Access to health care in South Africa--the influence of race and class.
OBJECTIVE
The first democratic government elected in South Africa in 1994 inherited huge inequities in health status and health provision across all sections of the population. This study set out to assess the impact of the new government's commitment to address these inequities and implement policies to improve population health in general and address inequalities in health care in particular.


METHODS
A 1998 household survey assessed many aspects of health delivery, including their own perceived and actual access to health care among different segments of South African society.


RESULTS
Race was the main predictor of perceived changes in access to health care, with black, coloured-and Indian respondents significantly more likely to feel that access had improved since 1994, compared with white respondents. Socio-economic status (SES) was the main predictor of actual access to health care, with low and middle SES classes significantly less likely to access care when ill.


CONCLUSIONS
One-third of respondents perceived health care access to have improved between 1994 and 1998, and this response was partially determined along racial lines. About one-quarter reported an inability to access health care when they required it, and this response was partially determined along socio-economic lines. This set of contrasting responses suggests that at a political level perceptions are largely influenced by race, but at the operational level actual access is influenced by SES.
Lalloo
R
R
Department of Community Oral Health, Faculty of Dentistry and WHO Collaborating Centre, University of the Western Cape, Cape Town.
Myburgh
N G
NG
Smith
M J
MJ
Solanki
G C
GC
D000328:Adult; D000368:Aged; D001294:Attitude to Health / Q000208:ethnology*; D044383:Black People / Q000706:statistics & numerical data*; D003906:Developing Countries; D005260:Female; D019538:Health Care Surveys; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care; D011203:Poverty; D011336:Probability; D018570:Risk Assessment; D012923:Social Class; D012959:Socioeconomic Factors; D013019:South Africa; D044465:White People / Q000706:statistics & numerical data*