Consanguineous marriages in Afghanistan

J Biosoc Sci. 2012 Jan;44(1):73-81. doi: 10.1017/S0021932011000253. Epub 2011 Jun 9.


The present cross-sectional study was done in order to illustrate the prevalence and types of consanguineous marriages among Afghanistan populations. Data on types of marriages were collected using a simple questionnaire. The total number of couples in the study was 7140 from the following provinces: Badakhshan, Baghlan, Balkh, Bamyan, Kabul, Kunduz, Samangan and Takhar. Consanguineous marriages were classified by the degree of relationship between couples: double first cousins, first cousins, first cousins once removed, second cousins and beyond second cousins. The coefficient of inbreeding (F) was calculated for each couple and the mean coefficient of inbreeding (α) estimated for each population. The proportion of consanguineous marriages in the country was 46.2%, ranging from 38.2% in Kabul province to 51.2% in Bamyan province. The equivalent mean inbreeding coefficient (α) was 0.0277, and ranged from 0.0221 to 0.0293 in these two regions. There were significant differences between provinces for frequencies of different types of marriages (p<0.001). First cousin marriages (27.8%) were the most common type of consanguineous marriages, followed by double first cousin (6.9%), second cousin (5.8%), beyond second cousin (3.9%) and first cousin once removed (1.8%). There were significant differences between ethnic groups for the types of marriages (χ2=177.6, df=25, p<0.001). Tajiks (Soni) and Turkmens (also Pashtuns) showed the lowest (α=0.0250) and highest (α=0.0297) mean inbreeding coefficients, respectively, among the ethnic groups in Afghanistan. The study shows that Afghanistan's populations, like other Islamic populations, have a high level of consanguinity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Afghanistan
  • Chi-Square Distribution
  • Consanguinity*
  • Cross-Sectional Studies
  • Ethnicity
  • Female
  • Humans
  • Male
  • Marriage / statistics & numerical data*
  • Prevalence
  • Rural Population
  • Statistics as Topic
  • Surveys and Questionnaires
  • Urban Population