Skip to main content
eScholarship
Open Access Publications from the University of California

UC Davis

UC Davis Previously Published Works bannerUC Davis

Malaria, malnutrition, and birthweight: A meta-analysis using individual participant data.

  • Author(s): Cates, Jordan E
  • Unger, Holger W
  • Briand, Valerie
  • Fievet, Nadine
  • Valea, Innocent
  • Tinto, Halidou
  • Tinto, Halidou
  • D'Alessandro, Umberto
  • Landis, Sarah H
  • Adu-Afarwuah, Seth
  • Dewey, Kathryn G
  • Ter Kuile, Feiko O
  • Desai, Meghna
  • Dellicour, Stephanie
  • Ouma, Peter
  • Gutman, Julie
  • Oneko, Martina
  • Slutsker, Laurence
  • Terlouw, Dianne J
  • Kariuki, Simon
  • Ayisi, John
  • Madanitsa, Mwayiwawo
  • Mwapasa, Victor
  • Ashorn, Per
  • Maleta, Kenneth
  • Mueller, Ivo
  • Stanisic, Danielle
  • Schmiegelow, Christentze
  • Lusingu, John PA
  • van Eijk, Anna Maria
  • Bauserman, Melissa
  • Adair, Linda
  • Cole, Stephen R
  • Westreich, Daniel
  • Meshnick, Steven
  • Rogerson, Stephen
  • et al.
Abstract

Background

Four studies previously indicated that the effect of malaria infection during pregnancy on the risk of low birthweight (LBW; <2,500 g) may depend upon maternal nutritional status. We investigated this dependence further using a large, diverse study population.

Methods and findings

We evaluated the interaction between maternal malaria infection and maternal anthropometric status on the risk of LBW using pooled data from 14,633 pregnancies from 13 studies (6 cohort studies and 7 randomized controlled trials) conducted in Africa and the Western Pacific from 1996-2015. Studies were identified by the Maternal Malaria and Malnutrition (M3) initiative using a convenience sampling approach and were eligible for pooling given adequate ethical approval and availability of essential variables. Study-specific adjusted effect estimates were calculated using inverse probability of treatment-weighted linear and log-binomial regression models and pooled using a random-effects model. The adjusted risk of delivering a baby with LBW was 8.8% among women with malaria infection at antenatal enrollment compared to 7.7% among uninfected women (adjusted risk ratio [aRR] 1.14 [95% confidence interval (CI): 0.91, 1.42]; N = 13,613), 10.5% among women with malaria infection at delivery compared to 7.9% among uninfected women (aRR 1.32 [95% CI: 1.08, 1.62]; N = 11,826), and 15.3% among women with low mid-upper arm circumference (MUAC <23 cm) at enrollment compared to 9.5% among women with MUAC ≥ 23 cm (aRR 1.60 [95% CI: 1.36, 1.87]; N = 9,008). The risk of delivering a baby with LBW was 17.8% among women with both malaria infection and low MUAC at enrollment compared to 8.4% among uninfected women with MUAC ≥ 23 cm (joint aRR 2.13 [95% CI: 1.21, 3.73]; N = 8,152). There was no evidence of synergism (i.e., excess risk due to interaction) between malaria infection and MUAC on the multiplicative (p = 0.5) or additive scale (p = 0.9). Results were similar using body mass index (BMI) as an anthropometric indicator of nutritional status. Meta-regression results indicated that there may be multiplicative interaction between malaria infection at enrollment and low MUAC within studies conducted in Africa; however, this finding was not consistent on the additive scale, when accounting for multiple comparisons, or when using other definitions of malaria and malnutrition. The major limitations of the study included availability of only 2 cross-sectional measurements of malaria and the limited availability of ultrasound-based pregnancy dating to assess impacts on preterm birth and fetal growth in all studies.

Conclusions

Pregnant women with malnutrition and malaria infection are at increased risk of LBW compared to women with only 1 risk factor or none, but malaria and malnutrition do not act synergistically.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
Current View