Kathleen Kahn

Profile: Agincourt Health and Socio-demographic Surveillance System

The Agincourt health and socio-demographic surveillance system (HDSS), located in rural northeast South Africa close to the Mozambique border, was established in 1992 to support district health systems development led by the post-apartheid ministry of health. The HDSS (90 000 people), based on an annual update of resident status and vital events, now supports multiple investigations into the causes and consequences of complex health, population and social transitions. Observational work includes cohorts focusing on different stages along the life course, evaluation of national policy at population, household and individual levels and examination of household responses to shocks and stresses and the resulting pathways influencing health and well-being. Trials target children and adolescents, including promoting psycho-social well-being, preventing HIV transmission and reducing metabolic disease risk. Efforts to enhance the research platform include using automated measurement techniques to estimate cause of death by verbal autopsy, full ‘reconciliation’ of in- and out-migrations, follow-up of migrants departing the study area, recording of extra-household social connections and linkage of individual HDSS records with those from sub-district clinics. Fostering effective collaborations (including INDEPTH multi-centre work in adult health and ageing and migration and urbanization), ensuring cross-site compatibility of common variables and optimizing public access to HDSS data are priorities.

Strengthening standardised interpretation of verbal autopsy data: the new InterVA-4 tool.

BACKGROUNDnVerbal autopsy (VA) is the only available approach for determining the cause of many deaths, where routine certification is not in place. Therefore, it is important to use standards and methods for VA that maximise efficiency, consistency and comparability. The World Health Organization (WHO) has led the development of the 2012 WHO VA instrument as a new standard, intended both as a research tool and for routine registration of deaths.nnnOBJECTIVEnA new public-domain probabilistic model for interpreting VA data, InterVA-4, is described, which builds on previous versions and is aligned with the 2012 WHO VA instrument.nnnDESIGNnThe new model has been designed to use the VA input indicators defined in the 2012 WHO VA instrument and to deliver causes of death compatible with the International Classification of Diseases version 10 (ICD-10) categorised into 62 groups as defined in the 2012 WHO VA instrument. In addition, known shortcomings of previous InterVA models have been addressed in this revision, as well as integrating other work on maternal and perinatal deaths.nnnRESULTSnThe InterVA-4 model is presented here to facilitate its widespread use and to enable further field evaluation to take place. Results from a demonstration dataset from Agincourt, South Africa, show continuity of interpretation between InterVA-3 and InterVA-4, as well as differences reflecting specific issues addressed in the design and development of InterVA-4.nnnCONCLUSIONSnInterVA-4 is made freely available as a new standard model for interpreting VA data into causes of death. It can be used for determining cause of death both in research settings and for routine registration. Further validation opportunities will be explored. These developments in cause of death registration are likely to substantially increase the global coverage of cause-specific mortality data. To access the supplementary material to this article The InterVA-4 User Guide please see Supplementary files under Article Tools online.Background : Verbal autopsy (VA) is the only available approach for determining the cause of many deaths, where routine certification is not in place. Therefore, it is important to use standards and methods for VA that maximise efficiency, consistency and comparability. The World Health Organization (WHO) has led the development of the 2012 WHO VA instrument as a new standard, intended both as a research tool and for routine registration of deaths. Objective : A new public-domain probabilistic model for interpreting VA data, InterVA-4, is described, which builds on previous versions and is aligned with the 2012 WHO VA instrument. Design : The new model has been designed to use the VA input indicators defined in the 2012 WHO VA instrument and to deliver causes of death compatible with the International Classification of Diseases version 10 (ICD-10) categorised into 62 groups as defined in the 2012 WHO VA instrument. In addition, known shortcomings of previous InterVA models have been addressed in this revision, as well as integrating other work on maternal and perinatal deaths. Results : The InterVA-4 model is presented here to facilitate its widespread use and to enable further field evaluation to take place. Results from a demonstration dataset from Agincourt, South Africa, show continuity of interpretation between InterVA-3 and InterVA-4, as well as differences reflecting specific issues addressed in the design and development of InterVA-4. Conclusions : InterVA-4 is made freely available as a new standard model for interpreting VA data into causes of death. It can be used for determining cause of death both in research settings and for routine registration. Further validation opportunities will be explored. These developments in cause of death registration are likely to substantially increase the global coverage of cause-specific mortality data. To access the supplementary material to this article ‘The InterVA-4 User Guide’ please see Supplementary files under Article Tools online.

Moving from Data on Deaths to Public Health Policy in Agincourt, South Africa: Approaches to Analysing and Understanding Verbal Autopsy Findings

Peter Byass and colleagues compared two methods of assessing data from verbal autopsies, review by physicians or probabilistic modeling, and show that probabilistic modeling is the most efficient means of analyzing these data

Assessing health and well-being among older people in rural South Africa

Background: The population in developing countries is ageing, which is likely to increase the burden of non-communicable diseases and disability. Objective: To describe factors associated with self-reported health, disability and quality of life (QoL) of older people in the rural northeast of South Africa. Design: Cross-sectional survey of 6,206 individuals aged 50 and over. We used multivariate analysis to examine relationships between demographic variables and measures of self-reported health (Health Status), functional ability (WHODASi) and quality of life (WHOQoL). Results: About 4,085 of 6,206 people eligible (65.8%) completed the interview. Women (Odds Ratio (OR)=1.30, 95% CI 1.09, 1.55), older age (OR=2.59, 95% CI 1.97, 3.40), lower education (OR=1.62, 95% CI 1.31, 2.00), single status (OR=1.18, 95% CI 1.01, 1.37) and not working at present (OR=1.29, 95% CI 1.06, 1.59) were associated with a low health status. Women were also more likely to report a higher level of disability (OR=1.38, 95% CI 1.14, 1.66), as were older people (OR=2.92, 95% CI 2.25, 3.78), those with no education (OR=1.57, 95% CI 1.26, 1.97), with single status (OR=1.25, 95% CI 1.06, 1.46) and not working at present (OR=1.33, 95% CI 1.06, 1.66). Older age (OR=1.35, 95% CI 1.06, 1.74), no education (OR=1.39, 95% CI 1.11, 1.73), single status (OR=1.28, 95% CI 1.10, 1.49), a low household asset score (OR=1.52, 95% CI 1.19, 1.94) and not working at present (OR=1.32; 95% CI 1.07, 1.64) were all associated with lower quality of life. Conclusions: This study presents the first population-based data from South Africa on health status, functional ability and quality of life among older people. Health and social services will need to be restructured to provide effective care for older people living in rural South Africa with impaired functionality and other health problems. Access the supplementary material to this article: INDEPTH WHO-SAGE questionnaire (including variants of vignettes), a data dictionary and a password-protected dataset (see Supplementary files under Reading Tools online). To obtain a password for the dataset, please send a request with ‘SAGE data’ as its subject, detailing how you propose to use the data, to global.health@epiph.umu.se

Household context and child mortality in rural South Africa: the effects of birth spacing, shared mortality, household composition and socio-economic status

Background Household characteristics are important influences on the risk of child death. However, little is known about this influence in HIV-endemic areas. We describe the effects of household characteristics on children’s risk of dying in rural South Africa. Methods We use data describing the mortality of children younger than 5 years living in the Agincourt health and socio-demographic surveillance system study population in rural northeast South Africa during the period 1994–2008. Using discrete time event history analysis we estimate children’s probability of dying by child characteristics and household composition (other children and adults other than parents) (N = 924 818 child-months), and household socio-economic status (N = 501 732 child-months). Results Children under 24 months of age whose subsequent sibling was born within 11 months experience increased odds of dying (OR 2.5; 95% CI 1.1–5.7). Children also experience increased odds of dying in the period 6 months (OR 2.1; 95% CI 1.2–3.6), 3–5 months (OR 3.0; 95% CI 1.5–5.9), and 2 months (OR 11.8; 95% CI 7.6–18.3) before another household child dies. The odds of dying remain high at the time of another child’s death (OR 11.7; 95% CI 6.3–21.7) and for the 2 months following (OR 4.0; 95% CI 1.9–8.6). Having a related but non-parent adult aged 20–59 years in the household reduces the odds (OR 0.6; 95% CI 0.5–0.8). There is an inverse relationship between a child’s odds of dying and household socio-economic status. Conclusions This detailed household profile from a poor rural setting where HIV infection is endemic indicates that children are at high risk of dying when another child is very ill or has recently died. Short birth intervals and additional children in the household are further risk factors. Presence of a related adult is protective, as is higher socio-economic status. Such evidence can inform primary health care practice and facilitate targeting of community health worker efforts, especially when covering defined catchment areas.

It's my secret : Barriers to paediatric HIV treatment in a poor rural South African setting

In South Africa, a third of children born are exposed to HIV, while fewer undergo an HIV confirmatory test. Anti-retroviral therapy (ART) coverage among children remains low-despite roll-out of the national ART programme in South Africa in 2004. This study sought to understand critical barriers to seeking HIV-related care for children in rural South Africa. Data presented in this article derive from community-based qualitative research in poor rural villages in north-east South Africa; this includes 21 in-depth interviews in 2008 among caregivers of children identified as HIV-positive in 2007 from a randomly selected community-based sample. Using NVIVO 8, data were coded and analysed, using a constant comparative method to identify themes and their repetitions and variations. Structural barriers leading to poor access to health care, and social and systems barriers, all influenced paediatric HIV treatment seeking. Of concern was the expressed need to maintain secrecy regarding a childs HIV status to avoid stigma and discrimination, and misconceptions regarding the course of HIV disease in children; this led to a delay in seeking appropriate care. These barriers need to be addressed, including through focused awareness campaigns, improved access to health care and interventions to address rural poverty and development at both household and community levels. In addition, training of health care professionals to improve their attitudes and practice may be necessary. However, this study only provides the perspective of the caregivers; further studies with health care providers are needed to gain a fuller picture for appropriate policy and practice guidance.

Social conditions and disability related to the mortality of older people in rural South Africa

Background: South Africa is experiencing a health and social transition including an ageing population and an HIV epidemic. We report mortality experience of an older rural South African population. Methods: Individual survey data and longer-term demographic data were used to describe factors associated with mortality. Individuals aged 50 years and over (nu2009=u20094085) answered a health and quality of life questionnaire in 2006 and were followed for 3 years thereafter. Additional vital events and socio-demographic data were extracted from the Agincourt Health and Demographic Surveillance System from 1993 to 2010, to provide longer-term trends in mortality. Cox regression analysis was used to determine factors related to survival. Results: In 10u2009967 person-years of follow-up between August 2006 and August 2009, 377 deaths occurred. Women had lower mortality {hazard ratio [HR] 0.35 [95% confidence interval (CI) 0.28–0.45]}. Higher mortality was associated with being single [HR 1.48 (95% CI 1.16–1.88)], having lower household assets score [HR 1.79 (95% CI 1.28–2.51)], reporting greater disability [HR 2.40 (95% CI 1.68–3.42)] and poorer quality of life [HR 1.59 (95% CI 1.09–2.31)]. There was higher mortality in those aged under 69 as compared with those 70 to 79 years old. Census data and cause specific regression models confirmed that this was due to deaths from HIV/TB in the younger age group. Conclusions: Mortality due to HIV/TB is increasing in men, and to some extent women, aged over 50. Policy makers and practitioners should consider the needs of this growing and often overlooked group.

Record-linkage comparison of verbal autopsy and routine civil registration death certification in rural north-east South Africa: 2006–09

Background: South African civil registration (CR) provides a key data source for local health decision making, and informs the levels and causes of mortality in data-lacking sub-Saharan African countries. We linked mortality data from CR and the Agincourt Health and Socio-demographic Surveillance System (Agincourt HDSS) to examine the quality of rural CR data. Methods: Deterministic and probabilistic techniques were used to link death data from 2006 to 2009. Causes of death were aggregated into the WHO Mortality Tabulation List 1 and a locally relevant short list of 15 causes. The matching rate was compared with informant-reported death registration. Using the VA diagnoses as reference, misclassification patterns, sensitivity, positive predictive values and cause-specific mortality fractions (CSMFs) were calculated for the short list. Results: A matching rate of 61% [95% confidence interval (CI): 59.2 to 62.3] was attained, lower than the informant-reported registration rate of 85% (CI: 83.4 to 85.8). For the 2264 matched cases, cause agreement was 15% (kappa 0.1083, CI: 0.0995 to 0.1171) for the WHO list, and 23% (kappa 0.1631, CI: 0.1511 to 0.1751) for the short list. CSMFs were significantly different for all but four (tuberculosis, cerebrovascular disease, other heart disease, and ill-defined natural) of the 15 causes evaluated. Conclusion: Despite data limitations, it is feasible to link official CR and HDSS verbal autopsy data. Data linkage proved a promising method to provide empirical evidence about the quality and utility of rural CR mortality data. Agreement of individual causes of death was low but, at the population level, careful interpretation of the CR data can assist health prioritization and planning.

Involvement of stakeholders in determining health priorities of adolescents in rural South Africa

Background When developing intervention research, it is important to explore issues from the community perspective. Interventions that promote adolescent health in South Africa are urgently needed, and Project Ntshembo (‘hope’) aims to improve the health of young women and their offspring in the Agincourt sub-district of rural northeast South Africa, actively using stakeholder involvement throughout the research process. Objective This study aimed to determine adolescent health priorities according to key stakeholders, to align stakeholder and researcher priorities, and to form a stakeholder forum, which would be active throughout the intervention. Design Thirty-two stakeholders were purposefully identified as community members interested in the health of adolescents. An adapted Delphi incorporating face-to-face discussions, as well as participatory visualisation, was used in a series of three workshops. Consensus was determined through non-parametric analysis. Results Stakeholders and researchers agreed that peer pressure and lack of information, or having information but not acting on it, were the root causes of adolescent health problems. Pregnancy, HIV, school dropout, alcohol and drug abuse, not accessing health services, and unhealthy lifestyle (leading to obesity) were identified as priority adolescent health issues. A diagram was developed showing how these eight priorities relate to one another, which was useful in the development of the intervention. A stakeholder forum was founded, comprising 12 of the stakeholders involved in the stakeholder involvement process. Conclusions The process brought researchers and stakeholders to consensus on the most important health issues facing adolescents, and a stakeholder forum was developed within which to address the issues. Stakeholder involvement as part of a research engagement strategy can be of mutual benefit to the researchers and the community in which the research is taking place.

Rural–urban variations in age at menarche, adult height, leg-length and abdominal adiposity in black South African women in transitioning South Africa

Abstract Background: The pre-pubertal socioeconomic environment may be an important determinant of age at menarche, adult height, body proportions and adiposity: traits closely linked to adolescent and adult health. Aims: This study explored differences in age at menarche, adult height, relative leg-length and waist circumference between rural and urban black South African young adult women, who are at different stages of the nutrition and epidemiologic transitions. Subjects and methods: We compared 18–23 year-old black South African women, 482 urban-dwelling from Soweto and 509 from the rural Mpumalanga province. Age at menarche, obstetric history and household socio-demographic and economic information were recorded using interview-administered questionnaires. Height, sitting-height, hip and waist circumference were measured using standardised techniques. Results: Urban and rural black South African women differed in their age at menarche (at ages 12.7 and 14.5 years, respectively). In urban women, a one-year increase in age at menarche was associated with a 0.65u2009cm and 0.16% increase in height and relative leg-length ratio, respectively. In both settings, earlier age at menarche and shorter relative leg-length were independently associated with an increase in waist circumference. Conclusions: In black South African women, the earlier onset of puberty, and consequently an earlier growth cessation process, may lead to central fat mass accumulation in adulthood.