ABSTRACT
Background
Smoking is undoubtedly a major risk factor for morbidity, disability and premature
death. Its use results in grave health and economic losses not only to the individual
but also to the population and the world at large. Many surveys have been done in
South Africa to estimate the prevalence of smoking. It is therefore imperative and
expedient to have an overall impression of the prevalence rates over time. And also it
is important to assess how subgroups affect the prevalence and trends in the national
population. This will be of help in determining which subgroups have achieved
reduction in smoking prevalence and which have not; evaluating the tobacco control
policies in the country; and in designing specific interventions. This research was
undertaken to determine the trends and patterns of smoking in the South African adult
population
Objectives
The objectives for this study were:
Regarding the South African adult population during 1995 – 1998, to:
1. Compute the prevalence of smoking and assess the trends of smoking
prevalence.
2. Assess the patterns and trends of smoking prevalence in subgroups by sex,
age, marital status, race, locality (urban or rural), education and province.
3. Identify factors in the population that may account for patterns and trends in
smoking prevalence over time
4. Make recommendations regarding the public health implications of the
findingsMethods
This was an analytical study involving secondary analysis of existing datasets from
four South African representative national surveys. From 11 surveys, which measured
smoking in the South African population, four surveys were selected using some
inclusion and exclusion criteria. The population of interest was the South Africa adult
population (18 – 49), so variables of interest (outcome variable was current smokers)
for this group were extracted. Prevalence (frequency) rates estimation of smoking in
the national population and in subgroups were then estimated. Unadjusted odds ratios
and adjusted odds ratios were computed by bi-variate cross tabulation and
multivariate logistic regression respectively. Time-trend analyses (Maentel Haenszel
chi-squared test) were computed by logistic regression for trend in proportions
Results
From 1995 to 1997 about 1/3 of the adult South African population were smokers, but
that dropped significantly to about ¼ in 1998. For the period however, there was no
significant trend. The prevalence of smoking varied with, and was largely depended
on population subgroup; while it was as high as 63.9% among Coloured males, 62.3%
among Coloured females, 53.7 % among all males, 52.7% among rural males, it was
as low as 11.4% among all females, 6.8% among rural females, 10.83% among Indian
females and 5.06% among Black females. The only significant trends was an
increasing smoking prevalence among Blacks, Coloured men, people with tertiary
education, Free State and Gauteng provinces, age group 35 – 44; urban men and a
decreasing smoking prevalence in all women, urban women and black women, age
group 18 – 24 and the Eastern Cape, Kwazulu-Natal, Northen Cape and Mpumalanga
provinces. Sex, race, age, and education were the major risk factors for smoking in the South African adult population. Locality (rural/urban) though had different smoking
rate was not a risk factor for smoking. Marital status was neither a determinant nor
risk factor for smoking.
Discussion and Conclusion
The prevalence of smoking in the South African adult population is very high and did
not achieve any significant trend between 1995 and 1998. However the significant
drop from 1997 to 1998 probably means that smoking prevalence in the national
population may have started declining; therefore, more monitoring is needed to
ascertain this. This high prevalence of smoking in the South African population,
which may have been for years, may predict a high burden of chronic smoking-related
diseases in the near future. The patterns of smoking analyses reveal that smoking in
the South African adult population is determined by a complex interplay of different
factors.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/4829 |
| Date | 15 May 2008 |
| Creators | Bello, Braimoh |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 344079 bytes, application/pdf, application/pdf |
Page generated in 0.0019 seconds