PRB Family Planning Data Sheet

2019Family Planning Data

What drives differences in family planning use across countries? How does the mix of contraceptive methods vary across countries and regions? To answer these questions and more, the 2019 Family Planning Data feature digs into fertility intentions, method mix, unmet need for family planning, reasons for not using family planning, and approaches for estimating contraceptive use.

Estimating Contraceptive Use
Survey vs. Modeled Estimates

The 2019 Family Planning Data Sheet presents survey estimates of contraceptive prevalence, one of two methods of estimating national contraceptive prevalence widely used today. To calculate these estimates, surveys are conducted that ask a nationally representative sample of women of reproductive age about their use of contraceptive methods. Such surveys include the Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), Performance Monitoring and Accountability 2020 (PMA2020) surveys, and others national surveys.

A second method of estimating contraceptive use, modeled estimates, come from statistical models developed using a set of available data points and assumptions relevant to contraceptive use. Modeled estimates of contraceptive use for countries around the world are produced using a modeling program called the Family Planning Estimation Tool (FPET) developed as part of a collaboration between the United Nations Population Division, the University of Massachusetts at Amherst, and Track20. FPET determines long-term trends in contraceptive use for countries based on all available survey estimates of contraceptive use and then produces current estimates and future projections. It can assign different weights to different sources of survey estimates, so the estimates from more reliable sources have a greater impact in the model. For some countries, FPET also incorporates service statistics to inform trends in contraceptive use. The model can also indicate the levels of uncertainty around their estimates. The accuracy of the FPET estimates therefore improves with the number of survey estimates available, the reliability of those estimates, the length of the period they cover, and the timeliness of the latest available estimates.

When a country has had a survey in a recent year, the modeled estimate for the current year should be similar to the latest survey estimate available. Modeled estimates are particularly valuable when no recent survey estimates are available. They may also provide insight when there are multiple estimates from different surveys that cover a similar period. However, it is important to understand the assumptions and strength of underlying data used to generate them.

Select Country

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Africa
Asia
Europe
Americas
Oceania

SELECT A COUNTRY mCPR

mCPR

Top three modern contraceptive methods

Modern Contraceptive Use Differs
Substantially Across Countries

While modern contraceptive use has increased around the world today, in many of the poorest countries, fewer than 15 percent of married women of reproductive age use a modern method. Eighteen countries currently fall into this lowest category of modern contraceptive use. Yet, at the same time, in more than 40 countries, at least 60 percent of married women of reproductive age use a modern method.

SURVEY VS. MODELED ESTIMATES

PERCENT OF MARRIED WOMEN AGES 15-49 USING MODERN CONTRACEPTION, 2018

SELECT A COUNTRY mCPR

mCPR

Top three modern contraceptive methods

< 15%
15-29%
30-44%
45-59%
≥ 60%
Data not available

SELECT COUNTRY

Sources: Demographic and Health Surveys (DHS); UNICEF, Multiple Indicator Cluster Surveys (MICS); Pan-Arab Project for Family Health; Performance Monitoring and Accountability (PMA) Surveys; U.S. Centers for Disease Control and Prevention, Reproductive Health Surveys; United National Population Division, World Contraceptive Use 2018; and national surveys.

Notes: In Argentina, Botswana, Canada, Czechia, Germany, Norway, Spain, and Uruguay, family planning use data refer to sexually active women, ever-married women, or all women.

In Argentina, Botswana, Canada, Uruguay, Japan, Ireland, and United Kingdom, figures by method do not add up to the total because some methods are used in combination.

The exact modern contraceptive prevalence rate for Canada is not available, but method-specific information indicates that it is greater than or equal to 60%.

China, Hong Kong SAR is a Special Administrative Region

More Educated Men and Women Want Smaller Families Than Those With Less Education

Examining men's and women's average ideal number of children provides insights into their fertility preferences across and within countries. Men generally report wanting more children than women do, but differences narrow or disappear in countries such as Haiti and India, where the desired number of children is relatively low.

Both men and women with at least secondary education report wanting fewer children than those with no secondary education. In countries where the desired number of children is relatively high, such as Mali and Nigeria, differences by educational status are particularly large among men.

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AVERAGE IDEAL NUMBER OF CHILDREN BY SEX AND EDUCATION

India 2015-16

2.5 2.5 1.9 2.1

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Haiti 2016-17

3.1 3.1 2.6 2.7

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Malawi 2015-16

3.9 3.9 3.0 3.2

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Zimbabwe 2015

4.8 5.3 3.6 4.2

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Tanzania 2015-16

5.1 5.5 3.7 3.9

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Zambia 2013-14

5.2 5.8 4.0 4.4

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Senegal 2017

5.7 8.0 4.4 5.5

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Mali 2012-13

6.1 8.4 4.8 6.0

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Nigeria 2013

7.9 10.8 5.0 6.3

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Kenya 2014

3.0 3.5 4.1 4.3

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Armenia 2015-16

2.6 2.6 2.7 2.8

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Source: Demographic and Health Surveys.

Method Types Remain Limited Despite Increasing Contraceptive Use

While increases in contraceptive use have been nearly universal, the types of methods commonly used are different across countries. For instance, while injectables are the most commonly used method in Kenya, Tanzania, and Ethiopia, the pill is the most widely used method in the Philippines and sterilization is the most commonly used method in Guatemala.

In many countries, recent increases in contraceptive use have been concentrated in one or two method types. While countries such as Tanzania have increased contraceptive use across a variety of methods, other countries show a skewed method mix, meaning one method accounts for more than half of all method use. For instance, in Ethiopia, the method mix is dominated by injectables. A skewed method mix indicates that women may lack access to a full range of choices. Introducing new contraceptive methods as well as expanding access to currently available methods can help countries increase contraceptive use.

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PERCENT OF ALL WOMEN AGES 15-49 USING CONTRACEPTION BY METHOD USED

Armenia

2015-16 2000

0% 5.7% 0.1% 1.7% 9.6% 0.5% 0.6% 18.6% 36.7%

0% 6.1% 0% 0.7% 4.4% 1.8% 1.3% 24.6% 39.0%

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Bangladesh

2011 1996-97

1.1% 0.7% 10.5% 25.5% 5.2% 5.9% 0% 8.6% 57.4%

0.1% 1.7% 5.9% 19.5% 3.6% 8.7% 0% 7.1% 46.6%

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Benin

2011-12 1996

0.8% 0.4% 1.7% 1.3% 3.2% 0.1% 1.4% 5.0% 14.0%

0% 0.4% 0.6% 1.0% 1.0% 0.3% 0% 13.4% 16.8%

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Bolivia

2008 1994

0% 5.6% 7.4% 2.4% 3.6% 4.4% 0.6% 17.4% 41.3%

0% 5.2% 0.5% 1.9% 1.0% 3.1% 0.1% 18.3% 30.1%

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Burkina Faso

2010 1998-99

2.9% 0.2% 5.1% 2.8% 3.1% 0.1% 0.1% 1.0% 15.3%

0.2% 0.4% 0.9% 1.7% 2.5% 0.1% 0.1% 6.2% 12.0%

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Cambodia

2014 2000

1.5% 3.0% 6.2% 11.9% 1.5% 2.3% 0.1% 11.9% 38.5%

0.1% 0.7% 4.4% 2.7% 0.6% 1.0% 1.8% 3.0% 14.2%

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Cameroon

2011 1998

0.5% 0.2% 2.3% 1.6% 10.8% 0.4% 0.3% 7.5% 23.7%

0% 0.5% 0.7% 1.9% 3.5% 1.2% 0.2% 16% 24.0%

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Chad

2014-15 1996-97

0.9% 0% 1.8% 0.3% 0.7% 0.2% 0.9% 0.5% 5.4%

0% 0% 0.2% 0.6% 0.3% 0.1% 0% 2.7% 3.9%

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Colombia

2015 1995

5.1% 3.9% 11.9% 6.5% 6.6% 27.4% 0.1% 3.5% 64.9%

0.4% 7.4% 1.8% 8.5% 3.2% 17.3% 1.0% 8.6% 48.1%

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Comoros

2012 1996

1.1% 0% 3.7% 2.0% 1.9% 0.6% 0.5% 3.8% 13.7%

0% 0.2% 2.5% 1.9% 1.6% 1.6% 0% 6.1% 13.8%

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Côte d'Ivoire

2011-12 1998-99

0.1% 0.1% 1.9% 6.1% 5.0% 0.1% 0.6% 5.8% 19.7%

0.1% 0.3% 1.1% 3.7% 4.4% 0.2% 0% 10.9% 20.7%

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Dominican Republic

2013 1996

0.3% 1.4% 4.2% 11.7% 4.5% 29.9% 0.5% 2.5% 55.1%

0.5% 2.0% 0.4% 8.4% 1.2% 28.7% 0.2% 3.3% 44.6%

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Egypt

2014 1995

0.5% 28.3% 8.0% 15.1% 0.4% 1.1% 0.1% 1.5% 55.0%

0% 27.8% 2.2% 9.7% 1.3% 1.1% 0.1% 2.2% 44.4%

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Malawi

2015-16 2000

9.0% 0.8% 22.5% 1.7% 2.6% 8.4% 0.1% 0.8% 46.0%

0.1% 0.1% 13.0% 2.3% 1.9% 3.8% 0.3% 3.4% 25.0%

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Kenya

2014 1998

7.1% 2.3% 18.7% 5.5% 3.1% 2.2% 0.1% 3.5% 42.6%

0.7% 1.9% 8.8% 6.5% 1.5% 4.2% 0% 6.3% 29.9%

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Guatemala

2014-15 1995

1.2% 1.0% 10.3% 2.2% 3.0% 14.4% 0.2% 7.2% 39.4%

0% 1.7% 1.6% 2.6% 1.5% 10.9% 0% 3.0% 21.4%

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Philippines

2017 1998

0.7% 2.2% 3.1% 12.7% 1.1% 4.8% 0.3% 8.7% 33.6%

0% 2.2% 1.4% 5.9% 1.0% 6.5% 0.1% 11.8% 28.9%

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Ethiopia

2016 2000

5.7% 1.4% 15.8% 1.3% 0.1% 0.3% 0.2% 0.5% 25.3%

0% 0.1% 2.1% 1.9% 0.4% 0.2% 0% 1.2% 5.9%

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Tanzania

2015-16 1996

5.6% 0.7% 9.9% 4.1% 3.9% 2.5% 0.3% 5.3% 32.4%

0% 0.5% 3.7% 4.8% 1.3% 1.4% 0% 4.3% 16.1%

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Gabon

2012 2000

0% 0.1% 0.2% 3.9% 18.5% 0.4% 0.9% 9.7% 33.6%

0% 0.1% 0.4% 4.4% 8.4% 0.8% 0.1% 21.3% 35.6%

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Ghana

2014 1998

3.7% 0.5% 6.0% 3.9% 2.0% 1.3% 0.5% 4.6% 22.8%

0.1% 0.5% 2.2% 3.1% 2.8% 0.9% 1.0% 7.4% 18.0%

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Guinea

2012 1999

0.1% 0.2% 1.6% 1.6% 2.4% 0.1% 1.1% 1.5% 8.5%

0% 0.2% 1.1% 2.0% 1.3% 0.3% 0% 2.7% 7.6%

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Haiti

2016-17 2000

1.4% 0.1% 12.0% 1.4% 6.2% 0.8% 0.4% 1.8% 24.1%

1.3% 0.1% 7.7% 1.4% 2.9% 2.0% 0.3% 3.6% 19.4%

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Honduras

2011-12 2005-06

0% 4.6% 11.2% 7.4% 3.6% 16.1% 0% 5.9% 48.8%

0% 4.4% 8.6% 7.1% 2.3% 15.1% 0.1% 5.4% 43.2%

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Indonesia

2012 1997

2.4% 3.0% 23.5% 10.0% 1.3% 2.5% 0% 3.0% 45.7%

5.6% 7.6% 19.7% 14.4% 0.6% 3.3% 0% 2.5% 53.7%

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Jordan

2012 1997

0.3% 20.3% 0.9% 7.7% 7.5% 2.2% 1.5% 17.9% 58.3%

0.1% 22.3% 0.7% 6.3% 2.3% 4.2% 0.5% 14.3% 50.7%

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Kyrgyzstan

2012 1997

0% 14.6% 0.3% 1.1% 5.3% 1.1% 0.1% 1.7% 24.4%

0% 27.6% 0.9% 1.2% 4.1% 1.4% 0.1% 7.5% 42.8%

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Liberia

2016 2007

3.5% 0.3% 18.9% 4.9% 1.3% 0.9% 1.1% 0.3% 31.0%

0% 0.2% 3.7% 3.8% 3.5% 0.4% 0% 1.6% 13.3%

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Mali

2012-13 1995-96

2.4% 0.3% 3.8% 2.6% 0.2% 0.1% 0% 0.4% 9.9%

0.1% 0.3% 0.2% 3.4% 0.7% 0.2% 0.1% 2.9% 7.9%

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Mozambique

2015 1997

1.7% 0.7% 11.7% 6.3% 4.0% 0.2% 1.2% 1.7% 27.4%

0% 0.4% 2.2% 1.6% 0.4% 0.7% 0% 0.7% 6.0%

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Namibia

2013 2000

0.1% 0.6% 21.2% 4.5% 19.2% 2.9% 1.2% 0.5% 50.2%

0% 0.7% 17% 5.7% 8.9% 4.6% 0.1% 0.7% 37.8%

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Nepal

2016 1996

2.6% 1.1% 6.9% 3.5% 3.3% 15.8% 0% 7.6% 40.8%

0.4% 0.2% 4.3% 1.3% 1.8% 16.5% 0.1% 2.3% 27.0%

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Niger

2012 1998

0.3% 0.1% 1.9% 5.0% 0.1% 0.1% 3.5% 1.5% 12.5%

0% 0.1% 1.3% 2.6% 0.1% 0.1% 0.1% 3.2% 7.6%

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Peru

2012 1996

0% 1.9% 11.9% 6.3% 9.8% 5.8% 0.5% 15.4% 51.5%

0.2% 7.6% 5.0% 4.0% 3.1% 6.1% 0.5% 14.5% 40.9%

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Rwanda

2014-15 2000

4.7% 0.7% 14.1% 4.7% 2.2% 0.8% 0.5% 3.1% 30.9%

0.1% 0.1% 1.0% 0.5% 0.5% 0.5% 0.7% 4.0% 7.4%

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Senegal

2017 1997

5.9% 1.5% 7.1% 2.9% 1.1% 0.2% 0.1% 1.0% 19.9%

0.2% 1.4% 1.3% 2.7% 1.0% 0.4% 0.2% 3.8% 10.8%

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Togo

2013-14 1998

3.4% 0.6% 5.1% 1.9% 5.4% 0.2% 0% 2.6% 19.3%

0.4% 0.8% 1.7% 1.1% 3.4% 0.3% 0.2% 17.5% 25.3%

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Turkey

2013 1998

0% 11.5% 0.4% 3.1% 10.7% 6.5% 0.1% 17.5% 49.7%

0% 13.7% 0.3% 3.0% 5.7% 3.0% 0.4% 18.0% 44.2%

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Uganda

2016 1995

4.7% 1.1% 13.9% 1.5% 3.1% 1.9% 1.0% 3.0% 30.3%

0% 0.3% 2.0% 2.3% 1.5% 1.2% 0.1% 6.0% 13.4%

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Yemen

2013 1997

0.6% 5.9% 4.2% 11.6% 0.5% 2.4% 4.0% 4.3% 33.5%

0% 2.8% 1.1% 3.6% 0.2% 1.5% 0.1% 10.3% 19.6%

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Zambia

2013-14 1996

4.2% 0.9% 13.8% 8.0% 3.5% 1.3% 0.8% 2.7% 35.1%

0% 0.3% 0.7% 5.2% 3.5% 1.4% 0.1% 7.9% 19.2%

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Zimbabwe

2015 1999

8.1% 0.4% 7.2% 27.0% 4.2% 0.6% 0.3% 0.7% 48.6%

0.4% 0.7% 5.9% 23.8% 2.3% 2.0% 0.6% 2.1% 37.7%

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- Africa
- Asia
- Americas

Notes: Total contraceptive prevalence rate (CPR) may not equal the sum of the individual methods due to rounding. The two surveys shown for Bangladesh, Egypt, and Jordan, as well as the earlier surveys for Nepal, Indonesia, and Yemen represent data for ever-married women.

Source: Demographic and Health Surveys.

What Is Unmet Need?

Women are considered to have unmet need if they are not using any contraception and are:

Married/in union or are single and sexually active, able to become pregnant, and do not want a child in the next two years or at all.
Pregnant or postpartum amenorrheic and identify their current pregnancy or recent birth in the last two years as unintended.

Women with met need are those who currently use any form of contraception. Women with no need are those who are not sexually active, are infecund, or want to become pregnant in the next two years.

Unpacking Unmet Need for Family Planning

WHAT IS UNMET NEED?

Estimates of unmet need for family planning can help identify where greater investments of family planning program resources are necessary to increase contraceptive use.

Unmet need may exist because women desire to space (they want a child after two or more years) or to limit (they want no more children) childbearing.

Combining unmet need with met need provides a picture of the total demand for family planning in a country. Countries with the same level of unmet need can differ greatly in total demand for family planning. For example, in both Mozambique and Chad, 19 percent of women of reproductive age have an unmet need for family planning. However, Mozambique has a much higher share of women using contraception at 27 percent for a total demand for family planning of 46 percent. In contrast, only 5 percent of women in Chad use contraception for a total demand for family planning of 24 percent. While both countries have high fertility, Mozambique has a lower total fertility rate (TFR) at 5.3 compared to a TFR of 6.4 in Chad.

Total demand for family planning increases as more women want to postpone (space) or stop (limit) childbearing, but levels of unmet need depend on the share of those women who use contraception. Reducing unmet need involves converting fertility preferences or contraceptive intentions into contraceptive use.

PERCENT OF ALL WOMEN AGES 15-49

Total demand for family planning

54%No Demand

Unmet Need

Met Need

diagram

diagram

diagram

diagram

Mozambique

TFR 5.3 2015

Total demand for family planning

76%No Demand

Unmet Need

Met Need

diagram

diagram

diagram

diagram

Chad

TFR 6.4 2014-15

Source: Demographic and Health Surveys.

PERCENT OF ALL WOMEN AGES 15-49

Total demand for family planning
Unmet Need
Met Need
No Demand

Reasons for Not Using Contraception Vary by Age

If policies and programs aim to reduce unmet need for family planning, it is important to understand why women with unmet need are not using contraception. Women with unmet need (both married and unmarried) in developing countries give a variety of reasons when asked why they are not using contraception despite not wanting a pregnancy. Reasons typically include opposition to use, concerns about side effects, postpartum amenorrhea, and infrequent or no sex. Lack of knowledge about a method or source also poses a significant barrier in certain countries such as the Democratic Republic of Congo (DRC) and Nigeria.

The relative importance of the reasons given may vary by age. Fear of side effects and, to a lesser extent, opposition to use are generally stronger concerns among women ages 25 and older. Postpartum breastfeeding is often cited by women under age 25 as a reason for not using contraception, potentially leaving these women at risk of an unintended pregnancy.

REASONS FOR NOT USING FAMILY PLANNING BY AGE GROUP AMONG ALL WOMEN WITH UNMET NEED

CONGO
DRC
KENYA
NAMIBIA
NIGERIA
UGANDA

2011-12 2013-14 2014 2013 2013 2011

Opposition
(self or others)

0%

0%
Side effects /
health impacts

0%

0%
No knowledge of
method / source

0%

0%
Cost

0%

0%
No / infrequent sex

0%

0%
Postpartum / breastfeeding

0%

0%

Top Line

Age < 25
Bottom Line

Age 25+

Source: Demographic and Health Surveys.

Countries Can Take Immediate Steps to Improve Their Voluntary Family Planning Programs and Services

Tailor investments to the local context

To be successful, investments should be based on the specific country context to increase or maintain contraceptive use and reduce unmet need. Depending on current total demand for family planning and contraceptive use, countries may benefit from strengthening service delivery and the family planning supply chain, or from demand generation through education programs.

Expand access to a full range of methods

Policymakers can promote contraceptive use and improve choice by ensuring that women have access to full range of contraceptive methods, including long-acting reversible contraceptives (LARCs).

Address key barriers among women with unmet need

Program staff can use data on the top reasons why women with unmet need don't use contraception—such as fear of side effects and being postpartum or breastfeeding—to reduce such barriers through user education or provider training.

VIEW DATA SHEET

Video Center

At the 2018 International Conference on Family Planning (ICFP), PRB was able to catch up with some of the foremost experts in family planning for their insights into trends in contraceptive prevalence (both globally as well as specifically in Kenya and Tanzania) and fertility preferences. Watch the videos below to see what experts had to say about the topics in our family planning web feature!

Explore data from PRB's data center

PERCENT OF MARRIED WOMEN 15-49 USING CONTRACEPTION, ALL METHODS

PERCENT OF MARRIED WOMEN 15-49 USING CONTRACEPTION, MODERN METHODS

DEMAND SATISFIED BY MODERN METHODS AMONG MARRIED WOMEN

TOTAL FERTILITY RATE

CURRENT YEAR POPULATION

MORE INDICATORS