Disability prevalence-context matters: A descriptive community-based survey

Abstract

Background: There is increasing interest in the collection of globally comparable disability data. Context may influence not only the rates but also the nature of disability, thus locally collected data may be of greater use in service delivery planning than national surveys.Objectives: The objective of this article was to explore the extent to which two areas, both under-resourced but geographically and socially distinct, differed in terms of the prevalence and patterns of disability.Method: A cross-sectional descriptive survey design was utilised, using stratified cluster sampling in two under-resourced communities in the Western Cape, South Africa. Nyanga is an informal urban settlement in Cape Town and Oudtshoorn is a semi-rural town. The Washington Group Short Set of questions was used to identify persons with disabilities (PWD), and a self-developed questionnaire obtained socio-demographic information.Results: The overall prevalence of disability was 9.7% (confidence intervals [CIs] 9.7–9.8) and the proportion of PWD was significantly different between the two sites (Chi-Sq = 129.5, p 0.001). In the urban area, the prevalence rate of any disability was 13.1% (CIs 12.0–14.3) with 0.3% (CIs 0.1–0.6) reporting inability to perform any function at all. In contrast, the semi-rural community had a lower overall prevalence rate of 6.8% (CIs 6.0% – 7.8%) but a higher rate of those unable to perform any function: 1% (CIs 0.07–1.4). Disability was associated with gender, age, unemployment and lower income status in both areas.Conclusion: Deprived areas tend to show higher disability prevalence rates than the National Census estimates. However, the discrepancy in prevalence and patterns of disability between the two under-resourced areas indicates the need for locally specific data when planning health interventions.

Transitioning to a life with disability in rural South Africa: A qualitative study

“…It is known that people with disabilities are more likely to be unemployed and experience higher rates of poverty with fewer resilience options than their peers without disabilities (Wapling 2012 ). Disability and poverty have been shown to interact in complex ways, where functional difficulties may result in reduced productivity, causing higher susceptibility to poverty, while poverty reduces a person’s access to assistive devices, accessible infrastructure and rehabilitation services that could support economic participation (Maart et al 2019 ; Mitra 2018 ; WHO 2002 ). In line with this, since becoming disabled, some participants lost their jobs and sources of income:…”

“…People with disabilities are estimated to be 15% of the general population, but possibly higher for those living in poverty (WHO 2011 ). In the last South African national census, the prevalence of disability was estimated to be 7.5% (Statistics South Africa 2016 ); however, this may reflect under-reporting because of stigma or limitations of measurement tools (Maart, Amosun & Jelsma 2019 ).…”

“…For example, Haihambo and Lightfoot ( 2010 ) found that in Namibia, disability is often seen as being caused by supernatural forces, and so is viewed negatively by community members; however, views may change if people are closely connected to a person with a disability. Maart et al ( 2019 ) implemented a survey in two communities in South Africa to demonstrate how disability experiences vary significantly between communities based on the factors such as language, culture and infrastructure.…”

Lessons from Disability Counting in Ecuador, with a Contribution from Primary Health Care

“…Continuity of care strengthens the identification of persons with disabilities, which are not as readily apparent as physical or sensory disabilities, for example, children with behavioral problems or with learning difficulties, and persons with mild difficulties or with mental problems. The identification of these persons, who perhaps were not taken into account in cross-sectional counting, may be a valuable contribution of disability-inclusive PHC to the reduction of the risk of their exclusion from services and to the development of an accurate local population’s disability profile, as disability data on national level may not reflect intracountry differences or specific characteristics of which being aware of is important for local disability policy planning and service implementation [ 5 ].…”

“…Whereas disability rates are often the first and only mentioned data, it is the nature of need and demand of persons with disabilities that are paramount for policy and planning. Research shows that “the simple reporting of only the prevalence of disability fails to capture the differences between communities” and “does not highlight the needs of different age groups or across different levels of severity” [ 5 ]. Counting cases a priori by first defining in a dichotomous way who is and who is not a person with disability risks “excluding people in need of targeted interventions” [ 6 ].…”