Determinants and spatial patterns of anaemia and haemoglobin concentration among pregnant women in Nigeria using structured additive regression models

• Published in: Spatial and spatio-temporal epidemiology Vol. 45; p. 100578
• Main Authors: Ezenweke, Chinenye Pauline, Adeniyi, Isaac Adeola, Yahya, Waheed Babatunde, Onoja, Rhoda Enemona
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.06.2023
• Subjects: Anemia - epidemiology; Anemia - etiology; Empirical Bayes; Female; Generalized additive mixed effects models; Geo-additive models; Hemoglobins - analysis; Humans; Iron deficiency; Maternal anaemia; Nigeria - epidemiology; Pregnancy; Pregnant Women; Prevalence; Risk Factors; Nigeria; Empirical Bayes; Geo-additive models; Maternal anaemia; Iron deficiency; Generalized additive mixed effects models; Risk factors
• ISSN: 1877-5845; 1877-5853
• DOI: 10.1016/j.sste.2023.100578

•Maternal anaemia (MA) and Haemoglobin (Hb) levels are analysed using NDHS data.•Semiparametric structured additive models are employed for analyses.•Spatial patterns and risk factors for MA and low Hb level are identified.•MA prevalence is highest and lowest in Imo and Cross River states respectively.•States in close proximity do not necessarily share similar spatial effects. Anaemia which is a condition that describes low haemoglobin (Hb) levels has been recognized as a major public health problem amongst pregnant women in many sub-Saharan African countries including Nigeria. The causes of maternal anaemia which are interconnected and complex vary between countries and can vary within a country. This study aimed to investigate the spatial pattern and identify demographic and socio-economic determinants associated with anaemia amongst Nigerian pregnant women aged 15–49 years using data from the 2018 Nigeria Demographic and Health Survey (NDHS). This study utilized chi-square tests of independence and semiparametric structured additive models to describe the relationship between the presumed factors and anaemia status or Hb level while also taking spatial effects at state level into account. The Gaussian and Binomial distributions were used for Hb level and anaemia status respectively. The overall observed prevalence of anaemia in pregnant women and average Hb level in Nigeria were 64% and 10.4 (SD = 1.6) g/dL respectively while the prevalence of mild, moderate and severe anaemia were 27.2%, 34.6% and 2.2% respectively. Higher education, older age, and currently breastfeeding were associated with higher Hb level. Low education, being unemployed and recently having a sexually transmitted infection were identified as risk factors for maternal anaemia. Body mass index (BMI) and household size had a nonlinear effect on Hb level while BMI and age were nonlinearly related to odds of anaemia. Bivariate analysis indicated that living in rural area, low wealth class, using unsafe water and non-usage of internet were significantly associated with increased risk of anaemia. Maternal anaemia prevalence was highest in the South Eastern part of Nigeria with Imo state producing the highest prevalence of maternal anaemia while Cross River state yielded the lowest prevalence of maternal anaemia. The spatial effects associated with states were significant but unstructured indicating that states in close proximity do not necessarily share similar spatial effects. Hence, unobserved characteristics shared by states in close proximity do not influence maternal anaemia and Hb level. The findings from this study can undoubtedly help in the planning and designing of anaemia interventions that match local conditions taking into consideration the aetiology of anaemia in Nigeria.