Biogeographical and Altitudinal Distribution of Cataract: A Nine-Year Experience Using Electronic Medical Record-Driven Big Data Analytics in India

ABSTRACT

Purpose: To use electronic medical record data to study the altitude, UV exposure, and biogeographical distribution of senile cataract in India.

Methods: This is a hospital-based, cross-sectional study of patients over 40 years old with an ophthalmologist-confirmed diagnosis of senile cataract (cortical, nuclear, posterior subcapsular, or a combination) in either or both eyes. Electronic medical record data entered between August 2010 to December 2019 were extracted from a large multi-tiered ophthalmology network in India. Residential districts were classified into their respective biogeographical zone based on nationally reported boundaries, and altitude at the geographic centroid was determined using Google Earth. Occupations were classified as low UV exposure and high UV exposure. Descriptive statistics, hypothesis testing, and multiple logistic regression analysis were done.

Results: In the 1,127,232 eligible patients, associations were found between high UV exposure (OR = 1.47, 95%CI: 1.45–1.49), low socioeconomic status (OR = 1.54, 95%CI: 1.52–1.55), rural geographies (OR = 1.32), female gender (OR = 1.33, 95%CI: 1.32–1.34), and older age (OR$\ge 3.98$) with cataract. This Indian patient population did not demonstrate increased formation of cataracts at higher altitudes (OR$\le 0.97$). Patients residing in the Deccan Peninsula (OR$\ge 1.56$) and those with high UV exposures within each increasing altitude category, except >750 m, (OR$\ge 1.09)$ had higher odds of senile cataract comparatively.

Conclusion: Female gender, occupations with high UV exposure, rural geography and increasing age were observed to have greater odds of developing senile cataract. Increased likelihood of cataracts in populations residing at low altitudes and within the Deccan Peninsula may be attributed to greater hospital development in those areas.

KEYWORDS:

• Altitude
• cataracts
• biogeographical zone
• ocular morbidity
• big data analytics

Acknowledgments

The authors wish to acknowledge the support of the Department of eyeSmart EMR & AEye team specially Mr.Ranganath Vadapalli and Mr.Mohammad Pasha.