Rapid Assessment of Avoidable Blindness in India

BACKGROUND: Rapid assessment of avoidable blindness provides valid estimates in a short period of time to assess the magnitude and causes of avoidable blindness. The study determined magnitude and causes of avoidable blindness in India in 2007 among the 50+ population. METHODS AND FINDINGS: Sixteen randomly selected districts where blindness surveys were undertaken 7 to 10 years earlier were identified for a follow up survey. Stratified cluster sampling was used and 25 clusters (20 rural and 5 urban) were randomly picked in each district.. After a random start, 100 individuals aged 50+ were enumerated and examined sequentially in each cluster. All those with presenting vision = 50 years were enumerated, and 94.7% examined. Based on presenting vision,, 4.4% (95% Confidence Interval[CI]: 4.1,4.8) were severely visually impaired (vision<6/60 to 3/60 in the better eye) and 3.6% (95% CI: 3.3,3.9) were blind (vision<3/60 in the better eye). Prevalence of low vision (<6/18 to 6/60 in the better eye) was 16.8% (95% CI: 16.0,17.5). Prevalence of blindness and severe visual impairment (<6/60 in the better eye) was higher among rural residents (8.2%; 95% CI: 7.9,8.6) compared to urban (7.1%; 95% CI: 5.0, 9.2), among females (9.2%; 95% CI: 8.6,9.8) compared to males (6.5%; 95% CI: 6.0,7.1) and people above 70 years (20.6%; 95% CI: 19.1,22.0) compared to people aged 50-54 years (1.3%; 95% CI: 1.1,1.6). Of all blindness, 88.2% was avoidable. of which 81.9% was due to cataract and 7.1% to uncorrected refractive errors/uncorrected aphakia. CONCLUSIONS: Cataract and refractive errors are major causes of blindness and low vision and control strategies should prioritize them. Most blindness and low vision burden is avoidable

Assessing longitudinal quality of life in prostate cancer patients and their spouses: a multilevel modeling approach

PURPOSE: This study aimed at examining the relationship between quality of life (QOL) in prostate cancer (PCa) patients and partners and how baseline demographics, cancer-related factors, and time-varying psychosocial and symptom covariates affect their QOL over time. METHODS: Guided by a modified Stress-Coping Model, this study used multilevel modeling to analyze longitudinal data from a randomized clinical trial that tested a family-based intervention to improve QOL in couples managing PCa. Patients and partners from the usual-care control group (N = 134 dyads) independently completed the measurements at baseline, and at 4-, 8-, and 12-month follow-ups. RESULTS: Correlations of QOL between patients and partners over time were small to moderate. Patients’ lower education level, partners’ older age, higher family income, and localized cancer at baseline were associated with better QOL in couples. Over time, couples’ QOL improved as their social support and cancer-related dyadic communication increased and as couples’ uncertainty, general symptoms, and patients’ prostate cancer-related sexual and hormonal symptoms decreased. CONCLUSIONS: Evidence indicates that couples’ QOL during cancer survivorship is affected by multiple contextual factors (e.g., baseline demographics and time-varying psychosocial factors and symptoms). Intervention research is needed to explore comprehensive strategies to improve couples’ QOL during the continuum of PCa survivorship