Question · asked by 1 review

Responsive complementary feeding (RCF) vs Other models of complementary feeding (traditional/non-responsive CF): Physical growth / weight gain

Population
Healthy, term-born, normal-birth-weight infants aged 4-24 months (breastfed and/or formula-fed) in Western industrialized countries
Intervention
Responsive complementary feeding (RCF)
Comparison
Other models of complementary feeding (traditional/non-responsive CF)
Outcome
Physical growth / weight gain

Two RCTs suggest responsive complementary feeding leads to better weight gain in the first two years, though effects were small and not always sustained (ungraded).

What each review found

Current versions only
FindingEffectStudiesGRADE certainty
Responsive complementary feeding (RCF) vs Other models of complementary feeding (traditional/non-responsive CF)
Physical growth / weight gain · Healthy, term-born, normal-birth-weight infants aged 4-24 months (breastfed and/or formula-fed) in Western… · First 2 years (up to 3-5 years), Outpatient care in Western industrialized (European/Anglo-Saxon) countries
Two RCTs suggest responsive complementary feeding leads to better weight gain in the first two years, though effects were small and not always sustained (ungraded).
Complementary Feeding Caregivers' Practices and Growth, Risk of Overweight/Obesity, and Other… (2022) All outcomes
The results of the two RCTs are consistent and suggest that RF during CF is effective, leading to better weight gain in the first 2 years of life; observational cohort results (2 RCTs and 5 observational studies) were…7 studiesGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Complementary Feeding Caregivers' Practices and Growth, Risk of Overweight/Obesity, and Other Non-Communicable Diseases: A Systematic…
2022 All outcomes
Updated to September 202124Low / Critically Low

Studies behind the findings

The primary studies the full-text reviews tie to this outcome. Reviews with headline outcomes only do not list them here.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.