dc.contributor.author
Pezzulo, Carla
dc.contributor.author
Nilsen, Kristine
dc.contributor.author
Carioli, Alessandra
dc.contributor.author
Tejedor-Garavito, Natalia
dc.contributor.author
Hanspal, Sophie E.
dc.contributor.author
Hilber, Theodor
dc.contributor.author
James, William H. M.
dc.contributor.author
Ruktanonchai, Corrine W.
dc.contributor.author
Alegana, Victor
dc.contributor.author
Sorichetta, Alessandro
dc.date.accessioned
2021-07-26T10:53:00Z
dc.date.available
2021-07-26T10:53:00Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/31397
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-31130
dc.description.abstract
Background
Understanding subnational variation in age-specific fertility rates (ASFRs) and total fertility rates (TFRs), and geographical clustering of high fertility and its determinants in low-income and middle-income countries, is increasingly needed for geographical targeting and prioritising of policy. We aimed to identify variation in fertility rates, to describe patterns of key selected fertility determinants in areas of high fertility.
Methods
We did a subnational analysis of ASFRs and TFRs from the most recent publicly available and nationally representative cross-sectional Demographic and Health Surveys and Multiple Indicator Cluster Surveys collected between 2010 and 2016 for 70 low-income, lower-middle-income, and upper-middle-income countries, across 932 administrative units. We assessed the degree of global spatial autocorrelation by using Moran's I statistic and did a spatial cluster analysis using the Getis-Ord Gi* local statistic to examine the geographical clustering of fertility and key selected fertility determinants. Descriptive analysis was used to investigate the distribution of ASFRs and of selected determinants in each cluster.
Findings
TFR varied from below replacement (2·1 children per women) in 36 of the 932 subnational regions (mainly located in India, Myanmar, Colombia, and Armenia), to rates of 8 and higher in 14 subnational regions, located in sub-Saharan Africa and Afghanistan. Areas with high-fertility clusters were mostly associated with areas of low prevalence of women with secondary or higher education, low use of contraception, and high unmet needs for family planning, although exceptions existed.
Interpretation
Substantial within-country variation in the distribution of fertility rates highlights the need for tailored programmes and strategies in high-fertility cluster areas to increase the use of contraception and access to secondary education, and to reduce unmet need for family planning.
en
dc.format.extent
11 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
age-specific fertility rates
en
dc.subject
total fertility rates
en
dc.subject
fertility determinants
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie
dc.title
Geographical distribution of fertility rates in 70 low-income, lower-middle-income, and upper-middle-income countries, 2010–16: a subnational analysis of cross-sectional surveys
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1016/S2214-109X(21)00082-6
dcterms.bibliographicCitation.journaltitle
The Lancet Global Health
dcterms.bibliographicCitation.number
6
dcterms.bibliographicCitation.pagestart
E802
dcterms.bibliographicCitation.pageend
E812
dcterms.bibliographicCitation.volume
9
dcterms.bibliographicCitation.url
https://doi.org/10.1016/S2214-109X(21)00082-6
refubium.affiliation
Geowissenschaften
refubium.affiliation.other
Institut für Geographische Wissenschaften / Centre for Development Studies (ZELF)
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
2214-109X
refubium.resourceType.provider
WoS-Alert