Active trachoma among children in Mali: Clustering and environmental risk factors

• Published in: PLoS neglected tropical diseases Vol. 4; no. 1; p. e583
• Main Authors: Hägi, Mathieu, Schémann, Jean-François, Mauny, Frédéric, Momo, Germain, Sacko, Doulaye, Traoré, Lamine, Malvy, Denis, Viel, Jean-François
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.01.2010; Public Library of Science (PLoS)
• Subjects: Access to education; Age; Age Factors; Alliances; Behavior; Child; Child, Preschool; Children & youth; Climate; Community; Disease; Ecology/Spatial and Landscape Ecology; Environmental factors; Environmental risk; Female; Health promotion; Households; Humans; Hygiene; Life Sciences; Male; Mali - epidemiology; Population density; Public Health and Epidemiology/Environmental Health; Public Health and Epidemiology/Social and Behavioral Determinants of Health; Risk Factors; Santé publique et épidémiologie; Social conditions; Studies; Temperature; Trachoma - epidemiology; Tropical diseases; Womens health; Mali; Climate; Age Factors; Mali; Humans; Risk Factors; Child, Preschool; Trachoma; Female; Male; Child
• DOI: 10.1371/journal.pntd.0000583
• ISSN: 1935-2735; 1935-2727

Active trachoma is not uniformly distributed in endemic areas, and local environmental factors influencing its prevalence are not yet adequately understood. Determining whether clustering is a consistent phenomenon may help predict likely modes of transmission and help to determine the appropriate level at which to target control interventions. The aims of this study were, therefore, to disentangle the relative importance of clustering at different levels and to assess the respective role of individual, socio-demographic, and environmental factors on active trachoma prevalence among children in Mali. We used anonymous data collected during the Mali national trachoma survey (1996-1997) at different levels of the traditional social structure (14,627 children under 10 years of age, 6,251 caretakers, 2,269 households, 203 villages). Besides field-collected data, environmental variables were retrieved later from various databases at the village level. Bayesian hierarchical logistic models were fit to these prevalence and exposure data. Clustering revealed significant results at four hierarchical levels. The higher proportion of the variation in the occurrence of active trachoma was attributable to the village level (36.7%), followed by household (25.3%), and child (24.7%) levels. Beyond some well-established individual risk factors (age between 3 and 5, dirty face, and flies on the face), we showed that caretaker-level (wiping after body washing), household-level (common ownership of radio, and motorbike), and village-level (presence of a women's association, average monthly maximal temperature and sunshine fraction, average annual mean temperature, presence of rainy days) features were associated with reduced active trachoma prevalence. This study clearly indicates the importance of directing control efforts both at children with active trachoma as well as those with close contact, and at communities. The results support facial cleanliness and environmental improvements (the SAFE strategy) as population-health initiatives to combat blinding trachoma.