Prevalence and causes of ocular morbidity in Mbeere District, Kenya. Results of a population-based survey.

Elena Schmidt

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

PURPOSE: Ocular morbidity (OM) describes any eye disease regardless of resultant visual loss. Ocular morbidity may affect large numbers of people in low income countries and could lead to many episodes of care. However there is limited evidence about the prevalence of ocular morbidity or resulting health-seeking behavior. This study in Mbeere District, Kenya, set out to explore both these issues. METHODS: A cross-sectional household survey was conducted in 2011. Trained teams moved from house to house examining and questioning residents on ocular morbidity and health-seeking behavior. Data were collected on standardized proformas and entered into a database for analysis. RESULTS: 3,691 people were examined (response rate 91.7%). 15.52% (95% CI 13.86-16.92) had at least one ocular morbidity in at least one eye. The leading cause was presbyopia which affected 25.11% (95% CI 22.05-28.45) of participants over 35 and increased with age. Other leading causes of OM were conditions that affected the lens (32.58%) and the conjunctiva (31.31%). No association was found between educational attainment or employment and OM. 9.63% (7.87-11.74) self-reported an ocular morbidity in the previous six months and 45.94% (95% CI 37.1-55.04) stated that they had sought treatment for the condition. CONCLUSION: A large number of people were affected by an ocular morbidity in this survey. Most of these people could potentially be managed in their own communities through primary care services (e.g. those with presbyopia). Further work is required to understand the best way of providing an effective, equitable service for ocular morbidity.
Original languageEnglish
Pages (from-to)e70009
JournalPLoS ONE
DOIs
Publication statusPublished - 1 Aug 2013
Externally publishedYes

Keywords

  • Young Adult
  • Eye Diseases
  • Prevalence
  • General Science & Technology
  • Adolescent
  • Data Collection
  • Aged
  • Infant, Newborn
  • Adult
  • Middle Aged
  • Child, Preschool
  • Female
  • Male
  • Health Behavior
  • Kenya
  • Infant
  • Child
  • MD Multidisciplinary
  • Humans

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