Modelling determinants, impact, and space-time risk of age-specific mortality in rural South Africa: integrating methods to enhance policy relevance

被引:12
作者
Sartorius, Benn [1 ]
机构
[1] Univ Witwatersrand, Fac Hlth Sci, Sch Publ Hlth, 7 York Rd, ZA-2193 Johannesburg, South Africa
基金
英国惠康基金; 英国医学研究理事会; 新加坡国家研究基金会; 瑞士国家科学基金会; 美国安德鲁·梅隆基金会;
关键词
mortality; space-time risk; determinants; population attributable fractions; demographic surveillance system; rural; South Africa; SPATIAL-TEMPORAL TRENDS; ADULT MORTALITY; INFORMATION-SYSTEMS; CHILD-MORTALITY; HEALTH; AGINCOURT; AREA; MIGRATION; INFANT; DEATH;
D O I
10.3402/gha.v6i0.19239
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: There is a lack of reliable data in developing countries to inform policy and optimise resource allocation. Health and socio-demographic surveillance sites (HDSS) have the potential to address this gap. Mortality levels and trends have previously been documented in rural South Africa. However, complex space-time clustering of mortality, determinants, and their impact has not been fully examined. Objectives: To integrate advanced methods enhance the understanding of the dynamics of mortality in space-time, to identify mortality risk factors and population attributable impact, to relate disparities in risk factor distributions to spatial mortality risk, and thus, to improve policy planning and resource allocation. Methods: Agincourt HDSS supplied data for the period 1992-2008. Advanced spatial techniques were used to identify significant age-specific mortality 'hotspots' in space-time. Multivariable Bayesian models were used to assess the effects of the most significant covariates on mortality. Disparities in risk factor profiles in identified hotspots were assessed. Results: Increasing HIV-related mortality and a subsequent decrease possibly attributable to antiretroviral therapy introduction are evident in this rural population. Distinct space-time clustering and variation (even in a small geographic area) of mortality were observed. Several known and novel risk factors were identified, and population impact was quantified. Significant differences in the risk factor profiles of the identified 'hotspots' included ethnicity; maternal, partner, and household deaths; household head demographics; migrancy; education; and poverty. Conclusions: A complex interaction of highly attributable multilevel factors continues to demonstrate differential space-time influences on mortality risk (especially for HIV). High-risk households and villages displayed differential risk factor profiles. This integrated approach could prove valuable to decision makers. Tailored interventions for specific child and adult high-risk mortality areas are needed, such as preventing vertical transmission, ensuring maternal survival, and improving water and sanitation infrastructure. This framework can be applied in other settings within the region.
引用
收藏
页码:27 / 37
页数:11
相关论文
共 44 条
[1]   Spatial risk for gender-specific adult mortality in an area of southern China [J].
Ali, Mohammad ;
Jin, Yang ;
Kim, Deok Ryun ;
De, Zhou Bao ;
Park, Jin Kyung ;
Ochiai, Rion Leon ;
Dong, Baiqing ;
Clemens, John D. ;
Acosta, Camilo J. .
INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS, 2007, 6 (1)
[2]  
[Anonymous], 2004, A life course approach to chronic disease epidemiology
[3]  
[Anonymous], 1999, WINBUGS VERSION 1 2
[4]  
[Anonymous], 2011, Stata statistical software: Release 12
[5]  
Becher H, 2004, B WORLD HEALTH ORGAN, V82, P265
[6]   A comparison of Bayesian spatial models for disease mapping [J].
Best, N ;
Richardson, S ;
Thomson, A .
STATISTICAL METHODS IN MEDICAL RESEARCH, 2005, 14 (01) :35-59
[7]  
Bradshaw D, 2000, INT C AIDS 2000 DURB
[8]   Bayesian spatial analysis and disease mapping: tools to enhance planning and implementation of a schistosomiasis control programme in Tanzania [J].
Clements, ACA ;
Lwambo, NJS ;
Blair, L ;
Nyandindi, U ;
Kaatano, G ;
Kinung'hi, S ;
Webster, JP ;
Fenwick, A ;
Brooker, S .
TROPICAL MEDICINE & INTERNATIONAL HEALTH, 2006, 11 (04) :490-503
[9]   Changing patterns of infectious disease [J].
Cohen, ML .
NATURE, 2000, 406 (6797) :762-767
[10]  
Collinson M.A., 2006, Africa on the Move: African Migration and Urbanisation in Comparative Perspective, P194, DOI DOI 10.1080/14034950701356401