Skip to main content

Advertisement

SpringerLink
Log in

Influences on Pregnancy-Termination Decisions in Matlab, Bangladesh

  • Published:
Demography

Abstract

We investigate factors affecting women’s decisions to terminate pregnancies in Matlab, Bangladesh, using logistic regression on high-quality data from the Demographic Surveillance System on more than 215,000 pregnancies that occurred between 1978 and 2008. Variables associated with the desire not to have another birth soon (very young and older maternal age, a greater number of living children, the recent birth of twins or of a son, a short interval since a recent live birth) are associated with a greater likelihood of pregnancy termination, and the effects of many of these explanatory variables are stronger in more recent years. Women are less likely to terminate a pregnancy if they don’t have any living sons or recently experienced a miscarriage, a stillbirth, or the death of a child. The higher the woman’s level of education, the more likely she is to terminate a pregnancy. Between 1982 and the mid-2000s, pregnancy termination was significantly less likely in the area of Matlab with better family planning services.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. We use the term “VPT” here rather than “induced abortion” because some terminations in Bangladesh—namely, those done by menstrual regulation (explained in the next section of this article)—are not considered to be abortions in Bangladesh.

  2. The median and average durations of pregnancies that end in VPT are shorter than those for miscarriages and, of course, LBs and stillbirths. See Appendix A.

  3. Abortion is a sensitive topic in Bangladesh; many of the restrictions on MR, particularly its availability only before pregnancy is clinically confirmed—and, in fact, its name—are to reinforce the perception of MR as something other than abortion. Nonetheless, in this article, we sometimes use the term “abortion” to refer to VPT to be consistent with use in the literature. What we call “abortions” includes MRs.

  4. The Comparison Area contraceptive-use rate might be underestimated because data collection procedures were less rigorous there than in the MCH-FP Area (icddr,b 2011).

  5. We also estimated a multinomial logistic regression explaining whether pregnancies end in VPT, miscarriage, or stillbirth, all relative to their ending in an LB. The conclusions about influences on VPT are identical to those presented here.

  6. We initially explored in bivariate analyses how the effects of age and of number of living children on VPT differed across a number of subperiods of time. For both of these explanatory variables, the largest differences were between subperiods before and after 2001. In the multivariate analysis, we interact all explanatory variables with a dichotomous indicator for 2001–2008; the statistical significance of the coefficients of the interaction indicates whether the effects of the variable differ significantly between the two time periods. We also show the statistical significance of the total effects in 2001–2008 of all explanatory variables.

  7. The duration of the IPI is computed as the amount of time between the date of previous pregnancy outcome and the estimated date of conception, which we compute as the date of last menstrual period (DLMP) before the index outcome plus two weeks. DLMP was not recorded in the Comparison Area before 2001. Also, there is no information on DLMP for women who entered the DSS area after their LMP. For the 42 % of cases with unknown DLMP, we estimated DLMP by subtracting the average outcome-specific duration of gestation for cases with known DLMP (8, 11, 33, and 36 weeks for VPT, miscarriage, stillbirth, and LB, respectively) from the date of the index outcome.

  8. In exploratory analyses, we considered each two-year subperiod in the 2000s, but effects did not differ significantly across the first three of these.

  9. The multivariate analysis controls for some variables correlated with older maternal age (e.g., number of living children). When we do not control for the other covariates, the effects are larger for older maternal ages than for the youngest ones.

  10. The regression also includes an explanatory variable for first pregnancies (as part of the IPI set of variables). All first pregnancies are cases in which there are no living children, so the effects of these two variables need to be considered together. The no-living-children effect by itself is for cases in which the pregnancy is not the woman’s first but her previous pregnancies did not result in the LB of a child who is still alive.

  11. These were first used for the MINIMAT project, which operates among a subset of women in the MCH-FP Area. They were so popular that other women in the area requested them (personal communication with K. Streatfield, October 27, 2011).

References

  • Ahmed, K., Rahman, M., & van Ginneken, J. (1998). Induced abortion in Matlab, Bangladesh: Trends and determinants. International Family Planning Perspectives, 24, 128–132.

    Article  Google Scholar 

  • Ahmed, K., Sarkar, A. H., & Rahman, M. (1996). Determinants of induced abortion in rural Bangladesh. Demography India, 25, 105–118.

    Google Scholar 

  • Ahmed, K., van Ginneken, J., & Razzaque, A. (2005). Factors associated with adolescent abortion in a rural area of Bangladesh. Tropical Medicine & International Health, 10, 198–205.

    Article  Google Scholar 

  • Alam, N., Mostafa, G., Mondol, L. A., & Bairagi, R. (1999). Recording vital events in Matlab, Bangladesh: Comparison of short and lengthy recall periods, 1996–97. Unpublished manuscript. Dhaka: International Centre for Diarrhoeal Disease Research.

  • Alauddin, M. (1986). Maternal mortality in Bangladesh: The Tangail district. Studies in Family Planning, 17, 13–21.

    Article  Google Scholar 

  • Bairagi, R. (2001). The effects of sex preference on contraceptive use, abortion, and fertility in Matlab, Bangladesh. International Family Planning Perspectives, 27, 137–143.

    Article  Google Scholar 

  • Bairagi, R., & Rahman, M. (1996). Contraceptive failure in Matlab, Bangladesh. International Family Planning Perspectives, 22, 21–25.

    Article  Google Scholar 

  • Bendavid, E., Avila, P., & Miller, G. (2011). United States aid policy and induced abortion in sub-Saharan Africa. Bulletin of the World Health Organization, 89, 873–880.

    Article  Google Scholar 

  • Bhatia, S., & Ruzicka, L. T. (1980). Menstrual regulation clients in a village-based family planning programme. Journal of Biosocial Science, 12, 31–39.

    Google Scholar 

  • Bhuiya, A., Aziz, A., & Chowdhury, M. (2001). Ordeal of women for induced abortion in a rural area of Bangladesh. Journal of Health, Population and Nutrition, 19, 281–290.

    Google Scholar 

  • Bongaarts, J. (1978). A framework for analyzing the proximate determinants of fertility. Population and Development Review, 4, 105–132.

    Article  Google Scholar 

  • DaVanzo, J., Hale, L., Razzaque, A., & Rahman, M. (2007). Effects of interpregnancy interval and outcome of the preceding pregnancy on pregnancy outcomes in Matlab, Bangladesh. BJOG (British Journal of Obstetrics and Gynecology), 114, 1079–1087.

    Article  Google Scholar 

  • Dixon-Mueller, R. (1988). Innovations in reproductive health care: Menstrual regulation policies and programs in Bangladesh. Studies in Family Planning, 19, 129–140.

    Article  Google Scholar 

  • Grimes, D. A., Benson, J., Singh, S., Romero, M., Ganatra, B., Okonofua, F. E., & Shah, I. H. (2006). Unsafe abortion: The preventable pandemic. The Lancet, 368, 1908–1919.

    Article  Google Scholar 

  • Huda, F. A., Ford, E., Deshpande, A., Al Haque, N., Quaiyum, M. A., Healy, J., . . . Johnson, H. B. (2010). Strengthening health system capacity to monitor and evaluate programmes targeting at reducing abortion-related maternal mortality (Reproductive Health Programme Working Paper No. 1). Dhaka, Bangladesh: International Centre for Diarrhoeal Disease Research, Bangladesh.

  • International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). (2011). Health and demographic surveillance system, Matlab: Volume forty two, registration of health and demographic events 2008 (Scientific Report No. 109). Dhaka, Bangladesh: icddr,b. Retrieved from www.icddrb.org

  • Khan, A. R., Jahan, F. A., & Begum, S. F. (1986a). Maternal mortality in rural Bangladesh: The Jamalpur district. Studies in Family Planning, 17, 7–12.

    Article  Google Scholar 

  • Khan, M. A., & Rahman, M. (1997). Determinants of contraceptive method-choice in rural Bangladesh. Asia Pacific Population Journal, 12, 65–82.

    Google Scholar 

  • Khan, A. R., Rochat, R. W., Jahan, F. A., & Begum, S. F. (1986b). Induced abortion in a rural area of Bangladesh. Studies in Family Planning, 17, 95–99.

    Article  Google Scholar 

  • Koenig, M. A., Hossain, M. B., & Whittaker, M. (1997). The influence of quality of care upon contraceptive use in rural Bangladesh. Studies in Family Planning, 28, 278–289.

    Article  Google Scholar 

  • Koenig, M. A., Rob, U., Khan, M. A., Chakraborty, J., & Fauveau, V. (1992). Contraceptive use in Matlab, Bangladesh in 1990: Levels, trends, and explanations. Studies in Family Planning, 23, 352–364.

    Article  Google Scholar 

  • Mitra, S., Ali, M., Islam, S., Cross, A., & Saha, T. (1994). Bangladesh Demographic and Health Survey, 1993–1994. Dhaka, Bangladesh, and Calverton, MD: Mitra and Associates, and Macro International, Inc.

    Google Scholar 

  • National Institute of Population Research and Training (NIPORT), Mitra and Associates, and MEASURE DHS ICF International. (2013). Bangladesh Demographic and Health Survey, 2011. Dhaka, Bangladesh, and Calverton, MD: NIPORT, Mitra Associates, and ICF International.

    Google Scholar 

  • National Institute of Population Research and Training (NIPORT), Mitra and Associates, & ORC Macro. (2009). Bangladesh Demographic and Health Survey, 2007. Dhaka, Bangladesh, and Calverton, MD: NIPORT, Mitra Associates, and ORC Macro International.

    Google Scholar 

  • National Institute of Population Research and Training (NIPORT), ORC Macro, Johns Hopkins University, & International Centre for Diarrhoeal Disease Research, Bangladesh. (2003). Bangladesh Maternal Health Services and Maternal Morbidity Survey 2001. Dhaka, Bangladesh, Calverton, MD, and Baltimore, MD: NIPORT, ORC Macro International, and the Johns Hopkins University.

    Google Scholar 

  • Population Reference Bureau. (2012). 2012 world population data sheet. Retrieved from http://www.prb.org/pdf12/2012-population-data-sheet_eng.pdf

  • Preston, S. H. (1978). The effects of infant and child mortality on fertility. New York: Academic Press.

    Google Scholar 

  • Rahman, M., Akbar, J., Phillips, J. F., & Becker, S. (1992). Contraceptive use in Matlab, Bangladesh: The role of gender preference. Studies in Family Planning, 23, 229–242.

    Article  Google Scholar 

  • Rahman, M., DaVanzo, J., & Razzaque, A. (2001). Do better family planning services reduce abortion in Bangladesh? The Lancet, 358, 1051–1056.

    Article  Google Scholar 

  • Rahman, M., & Sutradhar, S. C. (1996). Women’s status and fertility behavior in rural Bangladesh. In A. Kantner, A. Al-Sabir, & N. Chakraborty (Eds.), The Bangladesh Demographic Health Survey 1993–94: Extended analysis (pp. 195–212). Dhaka, Bangladesh, and Honolulu, HI: National Institute of Population and Training (NIPORT), East–west Center.

    Google Scholar 

  • Razzaque, A., DaVanzo, J., Rahman, M., Ahmed, S. (2011). Pregnancy Termination in Matlab, Bangladesh: Knowledge, Attitudes, and Decision-making Processes. Unpublished document. Dhaka: International Centre for Diarrhoeal Disease Research, Bangladesh.

  • Ronsmans, C., Vanneste, A. M., Chakraborty, J., & van Ginneken, J. (1997). Decline in maternal mortality in Matlab, Bangladesh: A cautionary tale. The Lancet, 350, 1810–1814.

    Article  Google Scholar 

  • Shah, I., & Åhman, E. (2009). Unsafe abortion: Global and regional incidence, trends, consequences, and challenges. Journal of Obstetrics and Gynaecology Canada, 31, 1149–1158.

    Google Scholar 

Download references

Acknowledgments

Support was provided by the WHO Research Program on Sexual and Reproductive Health and by the Office of Population and Reproductive Health, Bureau for Global Health, U.S. Agency for International Development under the terms of Cooperative Agreement No. GPO-A-00-05-00027-00 awarded to the Extending Service Delivery project (a partnership among Pathfinder International, IntraHealth International, Inc., Management Sciences for Health, and Meridian Group International, Inc., that ended in 2011). The views expressed are those of the authors and do not reflect the opinions of their organizations or the funders. The authors thank Maureen Norton for her helpful suggestions.

Author information

Authors and Affiliations

  1. RAND, 1776 Main Street, Santa Monica, CA, 90407-2138, USA

    Julie DaVanzo

  2. MEASURE Evaluation, Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA

    Mizanur Rahman

  3. icddr,b, Dhaka, Bangladesh

    Shahabuddin Ahmed & Abdur Razzaque

Authors
  1. Julie DaVanzo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mizanur Rahman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shahabuddin Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Abdur Razzaque
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Julie DaVanzo.

Appendices

Appendix A: Outcome-Specific Durations of Pregnancy

Table 3 shows mean and median durations of pregnancy in weeks (measured from the estimated date of conception, computed as the date of the last menstrual period (DLMP) + 2 weeks), by outcome, for pregnancies during the period 1978–2008 for which DLMP was reported (58 % of all cases considered here). We also show data for MR and other methods of VPT for the years that the VPT method can be distinguished in the DSS (1989–2008, excluding 2001).

Table 3 Mean and median durations of pregnancy (in weeks), by outcome
Full size table

Appendix B: Means of Explanatory Variables, 1978–2000 and 2001–2008

Table 4 Means of explanatory variables, 1978–2000 and 2001–2008
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

DaVanzo, J., Rahman, M., Ahmed, S. et al. Influences on Pregnancy-Termination Decisions in Matlab, Bangladesh. Demography 50, 1739–1764 (2013). https://doi.org/10.1007/s13524-013-0202-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13524-013-0202-8

Keywords

Search

Navigation