Responsive complementary feeding (RCF) vs usual care: Z score BMI
- 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
- usual care
- Outcome
- Z score BMI
In one RCT, responsive complementary feeding lowered BMIz at 13 months versus control (0.23 vs 0.42, p=0.01; low certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Responsive complementary feeding (RCF) vs Control (usual care) BMI z-score (overweight/obesity) at 13 months · Healthy, term-born, normal-birth-weight infants aged 4-24 months (breastfed and/or formula-fed) in Western… · 13 months, Outpatient care in Western industrialized (European/Anglo-Saxon) countries In one RCT, responsive complementary feeding lowered BMIz at 13 months versus control (0.23 vs 0.42, p=0.01; low certainty). Complementary Feeding Caregivers' Practices and Growth, Risk of Overweight/Obesity, and Other… (2022) All outcomes | Risk of overweight and obesity after 13 mo (RCT, BMIz): DANIELS 2012 - children in the intervention group had a lower BMIz at 13 months than controls (0.23 +/- 0.93 vs 0.42 +/- 0.85; p = 0.01); 698 (1 RCT); Low. | 1 study · 698 participants | Low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Complementary Feeding Caregivers' Practices and Growth, Risk of Overweight/Obesity, and Other Non-Communicable Diseases: A Systematic… 2022 All outcomes | Updated to September 2021 | 24 | Low / 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.
- Evaluation of an intervention to promote protective infant feeding practices to prevent childhood obesity: outcomes of the NOURISH RCT at… · 2012 · included by 1 of these review
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.