A number of definitional issues complicate the process of estimating unintended fertility and its distribution.
In general, data on unintended fertility come from representative population surveys in which women who are pregnant at the time of the survey or who have had at least one birth in the five years prior to the sur- vey are asked whether each of those births (including the outcome of the current pregnancy) was intended, mistimed because it came too early but was still within the desired number of births, or unwanted in that no more children were desired. Unfortunately, usage of these terms is not completely consistent; some authors include mistimed births as part of their estimates of unwanted births, while others count only those births that exceed the desired family size as unwanted (Brown & Eisenberg, 1995). The major weakness of this approach is that women may be reluctant to clas- sify specific births as unwanted, leading to artificially low estimates of unwanted births.
Measurement of fertility intentions has been criti- cized because it relies exclusively on mothers’ intentions and not the intentions of other family members—most importantly, fathers—to gauge unintended fertility.
EXHIBIT 5-3 Desired Family Size and Unmet Need for Contraception in Kenya
One rationale for family planning programs is that couples who want to have fewer children may be unable to do so either because they lack knowledge of the means of fertility control or because they lack access to those means, owing to an absence of supplies or services.
In the case of Kenya, even in the earliest surveys carried out, a high proportion of married women reported that they wanted no more children. At that time, the mean ideal number of children was reported to be 4.4, and 45.5% of women reported they did not want to have another child. The desired TFR (wanted fertility) was 4.5 births per woman, while the actual TFR was 6.7 births per woman. Thus, there was a big gap between desired fertility and actual fertility despite the inception in late 1970s of a nationwide family planning program. Among the barriers to achieving this low desired fertility were (1) the economic costs of access to services, including the cost of transportation, and supplies; (2) the social costs, including travel by women whose mobility was traditionally constrained; (3) the psychic costs of contraceptive use in a society that offered little social or familial support for low fertility; and (4) the health costs of side effects, whether subjective or objective, from contraceptive use.
These barriers have been overcome to the extent that in 2015, 58% of married women of reproductive age were current contraceptive users, compared to 43% in 2003 and 33% in 1989. Also, actual TFR in Kenya declined from 6.7 births per woman in 1989 to 4.9 births per woman in 2003 and then to 3.9 births per woman in 2014. However, wanted fertility did not remain at the 1989 level: It fell to 3.6 births per woman in 2003 and 3.0 births per woman in 2014. The unmet need for contraception among women at risk of pregnancy decreased from 35.5% in 1989 to 24.5% in 2003 and 17.5% in 2014.
It has been argued that the intentions of the mother, especially in many LMICs, may not accurately reflect the desirability of a birth. Evidence suggests that inter- generational differences in family size goals (i.e., pref- erences of grandparents versus parents) may be more pronounced than interspousal differences (Caldwell, 1986; Mason & Taj, 1987). Ultimately, the justification for relying on the stated preferences of the mother in determining desired family size and unintended or unwanted births stems from the fact that the mother is the person most responsible for the birth and child care (Tsui et al., 1997).
Demographic and Health Surveys (DHS) have been conducted since 1984 in approximately 75 LMICs (https://dhsprogram.com/). This research is intended to provide comparable information on a variety of subjects related to health and fertility issues. DHS
calculates, for each survey, both the total fertility rate (the number of children a woman would bear were she to live her reproductive life under the fertility condi- tions just prior to the survey) and the unwanted total fertility rate (the number of those children who would be unwanted) (Westoff, 2001). A birth is counted as unwanted only when the mother states she wanted no more children at the time of the pregnancy.
The results of DHS surveys conducted over the period 2010–2015 in 35 countries are shown in TABLE 5-4. On average, 17.7% of total fertility was unwanted, with the percentage varying considerably by region. The association between fertility level and proportion of unwanted births has been reversed in the last decade. Previously the regions with the low- est and highest fertility rates (Eastern Europe and sub- Saharan Africa, respectively) had the lowest
No Education Primary Education Secondary or Higher
Education Total
TFR Percentage
Unwanted TFR Percentage
Unwanted TFR Percentage
Unwanted TFR Percentage Unwanted Sub-Saharan Africa
Benin, 2011–2012 5.6 17.9 4.6 19.6 3.8 13.2 4.9 18.4
Cameroon, 2011 6.8 10.3 5.9 11.9 3.8 10.5 5.1 11.8
Chad, 2014–2015 6.5 4.6 7.4 4.1 4.8 4.2 6.4 4.7
Congo, 2011–2012 6.8 11.8 6.6 7.6 4.5 6.7 5.1 5.9
Democratic Republic of the Congo, 2013–2014
7.4 9.5 7.5 13.3 5.6 14.3 6.6 13.6
Ethiopia, 2011 5.8 19.0 4.6 26.1 1.6 6.3 4.8 20.8
Ghana, 2014 6.2 11.3 4.9 16.3 3.5 14.3 4.2 14.3
Guinea, 2012 5.7 8.8 5.1 9.8 3.0 10.0 5.1 9.8
Kenya, 2014 6.5 6.2 4.4 27.3 3.0 20.0 3.9 23.1
Lesotho, 2014 1.9 31.6 4.0 32.5 2.9 24.1 3.3 30.3
Liberia, 2013 5.9 11.9 5.1 11.8 3.4 11.8 4.7 10.6
TABLE 5-4 Total Fertility Rate and Percentage of Births Unwanted, by Mother’s Education, in Countries with DHS
Surveys Around 2010 and Beyond
Madagascar,
2008–2009 6.4 10.9 5.3 13.2 3.1 12.9 4.8 12.5
Malawi, 2010 6.9 18.8 5.9 20.3 3.6 16.7 5.7 21.1
Mali, 2012–2013 6.5 13.8 5.9 15.3 4.0 10.0 6.1 13.1
Namibia, 2013 5.3 26.4 4.8 27.1 3.3 15.2 3.6 19.4
Niger, 2012 8.0 2.5 7.0 5.7 4.9 4.1 7.6 2.6
Nigeria, 2013 6.9 2.9 6.1 6.6 4.2 7.1 5.5 5.5
Rwanda, 2014–2015 5.1 25.5 4.5 26.7 3.0 16.7 4.2 26.2
Senegal, 2014 6.2 11.3 4.4 9.1 3.2 6.3 5.0 10.0
Tanzania, 2010 7.0 10.0 5.6 14.3 3.0 10.0 5.4 13.0
Uganda, 2011 6.9 23.2 6.8 25.0 4.8 18.8 6.2 24.2
Zambia, 2013–2014 7.2 13.9 6.3 14.3 3.8 13.2 5.3 15.1
North Africa/West Asia/Europe
Armenia, 2010 — — 1.9 15.8 1.7 5.9 1.7 5.9
Egypt, 2014 3.8 21.1 3.6 22.2 3.5 20.0 3.5 20.0
Jordan, 2012 3.0 36.7 3.9 30.8 3.5 28.6 3.5 28.6
South and Southeast Asia
Bangladesh, 2014 2.4 37.5 2.4 29.2 2.2 18.2 2.3 26.1
Cambodia, 2014 3.3 12.1 3.1 9.7 2.3 4.3 2.7 11.1
Indonesia, 2012 2.8 10.7 2.9 13.8 2.6 15.4 2.6 15.4
Nepal, 2011 3.7 32.4 2.7 29.6 1.9 21.1 2.6 30.8
Pakistan, 2012–2013 4.4 20.5 4.0 20.0 2.9 17.2 3.8 21.1
Latin America and Caribbean
Colombia, 2010 4.3 39.5 3.2 34.4 2.0 20.0 2.1 23.8
Dominican Republic,
2013 5.1 25.5 3.2 28.1 2.3 13.0 2.5 20.0
Haiti, 2012 5.4 40.7 4.3 37.2 2.6 19.2 3.5 34.3
Honduras,
2011–2012 4.1 29.3 3.5 25.7 2.4 16.7 2.9 24.1
Peru, 2012 4.7 46.8 3.5 37.1 2.3 21.7 2.6 30.8
Data from Macro International Inc., 2010–2015, MEASURE DHS STAT compiler. Accessed on November 10, 2016 from http://www.measuredhs.com
proportions of unwanted births (the mean percent- ages were 8% for Eastern Europe and 16% for sub- Saharan Africa). Now the low-fertility region (Latin America and Caribbean) with average TFR of 2.72 births per woman has a 26.6% rate of unwanted births compared to a 14.8% rate of unwanted births in sub- Saharan countries with average TFR of 5.16 births per woman. This change is possibly due to faster decline of desired fertility than actual fertility in low-fertility regions, while in high-fertility countries both desired and actual fertilities decreased in the same pace. Vari- ations in this regard are also evident by countries within and between regions. Some countries with high total fertility rates had low proportions of unwanted births (e.g., Niger), whereas Uganda has high propor- tion of unwanted births despite a relatively high TFR.
The highest percentages of unwanted births (one- fourth or more) were found in countries with TFRs between 2.5 and 5.5 births per woman. Finally, in low- fertility countries where the TFR is less than 4 births per woman, a substantial proportion of those births remain unwanted (Macro International, 2015).
Note that this and earlier evidence suggest that increases in contraception prevalence rates do not necessarily cause a decline in the proportion of unwanted births and, in fact, may initially be associ- ated with an increase in the proportion of unwanted births (Tsui et al., 1997). This scenario can happen if desired fertility rates drop faster than the compensat- ing rises in contraceptive prevalence rates, and if the use of methods of fertility control is so effective that unintended births rarely occur. Thus, when couples have very high fertility desires, it is difficult to exceed those desires, so nearly all children are wanted. As desired fertility falls, use and effective use of contra- ception and abortion may not increase quickly enough to avoid unwanted births. Finally, at low levels of fer- tility, women want so few children that there remain many years after the last wanted child during which an unwanted pregnancy and birth can, and frequently do, occur. The differences by education within a coun- try can, in part, be explained by this phenomenon:
More-educated women within a society frequently are earlier adopters of contraception and, because they desire few children, a higher proportion of their chil- dren are unwanted.
With regard to mistimed births, DHS data from selected countries around 2005 (2002–2010) sug- gest that approximately 16% of births in LMICs were mistimed—that is, they came too early (Bradley, Croft,
& Rutstein, 2011). Highest proportion of mistimed births is reported from Latin America (29%), followed by Africa (20%), Asia (15%), the Middle East (11.5%),
and Europe (10%) (Bradley et al., 2011). There is no clear association between contraceptive prevalence and the proportion of mistimed births. Thus, even in a region such as sub-Saharan Africa, where contracep- tive use rate is low, considerable mistimed fertility is still observed. Contraceptive failures contributed only 29% of total mistimed births, while 71% of such births resulted from lack of contraceptive use ( Bradley et al., 2011). This finding suggests that there is a need for contraception to delay first births and control spac- ing of subsequent births even when there may be lit- tle demand for contraception to control the number of births (Bankole & Westoff, 1995; Rafalimanana &
Westoff, 2001).