Anthropometric Outcomes of a Mobile Health Intervention for Eating Behaviour and Lifestyle in Infancy

NCT ID: NCT06457750

Last Updated: 2025-09-05

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

440 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-11-01

Study Completion Date

2026-12-30

Brief Summary

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Lifestyle, activity, and feeding behaviours during early childhood set the foundation for subsequent lifelong metabolic health as an adult. The investigators have developed a digital tool, called Feeding, Lifestyle, Activity Goals (FLAGs) to assess lifestyle and feeding behaviours of young infants, simultaneously providing guidance and tailored advice for parents on ideal practices specific to their children. The investigators aim to assess its usability, acceptability, and feasibility , before proceeding to determine efficacy of the FLAGs intervention through conducting a randomized controlled trial, enrolling 440 infants from KK Women's and Children's Hospital. Half of them will receive standard routine infant care, whereas the other half will additionally receive the digital FLAGs assessment and advisory tool, complete with mobile nudges. The follow-up period will be over 12 months, with the main outcomes being i) indicators of good feeding and lifestyle behaviour at 12 months old, and ii) physical growth trends, body fat proportions. Demonstrating the benefits of using FLAGs will underscore the importance of integrating this digitalized tool into the screening and evaluation of well children, with the potential to be upscaled and adopted across hospitals, primary care, and community-based health programmes.

Detailed Description

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Childhood obesity rates have been steadily increasing worldwide, reaching 5.6% for girls and 7.8% for boys in 2016, compared to 0.7% and 0.9% in 1975, respectively. The rise has led to the development of multiple metabolic co-morbidities among children, including dysglycaemia, hypertension, hyperlipidaemia, and fatty liver disease. Childhood obesity also sets the stage for adult overweight and obesity, along with increased cardiovascular risks. Therefore, it is essential to start right early with healthy lifestyle and feeding practices since birth. Implementing interventions during the postpartum period holds the potential for long-term maternal-child benefits, fostering a virtuous cycle of health. Cardiometabolic risk factors have been clearly identified from early childhood, such as the consumption of sugar-sweetened beverages, suboptimal weaning practices with inadequate introduction of diverse food consistencies and tastes within the first six months of life, excessive or inadequate caloric intake, and excessive screen time exposure. These factors are associated with increased body mass index in children. Given the social and environmental nature of these influences, effective approaches are those which intervene holistically through community engagement to modify behaviour, adopting the use of digital and technology-based healthcare.

Existing infant care models undervalue the importance of establishing healthy lifestyle behaviours and optimal eating outcomes for infants and toddlers. Furthermore, there is a gap between what is known to increase a child's risks of developing non-communicable diseases as an adult, and what caregivers understand about optimizing their child's health. Addressing this unmet need requires innovative and sustainable intervention approach to apply for the general public. Digital technologies possess immense potential for advancing health promotion and public health initiatives, maximizing community outreach and engagement. The investigators have developed an innovative digitalized tool, called Feeding, Lifestyle, Activity Goals (FLAGs) to assess lifestyle and feeding behaviours of young children from birth to age 2. FLAGs provides performance evaluation, guidance, and tailored advice for parents on ideal practices specific to their children. This digital application can be easily administered right via computers or smart devices from birth. FLAGs has undergone content and expert validations by eight domain experts from primary and tertiary healthcare settings, receiving positive evaluations regarding tool validity through high scores on the scale content validity index and agreement test.

The investigators' goal is to establish healthy lifestyle behaviours in infants, leading to improved health outcomes in early years. The overall objective of this proposed study is to determine the effects of FLAGs intervention on infant's lifestyle behaviours, growth, and metabolic health outcomes. The central hypothesis is that infants whose caregivers are exposed to FLAGs intervention will exhibit healthier lifestyle behaviours, leading to optimal physical growth and metabolic health status at 12 months of age, compared to those without FLAGs intervention. To test the hypothesis, a prospective, two-arm, randomized controlled trial will be conducted, recruiting 440 infant-caregiver pairs with a 1-year follow-up from KK Women's and Children's Hospital. Participants in the intervention arm will be exposed to FLAGs over a 1-year period. The specific aims are as follows:

Aim 1: To determine usability, acceptability, and feasibility of the FLAGs digital tool by conducting a pilot phase study. From results of this pilot phase study, further refinement to the application's content, user interface, and features will be performed before proceeding on to determine its efficacy.

Aim 2: To examine the effect of FLAGs intervention on infant body mass index, weight for length, and body composition at 12 months of age. The investigators hypothesize that after 12 months of FLAGs intervention, infants will demonstrate lower body mass index, weight for length, and reduced body fat as measured by skinfold thickness and body fat percentage at 12 months of age.

Aim 3: To examine the effect of FLAGs intervention on infant's lifestyle and eating behaviours at 12 months of age. The investigators hypothesize that infants randomised to the FLAGs intervention arm will demonstrate significantly healthier lifestyle behaviour, as indicated by a higher total FLAGs score, along with healthier eating habits, compared to those randomised to the control arm without FLAGs intervention. The total FLAGs score will be derived from the summation scores of the infant eating, sleeping, and activity domains in the FLAGs tool. Eating habits will be measured using established and validated questionnaires.

This proposed study will demonstrate the benefits of using FLAGs, a digital assessment and advisory tool to shape an infant's behaviour and early health outcomes, thereby highlighting its importance to be integrated into current models of paediatric healthcare.

Conditions

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Childhood Obesity Prevention

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

PREVENTION

Blinding Strategy

NONE

Study Groups

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Intervention Arm (Exposed to FLAGs Digital Health Application)

Participants in the intervention group will have access to the FLAGs assessment tool together with the real-time feedback and advisory provided by the digital application, complete with mobile nudges.

Group Type EXPERIMENTAL

Feeding, Lifestyle, Activity Goals (FLAGs) Digital Health Application

Intervention Type BEHAVIORAL

Feeding, lifestyle, activity goals (FLAGs) is a digital assessment and advisory tool developed by the investigators to facilitate early identification of lifestyle behaviour problems and abnormal feeding patterns in infants, with real-time feedback for caregivers. The FLAGs questionnaire examines the domains of energy regulation, timeliness and adequacy of weaning, dietary practices, and lifestyle habits. Tailored recommendations have been developed for each domain accordingly. The objective of FLAGs is shaping healthy lifestyle and feeding behaviours from birth, charting a trajectory to optimal metabolic health.

Control Arm

Participants in the control group will not have access to the FLAGs advisory and monitoring functions will not be made available on their digital application. Participants will not receive any automated notifications or nudges.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Feeding, Lifestyle, Activity Goals (FLAGs) Digital Health Application

Feeding, lifestyle, activity goals (FLAGs) is a digital assessment and advisory tool developed by the investigators to facilitate early identification of lifestyle behaviour problems and abnormal feeding patterns in infants, with real-time feedback for caregivers. The FLAGs questionnaire examines the domains of energy regulation, timeliness and adequacy of weaning, dietary practices, and lifestyle habits. Tailored recommendations have been developed for each domain accordingly. The objective of FLAGs is shaping healthy lifestyle and feeding behaviours from birth, charting a trajectory to optimal metabolic health.

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

* Women
* 34-36 weeks' pregnant, or 3 days post-delivery.
* Pre-pregnancy BMI of at least 23 kg/m\^2, and/or with the diagnosis of gestational diabetes mellitus or type 2 diabetes mellitus.

Exclusion Criteria

* Women less than 21 years old
* Unable to understand English
* Not planning to reside in Singapore until baby is at least 1 year old
* Premature birth of baby (defined as below 37 weeks' gestation)
* Birth of a baby with congenital abnormalities, physical or neurodevelopmental disabilities
Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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KK Women's and Children's Hospital

OTHER_GOV

Sponsor Role lead

Responsible Party

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Daniel Chan

Consultant

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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KK Women's and Children's Hospital

Singapore, Singapore, Singapore

Site Status

Countries

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Singapore

Central Contacts

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Daniel Chan, MBBS, MMed, MRCPCh

Role: CONTACT

6563948430

Facility Contacts

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Daniel Chan, MBBS, MMed, MRCPCh

Role: primary

6563948430

References

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NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet. 2017 Dec 16;390(10113):2627-2642. doi: 10.1016/S0140-6736(17)32129-3. Epub 2017 Oct 10.

Reference Type BACKGROUND
PMID: 29029897 (View on PubMed)

Singh AS, Mulder C, Twisk JW, van Mechelen W, Chinapaw MJ. Tracking of childhood overweight into adulthood: a systematic review of the literature. Obes Rev. 2008 Sep;9(5):474-88. doi: 10.1111/j.1467-789X.2008.00475.x. Epub 2008 Mar 5.

Reference Type BACKGROUND
PMID: 18331423 (View on PubMed)

Scott JA. The first 1000 days: A critical period of nutritional opportunity and vulnerability. Nutr Diet. 2020 Jul;77(3):295-297. doi: 10.1111/1747-0080.12617. No abstract available.

Reference Type BACKGROUND
PMID: 32478460 (View on PubMed)

Kouvari M, Karipidou M, Tsiampalis T, Mamalaki E, Poulimeneas D, Bathrellou E, Panagiotakos D, Yannakoulia M. Digital Health Interventions for Weight Management in Children and Adolescents: Systematic Review and Meta-analysis. J Med Internet Res. 2022 Feb 14;24(2):e30675. doi: 10.2196/30675.

Reference Type BACKGROUND
PMID: 35156934 (View on PubMed)

Tanrikulu MA, Agirbasli M, Berenson G. Primordial Prevention of Cardiometabolic Risk in Childhood. Adv Exp Med Biol. 2017;956:489-496. doi: 10.1007/5584_2016_172.

Reference Type BACKGROUND
PMID: 27864799 (View on PubMed)

Chan D, Leong K, Ong C, Ku CW, Chan JKY, Chua MC, Yap F, Loy SL. Efficacy of a mobile app-based intervention to improve eating behaviours and lifestyle in infants of mothers with metabolic risk factors: study protocol of a randomised controlled trial. BMJ Open. 2025 Sep 30;15(9):e101684. doi: 10.1136/bmjopen-2025-101684.

Reference Type DERIVED
PMID: 41033754 (View on PubMed)

Other Identifiers

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AM/TP081/2024 (SRDUKAMR2481)

Identifier Type: -

Identifier Source: org_study_id

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