Introducing a quantitative method to calculate the rate of primary infertility.

• Main Authors: Mm Akhondi (Author), K Kamali (Author), F Ranjbar (Author), S Shafeghati (Author), Z Behjati Ardakani (Author), M Shirzad (Author), M Eslamifar (Author), K Mohammad (Author), M Parsaeian (Author)
• Format: Book
• Published: Tehran University of Medical Sciences, 2012-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2251-6085; 2251-6093
• Keywords: Iran; Primary infertility rate; Reproductive history; Public aspects of medicine; RA1-1270
• Source: Iranian Journal of Public Health, Vol 41, Iss 12 (2012)

In the previous studies, the rate of primary infertility was reported differently. It seems the main reasons are related to the different methods of data collection and information analysis. Therefore, introducing a precise method to determine the infertile couples and the population exposed to the risk of infertility is an important issue to study primary infertility.The proposed methodology for assessing primary infertility rate has been designed and applied by Avicenna Research Institute in a national survey. Sampling was conducted based on probability proportional to size cluster method. In this survey, after reviewing the former studies, the reproductive history was used as a basis for data collection. Every reproductive event was recorded with a code and a date in the questionnaire. To introduce a precise method, all possible events were considered thoroughly and for each situation, it was determined whether these cases should be considered in numerator, denominator or it should be eliminated from the study. Also in some situations where the correct diagnosis of infertility was not possible, a sensitivity analysis was recommended to see the variability of results under different scenarios.The proposed methodology can precisely define the infertile women and the population exposed to the risk of infertility. So, this method is more accurate than other available data collection strategies. To avoid bias and make a consistent methodology, using this method is recommended in future prevalence studies.