Trial Review

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Trial registered on ANZCTR


Registration number
ACTRN12616000368437
Ethics application status
Approved
Date submitted
17/03/2016
Date registered
22/03/2016
Date last updated
22/03/2016
Type of registration
Retrospectively registered

Titles & IDs
Public title
Appetite control and body composition in breastfed infants
Scientific title
Term fully breastfed infants - investigation of factors contributing to appetite control and body composition
Secondary ID [1] 288787 0
Nill known
Universal Trial Number (UTN)
Nill known
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Prevention of obesity 298054 0
Condition category
Condition code
Diet and Nutrition 298210 298210 0 0
Obesity
Oral and Gastrointestinal 298211 298211 0 0
Normal oral and gastrointestinal development and function
Reproductive Health and Childbirth 298212 298212 0 0
Breast feeding

Intervention/exposure
Study type
Observational
Patient registry
False
Target follow-up duration
Target follow-up type
Description of intervention(s) / exposure
1. Body composition is measured during first 12 months of lactation at 2, 5, 9 and 12 months of age (infant - with ultrasound skinfolds and bioimpedance; mother - with bioimpedance only). Infant and mother anthropometrics are measured.
2. Breastmilk macronutrients and components are measured at 2, 5, 9 and 12 months of lactation.
3. Gastric emptying (stomach volumes) of term fully breastfed infants feeding on demand is measured at 2 and 5 months of age together with breastmilk components.
4. Infant bladder is and stomach are measured in conjunction with bioimpedance at 2, 5, 9 and 12 months of age.
5. Levels of pesticide residues in human milk during the first year of lactation is measured.
All measurements are conducted at 2 or 5 months of age, infants followed up to 12 months of age with measurements at 5, 9 and/or 12 months of age. No further follow up.
Intervention code [1] 294233 0
Not applicable
Comparator / control treatment
N/A
Control group
Uncontrolled

Outcomes
Primary outcome [1] 297716 0
Primary Outcome 1: Longitudinal and cross-sectional associations between breastmilk macronutrients/appetite control components (eg. lactose, protein, whey protein, casein, fat, leptin, adiponectin, ghrelin, obestatin, insulin, lysozyme, lactoferrin, total carbohydrates; g /L) and infant body composition (percentage fat mass; assessed by bioimpedance spectroscopy and ultrasound skinfolds).

Electronic scales (BabyWeigh Scale, Medela AG, Switzerland, sensitive to 2g) are used to weigh infants before and after a feed. Infant body composition (percentage fat mass, %) is measured with bioimpedance spectroscopy (SBF7, Impedimed, Brisbane, QLD, Australia) and ultrasound skinfolds (Toshiba Aplio XG, Japan). Infant body length (cm) and head circumference (cm) are measured with non-stretch type.
Milk samples (2-3 mL) are collected pre- and post-feed for analyses of the milk content (eg. lactose, protein, whey protein, casein, fat, leptin, adiponectin, ghrelin, obestatin, insulin, lysozyme, lactoferrin, total carbohydrates and other). Protein concentration is measured using the Bradford Protein Assay. Lactose concentration is determined using the enzymatic-spectrophotometric method. Leptin and adiponectin concentration is measured using an enzyme linked immunosorbent assay (ELIZA) optimised to measure these hormones in breastmilk.
Timepoint [1] 297716 0
Timepoints: at 2, 5, 9 and 12 months of age.
Primary outcome [2] 297730 0
Primary Outcome 2: The effect of milk composition (assessed by pre- and post-feed breastmilk sample) on gastric emptying (mL/min; assessed by ultrasound) of term fully breastfed infants feeding on demand. Cross-sectional and longitudinal study.

Electronic scales (BabyWeigh Scale, Medela AG, Switzerland, sensitive to 2g) are used to weigh infants before and after a feed to measure milk intake. Gastric emptying rate is measured with ultrasound (Toshiba Aplio XG, Japan) before and after a feed and each 5 - 20 minutes till next feed. Milk samples (2-3 mL) are collected pre- and post-feed for analyses of the milk content (lactose, protein, whey protein, casein, fat, leptin, adiponectin, ghrelin, obestatin, insulin, lysozyme, lactoferrin). Infant feeding frequency (meals/day) at the time of the study session is reported by mother.
Timepoint [2] 297730 0
Timepoints: at 2 and/or 5 months of age.
Secondary outcome [1] 322005 0
Secondary Outcome 1: Effect of milk intake (mL) and extracellular fluid reservoirs on bioimpedance (resistance, ohm) measurements in term breastfed infants. Crossectional study.

Electronic scales (BabyWeigh Scale, Medela AG, Switzerland, sensitive to 2g) are used to weigh infants before and after a feed to measure milk intake. Infant body composition is measured with bioimpedance spectroscopy (SBF7, Impedimed, Brisbane, QLD, Australia) pre- and post-feed. Stomach and bladder volumes (mL) are measured with ultrasound (Toshiba Aplio XG, Japan) before and after a feed. Infant’s body length (cm) is measured with non-stretch type.
Resistance measurements at 0 kHz, 50 kHz and infinite frequency (R0, R50, Rinf) and resistance of intracellular water (Ricw) are analyzed with customized infant settings. Free-water volumes (mL) and free-water change (mL) are determined from stomach and bladder volumes (mL) calculated from ultrasound images. The effect of the milk intake (mL), feed duration (min), and the volume of the infant’s stomach and bladder (mL) on the resistance values (ohm) pre-/post-feed are assessed to establish the feasibility of using these values interchangeably during data collection.
Timepoint [1] 322005 0
Timepoints: 2, 5, 9 or 12 months of age at single assessment session following enrolment
Secondary outcome [2] 322006 0
Secondary Outcome 2: Determinants of body composition (percent fat mass, %) in breastfed infants using bioimpedance spectroscopy and ultrasound skinfolds – methods comparison. Cross sectional study.

Electronic scales (BabyWeigh Scale, Medela AG, Switzerland, sensitive to 2g) are used to weigh infants before a feed. Infant body composition (percentage fat mass, %) is measured with bioimpedance spectroscopy (SBF7, Impedimed, Brisbane, QLD, Australia) and ultrasound skinfolds (Toshiba Aplio XG, Japan). The performance of bioimpedance spectroscopy and ultrasound skinfolds in determining percentage fat mass (%) in breastfed infants is evaluated and compared to reference infant body composition models.
Timepoint [2] 322006 0
Timepoints: at 2, 5, 9 or 12 months of age at a single assessment session following enrolment for each infant.
Secondary outcome [3] 322007 0
Secondary Outcome 3: Longitudinal study on the change of pesticide residues in breastmilk (ng/mL) collected at 2, 5, 9 and 12 months.

Collected milk samples are extracted and cleaned with modified acetate buffered QuEChERS. The final extract is analysed with a Bruker Daltonics 450 Gas chromatography with a Bruker Daltonics Scion TQ triple quadruple mass spectrometer (GC-MS/MS) (Billerica, MA, USA). Identification and quantification are carried out by tandem mass spectrometry using scheduled multiple reaction monitoring (MRM) mode. Data collection and processing are performed using Bruker MSWS 8 software.
Timepoint [3] 322007 0
Timepoints: at 2, 5, 9 or/and 12 months of age
Secondary outcome [4] 322008 0
Secondary Outcome 4: Relationship between pesticide residues in breastmilk and demographic factors. Cross-sectional study.

Maternal and infant’s demographic information are summarized and analysed to establish possible associations between pesticides concentration (ng/mL) in maternal milk and both maternal demographics, such as age, parity, body mass index (BMI) and body composition (fat mass, kg; fat-free mass, kg; percentage fat mass, %), and infant’s demographics, such as infant birth weight (kg), body length (cm), head circumference (cm) and body composition (fat mass, kg; fat-free mass, kg; percentage fat mass, %).
Collected milk samples are extracted and cleaned with modified acetate buffered QuEChERS. The final extract is analysed with a Bruker Daltonics 450 Gas chromatography with a Bruker Daltonics Scion TQ triple quadruple mass spectrometer (GC-MS/MS) (Billerica, MA, USA). Identification and quantification are carried out by tandem mass spectrometry using scheduled multiple reaction monitoring (MRM) mode. Data collection and processing are performed using Bruker MSWS 8 software.
Timepoint [4] 322008 0
Timepoints: at 2, 5, 9 or 12 months of age a single assessment session following enrolment of the infant.
Secondary outcome [5] 322039 0
Secondary Outcome 5: Longitudinal and cross-sectional associations between breastmilk macronutrients/appetite hormones (ng/mL) and mother body composition (percentage fat mass).

Maternal height (cm) is self-reported or measured against marked wall with dropdown. Maternal body composition (percentage fat mass, %) is measured with bioimpedance spectroscopy (SBF7, Impedimed, Brisbane, QLD, Australia).
Milk samples (2-3 mL) are collected pre- and post-feed for analyses of the milk content (eg. lactose, protein, whey protein, casein, fat, leptin, adiponectin, ghrelin, obestatin, insulin, lysozyme, lactoferrin, total carbohydrates and other). Protein concentration is measured using the Bradford Protein Assay. Lactose concentration is determined using the enzymatic-spectrophotometric method. Leptin and adiponectin concentration is measured using an enzyme linked immunosorbent assay (ELIZA) optimised to measure these hormones in breastmilk.
Timepoint [5] 322039 0
Timepoints; at 2, 5, 9 and/or 12 months of age

Eligibility
Key inclusion criteria
Inclusion criteria were: singletons, gestational age greater than or equal to 37 weeks, fully breastfed at 2 and 5 months and breastfed at the time of the study.
Minimum age
2 Months
Maximum age
12 Months
Sex
Both males and females
Can healthy volunteers participate?
Yes
Key exclusion criteria
Exclusion criteria were: infant health issues that could potentially influence growth and development, and low maternal milk supply.

Study design
Purpose
Natural history
Duration
Longitudinal
Selection
Defined population
Timing
Prospective
Statistical methods / analysis
The initial aim was to recruit 30 infants, 2 or 5 months old for longitudinal study and 40 for cross-sectional (10 in each age group of 2, 5, 9 and 12 months old). Those recruited at 2 and 5 months were invited to continue as a part of longitudinal study. We expected to keep 80% of the cross-sectional participants (n=16) and would need extra 14 to a total of 54. We had to recruit 18 extra participants for cross-sectional study (n=58) to achieve gender balance, thus increasing target to 72.
Sample size calculation:
Participants with useable data were included in study Effect of milk intake (mL) and extracellular fluid reservoirs on bioimpedance (resistance, ohm) in term breastfed infants. Pilot data (n=5, two measurements under identical conditions) gave mean +/- SD within participant differences of 7.4 +/- 7.7. Using alpha = 0.05; 62 participants gives the study power of 0.8 to detect a mean difference between pre- and post-feed resistance measures of 2.4.
In an absence of any knowledge about how different two measures of %FM with bioimpedance and ultrasound skinfolds for study Determinants of body composition (percent fat mass, %) in breastfed infants using bioimpedance spectroscopy and ultrasound skinfolds – methods comparison we have taken an effect size of 0.5. To this effect size 33 participants would have given us power of 0.80. The number of participants was rounded to 40, ten in each age group. Recruitment was extended to achieve similar group sizes whilst maintaining the gender balance. Using alpha = 0.05, 58 participants give the study power of 0.94 to detect the effect size of 0.3.

Data analysis:
Statistical analysis used R 2.9.0 1 for Mac OSX with packages nlme, irr, multcomp, lattice, ggplot2, car and MASS. Descriptive statistics are reported as mean +/-SD (range), model parameters presented as estimate (95%CI). P values <0.05 were considered statistically significant except where an adjustment for multiple comparisons false discovery rate was performed. All tests were two-tailed. Analysis was carried out by age groups and by different sex within age.
Bioimpedance measurements were assessed for variability (CV) and repeatability (ICC, 95% CI) for a subset of infants (n=16, two per age/sex grouping). Changes in resistance pre-/post-feed (delta R) were assessed by calculating bias/95% CI for pre- versus post-feed BIS as per Bland and Altman (n=59). A 95% CI containing zero was interpreted as no consistent change. Associations between changes in resistance and predictors/covariates of interest were assessed using linear regression. Model selection used forwards stepwise selection. Age was treated as a categorical variable, and included in the models where an analysis of variance omnibus test indicated that one or more ages differed from the others. Association between infant age (factor) and pre-feed resistance were assessed using Tukey’s all-pair comparisons based on OLS regression. Model appropriateness tested using standard residual diagnostics. Infant movements pre-/post-feed were compared using paired Student’s t-test.
One-sample Kolmogorov-Smirnov tests were used to compare the 13 calculated sets of %FM results with distributions from each of the eight references. Each age/sex group has been compared with the most appropriate reference distributions. Raw data (n=58) was used for calculating averages to compare overall equations performances in the whole group. Some overall analyses were repeated after removing two equations with minimum (less than 1/3) matches to the references.
Linear mixed effects models with random intercept per participant were used to determine whether %FM measurements differed systematically by infant sex, infant age group, or equation. Where there were more than two levels of categorical variable, Tukey’s Honest Significant Difference was used to determine which levels differed. Possible sex differences between methods were tested with interaction between sex and equation.
For study Gastric emptying (mL/min) of term fully breastfed infants feeding on demand data were checked for normal distribution showing no evidence that the data required transformation. Linear regression with two fractional polynomial terms of continuous covariates was used with the random effect of different slopes over time for each participant and the time post-feed as the fixed effects. The model accounted for the small stomach volumes/long time post-feed. The time immediately post-feed was coded as 0.5 minute not 0.0 minute as 0 is not a valid value for some of the polynomial terms. Final model was selected using the decrease in the log likelihood.
Final selected models (fractional polynomials of time, up to two terms, plus initial feed volume) were used to investigate the association between post-feed stomach volumes (dependent variable) and concentrations and doses of leptin, lactose and fat (predictors). The fractional polynomial model for protein concentration and dose failed to converge and more simplistic model was used with linear random effects vs. intercept only random effect.
A linear regression (univariate models) was used to test relationships between stomach pre-feed residual volume, milk intake, feed duration and leptin and macronutrients’ concentrations and doses. Multivariate models accounting for total feed volume were used for testing relationship with feed volume dependent predictor (fat dose and concentration).
Statistical analyses for longitudinal study on the change of pesticide residues in breatmilk were performed using the SPSS software (SPSS, version 19.0 for windows, SPSS, USA). Data were presented based on volume of human milk (ng/mL) and milk fat (ng/g fat). Only values above detection limit were used. One-way ANOVA with Bonferronil and Tukey multiple comparison tests were used to compare differences in pesticides concentration between pre- and post-feed milk samples, and pesticides at different lactation stages.
Multiple linear regressions were used to analyse associations between pesticides concentration in mother’s milk and maternal demographics, such as age, parity, body mass index (BMI) and body composition (% fat mass), and infant’s demographics, such as infant’s birth weight (kg), body length (cm), head circumference (cm) and baby body composition (% fat mass).

1. R Core Team. R: a language and environment for statistical computing. In: Pinheiro J, Bates D, DebRoy S, Sarkar D, Team RC, eds. Vienna, Austria: R Foundation for Statistical Computing, 2009.

Recruitment
Recruitment status
Completed
Date of first participant enrolment
Anticipated
Actual
21/03/2013
Date of last participant enrolment
Anticipated
Actual
2/10/2015
Date of last data collection
Anticipated
Actual
Sample size
Target
72
Accrual to date
Final
60
Recruitment in Australia
Recruitment state(s)
WA

Funding & Sponsors
Funding source category [1] 293151 0
Commercial sector/Industry
Name [1] 293151 0
Unrestricted research grant from Medela AG (Switzerland)
Country [1] 293151 0
Switzerland
Primary sponsor type
Individual
Name
A/Prof Donna T. Geddes
Address
School of Chemistry and Biochemistry (M310)
Faculty of Life and Physical Sciences
The University of Western Australia
35 Stirling Highway
Crawley, WA 6009, Australia
Country
Australia
Secondary sponsor category [1] 291951 0
None
Name [1] 291951 0
Address [1] 291951 0
Country [1] 291951 0
Other collaborator category [1] 278905 0
Individual
Name [1] 278905 0
Professor Leigh C. Ward
Address [1] 278905 0
School of Chemistry and Molecular Biosciences
Molecular Biosciences Building #76
University of Queensland
St Lucia
Brisbane
QLD 4072
Country [1] 278905 0
Australia

Ethics approval
Ethics application status
Approved
Ethics committee name [1] 294647 0
The Human Research Ethics Office of The University of Western Australia
Ethics committee address [1] 294647 0
Ethics committee country [1] 294647 0
Australia
Date submitted for ethics approval [1] 294647 0
Approval date [1] 294647 0
30/08/2010
Ethics approval number [1] 294647 0
RA/4/1/4253
Ethics committee name [2] 294648 0
The Human Research Ethics Office of The University of Western Australia
Ethics committee address [2] 294648 0
Ethics committee country [2] 294648 0
Australia
Date submitted for ethics approval [2] 294648 0
Approval date [2] 294648 0
13/05/2011
Ethics approval number [2] 294648 0
RA/4/1/4668
Ethics committee name [3] 294649 0
The Human Research Ethics Office of The University of Western Australia
Ethics committee address [3] 294649 0
Ethics committee country [3] 294649 0
Australia
Date submitted for ethics approval [3] 294649 0
Approval date [3] 294649 0
02/04/2013
Ethics approval number [3] 294649 0
RA/4/1/2639

Summary
Brief summary
Trial website
Trial related presentations / publications
Public notes

Contacts
Principal investigator
Name 64474 0
A/Prof Donna T. Geddes
Address 64474 0
The University of Western Australia
M310, 35 Stirling Highway
Crawley WA 6009
Country 64474 0
Australia
Phone 64474 0
+61 8 6488 7006
Fax 64474 0
+61 8 6488 7086
Email 64474 0
[email protected]
Contact person for public queries
Name 64475 0
Donna T. Geddes
Address 64475 0
The University of Western Australia
M310, 35 Stirling Highway
Crawley WA 6009
Country 64475 0
Australia
Phone 64475 0
+61 8 6488 7006
Fax 64475 0
+61 8 6488 7086
Email 64475 0
[email protected]
Contact person for scientific queries
Name 64476 0
Donna T. Geddes
Address 64476 0
The University of Western Australia
M310, 35 Stirling Highway
Crawley WA 6009
Country 64476 0
Australia
Phone 64476 0
+61 8 6488 7006
Fax 64476 0
+61 8 6488 7086
Email 64476 0
[email protected]

No information has been provided regarding IPD availability


What supporting documents are/will be available?

No Supporting Document Provided



Results publications and other study-related documents

Documents added manually
No documents have been uploaded by study researchers.

Documents added automatically
SourceTitleYear of PublicationDOI
EmbaseAssociations between maternal body composition and appetite hormones and macronutrients in human milk.2017https://dx.doi.org/10.3390/nu9030252
EmbaseHuman milk adiponectin and leptin and infant body composition over the first 12 months of lactation.2018https://dx.doi.org/10.3390/nu10081125
EmbaseHuman milk casein and whey protein and infant body composition over the first 12 months of lactation.2018https://dx.doi.org/10.3390/nu10091332
EmbaseRelationships between breastfeeding patterns and maternal and infant body composition over the first 12 months of lactation.2018https://dx.doi.org/10.3390/nu10010045
EmbaseCarbohydrates in human milk and body composition of term infants during the first 12 months of lactation.2019https://dx.doi.org/10.3390/nu11071472
EmbaseDevelopment of visceral and subcutaneous-abdominal adipose tissue in breastfed infants during first year of lactation.2021https://dx.doi.org/10.3390/nu13093294
EmbaseHuman milk immunomodulatory proteins are related to development of infant body composition during the first year of lactation.2021https://dx.doi.org/10.1038/s41390-020-0961-z
N.B. These documents automatically identified may not have been verified by the study sponsor.