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Quantification of Oculomotor Responses and Accommodation Through Instrumentation and Analysis Toolboxes
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Accommodative insufficiency in a student population in Iran.

Hassan Hashemi1, Mehdi Khabazkhoob2, Payam Nabovati3

  • 1Noor Research Center for Ophthalmic Epidemiology, Noor Eye Hospital, Tehran, Iran.

Journal of Optometry
|May 27, 2018
PubMed
Summary

This study found accommodative insufficiency (AI) in 4.07% of Iranian college students, with females showing a significantly higher prevalence than males. Age and refractive error were not significantly associated with AI.

Keywords:
Accommodative insufficiencyEstudianteInsuficiencia acomodativaPrevalencePrevalenciaStudent

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Area of Science:

  • Ophthalmology
  • Optometry
  • Public Health

Background:

  • Accommodative insufficiency (AI) is a common cause of asthenopia in young adults.
  • Understanding the prevalence and risk factors of AI is crucial for effective vision care in student populations.

Purpose of the Study:

  • To determine the prevalence of accommodative insufficiency (AI) in Iranian college students.
  • To investigate the relationship between AI and demographic factors (age, gender) and refractive errors.

Main Methods:

  • A cross-sectional study was conducted in 2017 with optometric examinations.
  • Amplitude of accommodation was measured using the Donders' push-up method (RAF rule).
  • Accommodative facility and response were assessed using flipper lenses and dynamic retinoscopy (MEM).

Main Results:

  • The prevalence of AI was 4.07%, with a significantly higher rate in females (6.04%) compared to males (2.01%).
  • Logistic regression revealed a 3.14 times higher odds of AI in females (p=0.009).
  • No significant association was found between AI and age or refractive error (emmetropia, myopia, hyperopia).

Conclusions:

  • The prevalence of AI in this Iranian college student population is relatively low.
  • Gender is a significant factor associated with AI, with females being more affected.
  • Further research may explore the underlying reasons for the gender disparity in AI prevalence.