5 Fertility studies: concepts and measures

Shalini Singh and Gautam Kshatriya

Contents:

1) Introduction to Demography

2) Fertility Theory : Structure and Development

2.1) Malthusian thoughts and Population Theory

3) Fertility Transition

4) Fertility Measurement

4.1) Crude Birth rate

4.2) Child Women Ratio

4.3) General Fertility Rate

4.4) Age Specific Fertility rates

4.5) Total Fertility Rate

4.6) Parity Progession Ratio

Learning Objectives:

The text is an attempt to understand about the concept of fertility.
It enriches our knowledge about various common measures of fertility with its advantages and disadvantages.
It makes us understand the difference between period and cohort measures of fertility.

1) Introduction to Demography

Demography is considered a social science and its unique character lies in the discipline’s emphasis on quantification, analytical models, censuses and large scale sample surveys. It remains a social science where the central subject deals with population and population dynamics. It is also the social phenomenon emerging from the aggregation of individual life events, to a great extent socially determined and with profound social consequences. In The state of Population Theory (1986) Schofield and Coleman characterised demography as a discipline with a hard mathematic core and softer surrounding of an explanatory body of theory. The emerging picture of demography is that of an accurate, but relatively dull science, strong in accountancy, but is considered relatively weak in conceptualisation. In course of the development of the discipline, similar statements have been made by Vance (1959), Ford and De Jong (1970), McNioll (1980, 1992), Greenhaulgh (1995b). A one sided sophistication of data collection and mathematic analysis can never substitute the role of theoretical fundament for the formulation of research questions and interpretation of data. In order to understand the demographic phenomenon, theories and conceptual frameworks identifies the causal mechanisms underlying the relations between relevant variables ( Wunsch, 1995).

Demography focuses on three main processes of fertility, mortality and migration and among these fertility is perhaps the most abundant and comprehensive theoretical foundation.

2) FERTILITY THEORY: STRUCTURE AND DEVELOPMENT

Demography is identified and demarcated by population and population change. The easily quantifiable nature of the major phenomenon of interests bolsters up this empiricist bias. Various disciplines like economics, sociology, history, anthropology, biology, psychology and medical science have invaded the relative vaccum of theoretical substance, justifying demography as interdisciplinary. This equates the status of demographic theory in general, it equally pertains to that of the theoretical body dealing with fertility.

Malthusian thoughts and Population Theory

The ideas and observation in regard to fertility and population can be traced back to classic antiquity and ancient Chinese philosophers. These consideration foreshadowed the development of many principles of population, population growth and development and often addressed the implications for public policy, and remained largely speculative at a low level of generalisation. The writings of Malthus at the end of the 18th and beginning of the 19th centuries usually credited with being the first systematic account of the principle of population change. In his first Essay on the Principle of Population, published in 1798, the idea that the capacity of human populations to reproduce is unlimited and also proceeded with a geometric ratio whereas the capacity to produce the means of subsistence is necessarily limited and increases at best in arithmetic fashion. The belief that population and means of subsistence increase with different ratios means that populations will grow where food production increases, but eventually they face a level where no more people can be sustained and any surplus population dies of starvation, but also other misery, such as epidemics, wars and plagues. He also conceived of a number of preventive checks, which operated through people’s voluntary acts to limit their number of children. Malthus also focused on moral restraint i.e.the sexual abstinence within marriage was considered ineffective because of the over powering passion between the sexes. Malthus world view was violently opposed to other means of birth control, like abortion and contraception.

The cristism of Malthusian project has always been often and severe on various ideological grounds, indeed it is still the subject of heated debate among scientists and policymakers. One of the main lines of attack concerns of Malthus assumption of the capacity to increase agricultural output. Another shortcoming of Malthusian reasoning is its failure to distinguish the power of population to increase from their tendency to do so. Many anthropologic studies have shown that populations have a large variety of mechanisms at their disposal to keep population size in accordance with the carrying capacity of their environment, ranging from marriage patterns and migration to contraception and child fostering. Despite the recognition that technologic innovations keep on pushing up the limits of population growth, the essence of the problem continues to permeate the debate, not only with regard to the food supply, but also in the broader perspective of sustainable development with regard to the exhaustive of nn renewable sources of energy.

3) Fertility Transition

For most of his century, demographers and social scientists have been intrigued by the regularities of demographic change in many different settings all over the world. The apparent processes of demographic transition proceeds in the course of modernization and economic development from a situation characterized by high mortality and high fertility to one where mortality and high fertility. to one where mortality and fertility to one where mortality and high fertility are low. The notion of demographic transition gained full momemtum only after the seminal publications by Davis (1945) and Nolestein (1945), although the full essence of the contingency between modernization and declining mortality and fertility, as well as the three stage evolution had already been comphrehensively formulated by Thompson in 1929. The classic representation of demographic transition. As for instance sketched by Nolestein, claimed that mortality declined in the wake of the industrial revolution, which brought material changes in the sense of agricultural innovation, better communication, higher productivity and improved health conditions. Fertility is ought to be less responsive to such modernisation and its decline depended largely on the extent of collapse following mortality decline of ideational and normative systems that supported high fertility. The principles of historic demographic transitions were thought to be applicable to any contemporary situation in the sense that every nation region, or population could be located on the evolutionary track of modernisation and the shift from socioeconomic to cultural ideational and psychological determinants of fertility decline.

A notion often associated with the transition from high to low fertility covers the post transitional stage, where fertility is under complete control of couples and individuals, where the pre transitional stage it is to large degree left to biologic principles, although constrained by socially constructed boundaries. The analysis of fertility in pre transitional population has immensely improved since Louis Henry (1953) defined natural fertility as an absence of deliberated control through abortion or contraceptive practice, assuming the fact that the reproductive behaviour doesn’t depends on the number of children already born to couple. Under the concept of natural fertility, reproduction is determined by a number of biological principles, such as age at menarch, fecundibility, time required for gestation, intrauterine mortality and post partum amenorrhea. The social behaviour factors affecting fertility includes marriage patterns, spousal separation, rules for sexual abstinence in certain periods, and duration and intensity of breast feeding, with its effects on the post partum amenorrhea.

The concet of natural fertility has evolved over time and a culmination point has been achieved in the model of proximate determinats fertility developed by Bongaarts. Kinslay Davis and Judith Blake provided an eminent contribution with the development of an analytical framework of intermediate determinants of fertility affecting the exposure to intercourse. Bongaarts further added to this framework by quantifying the effect of Davis and Blake’s intermediate variables and collapsing them into eight, and later seven, proximate determinants of fertility. Any level of fertility in a population can always be accounted to variations in one or more of the following determinants:

The proportion of women of reproductive age that is married which is considered as a measure of the proportion exposed to sexual intercourse.
Effective ues of contraception
Induced abortion
Postpartum infecundability primarily determined by the duration and intensity of breast-feeding
The frequency of intercourse including the effect of temporary separation and abstinence practices.
The onset of permanent sterility (particularly as related to menopause)
Spontaneous intrauterine mortality

A women can reproduce a less number of 15 children, sticking to each of these factors and can contribute to her reproductive career. Marriage, contraceptive practices, abortion, and postpartum infecundability have by far the strongest effect on levels and differentials of fertility. The model suggests therefore that the total fertility rate can be described as:

TFR = C(m) x C(c) x C(a) x C(i) x TF

where TFR is the total fertility rate

C(m) is the index of proportion married

C(c) is the index of noncontraception

C(a) is the index of induced abortion,

C(i) is the index of lactational infecundity

TF is the potential total fertility.

Due to the framework’s exceptional clarity and organizational power it has an enormous impact on the various research agenda of fertility studies—particularly for developing countries and also for historic populations. The WFS and DHS provided the necessary data to apply the model in a comparative perspective. The significance of the model is partly situated in the structuring of attention and efforts in the search for the ultimate determinants of fertility and fertility change. Whereas Bongaarts’ model of proximate determinants, as well as the version of Davis and Blake, analyzes fertility at the level of populations and societies, several researchers tried to translate it to the individual level. Hobcraft and Little (1984), for instance, calculate fecundity and fertility as the outcome of the fecundity-reducing effects associated with the particular set of states that describe women’s positions in their reproductive career (states related to pregnancy, absence from sexual relations, contraceptive use, postpregnancy infecundity). Becker’s model of adolescent fertility (S. Becker, 1993) specifies conditional probabilities of live birth, conception, and coitus on the basis of individual data. Hull (1983) and de Bruijn (1999) explicitly incorporate the proximate determinants in a decision-making approach. The value of this integration is that fertility is not seen as the product of one single decision, but as the possible combined effects of numerous decisions with regard to the—behavioral— proximate determinants such as marriage and divorce, contraceptive use, abortion, frequency and patterns of sexual intercourse, and breast-feeding practices. This reformulation represents a means to increase the relevance of the concept of individual choice for situations under conditions of natural fertility. Although the popularization of the proximate determinants model is mainly due to its application to developing countries, it is perhaps a mistake to presume that its value may be discarded completely for developed countries (Easterlin and Crimmins,1985). Although in Western countries fertility is considered to be under volitional control and childbirth to be a matter of demand rather than supply, it is worthwhile recognizing that here too fertility not only depends on behavioral factors, but also on biologic processes. Until recently the main fertility problem was the control of unwanted childbearing and the attainment of a perfect contraceptive population.

4) FERTILITY MEASUREMENT

Fertility measurement deals about the producing rates that relate numbers of births to numbers of women. The most widely accepted measure of fertility is the Total Fertility Rate (TFR). It is quite a complex measure but deals within in depth.

The different measures which we are going to discuss in this section of the module are as follows.

4.1) CRUDE BIRTH RATE

This measure is a simple ratio of the number of births in a particular period which is further divided by the total population size. It is defined as the number of live births per 1000 estimated mid year population in a given year, irrespective of age sex composition. Mathematically it is represented as,

CBR= LB *K

Where,

B= total live births during a year, for this study it is

P= total mid-year population here it is

K = constant, generally taken as 1000

The measure is well suited for construction from vital registration providing the numerator and the census data providing the denominator. It can be easily and accurately be calculated in developed countries with well developed vital registration systems and good census data. The denominator is a representative of an average population size for the period concerned.

However, one shortcoming of this measure is that it takes into account the whole population, but the whole population is not exposed to the child bearing age and since the crude birth rate takes into account the whole population and not only the women in reproductive age group, therefore it does not give a true idea of the fertility of a population. Yet still it is of great importance in demographic studies, especially for planning purpose,

The Crude Birth rate approximates numbers of births when limited information is available.

Disadvanatges of the Measure

A CBR considers the total population in the denominator and treats all ages equally. This is considered as a weakness because the driver of the production of births is the women in the age group of 15-49 years.
The CBR is confounded by age structure and is hence not considered as an accurate measure of fertility by demographers.

4.2) CHILD WOMEN RATIO

It is defined as the number of young children aged 0-4 years per 1000 women of child bearing age 15-44 of mid year population. Symbolically the formula stands as,

CWR= Number of children up to 4 years of age *1000

number of women aged 15-44 years ( mid year )

Its problem as a true measure of fertility is with the numerator as it misses the children who have died. In a high mortality situation, the fertility estimate will be under determined. As a fertility measure it is rather a rough measure telling about the burden of children in a community. It is also used demographically as a measure of youngness in a population and is alo useful for that purpose. It is normally considered as a figure below one for low fertility countries and just under one for high fertility countries. This may seem a low figure for high fertility countries but even in these countries more than two children below 5 at any one time is relatively uncommon.

4.3) GENERAL FERTILITY RATE ( GFR)

It is much better measure of fertility than the former two because it takes into account only the women in the child bearing age. It is defined as the number of births per thousand women of child bearing age.

GFR= total number of live births in a year ( b) × 1000

Total women of child bearing age at the mid point of that year (w15-44 )

WHERE,

B= total live births in any one year, here which

W15-44=total fertile, those who are capable of reproducing and were married, i.e. in the age group of 15 to 44 years in that year, here it is equal to

K= Constant, here is taken as 1000

It can be easily constructed from vital registration, census or survey data and its estimation doesn’t relies on exact ages. Moreover, this meaure is a step above the previous two measures and is potentially useful and reasonably accurate measure of fertility because the numerator and denominator are focussed and is well specified.

The measure has its use in circumstances when one wants to know a total number of births for all women in the fertile ages. But in general it is not widely used because it still suffers a disadvantage concerning the structure of the population. The problem is much similar to the problem with the CBR although on a smaller scale. This problem is that the fertilie ages- nominally 15-49 years is 35 years wide and so within that range there can be substantial differences in the age structure between populations. For an international or secular comparison one needs to measure the independent age structure.

4.4) AGE SPECIFIC FERTILITY RATE ( ASFR)

Age specific fertility rate is considered to be a more precise measure of fertility. It is defined as the number of live births in a year to 1000 women in any specified age group.

Mathematically the formula for ASFR can be represented as,

ASFR= BX ×K

WHERE,

BX= births in a year to women aged ‘x’ in this case ‘x’ represents age categories.

WX= Average women of age ‘x’, here it will be women in the age category ‘x’

K= constant, taken as 1000

The age specific fertility rate examines fertility in detail. The groups consist of varied width or comprises of single years of age but conventionally form seven 5 year age groups., which cover the range of 15-49 years of age. The pattern of fertility is an important concept in demography. As with the mortality we can be sure about the pattern of the phenomenon and recognise the distinct ways in which the rate changes under certain circumstances.

4.5) TOTAL FERTILITY RATE (TFR)

The total fertility rate is defined as the sum of the age specific fertility rate over the whole range of reproductive ages of a particular period.” It can also be interpreted as the average number of children that would be born to married women if she experiences the current fertility pattern throughout her reproductive span.

Symbolically it is represented as,

TFR= (∑ASFR) ×5

1000

A better phrase to define total fertility rate would be “ the average number of children a women can expect to have, given the current levels of fertility.

On exploring the TFR a little deeper, it invariably means “period TFR” unless otherwise stated. It is derived from a synthetic cohort and also represents a measure dering from data for a particular period-usually a single year. All the period measures tends to change from year to year. In developed countries children are expensive commodities and also in periods of economic hardships or strife families delay having children.

http://demographicestimation.iussp.org/content/overview-fertility-estimation-methods-based-pf-ratio

Total period fertility rate by year in France

The given figure shows a time series of TFRs for France and it can be seen that there is variability by year by year. During the first world war and immediately after the second Second World War, there was a steep decline in the early 70s which accounts for problem of this measure as it is highly variable and can change rapidly from one year to the another year. To understand the variability of measure two terms are associated with TFR- Tempo and Quantum. Quantum relates to the real value of the TFR over a substantial time. Like for instance, if TFR is 4.2 then one expects that over a reproductive lifetime of 4.2 births will be produced per women on an average. 4.2 is the quantum of fertility where fertility is truly rising and one expects more than 4.2 births to be the result. TFR can fluctuate considerably from year to year following economic trends, strife etc. Although TFR is widely used at times when demographers want to deal with measures that are free from tempo effects and are therefore stable. If couples decide to space births further apart because of the availing economic conditions. TFR is widely used when demographers want to deal with measures that are free from tempo effects . The period TFR can fluctuate because of tempo effects- that is changing child bearing decisions on a year by year basis. The normal data source in developing countries is a survey despite of data collected from vital registration and censuses.

The demographic survey usually enquires the birth history of a women (full or half). Cohort fertility is the fertility produced by a particular group of women throughout their reproductive life i.e. real cohort. If the average number of live births is 4.2 then it is expressed as a Total Cohort Fertility Rate of 4.2. It is often called as the completed family size which is not be confused with the period TFR. Cohort fertility is more stable than period fertility but has a disadvantage as it relates to an earlier period of time and is not current. A series of cohort fertility measures plotted like this usually shows less variability than a series of period TFRs and accounts a truer picture of fertility quantum.

Period Fertility vs. Cohort Fertility

The given table lists the main contrasts between the period and cohort approach to measuring fertility. Both are full of their own uses and applications and also gives a different view point of the quantum of fertility.

TFR is an important estimate as it is effectively independent of the age structure and so measures the fertility. The number of births that women give birth to in a purer way can be estimated as it is devoid of confounding factors such as different proportions of women at particular ages.

It is by far the most widely used measure of fertility because it is intuitive and completely comparable across nations owing to the fact that they have been standardised to remove any anomalies caused by different population structures.

4.6) PARITY PROGRESSION RATIOS

It is the most widely used measure of fertility are period measures- age specific fertility rates and the total fertility rate. These are very useful measures but they do suffer from one failing- they are not good at detecting real changes in fertility in the short term. In developed countries one cannot be completely sure, for several years, that an apparent decline in fertility is not atleast partially due to delaying of births until older ages, to fit in with careers and a fashion for establishing households and financial security before child bearing.

Parity Progression ratio are rather a different way of measuring fertility. They are not well appreciated outside of demography. It measures the proportion of women with n children who go on to have n+1 children. So PPRs are order specific and comes in sets, rather than being single summary measures such as the TFR. The conventional symbol for a PPR of a certain birth order is an so a set of PPRs would be:

a0 = proportion of women with 0 children who have 1 child

a1 = proportion of women with 1 child who go on to have 2 children.

a2 = proportion of women with 2 children who go on to have 3 children.

a3 = etc.

up to a suitable birth order, depending on the level of fertility.

http://demographicestimation.iussp.org/content/overview-fertility-estimation-methods-based-pf-ratio

The figure shows a PRR series from a0 to a9- for Thailand 1960 and shows the fertility of a society which seems to accept as many children as come. The next stage superimpose the PPR series for 1987-27 years later. a0 and a1 are almost identical. a2 is noticeably lower and a large drop can be seen at a3 and a4. This patterns strongly suggest that couples are introducing choice into planning their families as they have two children but fewer go on to have third and fewer child. The choice is implemented usually by adoption of contraception in some countries.

Summary

The fertility is one of the big overarching topics of demography and it deserves serious study. Fertility is the number of live births, not the medical concept of potential to conceive. The crude birth rate is important because of its place in the demographic balancing equation, from which the population growth can be estimated. Age specific fertility rates are important as they allow to sdee patterns of fertility which gives us a good idea of traditional and modern/ early and late patterns of fertility.
The measure Total fertility Rate is very important because it is widely used and quoted. It is derived directly from ASFRs and is a standardised measure which allows international comparisons. It is, by default, a period measure, although cohort TFRs are possible.
Parity progression ratios, in their simple form, are cohort measures and also provide a different appreciation of fertility- without tempo effects. They are particularly sensitive at identifying choice in child bearing.
Fertility is an area of demography where many theories exist to explain fertility change, especially focussing on how and why fertility decline commences. This is an interesting area but this module focuses on the technical assessment of fertility and the key measures that demographers must understand and know how to calculate and interpret.

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Suggested Readings

Bulatao, R. A. (Ed.). (1983). Determinants of fertility in developing countries: a summary of knowledge. National Academy.
Bongaarts, J. (1978). A framework for analyzing the proximate determinants of fertility. Population and development review, 105-132.
Bongaarts, J., & Potter, R. E. (2013). Fertility, biology, and behavior: An analysis of the proximate determinants. Academic Press.
Carmichael, G. A. (2016). Fundamentals of demographic analysis: Concepts, measures and methods. Springer.
Caselli, G., Vallin, J., & Wunsch, G. (2005). Demography: Analysis and Synthesis, Four Volume Set: A Treatise in Population. Academic press.
Dyson, T. (2013). Population and development: the demographic transition. Zed Books Ltd..
Farooq, G. M., & Simmons, G. B. (Eds.). (2016). Fertility in Developing Countries. Springer.
Furedi, F. (1997). Population and development: a critical introduction.
Lutz, W., Sanderson, W. C., & Scherbov, S. (2004). The end of world population growth in the 21st century: New challenges for human capital formation and sustainable development. Earthscan.
Padmadas, S. S. (2016). Gordon A. Carmichael: Fundamentals of Demographic Analysis: Concepts, Measures and Methods. European Journal of Population, 32(5), 761-763.
Population: An Introduction to Concepts and Issues- John R weeks.
Weeks, J. (2011). Population: An introduction to concepts and issues. Nelson Education.