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The Congo offers highly contrasted situations with respect to the prevalences of CED, and these depended on the ecological zone and degree of urbanization. BMI therefore appears to be a good indicator of nutritional transition. The main features were a significant degree of maternal depletion with age in rural areas and a large trend towards obesity in the capital city despite the persistence of a proportion of adults with CED.

Fig. 5. Mean weight-for-height of children 1-3 years old by body mass index category of their mothers.

The BMI in mothers also appears to be linked with the degree of wasting in their children, as shown in Fig. 5. The mean weight-for-height of <5-year-old children in Brazzaville and in the rural Plateaux was significantly different between categories of mothers' BMI, being lower for CED mothers than for mothers with a normal BMI or for obese mothers. This relationship may be a true causal one: that is mothers with CED tend to have low birth weight babies or poorly growing infants: alternatively there may be various confounding factors, i.e. factors leading to CED in mothers that also produce some degree of wasting in children such as a low food availability in the household. Unfortunately we cannot confirm this at present because we need more in depth studies. But the existence of such a link allows us to use mothers' BMI in the Congo as a more general indicator of the nutritional risk of both mothers and children.

From the present data we can also conclude that the prevalence of low BMIs is clearly linked with the socio-economic level and is particularly sensitive to economic changes over time. In parallel we have observed that the prevalence of wasting (weight-for-height <-2 SD) in infants has also changed between 1986 and 1991, from 1.8% to 5.9%; (P <0.001). As both maternal and child changes are rather tightly linked, this reinforces our view that BMI in such situations of rapid economic changes may be used as a core indicator for nutritional surveillance purposes in the Congo.

Our results also suggest that the analysis of BMI population data must be done by age groups and by gender as each group may be affected differently over time without a change in the total population's BMI.

Finally, we should ask whether low BMI values have the same significance in women and in men, in the young and the old? Are the changes strictly linked to poverty or could they reflect some physiological differences? Although the comparison between rural and urban populations tends to favour the view that poverty is the key, studies on body composition would be helpful to solve these questions. We are therefore currently implementing studies of big-impedance analysis in the Congo to further assess this issue.

Acknowledgements - We would like to thank E Tchibindat, I. Goma and F. Simondon for participating in the conception of the 1986 and 1987 surveys; L. Faucon and M. Bonnefond for having collaborated with the 1986 and 1987 surveys and L. Berard and Y. Kameli with the 1991 and 1992 surveys. We are grateful to M. Lallemant (ORSTOM), D. Olivola (CARE-Congo) and P Villeneuve (UNICEF Brazzaville) for participating in the conception and financial support respectively of the 1986, 1987 and 1991 surveys.


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