Comparison of a possession score and a poverty index in predicting anaemia and undernutrition in pre-school children and women of reproductive age in rural and urban Côte d'Ivoire

Abstract

Objective: To determine whether a possession score or a poverty index best predicts undernutrition and anaemia in women of reproductive age (15-49 years; WRA) and children aged 6-59 months living in Côte d'Ivoire. Design: Anthropometric measurements were converted to Z-scores to assess stunting, wasting and underweight in children, and converted to BMI in WRA. A venous blood sample was drawn, and Hb concentration and Plasmodium spp. infection were determined. A possession score was generated with categories of zero to four possessions. A five-point (quintile) poverty index using household assets was created using principal component analysis. These socio-economic measures were compared for their ability to predict anaemia and malnutrition. Setting: Data were from a nationally representative survey conducted in Côte d'Ivoire in 2007. Subjects: A sample of 768 WRA and 717 children aged 6-59 months was analysed. Results: Overall, 74?9 % of children and 50?2 % of WRA were anaemic; 39?5 % of the children were stunted, 28?1 % underweight and 12?8 % wasted, while 7?4 % of WRA had BMI , 18?5 kg/m 2 . In general, there were more stunted and underweight children and thin WRA in rural areas. The poverty index showed a stronger relationship with nutritional status than the possession score; mean Hb difference between the poorest and wealthiest quintiles in children and WRA was 8?2 g/l and 6?5 g/l, respectively (13?9 % and 19?8 % difference in anaemia, respectively; P , 0?001), and Z-scores and BMI were significantly better in the wealthiest quintile (P , 0?001). Conclusions: The poverty index was generally a better predictor of undernutrition in WRA and pre-school children than the possession score.

Determinants of Body Mass Index and Intelligence Quotient of Elementary School Children in Mountain Area of Nepal: An Explorative Study

“…There was a positive association between age, grade and BMI during the childhood period [ 48 , 49 ] and the same trend showed in our study but the association is not linear ( Table 2 : Age 2 ~ −0.22). Likewise, poor economic status of the household was found to be a good predictor of low BMI in all family members and especially in the children [ 50 , 51 ], and these findings match our study results. BMI was significantly lower in families of lower SES in comparison with middle and high economic status, and nutrition and quality of food were associated with BMI [ 52 ].…”

The effect of productive SafetyNet program on wasting among under-five children in the rural community of South Gondar Zone, Northwest Ethiopia

“…As a result, children from households enrolled with PSNP were 37% (AOR: 0.63, 95% CI (0.40, 0.99)) less likely to develop wasting as compared to families without PSNP which is similar to other studies conducted in Bangladesh and Cote d'Ivoire [27,28]. This may be due to the strong relationship between low socioeconomic status and nutritional status.…”

Approaches and Alternatives to the Wealth Index to Measure Socioeconomic Status Using Survey Data: A Critical Interpretive Synthesis

“…Their use of a simple count of radio, television, bicycle, motorcycle, telephone, and electricity to construct wealth quintiles resulted in 49.1% of households in the lowest SES quintile and only 4.2% of the highest SES quintile having all three outcomes of interest, while the wealth index produced equivalent percentages of 28.6% and 11.4%, respectively. However, this study was strongly disputed by another team using the same indices in Cote d'Ivoire with rigorous biometric measures of nutritional status while accounting for the effect of malarial infection, age, and residency; where the wealth index resulted in larger socioeconomic inequalities in anemia, stunting, and wasting in children and women of reproductive age than the count score (Rohner et al 2012). In sum, count measures may present an easily constructed and persuasive SES measure, but results are highly dependent on the judgement of the analyst of which household assets to include and may not be transferable to other contexts.…”

“…Hundreds of manuscripts have used the wealth index to examine topics ranging from malnutrition (Mohsena et al 2010;Sahn and Stifel 2003), educational attainment (Booysen et al 2008;Nwaru et al 2012), malaria transmission (Chuma and Molyneux 2009;Rohner et al 2012), and poverty (Harttgen and Vollmer 2013;Zeller et al 2006). For fifteen years, the overwhelming majority of researchers creating these indices have followed the method developed by Filmer and Pritchett (2001) that summarizes multi-dimensional information on ownership of various household assets using principal components analysis (PCA) (Filmer and Scott 2012).…”