scholarly journals Child anthropometry data quality from Demographic and Health Surveys, Multiple Indicator Cluster Surveys, and National Nutrition Surveys in the West Central Africa region: are we comparing apples and oranges?

2018 ◽  
Vol 11 (1) ◽  
pp. 1444115 ◽  
Author(s):  
Daniel J. Corsi ◽  
Jessica M. Perkins ◽  
S. V. Subramanian
Keyword(s):  
Data Quality ◽  
Health Surveys ◽  
Central Africa ◽  
Demographic And Health Surveys ◽  
The West ◽  
Nutrition Surveys ◽  
West Central ◽  
Multiple Indicator

scholarly journals Four decades of measuring stillbirths and neonatal deaths in Demographic and Health Surveys: historical review

2021 ◽  
Vol 19 (S1) ◽  
Author(s):  
Joseph Akuze ◽  
Simon Cousens ◽  
Joy E. Lawn ◽  
Peter Waiswa ◽  
Vladimir Sergeevich Gordeev ◽  
...  
Keyword(s):  
Data Quality ◽  
Health Surveys ◽  
Historical Review ◽  
Quality Criteria ◽  
Demographic And Health Surveys ◽  
Household Surveys ◽  
Middle Income ◽  
Neonatal Deaths ◽  
Live Births ◽  
Over Time

Abstract Background Worldwide, an estimated 5.1 million stillbirths and neonatal deaths occur annually, 98% in low- and middle-income countries. Limited coverage of civil and vital registration systems necessitates reliance on women’s retrospective reporting in household surveys for data on these deaths. The predominant platform, Demographic and Health Surveys (DHS), has evolved over the last 35 years and differs by country, yet no previous study has described these differences and the effects of these changes on stillbirth and neonatal death measurement. Methods We undertook a review of DHS model questionnaires, protocols and methodological reports from DHS-I to DHS-VII, focusing on the collection of information on stillbirth and neonatal deaths describing differences in approaches, questionnaires and geographic reach up to December 9, 2019. We analysed the resultant data, applied previously used data quality criteria including ratios of stillbirth rate (SBR) to neonatal mortality rate (NMR) and early NMR (ENMR) to NMR, comparing by country, over time and by DHS module. Results DHS has conducted >320 surveys in 90 countries since 1984. Two types of maternity history have been used: full birth history (FBH) and full pregnancy history (FPH). A FBH collecting information only on live births has been included in all model questionnaires to date, with data on stillbirths collected through a reproductive calendar (DHS II-VI) or using additional questions on non-live births (DHS-VII). FPH collecting information on all pregnancies including live births, miscarriages, abortions and stillbirths has been used in 17 countries. We found no evidence of variation in stillbirth data quality assessed by SBR:NMR over time for FBH surveys with reproductive calendar, some variation for surveys with FBH in DHS-VII and most variation among the surveys conducted with a FPH. ENMR:NMR ratio increased over time, which may reflect changes in data quality or real epidemiological change. Conclusion DHS remains the major data source for pregnancy outcomes worldwide. Although the DHS model questionnaire has evolved over the last three and half decades, more robust evidence is required concerning optimal methods to obtain accurate data on stillbirths and neonatal deaths through household surveys and also to develop and test standardised data quality criteria.

scholarly journals Prenatal care coverage and correlates of HIV testing in sub-Saharan Africa: Insight from demographic and health surveys of 16 countries

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242001
Author(s):  
Oluwafemi Emmanuel Awopegba ◽  
Amarachi Kalu ◽  
Bright Opoku Ahinkorah ◽  
Abdul-Aziz Seidu ◽  
Anthony Idowu Ajayi
Keyword(s):  
Prenatal Care ◽  
Pregnant Women ◽  
Hiv Testing ◽  
Health Surveys ◽  
Central Africa ◽  
Sub Saharan Africa ◽  
Demographic And Health Surveys ◽  
West And Central Africa ◽  
Sub Saharan ◽  
Ssa Countries

Background Prenatal screening of pregnant women for HIV is central to eliminating mother-to-child-transmission (MTCT) of HIV. While some countries in sub-Saharan Africa (SSA) have scaled up their prevention of MTCT programmes, ensuring a near-universal prenatal care HIV testing, and recording a significant reduction in new infection among children, several others have poor outcomes due to inadequate testing. We conducted a multi-country analysis of demographic and health surveys (DHS) to assess the coverage of HIV testing during pregnancy and also examine the factors associated with uptake. Methods We analysed data of 64,933 women from 16 SSA countries with recent DHS datasets (2015–2018) using Stata version 16. Adjusted and unadjusted logistic regression models were used to examine correlates of prenatal care uptake of HIV testing. Statistical significance was set at p<0.05. Results Progress in scaling up of prenatal care HIV testing was uneven across SSA, with only 6.1% of pregnant women tested in Chad compared to 98.1% in Rwanda. While inequality in access to HIV testing among pregnant women is pervasive in most SSA countries and particularly in West and Central Africa sub-regions, a few countries, including Rwanda, South Africa, Zimbabwe, Malawi and Zambia have managed to eliminate wealth and rural-urban inequalities in access to prenatal care HIV testing. Conclusion Our findings highlight the between countries and sub-regional disparities in prenatal care uptake of HIV testing in SSA. Even though no country has universal coverage of prenatal care HIV testing, East and Southern African regions have made remarkable progress towards ensuring no pregnant woman is left untested. However, the West and Central Africa regions had low coverage of prenatal care testing, with the rich and well educated having better access to testing, while the poor rarely tested. Addressing the inequitable access and coverage of HIV testing among pregnant women is vital in these sub-regions.

scholarly journals Using DHS and MICS data to complement or replace NGO baseline health data: an exploratory study

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 69
Author(s):  
Peter R. Berti ◽  
Milena Nardocci ◽  
Minh Hung Tran ◽  
Malek Batal ◽  
Rebecca Brodmann ◽  
...  
Keyword(s):  
Health Surveys ◽  
Social Indicators ◽  
Absolute Difference ◽  
Baseline Survey ◽  
Demographic And Health Surveys ◽  
Government Organizations ◽  
Governmental Organizations ◽  
Non Governmental Organizations ◽  
Multiple Indicator ◽  
Yield Difference

Background: Non-government organizations (NGOs) spend substantial time and resources collecting baseline data in order to plan and implement health interventions with marginalized populations. Typically interviews with households, often mothers, take over an hour, placing a burden on the respondents. Meanwhile, estimates of numerous health and social indicators in many countries already exist in publicly available datasets, such as the Demographic and Health Surveys (DHS) and the Multiple Indicator Cluster Surveys (MICS), and it is worth considering whether these could serve as estimates of baseline conditions. The objective of this study was to compare indicator estimates from non-governmental organizations (NGO) health projects’ baseline reports with estimates calculated using the Demographic and Health Surveys (DHS) or the Multiple Indicator Cluster Surveys (MICS), matching for location, year, and season of data collection. Methods: We extracted estimates of 129 indicators from 46 NGO baseline reports, 25 DHS datasets and three MICS datasets, generating 1,996 pairs of matched DHS/MICS and NGO indicators. We subtracted NGO from DHS/MICS estimates to yield difference and absolute difference, exploring differences by indicator. We partitioned variance of the differences by geographical level, year, and season using ANOVA. Results: Differences between NGO and DHS/MICS estimates were large for many indicators but 33% fell within 5% of one another. Differences were smaller for indicators with prevalence <15% or >85%. Difference between estimates increased with increasing year and geographical level differences. However, <1% of the variance of the differences was explained by year, geographical level, and season. Conclusions: There are situations where publicly available data could complement NGO baseline survey data, most importantly when the NGO has tolerance for estimates of low or unknown accuracy.

THE IRON AGE IN WEST CENTRAL AFRICA: RADIOCARBON DATES FROM CORISCO ISLAND (EQUATORIAL GUINEA)

2016 ◽  
Vol 57 (3) ◽  
pp. 345-365
Author(s):  
MANUEL SÁNCHEZ-ELIPE LORENTE ◽  
ALFREDO GONZÁLEZ-RUIBAL ◽  
JESÚS F. JORDÁ PARDO ◽  
CARLOS MARÍN SUÁREZ
Keyword(s):  
Iron Age ◽  
Central Africa ◽  
Equatorial Guinea ◽  
The West ◽  
Radiocarbon Dates ◽  
West Central ◽  
Southern Cameroon ◽  
African Iron Age

AbstractOver the last few decades the number of radiocarbon dates available for West Central Africa has increased substantially, even though it is still meagre compared with other areas of the continent. In order to contribute to a better understanding of the Iron Age of this area we present and analyze a total of 22 radiocarbon dates obtained from sites from the island of Corisco (Equatorial Guinea). By comparing them with those from Equatorial Guinea, southern Cameroon, and coastal Gabon and Congo we intend to clarify the picture of the West Central African Iron Age and propose a more accurate archaeological sequence.

The States General and the Stadholder: Dutch Diplomatic Practices in the Atlantic World before the West India Company

2013 ◽  
Vol 3 (1) ◽  
pp. 43-58 ◽  
Author(s):  
Mark Meuwese
Keyword(s):  
South America ◽  
Foreign Relations ◽  
Atlantic World ◽  
Central Africa ◽  
Gold Coast ◽  
New Netherland ◽  
The West ◽  
West Central ◽  
Indigenous Groups ◽  
West India Company

After a discussion of the States General and the office of stadholder as the two key institutions of Dutch sovereignty in Dutch foreign relations, this article analyzes to what extent the two institutions were involved in Dutch diplomacy with non-European peoples in the Atlantic World before the founding of the West India Company in 1621. On the Gold Coast and in West-Central Africa, regions controlled by centralized states and shaped by the presence of Iberian colonizers, Dutch traders relied on the support of the States General and the stadholder to establish alliances. On the Wild Coast of South America and in New Netherland, uncontested regions dominated by decentralized Indigenous groups, Dutch merchants did not require the diplomatic support of the States General or the stadholder but instead established alliances based on local Indigenous protocol.

Slave Exports from West and West-Central Africa, 1700–1810: new estimates of volume and distribution

1989 ◽  
Vol 30 (1) ◽  
pp. 1-22 ◽  
Author(s):  
David Richardson
Keyword(s):  
Eighteenth Century ◽  
West Coast ◽  
Slave Trade ◽  
Central Africa ◽  
The West ◽  
Commodity Production ◽  
West Central ◽  
New Evidence ◽  
The Relationship ◽  
Demographic Effects

Using new evidence on the British, French and North American slave-carrying trades, this article seeks to revise Lovejoy's recently published estimates of the levels of slave exports from West and West-Central Africa in the eighteenth century. The figures suggest that Lovejoy's estimate of the total volume of slave exports from the west coast of Africa to America between 1700 and 1810 was probably reasonably accurate, being only 8 per cent lower than the total indicated here. However, the new data reveal temporal and coastal distributions of slave exports that differ substantially from those proposed by Lovejoy. In particular, they suggest that previous work significantly understated levels of slave exports between 1713 and 1740, and again in the 1760s and 1770s. Contrary to earlier findings, in fact, it appears that slave exports from the west coast of Africa to America in the decade prior to the War of American Independence were very similar to levels attained after 1783. Furthermore, in terms of coastal distributions, it seems that the Bight of Biafra and West-Central Africa, particularly the Loango coast, contributed much more substantially to the slave traffic to America during the early decades of the century than was previously assumed. These revisions of Lovejoy's figures have important implications for movements in slave prices in Africa and for assessing the demographic effects of the trade on the slave-supplying regions. In addition, they help to improve our understanding of the relationship between the slave trade and changes in sugar and other commodity production in America during the eighteenth century.

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