Journal of Biosocial Science

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Regular Articles

SKEWED CONTRACEPTIVE METHOD MIX: WHY IT HAPPENS, WHY IT MATTERS


TARA M.  SULLIVAN  a1 , JANE T.  BERTRAND  a1 , JANET  RICE  a2 and JAMES D.  SHELTON  a3
a1 Center for Communication Programs, Johns Hopkins Bloomberg School of Public Health
a2 Department of Biostatistics, Tulane University School of Public Health and Tropical Medicine
a3 Office of Population and Reproductive Health, United States Agency for International Development

Article author query
sullivan tm   [PubMed][Google Scholar] 
bertrand jt   [PubMed][Google Scholar] 
rice j   [PubMed][Google Scholar] 
shelton jd   [PubMed][Google Scholar] 

Abstract

Contraceptive prevalence has been central to family planning research over the past few decades, but researchers have given surprisingly little consideration to method mix, a proxy for method availability or choice. There is no ‘ideal’ method mix recognized by the international community; however, there may be reason for concern when one or two methods predominate in a given country. In this article method skew is operationally defined as a single method constituting 50% or more of contraceptive use in a given country. Of 96 countries examined in this analysis, 34 have this type of skewed method mix. These 34 countries cluster in three groups: (1) sixteen countries in which traditional methods dominate, most of which are in sub-Saharan Africa; (2) four countries in which female sterilization predominates (India, Brazil, Dominican Republic and Panama); and (3) fourteen countries that rely on a single reversible method (the pill in Algeria, Kuwait, Liberia, Morocco, Sudan and Zimbabwe; the IUD in Cuba, Egypt, Kazakhstan, Kyrgyz Republic, Moldova, Turkmenistan and Uzbekistan; and the injectable in Malawi). A review of available literature on method choice in these countries provides substantial insight into the different patterns of method skew. Method skew in some countries reflects cultural preferences or social norms. Yet it becomes problematic if it stems from restrictive population policies, lack of access to a broad range of methods, or provider bias.

(Published Online August 23 2005)