Factors associated with mortality in HIV-infected people in rural and urban South Africa

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dc.contributor.authorOtwombe, KN
dc.contributor.authorPetzold, M
dc.contributor.authorModisenyane, T
dc.date.accessioned2016-01-29T12:52:41Z
dc.date.available2016-01-29T12:52:41Z
dc.date.issued2014
dc.departmentObstetrics and GynaecologyE
dc.descriptionPKen_ZA
dc.description.abstractBackground: Factors associated with mortality in HIV-infected people in sub-Saharan Africa are widely reported. However rural urban disparities and their association with all-cause mortality remain unclear. Furthermore, commonly used classical Cox regression ignores unmeasured variables and frailty. Objective: To incorporate frailty in assessing factors associated with mortality in HIV-infected people in rural and urban South Africa. Design: Using data from a prospective cohort following 6,690 HIV-infected participants from Soweto (urban) and Mpumalanga (rural) enrolled from 2003 to 2010; covariates of mortality were assessed by the integrated nested Laplace approximation method. Results: We enrolled 2,221 (33%) rural and 4,469 (67%) urban participants of whom 1,555 (70%) and 3,480 (78%) were females respectively. Median age (IQR) was 36.4 (31.0 44.1) in rural and 32.7 (28.2 38.1) in the urban participants. The mortality rate per 100 person-years was 11 (9.7 12.5) and 4 (3.6 4.5) in the rural and urban participants, respectively. Compared to those not on HAART, rural participants had a reduced risk of mortality if on HAART for 6 12 (HR: 0.20, 95% CI: 0.10 0.39) and 12 months (HR: 0.10, 95% CI: 0.05 0.18). Relative to those not on HAART, urban participants had a lower risk if on HAART 12 months (HR: 0.35, 95% CI: 0.27 0.46). The frailty variance was significant and 1 in rural participants indicating more heterogeneity. Similarly it was significant but B1 in the urban participants indicating less heterogeneity. Conclusion: The frailty model findings suggest an elevated risk of mortality in rural participants relative to the urban participants potentially due to unmeasured variables that could be biological, socio economic, or healthcare related. Use of robust methods that optimise data and account for unmeasured variables could be helpful in assessing the effect of unknown risk factors thus improving patient management and care in South Africa and elsewhere.en_ZA
dc.identifier.citationOtwombe, K. N., Petzold, M., Modisenyane, T., et al. 2014. Factors associated with mortality in HIV-infected people in rural and urban South Africa. Global health action; 7:25488en_ZA
dc.identifier.urihttp://hdl.handle.net/10539/19409
dc.language.isoenen_ZA
dc.subjectHIV Infectionsen_ZA
dc.subjectHIV Infections/mortalityen_ZA
dc.subjectSouth Africa/epidemiologyen_ZA
dc.titleFactors associated with mortality in HIV-infected people in rural and urban South Africaen_ZA
dc.typeArticleen_ZA
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