Knowledge and determinants of women’s knowledge on vertical transmission of HIV and AIDS in South Africa
Bibliographic record
Abstract
BACKGROUND: HIV/AIDS is still one of the major public health concerns globally. It is one of the major contributory causes of deaths among women in the reproductive age (15-49 years) and has resulted in about 14 million orphaned children globally. Knowledge of Mother-to Child transmission is one of the strategies to fight against HIV. This study, therefore, sought to assess the knowledge and determinants of women's knowledge on vertical transmission of HIV and AIDS in their reproductive age in South Africa. METHODS: Data were obtained from the South Africa Demographic and Health Survey (SADHS) 2016. Both descriptive (frequencies and percentages) and inferential analysis (multilevel mixed-effects complementary log-log regression model) were conducted and the statistical significance was set at p < 0.05. RESULTS: The prevalence of knowledge of mother to child transmission of HIV and AIDS during pregnancy, delivery, breastfeeding and at least knowledge of one source are 87.0%, 81.1%, 80.3% and 91.4% respectively. At the individual level, those with secondary [AOR = 1.28, CI = 1.04,1.57] and higher [AOR = 1.55, CI = 1.21,1.99], those who read newspaper less than once a week [AOR = 1.16, CI = [1.05,1.28], at least once a week [AOR = 1.14, CI = 1.04,1.25], and those who listen to the radio less than once a week [AOR = 1.22, CI = 1.03,1.43] had higher odds of knowledge on MTCT of HIV and AIDS. However, those with parity 0 [AOR = 0.73, CI = [0.63,0.85] had lower odds of knowledge of MTCT of HIV and AIDS compared with those with parity 4 or more. At the contextual level, those in the poorest wealth quintile [AOR = 0.82,CI = 0.69,0.97] had lower odds of having knowledge of MTCT of HIV and AIDS. Those in the urban areas [AOR = 1.17, CI = [1.04,1.31], those in Limpopo [AOR = 1.35, CI = [1.12,1.64], Gauteng [AOR = 1.35, CI = [1.12,1.62] and North west[AOR = 1.49, CI = [1.22,1.81] had higher odds of knowledge of mother to child transmission of HIV and AIDS. CONCLUSION: The study has demonstrated that there is relatively high knowledge of mother to child transmission of HIV and AIDS in South Africa. The factors associated with the knowledge are educational level, exposure to mass media, parity, wealth status, place of residence and the region of residence. To further increase the knowledge, it is imperative to adopt various messages and target respondents in different part of SSA through the mass media channels. This should be done taking cognizant of the rural-urban variations and socio-economic status.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".