Evidence map›Paper›PMID 40097365›Full record

ArticleMaternal & child nutrition2025

Adaptation of the Remote Food Photography Method to Assess Infant Intake During Bottle-Feeding of Ready-to-Feed Formula.

Bhagya L Narayanan, Jonathan D Ventura, Alison K Ventura

Abstract read
In one paragraph

Article in Maternal & child nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Bhagya L NarayananDepartment of Kinesiology and Public Health, Center for Health Research, California Polytechnic State University, San Luis Obispo, California, USA.
Jonathan D VenturaDepartment of Computer Science & Software Engineering, California Polytechnic State University, San Luis Obispo, California, USA.ORCID 0000-0003-1661-8529
Alison K VenturaDepartment of Kinesiology and Public Health, Center for Health Research, California Polytechnic State University, San Luis Obispo, California, USA.ORCID 0000-0002-2948-4446

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bottle-fed infants are at a higher risk for obesity, yet interventions to modify bottle-feeding patterns have shown limited success. Accurate assessment of bottle-feeding patterns is an important basis for targeted interventions. Caregiver reports are susceptible to bias, highlighting the need for more robust methods. One promising approach is the Remote Food Photography Method (RFPM), which involves analysis of digital photographs to objectively assess intake. The purpose of this study was to adapt RFPM to measure the amount of ready-to-feed formula in bottles. Research assistants took digital photographs of bottles with varying amounts of formula and assessed bottle weight to create a predictive model data set (n = 100) and an external validation data set (n = 100). Image processing software was used to determine the area of formula in pixels. Formula area was regressed on actual bottle weight and the resulting regression parameters were used to calculate estimated bottle weights. Predictive models were validated by applying them to the external validation data set. Within the predictive model data set, the mean difference between estimated and actual bottle weight was equivalent within ±10% equivalence bounds (0.0005 g [90% CI, -0.45, 0.45]). Within the external validation data set, the mean difference between estimated and actual bottle weight was also equivalent within ±10% equivalence bounds (-17.0 g [90% CI, -18.85, -15.17]). Findings were similar when bottle weight was converted to calories. In sum, the present study provided preliminary evidence for the feasibility and accuracy of an adapted RFPM to assess changes in the amount and caloric content of ready-to-feed formula in bottles.

Indexed as

Bottle FeedingInfant FormulaPhotographyFemaleHumansInfantInfant Nutritional Physiological PhenomenaMalebottle‐feedingdietary assessmentfood photographyimage processing softwareinfant feeding practicesrapid infant weight gainready‐to‐feed formula

Identifiers

PMID40097365
PMCPMC12150128

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.