Prevalence and Determinants of Placental Malaria in Gezira State, Sudan: The Role of Demographic, Clinical, and Socioeconomic Factors

Ibrahiem Ismail¹, Nosiba  Alkareem², Madina Mohammed³, Basil Elsir⁴, Huda Mahmoud⁵

Authors

  • Ibrahiem Ismail Author
  • Nosiba Nosiba Abd Alraheem Aljack Awad Alkareem Author
  • Madina Abass Tyrab Mohammed Author
  • Basil Elsir Author
  • Huda Mahmoud Author

Keywords:

placental malaria; Plasmodium falciparum; pregnancy; Sudan; Gezira State; risk factors; histology; antenatal care; insecticide-treated nets.

Abstract

Background:

 PLacental malaria (PM) due to Plasmodium falciparum remains a significant cause of maternal anaemia, low birth weight (LBW), preterm birth, and perinatal mortality in malaria-endemic regions, particularly in sub-Saharan Africa.[1–4] The burden of malaria in pregnancy (MiP) varies with transmission intensity, parity, age, and socioeconomic conditions.[1,5–7] In Sudan, several hospital-based studies have documented high PM prevalence and important regional variation,[8–11] but data from Gezira State remain limited. This study estimated the prevalence of PM in Gezira and explored demographic, clinical, and socioeconomic determinants.

Methods: A cross-sectional hospital-based study was conducted from January to December 2021 in three central localities of Gezira State (Wad Medani, Hasahesa, and Almanagil). Consecutive women with singleton pregnancies delivering at selected public facilities were enrolled (n = 275). A structured questionnaire and record review captured information on age, parity, education, residence, antenatal care (ANC) utilisation, insecticide-treated net (ITN) use, body mass index (BMI), and obstetric history. Peripheral maternal blood and cord blood were examined by microscopy, and placental biopsies were examined histologically and classified as no infection, active, active-chronic, or past-chronic infection. Placental malaria for analysis was defined as any histological evidence of infection. Associations were explored using chi-square tests and multivariate logistic regression.

Results: The mean maternal age was 28.06 years (median 28; range 21 years). Age group, parity, education level, and place of residence were all significantly associated with malaria status in bivariate analyses (p < 0.001 for age, parity, and education; p = 0.008 for residence). Overall, 40.0% of women had peripheral parasitaemia and 40.0% had cord blood parasitaemia. Placental histology revealed that 20.0% had active infection, 20.0% had active-chronic infection, and 20.0% had past-chronic infection, yielding a cumulative histological PM prevalence of 60.0%. ITN use (reported by 60.0% of women) was not associated with malaria status (p = 1.0). In multivariate logistic regression, age remained a strong independent predictor of PM (β = 0.4236, p < 0.001), while parity was not significant (β = −0.0747, p = 0.515). The highest infection burdens were observed in women aged 26–35 years with parity 2–3. None of the women classified as overweight had malaria, whereas 50.0% of women with normal BMI were infected.

Conclusion: Placental malaria is highly prevalent among women delivering in Gezira State, with histology revealing a 60% cumulative infection burden despite relatively high ANC attendance and self-reported ITN use. Age was the dominant independent predictor, and the expected protective effect of increasing parity was not seen after adjustment. The findings highlight the influence of socio-environmental conditions and gaps in the quality of preventive services, and suggest that MiP control strategies in Gezira should extend beyond primigravidae to include older multigravid women

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Published

2025-12-09

Conference Proceedings Volume

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Articles

How to Cite

Ismail, I. (2025) “Prevalence and Determinants of Placental Malaria in Gezira State, Sudan: The Role of Demographic, Clinical, and Socioeconomic Factors: Ibrahiem Ismail¹, Nosiba  Alkareem², Madina Mohammed³, Basil Elsir⁴, Huda Mahmoud⁵”, Journal of Advanced Research -EMR, 69(27), p. 44. Available at: https://wos-emr.net/index.php/JAREM/article/view/DataScience-WebofScience-Emr-Globalresearchcollaboration4emr112O (Accessed: 15 April 2026).

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