Joint spatial mapping of childhood anemia and malnutrition in sub-Saharan Africa: A cross-sectional study of small-scale geographical disparities

Abstract

Background: In epidemiological studies, several diseases share common risk factors or co-exist in their spatial prevalence. Disease mapping allows the health practitioners and epidemiologists to proffer hypothesis pertaining to their etiology and gain better understanding of the geographical pattern of the disease risks. Objective: This paper investigates the differences in small scale geographical variations and the underlying risk factors on child’s health outcomes (anemia, stunting and wasting) in Sub-Saharan Africa using spatial epidemiology. Method: The study first carried out an independent univariate analysis on each malnutrition indicator to identify underlying risk factors. A multivariate conditional autoregressive prior model was later explored to jointly model the spatial association between the malnutrition indicators and the geographical disparities across the sub-national-levels. Results: The approach was implemented on data from National cross-sectional household- based demographic and health surveys conducted among 17,307 children under five years of age in Burkina Faso and Mozambique in 2010-2012. Out of these children, 31.8% are found to be stunted, 15.5% wasted and 30.9% had anemia among Burkina Faso children, while 42.5% of Mozambican children were stunted, 5.9% wasted and 30.9% suffered from iron-deficiency anemia. The multivariate analysis revealed that the with geographical variations of stunting across regions in Burkina Faso was estimated as :0.7549, CI (0.4693, 1.264); wasting 0.9197; (95%CI : 0.535, 1.591)and anemia : 0.734; (0.4606, 1.214). In addition, the conditional l correlation of structured random effects between stunting and wasting was negatively correlated: -0.998; 95% CI (-1.000, -0.984), and a perfect negative correlation ;(-1) between stunting and anemia, and a significantly positive correlation in spatial prevalence between wasting and anemia of 0.997; (0.978, 1.000). Among Mozambican children, there were strong positive correlation between stunting and wasting; 0.986; (0.899, 1.000) and a significant negative correlation between stunting and anemia: -0.720, (-0.934, -0.308) and wasting and anemia: -0.640; (-0.903 -0.174) with individual malnutrition status geographical variations of 1427, (913.6, 2268); : 1751, (1117, 2803) and 556, (279.5, 978.9) for in child stunting, wasting and anemia respectively. These extra random effect parameters computed in our multivariate approach would outperform a univariate analysis in similar studies. Our model further detected high prevalent of malnutrition and anemia in the northern Burkina Faso, but high anemia prevalent found in central Mozambique, and high stunting and wasting identified Southern Mozambique. In addition, the risk factors of malnutrition and iron deficiency anemia included household poverty, morbidity, short birth interval (less 18 months), breast feeding, antenatal attendance and maternal literacy. Conclusion: The statistical relevance of the identified risk factors in this study is useful to target specific individual intervention and the maps of the geographical inequalities in sub-national region can be used for designing a combination of nutrition interventions and allocation of scarce health resources.