Explaining fertility transition of a developing country: an analysis of quantum and tempo effect
© Fazle Rabbi and Kabir; licensee BioMed Central. 2015
Received: 20 May 2014
Accepted: 19 November 2014
Published: 21 April 2015
The Total Fertility Rate (TFR) is defined as the average number of births a woman would have if she were to live throughout the reproductive span and bear children at each age at the rates observed in a particular year or period. The current demographic explanation for decline in TFR is primarily attributed to an increase in postponement in pregnancy. Being cross-sectional, fertility measures can be confounded by changes in the timing of births across women’s lifetimes (tempo) and by changes in the numbers of children that they have by the time they end their childbearing (quantum). After a sharp fall in the last two decades, TFR of Bangladesh is now 2.3; whereas the TFR was greater than 3 in the last decade. However, mean age at childbearing showed decreasing trend in the last decade.
This is a secondary analysis of data from the three consecutive Bangladesh Demographic Health Surveys; BDHS-2004, 2007 and 2011. The method of Bongaarts and Feeney has been applied to estimate the tempo of fertility. Life Table analyses were applied on birth intervals to explain the tempo effect.
There was a sustained decline of the fertility quantum (the number of births per woman) as estimated by the conventional TFR; due to tempo effects during the last three BDHS surveys. Mean age at childbearing also showed decreasing trend in the last decade.
The current study shows the presence of a significant tempo effect with variability of timing in having first or higher order births. If this trend continues, Bangladesh will be able to achieve below replacement level of fertility soon.
Policy-makers have considered different strategies and interventions aimed at achieving a replacement level of fertility, while researchers search for factors and explanations affecting fertility. The most used indicator of fertility rate is Total Fertility Rate (TFR) which is conceptualized as the average number of children a woman will have over the course of her life if the prevailing age specific fertility rates (period fertility) are assumed to be constant. Demographers and policy makers rely profoundly on the TFR for examining trends in fertility for a number of conveniences . First, the data requirements for the TFR are limited and easy to estimate. Second, the TFR is a synthetic measure of fertility. Third, the TFR is a contemporary measure of fertility and unlike the cohort TFR it can be computed for the year just passed . Using TFR as standard measure of fertility has one important flaw; it is sensitive to shifting in the age pattern or timing of fertility . In conventional use quantum refers to the average number of children born to women in a cohort, and tempo to the timing of births by age of mother within the cohort. Tempo is often measured by the mother‘s mean age at child bearing, but in this paper tempo is measured by the mean ages at child bearing at each birth order .
The age pattern of fertility may change for various reasons. Perturbations in the age pattern of childbearing are more subtle, and in recent years are facilitated by effective contraceptive methods. However, a postponement of births not only leads to a rising mean age at child bearing, but it also affects the observed fertility rates and thus the TFR [2, 4, 5]. Specifically, a postponement of fertility leads to a decrease in the observed ASFRs and TFR because events are spread over a longer period of time. Thus, the fertility measures can be confounded by changes in the timing of births across women’s lifetimes (tempo) as well as by changes in the numbers of children that they have by the time they end their childbearing (quantum). This effect was first identified by Ryder , but a very simple and effective method to estimate the tempo effect on aggregate level of fertility was invented by Bongaarts and Feeney .
Bongaarts and Feeney estimated the effect of timing by decomposing age specific fertility rates applying the parity progression ratio in a calendar year. This method considered the shift in the mean age of childbearing for each birth (parity). Parity-specific analysis provides more detailed insights that cannot be observed using conventional age-specific analysis of fertility. Another important benefit of parity-specific analysis is its capability of providing few threshold measures that can be related more directly to behavioral responses than is the case with age specific fertility rates . Using these measures facilitates deduction about changes that are long-term (quantum) and changes that are temporal (tempo).
The socio-economic and policy changes over the years regarding population and public health sectors in Bangladesh are associated with the fall in fertility. After a fall in the last two decades, TFR is now 2.3 in Bangladesh. If the present trend continues then it is expected that Bangladesh will be able to achieve its demographic goal as envisaged in the population policy. If we divide the country by east and west, BDHS 2011 demonstrates that the west has already achieved replacement fertility but eastern regions such Syllhet and Chittagong are lagging far behind. Health Nutrition Population Sector Development Program (HNPSDP) identified several factors such as utilization of mass media, women empowerment, increased enrolment of girls in education, participation of women in employment and migration. Although significant fertility transition occurred in Bangladesh between 1975 and 2011, Bangladesh has to pass many barriers including high rates of adolescent marriage, lower use of contraception by newly married couples, low education of women and low employment rate of women [7–10]. Declining TFR from 6.3 to 2.3 was not so gradual; Bangladesh has had to pass many barriers. Another possible determinant of this transition may be the emerging success on the fourth goal of MDG; ‘reducing infant mortality rates’; which indirectly contributed to the fall of fertility in the last two decades .
Besides decline in the ASFRs, mean age of childbearing also declined since the mid 1970’s which obviously should have some effect on aggregate fertility level of the country. If the TFR changes in a particular year, how we can infer whether fertility rates of the cohorts who are bearing children in that year also changes? It is difficult to predict and interpret changes until relevant cohorts have completed child bearing. A timing change is also known as a tempo change and the tempo effect has a dramatic effect on period fertility rates, but probably has comparatively little effect on cohort rates. Influences on fertility which do affect cohort rates are called quantum effects. However, there have not been enough studies that provide better understanding of recent fertility transition (declining fertility rates from a higher level to replacement level) and its relationship with the change in population size and composition . Few studies have estimated the tempo adjusted TFR of Bangladesh for certain time point [12, 13]. The aim of the present paper is to understand to which extent the fall in TFR can be attributed to the change in age specific fertility rate and to which extent to the period fertility (cross-sectional measure of fertility rate) using three consecutive BDHS data. The decomposed factors of tempo effects like Age-Specific Fertility Rates (ASFR), and mean age at childbearing (MAC) are analyzed to explain tempo adjusted TFR.
Data for the analyses in this study come from Bangladesh Demographic and Health Surveys (BDHS). BDHS is a nationally representative survey that was conducted under the authority of the National Institute for Population, Research and Training (NIPORT) of the Ministry of Health and Welfare, Bangladesh and funded by USAID. Three consecutive surveys (2004, 2007 and 2011) have been included in the present study. Stratified Multi-stage Cluster Sampling design was used to collect data and BDHS 2004, BDHS 2007 and BDHS 2011 includes 11400, 10996 and 17749 ever-married women of child bearing age of all six divisions in the country respectively .
Where, x = 15,20,25,35,40,45; (x + 2.5) represents the midpoint of each age interval and 5fx represents the age specific fertility rates for five year age group . To compare and contrast highest tempo distorted parity progression, life tables are constructed for corresponding birth intervals using the methods of Rodriguez and Hobcraft .
Quantum and Tempo of fertility for Bangladesh (BDHS 2004, 2007, 2011)
adj TFR i
adj TFR i
adj TFR i
The case of birth order 5 or higher is different from parity progression from birth order 4. The trend of MAC is irregular for higher order births; in BDHS 2007 MAC5+ is lower than MAC5+ for BDHS 2004. This is due to rapid decline in higher order births as Bangladesh approaches a two child family. Tempo adjusted TFR obtained for three combined BDHS (BDHS 1993–94, 1996–97, 1999–2000) was 0.6 ; while tempo adjusted TFR for BDHS 2004 is 1.08 in present study .In order to find explanations for the obtained pattern of tempo adjusted TFR an analysis of birth intervals was performed and shows an increasing pattern in all three BDHSs. In BDHS 2004 the median birth interval was 39.3 months, which increased to 43.6 months in BDHS 2007 and 47.4 months in BDHS 2011. This clearly suggests the shift in MAC for each order which creates the tempo effect on TFR. But the Figure 2 shows a consistent trend in age specific fertility rates with highest rates in all the three surveys concentrated at age 20–24 indicating mean age child bearing is moving towards younger ages (Figure 2).
Life table summary measure for first birth intervals for Bangladesh (BDHS 2004, 2007, 2011)
Median (q 2 )
Here B20 means the cumulative probability of having first birth within 20 months of marriage; B40 means cumulative probability for 40 months and so on. When the probability is computed for a duration of 60 months (B60) it is called ‘quintum’ . The probability of having first birth increased for shorter duration, though the median of first birth interval increased slightly. It should be noted that, most of the births were first order births in all of the BDHSs. Compare to overall birth intervals in BDHSs; first birth interval is comparatively lower. Comparison of three consecutive BDHSs suggests an increase of marriage to first birth interval in Bangladesh. In the BDHS-2004, Tukey’s Trimean was 16.25 for first birth interval which increases to 17.75 months in BDHS-2011. Similarly, spread of births also increased between BDHS-2007 and BDHS-2011 which may be due to the presence of a large tempo effect of first birth.
The aim of the present paper is to understand to which extent the decline in Total Fertility Rate (TFR) can be attributed to the quantum effect and to what extent it is due to tempo effect. The period TFR is one of the most often used indices of fertility, but it is sensitive to variation in the parity distribution of women that results from shifting in the time of childbearing in successive cohorts. The Bongaarts-Feeney tempo adjusted TFR method is one of several attempts to produce better period measure (cross-sectional measures of fertility) of the fertility quantum. Bangladesh, a country of Southeast Asia, has shown significant fertility transition in the last two decades. For Bangladesh, clearly, the impact of timing on the aggregate level of fertility is present. This tempo effect is the result of change in the birth intervals and mean age of childbearing for each birth order. The results indicate the importance of analysis of the timing effect on the aggregate level of fertility which has implications in policy consideration. The primary distortion was caused by an increase in the mean age at child bearing. The analysis shows that tempo adjusted TFR will be half a child higher than the estimates suggest in 2011 BDHS (2.81 as opposed to 2.30). However, the distortion effects of a changing mean age of child bearing by birth order are important in order to understand fertility behavior and its implications on future population growth.
The tempo effect of TFR could be reduced by motivating mothers to widen spacing between consecutive births. Even if Bangladesh achieved replacement fertility by 2015 as envisaged in the population policy of Bangladesh, population growth will continue due to population momentum. The most feasible approaches to reduce the impact of population momentum should be taken into account as policy measures and include delayed age at marriage, delayed age at first birth and wider spacing of successive births.
Despite this, there may be debate about the use of the period measure of TFR. If couples have their children earlier, the mean age at child bearing falls and the period rate will rise. On the other hand, if they have them later, it will fall. Using the Bongaarts and Feeney method one can estimate the effect of shifting in the MAC to the aggregate level fertility only for consecutive years (but not for long periods) [16, 17]. However, the tempo effect of fertility may be distorted due to sampling fluctuations . This limitation is an important policy issue while measuring the tempo effect of TFR might have affected the results of current study.
Life table analysis shows that the highest tempo effect was obtained from age at first parity. The other important consideration from this analysis is the increase in variability in age at first birth and higher order births. Several explanations may be inferred from previous studies, such as lower family planning practices among the adolescents mothers, ‘catching-up’ effects of the educated mothers (having the first birth earlier to overcome the reproductive life span passed before marriage) and so on [10, 18]. This variability of timing in having first or higher order births are thus equally important to understand the fertility transition in Bangladesh.
The current study shows the presence of a significant tempo effect. Decomposition of parity specific analysis suggests the highest tempo effect on first order birth which is strongly associated with age at marriage. Age at marriage is the most prominent and key-factor explaining fecundability for every sub-group of the study population. Findings from the current study suggest that new policy regarding the present child bearing situation will have important impact on the TFR and maternal and child heath. Further research using cohort measures may identify potentially relevant factors that impact the tempo effect in order to better understand the context.
- Kohler HP, Ortega JA: Tempo-adjusted period parity progression measures, fertility postponement and completed cohort fertility. Demographic Res 2002,6(6):91–144.View ArticleGoogle Scholar
- Hajnal J: The analysis of birth statistics in the light of the recent international recovery of the birth-rate. Popul Stud 1947, 1:137–64. 10.1080/00324728.1947.10415527View ArticleGoogle Scholar
- Ryder NB: Problems of trend determination during a transition in fertility. Milbank Memorial Fund Quart 1956, 34:5–21. 10.2307/3348329View ArticleGoogle Scholar
- Feeney G: Population dynamics based on birth intervals and parity progression. Popul Stud 1983, 37:77–89.View ArticleGoogle Scholar
- Ryder NB: The process of demographic translation. Demography 1964, 1:74–82. 10.1007/BF03208446View ArticleGoogle Scholar
- Bongaarts J, Feeney G: On the quantum and tempo of fertility. Population Dev Rev 1998,24(2):271–91. 10.2307/2807974View ArticleGoogle Scholar
- Caldwell JC, Khuda BE, Caldwell BC, Pieris I, Caldwell P: The Bangladesh Fertility Decline: an Interpretation. Population Dev Rev 1999,25(1):67–84. 10.1111/j.1728-4457.1999.00067.xView ArticleGoogle Scholar
- Bongaarts J: The fertility impact of changes in the timing of childbearing in the developing world. Popul Stud 1999,53(3):277–89. 10.1080/00324720308088View ArticleGoogle Scholar
- National Institute of Population Research and Training (NIPORT), Mitra and Associates, ICF International: Bangladesh Demographic and Health Survey 2011. Dhaka, Bangladesh and Calverton, Maryland, USA: NIPORT, Mitra and Associates, and ICF International; 2013.Google Scholar
- Kamal N, Saha UR, Khan MA, Bairagi R: Use of Periodic Abstinence in Bangladesh: do They Really Understand? J Biosoc Sci 2007, 39:27–40. 10.1017/S002193200500115XView ArticlePubMedGoogle Scholar
- Akter S, Rahman JA, Rahman MM, Abedin S: The influence of birth spacing on child survival in Bangladesh: a life table approach. World Health Popul 2010,12(1):42–56.PubMedGoogle Scholar
- Islam MA, Islam MM, Chakraborty N: CPD-UNFPA Paper Series 23. CPD, Dhaka: Bangladesh’s population policy: Emerging issues and future agenda; 2003.Google Scholar
- Rabbi AMF, Karmaker SC, Mallick SA, Sharmin S: Determinants of birth spacing and its effect on fertility in Bangladesh. Dhaka Univ J Science 2013,61(1):105–10.View ArticleGoogle Scholar
- Rodriguez G, Hobcraft J: Illustrative analysis: Life table analysis of birth intervals in Columbia. WFS Scientific Reports No 16, International Statistical Institute, Voorburg; 1980.Google Scholar
- Kohler HP, Philipov D: Variance effects in the Bongaarts–Feeney formula. Los Angeles: Paper presented at the Annual Meeting of the Population Association of America; 2000.Google Scholar
- Zeng Y, Land KC: A sensitivity analysis of the Bongaarts–Feeney method for adjusting bias in observed period total fertility rates. Duke University: Working Paper Z4, Center for Demographic Studies; 2000.Google Scholar
- Bongaarts J, Feeney G: On the quantum and tempo of fertility: reply. Population Dev Review 2000,26(3):560–4. 10.1111/j.1728-4457.2000.00560.xView ArticleGoogle Scholar
- Lappegård T, Rønsen M: The Multifaceted Impact of Education on Entry into Motherhood. European J Population 2005, 21:31–49. 10.1007/s10680-004-6756-9View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.