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Duration Since Marriage as a Determinant of Infertility in an Indian Scenario: Analysis Based on National Family
Anushri P Patil1, Naresh K Tyagi1, Hema S Patil2
1Department of Epidemiology and Biostatistics, Jawaharlal Nehru Medical College, KLE Academy of Higher Education and Research (Deemed to-be University), Belagavi, Karnataka, India.
Background:
The demographic definition of female infertility is a woman of reproductive age when she fails to conceive even after 5 years of unprotected sexual intercourse. The World Health Organization estimates the overall prevalence of primary infertility in India between 3.9% and 16.8%. The present study was aimed at evaluating the "duration since marriage" (DSM) of a woman as a determinant of infertility using National Family Health Survey (NFHS), India data, as no such previous literature is available.
Materials And Methods:
National Family Health Survey-4 (2015-16) data of Indian married women who were yet to deliver or having no more than one child and experiencing their reproductive life (between 15 and 49 years) were included to evaluate infertility. Chi-square statistics was applied to establish association of infertility with its determinants. Cox regression analysis was used to analyze the rate of infertility by different duration since marriage (DSM) categories through its determinants using IBM SPSS 20 version software®.
Results:
The risk ratios of infertility for "DSM1+," "DSM3+," and "DSM5 + years" groups were significantly higher for "30 + years" age at the marriage group (1.21%, 1.7%, and 1.78%, respectively) (P < 0.05) when standardized with age at marriage "20-29 years" group. Women in rural areas were at higher risk (RR of 1.18%, 1.2%, and 1.33%, respectively) (P < 0.05) for infertility versus urban populations. Illiteracy, nonusage of contraceptives, and MTPs carried higher risks of infertility versus literate women using contraceptive methods. Cox regression analysis of infertility by its covariates revealed standardized RR in "30 + years" age at the marriage group was 1.04 (P < 0.05) against "20-29-year." RR for poor wealth index women was 1.21 (P < 0.001) against middle and rich wealth index groups. Contraceptive use was associated with significantly lower (0.83) standardized RR (P < 0.001) against nonusers.
Conclusion:
Higher age at marriage, rural residency, illiteracy, employment, poor wealth index, and lower BMI increased risk of infertility, while use of contraception reduced it. The Cox regression highlights these determinants as key factors of infertility and should be stressed upon for effective planning and implementation of reproductive health programs to reduce primary infertility in India.
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