Impact of cash transfer programs on birth and child growth outcomes: systematic review.
Cinthia Soares LisboaNathalia Sernizon GuimarãesAndrêa Jacqueline Fortes FerreiraKarine Brito Beck da SilvaFlavia Jôse Oliveira AlvesAline dos Santos RochaNaiá OrtelanCamila Silveira Silva TexeiraIla Rocha FalcãoNatanael Jesus da SilvaRita de Cássia Ribeiro SilvaDjanilson Barbosa Dos SantosMaurício Lima BarretoPublished in: Ciencia & saude coletiva (2023)
To investigate the impact of cash transfer (CTs) on birth outcomes, including birth weight, low birth weight and prematurity, as well as child physical growth were included, as assessed by anthropometric indices in children under five years of age. Searching was performed using the PubMed/Medline, Embase, LILACS, Cochrane Library, Scopus and Web of Science databases. Quantitative observational, experimental and quasi-experimental. Eleven studies were included in the review. The majority (81.8%) were carried out in low-and middle-income countries and most involved conditional CTs (63.6%). Four were clinical trials and seven were observational studies. Conditional CTs were found to be associated with a reduction in height-for-age (-0.14; 95%CI -0.27, -0.02); (OR 0.85; 95%CI 0.77-0.94); (OR = 0.44; 95%CI 0.19-0.98), a significantly reduced chance of low weight-for-age (OR = 0.16; 95%CI -0.11-0.43), low weight-for-height (OR = -0.68; 95%CI -1.14, -0.21), and low weight-for-age (OR = 0.27; 95%CI 0.10; 0.71). Unconditional CTs were associated with reduced birth weight (RR = 0.71; 95%CI 0.63-0.81; p < 0.0001) and preterm births (RR = 0.76; 95%CI 0.69-0.84; p < 0.0001). Conditional CTs can positively influence birth outcomes and child growth.
Keyphrases
- gestational age
- birth weight
- preterm birth
- low birth weight
- weight gain
- body mass index
- systematic review
- mental health
- preterm infants
- physical activity
- clinical trial
- human milk
- public health
- young adults
- randomized controlled trial
- type diabetes
- high resolution
- body composition
- adipose tissue
- pregnant women
- metabolic syndrome
- mass spectrometry
- big data
- skeletal muscle
- artificial intelligence