There were approximately 510 million people globally with near vision impairment caused by uncorrected presbyopia in 2020,1,2 with the burden greatest in low-and-middle-income countries (LMICs), rural areas, and amongst women.1–3 The annual global cost of productivity losses associated with near vision impairment is estimated to be $25.367 billion.4 Though both near and distance refractive error are easily corrected with spectacles, rates of spectacle coverage in LMICs are as low as 10%.5 In Bangladesh, spectacle coverage is reported to be 25% with lower coverage among women (20.9%) and in rural areas (15.9%).6
Bangladesh is home to the second-largest readymade garment (RMG) industry in the world, following China.7 Garment production accounts for over 80% of Bangladesh's total export earnings8 and employs approximately 4 million workers, over half of whom are women.9 The nature of tasks involved in the production of garments, such as sewing and cutting, requires close viewing of the material and tools, making good near vision a requirement for garment workers.
Eye health organization Orbis Bangladesh, together with Nari Uddug Kendra (NUK), a nongovernmental national women's development support society, carried out free eye health screening and service delivery for female garment workers in Bangladesh in 2019. The current study reports the prevalence of near and correctable distance vision impairment among screened participants and explores associations with income, age, and urban versus rural residence.
METHODS
The Human Research Ethics Committee of the Asian Institute of Disability and Development (AIDD) provided review and approval for the study. Participants gave verbal consent before enrollment, and all data were analyzed in deidentified fashion. The study followed the tenets of the Declaration of Helsinki.
Setting and Participants
Eye health screenings and service delivery were performed at 4 garment factories during September and October 2019. These included 2 urban factories in Dhaka (Shanin Clothing Ltd and Mac-Tex Industries Ltd), and 2 rural factories located near Mymensingh (Targeted Garments Ltd 1, and Targeted Garments Ltd 2).
The eye health screenings and service delivery included women working in a variety of job categories. Dates were scheduled in consultation with factory owners and participants were recruited based on their availability to attend on the selected days and their consent to participate in the study. Training for future screenings, outside of the study, was provided to mid-level management and nursing staff at the factories so that all workers would eventually have the opportunity to attend an eye health screening.
Vision Screening and Ocular Examination
The eye health screening and service delivery teams each consisted of 1 ophthalmologist, 1 refractionist, 2 ophthalmic assistants, 1 counselor, 2 data recorders, 1 spectacle dispenser, and 1 coordinator. Ocular examinations were carried out according to a standard screening protocol and included:
- 1. Patient registration
- 2. Assessment of correctable distance visual acuity separately in each eye using an ocular occluder and Snellen Tumbling E chart at a distance of 3 m in a well-lighted indoor area of the factory
- 3. Near vision testing with both eyes together using an N-type handheld chart at a distance of 40 cm
- 4. Examination of the anterior segment by handlight and the posterior pole by direct ophthalmoscopy, both performed by an ophthalmologist
- 5. Distance refraction by a trained refractionist where presenting distance visual acuity was <6/12 in at least 1 eye, and near refraction was performed if near vision was N8 or worse.1,10
- 6. Free medications (predominantly topical ocular antibiotics, antiallergy drops and artificial tears) were dispensed as needed. Free presbyopic and myopic spectacles were provided to all those whose vision improved with refraction.
- 7. Dilation of the pupil in cases of suspected cataract (based on handlight examination), after which a medical officer performed a torchlight examination of the anterior segment and direct ophthalmoscopy to confirm the diagnosis.
- 8. Those identified needing further investigation or surgical intervention for cataract or epiphora were referred to the National Institute of Ophthalmology and Hospital (NIO&H) for treatment.
Data Collection and Management
A questionnaire was administered to all participants, inquiring about age, marital and educational status, income, job designation and years of seniority, daily hours worked, district of residence, spectacle ownership, and vision complaints. Presenting distance visual acuity as assessed by an ophthalmic assistant, distance refractive power as measured by refractionists using streak retinoscopy, presenting near visual acuity, near refraction tested by using plus lenses, and ocular conditions diagnosed during the examination were recorded separately for each eye.
Patient demographic, clinical, and questionnaire data were entered into Microsoft Excel 365 (Redmond, WA, US) by a trained data entry specialist. A password-protected administrative database containing all respondent contact details and managed by the Orbis Bangladesh office was used for contact purposes and oversight of the data collection process. Paper records of contact sheets, registration documents, questionnaires, and other forms were archived under lock and key. All data for research analysis were provided to the study statistician (JLP) in deidentified format.
Statistical Methods
Data were downloaded from Microsoft Excel 365 and imported into SAS version 9.4 (Cary, NC, US) for statistical analysis. Distance vision impairment was the presence of uncorrected vision of <6/12 in either eye, correctable to ≥6/7.5 with distance refraction. Distance refractive error was defined according to recorded clinical diagnosis during the examination and included myopia, hyperopia, and/or astigmatism. Near vision impairment was defined as 1 or more of the following: 1) either eye with presenting near vision <N8 at 40 cm with distance visual acuity >6/12 in the same eye; 2) having been prescribed near add spectacle power in examination records; and/or 3) clinical diagnosis of presbyopia at the time of screening. Monthly income was self-reported via the survey and converted to US dollars by dividing reported Taka by 83.2.11
Basic frequencies are presented for categorical variables, and means, standard deviations (SD), and medians are given for age and monthly income. Chi-square tests were utilized to compare urban and rural residents with regard to presenting correctable distance visual acuity, distance spherical equivalent refractive power in the better-seeing eye, and near vision impairment. Statistical testing was performed on the entire cohort and stratified by age category (<25, 25–29, 30–34, 35–39, and 40+ years). Univariate and multivariable linear regression was utilized to assess predictors of monthly income, and parameter estimates (β), standard errors (SE), and P values are presented for each. The final multivariate model applied backward stepwise selection to include variables contributing to the model at P < 0.10. A sensitivity analysis was performed that included only participants who worked in the operators/sewing section since this job type likely requires near vision activities the most. Similar methods were utilized for univariate and multivariable linear regression models with monthly income as the primary outcome.
RESULTS
A total of 915 participants (100% female) with mean age of 29.8 (SD 8.25 years) were screened. Participants reported a mean monthly income of $96.90, two-thirds (n = 609, 66.6%) had a primary school or lower education, and most (80.9%, n = 740) were married. Workers had a mean of 5.04 (SD 4.16) years of seniority in their current jobs and worked for a mean of 10.8 hours/day. A small percentage (9.29%, n = 85) of workers owned spectacles at the time of the survey, and one-quarter (28.5%, n = 261) reported symptoms of asthenopia (Table 1).
Table 1 -
Demographic and Professional Characteristics and Baseline Ownership of Spectacles Among Garment Workers Participating in the Study
|
All Study Participants |
| Female, n (%) |
915 (100%) |
| Age, y |
| Mean (SD) |
29.8 (8.25) |
| Median (IQR) |
30.0 (24.0–35.0) |
| Range |
18–70 |
| Age 35 and older |
297 (32.5%) |
| Married, n (%) |
740 (80.9%) |
| Educational status |
| No education |
150 (16.4%) |
| Nongraded religious education |
41 (4.48%) |
| Primary school only |
418 (45.7%) |
| Secondary school |
287 (31.4%) |
| Higher secondary/Masters |
19 (2.08%) |
| Monthly income (US$∗) (n = 905) |
| Mean (SD) |
97.1 (33.1) |
| Median (IQR) |
96.4 (72.3–118) |
| Range |
12.0–301 |
| Job designation |
| Helper |
91 (9.95%) |
| Quality control |
72 (7.87%) |
| Operator/Sewing section |
626 (68.4%) |
| Cleaner |
42 (4.59%) |
| Folding woman |
78 (8.52%) |
| Unknown |
6 (0.66%) |
| No. y on the job (n = 910) |
| Mean (SD) |
5.04 (4.16) |
| Median (IQR) |
4.00 (2.00–8.00) |
| Range |
0–25.0 |
| Daily time working, hr (n = 913) |
| Mean (SD) |
10.8 (2.10) |
| Median (IQR) |
12.0 (8.00–12.0) |
| Range |
7.00–18.0 |
| District of residence |
| Urban |
447 (48.9%) |
| Rural |
468 (51.2%) |
| Baseline ownership of spectacles |
85 (9.29%) |
| Self-reporting symptoms of asthenopia |
261 (28.5%) |
∗1 US$ = Taka 83.0 on October 31, 2019.IQR indicates interquartile range; n, number of study participants; SD, standard deviation.
Correctable distance refractive error, defined by the presence of myopia, hyperopia, or astigmatism, was present in 29.2% (n = 267) of workers undergoing eye health screenings, with a similar prevalence among urban participants (30.4%, n = 136) compared to rural dwellers (28.0%, n = 131). Rural participants in the 40+ age group had significantly better presenting correctable distance visual acuity compared to their urban counterparts (P = 0.0132) (Table 2).
Table 2 -
Presenting Correctable Distance Visual Acuity in the Better-Seeing Eye Among Urban and Rural Residents
|
|
Urban |
Rural |
| Age Group |
Total |
= 6/6 |
6/9–6/12 |
6/18–6/60 |
= 6/6 |
6/9–6/12 |
6/18–6/60 |
| <25 |
249 |
106 (98.2%) |
0 (0%) |
2 (1.85%) |
137 (97.2%) |
1 (0.71%) |
3 (2.13%) |
| 25–29 |
197 |
110 (94.0%) |
7 (5.98%) |
0 (0%) |
72 (90.0%) |
6 (7.50%) |
2 (2.50%) |
| 30–34 |
172 |
89 (90.8%) |
7 (7.14%) |
2 (2.04%) |
70 (94.6%) |
3 (4.05%) |
1 (1.35%) |
| 35–39 |
165 |
68 (88.3%) |
7 (9.09%) |
2 (2.60%) |
85 (96.6%) |
3 (3.41%) |
0 (0%) |
| 40+∗
|
132 |
37 (78.7%) |
3 (6.38%) |
7 (14.9%) |
71 (83.5%) |
12 (14.1%) |
2 (2.35%) |
| Total |
915 |
410 (91.7%) |
24 (5.37%) |
13 (2.91%) |
435 (92.9%) |
25 (5.34%) |
8 (1.71%) |
∗Urban and rural significantly different in distribution of presenting correctable distance visual acuity (P = 0.0132, chi-square test) for this age group.
Just over one-quarter of screened participants (n = 245, 26.8%) had near vision impairment. Of the 245 participants with near vision impairment (near visual acuity <N8, Snellen equivalent 6/12, in either eye), 30.6% (n = 75) had near visual acuity <N10 in either eye (Snellen equivalent 6/18). Prevalence of near vision impairment was significantly higher among rural residents (34.2%) compared to urban overall (19.0%, P < 0.0001) with the largest differences occurring in the 35 to 39 (68.2% vs 44.2%, P = 0.002) and 40+ (85.9% vs 48.9%, P < 0.0001) year age groups (Fig. 1). Prevalence of near vision impairment was already high among urban (20.4%, n = 20) and rural (23.0%, n = 17) workers at young ages (30 to 34 years).
;)
Figure 1: Prevalence of near vision impairment by urban/rural residence and age group.
In simple linear regression models, participants with near vision impairment earned $13.3 (SE 2.44, P < 0.0001) less per month than those without, while urban residents earned $40.6 (SE 1.74, P < 0.0001) more than rural ones (Table 3). In the final multivariable linear model, both near vision impairment ($6.51 lower monthly earnings, SE 1.84, P = 0.0004) and urban residence ($43.2 higher monthly earnings, SE 2.39, P < 0.0001) remained significantly associated with income (Table 3). The sensitivity analysis that included only females in the operator/sewing section job type had similar univariate and multivariable findings for near vision impairment and urban/rural residence. Correctable distance visual impairment was not significantly associated with earnings.
Table 3 -
Univariate and Multivariate Regression Models of Potential Predictors of Monthly Salary (US$, n = 905)
|
Univariate |
Multivariate |
| Potential Predictor |
β (SE) |
P value |
β (SE) |
P value |
| Near vision impairment |
−13.3 (2.44) |
<0.0001 |
−6.51 (1.84) |
0.0004 |
| Age, y |
−0.238 (0.133) |
0.074 |
– |
|
| Time on the job, y |
3.35 (0.240) |
<0.0001 |
2.21 (0.195) |
<0.0001 |
| Daily time working, h (n = 903) |
−5.56 (0.488) |
<0.0001 |
2.54 (0.551) |
<0.0001 |
| Married, n (%) |
−1.59 (2.79) |
0.568 |
– |
|
| Educational status |
| No education |
Reference |
– |
Reference |
– |
| Non-graded religious education |
17.0 (5.86) |
0.004 |
−4.43 (4.30) |
0.304 |
| Primary school only |
13.1 (3.12) |
<0.0001 |
1.49 (2.33) |
0.520 |
| Secondary school |
14.4 (3.30) |
<0.0001 |
4.70 (2.48) |
0.058 |
| Higher secondary/Masters |
36.4 (7.93) |
<0.0001 |
24.1 (5.78) |
<0.0001 |
| Job designation |
| Helper |
Reference |
– |
Reference |
– |
| Quality control |
28.6 (4.92) |
<0.0001 |
18.0 (3.63) |
<0.0001 |
| Operator/Sewing section |
31.8 (3.44) |
<0.0001 |
16.7 (2.58) |
<0.0001 |
| Cleaner |
35.9 (5.87) |
<0.0001 |
13.8 (4.39) |
0.002 |
| Folding woman |
37.4 (4.79) |
<0.0001 |
9.06 (3.62) |
0.0126 |
| Urban residence |
40.6 (1.74) |
<0.0001 |
43.2 (2.39) |
<0.0001 |
| Baseline ownership of spectacles |
14.5 (3.74) |
0.0001 |
– |
|
SE indicates standard error.
DISCUSSION
This study found high rates of near vision impairment among garment workers, particularly rural study participants. We observed a near vision impairment prevalence of 20% to 23% between the ages of 30 and 34 years, which is consistent with other studies documenting the loss of accommodative reserve before age 40.12,13 This was presumably due to the existing high prevalence of hyperopia in this cohort, consistent with the observed higher prevalence of near vision impairment in rural workers; hyperopia has commonly been seen at higher rates in rural populations,14–17 due to lack of educational exposure.18,19 The presence of near vision impairment was also associated with lower monthly salary, even after adjusting for potential confounding variables such as years on the job, daily working hours, education, job type, and rural versus urban residence. Inexpensive treatment with near glasses, proven effective in the long term,20–22 could increase earnings by some $70 per year, a difference by itself sufficient to guarantee 6 weeks of income above the World Bank's poverty line.23 Workplace screening and provision of near glasses similar to this program could serve as a scalable poverty reduction strategy in service of the United Nations Sustainable Development Goal 1—to end poverty in all its forms everywhere.24
While this study did not include productivity measures, the decrease in salary for participants with near vision impairment may have been due to vision-related reduction in quality and/or output among these garment workers, as recruitment and salary increases are tied to productivity tests and annual adjustments based on performance. Improving near vision with spectacle correction has been shown to increase productivity among textile workers25 and in other sectors, such as agriculture, that depend on good near vision.20 Of the 245 participants with near vision impairment (near visual acuity <N8, Snellen equivalent 6/12, in either eye), 30.6% (n = 75) had near visual acuity <N10 in either eye (Snellen equivalent 6/18). The degree of near vision impairment present in this cohort was thus modest, consistent with other assessments showing the impact of near vision impairment in the workplace, for example in the PROSPER trial on presbyopic Indian tea pickers,20 less than 20% of participants (who had to have near visual acuity <N8 in both eyes) had near visual acuity <N10. It would appear that even modest degrees of near vision impairment can negatively impact workplace productivity. In view of the very significant global productivity losses associated with near vision impairment among persons of working age,4 and the observed high burden among younger workers with many remaining years in the workplace, the financial benefits of near vision correction for this population could be significant. Both workers and factories could benefit from increased productivity, with a synergistic impact on economic growth.
This study included only female garment workers, who constitute the majority of workers in the industry. Women often require near vision correction at an earlier age than men,26–28 presumably due to reduced access to education compared to men and higher prevalence of hyperopia. This may have contributed to the high prevalence of near vision impairment in this study. Globally, women carry a larger burden of vision impairment than men,2 and women living in LMICs make a significant contribution to the economy in rural settings,29 where we found a higher prevalence of near vision impairment. Therefore, focusing on industries with a high proportion of female workers, such as readymade garments, may be effective in addressing gender disparities in vision impairment and its economic impact.
As previously mentioned, limitations of the study include the lack of productivity measures before and after correction of near vision impairment. More trials on the impact of spectacle correction on productivity in textiles and other vision-intensive sectors are needed, to broaden the evidence base for action. Strengths of the study include presentation of data from both urban and rural locations, the large sample size, and the focus on LMICs, whose populations account for 90% of uncorrected near vision impairment globally,1,2 and where the need for practical poverty alleviation strategies is especially acute.
CONCLUSIONS
This study found high rates of near vision impairment among female garment workers in Bangladesh, particularly rural dwellers, and at a younger age than expected. Further, the presence of near vision impairment was associated with significantly decreased income, even after adjusting for a variety of potential confounders. This study suggests that focusing on industries with a high proportion of female workers, such as readymade garments, may be effective in addressing gender disparities in vision impairment, its economic impact, and as a potential poverty alleviation strategy in this setting. Additional studies, and especially trials, addressing near vision impairment in the garment industry would be beneficial in increasing understanding, and quantifying the potential economic impact.
ACKNOWLEDGEMENTS
We would like to acknowledge and thank the following persons and institutions: Md. Iqbal Hossain, Senior Program Manager, Orbis International Bangladesh, for program implementation, supervision, and monitoring; Mohammad Shamsal Islam, for coordinating the field team for data collection and data entry; Asian Institute of Disability and Development (AIDD) for ethical approval; Nari Uddug Kendra (NUK) for organizing of screening camps, ocular examinations, and facilitating in data collection; Shanin Clothing Ltd, MAC-Tex Industries Ltd, Target Garments Ltd. Unit 1, and Target Garments Ltd. Unit 2 for partnering with us to screen their employees; Global Giving for funding the programmatic initiatives.
REFERENCES
1. GBD 2019 Blindness and Vision Impairment Collaborators, on behalf of the Vision Loss Expert Group of the Global Burden of Disease Study (VLEG-GBD). Trends in prevalence of blindness and distance and near vision impairment over 30 years: an analysis for the Global Burden of Disease Study.
Lancet Glob Health 2021; 9:e130–e143.
2. Burton MJ, Ramke J, Marques AP, et al. The Lancet Global Health Commission on Global Eye Health: vision beyond 2020.
Lancet Glob Health 2021; 9:e489–e551. doi: 10.1016/S2214-109X(20)30488-5.
3. Fricke TR, Tahhan N, Resnikoff S, et al. Global prevalence of presbyopia and vision impairment from uncorrected presbyopia: systematic review, meta-analysis, and modelling.
Ophthalmology 2018; 125:1492–1499. doi: 10.1016/j.ophtha.2018.04.013.
4. Frick KD, Joy SM, Wilson DA, et al. The global burden of potential productivity loss from uncorrected presbyopia.
Ophthalmology 2015; 122:1706–1710. doi: 10.1016/j.ophtha.2015.04.014.
5. Chan VF, MacKenzie GE, Kassalow J, et al. Impact of presbyopia and its correction in low- and middle-income countries.
Asia Pac J Ophthalmol (Phila) 2018; 7:370–374. doi: 10.22608/APO.2018449.
6. Bourne RRA, Dineen BP, Noorul Huq DM, et al. Correction of refractive error in the adult population of bangladesh: meeting the unmet need.
Invest Ophthalmol Vis Sci 2004; 45:410–417.
8. The Bangladesh Garment Manufacturers and Exporters Association (BGMEA). Comparative statement on export of RMG and total export of Bangladesh. 2020.; Dhaka, Bangladesh: BGMEA,
https://www.bgmea.com.bd/page/Export_Performancehttps://www.bgmea.com.bd/page/Export_Performance. Accessed May 6, 2021.
9. International Labour Organization (ILO). Improving working conditions in the ready-made garment industry: Progress and achievements. 2016; Geneva: International Labour Organization,
https://www.ilo.org/dhaka/Whatwedo/Projects/WCMS_240343/lang--en/index.htmhttps://www.ilo.org/dhaka/Whatwedo/Projects/WCMS_240343/lang--en/index.htm. Accessed March 3, 2021.
10. Holden BA, Fricke TR, Ho SM, et al. Global vision impairment due to uncorrected presbyopia.
Arch Ophthalmol 2008; 126:1731–1739. doi: 10.1001/archopht.126.12.1731.
11. OANDA Corporation. Currency Converter. Currency Converter: Bangladeshi Taka to US Dollar.
https://www1.oanda.com/currency/converter/. Accessed November 22, 2021.
12. Win-Hall DM, Glasser A. Objective accommodation measurements in prepresbyopic eyes using an autorefractor and an aberrometer.
J Cataract Refract Surg 2008; 34:774–784. doi: 10.1016/j.jcrs.2007.12.033.
13. Anderson HA, Stuebing KK. Subjective versus objective accommodative amplitude: preschool to presbyopia.
Optom Vis Sci 2014; 91:1290–1301. doi: 10.1097/OPX.0000000000000402.
14. Dandona R, Dandona L, Srinivas M, et al. Refractive error in children in a rural population in India.
Invest Ophthalmol Vis Sci 2002; 43:615–622.
15. Murthy GVS, Gupta SK, Ellwein LB, et al. Refractive error in children in an urban population in New Delhi.
Invest Ophthalmol Vis Sci 2002; 43:623–631.
16. He M, Zeng J, Liu Y, et al. Refractive error and visual impairment in urban children in southern China.
Invest Ophthalmol Vis Sci 2004; 45:793–799.
17. He M, Huang W, Zheng Y, et al. Refractive error and visual impairment in school children in rural southern China.
Ophthalmology 2007; 114:374–382. doi: 10.1016/j.ophtha.2006.08.020.
18. Morgan IG, Ohno-Matsui K, Saw SM. Myopia.
Lancet 2012; 379:1739–1748. doi: 10.1016/S0140-6736(12)60272-4.
19. UN Women. Commission on the status of women 2012: Facts and figures.
https://www.unwomen.org/en/news/in-focus/commission-on-the-status-of-women-2012/facts-and-figures. Accessed October 8, 2021.
20. Reddy PA, Congdon N, MacKenzie G, et al. Effect of providing near glasses on productivity among rural Indian tea workers with presbyopia (PROSPER): a randomised trial.
Lancet Glob Health 2018; 6:e1019–e1027. doi: 10.1016/S2214-109X(18)30329-2.
21. Ramke J, du Toit R, Palagyi A, et al. Correction of refractive error and presbyopia in Timor-Leste.
Br J Ophthalmol 2007; 91:860–866. doi: 10.1136/bjo.2006.110502.
22. Laviers HR, Omar F, Jecha H, et al. Presbyopic spectacle coverage, willingness to pay for near correction, and the impact of correcting uncorrected presbyopia in adults in Zanzibar, East Africa.
Invest Ophthalmol Vis Sci 2010; 51:1234–1241. doi: 10.1167/iovs.08-3154.
24. UN General Assembly. Transforming our world: the 2030 Agenda for Sustainable Development. New York, US: United Nations, 2021.
https://sdgs.un.org/2030agenda. Accessed November 22, 2021.
25. Naidoo K, Jaggernath J, Chinanayi F, et al. Near vision correction and work productivity among textile workers.
Afr Vision Eye Health 2016; 75:a357doi: 10.4102/aveh.v75i1.357.
26. Burke AG, Patel I, Munoz B, et al. Population-based study of presbyopia in rural Tanzania.
Ophthalmology 2006; 113:723–727.
27. Umar MM, Muhammad N, Alhassan MB. Prevalence of presbyopia and spectacle correction coverage in a rural population of North West Nigeria.
Clin Ophthalmol 2015; 9:1195–1201.
28. Hashemi H, Khabazkhoob M, Jafarzadehpur E, et al. Population-based study of presbyopia in Shahroud, Iran.
Clin Exp Ophthalmol 2012; 40:863–868. doi: 10.1111/j.1442-9071.2012.02799.x.
29. Inter-Agency Task Force on Rural Women. Facts and figures: Rural women and the millenium development goals. 2012; Geneva Switzerland: United Nations,
https://www.un.org/womenwatch/feature/ruralwomen/facts-figures.htmlhttps://www.un.org/womenwatch/feature/ruralwomen/facts-figures.html. Accessed March 17, 2021.
