Socio-demographic differences of disability prevalence among the population aged 60 years and over in Bangladesh

This study aims to delineate the sociodemographic differences in disability prevalence across the population aged 60 years and over in Bangladesh, and to investigate the association of factors with reporting disability in later life. A microdata sample for those aged 60 years or over from the Census of Bangladesh 2011 was used where disability was assessed with a self-reported single response question. Logistic regression models were performed separately for men and women. Results reveal that the disability prevalence rate increased sharply with age, and it was higher among older women (5.2 per cent) compared to men (4.8 per cent). Physical and vision disabilities were the two categories with the highest prevalence of reported disabilities, with a higher prevalence of physical disability among men and vision disability among women. Being older, female, currently not in marital partnership, and having a lower educational attainment, not being employed, living alone, and residing in the rural areas were significantly associated with reporting disability in later life. The higher prevalence of disability among older women, those who are illiterate, and those residing in rural areas highlights the need for policies prioritising these groups. Special attention should also be given to those who are currently not in marital partnership, particularly women who are living alone.     

URBAN SPRAWL,OBESOGENIC ENVIRONMENT,AND CHILD WEIGHT

Using the 1979 National Longitudinal Survey of Youth along with the child survey, we examine the relationship between urban sprawl of U.S. metro counties and the body mass index (BMI) of children who reside in these counties. We make a distinction between urban sprawl in a county and its geographical placement in the urban hierarchy. Even after accounting for unobserved individual heterogeneity and resulting selection bias, we find that urban sprawl is positively related to child BMI and distance to large metros is negatively related to child BMI. These effects are somewhat pronounced among girls and middle/high school children.     

European developments in strategic spatial planning

Strategic spatial planning which takes an integrated approach to the development of a territory seemed to go out of fashion, but now there are signs that it is being re‐established. This paper explores these developments using case studies from 10 European countries. The analysis uses an ‘institutionalist’ approach, which examines how the ‘agency’ of spatial planning practices responds to the ‘structure’ of contextual forces, at the same time influencing that structure. The ‘driving forces’ which are influencing strategic spatial planning are investigated, as are two aspects of the changes in spatial planning: institutional relations and policy agendas. The conclusions are that—at least in the case studies—there is a movement in the institutional relations towards horizontal articulation, territorial logic, and negotiative forms. Policy agendas too are changing, becoming more selective and using new conceptions of space and place. Those institutional developments, however, are not necessarily being translated into territorially‐integrated policy (as distinct from functional/sectoral policy). That translation appears to require simultaneous re‐framing of relational resources (trust, social capital), knowledge resources (intellectual capital), linked to strong mobilization efforts (political capital). The cases considered varied significantly in how far that had been done. Where it had, strategic spatial plan‐making practices were playing a key role in developing institutional territorial integration and re‐invigorating territorial identities.     

Real-time Seismic Damage Detection of Concrete Shear Walls Using Artificial Neural Networks

Concrete shear walls are widely employed in buildings as a main resistance system against lateral loads. Early identification of seismic damage to concrete shear walls is vital for deciding post-earthquake occupancy in these structures. In this article, a method based on artificial neural networks for real-time identification of seismic damage to concrete shear walls was proposed. Inter-story drifts and plastic hinge rotation of concrete walls were used as the inputs and outputs of a MLP neural network. Modal Pushover Analysis was employed to prepare well-distributed data sets for training the neural network. The proposed method was applied to a five-story concrete shear wall building. The results from the network were compared with those obtained from Nonlinear Time History Analysis. It was observed that the trained neural network successfully detected damage to concrete shear walls and accurately estimated the severity of seismic-induced damage.