Prevalence of early and late age-related macular degeneration in a rural population in Northern India: The INDEYE Feasibility Study

PURPOSE. To assess the prevalence of age-related macular degeneration (AMD) in a rural population in Northern India. METHODS. In a pilot feasibility study, 1443 people (median age, 60 years; 52% women), were identified from enumeration of the 50+ age group in 11 randomly sampled villages from a rural, periurban district of Haryana, Northern India. Of those identified, 87% attended an eye examination that included digital fundus photography. Fundus images were graded at a single reading center using definitions from the Wisconsin Age-Related Maculopathy Grading System. RESULTS. Fundus photographs were available for 1101 participants. Overall, 28.8% of participants had ungradable fundus images due to cataract. Including all with ungradable images in the denominator, the prevalence of soft drusen was 34.0% (95% confidence interval [CI] 26.1–42.9); of soft indistinct drusen, 2.2% (95% CI, 1.1–4.4); and of pigmentary irregularities, 10.8% (95% CI, 7.1–16.1). There were 15 (1.4%) cases of late-stage AMD (95% CI, 0.8–2.3) with the prevalence rising from 0.4% in the 50- to 59-year age range to 4.6% in those aged 70 years or older. CONCLUSIONS. Drusen and pigmentary irregularities are common among the rural northern Indian population. The prevalence of late AMD is similar to that encountered in Western settings and is likely to contribute significantly to the burden of vision loss in older people in the developing world.

Willingness to Pay for Rural Landscape Improvements: Combining Mixed Logit and Random-Effects Models

This paper reports the findings from a discrete-choice experiment designed to estimate the economic benefits associated with rural landscape improvements in Ireland. Using a mixed logit model, the panel nature of the dataset is exploited to retrieve willingness-to-pay values for every individual in the sample. This departs from customary approaches in which the willingness-to-pay estimates are normally expressed as measures of central tendency of an a priori distribution. Random-effects models for panel data are subsequently used to identify the determinants of the individual-specific willingness-to-pay estimates. In comparison with the standard methods used to incorporate individual-specific variables into the analysis of discrete-choice experiments, the analytical approach outlined in this paper is shown to add considerable explanatory power to the welfare estimates.

Using choice experiments to explore the spatial distribution of willingness to pay for rural landscape improvements

We report findings from a choice experiment survey designed to estimate the economic benefits of policy measures to improve the rural landscape in the Republic of Ireland. Using a panel mixed logit specification to account for unobserved taste heterogeneity we derived individual-specific willingness-to-pay (WTP) estimates for each respondent in the sample. We subsequently investigated the spatial dependence of these estimates. Results suggest the existence of positive spatial autocorrelation for all rural landscape attributes. As a means of benefit transfer, kriging methods were employed to interpolate WTP estimates across the whole of the Republic of Ireland. The kriged WTP surfaces confirm the existence of spatial dependence and illustrate the implied spatial variation and regional disparities in WTP for all the rural landscape improvements investigated.

Bridging top down and bottom up: Modelling community preferences for a dispersed rural settlement pattern

This paper explores the scope to bridge top-down and bottom-up perspectives on spatial planning by drawing on EU-funded action research in relation to rural settlement planning in Northern Ireland. The empirical work is located within a review of planning theory that exposes a long running tension between the technocratic stances of government planners and the aspirations of engaged citizens. It demonstrates the operation of a large group planning methodology that delivers community preference with environmental responsibility as a participatory input into planning policy formulation. Transferable insights into the dynamics of spatial planning are identified.