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Factors related to environmental barriers experienced by persons with and without disabilities in diverse African settings.

Factors related to environmental barriers experienced by persons with and without disabilities in diverse African settings.
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Visagie S, Eide AH, Dyrstad K, Mannan H, Swartz L, Schneider M, Mji G, Munthali A, Khogali M, van Rooy G, Hem KG, MacLachlan M,


Visagie S, Eide AH, Dyrstad K, Mannan H, Swartz L, Schneider M, Mji G, Munthali A, Khogali M, van Rooy G, Hem KG, MacLachlan M, (click to view)

Visagie S, Eide AH, Dyrstad K, Mannan H, Swartz L, Schneider M, Mji G, Munthali A, Khogali M, van Rooy G, Hem KG, MacLachlan M,

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PloS one 2017 10 1212(10) e0186342 doi 10.1371/journal.pone.0186342
Abstract

This paper explores differences in experienced environmental barriers between individuals with and without disabilities and the impact of additional factors on experienced environmental barriers. Data was collected in 2011-2012 by means of a two-stage cluster sampling and comprised 400-500 households in different sites in South Africa, Sudan Malawi and Namibia. Data were collected through self-report survey questionnaires. In addition to descriptive statistics and simple statistical tests a structural equation model was developed and tested. The combined file comprised 9,307 participants. The Craig Hospital Inventory of Environmental Factors was used to assess the level of environmental barriers. Transportation, the natural environment and access to health care services created the biggest barriers. An exploratory factor analysis yielded support for a one component solution for environmental barriers. A scale was constructed by adding the items together and dividing by number of items, yielding a range from one to five with five representing the highest level of environmental barriers and one the lowest. An overall mean value of 1.51 was found. Persons with disabilities scored 1.66 and persons without disabilities 1.36 (F = 466.89, p < .001). Bivariate regression analyses revealed environmental barriers to be higher among rural respondents, increasing with age and severity of disability, and lower for those with a higher level of education and with better physical and mental health. Gender had an impact only among persons without disabilities, where women report more barriers than men. Structural equation model analysis showed that socioeconomic status was significantly and negatively associated with environmental barriers. Activity limitation is significantly associated with environmental barriers when controlling for a number of other individual characteristics. Reducing barriers for the general population would go some way to reduce the impact of these for persons with activity limitations, but additional and specific adaptations will be required to ensure an inclusive society.

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