DETERMINANTS OF MALARIA IN PREGNANCY IN A RUBBER PLANTATION COMMUNITY IN NIETE, CAMEROON (WEST AFRICA)

Abstract

Introduction: Malaria is a major public health problem in Cameroon (West Africa) where 100% of the population is at risk. Malaria in Cameroon is mainly due to infections by Plasmodium falciparum. Some population groups including pregnant women are at considerably higher risk of contracting malaria, and developing severe disease, than others. In Africa, 30 million women living in malaria-endemic areas become pregnant each year. It is known that malaria infection during pregnancy is a significant public health problem in Cameroon with substantial risks for the pregnant woman, her foetus, and the new-born child. The symptoms and complications of malaria in pregnancy vary according to malaria transmission intensity in the given geographical area and the individual’s level of acquired immunity. Agricultural practices of the population are often associated with malaria. Ecological complexity is both at the heart of agricultural impacts on malaria transmission and also the deepest challenge to successful collaboration between the agricultural and health sectors. Thus, malaria in pregnancy in plantation settings presents an important opportunity for health-related interventions that can simultaneously improve outcomes for both mother and child in Cameroon.

Objectives: 1. To identify socio-demographic factors associated with malaria in pregnancy in the plantation community at Niete, Cameroon. 2. To identify the antenatal, housing and environmental factors associated with malaria in pregnancy in this population. 3. To identify the outcomes associated with malaria in pregnancy in this population. Methods: The study design was case-control. The sample size comprised of 120 participants. There were 60 cases and 60 controls. Data was collected from hospital records and also by interview technique as well as observation of investigator. Univariate and Multivariate analysis were conducted for comparison purposes. In this study, a p-value <0.05 was considered as statistically significant. Results: In univariate analysis for determinants of malaria in pregnancy it was revealed that there were significant association between these factors listed below and malaria in pregnancy in the Niete Plantation: Socio- Demographic Factors: Younger Maternal Age, Lower Education, Lower Household Income, Women not being employed and Women Rubber Tappers. Antenatal Factors: Lower Frequency of antenatal attendance Housing Factors: Absence of Fan, No Toilet Facility, Wooden Floor Material, Wooden Wall Material, Wooden Floor Holes, Wooden Wall Holes, Zinc Roof Holes, More than six months older Insecticide Treated Net (ITN), Holes on Currently Using ITN’s, Lower Usage of ITN by Pregnant Women, and Lower Usage of ITN by All Age Groups Environmental Factors: Presence of Bush Around the House Compound, Presence of Mosquito Breeding Sites, Absence of Personal Use of Insecticides or Sprays, Less Than One Kilometre distance of water body from house and ownership of livestock especially pig. Then using Multiple Logistic Regression the confounders were removed and this analysis revealed that the best significant predictors of malaria in pregnancy which were ownership of fan (p = 0.001*, OR = 6.349, 95% CI = 2.679 – 15.045), bush around compound (p = 0.016*, OR = 2.378, 95% CI = 1.175 – 4.812), presence of mosquito breeding site (p = 0.009*, OR = 3.882, 95% CI = 1.407 – 10.712), and use of personal insecticides or sprays (p = 0.027*, OR = 2.229, 1.098 – 4.524). Furthermore, it was observed that women whom had malaria in pregnancy were significantly (P < 0.05) more likely to have babies with medical problems such as low birth weight and neonatal asphyxiation as compared to women who did not have malaria in pregnancy. Conclusion: This study identified the maintenance of a clean environment free of mosquito breeding sites and use personal protections in the form of mosquito repellents as most essential measures for reducing mortality and morbidity rates associated with malaria in pregnancy. Keywords: Predictors, Malaria, Pregnancy, Cameroon, Multiple Logistic Regression