| 1. |
- Coates, Matthew M., et al.
(författare)
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A comparison of all-cause and cause-specific mortality by household socioeconomic status across seven INDEPTH network health and demographic surveillance systems in sub-Saharan Africa
- 2019
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Ingår i: Global Health Action. - : Taylor & Francis Group. - 1654-9716 .- 1654-9880. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Understanding socioeconomic disparities in all-cause and cause-specific mortality can help inform prevention and treatment strategies.Objectives: To quantify cause-specific mortality rates by socioeconomic status across seven health and demographic surveillance systems (HDSS) in five countries (Ethiopia, Kenya, Malawi, Mozambique, and Nigeria) in the INDEPTH Network in sub-Saharan Africa.Methods: We linked demographic residence data with household survey data containing living standards and education information we used to create a poverty index. Person-years lived and deaths between 2003 and 2016 (periods varied by HDSS) were stratified in each HDSS by age, sex, year, and number of deprivations on the poverty index (0-8). Causes of death were assigned to each death using the InterVA-4 model based on responses to verbal autopsy questionnaires. We estimated rate ratios between socioeconomic groups (2-4 and 5-8 deprivations on our poverty index compared to 0-2 deprivations) for specific causes of death and calculated life expectancy for the deprivation groups.Results: Our pooled data contained almost 3.5 million person-years of observation and 25,038 deaths. All-cause mortality rates were higher among people in households with 5-8 deprivations on our poverty index compared to 0-2 deprivations, controlling for age, sex, and year (rate ratios ranged 1.42 to 2.06 across HDSS sites). The poorest group had consistently higher death rates in communicable, maternal, neonatal, and nutritional conditions (rate ratios ranged 1.34-4.05) and for non-communicable diseases in several sites (1.14-1.93). The disparities in mortality between 5-8 deprivation groups and 0-2 deprivation groups led to lower life expectancy in the higher-deprivation groups by six years in all sites and more than 10 years in five sites.Conclusions: We show large disparities in mortality on the basis of socioeconomic status across seven HDSS in sub-Saharan Africa due to disparities in communicable disease mortality and from non-communicable diseases in some sites. Life expectancy gaps between socioeconomic groups within sites were similar to the gaps between high-income and lower-middle-income countries. Prevention and treatment efforts can benefit from understanding subpopulations facing higher mortality from specific conditions.
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| 2. |
- Gomez-Olive, Francesc Xavier, et al.
(författare)
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Variations in disability and quality of life with age and sex between eight lower income and middle-income countries : data from the INDEPTH WHO-SAGE collaboration
- 2017
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Ingår i: BMJ Global Health. - : BMJ Publishing Group Ltd. - 2059-7908. ; 2:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: Disability and quality of life are key outcomes for older people. Little is known about how these measures vary with age and gender across lower income and middle-income countries; such information is necessary to tailor health and social care policy to promote healthy ageing and minimise disability.Methods: We analysed data from participants aged 50 years and over from health and demographic surveillance system sites of the International Network for the Demographic Evaluation of Populations and their Health Network in Ghana, Kenya, Tanzania, South Africa, Vietnam, India, Indonesia and Bangladesh, using an abbreviated version of the WHO Study on global AGEing survey instrument. We used the eight-item WHO Quality of Life (WHOQoL) tool to measure quality of life and theWHO Disability Assessment Schedule, version 2 (WHODAS-II) tool to measure disability. We collected selected health status measures via the survey instrument and collected demographic and socioeconomic data from linked surveillance site information. We performed regression analyses to quantify differences between countries in the relationship between age, gender and both quality of life and disability, and we used anchoring vignettes to account for differences in interpretation of disability severity.Results: We included 43 935 individuals in the analysis. Mean age was 63.7 years (SD 9.7) and 24 434 (55.6%) were women. In unadjusted analyses across all countries, WHOQoL scores worsened by 0.13 points (95% CI 0.12 to 0.14) per year increase in age and WHODAS scores worsened by 0.60 points (95% CI 0.57 to 0.64). WHODAS-II and WHOQoL scores varied markedly between countries, as did the gradient of scores with increasing age. In regression analyses, differences were not fully explained by age, socioeconomic status, marital status, education or health factors. Differences in disability scores between countries were not explained by differences in anchoring vignette responses.Conclusions: The relationship between age, sex and both disability and quality of life varies between countries. The findings may guide tailoring of interventions to individual country needs, although these associations require further study.
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| 3. |
- Streatfield, P Kim, et al.
(författare)
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Mortality from external causes in Africa and Asia : evidence from INDEPTH Health and Demographic Surveillance System Sites
- 2014
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Ingår i: Global Health Action. - : CoAction Publishing. - 1654-9716 .- 1654-9880. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Mortality from external causes, of all kinds, is an important component of overall mortality on a global basis. However, these deaths, like others in Africa and Asia, are often not counted or documented on an individual basis. Overviews of the state of external cause mortality in Africa and Asia are therefore based on uncertain information. The INDEPTH Network maintains longitudinal surveillance, including cause of death, at population sites across Africa and Asia, which offers important opportunities to document external cause mortality at the population level across a range of settings.OBJECTIVE: To describe patterns of mortality from external causes at INDEPTH Network sites across Africa and Asia, according to the WHO 2012 verbal autopsy (VA) cause categories.DESIGN: All deaths at INDEPTH sites are routinely registered and followed up with VA interviews. For this study, VA archives were transformed into the WHO 2012 VA standard format and processed using the InterVA-4 model to assign cause of death. Routine surveillance data also provide person-time denominators for mortality rates.RESULTS: A total of 5,884 deaths due to external causes were documented over 11,828,253 person-years. Approximately one-quarter of those deaths were to children younger than 15 years. Causes of death were dominated by childhood drowning in Bangladesh, and by transport-related deaths and intentional injuries elsewhere. Detailed mortality rates are presented by cause of death, age group, and sex.CONCLUSIONS: The patterns of external cause mortality found here generally corresponded with expectations and other sources of information, but they fill some important gaps in population-based mortality data. They provide an important source of information to inform potentially preventive intervention designs.
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| 7. |
- Bocquier, Philippe, et al.
(författare)
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Are health and demographic surveillance system estimates sufficiently generalisable?
- 2017
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Ingår i: Global Health Action. - : Taylor & Francis. - 1654-9716 .- 1654-9880. ; 10:1, s. 1-3
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Tidskriftsartikel (refereegranskat)abstract
- Sampling rules do not apply in a Health and Demographic Surveillance System (HDSS) that covers exhaustively a district-level population and is not meant to be representative of a national population. We highlight the advantages of HDSS data for causal analysis and identify in the literature the principles of conditional generalisation that best apply to HDSS. A probabilistic view on HDSS data is still justified by the need to model complex causal inference. Accounting for contextual knowledge, reducing omitted-variable bias, detailing order of events, and high statistical power brings credence to HDSS data. Generalisation of causal mechanisms identified in HDSS data is consolidated through systematic comparison and triangulation with national or international data.
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| 8. |
- Byass, Peter, et al.
(författare)
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Comparing verbal autopsy cause of death findings as determined by physician coding and probabilistic modelling : a public health analysis of 54 000 deaths in Africa and Asia
- 2015
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Ingår i: Journal of Global Health. - 2047-2978 .- 2047-2986. ; 5:1, s. 65-73
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Coverage of civil registration and vital statistics varies globally, with most deaths in Africa and Asia remaining either unregistered or registered without cause of death. One important constraint has been a lack of fit-for-purpose tools for registering deaths and assigning causes in situations where no doctor is involved. Verbal autopsy (interviewing care-givers and witnesses to deaths and interpreting their information into causes of death) is the only available solution. Automated interpretation of verbal autopsy data into cause of death information is essential for rapid, consistent and affordable processing.METHODS: Verbal autopsy archives covering 54 182 deaths from five African and Asian countries were sourced on the basis of their geographical, epidemiological and methodological diversity, with existing physician-coded causes of death attributed. These data were unified into the WHO 2012 verbal autopsy standard format, and processed using the InterVA-4 model. Cause-specific mortality fractions from InterVA-4 and physician codes were calculated for each of 60 WHO 2012 cause categories, by age group, sex and source. Results from the two approaches were assessed for concordance and ratios of fractions by cause category. As an alternative metric, the Wilcoxon matched-pairs signed ranks test with two one-sided tests for stochastic equivalence was used.FINDINGS: The overall concordance correlation coefficient between InterVA-4 and physician codes was 0.83 (95% CI 0.75 to 0.91) and this increased to 0.97 (95% CI 0.96 to 0.99) when HIV/AIDS and pulmonary TB deaths were combined into a single category. Over half (53%) of the cause category ratios between InterVA-4 and physician codes by source were not significantly different from unity at the 99% level, increasing to 62% by age group. Wilcoxon tests for stochastic equivalence also demonstrated equivalence.CONCLUSIONS: These findings show strong concordance between InterVA-4 and physician-coded findings over this large and diverse data set. Although these analyses cannot prove that either approach constitutes absolute truth, there was high public health equivalence between the findings. Given the urgent need for adequate cause of death data from settings where deaths currently pass unregistered, and since the WHO 2012 verbal autopsy standard and InterVA-4 tools represent relatively simple, cheap and available methods for determining cause of death on a large scale, they should be used as current tools of choice to fill gaps in cause of death data.
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| 9. |
- Byass, Peter, et al.
(författare)
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Lessons from History for Designing and Validating Epidemiological Surveillance in Uncounted Populations
- 2011
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:8, s. e22897-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Due to scanty individual health data in low- and middle-income countries (LMICs), health planners often use imperfect data sources. Frequent national-level data are considered essential, even if their depth and quality are questionable. However, quality in-depth data from local sentinel populations may be better than scanty national data, if such local data can be considered as nationally representative. The difficulty is the lack of any theoretical or empirical basis for demonstrating that local data are representative where data on the wider population are unavailable. Thus these issues can only be explored empirically in a complete individual dataset at national and local levels, relating to a LMIC population profile. Methods and Findings: Swedish national data for 1925 were used, characterised by relatively high mortality, a low proportion of older people and substantial mortality due to infectious causes. Demographic and socioeconomic characteristics of Sweden then and LMICs now are very similar. Rates of livebirths, stillbirths, infant and cause-specific mortality were calculated at national and county levels. Results for six million people in 24 counties showed that most counties had overall mortality rates within 10% of the national level. Other rates by county were mostly within 20% of national levels. Maternal mortality represented too rare an event to give stable results at the county level. Conclusions: After excluding obviously outlying counties (capital city, island, remote areas), any one of the remaining 80% closely reflected the national situation in terms of key demographic and mortality parameters, each county representing approximately 5% of the national population. We conclude that this scenario would probably translate directly to about 40 LMICs with populations under 10 million, and to individual states or provinces within about 40 larger LMICs. Unsubstantiated claims that local sub-national population data are "unrepresentative" or "only local" should not therefore predominate over likely representativity.
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