Understanding Unmet Need

History, Theory, and Measurement

Datos Bibliográficos

ID10796591
AutoresSarah E K Bradley (0000-0002-5441-5223, University of California, Berkeley), Sarah E Bradley (0000-0003-0233-5851, International Computer Science Institute, autor de correspondencia), John B Casterline (0000-0002-0058-9973, Robert T. Lazarus Professor in Population Studies, Department of Sociology, Ohio State University.)
Año2014
Volumen45
Número2
Páginas123-150
Fecha de publicación2014-06-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaStudies in Family Planning (JOURNAL)
Identificadores de la revistaISSN: 0039-3665 • E-ISSN: 1728-4465
EditorialWiley (PUBLISHER • GB)
DOI10.1111/j.1728-4465.2014.00381.x
PMID24931072
PMCIDPMC4369378
OpenAlexW2063853887
IdiomaEN
Citas recibidas50
Referencias citadas27

During the past two decades, estimates of unmet need have become an influential measure for assessing population policies and programs. This article recounts the evolution of the concept of unmet need, describes how demographic survey data have been used to generate estimates of its prevalence, and tests the sensitivity of these estimates to various assumptions in the unmet need algorithm. The algorithm uses a complex set of assumptions to identify women: who are sexually active, who are infecund, whose most recent pregnancy was unwanted, who wish to postpone their next birth, and who are postpartum amenorrheic. The sensitivity tests suggest that defensible alternative criteria for identifying four out of five of these subgroups of women would increase the estimated prevalence of unmet need. The exception is identification of married women who are sexually active; more accurate measurement of this subgroup would reduce the estimated prevalence of unmet need in most settings

Environmental health · Family medicine · Family planning · Identification (biology · Population · Research methodology · Sexually active · Sociology · Demographic Trends and Gender Preferences · Demography · Gender, Labor, and Family Dynamics · Global Maternal and Child Health · Medicine · Gerontology