Journal of Epidemiology and Global Health (Jan 2023)

Impact of Sub-patent Malaria During Pregnancy on Birth-Weight in Odisha, India: Time-to-Event Analysis of Prospective Longitudinal Follow-Up of a Survey

  • Madhusmita Bal,
  • Jyoti Ghosal,
  • Arundhuti Das,
  • Sonali Sandeepta,
  • Sanghmitra Pati,
  • Ambarish Dutta,
  • Manoranjan Ranjit

DOI
https://doi.org/10.1007/s44197-022-00082-0
Journal volume & issue
Vol. 13, no. 1
pp. 23 – 31

Abstract

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Abstract Objective The current study aimed to estimate prevalence of malaria infection, especially sub-patent infection, in pregnant women residing in high malaria-endemic, hard-to-reach pockets of the Indian state of Odisha; and also measure its impact on birth-weight of their new-borns. Method A time-to-event analysis of prospective longitudinal follow-up study nested within a cross-sectional survey of people residing in high malaria-endemic six districts of Odisha was conducted during July–November 2019. Malaria status in pregnant mothers was categorized as malaria free; sub-patent, and patent. Hazards Ratio (HR) of low birth-weight (LBW; birth-weight < 2500 gms) was estimated in these three categories (n = 308) adjusted for residence (block), gravida, caste, age and gestational age at testing. Results 50.3% pregnant women had sub-patent malaria infection, 3.9% had patent infection. In fully adjusted model, hazards ratio of LBW was 3.76 (95% CI 1.12, 12.64, p = 0.032) in pregnant women with patent infection and 1.82 (95% CI 0.87, 3.81, p = 0.109) in women with sub-patent infection when compared to no malaria group. Conclusion The study showed that half of the pregnant women in high-endemic pockets had sub-patent infection which posed deleterious influence on birth-weight of their new-borns. The study thereby flags the prevalence of sub-patent infection as a public health concern, because sub-patent infection in pregnant mothers may persist as a “silent” reservoir, with the potential to derail the malaria control program, especially when the country plans malaria elimination by 2030.

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