting that the app failed to work at times. There were no significant differences between groups in any of the target behaviors. Growth trajectories also did not differ between the 2 groups. ConclusionsAn mHealth intervention using a smartphone app to promote healthy infant feeding behaviors is a feasible and acceptable mode for delivering obesity prevention intervention to parents; however, app usage declined over time. Learnings from this study will be used to further enhance the program so as to improve its potential for changing infant feeding behaviors.

BackgroundInfancy is an important life stage for obesity prevention efforts. Parents’ infant feeding practices influence the development of infants’ food preferences and eating behaviors and subsequently diet and weight. Mobile health (mHealth) may provide a feasible medium through which to deliver programs to promote healthy infant feeding as it allows low cost and easy access to tailored content. ObjectiveThe objective of this study was to describe the effects of an mHealth intervention on parental feeding practices, infant food preferences, and infant satiety responsiveness. MethodsA quasi-experimental study was conducted with an mHealth intervention group (Growing Healthy) and a nonrandomized comparison group (“Baby's First Food"). The intervention group received access to a free app with age-appropriate push notifications, a website, and an online forum that provided them with evidence-based advice on infant feeding for healthy growth from birth until 9 months of age. Behavior change techniques were selected using the Behaviour Change Wheel framework. Participants in both groups completed three Web-based surveys, first when their infants were less than 3 months old (baseline, T1), then at 6 months (time 2, T2), and 9 months of age (time 3, T3). Surveys included questions on infant feeding practices and beliefs (Infant Feeding Questionnaire, IFQ), satiety responsiveness (Baby Eating Behaviour Questionnaire), and infant’s food exposure and liking. Multivariate linear regression models, estimated using maximum likelihood with bootstrapped standard errors, were fitted to compare continuous outcomes between the intervention groups, with adjustment for relevant covariates. Multivariate logistic regression adjusting for the same covariates was performed for categorical outcomes. ResultsA total of 645 parents (Growing Healthy: n=301, Baby's First Food: n=344) met the eligibility criteria and were included in the study, reducing to a sample size of 546 (Growing Healthy: n=234, Baby's First Food: n=312) at T2 and a sample size of 518 (Growing Healthy: n=225, Baby's First Food: n=293) at T3. There were approximately equal numbers of boy and girl infants, and infants were aged less than 3 months at baseline (Growing Healthy: mean 7.0, SD 3.7 weeks; Baby's First Food: mean 7.9, SD 3.8 weeks), with Growing Healthy infants being slightly younger than Baby's First Food infants (P=.001). All but one (IFQ subscale “concerns about infant overeating or becoming overweight” at T2) of the measured outcomes did not differ between Growing Healthy and Baby's First Food. ConclusionsAlthough mHealth can be effective in promoting some health behaviors and offers many advantages in health promotion, the results of this study suggest that design and delivery characteristics needed to maximize the impact of mHealth interventions on infant feeding are uncertain. The sensitivity of available measurement tools and differences in baseline characteristics of participants may have also affected the results.

BackgroundInfant feeding practices, including breastfeeding and optimal formula feeding practices, can play a role in the prevention of childhood obesity. The ubiquity of smartphone ownership among women of childbearing age provides important opportunities for the delivery of low-cost, broad reach parenting interventions delivered by mobile phone (mHealth or mobile health interventions). Little is known about how parents engage with mHealth programs targeting infant feeding and how such programs might influence infant feeding practices. ObjectiveThe objectives of this study were to explore participant views on (1) factors influencing engagement with the Growing healthy program, an mHealth program targeting healthy infant feeding practices from birth to 9 months of age, and (2) the ways in which the program influenced behavioral determinants of capability, opportunity, and motivation for breastfeeding and optimal formula feeding behaviors. MethodsSemistructured, telephone interviews were conducted with a purposeful sample (n=24) of mothers participating in the Growing healthy program. Interviews explored participants’ views about engagement with the program and its features, and the ways the program influenced determinants of infant feeding behaviors related to breastfeeding and optimal formula feeding. The interview schedule was informed by the Capability, Opportunity, Motivation, and Behavior (COM-B) model. ResultsParticipants reported that engagement fluctuated depending on need and the degree to which the program was perceived to fit with existing parenting beliefs and values. Participants identified that the credibility of the program source, the user friendly interface, and tailoring of content and push notifications to baby’s age and key transition points promoted engagement, whereas technical glitches were reported to reduce engagement. Participants discussed that the program increased confidence in feeding decisions. For breastfeeding mothers, this was achieved by helping them to overcome doubts about breast milk supply, whereas mothers using formula reported feeling more confident to feed to hunger and satiety cues rather than encouraging infants to finish the bottle. Participants discussed that the program provided around-the-clock, readily accessible, nonjudgmental information and support on infant feeding and helped to reinforce information received by health professionals or encouraged them to seek additional help if needed. Participants reflected that their plans for feeding were typically made before joining the program, limiting the potential for the program to influence this aspect of motivation. Rather, the program provided emotional reassurance to continue with current feeding plans. ConclusionsOur findings suggest that engagement with the program was influenced by an interplay between the program features and needs of the user. Participants reported that the program enhanced confidence in feeding decisions by providing a 24/7 accessible, expert, nonjudgmental support for infant feeding that complemented health professional advice. It is likely that interventions need to commence during pregnancy to maximize the impact on breastfeeding intentions and plans.