Abstract
Background
Uncorrected refractive errors (URE) and presbyopia are leading causes of visual impairment (VI) globally. Bhutan currently lacks population-based data on adult refractive error, hindering efforts to meet WHO’s 2030 targets for effective refractive error coverage (eREC).
Aim
To estimate the prevalence of URE, presbyopia, spectacle use, and eREC among individuals aged 18 to 49 years in Bhutan.
Methods
A population-based cross-sectional survey using the Rapid Assessment of Refractive Error (RARE) methodology was conducted in Bhutan across 61 clusters in 19 districts. Participants aged 18 to 49 were recruited via multistage random sampling. Distance visual acuity (VA) was measured unaided, with current correction, and with pinhole using a LogMAR chart at 4 m. Near VA was assessed at 40 cm with an N- notation chart. Prevalence estimates were age- and sex-standardized to the 2017 Bhutan national census data. The REC, eREC and relative quality gap were calculated per WHO definitions.
Results
From a pool of 3,660 eligible participants, 3,523 (96.3%) were examined. The age- and sex-adjusted prevalence of distance VI was 11.0% (95% CI: 10.0–12.0), and refractive error affected 9.95% (95% CI: 8.9-10.98). The adjusted URE prevalence was 2.44% (95% CI: 1.84–3.04), higher in females (p = 0.04). Individuals with monastic education (OR: 7.65) and unemployed individuals/housewives (OR: 4.44) had higher URE odds (p = 0.01, for both). Among those aged 35 or older (n = 1423), adjusted prevalence of uncorrected presbyopia was 30.5% (95% CI: 28.3–32.8%); higher in males and older age groups (45–49 years) (p < 0.05, for both). Distance eREC was 74.1% (95% CI: 71.2–77.0), significantly lower in females (67.7%) than males (79.9%) (p < 0.001), and near eREC was 31.3% (95% CI: 29.8–34.6). The relative quality gap for distance and near was 10.9% and 2.8%, respectively. Spectacle use was 23.5%, higher in females (25.3%, p = 0.01).
Conclusion
URE prevalence in Bhutan is low, but gaps remain in near vision correction, gender equity in eye care access, and quality of service. Strengthening near-vision services, enhancing public-private optical partnership, and implementing gender-responsive strategies for service delivery are essential to achieve WHO’s 2030 eREC targets.
Keywords: Bhutan, Eye health, Epidemiology, Gender disparity, Presbyopia, Rapid assessment, Refractive errors, Visual impairment
Introduction
Uncorrected refractive errors (UREs), including presbyopia, remain the leading cause of vision impairment (VI) globally, with the burden disproportionately affecting low- and middle-income countries (LMICs), where access to basic eye care services is limited. The Global Burden of Disease Study 2019 estimated that 3.7 million individuals were blind and that 157 million had moderate to severe visual impairment (MSVI) due to URE [1, 2]. These estimates reflect a growing public health concern, with an observed increase of 21.8% in blindness and 72.0% in MSVI due to URE since 2000 [2]. Furthermore, in 2015, approximately 1.8 billion people, constituting approximately 25% of the global population, were estimated to be affected by presbyopia, with 826 million experiencing near VI due to a lack of, or inadequate, vision correction [3].
Presbyopia, despite its near-universal prevalence with advancing age, has historically received limited attention in both scientific research and healthcare service delivery. Recent reviews have revealed that fewer than one-third of individuals with presbyopia in LMICs have access to effective optical correction [3]. The impact of uncorrected presbyopia extends beyond diminished visual function and quality of life, contributing to decreased economic productivity and increased occupational and daily living safety risks [4, 5].
URE is readily treatable through simple, low-cost interventions such as the provision of spectacles. Despite this, URE continues to be a leading cause of avoidable VI, particularly in LMICs [6]. In recognition of the critical importance of addressing URE to advance universal eye health, the 74th World Health Assembly (WHA) in 2021 set an ambitious global target to achieve a 40 percentage-point increase in effective refractive error coverage (eREC) by 2030. Despite growing attention to refractive error worldwide, service coverage and access remain limited in many LMICs, particularly among working-age populations [7].
Bhutan has a publicly funded health care system and has made notable advancements in health outcomes over recent decades. Eye health, including refractive error (RE) services, is incorporated within the primary health care framework and receives dedicated attention through the country’s national eye care programme [8]. Despite these efforts, Bhutan currently lacks a dedicated policy or strategic framework aligned to achieve the 2030 eREC targets.
Previous surveys in Bhutan have focused primarily on two distinct age cohorts: individuals aged 50 years and older, using the Rapid Assessment of Avoidable Blindness (RAAB) methodology, and school-aged children (5 to18 years), using the Refractive Error in School Children (RESC) study [9, 10]. However, there is a lack of population-based data on RE among individuals aged 18 to 49 years. These economically productive age groups frequently encounter significant barriers to eye care and present high levels of unmet needs [11]. The increasing prevalence of myopia among adolescents and middle-aged adults is attributable to factors such as urbanization, prolonged education, and increased digital screen exposure, further underscoring the urgency of addressing these data and the service gap [12].
This data gap hinders a comprehensive understanding of the national burden of RE within the working-age population. To address this limitation, the present study utilized the Rapid Assessment of Refractive Error (RARE) methodology. RARE is a cost-effective, standardized, and scientifically robust survey technique that has been extensively implemented in other LMICs [13] to generate reliable baseline data on RE prevalence and service coverage.
This study aimed to estimate the prevalence of distance RE and presbyopia, identify associated demographic determinants, and assess eREC and quality gaps among individuals aged 18 to 49 years in Bhutan. The findings from this RARE survey are expected to inform national eye health strategies and refractive service delivery models, in alignment with the WHO’s Integrated People-Centred Eye Care (IPEC) framework and the SPECS 2030 targets [14, 15]. Furthermore, the findings will serve as a baseline for establishing national targets for achieving the WHO 2030 goals for eREC.
Methodology
Study design and setting
This population-based cross-sectional study employed the RARE methodology. The RARE survey is an internationally validated methodology that has been implemented in several LMICs to generate data on VI due to URE and presbyopia [16–19]. The survey was conducted between June and October 2024 across 61 clusters spanning 19 of the 20 Dzongkhags (districts) in Bhutan.
Study population
In each selected cluster, all individuals aged 18 to 49 years who had resided in the household for a minimum of six months within the preceding 12 months were enumerated. Eligible participants were those capable of providing informed consent and completing standard ophthalmic examination procedures. Individuals who were unable to communicate due to physical or mental health conditions or who declined participation were excluded.
Sample size
The Population and Housing Census of Bhutan (PHCB 2017), estimated that the population aged 18 to 49 years was approximately 379,843 individuals. In the absence of empirical prevalence data for VI within this age group, the sample size was determined using an assumed prevalence of 5% for VI defined as presenting visual acuity (VA) of less than 6/12. The calculation incorporated a relative precision of 20% and a 95% confidence level. To account for the study design, a design effect of 1.6 was applied. Additionally, an allowance of 20% was included to mitigate the impact of potential non-responses. These parameters yielded a final required sample size of 3,650 participants to be selected from 61 clusters, each comprising 60 individuals.
Sampling method
To ensure the representativeness of the study population, a multistage stratified random sampling method was employed. The sampling frame was derived from the Bhutan Living Standard Survey, which was constructed by the National Statistical Bureau (NSB). In the first stage, primary sampling units were defined as clusters, comprising 1044 chiwogs (the smallest electoral/village-cluster administrative unit within a sub-district) and 1529 enumeration areas within thromdes (urban municipalities). A total of 61 clusters were randomly selected using a probability proportional to size, based on the data from the 2017 PHCB. Each selected cluster had an estimated population ranging from 250 to 500 individuals. The final sample included representatives from 19 out of Bhutan’s 20 administrative districts.
In each selected cluster, households were randomly sampled. Within each selected household, all eligible individuals aged 18 to 49 years were invited to participate in the study. Data collection commenced from a randomly selected household, after which subsequent households were chosen sequentially in a predetermined direction until a target of 60 eligible participants per cluster was achieved. In instances where a household was locked, neighbours were consulted to determine whether any eligible individuals resided there. If eligible residents were identified, up to two follow-up visits were identified, and up to two follow-up visits were conducted to enrol them. If participants remained unavailable after two attempts, the household was excluded, and the individuals were recorded as unavailable.
Training and quality assurance
Three field teams were constituted for the study, each consisting of an optometrist, an experienced ophthalmic technician, and a general graduate assistant. Prior to the commencement of data collection, all team members participated in a two-day intensive training and pilot exercise, which covered standardized distance VA testing, near vision assessment, spectacle use evaluation, informed consent procedures, and structured data collection protocols. Interobserver reliability for VA measurements was high, with a kappa coefficient exceeding 0.7, indicating a good agreement. Fieldwork commenced immediately following the training. The principal investigator provided daily oversight, including random quality assurance checks, to ensure strict adherence to the study protocols and data integrity.
Examination procedures
Each participant underwent a comprehensive eye examination in accordance with the RARE protocol. Distance presenting VA was initially assessed via an illuminated LogMAR E chart positioned at a distance of four metres under ambient lighting conditions. Participants presenting with a VA worse than 6/12 in either eye were subsequently evaluated via pinhole testing to determine the presence of correctable RE. Near vision was assessed in participants aged 35 years and older via a standard N-notation near vision chart held at a working distance of 40 centimetres. Individuals with a distance VA better than 6/12 but near VA worse than N8, who showed improvement to N8 or better with ready-made reading spectacles, were provided with free spectacles. These spectacles were provided through external donations and distributed with the approval of the Head of Ophthalmology at the National Eye Center, Bhutan.
A brief, structured interview was administered to collect demographic data, including education attainment, occupational status, current spectacle use, reasons for nonuse of spectacles, and the source from which spectacles were obtained. Participants presenting with a VA < 6/12 in the better-seeing eye were referred to the nearest eye facility for refractive assessment.
Operational definitions
Distance visual impairment (VI) was operationally defined as presenting visual acuity (PVA) worse than 6/12 in the better-seeing eye. Refractive error (RE) was defined as an uncorrected visual acuity (UCVA) worse than 6/12 that improved to 6/12 or better with pinhole correction. Uncorrected refractive error (URE) was similarly defined as a distance PVA worse than 6/12 that improved to 6/12 or better with pinhole correction. Among participants aged over 35 years, presbyopia was defined as binocular near PVA worse than N8 at a working distance of 40 cm in the presence of binocular distance PVA of 6/12 or better. These definitions have been applied in other population-based RARE studies and published elsewhere [16–19].
The operational definitions for refractive error correction status were based on WHO definitions [20] as follows:
Met need: For distance, it referred to individuals with UCVA worse than 6/12 in the better eye, which improved to 6/12 or better with their current spectacles or contact lens (corrected RE). For near, it referred to individuals with UCVA worse than N6 at 40 cm in the better eye, who present with spectacles for near vision and whose PVA is equal to or better than N6 in the better eye.
Undermet need: For distance, it referred to individuals with UCVA worse than 6/12 in the better eye who present with spectacles or contact lenses for distance vision and a PVA of worse than 6/12 in the better eye, but who improve to equal to or better than 6/12 on pinhole (inadequately corrected RE). For near, it referred to individuals with distance BCVA that is equal to or better than 6/12 in at least one eye, who present with spectacles for near vision and whose PVA is worse than N6 in the better eye.
Unmet need: For distance, it referred to individuals with UCVA worse than 6/12 in the better eye who do not have distance vision correction and who improve to equal to or better than 6/12 on pinhole (uncorrected RE). For near, it referred to individuals with distance BCVA that is equal to or better than 6/12 in at least one eye, who do not have correction for near vision and whose UCVA is worse than N6 in the better eye.
The ‘total need’ was calculated as the sum of individuals with met, unmet, and undermet needs.
REC, eREC and relative quality gap, for both distance and near, were calculated using WHO definitions [21].
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Relative quality gap (%) = 1- (eREC/REC) × 100. This is the relative quality gap between REC (%) and eREC (%).
Data management and statistical analysis
Data collection was conducted electronically using mobile phones. To minimize transcription errors, the data capture system incorporated real-time validation through built-in logic checks, automated skip patterns, and standardized dropdown menus. The principal investigator conducted daily field-based quality assurance reviews to verify the completeness and accuracy of the collected data. Upon completion of data collection, all records were securely exported to a centralized database and subsequently analysed using IBM SPSS, version 26.0.
Descriptive statistics were used to summarize the demographic characteristics of the study population. Differences in demographic distributions (region, qualification, and occupation) by gender were assessed using chi-square tests for categorical variables and t-tests for continuous variables. Age- and sex-standardized prevalence rates for RE and presbyopia were estimated using the direct standardization method, with the 2017 Bhutan national census population as the reference. The prevalence of VI between genders was compared using chi-square tests. Associations between RE, presbyopia, and selected independent variables (age, gender, education level, geographic region, and occupation) were assessed using multiple logistic regression analysis. Adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated. Statistical significance was determined at a threshold of p < 0.05.
Results
The study enumerated a total of 3,660 individuals aged 18 to 49 years from 61 clusters, encompassing 19 of the 20 Dzongkhags (districts) in Bhutan. Among those individuals, 92 (2.5%) were unavailable on the day of examination, 16 (0.4%) were unable to communicate due to physical or mental impairments, and 29 (0.8%) declined to participate in the eye examination. Consequently, 3,523 participants were successfully examined, yielding a response rate of 96.3%. A statistically significant difference was observed between the study sample and the national census population with respect to age and sex distribution (χ²= 115.4, df = 7, p < 0.01), as shown in Table 1. To address this discrepancy, prevalence estimates were adjusted for age and sex.
Table 1.
Distribution of the sample and the census population by age and gender
| Age Group | Male Sample n (%) |
Male Census n (%) |
Female Sample n (%) |
Female Census n (%) |
Total Sample n (%) |
Total Census n (%) |
|---|---|---|---|---|---|---|
| 18–24 | 378 (20.7) | 54,906 (27.0) | 362 (21.3) | 47,900 (27.2) | 740 (21.0) | 102,806 (27.1) |
| 25–34 | 681 (37.3) | 77,861 (38.3) | 646 (38.1) | 66,599 (37.8) | 1,327 (37.7) | 144,460 (38.0) |
| 35–44 | 525 (28.7) | 51,963 (25.5) | 469 (27.6) | 45,081 (25.6) | 994 (28.2) | 97,044 (25.6) |
| 45–49 | 242 (13.3) | 18,865 (9.3) | 220 (13.0) | 16,668 (9.5) | 462 (13.1) | 35,533 (9.4) |
| Total | 1,826 (51.9) | 203,595 (53.6) | 1,697 (48.1) | 176,248 (46.4) | 3,523 (100) | 379,843 (100) |
The study population comprised 1,826 males (51.9%) and 1,697 females (48.1%), with a mean age of 32.8 years (SD ± 8.6). There was no statistically significant difference in age distribution between males and females (χ², p = 0.86). In contrast, statistically significant gender differences were observed in both regional distribution and educational qualifications (p < 0.01 for each). The demographic characteristics of the study participants are presented in Table 2.
Table 2.
Demographic distribution of the study participants by gender
| Variable | Category | Males (n = 1,826) |
Females (n = 1,697) |
Total (n = 3,523) |
p value (χ²) |
|---|---|---|---|---|---|
| Age Range | 14–24 years | 378 (20.7%) | 362 (21.3%) | 740 (21.0%) | 0.8616 |
| 25–34 years | 681 (37.3%) | 646 (38.1%) | 1,327 (37.7%) | ||
| 35–44 years | 525 (28.7%) | 469 (27.6%) | 994 (28.2%) | ||
| 45–49 years | 242 (13.3%) | 220 (13.0%) | 462 (13.1%) | ||
| Region | Central | 567 (31.1%) | 308 (18.1%) | 875 (24.8%) | <0.0001 |
| East | 436 (23.9%) | 342 (20.2%) | 778 (22.1%) | ||
| West | 823 (45.1%) | 1,047 (61.7%) | 1,870 (53.1%) | ||
| Education | No formal education | 270 (14.8%) | 353 (20.8%) | 623 (17.7%) | < 0.0001 |
|
Primary education |
121 (6.6%) | 116 (6.8%) | 237 (6.7%) | ||
| Lower Secondary | 101 (5.5%) | 107 (6.3%) | 208 (5.9%) | ||
| Middle Secondary | 243 (13.3%) | 213 (12.5%) | 456 (12.9%) | ||
| Higher Secondary | 462 (25.3%) | 386 (22.7%) | 848 (24.1%) | ||
| Technical/Vocational education | 138 (7.6%) | 96 (5.7%) | 234 (6.6%) | ||
| Tertiary education | 463 (25.4%) | 408 (24.0%) | 871 (24.7%) | ||
| Monastic education | 37 (2.0%) | 18 (1.1%) | 55 (1.6%) | ||
| Occupation | Civil Servant | 520 (28.5%) | 384 (22.6%) | 904 (25.7%) | <0.001 |
| Business | 337 (18.5%) | 337 (19.8%) | 674 (19.1%) | ||
| Unemployed (incl. housewife) | 281 (15.4%) | 471 (27.8%) | 752 (21.3%) | ||
| Private/Corporate employee | 377 (20.7%) | 296 (17.4%) | 673 (19.1%) | ||
| Farmer | 129 (7.1%) | 90 (5.3%) | 219 (6.2%) | ||
| Student | 100 (5.5%) | 77 (4.5%) | 177 (5.0%) | ||
| Others* | 82 (4.5%) | 37 (2.2%) | 119 (3.4%) |
*monks, armed forces, parliamentarians
Visual impairment
Among the 3,523 individuals screened, 368 had distance VI, yielding crude prevalence of 10.4% (95% CI: 9.4–11.5). The age- and sex-adjusted prevalence of distance VI was 11.0% (95% CI: 10.0–12.0) with no significant difference between gender (χ², p = 0.97). Extrapolating to the 2017 census data, an estimated 41,782 individuals (95% CI: 37,984–45,581) aged 18–49 years in Bhutan are likely to have VI.
Refractive error
The crude prevalence of RE was 9.3%, accounting for 89.4% (329 out of 368) of all cases of distance VI. The age- and sex-adjusted prevalence of distance RE was 9.95% (95% CI: 8.91–10.98), with no significant difference between males (10.5%, 95% CI: 9.0–11.9.0.9 and females (9.4%, 95% CI: 8.0–10.9.0.9) (χ², p = 0.73).
After adjusting for age and sex, the prevalence of distance RE was 9.95% (95% CI: 8.91–10.98). There was no statistically significant difference in prevalence between males (10.5%, 95% CI: 9.0–11.9.0.9) and females (9.4%, 95% CI: 8.0–10.9.0.9) (χ², p = 0.73). The highest prevalence was observed in the 18 to–24 year age group, with significantly reduced odds among older age groups (logistic regression, p < 0.001 for all comparisons). Regionally, the prevalence was higher in the eastern region (OR: 3.74; 95% CI: 2.69–5.21) and western (OR: 1.46; 95% CI:1.06–2.02) than in the central region (p < 0.05). Individuals with higher secondary (OR 1.97, 95% CI 1.30–2.99) and tertiary education (OR 1.69, 95% CI 1.11–2.50) had greater odds of RE (p < 0.05). Compared with civil servants, both students (OR: 2.56; 95% CI: 1.29–5.09) and private/corporate employees (OR: 2.05; 95% CI: 1.16–3.63) had significantly higher odds of RE (p < 0.05). These findings are detailed in Table 3.
Table 3.
Prevalence and associations of refractive error with demographic characteristics among adults aged 18 to 49 years using logistic regression (n = 3523)
| Variable | Category | Total Screened | n (%) | Prevalence % (95% CI) | OR (95% CI) | P value (χ²) |
|---|---|---|---|---|---|---|
| Age range | 18–24 years | 740 | 120 (16.22) | 16.22 (13.64–19.09) | 1.00 (Ref) | – |
| 25–34 years | 1,327 | 109 (8.21) | 8.21 (6.80–9.85) | 0.46 (0.35–0.61) | < 0.001 | |
| 35–44 years | 994 | 76 (7.65) | 7.65 (6.08–9.53) | 0.43 (0.32–0.58) | < 0.001 | |
| 45–49 years | 462 | 24 (5.19) | 5.19 (3.38–7.61) | 0.28 (0.18–0.45) | < 0.001 | |
| Region | Central | 875 | 63 (7.20) | 7.20 (5.58–9.16) | 1.00 (Ref) | – |
| East | 778 | 139 (17.87) | 17.87 (15.21–20.83) | 3.74 (2.69–5.21) | < 0.001 | |
| West | 1,870 | 127 (6.79) | 6.79 (5.71–8.03) | 1.46 (1.06–2.02) | 0.022 | |
| Education | No formal education | 871 | 35 (4.02) | 4.02 (2.82–5.55) | 1.00 (Ref) | – |
| Primary education | 848 | 20 (2.36) | 2.36 (1.46–3.62) | 1.33 (0.73–2.41) | 0.35 | |
| Lower Secondary | 623 | 11 (1.77) | 1.77 (0.89–3.15) | 0.82 (0.40–1.69) | 0.59 | |
| Middle Secondary | 456 | 43 (9.43) | 9.43 (6.91–12.52) | 1.44 (0.89–2.34) | 0.137 | |
| Higher Secondary | 237 | 105 (44.30) | 44.30 (37.97–50.79) | 1.97 (1.30–2.99) | 0.001 | |
| Technical/Vocational education | 234 | 20 (8.55) | 8.55 (5.32–12.84) | 1.14 (0.63–2.06) | 0.669 | |
| Tertiary education | 208 | 93 (44.71) | 44.71 (37.82–51.78) | 1.69 (1.11–2.57) | 0.015 | |
| Monastic education | 55 | 2 (3.64) | 3.64 (0.63–12.15) | 0.38 (0.09–1.67) | 0.201 | |
| Occupation | Civil Servant | 904 | 96 (10.62) | 10.62 (8.68–12.85) | 1.00 (Ref) | – |
| Business | 674 | 57 (8.46) | 8.46 (6.48–10.84) | 1.50 (0.87–2.59) | 0.143 | |
| Unemployed (incl. housewife) | 752 | 65 (8.64) | 8.64 (6.74–10.92) | 1.36 (0.76–2.43) | 0.296 | |
| Private/Corporate Employee | 673 | 60 (8.92) | 8.92 (6.88–11.37) | 2.05 (1.16–3.63) | 0.014 | |
| Farmer | 219 | 17 (7.76) | 7.76 (4.61–12.13) | 1.27 (0.71–2.29) | 0.416 | |
| Student | 177 | 28 (15.82) | 15.82 (10.73–22.21) | 2.56 (1.29–5.09) | 0.007 | |
| Others* | 119 | 6 (5.04) | 5.04 (1.98–10.61) | 0.51 (0.19–1.36) | 0.178 |
*monks, armed forces, parliamentarians
Uncorrected refractive error
The overall crude prevalence of URE was 2.41% (95% CI: 1.94–2.97). The age-sex adjusted prevalence of URE was 2.44% (95% CI: 1.84–3.04); significantly lower in males (2.0%, 95% CI: 1.37–2.63) than females (2.96%, 95% CI: 1.89–4.03) (p = 0.04). Extrapolating these findings to national census data, approximately 4,072 males and 5,217 females aged 18 to 49 years in Bhutan are affected by URE, totaling about 9,289 adults.
The odds of URE varied significantly by education and occupation but not by age or region. Individuals with higher secondary (OR: 0.20, 95% CI: 0.06–0.70, p = 0.01) and technical/vocational education (OR: 0.28, 95% CI: 0.08–0.96, p = 0.03) had significantly lower odds of URE than those with no formal education. In contrast, individuals with monastic education demonstrated markedly greater odds (OR: 7.65; 95% CI: 4.01–14.57; p < 0.01) of URE. Unemployed individuals, including housewives, had greater odds of URE than civil servants (OR: 4.44, 95% CI: 2.13–9.23, p < 0.01). The associations between URE and demographic variables are presented in Table 4.
Table 4.
Prevalence and associations of uncorrected refractive error (URE) with demographic characteristics among adults aged 18 to 49 years using logistic regression (n = 3523)
| Variables | Category | Total Screened | URE n (%) |
Prevalence % (95% CI) | OR (95% CI) | P value (χ²) | Wald χ² (df = 1) |
|---|---|---|---|---|---|---|---|
| Age range | 18–24 years | 740 | 19 (2.57) | 2.81 (1.65–3.98) | 1.00 (Ref) | – | – |
| 25–34 years | 1,327 | 30 (2.26) | 2.4 (1.59–3.21) | 1.00 (0.53–1.90) | 1 | 0 | |
| 35–44 years | 994 | 27 (2.72) | 2.9 (1.87–3.92) | 0.88 (0.49–1.57) | 0.66 | 0.19 | |
| 45–49 years | 462 | 9 (1.95) | 2.34 (1.03–3.66) | 1.06 (0.58–1.92) | 0.849 | 0.04 | |
| Region | Central | 875 | 19 (2.17) | 2.38 (1.39–3.37) | 1.00 (Ref) | – | – |
| East | 778 | 23 (2.96) | 3.19 (1.98–4.4) | 0.75 (0.34–1.68) | 0.489 | 0.48 | |
| West | 1,870 | 43 (2.3) | 2.4 (1.71–3.08) | 1.00 (0.53–1.90) | 1 | 0 | |
| Education | No formal education | 871 | 15 (1.72) | 1.93 (1.05–2.82) | 1.00 (Ref) | – | – |
| Primary education | 848 | 3 (0.35) | 0.58 (0.12–1.03) | 1.37 (0.74–2.54) | 0.311 | 1.04 | |
| Lower Secondary | 623 | 3 (0.48) | 0.79 (0.16–1.41) | 1.06 (0.61–1.83) | 0.833 | 0.04 | |
| Middle Secondary | 456 | 14 (3.07) | 3.46 (1.84–5.09) | 1.00 (0.49–2.06) | 1 | 0 | |
| Higher Secondary | 237 | 28 (11.81) | 12.42 (8.3–16.55) | 0.20 (0.06–0.70) | 0.005 | 7.81 | |
| Technical/Vocational education | 234 | 6 (2.56) | 3.33 (1.18–5.48) | 0.28 (0.08–0.96) | 0.03 | 4.7 | |
| Tertiary education | 208 | 15 (7.21) | 7.99 (4.42–11.56) | 1.81 (0.86–3.78) | 0.111 | 2.57 | |
| Monastic education | 55 | 1 (1.82) | 4.96 (0.32–9.61) | 7.65 (4.01–14.57) | < 0.001 | 15.92 | |
| Occupation | Civil Servant | 904 | 18 (1.99) | 2.19 (1.26–3.13) | 1.00 (Ref) | – | – |
| Business | 674 | 15 (2.23) | 2.5 (1.35–3.64) | 1.50 (0.58–3.91) | 0.402 | 0.69 | |
| Unemployed (incl. housewife) | 752 | 24 (3.19) | 3.43 (2.15–4.7) | 4.44 (2.13–9.23) | < 0.001 | 13.4 | |
| Private/Corporate employee | 673 | 16 (2.38) | 2.65 (1.47–3.83) | 1.06 (0.14–8.15) | 0.958 | 0 | |
| Farmer | 219 | 4 (1.83) | 2.66 (0.71–4.6) | 1.00 (0.52–1.93) | 1 | 0 | |
| Student | 177 | 7 (3.95) | 4.93 (1.93–7.94) | 1.12 (0.56–2.24) | 0.748 | 0.1 | |
| Others* | 119 | 1 (0.84) | 2.38 (0.15–4.61) | 1.62 (0.87–3.01) | 0.122 | 2.35 |
*monks, armed forces, parliamentarians
Presbyopia and uncorrected presbyopia
In the study population, 1423 individuals (767 male and 687 female) were aged 35 years and older. The crude prevalence of presbyopia and uncorrected presbyopia was 47.6% (95% CI: 44.9–50.4, n = 677) and 32.3% (95% CI: 29.8–34.7, n = 459), respectively.
After direct standardization to the national census, the age sex-adjusted prevalence of presbyopia was 51.0% (95% CI: 48.3–53.8) and uncorrected presbyopia was 30.5% (95% CI: 28.3–32.8%).
Extrapolating this finding to national census data, an estimated 40,500 individuals aged 35–49 years in Bhutan live with uncorrected presbyopia, of whom approximately 23,400 are male and 17,200 are female.
Presbyopia was significantly higher in males (52.8%, 95% CI: 49.3–56.3) compared with females (46.8%, 95% CI: 42.9–50.7, p = 0.03). Similarly, uncorrected presbyopia was higher in males (33.0%, 95% CI: 29.9–36.1) than in females (27.8%, 95% CI: 24.6–30.9). The difference between sexes was significant (χ² = 4.96, df = 1, p = 0.026). These findings are presented in Table 5.
Table 5.
Prevalence of presbyopia and uncorrected presbyopia by sociodemographic characteristics among adults aged 35–49 years
| Variables | Category | Total Screened | Presbyopia | Uncorrected Presbyopia | ||
|---|---|---|---|---|---|---|
| n (%) | Prevalence % (95% CI) | n (%) | Prevalence % (95% CI) | |||
| Age | 35–44 yrs | 979 | 277 (28.3) | 28.3 (25.6–31.2) | 197 (20.1) | 20.1 (17.6–22.7) |
| 45–49 yrs | 444 | 400 (90.1) | 90.1 (87.0–92.5) | 262 (59.0) | 59.0 (54.4–63.5) | |
| Region | Central | 420 | 209 (49.8) | 49.8 (45.0–54.5) | 155 (36.9) | 36.9 (32.3–41.8) |
| East | 224 | 100 (44.6) | 44.6 (38.3–51.2) | 48 (21.4) | 21.4 (16.7–27.5) | |
| West | 779 | 368 (47.2) | 47.2 (43.8–50.8) | 256 (32.9) | 32.9 (29.6–36.4) | |
| Education | No formal education | 317 | 166 (52.4) | 52.4 (46.9–57.8) | 109 (34.4) | 34.4 (29.6–39.5) |
| Primary education | 107 | 57 (53.3) | 53.3 (43.9–62.4) | 31 (29.0) | 29.0 (21.4–37.7) | |
| Lower Secondary | 102 | 49 (48.0) | 48.0 (38.6–57.6) | 33 (32.4) | 32.4 (24.2–41.5) | |
| Middle Secondary | 198 | 98 (49.5) | 49.5 (42.6–56.4) | 70 (35.4) | 35.4 (29.3–42.0) | |
| Higher Secondary | 275 | 118 (42.9) | 42.9 (37.2–48.8) | 78 (28.4) | 28.4 (23.6–33.7) | |
| Technical/Vocational | 84 | 30 (35.7) | 35.7 (26.3–46.4) | 21 (25.0) | 25.0 (17.4–34.5) | |
| Tertiary | 318 | 144 (45.3) | 45.3 (39.9–50.8) | 106 (33.3) | 33.3 (28.6–38.5) | |
| Monastic education | 22 | 15 (68.2) | 68.2 (47.3–83.6) | 11 (50.0) | 50.0 (29.8–69.5) | |
| Occupation | Civil servant | 375 | 172 (45.9) | 45.9 (40.9–50.9) | 114 (30.4) | 30.4 (26.0–35.1) |
| Business | 316 | 152 (48.1) | 48.1 (42.6–53.6) | 82 (26.0) | 26.0 (21.6–30.8) | |
| Unemployed/Housewife | 300 | 148 (49.3) | 49.3 (43.7–55.0) | 94 (31.3) | 31.3 (26.6–36.4) | |
| Private/Corporate employee | 246 | 106 (43.1) | 43.1 (37.1–49.3) | 85 (34.6) | 34.6 (28.8–40.7) | |
| Farmer | 105 | 52 (49.5) | 49.5 (40.1–58.9) | 45 (42.9) | 42.9 (33.8–52.3) | |
| Student | 34 | 18 (52.9) | 52.9 (36.7–68.5) | 19 (55.9) | 55.9 (39.1–70.7) | |
| Others* | 47 | 29 (61.7) | 61.7 (47.4–74.2) | 20 (42.6) | 42.6 (29.2–56.9) | |
*monks, armed forces, parliamentarians
Participants aged 45–49 years had significantly higher odds of presbyopia (OR: 25.94, 95% CI: 19.35–34.77, p < 0.01) and uncorrected presbyopia (OR:5.72, 95% CI 4.53–7.2, p < 0.01) than those aged 35–44 years. Uncorrected presbyopia was significantly less prevalent in (21.4%) Eastern region than the Central region (36.9%) (OR = 0.47, 95% CI: 0.32–0.68, p < 0.0001). Participants with higher secondary education (OR: 0.68, 95% CI 0.47–0.98, p = 0.04) and technical/vocational (OR: 0.50, 95% CI: 0.29–0.87, p < 0.01) had lower odds of presbyopia.
By occupation, participants classified as “Others”, which included monks, armed forces and parliamentarians had significantly greater odds of presbyopia (OR: 1.86, 95% CI: 1.01–3.44, p = 0.04). Farmers (42.9%) and students (55.9%) had significantly higher prevalence of uncorrected presbyopia than civil servants (OR = 1.72, 95% CI: 1.09–2.69, p = 0.0186) and (OR = 2.90, 95% CI: 1.43–5.89, p = 0.0032), respectively. The association of presbyopia and uncorrected presbyopia sociodemographic factors is shown in Table 6.
Table 6.
The associations of presbyopia and uncorrected presbyopia with sociodemographic factors among adults aged 35–49 years using logistic regression (n = 1,423)
| Variable | Category | Presbyopia | Uncorrected Presbyopia | ||||
|---|---|---|---|---|---|---|---|
| OR (95% CI) | p-value | Wald χ² | OR (95% CI) | p-value | Wald χ² | ||
| Age | 35–44 yrs | 1.00 (Ref) | – | – | 1.00 (Ref) | – | – |
| 45–49 yrs | 25.94 (19.35–34.77) | < 0.001 | 474.2 | 5.72 (4.53–7.21) | < 0.0001 | 216.7 | |
| Region | Central | 1.00 (Ref) | – | – | 1.00 (Ref) | – | – |
| East | 0.81 (0.58–1.14) | 0.23 | 1.49 | 0.47 (0.32–0.68) | < 0.0001 | 15.3 | |
| West | 0.91 (0.70–1.18) | 0.47 | 0.5 | 0.84 (0.65–1.09) | 0.18 | 1.8 | |
| Education | No formal education | 1.00 (Ref) | – | – | 1.00 (Ref) | – | – |
|
Primary education |
1.04 (0.65–1.66) | 0.88 | 0.03 | 0.78 (0.48–1.26) | 0.31 | 1.04 | |
| Lower Secondary | 0.84 (0.52–1.36) | 0.49 | 0.51 | 0.91 (0.57–1.47) | 0.71 | 0.14 | |
| Middle Secondary | 0.93 (0.63–1.38) | 0.73 | 0.1 | 1.04 (0.72–1.51) | 0.82 | 0.05 | |
| Higher Secondary | 0.68 (0.47–0.98) | 0.04 | 4.25 | 0.76 (0.53–1.08) | 0.12 | 2.41 | |
| Technical/Vocational | 0.50 (0.29–0.87) | 0.01 | 6.47 | 0.64 (0.37–1.11) | 0.11 | 2.57 | |
| Tertiary education | 0.71 (0.50–1.01) | 0.06 | 3.54 | 0.95 (0.69–1.33) | 0.78 | 0.08 | |
| Monastic education | 1.99 (0.80–4.96) | 0.14 | 2.01 | 1.91 (0.89–4.09) | 0.1 | 2.75 | |
| Occupation | Civil Servant | 1.00 (Ref) | – | – | 1.00 (Ref) | – | – |
| Business | 1.09 (0.80–1.48) | 0.59 | 0.29 | 0.80 (0.58–1.11) | 0.19 | 1.76 | |
| Unemployed/Housewife | 1.18 (0.86–1.63) | 0.3 | 1.06 | 1.04 (0.76–1.44) | 0.79 | 0.07 | |
| Private/Corporate employee | 0.90 (0.64–1.28) | 0.57 | 0.33 | 1.21 (0.86–1.70) | 0.28 | 1.18 | |
| Farmer | 1.19 (0.73–1.93) | 0.48 | 0.5 | 1.72 (1.09–2.69) | 0.019 | 5.55 | |
| Student | 1.34 (0.62–2.92) | 0.46 | 0.55 | 2.90 (1.43–5.89) | 0.003 | 8.67 | |
| Others* | 1.86 (1.01–3.44) | 0.04 | 4.12 | 1.70 (0.93–3.09) | 0.08 | 2.99 | |
*monks, armed forces, parliamentarians
REC, eREC and relative quality gap for distance and near
The REC, eREC and relative quality gap for distance and near vision, stratified by gender is presented in Table 6. The distance REC was 83.2%, with greater coverage in males (84.4%) than in females (81.9%) (χ², p = 0.03). The distance eREC was 74.1% (95% CI: 71.2–77.0), significantly higher in male (79.9%) than females (67.7%) (χ², p < 0.001). The relative quality gap was 10.9%; significantly greater among females (17.5%) than males (5.3%) (χ²,p < 0.001).
The near REC was 32.2% (95% CI: 29.8–34.6), and the near eREC was 31.3% (95% CI: 28.9–33.7). Both coverage was relatively greater among females (REC: 35.5%, eREC: 33.9%) than among males (REC: 29.5%, eREC: 29.2%). The relative quality gap was 2.8%, higher in females (4.5%) than males (1.0%) (χ², p < 0.001) [Table 7].
Table 7.
REC, eREC and relative quality gap for distance and near vision, stratified by gender
| Component | Distance Vision | Near Vision | ||||
|---|---|---|---|---|---|---|
| Male | Female | Total | Male | Female | Total | |
| Met (n) | 139 | 105 | 244 | 108 | 104 | 212 |
| Undermet (n) | 8 | 22 | 30 | 1 | 5 | 6 |
| Unmet (n) | 27 | 28 | 55 | 261 | 198 | 459 |
| Total need (n) | 174 | 155 | 329 | 370 | 307 | 677 |
| REC (%) | 84.4 | 81.9 | 83.2 | 29.5 | 35.5 | 32.2 |
| eREC (%) | 79.9 | 67.7 | 74.1 | 29.2 | 33.9 | 31.3 |
| Relative Quality gap (%) | 5.3 | 17.5 | 10.9 | 1.0 | 4.5 | 2.8 |
Spectacle use and determinants of non-use
At the time of the study, 832 out of 3,523 participants were using spectacles. The age-and sex-adjusted prevalence was 23.5% (95% CI 23.45–23.48), higher in females (25.3%, n = 435) than males (21.8%, n = 397) (χ², p = 0.01). The majority of spectacle users wore single vision (SV) distance lenses (male 78.3% and female 79.5%). Bifocal and multifocal lenses were least used (< 3%), whereas approximately 5% of users had separate spectacles for distance and near vision. Most individuals (73.6%) obtained their spectacles from private optical practices within the country (76.1% of males; 71.3% of females), followed by government hospitals (23.1%). A small fraction sourced spectacles from private optical (ex-country) or informal local markets, as detailed in Table 8.
Table 8.
Distribution of spectacle users by age group, type of spectacles, and source, stratified by gender (n = 832)
| Category | Male (n = 397) | Female (n = 435) | Total (n = 832) | |
|---|---|---|---|---|
| Age Group | 18–24 years | 102 (25.7%) | 91 (20.9%) | 193 (23.2%) |
| 25–34 years | 126 (31.7%) | 147 (33.8%) | 273 (32.8%) | |
| 35–44 years | 91 (22.9%) | 124 (28.5%) | 215 (25.8%) | |
| 45–49 years | 78 (19.6%) | 73 (16.8%) | 151 (18.1%) | |
| Types of Spectacles | Single Vision (Distance) | 311 (78.3%) | 346 (79.5%) | 657 (79.0%) |
| Single Vision (Near) | 46 (11.6%) | 48 (11.0%) | 94 (11.3%) | |
| Bifocal | 11 (2.8%) | 12 (2.8%) | 23 (2.8%) | |
| Multifocal | 11 (2.8%) | 4 (0.9%) | 15 (1.8%) | |
| SV (Distance) + SV (Near) | 18 (4.5%) | 25 (5.7%) | 43 (5.2%) | |
| Sources of spectacles | Government hospital (in-country) | 83 (20.9%) | 109 (25.1%) | 192 (23.1%) |
| Private optical (in-country) | 302 (76.1%) | 310 (71.3%) | 612 (73.6%) | |
| Private optical (ex-country) | 12 (3%) | 14 (3.2%) | 26 (3.1%) | |
| Market/Pharmacy | 0 (0.0%) | 2 (0.5%) | 2 (0.2%) |
Among the 151 individuals who were not wearing their prescribed spectacles, the most frequently reported reason was “did not wear it today” (37.7%, n = 57). This was followed by spectacles being broken or scratched (15.9%, n = 24), losing spectacles (14.6%, n = 22), and experiencing discomfort while wearing spectacles (13.2%, n = 20). Additional reasons included perceiving no need due to adequate vision without spectacles (10.6%), not having undergone an eye examination (5.3%), concerns about appearance or feeling less attractive (2.0%), and financial constraints (0.7%). These findings are illustrated in Fig. 1.
Fig. 1.
Reasons for not wearing prescribed spectacles
Discussion
This study represents the first implementation of the rapid assessment of refractive error (RARE) methodology in Bhutan, yielding critical data on prevalence of URE, presbyopia, spectacle coverage, eREC and relative quality gap among adults aged 18 to 49 years. While several studies have reported on eREC, most are based on extrapolated data. To the best of our knowledge, this is one of the first studies to directly estimate national-level eREC for both distance and near vision. Such baseline data are critical to assess progress toward the WHO eREC target for 2030.
In Bhutan, the eREC was estimated at 74.1% for distance vision and 31.3% for near vision. The markedly low near eREC, coupled with significant quality gaps, particularly among women, shows major inequalities in both access to and quality of RE services. These findings provide valuable insights into Bhutan’s current status and highlight key areas requiring target intervention to achieve the WHO eREC targets by 2030.
The adjusted prevalence of distance URE was 2.44%; higher in females compared to males. This aligns with studies from RARE surveys conducted in comparable LMICs. The prevalence of URE among adults aged 15–50 years was 1.95% in Koshi Province, Nepal, Bhutan’s closest province with similar geography [16]. Similarly, RARE surveys reported 3.0% URE in South India and 1.5% URE in South Africa [17, 18]. These figures indicate that Bhutan’s URE burden is broadly consistent with regional trends.
The higher URE prevalence in females is consistent with global patterns in LMICs, where women often face greater barriers to accessing eye care, leading to higher disability-adjusted life years (DALYs) from URE than men [22, 23]. Monastic education was associated with higher odds of URE, likely reflecting limited service integration in monastic settings and health-seeking behaviors. Similarly, unemployed individuals, including housewives, also had greater odds of URE than civil servants. This could be attributed to socioeconomic constraints, reduced exposure to workplace health programs, and awareness gaps [24].
In contrast, Bhutan’s distance eREC was 74.1%, substantially higher than the Southeast Asia regional estimate of 54.6% and the global median of 65.8% [25]. Based on the extrapolation from the 2017 RAAB data, the mean eREC in Bhutan was calculated at 47.4% [25]. The comprehensive integration of eye care, including refraction services within the primary health care framework, could have possibly contributed to high rates of REC and minimal access-related barriers in Bhutan. Data from the Bhutan School Sight Survey (BSSS) and the 2018 RAAB further underscore the strength of Bhutan’s eye health system. The RAAB reported a cataract surgical coverage of 86% and a comparatively low prevalence of avoidable blindness, indicating effective service delivery and access to essential ophthalmic care [9]. Furthermore, this high eREC may, in part, also be attributed to a nationwide spectacle distribution initiative in the past few years. Notably, in 2019, a large-scale campaign supported by Essilor International facilitated the donation and distribution of ready-made spectacles across the country [26]. This extensive public‒private partnership likely increased access to refractive services, particularly among underserved and rural populations. Comparable mass spectacle distribution initiatives in other LMICs have similarly been linked to improvements in eRECs [27].
However, presbyopia continues to present a significant public health concern. In this study, 51.0% of adults were presbyopic, and 32.3% had uncorrected presbyopia. The near eREC was 31.3% lying between estimates from Andhra Pradesh (48.0%) and Tamil Nadu (9.6%) [28, 29]. These findings align with global patterns, which estimate that approximately 45% of individuals with presbyopia remain without appropriate correction [3]. This study noted a higher prevalence in female and older age groups (45–49 years). The age-related increase is expected and consistent with physiological changes. However, the higher prevalence in males contradicts many studies, where females often show higher rates of presbyopia [30]. In Bhutan, this discrepancy may relate to occupational patterns, as men often work in jobs that demand little near vision, which may delay their recognition of symptoms rather than the actual onset of the condition itself. Further investigation is warranted to clarify this finding.
The significant variation between the distance eREC (74.1%) and near-eREC (31.3%) noted in this study could be attributed to several factors. Presbyopia often goes unnoticed or ignored, particularly in those under age 50, where early symptoms may be dismissed or adapted. The demand for near-vision correction also depends on near-vision tasks like reading, writing, and using mobile phones, which are less common in rural settings, reducing the motivation to wear or keep near glasses. Even when presbyopic spectacles are provided, they could often be underutilized due to discomfort, stigma, or loss. Furthermore, health programs tend to focus more on distance vision due to mobility-related disability. These gaps, combined with social and gender-related barriers, could have contributed to the lower near eREC. To address this issue, awareness campaigns for presbyopic correction, integrating near vision screening into health programs, and training health workers to identify and manage presbyopia would be required. Bhutan has begun this approach, but broader implementation is needed to train all health assistants and scale up services effectively [31].
Bhutan’s estimated distance eREC exceeds global averages; however, substantial gaps persist, particularly among women, in both service coverage and quality. Historical data indicate gender-based inequities in access to cataract services in Bhutan, mirroring a global trend in which women encounter greater barriers to obtaining eye care services [9, 25]. Evidence highlights that women and girls continue to face sociocultural barriers due to travel constraints, household responsibilities, and limited decision-making autonomy, which often require them to prioritise family needs over their own health [32]. To address these disparities, gender-sensitive strategies should be implemented. Enhancing community-based outreach eye services with female health workers can minimize decision-making barriers, and enhance service accessibility and foster trust among women. Additionally, health education and awareness programs should be established to prioritize women’s eye health alongside household needs. Integrating RE screening into existing maternal and child health services, as well as women-focused initiatives such as cervical cancer screening, will facilitate early detection and intervention.
A majority of participants (73.6%) reported obtaining spectacles from private in-country optical outlets, with government hospitals accounting for 23% of the reported sources. This distribution indicates that initial free provision may have generated awareness and stimulated demand, subsequently motivating individuals to procure additional or replacement spectacles from private providers. A key barrier to spectacle use remains the lack of perceived need for vision correction [33]. Evidence from previous studies suggests that one-time subsidies or free spectacle provisions significantly increase the likelihood of future out-of-pocket expenditures on vision-related products and services [34, 35]. These findings underscore the potential of targeted, time-limited public health interventions to catalyse sustainable, market-driven solutions and improve long-term spectacle coverage.
The present study revealed that cost was not a primary factor for the discontinuation of spectacle use. Rather, participants more frequently cited reasons such as discomfort, a perceived lack of necessity, and damaged spectacles. This contrasts with findings from RARE studies conducted in other LMICs, where cost has been consistently reported as the major barrier to spectacle use [36]. The delivery of free spectacles acquired through donations could have reduced initial financial barriers. The private optical sector has also maintained moderate pricing, possibly due to low import taxes on spectacles and a noncommercialized market. Moreover, spectacles are often perceived as medical aids rather than consumer items, with users being more concerned about comfort, damage, or perceived need than price. To address nonfinancial factors, there is a need to incorporate user-centered design principles, enhance patient counselling, and ensure appropriate follow-up to support sustained spectacle wear.
This study has several strengths. It is nationally representative, employs the validated RARE methodology, reports age- and sex-standardized prevalence estimates and has a good response rate. Nonetheless, certain limitations must be acknowledged including constraints of the RARE methodology, as highlighted in previous studies [9, 16–19]. This study targets ages 18 to 49, and does not include other age groups. As a result, it prevents derivation of national eREC figures and limits direct comparability with global eREC estimates. Secondly, uncorrected or undercorrected myopes may use their far point for near tasks, potentially underestimating presbyopia; to address this, participants with presenting distance visual acuity worse than 6/12 were excluded from near assessment. Finally, the cross-sectional design precludes causal inference and does not capture the long-term impact of spectacle correction quality or related service delivery outcomes.
Bhutan’s relatively well-integrated eye care system and provision of free refractive services provide a strong foundation to meet WHO targets. Nonetheless, targeted actions are required to further expand coverage and strengthen quality. Policy implications include targeted outreach programs for underserved populations which include women, unemployed groups, and monastic institutions. Expanded optometry services in underserved areas, improved availability and accessibility of corrective spectacles, targeted interventions to address gender-based disparities and sustained public health advocacy are necessary.
Conclusion
This first nationally representative RARE survey establishes a critical baseline for RE services in Bhutan. Bhutan has demonstrated substantial progress in enhancing access to refractive services and improving effective coverage for distance vision. This achievement can be attributed to the integration of eye health, including refractive services, into primary health care, supported by a robust public health infrastructure. While distance eREC is notably higher than global and regional estimates, the near eREC remains notably low. The marked gender and socioeconomic disparities, and deficiencies in service coverage and quality, reveal underlying inequities in access and service delivery. To address these gaps and achieve the 2030 eREC targets, it is imperative that Bhutan prioritizes the strengthening and advocating for near vision services, expands public–private engagement in optical services, and implements systematic, gender-responsive strategies in refractive service delivery.
Acknowledgements
The authors thank Dr. Zelalem G Dessie, University of KwaZulu Natal, South Africa, for data analysis. The authors also acknowledge the Khesar Gyalpo University of Medical Science of Bhutan for funding this study and express gratitude to the study participants for their time and cooperation.
Authors’ contributions
IPS is the study’s principal investigator. IPS, KSN and KPM conceptualized the protocol, and study design. IPS and NTL participated in study implementation including data collection. NTL provided technical guidance and assisted in fund acquisition. KSN, KPM and NTL were involved in the interpretation of the finding and validated the data. IPS drafted the manuscript and all authors critically reviewed the draft manuscript and approved the final version.
Funding
This work was supported by the Medical Education Center for Research Innovation and Training (MECRIT), Khesar Gyalpo University of Medical Science of Bhutan (Ref. (16) MECRIT/Research/Award/2022/438 dated 2nd November 2022). The funding agency had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of this manuscript.
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Ethical approval was obtained from both the Research Ethics Board of Health (REBH), Ministry of Health, Bhutan (Ref: REBH/Approval/2023/003) and the Biomedical Research Ethics Committee (BREC), University of KwaZulu-Natal, South Africa (Approval no: BREC/00004482/2022). Administrative approval was secured from the Policy and Planning Division of the Ministry of Health, Bhutan.
Prior to enrollment in the study, all participants were informed about the study’s objectives, procedures, potential risk and benefits. Participation was entirely voluntary and had the option to withdraw anytime without any consequences.Written informed consent was obtained in the participants' preferred language. For participants with no formal education/illiterates, informed consent to participate was obtained from the legal guardian or an appropriate representative of any participant. The study involved no invasive procedures. Data confidentiality was strictly maintained: no personal identifiers were recorded, and datasets were anonymized. The study adhered to the principles of the Declaration of Helsinki and followed international best practices for clinical and public health research.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.