Eva K. Fenwick

Determine the prevalence and vision-related quality of life (VRQoL) effects of single and multiple visual function impairments (VFIs) in multi-ethnic older Asians. A total of 2380 participants from a population-based cohort study were included. Visual function comprised presenting visual acuity (VA), contrast sensitivity (CS), depth perception (DP), and color vision (CV). Rasch-transformed VRQoL was obtained using the Brief Impact of Visual Impairment questionnaire. Multiple linear regression explored the independent (mutually adjusting for each VFI) impact of bilateral single (VAI, CSI, CVI and DPI) and multiple (i.e., the co-occurrence of any two, three, or four bilateral VFI) VFIs on VRQoL. Dominance analysis estimated the relative contribution for each of the single VFI on VRQoL. The prevalence of bilateral VAI, CSI, CVI, or DPI alone was 15.3%, 20.7%, 8.1%, and 23.5%, respectively, whereas for concurrent two, three and four bilateral VFIs was 11%, 4.1% and 1.6%, respectively. Participants with single bilateral VFI (except CVI) experienced poorer overall VRQoL (β -0.25 to -0.34; all p < 0.05) compared to those without. CSI had the largest contribution (25%), to the decline in overall VRQoL. As the number of concurrent bilateral VFIs increased, VRQoL progressively worsened (% decrements -12.26% to -25.61%; all P < 0.001) compared to no VFI. Bilateral single and multiple VFIs are prevalent in older Asians. CSI had the largest contribution to VRQoL decrements. There was a systematic worsening in VRQoL scores with an increase in concurrent bilateral VFI. Comprehensive visual function testing may be warranted to prevent the debilitating consequences of VFIs on healthy aging.

To optimize the psychometric properties of myopia refractive intervention quality of life (QoL) item banks (IBs), and evaluate their performance using computerized adaptive testing (CAT) simulations. In this clinical study, adults utilizing myopic refractive intervention modalities answered 204 items within seven IBs: Activity Limitation (AL); Comfort (CM); Concerns (CN); Convenience (CV); Emotional (EM); Mobility (MB); and Work (WK), referred to collectively as "MyoRICAT". The psychometric properties of each IB were assessed with Rasch analysis, and CAT simulations with 1000 respondents determined the average number of items needed to achieve moderate (standard error of measurement [SEM] = 0.387) and high (SEM = 0.30) precision levels. Of the 291 participants (mean age 34.02 ± 11.04 years; 65.64% female), 61 (20.96%) wore spectacles only, 123 (42.27%) used both spectacles and contact lenses, and 107 (36.76%) underwent laser refractive surgery. AL, CM, CN, CV, and EM showed satisfactory psychometric properties after minor amendments. WK lacked measurement precision owing to certain items being applicable only to specific subsets of refractive modalities. This IB was therefore retained as a fixed length rather than a CAT operationalized scale. Conversely, MB demonstrated such poor targeting that it was not considered further. In CAT simulations, the mean number of items required per IB ranged from 10 (CV) to 12 (AL) for moderate, and 15 (CV) to 19 (AL) for high measurement precision. Five IBs demonstrated strong psychometric properties and potential CAT efficiency. MyoRICAT can provide a comprehensive measurement of the QoL impact of myopic refractive intervention modalities.

To determine the prevalence, factors, temporal trends, and projections of glaucoma over 15 years among multiethnic older Asian adults aged 60 to 100 years. We included 2380 participants (mean [SD] age, 73.6 [8.5] years; 55.2% female) from the baseline phase of the Population Health and Eye Disease Profile in Elderly Singaporeans (PIONEER; 2017-2022) study. Comprehensive eye examinations and standardized questionnaires assessed sociodemographic, clinical, and lifestyle factors. Glaucoma and subtypes were defined using International Society of Geographical and Epidemiological Ophthalmology guidelines, with age-standardized prevalence rates based on the 2020 Singapore census. Logistic regression using generalized estimating equations identified risk factors, temporal trends were analyzed using population-based data, and projections utilized United Nations population data. The census-adjusted glaucoma prevalence was 5.1%, comprising 3.4% primary open-angle glaucoma, 0.7% primary angle-closure glaucoma, and 1% secondary glaucoma. Prevalence was higher among Malays (6.5%) and Indians (6.2%) compared to Chinese (4.9%). Significant factors included older age (odds ratio [OR], 1.07), Malay ethnicity (OR, 2.07), higher intraocular pressure (OR, 1.14), longer axial length (OR, 1.20), cataract surgery (OR, 1.81), and polypharmacy (OR, 2.04). Over two decades, age-adjusted glaucoma prevalence in Singapore remained stable (5%-7%) but increased among Indians (3.65% in 2013 to 6.70% in 2022), likely due to the high rates of systemic diseases. Currently, ∼57,800 Singaporeans aged ≥60 years have glaucoma, projected to rise by 43%, reaching 85,800 by 2040. Glaucoma is common among older Singaporeans, with notable sociodemographic and modifiable clinical factors. Rising prevalence among Indians and the projected increase in cases underscore the need for targeted screening and early interventions.

To determine the prevalence of under-corrected refractive error (UCRE) and its associated risk factors and patient-reported, health-related, and economic impact in a multiethnic cohort of older adults. This study included 2592 older participants from a population-based cohort study. UCRE was defined as an improvement of at least 0.2 logMAR in best-corrected distance visual acuity from presenting distance visual acuity (PDVA) in the better-eye with PDVA worse than 20/40 (>0.3 logMAR). Patient-reported and economic outcomes, including visual functioning and healthcare expenditures, were assessed using validated questionnaires. Prevalence was weighted according to Singapore's 2020 population census, and multivariable regression models were used to analyze the risk factors of UCRE and its association with patient-reported and economic outcomes. The weighted prevalence of UCRE was 8%. Lower socioeconomic status (odds ratio [OR] = 2.98; P < 0.001) and greater spherical equivalent (per 0.50-D increase, OR = 1.07; P = 0.018) were associated with increased odds of UCRE, contributing 39.2% and 23.2%, respectively, of the total variance. UCRE was significantly associated with lower visual functioning scores (-5.7%; β = -0.22; P = 0.046), higher likelihood of loneliness (OR = 2.96; P = 0.015), slower gait speed (OR = 2.03; P = 0.02), and presence of sarcopenia (OR = 2.41; P < 0.001). Individuals with UCRE incurred 2.33-times higher healthcare costs (P = 0.05) compared to those without. One in 12 older Singaporeans had UCRE. Given the substantial adverse patient-centered and health-related impact and economic burden associated with UCRE, targeted vision screening, treatment for visual impairment, and public health education on the importance of regular eye examinations and wearing appropriate glasses are recommended to mitigate these challenges and reduce associated costs.

Objective: We determined the rates, predictors, and barriers/facilitators of non-adherence to annual follow-up screenings for Diabetic Retinopathy (DR), nephropathy (DN) and foot complications (DFC) screening in primary care patients with type 2 diabetes. Methods: This prospective, mixed-method, clinical study, included 934 patients (mean ± SD age 60.4 ± 9.4 years, 46.9 % women) who underwent DR/DN/DFC screenings (N = 2012 appointments). Logistic regression analysis determined the baseline predictors of non-adherence to follow-up screening (failure to attend annual follow-up screening within ± 4 months). Qualitative interviews on barriers/facilitators of screening adherence were conducted with 36/24 non-adherent/adherent patients and 9 healthcare professionals (HCPs). Results: Non-adherence rates to DR, DFC and DN follow-up screening were 27.6 % (n = 186), 29.8 % (n = 225) and 12.7 % (n = 74), respectively. Predictors included higher total cholesterol (DR); poor self-rated Diabetes Control (DN); and higher satisfaction with diabetes support (DFC and DN). Better self-efficacy was protective (DFC). Poor HCP-patient communication and long waiting times were patient-reported barriers to adherence, while knowledge about benefits of diabetes complications screening was a facilitator. Time constraints prevented HCPs from reinforcing the importance of screening to patients. Conclusions: Non-adherence to diabetic microvascular complications follow-up screening was suboptimal in Singapore and driven by multi-faceted predictors and barriers. Targeted interventions are needed to improve follow-up screening adherence.