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Socioeconomic differences in mortality in the antiretroviral therapy era in Agincourt, rural South Africa, 2001–13: a population surveillance analysis 

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Presentation on theme: "Socioeconomic differences in mortality in the antiretroviral therapy era in Agincourt, rural South Africa, 2001–13: a population surveillance analysis "— Presentation transcript:

1 Socioeconomic differences in mortality in the antiretroviral therapy era in Agincourt, rural South Africa, 2001–13: a population surveillance analysis  Mr Chodziwadziwa W Kabudula, MSc, Brian Houle, PhD, Mark A Collinson, PhD, Prof Kathleen Kahn, PhD, Francesc Xavier Gómez- Olivé, PhD, Prof Stephen Tollman, PhD, Prof Samuel J Clark, PhD  The Lancet Global Health  Volume 5, Issue 9, Pages e924-e935 (September 2017) DOI: /S X(17) Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions

2 Figure 1 Age distribution in the original 21 villages of the Agincourt Health and socio-Demographic Surveillance System (A) Population, July 1, (B) Population, July 1, (C) Population, July 1, (D) Population, July 1, 2013. The Lancet Global Health 2017 5, e924-e935DOI: ( /S X(17) ) Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions

3 Figure 2 Differences in mortality and life expectancy at birth by household wealth and time period (A) Mortality in children younger than 5 years. (B) Mortality in women. (C) Mortality in men. (D) Life expectancy at birth in women. (E) Life expectancy at birth in men. The Lancet Global Health 2017 5, e924-e935DOI: ( /S X(17) ) Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions

4 Figure 3 Annual probability of dying, by cause and quintile of household wealth for 2001–13 (A) HIV/AIDS and tuberculosis. (B) Other communicable diseases (excluding HIV/AIDS and tuberculosis) and maternal, perinatal, and nutritional causes. (C) Non-communicable diseases. (D) Injuries. Data are predicted summed annual probabilities of death per 1000 person-years, by cause of death and household wealth quintiles that were estimated by multinomial logistic regression. All measures are adjusted for age, sex, and time period. SES=socioeconomic status. The Lancet Global Health 2017 5, e924-e935DOI: ( /S X(17) ) Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Terms and Conditions


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