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and their age ranges; whilst malnutrition showed significant association with the municipality supporting the existence of marked differences in accessibility of food explained by transport conditions available to each municipality. 260 We were also interested to distinguish the differences could exist among the mean height of Afro groups with different origin worldwide. We compared the mean height of Afro children from Cauca Pacific coast aged between 2-15 years with reported for black Caribbean and African children living in England (16); Cauca black girls’ average height (135,6 cm) was slightly above Caribbean (134 cm) and African (131,8 cm) while boys’ average (136,1 cm) was below than that of Caribbean and above African. We could speculate these differences are caused mainly by differences of physical activity and food provision. Several authors have assessed the impact of living conditions on children’s health and nutritional indicators (17). However, ENSIN and PANES surveys did not collected data on sociodemographic variable to broaden the scope of our results. Acosta and Meisel proposed an index of wealth for evaluating socio-economic status from anthropometric data of individuals categorized by ethnic groups in the National Survey of Demography and Health (ENDS, in Spanish) and National Survey of Nutritional Situation (13). This index enabled to extrapolate household income from observable living conditions. It was found that wealth/nutrition was positively correlated with Ortega R. y cols. height; individuals at the top of the socio-economic pyramid were taller than those at the bottom, being this, a generalized situation to indigenous, Afro-Colombians and others races. On the other hand, tendency of growth’s indices already reported may also be understood from disparities that exist in the availability of transport among the three municipalities target and their effect on families’ access to food. Mining is one of the main economic activities in this area of Pacific coast, but Guapi is the only municipality has three flights a week from Cali (the nearest main city), while arriving to Timbiquí and Lopez de Micay is addressed mainly by boat from Guapi. Hence, no native products become more expensive and inaccessible to general community, especially, the residents of Lopez de Micay and Timbiquí who reside predominantly in rural areas. Not surprisingly, risk of stunting, thinness and risk of thinness in these areas could be correlated with the consequences provoked by the illegal activities and armed conflict which have affected a homogenous and proper distribution of potable water for these families; in addition, its acquisition is limited either by high prices or because its use is prioritized for other activities. In this context, evidence on health disparities by ethnic (involving the risk of diseases and negative effects) (7) may also encourage the levels of malnutrition found in schoolchildren of this geographical region where there is prevalence of Afro. The most significant contribution that these findings bring to light is the disaggregation of the school nutritional status of TABLE 5 The relation between growth indicators according to BMI/A and Height/A and potentially predictor variables. Independent variables Coefficient P R2 Model 1. Students in normal nutritional status according to BMI/A 0,705 Municipality 2,358 0,000 Age range 0,609 0,000 Area 0,254 0,000 Ethnicity 0,217 0,016 Gender 0,000 0,976 Model 2. Students in malnutrition nutritional status according to BMI/A 0,198 Municipality 2,609 0,000 Age range 0,445 0,000 Area 0,000 0,987 Gender 0,015 0,427 Ethnicity 0,032 0,094 Model 3. Students in normal nutritional status according to Height/A 0,028 Municipality 0,165 0,000 Age range -0,062 0,000 Gender -0,080 0,002 Area 0,023 0,183 Ethnicity -0,014 0,385 Model 4. Students in malnutrition nutritional status according to Height/A 0,014 Municipality -0,113 0,000 Age range -0,019 0,313 Gender 0,014 0,461 Area 0,004 0,834 Ethnicity -0,001 0,952


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