The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
The socioeconomic determinants of HIV incidence: evidence from a longitudinal, population-based study in rural South Africa
Open accessAbstract
BACKGROUND: Knowledge of the effect of socioeconomic status on HIV infection in Africa stems largely from cross-sectional studies. Cross-sectional studies suffer from two important limitations: two-way causality between socioeconomic status and HIV serostatus and simultaneous effects of socioeconomic status on HIV incidence and HIV-positive survival time. Both problems are avoided in longitudinal cohort studies. METHODS: We used data from a longitudinal HIV surveillance and a linked demographic surveillance in a poor rural community in KwaZulu-Natal, South Africa, to investigate the effect of three measures of socioeconomic status on HIV incidence: educational attainment, household wealth categories (based on a ranking of households on an assets index scale) and per capita household expenditure. Our sample comprised of 3325 individuals who tested HIV-negative at baseline and either HIV-negative or -positive on a second test (on average 1.3 years later). RESULTS: In multivariable survival analysis, one additional year of education reduced the hazard of acquiring HIV by 7% (P = 0.017) net of sex, age, wealth, household expenditure, rural vs. urban/periurban residence, migration status and partnership status. Holding other factors equal, members of households that fell into the middle 40% of relative wealth had a 72% higher hazard of HIV acquisition than members of the 40% poorest households (P = 0.012). Per capita household expenditure did not significantly affect HIV incidence (P = 0.669). CONCLUSION: Although poverty reduction is important for obvious reasons, it may not be as effective as anticipated in reducing the spread of HIV in rural South Africa. In contrast, our results suggest that increasing educational attainment in the general population may lower HIV incidence.
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Cites
Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779
Proportional hazards tests and diagnostics based on weighted residuals
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“We tested the proportional hazards assumption for all variables jointly and for each variable individually using the tests proposed by Grambsch and Therneau [47].”
MethodPettifor, A. E., Rees, H. V., Kleinschmidt, I., Steffenson, A. E., MacPhail, C., Hlongwa-Madikizela, L., Vermaak, K., & Padian, N. S. (2005) · AIDS · doi:10.1097/01.aids.0000183129.16830.06 · Cited by 645
Dunkle, K. L., Jewkes, R. K., Nduna, M., Levin, J., Jama, N., Khuzwayo, N., Koss, M. P., & Duvvury, N. (2006) · AIDS · doi:10.1097/01.aids.0000247582.00826.52 · Cited by 324
The spread and effect of HIV-1 infection in sub-Saharan Africa
Buvé, A., Bishikwabo-Nsarhaza, K., & Mutangadura, G. (2002) · The Lancet · doi:10.1016/s0140-6736(02)08823-2 · Cited by 298
Cited by
Saul, J., Bachman, G., Allen, S., Toiv, N. F., Cooney, C., & Beamon, T. (2018) · PLOS ONE · doi:10.1371/journal.pone.0208167 · Cited by 319
Metadata
- Authors
- Bärnighausen, T., Hosegood, V., Timaeus, I. M., & Newell, M.-L.
- Venue
- AIDS
- Published
- 2007-11
- Volume
- 21
- Issue
- Suppl 7
- Pages
- S29-S38
- ISSN
- 0269-9370 (ISSN-L)
- OpenAlex
- W2030576043
- Cited by
- 272
- References
- 5
- FWCI
- 9.99
- Type
- journal article
- Language
- en
- Open access
- green
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- Bärnighausen, T., Hosegood, V., Timaeus, I. M., & Newell, M.-L. (2007). The socioeconomic determinants of HIV incidence: evidence from a longitudinal, population-based study in rural South Africa. AIDS. https://doi.org/10.1097/01.aids.0000300533.59483.95
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