Most available methodologies for evaluating the impact of a family planning programme are based on the concept of 'acceptors'. Although these methodologies have proved useful in applications in a number of developing countries, they have certain drawbacks as pointed out by Bongaarts and Kirmeyer (1982:391). Firstly, these methodologies require a large amount of data which are often not available in developing countries. Secondly, the definition of 'acceptor' is often hard to maintain because couples either discontinue use or switch methods frequently. Thirdly, the continuation rate and potential fertility of the acceptors are very difficult to obtain. Fourthly, information collected on acceptors based on the family planning programme service statistics is often unrepresentative of the country as more agencies are becoming involved in distributing family planning methods. A large number of couples may be using commercial outlets to obtain contraceptives rather than those provided by the programme. Many agencies which distribute contraceptives do not provide statistics to
the national family planning programme for evaluation. Most of these points are relevant to the family planning programme of Pakistan.
Nortman and Hofstatter (1980:94) pooled data from 32 developing and seven developed countries to explain the relationship between fertility level and contraceptive prevalence. They then derived the regression equation which forms the basis of the Bongaarts and Kirmeyer model (1982). The resulting equation is:
CBR = 46.9 - 42.0 x u ... (1)
where CBR is the crude birth rate and u is the proportion of married women of reproductive age using contraception. The proportion of women using contraception in Pakistan during 1984-85 was 0.091. Hence, CBR for Pakistan according to equation (1) was 43.1. The problem with the crude birth rate is that it is affected by the changing age structure of the population, the marriage pattern, the duration of breastfeeding and the incidence of induced abortion. Instead of using the crude birth rate as an index of fertility, Bongaarts and Kirmeyer used the total fertility rate which is free from the effect of the age structure of the population. They developed the following set of equations to remove the effects of the confounding variables:
TFR = 7.30 - 6.42 x u
= 7.30 x (1-0.879 x u ) --- (2)
where TFR is the total fertility rate and u is the proportion of married women of reproductive age using contraception.
Equation 2 yields an estimate which is unaffected by changes in age structure. The TFR estimate according to equation (2) is 6.7 for Pakistan. The intercept 7.30 represents the expected level of natural fertility, that is, fertility in the absence of contraception (and induced abortion). The slope of the regression line, equal to 6.42, gives an estimate of the decline in the total fertility rate associated with an increase in u and the relative slope equal to 0.879 gives the proportional decline. In Pakistan, for example, if 9.1 per cent of married women of reproductive age are current users of contraception (u = 0.091), then a decline in the total fertility rate is expected to be 6.42
x 0.091 = 0.584 of the natural level of 7.30, a reduction of 8 per cent (0.879 x 0.0.091 = 0.080).
TMFR = 9.54-4.81 x u
= 9.54 x (1-0.504 x u ) ...(3)
where TMFR is total marital fertility rate adjusted for the effects of age-structure and the marriage pattern.
To examine the effects of contraceptive use on fertility free of the influence of the marriage pattem, the total marital fertility rate is used as the fertility indicator in the above regression equation and comes to 9.1 for Pakistan.
TMFRA = 15.25- 13.71 x u
= 15.25 x (1-0.899 x u ) ... (4)
where TMFRA is the total marital fertility rate adjusted for the effect of lactation. According to this equation, the TMFRA for Pakistan comes to 14.0.
Bongaarts and Kirmeyer claimed that equation (4) yields an unbiased estimate of the fertility impact of contraceptive prevalence because the effects of age structure, marriage pattem, and duration of breastfeeding are controlled. No control was made to remove the effects of the remaining other proximate determinants of fertility (such as fecundability, spontaneous intra-uterine mortality, and the prevalence of permanent sterility) because fertility is relatively insensitive to variations in these factors (Bongaarts and Kirmeyer, 1982:387).
Bongaarts and Kirmeyer suggest that the above procedures for analysing the relationship between aggregate measures of fertility and contraceptive prevalence can also be applied to age-specific fertility rates. Since the main aim is to measure the change in the aggregate fertility level (total fertility rate), the aggregate model is considered here.
In cases where there are changes in contraceptive prevalence and effectiveness over time, it is not possible to rely directly on the regression results because they do not explicitly take into account the trends in contraceptive effectiveness. Therefore,
equation (5) is suggested by Bongaarts and Kirmeyer (1982:396) to obtain an estimate of change in fertility in a situation where there is no change in marriage pattem and duration of breastfeeding.
TFR9 = l-Ceoxu^yf?
... ... (5) TFRj = H e j x u ^ /f !
where TFR is total fertility rate; subscripts 1 and 2 refer to 1975 and 1985 respectively; e and u refer to contraceptive use-effectiveness and prevalence levels, respectively; and f | and f2 refer to the proportion of women that is fecund.
The objective is to estimate the decline in total fertility rate from 1975 to 1985. The information required to estimate changes in fertility is contraceptive prevalence (U i and U2) in years 1 and 2 and the contraceptive use-effectiveness levels in the same years (ej and e2). U j and U2 are obtained from the Pakistan Fertility Survey 1975 and the Pakistan Contraceptive Prevalence Survey 1984-85 data, respectively. To obtain ej and e2, the distribution of contraceptive methods in year 1 and year 2 are employed with suggested method-specific effectiveness levels as contained in Appendix 5.11. For Pakistan, the values obtained for uj is 0.053, for U2 is 0.091, ej is 0.83 and e2 is 0.84. In most populations f is constant and close to the average of 0.927 (Bongaarts,
1982:394-396). As such an f value of 0.927 has been applied both for fj and f2-
In the case of Pakistan, replacing the values in equation 5, the following estimate o f fertility change was obtained:
TFR 1985 = l-(0.84 x 0.091)/0.927 TFR 1975 = M 0.83 x 0.053)/0.927 TFR 1985/T FR 1975 = 0.96
So the ratio between TFR 2 (1985) / TFR 1 (1975) reveals that the TFR in 1985 was 96 per cent o f the TFR in 1975. Hence only 4 per cent o f the decline in the TFR occurred between 1975 and 1985. Considering the fact that this ratio is not adjusted for the changes in breastfeeding and marriage patterns, the impact of family planning on fertility decline in Pakistan may be even lower than four per cent.