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A spatial analysis of childhood mortality in West Africa

Identifieur interne : 000F74 ( Main/Exploration ); précédent : 000F73; suivant : 000F75

A spatial analysis of childhood mortality in West Africa

Auteurs : Deborah Balk [États-Unis] ; Thomas Pullum [États-Unis] ; Adam Storeygard [États-Unis] ; Fern Greenwell [États-Unis] ; Melissa Neuman [États-Unis]

Source :

RBID : ISTEX:3C1DCAC56B41F6C5935AC298BBDF52FB6DED5106

Descripteurs français

English descriptors

Abstract

It is suggested that environmental or geographical factors (e.g. population density, climate and disease environment) play an important role in determining infant and child survival above and beyond that played by individual and household level factors. Only recently, however, have relevant spatial data become available and have demographic survey data systematically recorded geographical location of surveyed households, or has the technology to integrate these data become accessible. This study estimates the risk of infant and child death in ten West African countries attributable to individual, household and spatially explicit geographical factors; 120,000 births occurring in the 10 years prior to the 1997–2001 Demographic and Health Survey dates are evaluated. Results from a generalised linear model show that spatial variables explain away a good deal of the country‐specific variation in mortality, and that they are associated with (and may be mediated by) the household characteristics. Implications for research and policy are addressed. Copyright © 2004 John Wiley & Sons, Ltd.

Url:
DOI: 10.1002/psp.328


Affiliations:


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Le document en format XML

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<term>Environmental characteristics</term>
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<term>Excess rain</term>
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<term>Higher rainfall</term>
<term>Higher risk</term>
<term>Higher risks</term>
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<term>Household characteristics</term>
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<term>International earth science information network</term>
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<term>John wiley sons</term>
<term>Last column</term>
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<term>Malaria</term>
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<term>Mapping agency</term>
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<term>More education</term>
<term>Mortality</term>
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<term>Mortality experience</term>
<term>Mortality outcomes</term>
<term>Mortality rates</term>
<term>Mosley</term>
<term>Mother mother</term>
<term>Multiple birth</term>
<term>Multiple birth birth</term>
<term>Multiple births</term>
<term>Multivariate</term>
<term>Multivariate analysis</term>
<term>Multivariate model</term>
<term>National research council</term>
<term>Nations environment programme</term>
<term>Nations world food programme</term>
<term>Nearest point</term>
<term>Niger</term>
<term>Niger surveys</term>
<term>Notable exceptions</term>
<term>Numerous studies</term>
<term>Older children</term>
<term>Older mothers</term>
<term>Optimal category</term>
<term>Optimal farming system</term>
<term>Other factors</term>
<term>Other sources</term>
<term>Other variables</term>
<term>Overall effect</term>
<term>Percentile</term>
<term>Phnom penh</term>
<term>Place density</term>
<term>Popul</term>
<term>Population data</term>
<term>Population density</term>
<term>Population geography</term>
<term>Population studies</term>
<term>Preliminary analysis</term>
<term>Present analysis</term>
<term>Primary education</term>
<term>Principe gabon figure</term>
<term>Probability models</term>
<term>Programme</term>
<term>Proximate</term>
<term>Proximate determinants</term>
<term>Proximate factors</term>
<term>Public health</term>
<term>Quintile</term>
<term>Rainfall</term>
<term>Recent survey</term>
<term>Recent time period</term>
<term>Reference category</term>
<term>Reference combination</term>
<term>Reference country</term>
<term>Refrigerator education</term>
<term>Relative risk</term>
<term>Residual effects</term>
<term>Rural areas</term>
<term>Sahara algeria mauritania niger mali chad senegal</term>
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<term>Second quintile</term>
<term>Secondary schooling</term>
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<term>Subsaharan africa</term>
<term>Subsequent birth interval</term>
<term>Subsequent models</term>
<term>Survey clusters</term>
<term>Survey countries</term>
<term>Survey region</term>
<term>Survival analysis</term>
<term>Survival chances</term>
<term>Survival curves</term>
<term>Survival density functions</term>
<term>Survival distributions</term>
<term>Survival models</term>
<term>Systems analysis</term>
<term>Time period</term>
<term>Togo</term>
<term>Toilet facilities</term>
<term>Toilet type</term>
<term>Total deviance</term>
<term>Tree crops</term>
<term>Tropical medicine</term>
<term>Urban area</term>
<term>Urban areas</term>
<term>Urban density</term>
<term>Urban distance</term>
<term>Urban extents</term>
<term>Urban residence</term>
<term>Water surface water</term>
<term>Water type</term>
<term>Water water</term>
<term>West africa</term>
<term>Wiley</term>
<term>World health organization</term>
<term>Worst category</term>
<term>Worst combination</term>
<term>Young mothers</term>
</keywords>
<keywords scheme="Wicri" type="geographic" xml:lang="fr">
<term>Bénin</term>
<term>Cameroun</term>
<term>Ghana</term>
<term>Guinée</term>
<term>Mali</term>
<term>Niger</term>
<term>Sénégal</term>
<term>Togo</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr">
<term>Production agricole</term>
<term>Zone aride</term>
<term>Changement climatique</term>
<term>Droit d'auteur</term>
<term>Base de données</term>
<term>Eau potable</term>
<term>Développement économique</term>
<term>Planification de la famille</term>
<term>Système d'exploitation agricole</term>
<term>Enseignement supérieur</term>
<term>Mortalité infantile</term>
<term>Mortalité</term>
<term>Densité de population</term>
<term>Enseignement primaire</term>
<term>Santé publique</term>
<term>Zone urbaine</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">It is suggested that environmental or geographical factors (e.g. population density, climate and disease environment) play an important role in determining infant and child survival above and beyond that played by individual and household level factors. Only recently, however, have relevant spatial data become available and have demographic survey data systematically recorded geographical location of surveyed households, or has the technology to integrate these data become accessible. This study estimates the risk of infant and child death in ten West African countries attributable to individual, household and spatially explicit geographical factors; 120,000 births occurring in the 10 years prior to the 1997–2001 Demographic and Health Survey dates are evaluated. Results from a generalised linear model show that spatial variables explain away a good deal of the country‐specific variation in mortality, and that they are associated with (and may be mediated by) the household characteristics. Implications for research and policy are addressed. Copyright © 2004 John Wiley & Sons, Ltd.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>États-Unis</li>
</country>
<region>
<li>Texas</li>
<li>État de New York</li>
</region>
<settlement>
<li>Austin (Texas)</li>
<li>New York</li>
</settlement>
<orgName>
<li>Université Columbia</li>
<li>Université du Texas à Austin</li>
</orgName>
</list>
<tree>
<country name="États-Unis">
<region name="État de New York">
<name sortKey="Balk, Deborah" sort="Balk, Deborah" uniqKey="Balk D" first="Deborah" last="Balk">Deborah Balk</name>
</region>
<name sortKey="Balk, Deborah" sort="Balk, Deborah" uniqKey="Balk D" first="Deborah" last="Balk">Deborah Balk</name>
<name sortKey="Greenwell, Fern" sort="Greenwell, Fern" uniqKey="Greenwell F" first="Fern" last="Greenwell">Fern Greenwell</name>
<name sortKey="Neuman, Melissa" sort="Neuman, Melissa" uniqKey="Neuman M" first="Melissa" last="Neuman">Melissa Neuman</name>
<name sortKey="Pullum, Thomas" sort="Pullum, Thomas" uniqKey="Pullum T" first="Thomas" last="Pullum">Thomas Pullum</name>
<name sortKey="Storeygard, Adam" sort="Storeygard, Adam" uniqKey="Storeygard A" first="Adam" last="Storeygard">Adam Storeygard</name>
</country>
</tree>
</affiliations>
</record>

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