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

Anthropometric and Body Composition Outcomes of a Mobile Health Intervention to Improve Eating Behaviours and Lifestyle Habits During Infancy

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Childhood Obesity Prevention
• Intervention / Treatment: Behavioral: Feeding, Lifestyle, Activity Goals (FLAGs) Digital Health Application

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Estimated): 440
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Daniel Chan, MBBS, MMed, MRCPCh; Phone Number: 6563948430; Email: daniel.chan.w.k@singhealth.com.sg

Study Locations

• Singapore
  • Singapore
    • Singapore, Singapore, Singapore, 229899
      • KK Women's and Children's Hospital
      • Contact: Daniel Chan, MBBS, MMed, MRCPCh; Phone Number: 6563948430; Email: daniel.chan.w.k@singhealth.com.sg

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: 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.	Behavioral: 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.
No Intervention: 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Longitudinal growth trajectories and markers of infant metabolic health	Weight (kilograms)	12 months from recruitment
Longitudinal growth trajectories and markers of infant metabolic health	Length (meters)	12 months from recruitment
Longitudinal growth trajectories and markers of infant metabolic health	Body mass index (kg/m^2) will be determined by taking the weight (kilograms) divided by the squared value of the length (meters).	12 months from recruitment
Longitudinal growth trajectories and markers of infant metabolic health	Weight for length percentile (%) will be determined using the WHO 2006 Child Growth Standards	12 months from recruitment
Longitudinal growth trajectories and markers of infant metabolic health	Body composition, using skinfold thickness measurements (centimeters)	12 months from recruitment

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Indicators of good feeding and lifestyle behaviour	Feeding Lifestyle Activity Goals score, % -higher score denotes better feeding and lifestyle behaviour	12 months from recruitment
Indicators of good feeding and lifestyle behaviour	Baby Eating Behaviour Questionnaire; this is a psychometric measure of infant appetite and eating behavior; no scoring system available, findings are not reported on a scale	12 months from recruitment
Indicators of good feeding and lifestyle behaviour	Children Eating Behaviour Questionnaire; psychometric measure of a child's appetite and eating behavior; no scoring system available, findings are not reported on a scale	12 months from recruitment
Indicators of good feeding and lifestyle behaviour	Picky Eating Questionnaire; psychometric measure of dietary diversity; no scoring system available, findings are not reported on a scale	12 months from recruitment

Collaborators and Investigators

• Sponsor: KK Women's and Children's Hospital

Publications and helpful links

General Publications

• 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.
• 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.
• 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.
• 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.
• 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.

Study record dates

Study Major Dates

• Study Start (Estimated): November 1, 2025
• Primary Completion (Estimated): December 1, 2026
• Study Completion (Estimated): December 30, 2026

Study Registration Dates

• First Submitted: May 30, 2024
• First Submitted That Met QC Criteria: June 9, 2024
• First Posted (Actual): June 13, 2024

Study Record Updates

• Last Update Posted (Estimated): September 5, 2025
• Last Update Submitted That Met QC Criteria: August 28, 2025
• Last Verified: August 1, 2025

More Information

Terms related to this study

• Keywords: childhood obesity; population health; paediatrics; Developmental origins of health and disease; life course approach
• Additional Relevant MeSH Terms: Urogenital Diseases; Nutrition Disorders; Female Urogenital Diseases and Pregnancy Complications; Overnutrition; Body Weight; Pregnancy Complications; Overweight; Obesity; Prenatal Injuries; Pathological Conditions, Signs and Symptoms; Nutritional and Metabolic Diseases; Signs and Symptoms; Prenatal Exposure Delayed Effects; Pediatric Obesity; Developmental Origins of Health and Disease
• Other Study ID Numbers: AM/TP081/2024 (SRDUKAMR2481)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Deidentified individual participant data (IPD) underlying the published results will be made available on reasonable request from the corresponding author. Supporting documents, including the study protocol and statistical analysis plan, will also be shared.
• IPD Sharing Time Frame: Data will be available beginning 6 months after publication and for up to 5 years thereafter.
• IPD Sharing Access Criteria: Requests should be directed to the corresponding author (daniel.chan@duke-nus.edu.sg). Proposals must include a methodologically sound plan, and access will be granted for research aligned with the aims outlined in the approved proposal.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ICF; ANALYTIC_CODE; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No