Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa

Samuel H Nyarko; Ebenezer N K Boateng; Kwamena S Dickson; David Adzrago; Isaac Y Addo; Evelyn Acquah; Castro Ayebeng

doi:10.1186/s12884-023-06008-3

Geospatial disparities and predictors of anaemia among pregnant women in Sub-Saharan Africa

BMC Pregnancy Childbirth. 2023 Oct 20;23(1):743. doi: 10.1186/s12884-023-06008-3.

Authors

Samuel H Nyarko¹, Ebenezer N K Boateng², Kwamena S Dickson³, David Adzrago⁴, Isaac Y Addo⁵, Evelyn Acquah⁶, Castro Ayebeng⁷

Affiliations

¹ Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA.
² Department of Geography and Regional Planning, University of Cape Coast, Cape Coast, Ghana.
³ Department of Population and Health, University of Cape Coast, Cape Coast, Ghana.
⁴ Center for Health Promotion and Prevention Research (CHPPR), School of Public Health, The University of Texas Health Science Center at Houston (UTHealth), Houston, TX, USA.
⁵ Centre for Social Research in Health, The University of New South Wales, Sydney, Australia.
⁶ Centre for Health Policy and Implementation Research, Institute of Health Research, University of Health, and Allied Sciences, Ho, Ghana.
⁷ Department of Population and Health, University of Cape Coast, Cape Coast, Ghana. castro.ayebeng@stu.ucc.edu.gh.

Abstract

Background: Anaemia has become a major public health concern among women in Sub-Saharan Africa (SSA). However, little is known about the spatial disparities in anaemia prevalence and their associated factors among pregnant women in the region. This study analysed the spatial disparities in anaemia and their associated factors among pregnant women in rural and urban settings in SSA.

Methods: This is a secondary analysis of the most recent demographic and health surveys of 26 countries in SSA. Spatial autocorrelation and hotspot assessment were conducted, while a multivariate logistic regression model was used to identify demographic factors associated with anaemia.

Results: Anaemia was reported among ~50% of pregnant women in urban and rural areas of SSA. The hotspot analysis identified the West African sub-region as having a higher concentration of anaemia cases in rural settings. In urban areas, the odds of anaemia were significantly higher among pregnant women in their second trimester (Adjusted OR = 2.39, CI = 1.99, 2.76). On the other hand, pregnant women in their third trimester (Adjusted OR = 1.98, CI = 1.77, 2.22) and those who had taken intestinal parasite drugs (Adjusted OR = 1.12 CI = 1.02, 1.23) had a higher likelihood of having anaemia in rural areas. Pregnant women aged 35-39 years (Adjusted OR = 0.52, CI = 0.33, 0.81) and those aged 40-44 years (Adjusted OR = 0.69, CI = 0.50, 0.95) had a lesser likelihood of having anaemia compared to women aged 15-19 years in urban and rural areas respectively. Compared to Congo DR, Benin (OR = 2.22, CI = 1.51, 3.28) and Mali (OR = 3.71, CI = 2.73, 5.05) had higher odds of anaemia in urban and rural areas respectively.

Conclusions: Spatial disparities in anaemia persist among pregnant women in rural and urban settings in SSA. Prevailing spatial variations in anaemia may be addressed by specialised interventions considering the contextual residential settings and socio-economic factors highlighted in this study.

Keywords: Anaemia; Geospatial; Pregnant women; Sub-Saharan Africa.

MeSH terms

Anemia* / epidemiology
Female
Humans
Mali
Pregnancy
Pregnancy Trimester, Third
Pregnant Women*
Rural Population