Socioeconomic inequalities in hidden hunger, undernutrition, and overweight among under-five children in 35 sub-Saharan Africa countries

Abstract

Background: Many underlying factors are assumed to contribute to the disparities in magnitude of childhood malnutrition. Notwithstanding, socioeconomic inequalities remain key measures to determine chronic and hidden hunger among under-five children. This study was undertaken to explore childhood malnutrition problems that are associated to household wealth-related and mother's educational attainment in sub-Saharan Africa (SSA). Methods: Secondary data from birth histories in 35 SSA countries was used. The Demographic and Health Survey (DHS) data of 384,747 births between 2008 and 2017 in 35 countries was analyzed. The outcome variables of interest were mainly indicators of malnutrition: stunting, underweight, wasting, overweight, anemia, and under-five children survival. Household wealth-related and mother's educational level were the measures of socioeconomic status. Concentration index and Lorenz curves were the main tools used to determine inequalities for nutritional outcomes. The statistical significance level was determined at 5%. Results: Based on the results, Burundi (54.6%) and Madagascar (48.4%) accounted for the highest prevalence of stunted children. Underweight children were 32.5% in Chad and 35.5% in Niger. Nigeria (16.6%) and Benin (16.4%) had the highest burdens of wasted children. Overall, overweight and under-five survival were significantly more in the higher household wealth, compared with the lower household wealth (Conc. Index = 0.0060; p < 0.001 and Conc. Index = 0.0041; p = 0.002 respectively). Conversely, stunting (Conc. Index = − 0.1032; p < 0.001), underweight (Conc. Index = − 0.1369; p < 0.001), wasting (Conc. Index = − 0.0711; p < 0.001), and anemia (Conc. Index = − 0.0402; p < 0.001) were significantly lower in the higher household wealth status, compared with the lower household wealth groups. Furthermore, under-five children survival was significantly more from mothers with higher educational attainment, compared with children from mothers with lower educational attainment (Conc. Index = 0.0064; p < 0.001). Conversely, stunting (Conc. Index = − 0.0990; p < 0.001), underweight (Conc. Index = − 0.1855; p < 0.001), wasting (Conc. Index = − 0.1657; p < 0.001), overweight (Conc. Index = − 0.0046; p < 0.001), and anemia (Conc. Index = 0.0560; p < 0.001) were significantly more among children from mothers with lower educational attainment. The test for differences between children from urban vs. rural was significant in stunted, underweight, overweight, and anemia for household wealth status. Also, the difference in prevalence between children from urban vs. rural was significant in stunted, underweight, and wasted for mother's educational attainment.

Extent of and trends in inequalities in child stunting in Sierra-Leone from 2005 to 2013: evidence from demographic and health surveys and multiple indicator cluster surveys

“…Our finding that stunting is more common among children of women with low educational attainment is aligned with similar prior findings [16,39,42]. The possible explanation for this is that a higher maternal education could lead to improved health care use which, in turn, affects health-related decisions that improve child nutritional outcomes [45].…”

“…Similar wealth related disparity in stunting was documented in literature [41]. A multi-country analysis based on DHSs conducted in 35 SSA countries showed that stunting was more concentrated among the poorer households [42]. Akombi BJ et al (2019) indicated that children born to women who fell in the richest wealth category had, on average, a 47% lower odd of experiencing stunting compared with children born to women in the poorest wealth quintile [39].…”

Household factors associated with infant and under-five mortality in sub-Saharan Africa countries

“…The policy implication of the findings is that concerted efforts of social welfare intervention towards household structure improvement could serve as a panacea for child mortality by operating through either socioeconomic status or fertility-related behaviour. For instance, household socioeconomic status determined the children nutrition patterns (Ekholuenetale et al 2020). No doubt, the time and resources available for a child's care are assumed to be affected by household structure or family Table 4 (continued) Model III Crude model, Model IV Adjusted model, n/a not estimated due to small sample, HR hazard ratio; CI Confidence Interval *Significant at p < 0.05 characteristics (Akinyemi et al 2013).…”

Prevalence and Socioeconomic Inequalities in Eight or More Antenatal Care Contacts in Ghana: Findings from 2019 Population-Based Data

“…The concentration index was used in eight or more ANC contacts to compute the contrast. 43 , 44 Statistical significance was determined at p< 0.05. Stata version 14 (StataCorp., College Station, TX, USA) was used for data analysis.…”