Rapid assessment of visual impairment (RAVI) in marine fishing communities in South India - study protocol and main findings

BACKGROUND: Reliable data are a pre-requisite for planning eye care services. Though conventional cross sectional studies provide reliable information, they are resource intensive. A novel rapid assessment method was used to investigate the prevalence and causes of visual impairment and presbyopia in subjects aged 40 years and older. This paper describes the detailed methodology and study procedures of Rapid Assessment of Visual Impairment (RAVI) project. METHODS: A population-based cross-sectional study was conducted using cluster random sampling in the coastal region of Prakasam district of Andhra Pradesh in India, predominantly inhabited by fishing communities. Unaided, aided and pinhole visual acuity (VA) was assessed using a Snellen chart at a distance of 6 meters. The VA was re-assessed using a pinhole, if VA was < 6/12 in either eye. Near vision was assessed using N notation chart binocularly. Visual impairment was defined as presenting VA < 6/18 in the better eye. Presbyopia is defined as binocular near vision worse than N8 in subjects with binocular distance VA of 6/18 or better. RESULTS: The data collection was completed in <12 weeks using two teams each consisting of one paramedical ophthalmic personnel and two community eye health workers. The prevalence of visual impairment was 30% (95% CI, 27.6-32.2). This included 111 (7.1%; 95% CI, 5.8-8.4) individuals with blindness. Cataract was the leading cause of visual impairment followed by uncorrected refractive errors. The prevalence of blindness according to WHO definition (presenting VA < 3/60 in the better eye) was 2.7% (95% CI, 1.9-3.5). CONCLUSION: There is a high prevalence of visual impairment in marine fishing communities in Prakasam district in India. The data from this rapid assessment survey can now be used as a baseline to start eye care services in this region. The rapid assessment methodology (RAVI) reported in this paper is robust, quick and has the potential to be replicated in other areas.