Date Published: July 29, 2015
Publisher: Public Library of Science
Author(s): Jennifer L. Smith, Selvaraj Sivasubramaniam, Mansur M. Rabiu, Fatima Kyari, Anthony W. Solomon, Clare Gilbert, Thomas M. Lietman. http://doi.org/10.1371/journal.pntd.0003826
Abstract: The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.
Partial Text: Trachoma is the leading infectious cause of blindness worldwide, most recently estimated to be responsible for the loss of 333,000 disability-adjusted life years (DALYs) in 2010 . Recurrent episodes of infection with the bacterium Chlamydia trachomatis and associated inflammation cause cumulative scarring of the under surface of the upper eyelid which, in some individuals, eventually leads to trichiasis–a clinical stage of trachoma where the eyelashes turn inwards and touch the eye. Without surgical intervention, this condition can progressively damage the cornea and lead to visual impairment and irreversible blindness later in life [2,3].
The present study provides evidence that both individual-level risk factors and broader climatic conditions are associated with later stages of trachoma in adults over the age of 40 years in Nigeria, using uniquely detailed national survey data. The hierarchical approach used in this analysis has the advantage of incorporating risk factors at multiple levels and explicitly modelling residual spatial correlation in TT/CO that could affect the standard errors of estimates of association. A number of well-established individual-level risk factors for trichiasis were identified that included age, gender and occupation, as well as large-scale climatic and environmental factors (precipitation, LST, temperature and urban classification) that explained further variation in risk across the country. After adjusting for these factors, there remained a large cluster of higher risk localised in northern Nigeria (North-East and North-West zones). This finding suggests the presence of unknown risk factors which are locally clustered in these areas or spatially-varying relationships between included covariates and disease.