A research report submitted to the Faculty of Health sciences,
University of the Witwatersrand, Johannesburg, in partial
fulfillment of the requirements for the degree of Master of
Science in Epidemiology & Biostatistics
Johannesburg, October 2014 / Introduction
Disability is a major public health concern worldwide. The situation in Africa is serious. It is
estimated that ten percent of the world’s population is living with a disability and close to
two-thirds of all people with a disability live in low-income countries. The main objective of
this study was to determine the spatial distribution of disability and disability grant allocation
and to identify factors associated with disability within the Gauteng Province (2007).
Materials and Methods
An analytical cross-sectional study design was used to analyse secondary data from the 2007
South African survey data. The population of Gauteng was the focus of the study. The
prevalence of disability in Gauteng was estimated. Chi-square test of proportions was used to
analyse the distribution of social and demographic characteristics among participants.
Poisson regression models were constructed to determine the association between disability
and socio-demographics characteristics.
Results
Of a sample of 133 691 individuals in Gauteng Province, 4 492 (3.4%) reported being
disabled, and of these, 2 333 (51,94%) were male and 2159 (48,06%) were female. The
overall prevalence of disability or disability rate was 3.4%.
Most of the disabled people were older individuals aged 40 to 64 years (51,51%), followed
by those aged 18 to 39 years (33,17%); the rest were individuals aged over 64 years of age
(retirement age category).
Most of these disabled participants were black (77,8%), with whites contributing 15,69%.
Almost half (42,72%) of the disabled participants were never married. More than half of the
disabled participants (59,75%) had a high school level of education, followed by those with
primary school as their level of education (25,31%). Almost 18% of the disabled people were
employed and the remaining percentage was unemployed (82%). More than half of the
disabled population in Gauteng resided in Johannesburg (34,93%) and Ekurhuleni (26,89%),
followed by Tshwane (19.08%).
There was a statistically difference in disability grant allocation between the disabled males
(51,34%) and (48,66%) females. About 67,93% of the disability grant was given to the older
working age category (40-64 years). More than 80% of the disability grants support was
issued to the black population group. More than 45 % of the disability grants support issued
was given to people who had never married. More than 80% of the disability grants issued
was given to the non-economically active category of disabled people. More than 60% of the
disability grants support went to those in Johannesburg, Tshwane and Ekurhuleni.
Variables associated with disability in Poisson regression analysis included the following:
Female participants in the study showed a lower risk (40%) of disability compared to males,
and this difference was statistically significant (IRR 0.6, CI 0.59-0.67, p= <0.001).
The older working age category (39 to 64 years) (IRR2.9, CI 2.6-3.1, p=<0001) and
retirement age category (65 years and above) (IRR 3.0, CI 2.5-3.5, p=<0.001) were
respectively associated with a higher risk of disability.
Coloured (IRR 1.37,CI 1.2-1.6, p <0.001) and white (IRR 1.41, CI 1.3-1.6, p<0.001)
participants showed a 1.4 times greater risk of having disability compared to individuals of
the black community, and these differences were statistically significant. While Indians (IRR
1.13, CI 0.9-1.4, p=0.247) had 1.1 times the risk of having disability compared to black
participants but the difference was not statistically different.
The risk of disability in individuals living in Tshwane (IRR 0.87,CI 0.80-0.95, p=0.001) and
the West Rand (IRR 0.86,CI 0.75-0.99, p=0.037) districts was lower by 10% relative to
individuals staying in the city of Johannesburg. This risk was relatively lower by 20% in
Metsweding (IRR 0.77,CI 0.63-0.94, p=0.012) compared to Johannesburg. These differences
were statistically significant. On the other hand, although not significant, the risk of disability
was higher by 7% in Sedibeng district (IRR 1.07,CI 0.97-1.18, p=0.187).
Participants in a traditional marriage (IRR 1.1, CI 0.97-1.24, p =0.14) and those who were
polygamous (IRR 1.0, CI 0.33-3.21, p= 0.96) were not associated with disability compared to
civil/ religiously married participants. Others categories of marital status included living
together as married (IRR 1.2, CI 1.06-1.37, p=0.006); never married (IRR 1.6, CI 1.49-1.78,
p< 0.001); widow/widower (IRR 1.4, CI 1.2-1.6, p <0.001); separated (IRR 1,6, CI1.34-2.08,
p<0.001 and divorced (IRR 1.9,CI 1.65-2.24, p<0.001) were associated with disability and
the observed differences were statistically significant.
Those who had attended high school (IRR 0.48, CI 0.44-0.53, p <0.001) and those who had
post matric studies (higher school)(IRR 0.34, CI 0.27-0.42, p< 0.001) were less associated
with disability compared to those who only had a primary school level of education (IRR
0.8, CI 0.76-0.93, p = 0.001).
Participants classified as not economically active were 7.5 times at risk of being disabled
(IRR 7.5, CI6.95-8.19, p < 0.001). The observed difference was statistically significant.
The least poor households were 0.7 times at risk of having a disabled member (IRR 0.7, CI
0.62-0.75, p <0.001) while the poor households had a 0.9 times the risk of having a family
member with any disability (IRR 0.9, CI 0.81-0.94, p <0.001) - compared to most poor
households, and the difference was statistically significant.
Conclusion
Gauteng showed a prevalence of individuals living with a disability in South Africa. In fact, it
was found that the overall prevalence of disability in the Gauteng Province was 3,6%.
During the same period Statistics South Africa estimated the whole county disability rate to
be 4%. Statistically significant risk factors associated with disability in Gauteng included
males aged 39 years and older; the coloured and white population group; living in the
Sedibeng district; living together as married, never married, widower/widow, separated and
divorced; not educated; not economically active; and most poor households. The spatial
distribution of grant allocation was proportional to the disability burden per district as well as
well as per local municipality, with a statistically significant relationship between disability
burden and grants allocation. A higher proportion of males disabled received a grant
compared to disabled females. Sedibeng district was highly associated with any disability,
whilst Metsweding was the safest district.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/17495 |
| Date | 21 April 2015 |
| Creators | Mpinda, Beya |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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