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Malnutrition among children under the age of five in the Democratic Republic of Congo (DRC): does geographic location matter?

Kandala NB, Madungu TP, Emina JB, Nzita KP, Cappuccio FP - BMC Public Health (2011)

Bottom Line: Each record represents a child and consists of nutritional status information and a list of covariates.The findings suggest that models of nutritional intervention must be carefully specified with regard to residential location.Improving maternal and child nutritional status is a prerequisite for achieving MDG 4, to reduce child mortality rate in the DRC.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Warwick, Warwick Medical School, Health Sciences Research Institute, Warwick Evidence, Gibbet Hill, CV4 7AL, Coventry, UK. N-B.Kandala@warwick.ac.uk

ABSTRACT

Background: Although there are inequalities in child health and survival in the Democratic Republic of Congo (DRC), the influence of distal determinants such as geographic location on children's nutritional status is still unclear. We investigate the impact of geographic location on child nutritional status by mapping the residual net effect of malnutrition while accounting for important risk factors.

Methods: We examine spatial variation in under-five malnutrition with flexible geo-additive semi-parametric mixed model while simultaneously controlling for spatial dependence and possibly nonlinear effects of covariates within a simultaneous, coherent regression framework based on Markov Chain Monte Carlo techniques. Individual data records were constructed for children. Each record represents a child and consists of nutritional status information and a list of covariates. For the 8,992 children born within the last five years before the survey, 3,663 children have information on anthropometric measures.Our novel empirical approach is able to flexibly determine to what extent the substantial spatial pattern of malnutrition is driven by detectable factors such as socioeconomic factors and can be attributable to unmeasured factors such as conflicts, political, environmental and cultural factors.

Results: Although childhood malnutrition was more pronounced in all provinces of the DRC, after accounting for the location's effects, geographic differences were significant: malnutrition was significantly higher in rural areas compared to urban centres and this difference persisted after multiple adjustments. The findings suggest that models of nutritional intervention must be carefully specified with regard to residential location.

Conclusion: Childhood malnutrition is spatially structured and rates remain very high in the provinces that rely on the mining industry and comparable to the level seen in Eastern provinces under conflicts. Even in provinces such as Bas-Congo that produce foods, childhood malnutrition is higher probably because of the economic decision to sell more than the population consumes. Improving maternal and child nutritional status is a prerequisite for achieving MDG 4, to reduce child mortality rate in the DRC.

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Related in: MedlinePlus

Histogram, kernel density of stunting (left) and mean standardized Z-score for stunting by child's age (right)
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Related In: Results  -  Collection

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Figure 1: Histogram, kernel density of stunting (left) and mean standardized Z-score for stunting by child's age (right)

Mentions: Figure 1 shows a histogram and kernel density estimates of the distribution of the Z-scores, together with a normal density, with mean and variance estimated from the sample. This gave us clear evidence that a Gaussian regression model is a reasonable choice for our inference for the dependent variable stunting.


Malnutrition among children under the age of five in the Democratic Republic of Congo (DRC): does geographic location matter?

Kandala NB, Madungu TP, Emina JB, Nzita KP, Cappuccio FP - BMC Public Health (2011)

Histogram, kernel density of stunting (left) and mean standardized Z-score for stunting by child's age (right)
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3111378&req=5

Figure 1: Histogram, kernel density of stunting (left) and mean standardized Z-score for stunting by child's age (right)
Mentions: Figure 1 shows a histogram and kernel density estimates of the distribution of the Z-scores, together with a normal density, with mean and variance estimated from the sample. This gave us clear evidence that a Gaussian regression model is a reasonable choice for our inference for the dependent variable stunting.

Bottom Line: Each record represents a child and consists of nutritional status information and a list of covariates.The findings suggest that models of nutritional intervention must be carefully specified with regard to residential location.Improving maternal and child nutritional status is a prerequisite for achieving MDG 4, to reduce child mortality rate in the DRC.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Warwick, Warwick Medical School, Health Sciences Research Institute, Warwick Evidence, Gibbet Hill, CV4 7AL, Coventry, UK. N-B.Kandala@warwick.ac.uk

ABSTRACT

Background: Although there are inequalities in child health and survival in the Democratic Republic of Congo (DRC), the influence of distal determinants such as geographic location on children's nutritional status is still unclear. We investigate the impact of geographic location on child nutritional status by mapping the residual net effect of malnutrition while accounting for important risk factors.

Methods: We examine spatial variation in under-five malnutrition with flexible geo-additive semi-parametric mixed model while simultaneously controlling for spatial dependence and possibly nonlinear effects of covariates within a simultaneous, coherent regression framework based on Markov Chain Monte Carlo techniques. Individual data records were constructed for children. Each record represents a child and consists of nutritional status information and a list of covariates. For the 8,992 children born within the last five years before the survey, 3,663 children have information on anthropometric measures.Our novel empirical approach is able to flexibly determine to what extent the substantial spatial pattern of malnutrition is driven by detectable factors such as socioeconomic factors and can be attributable to unmeasured factors such as conflicts, political, environmental and cultural factors.

Results: Although childhood malnutrition was more pronounced in all provinces of the DRC, after accounting for the location's effects, geographic differences were significant: malnutrition was significantly higher in rural areas compared to urban centres and this difference persisted after multiple adjustments. The findings suggest that models of nutritional intervention must be carefully specified with regard to residential location.

Conclusion: Childhood malnutrition is spatially structured and rates remain very high in the provinces that rely on the mining industry and comparable to the level seen in Eastern provinces under conflicts. Even in provinces such as Bas-Congo that produce foods, childhood malnutrition is higher probably because of the economic decision to sell more than the population consumes. Improving maternal and child nutritional status is a prerequisite for achieving MDG 4, to reduce child mortality rate in the DRC.

Show MeSH
Related in: MedlinePlus