| Literature DB >> 35502064 |
Parikshit M Gogate1, Supriya P Phadke2, Taraprasad Das3, Shrivallabh Sane4, Soumya Moosa5, Ashok Dhangar2, Minhaj Inamdar2, Rajiv Khandekar6, Renu Magdum7, Jitendra S Bhawalkar8, Kashinath Bhoosnurmath5.
Abstract
Purpose: To estimate the prevalence of blindness and severe visual impairment (SVI) by using a door-to-door screening and vision center (VC) examination strategy in an urban area in western Maharashtra (Pune), India and repeat the exercise after 4 years to study its impact.Entities:
Keywords: Cataract; India; blindness; vision centre; visual impairment
Mesh:
Year: 2022 PMID: 35502064 PMCID: PMC9332945 DOI: 10.4103/ijo.IJO_2314_21
Source DB: PubMed Journal: Indian J Ophthalmol ISSN: 0301-4738 Impact factor: 2.969
Age and gender distribution in two cohorts
| 2015-16 | 2018-19 | |||||
|---|---|---|---|---|---|---|
|
|
| |||||
| Male (%) | Female (%) | Total (%) | Male (%) | Female (%) | Total (%) | |
| Age group in years | ||||||
| <5 | 1968 (8.9%) | 1857 (8.3%) | 3825 (8.6%) | 419 (1.9%) | 373 (1.7%) | 792 (1.8%) |
| 6-18 | 5433 (24.5%) | 5054 (22.6%) | 10487 (23.6%) | 5006 (23%) | 4724 (21.5%) | 9730 (22.3%) |
| 19-30 | 5772 (26%) | 6132 (27.4%) | 11904 (26.7%) | 5523 (25.4%) | 5701 (26%) | 11224 (25.7%) |
| 31-50 | 6163 (27.8%) | 6389 (28.6%) | 12552 (28.2%) | 7011 (32.2%) | 7273 (33.1%) | 14284 (32.9%) |
| 51-70 | 2259 (10.2%) | 2305 (10.3%) | 4564 (10.2%) | 3192 (14.7%) | 3228 (14.7%) | 6420 (14.7%) |
| >70 | 579 (2.61%) | 593 (2.7%) | 1172 (2.6%) | 623 (2.9%) | 632 (2.9%) | 1255 (2.9%) |
| Total | 22174 | 22330 | 44504 | 21774 | 21931 | 43705 |
| Age data not available | 14 | 17 | 31 | 2 | 1 | 3 |
| Grand Total | 22188 | 22347 | 44535 | 21776 | 21932 | 43708 |
Visual acuity of examined individuals in 2015-16 and 2018-19 (better eye)
| Parameters | <3/60 | 3/60-6/60 | 6/60-6/24 | >6/18 | Total |
|---|---|---|---|---|---|
| All | |||||
| 2015 | 118 (0.26%) | 43 (0.1%) | 579 (1.3%) | 43795 (98.3%) | 44535 |
| 2019 | 72 (0.16%) | 23 (0.05%) | 460 (1.1%) | 43153 (98.7%) | 43708 |
| Male | |||||
| 2015 | 51 (0.2%) | 20 (0.1%) | 237 (1.1%) | 21880 (98.6%) | 22188 |
| 2019 | 32 (0.1%) | 8 (0.0%) | 176 (0.9%) | 21559 (99.0%) | 21775 |
| Female | |||||
| 2015 | 67 (0.3%) | 23 (0.1%) | 342 (1.5%) | 21915 (98.1%) | 22347 |
| 2019 | 40 (0.2%) | 15 (0.0%) | 281 (0.9%) | 21597 (98.5) | 21933 |
| Age | |||||
| <5 | |||||
| 2015 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 3825 (100.0%) | 3825 |
| 2019 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 792 (100%) | 792 |
| 6-18 | |||||
| 2015 | 1 (0.0%) | 0 (0.0%) | 6 (0.1%) | 10480 (99.9%) | 10487 |
| 2019 | 0 (0.0%) | 0 (0.0%) | 2 (0.02%) | 9728 (99.9%) | 9730 |
| 19-30 | |||||
| 2015 | 7 (0.1%) | 1 (0.0%) | 17 (0.1%) | 11879 (99.8%) | 11904 |
| 2019 | 5 (0.04%) | 0 (0.0%) | 15 (0.1%) | 11204 (99.8%) | 11224 |
| 31-50 | |||||
| 2015 | 13 (0.1%) | 4 (0.0%) | 120 (1.0%) | 12415 (98.9) | 12552 |
| 2019 | 6 (0.04%) | 3 (0.02%) | 47 (0.3%) | 14288 (99.6%) | 14284 |
| 51-70 | |||||
| 2015 | 38 (0.8%) | 27 (0.6%) | 313 (6.9%) | 4186 (91.7%) | 4564 |
| 2019 | 26 (0.4%) | 13 (0.2%) | 286 (4.5%) | 6095 (94.9%) | 6420 |
| >70 | |||||
| 2015 | 59 (5.0%) | 11 (0.9%) | 123 (10.5) | 979 (83.5%) | 1172 |
| 2019 | 35 (2.8%) | 7 (0.6%) | 107 (8.5%) | 1106 (88.1%) | 1255 |
| Age missing | |||||
| 2015 | 0 | 0 | 0 | 31 (100%) | 31 |
| 2019 | 0 | 0 | 3 | 0 | 3 |
| Head of Family | |||||
| 2015 | 51 (1.3%) | 12 (0.3%) | 151 (3.8%) | 3796 (94.7%) | 4010 |
| 2019 | 40 (1.1%) | 8 (0.2%) | 116 (3.0%) | 3643 (95.7%) | 3807 |
| Other Members | |||||
| 2015 | 67 (0.2%) | 31 (0.1%) | 428 (1.1%) | 39999 (98.7%) | 40525 |
| 2019 | 32 (0.1%) | 15 (0.0%) | 341 (0.9%) | 39513 (99.0) | 39901 |
The visual disability grades were significantly different in the cohort of 2015 compared to 2019, Chi-square=26.6, degree of freedom=3, P<0.001. The visual disability grades were significantly different among males (Chi square=14.7, degree of freedom=3, P=0.0001) and females (Chi square=13.3, degree of freedom=3, P=0.0003) when compared to 2015-2019. This variation of visual disability grade in two screening years was more among females compared to males
Visual acuity of examined individuals in 2015-16 and 2018-19 (as per worse eye)
| Parameters | <3/60 | 3/60-6/60 | 6/60-6/24 | ≥6/18 | Total |
|---|---|---|---|---|---|
| All | |||||
| 2015 | 322 (0.72%) | 47 (0.1%) | 744 (1.7%) | 43,421 (97.5%) | 44,534 |
| 2019 | 195 (0.44%) | 31 (0.07%) | 651 (1.49%) | 42,831 (97.99%) | 43,708 |
| | <0.001 | ||||
| Male | |||||
| 2015 | 130 (0.6%) | 187 (0.8%) | 138 (0.6%) | 21,732 (97.9%) | 22,187 |
| 2019 | 74 (0.3%) | 13 (0.1%) | 256 (1.2%) | 21,431 (98.4%) | 21,774 |
| Female | |||||
| 2015 | 192 (0.9%) | 262 (1.1%) | 204 (0.9%) | 21,689 (97%) | 22,347 |
| 2019 | 121 (0.6%) | 18 (0.1%) | 392 (1.8%) | 21,403 (97.6%) | 21,934 |
| Age | |||||
| <5 | |||||
| 2015 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 3825 (100%) | 3825 |
| 2019 | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 792 (100%) | 792 |
| 6-18 | |||||
| 2015 | 3 (0.0%) | 3 (0.0%) | 4 (0.0%) | 10,477 (99.9%) | 10,487 |
| 2019 | 5 (0.05%) | 0 (0.0%) | 3 (0.1%) | 9725 (99.9%) | 9728 |
| 19-30 | |||||
| 2015 | 8 (0.1%) | 9 (0.1%) | 9 (0.1%) | 11,878 (99.8%) | 11,904 |
| 2019 | 5 (0.04%) | 0 (0.0%) | 15 (0.1%) | 11,204 (99.8%) | 11,224 |
| 31-50 | |||||
| 2015 | 32 (0.3%) | 94 (0.7%) | 96 (0.8%) | 12,330 (98.2%) | 12,552 |
| 2019 | 10 (0.2%) | 6 (0.1%) | 82 (0.6%) | 14,187 (99.3%) | 14,285 |
| 51-70 | |||||
| 2015 | 165 (3.6%) | 245 (5.4%) | 187 (4.1%) | 3967 (86.9%) | 4564 |
| 2019 | 109 (1.7%) | 16 (0.2%) | 424 (6.6%) | 5871 (91.4%) | 6420 |
| >70 | |||||
| 2015 | 114 (9.7%) | 98 (8.4%) | 46 (3.9%) | 913 (78%) | 1171 |
| 2019 | 69 (5.5%) | 9 (0.8%) | 124 (9.9%) | 1052 (83.9%) | 1254 |
| Age missing | |||||
| 2015 | 0 | 0 | 0 | 31 (100%) | 31 |
| 2019 | 0 | 0 | 3 | 0 | 3 |
| Head of Family | |||||
| 2015 | 113 (2.8%) | 120 (2.9%) | 93 (2.3%) | 3683 (91.8%) | 4009 |
| 2019 | 77 (2.0%) | 6 (0.2%) | 175 (4.6%) | 3548 (93.2%) | 3806 |
| Other Members | |||||
| 2015 | 209 (0.5%) | 329 (0.8%) | 249 (0.61%) | 39,738 (98%) | 40,525 |
| 2019 | 118 (0.3%) | 25 (0.1%) | 473 (1.2%) | 39,286 (98.5%) | 39,902 |
There was a significant difference between 2015 and 2019 for the worse eye data (P<0.0001) and the change in males, females, age 51-70 and >70 years by the Wilcoxon signed-rank test
Causes of blindness (VA <3/60) in two-time point cohorts
| Causes | 2015-16 | 2018-19 |
|
|---|---|---|---|
| Phthisical Eye | 6 (5%) | 5 (6.9%) | 0.594 |
| Anophthalmos | 2 (2.5%) | 2 (2.8%) | 0.614 |
| Optic Atrophy | 3 (1.6%) | 2 (2.8%) | 0.922 |
| Cataract | 53 (44.9%) | 30 (41.6%) | 0.661 |
| Pseudophakia Refraction | 8 (6.8%) | 8 (11.11%) | 0.297 |
| Glaucoma | 11 (9.3%) | 8 (11.11%) | 0.69 |
| Diabetic Retinopathy | 2 (2.5%) | 2 (2.8%) | 0.614 |
| Refraction | 8 (6.8%) | 4 (5.6%) | 0.736 |
| Unknown | 13 (11%) | 4 (5.6%) | 0.201 |
| Corneal Causes | 9 (7.6%) | 7 (9.7%) | 0.614 |
| Nystagmus | 3 (1.6%) | 0.173 | |
| Total | 118 (100% | 72 (100%) |
P>0.05 (Not Significant) Chi-square test used
Causes of severe visual impairment (3/60-<6/60) in two-time point cohorts
| (VA 3/60-6/60) Causes | 2015-16 | 2018-19 |
|
|---|---|---|---|
| Cataract | 25 (58.1%) | 14 (60.9%) | 0.830 |
| Pseudophakia Refraction | 4 (9.3%) | 0 | 0.131 |
| Glaucoma | 3 (7%) | 2 (8.7%) | 0.801 |
| Diabetic Retinopathy | 2 (4.7%) | 1 (4.35%) | 0.955 |
| Refraction | 4 (9.3%) | 5 (21.7%) | 0.161 |
| Unknown | 1 (2.32%) | 0 | 0.461 |
| Corneal Causes | 6 (14%) | 0 | 0.060 |
| Microcornea with iris coloboma | 1 (2.32%) | 0 | 0.461 |
| Phthisical Eye | 0 | 1 (4.35%) | 0.168 |
| Total | 43 (100%) | 23 (100%) |
P>0.05 (Not Significant) Chi-square test used