Datos de la población mundial 2015. (Population Reference Bureau) 2015 world-population-data-sheet e

P OPUL AT ION R EF E RENC E BUR E AU

2015 World Population Data Sheet w i t h a s p e c i a l f o c u s o n w o m e n ’s e m p o w e r m e n t

71 Worldwide average life expectancy in years— 73 years for women, 69 years for men.

7.3

$15,030

The world population in 2015.

Average global gross national income per capita—$39,020 in more developed countries, $2,270 in least developed.

billion

I N F O R M | E M P O W E R | A DVA N C E | w w w. p r b .o r g

MOST POPULOUS COUNTRIES, 2015 AND 2050 2014

COUNTRY, 2015

2050

POPULATION (MILLIONS)

COUNTRY, 2050

POPULATION (MILLIONS)

China

1,372

India

1,660

India

1,314

China

1,366

United States

321

United States

398

Indonesia

256

Nigeria

397

Brazil

205

Indonesia

366

Pakistan

199

Pakistan

344

Nigeria

182

Brazil

226

Bangladesh

160

Bangladesh

202

Russia

144

Congo, Dem. Rep.

194

Mexico

127

Ethiopia

165

COUNTRIES WITH THE HIGHEST AND LOWEST TOTAL FERTILITY RATES HIGHEST

2015

LOWEST

2015

Niger

7.6

Bosnia-Herzegovina

1.2

South Sudan

6.9

Korea, South

1.2

Congo, Dem. Rep.

6.6

Portugal

1.2

Somalia

6.6

Taiwan

1.2

Chad

6.5

Greece

1.3

Burundi

6.2

Moldova

1.3

Central African Republic

6.2

Poland

1.3

Angola

6.1

Romania

1.3

Burkina Faso

6.0

Singapore

1.3

Mali

5.9

Spain

1.3

Mozambique

5.9

Uganda

5.9

NOTE: 2015 data refer to latest data available.

© 2015 Population Reference Bureau

See notes on page 21

2015 WORLD POPULATION DATA SHEET

2

POPULATION CLOCK, 2015 WORLD

MORE DEVELOPED COUNTRIES

LESS DEVELOPED COUNTRIES

7,336,435,000

1,254,199,000

6,082,235,000

Year

145,973,000

13,760,000

132,213,000

Day

399,926

37,700

362,226

278

26

252

Year

57,052,000

12,283,000

44,769,000

Day

156,306

33,652

122,654

Population

Births per

Minute

Deaths per

109

23

85

Year

88,921,000

1,477,000

87,444,000

Day

243,620

4,047

239,573

169

3

166

Year

5,351,000

73,000

5,278,000

Day

14,660

201

14,459

10

0.1

10

Minute

Natural increase per

Minute

Infant deaths per

Minute

© 2015 Population Reference Bureau

See notes on page 21

2015 WORLD POPULATION DATA SHEET

3

WPO DT I OPNOHPI GUHLL IAG TH TI SO WOR LD O PRULL A

OPULATION (MILLIONS)

N

FOCUS ON WOMEN’S EMPOWERMENT

FOCUS ON WOMEN’S EMPO

1,660

Rates of Early Marriage Fall, Particularly Among Those Under 15 1,366

Women Post Uneven Gains in Household Decisionmaking Power

Rates of Early Marriage Fall, Particularly Among Those Under 15

Women

Early marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to 398 risks of early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of 20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases.

397 attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls girls educational Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types also can help delay marriages. In Bangladesh, employment in the garment is linked to the notably lower rates marriage of important decisions. For example, only 66them percent vulnerable of women have ato saythe about their own health care decisions.

The same women in Early expanded marriage (before age 18) industry undermines rights andoflivelihood opportunities of adolescent girls inbyNepal, leaving health Married among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest percentage of Zambian women have the opportunity to make decisions about large household purchases.

366 risks of early pregnancy childbearing, and prematurely every type of dec potential brides tend to postpone marriage by only a few years.

The majorityand of Bangladeshi girls continue to marry before age 18.ending their schooling. Rates of early marriage have declined broadly in the past

20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As of Currently Married Women Who Have a Say Decisions and Aboutgirls This Topic marrying early tends toPercent fall. Better employment opportunities forin women also can help delay marriages. In Bangladesh, expanded employment in the garment industry is linked to notably lower rates of marriage Own Health among rural migrants under age 15. The percentage of Bangladeshi girls married 100 by age 18 has declined much more slowly as the youngest potential brides tend to postpone marriage by only a few years. The majority of Bangladeshi girls continue to marry before age 18.

344

Percent of Young Women Married girls

by Age 15 (numbers inattainment white) and Age 18 (numbersthe in black) educational improves, proportion

226

202 194

90

83

165

76

80 Percent of Young Women Married by Age 15 (numbers in white) and Age 18 (numbers in black) 65

70 60

49 47

2015

76

29

28

1.2

19

1.2

2012

1993 – 1994

Niger 1.2

2011

2000

Bangladesh

20

16

1.2 1992

19

18

17

2011

Ethiopia

7

2

1992

2014

65

10 3

3

1991– 1992

Egypt

1.3

47

EVELOPED COUNTRIES

Niger

2012– 2013

2001

2006

2011

2001– 2002

Nepal

2007

2013– 2014

2000

Zambia

2004 – 2012 2006

36

Philippines

2012

60 50

2011

19

2011

1992

Ethiopia

71

17 17

7

Percent Who Agree That Husband Is 2Justified Beating Wife if 3 She Leaves 3the House Without Informing Him

2000

80

Bangladesh

40

2014

1991– 1992

Egypt

2012

0 Men

Women

2001 2

Peru

M

40

38

26

32

43

47

2006

2011

Uganda

Source: ICF Intern 13

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

Family Planning Needs Increasingly Met by Modern Methods, 31

25

19

52 Kenya

2007

Jordan

27 a serious challenge to women’s empowerment. Combating such violence often requires changing Violence against women poses 30 the attitudes and beliefs of both men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife 19 18that these beliefs appear to be moderating in most countries.

17husband. It is encouraging who goes out on her own without telling the 20 For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable 16 drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global 10 tolerance of this harmful practice.

58

40

2002

Peru

52

© 2015 Population Reference Bureau 362,226

252

70

Source: ICF International, Demographic and Health Surveys.

082,235,000 41

80

15

Acceptance of Wife Beating Recedes

64 Egypt

132,213,000 Jordan

27

18

Source: ICF International, Demographic and Health Surveys.

28 as a key indicator of contraceptive availability and use. The 1.3 “Demand for family planning satisfied with modern methods” has emerged indicator measures the proportion of women who want to delay or limit childbearing and who are using modern methods of contraception.

Family planning 1.3 experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two decades, a significant number of less developed countries have seen increases in the share of demand satisfied with modern methods, but many countries remain far below the proposed 75 percent benchmark. They will need to accelerate progress over the coming decade so that increased contraceptive use can translate into improved maternal and child health, slower population growth, increased economic well-being, and environmental sustainability.

1993 – 1994

90

41

29

2012

100

37

Mali

49

1.3 Planning Needs Increasingly Met by Modern Methods, Family 1.3 but More Progress Needed

1992

18

2001 2006

Peru

47

Percent of Demand for Family Planning Satisfied by Modern Contraceptive Methods

17

20

64

0

2012

1.3

Source: ICF International, Demographic and Health Surveys.

17

77

71

42

30

73

89

56

32

27

91

Percent of Curr

79

72

66

57

47

40

83

75

50

41

47

53

74

74 65

66

88

84

83

73

women and child Progress in these important deci Largeof Purchases percentage of Za

4

Accepta

L AWTOI ROL DN P OHPIUG L AH T ILOINGHH I GTH S LIGHTS OCUS ON W O M E N ’ S E M P O W E RFM ENT

WOMEN’S EMPOWERMENT

Rates of Early Marriage Fall, Particularly Among Those Under 15

der 15

Women Post Uneven Gains in Household Decisionmaking Power

Women Post Uneven Gains in Household Decisionmaking Power

Early marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to risks of early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of 20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases. girls educational attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types alsothe can health help delay marriages. In Bangladesh, expanded employment in the garment industry are is linked to notably lowerlikely rates ofto marriage of important decisions.

For example, in Nepal,gains only 66 percent of women have a sayapply about their le to Married women in many countries increasingly have a say in household decisions, but these do not necessarily to own health care decisions. The same among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest percentage of Zambian women have the opportunity to make decisions about large household purchases. adlypotential in thebrides pasttend to postpone marriage every of decision. women are included in decisions about household spending, more money tends to be spent for the benefit of by onlytype a few years.

The majorityWhen of Bangladeshi girls continue to marry before age 18.

ducation: As women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases.

Percent Age 15 (numbers in white) andhas Age varied 18 (numbers in black) and even in countries showing Percent of Currently Married Women Who Have a Say in Decisions Topic n and girlsof Young Women Married by Progress in these areas by country, notable gains, many women still do not engage About in allThis types of marriage of important decisions. For example, in Nepal, only 66 percent of women have a say about their own health care decisions. The same Own Health as the youngest percentage of Zambian women have the opportunity to make decisions about100 large household purchases. e 18.

–

90

83

76

73

65

47

100

47

27

19

30

2012

1993 – 1994

2011

60 Bangladesh

Niger

74

16

2000

2011

Ethiopia

7

2

1992

2014

Egypt

3

3

66 1991– 53

65

2012

1992

57

56

Mali

64 Egypt

84

89

74

15 75

79

77

72

2012– 2013

2001

71 2006

2011

2001– 64 2002

Nepal

2007

2013– 2014

2000

Zambia

2004 – 2012 2006

2006

2011

802001–

2002

71

Nepal

2007

2013– 2014

2000

Zambia

2004 – 2012 2006

2002

Peru

2007

Jordan

52

40 © 2015 Population Reference Bureau

hods,

36

Philippines

Men

Women

2012

40

38

26

32

43

47

2006

Acceptance of Wife Beating Recedes 31

2011

Uganda

25

19

52 Kenya

2012

Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him

58

Jordan

2007

Jordan

Source: ICF International, Demographic and Health Surveys.

Source: ICF International, Demographic and Health Surveys.

41

2002

Peru

Violence against women poses a serious challenge to women’s empowerment. Combating such violence often requires changing the attitudes and beliefs of both men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife who goes out on her own without telling the husband. It is encouraging that these beliefs appear to be moderating in most countries.

For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global tolerance of this harmful practice.

3

2001

91

37

Acceptance of Wife Beating Recedes

37

Percent of Demand for Family Planning Satisfi 0 ed by Modern Contraceptive Methods

2012– 2013

42

88

42

“Demand for family planning satisfied with modern methods” has emerged as a key indicator of contraceptive availability and use. The 19 20 childbearing 27 modern methods of contraception. indicator measures the proportion of women who want to delay or limit 18 and who are using 17 20 for meeting Family planning experts have urged countries to strive at least 75 percent of demand with modern methods. Over the past two decades, a significant number of less developed countries have seen increases in the share of demand satisfied with modern methods, 18 They will need to accelerate progress over the coming decade but many countries remain far below the proposed 75 percent 17 benchmark. so that increased contraceptive use can translate10 into improved maternal and15 child health, slower population growth, increased economic well-being, and environmental sustainability.

2001 2006

64

27

18

Mali

47

40

18

2001 2006

Peru

Family Planning Needs Increasingly Met by Modern Methods, 32 but More Progress Needed 30

Peru

17

20

77

56

0

66

Source: ICF International, Demographic and Health Surveys.

50

2012

17

20 10

70 1992

83

19

18

17

32

89

71

66 Large Purchases

57

47

40

29

80

53

66

91

79

72

65

50

41

90 28

75

Own Health

60

49

74

74

70

88

84

83

80 Percent of Currently Married Women Who Have a Say in Decisions About This Topic

Large Purchases

13

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

5

2 1992

2012

1993 – 1994

2011

2000

2011

1992

2014

1991– 1992

0

2012

2001 2

WO R L D P O P U L AT I O N H I G H L I G H T S Niger

EVELOPED OUNTRIES

Ethiopia

Egypt

Peru

FOCUS ON WOMEN’S EMPOWERMENT

Source: ICF International, Demographic and Health Surveys.

82,235,000

132,213,000 Rates of

Bangladesh

Early Marriage Fall, Particularly Among Those Under 15

Source: ICF Intern

Women Post Uneven Gains in Household Decisionmaking Power

Early marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health 362,226 risks of early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past 20 years,252 particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As girls educational attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls also can help delay marriages. In Bangladesh, expanded employment in the garment industry is linked to notably lower rates of marriage 44,769,000 among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest potential brides tend to postpone marriage by only a few years. The majority of Bangladeshi girls continue to marry before age 18.

Family Planning Needs Increasingly Met by Modern Methods, but More Progress Needed

122,654

Accepta

Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases.

Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types of important decisions. For example, in Nepal, only 66 percent of women have a say about their own health care decisions.

The same against Violence percentage of Zambian women have the opportunity to make decisions about large household purchases.

“Demand for family planning satisfied with modern methods” has emerged as a key indicator of contraceptive availability and use. The Percent of Currently Married Womenmodern Who Havemethods a Say in Decisions About This Topic want to delay or limit childbearing and who are using of contraception.

Family planning experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two Own Health decades, a significant number of less developed countries have seen increases100 in the share of demand satisfied with modern methods, but many countries remain far below the proposed 75 percent benchmark. They will need to accelerate progress over the coming decade 90 84 so that increased contraceptive use can translate into improved maternal and child health, slower population growth, increased economic 83 73 well-being, and environmental sustainability.

80 74 74

Percent of

by Age 15 (numbers in white) Age 18 (numbers in black) measures the and proportion of women who 85Young Women Marriedindicator

87,444,000 239,573 83 166

76

5,278,000

65

14,459

60

49

47

1992

19

18

16 7

2012

1993 – 1994

Niger

2011

Bangladesh

2000

2011

Ethiopia

2

1992

2014

3

3

1991– 1992

Egypt

gross enrollment ratio the tertiary gross Jordan Source: ICF International, Demographic and Health Surveys.

Kenya 41 en. An index less than 40 n are more represented an women, while an index

by Modern ates Family that women arePlanning Needs Increasingly Met Philippines 36 ta arebut from UNESCO More Progress Needed

2012

40

Kenya

36

5

15

58

2012– 2013

2001

Mali

Methods,

2006

2011

2001– 2002

Nepal

2007

52

2013– 2014

2000

Zambia

2004 – 2012 2006

2002

Peru

2007

2012

Jordan

43

47

Acceptance of Wife Beating Recedes 31 Violence against women poses a serious challenge to women’s empowerment. Combating such violence often requires changing the attitudes and beliefs of both men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife who goes out on her own without telling the husband. It is encouraging that these beliefs appear to be moderating in most countries.

For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global tolerance of this harmful practice.

4

Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him Men

Women

80

2002

2006

2010

2014

71 52 40

38

26

32

43

47

2006

31

2011

Uganda

25

19

52

Financial Inclusion of Women Expands

Philippines

27

18

Source: ICF International, Demographic and Health Surveys.

nagricultural

© 2015 Population Reference Bureau s in wage employment sector who are women.

18

2001 2006

Peru

efined as the proportion 13 Senegal 15 years andof older Percent Demand for Family Planning Satisfied by Modern Contraceptive Methods active, including those oyed. A ratio less than 1994 1998 1990 male labor force eater than the female Note: Data points are for each corresponding survey year. ore than one indicates64 Egypt greater than the male Source: ICF International, Demographic and Health Surveys.58 e World Bank for 2013.

Jordan

17

20

0

“Demand for family planning satisfied with modern methods” has emerged as a key indicator of contraceptive availability and use. The Pakistan indicator measures the proportion of women who want 21 to delay or limit childbearing and who are using modern methods of contraception. or Force Family planning experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two decades, a significant number of less developed countries have seen increases in the share of demand satisfied with modern methods, butforce manyparticipation countries remain far below the proposed 75 percent benchmark. They will need to accelerate progress over the coming decade e labor Nigeria 13improved that increased contraceptive use can translate into maternal and child health, slower population growth, increased economic e. Thesolabor force well-being, and environmental sustainability.

41

17

20 10

students. Data are from 14.

der Parity Index

17

71

37

30

64 Egypt

19

42

32

27 29

64

80

56

47

40

28

66

57

50

41

47

53

77

Percent Who Ag 71

72

65

66

w the attitudes and husband has the r who goes out on example, in 20 LargeFor Purchases husband as justific 91 drops 89 for both me 88 tolerance of this h

79

75

70

Percent of Demand for Family Planning Satisfied by Modern Contraceptive Methods

10

M

Source: ICF Interna 13

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

6

U.S. Gen

–

0

2012

2001 2006

2012– 2013

2001

2006

2011

2001– 2002

2007

2013– 2014

2000

2004 – 2012 2006

2002

2007

2012

WO R L D P O P U L AT I O N H I G H L I G H T S

Peru

Mali

Nepal

Zambia

Peru

Jordan

FOCUS ON WOMEN’S EMPOWERMENT

Source: ICF International, Demographic and Health Surveys.

Rates of Early Marriage Fall, Particularly Among Those Under 15

hods,

Women Post Uneven Gains in Household Decisionmaking Power

Acceptance of Wife Beating Recedes

Early marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to risks of early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of 20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases. girls educational attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types also can help delay marriages. In Bangladesh, expanded employment in the garment industry is linked tochallenge notably lower rates of marriage empowerment. of important decisions. Forsuch example, in Nepal, only 66 percent of women have a say about their own health care decisions. The same Violence against women poses a serious to women’s Combating violence often requires changing among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest percentage of Zambian women have the opportunity to make decisions about large household purchases. the and both men and women.

In fact, potential brides tend to postpone marriage by attitudes only a few years.

Thebeliefs majority ofof Bangladeshi girls continue to marry before age 18.in some countries, substantial percentages of women actually agree that a

use. The husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife Percent of Young Women Married by Age 15 (numbers in white) and Age 18 (numbers in black) Currently Married Women Who Have a Say in Decisions About This Topic ontraception. who goes out on her own without telling the husband. It is encouraging thatPercent theseof beliefs appear to be moderating in most countries. r the past two For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the Own Health methods, husband as justification for wife beating, down from 19 percent and 32 percent, 100 respectively, in 2008. Zambia also showed notable ming decade drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global 90 83 84 ed economic 83 tolerance of this harmful practice.

76 73

80

74

74

65 Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him 70 65 66

60

49

80 47

71 52 19

1992

52

2012

1993 – 1994

Niger

2011

Bangladesh

2000

16

2011

Ethiopia

40

20

38 7

2

1992

2014

10

26 3

3 1991– 1992

Egypt

2006

43

19

18

Peru

64

15

2012– 2013

2001

25 2006

2011

2001– 2002

Nepal

2008

2007

13 2013– 2014

2000

Zambia

2004 – 2012 2006

2013

20132014

Violence against women poses a serious challenge to women’s empowerment. Combating such violence often requires changing the attitudes and beliefs of both men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife who goes out on her own without telling the husband. It is encouraging that these beliefs appear to be moderating in most countries.

For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global tolerance of this24 harmful practice.

24

12

11

Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him

2007

80

2012

71 52 40

58

Source: ICF International, Demographic and Health Surveys.

38

26

32

40 © 2015 Population Reference Bureau Philippines

43

47

2006

2011

Uganda

U.S. Gender Gap in College Completion Eases; 31

25

19

52

36

Men

Women

Indonesia

64 Egypt

Kenya

2012

Acceptance of Wife Beating Recedes

Percent of Demand for Family Planning Satisfied by Modern Contraceptive Methods

Jordan

2007

Jordan

Nigeria

“Demand for family planning satisfied with modern methods” has emerged as a key indicator of contraceptive availability and use. The indicator measures the proportion of women who want to delay or limit childbearing and who are using modern methods of contraception.

Family planning experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two decades, a significant number of less developed countries have seen 42increases in the share of demand satisfied with modern methods, but many countries remain far below the proposed 75 percent benchmark. They will need over the coming decade 32 to accelerate progress30 so that increased contraceptive use can translate into improved maternal and child health, slower population growth, increased economic well-being, and environmental sustainability.

16

41

2002

Peru

Source: ICF International, Demographic and Health Surveys.

Planning Needs Increasingly Met by Modern Methods, but More Progress Needed

Zambia

77 71

27

18

19 Mali

2011

2007

18

32 2001 2006

31Family

2014

17

20

0

2012

Uganda

Source: ICF International, Demographic and Health Surveys.

17

79

37

30 17

89

42

32

27 29

28

91

Men

56

47

40

88

72

66

Women

57

50

41

47

53

75

Large Purchases

13

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

7

15 years and older active, including those oyed. A ratio less than male labor force eater than the female ore than one indicates greater than the male e World Bank for 2013.

WO R L D P O P U L AT I O N H I G H L I G H T S 1990

1994

1998

2002

2006

2010

2014

Note: Data points are for each corresponding survey year.

FOCUS ON WOMEN’S EMPOWERMENT

Source: ICF International, Demographic and Health Surveys.

agricultural

Rates of Early Marriage Fall, Particularly Among Those Under 15

Source: ICF Interna

Women Post Uneven Gains in Household Decisionmaking Power

Financial Inclusion of Women Expands

U.S. Gen Earnings

developed countries show effective gender parity at high levels of usage. Rapid 100 expansion of mobile money and other financial services available via mobile devices, particularly in Africa, provide a convenient way for both men and women to access such services. Women are currently using mobile more than other formal accounts in several African countries (see table). 90 84 83

actually started ou ages 25 and older 91 89 earnings gap pers degrees in higheronly 26 77 percent of 71 year-round worker

s in wage Early employment marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of sectorrisks whoofare women.

20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases. ountries the definition girls educational attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types the following: the Financial inclusion—making appropriate, affordable, financialofservices available to all people—is global development priority. also can help delay marriages. In Bangladesh, expanded employment in the garment industry is linked to notably lowerand rates convenient of marriage important decisions.

For example, in Nepal, only 66 a percent of women have a say about their own health care decisions. The same among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest Zambian women have the opportunity to make decisions about large household purchases. pulation in nonagriculture, For by women, access to savings, credit, and other services can help them gainpercentage more fiofnancial independence, better manage and leverage their potential brides tend to postpone marriage only a few years.

The majority of Bangladeshi girls continue to marry before age 18. l employment in Educational attain resources, and build capital to support income-generating activities. A core measure of financial inclusion is whether an individual uses an aid employment, and ages 25 and older Percent of Young Women Marriedaccount

by Age 15at (numbers in white) and Age 18 (numbers in black) Percent ofleast Currently Married Women Who Have a Sayof in women Decisions About This Topic a bank or other formal fi nancial institution.

In most countries, even many developed ones, the share with such blic sector. Data are college degree qu accounts has increased over the past few years. Gaps remain between men and women, but these have narrowed in many cases, and most 8-2013.

Own Health Large Purchases

iament Members

ts in a country’s single 83 gher and lower chambers 76 ent, or other national men. Data are from the ion from May 1, 2015.

73

Percent 65 Who Have Used an Account at a Formal Financial Institution in the Past 12 Months, 2011 and 2014

ata Dashboard where multiple indicators for ries. on what the data ate of women’s 1992

41

47

Congo, Dem. Rep.

Women

5 27

Cambodia 2012

1993 – 1994

orld map illustrating Niger c variables by country

2011

Bangladesh

Source: ICF International, Demographic and Health Surveys.

2000

16 Women

13

Men 2011

Colombia

cations (discounts rders):

2

1992

Ethiopia

Women

19

18

2014

Egypt

20

17

18

15

3

3

1991– 1992

Peru

25

34

Men

36

Ukraine but many countries remain far below the proposed 75 percent benchmark. They will need to accelerate progress over the coming decade so that increased contraceptive use can translate into improved maternal and child health, slower population growth, increased economic RB demographers Men well-being, d Kristin Bietsch.and environmental sustainability.

Percent of Demand for Family Planning Satisfied by Modern Contraceptive Methods

Canada

ISSN 0085-8315 : © Jörg Dickmann,

Women

Mobile 42 Financial 37 Services

Other Formal Financial Institution

Côte d'Ivoire

20

12

15

Uganda

29

23

27

Tanzania 2001 2006

2012– 2013

2001

26

2006

Zimbabwe

Mali

2011

Nepal

2001– 2002

19

2013– 2014

Zambia

42 Acceptance

39

30

2000

15

2004 – 2012 2006

Kenya

36

2002

Philippines

2007

2012

Jordan25

Peru

20

of Wife Beating Recedes

15

against women poses a serious challenge to women’s empowerment. Combating such violence often requires changing 44Violence 62 the attitudes and beliefs of both men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting 10a wife who goes out on her own without telling the husband. It is encouraging that these beliefs appear to be moderating in most countries.

For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the 52 husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable 5 drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global 44tolerance of this harmful 54 practice.

Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him

94

99

Women

0 1970

Men

1974

99

71

40

58

38

26

32

43

47 31

2006

2011

Uganda

25

19

52

40 © 2015 Population Reference Bureau

Wom Men

35

52

Source: World Bank, Global Findex Database.

Jordan

40

Source: 44 ICF International, Demographic and Health Surveys.

97

64 Egypt

41

Percent Who Ha

17 2007

80

Men

64

18

0

2012

26 Family Planning Needs IncreasinglyWomen Met by Modern Methods, rb.org.

India @prb.org. but More Progress Needed Men 0-877-9881.

“Demand for family planning satisfied with modern methods” has emerged as a key indicator of contraceptive availability and use. The 937.indicator measures the proportion of women who want to delay or limit childbearing and who are using modern methods of contraception. necticut Ave., NW, experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two Family planning Women decades, a significant number of less developed countries have seen increases in the share of demand satisfied with modern methods, hington, DC 20009.

ce Bureau.

32

Numbers in black 17 20 show percent in 2014 10

47

47

30

11

4

56

79

72

66 Percent of Women Using Financial 66 Services 53

by Type, 2014 57

50

17 19

75 65

Numbers in white 40 show percent in 2011

9

Men

29

28

3

74

74

70 60

49

Population Data47Sheet sh, French, and b.org. Also online:

80

88

Source: U.S. Censu Survey; American Co 13

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

8

2014

2007

2007

20132014

2012

WO R L D P O P U L AT I O N H I G H L I G H T S Zambia

Indonesia

FOCUS ON WOMEN’S EMPOWERMENT

Source: ICF International, Demographic and Health Surveys.

Rates of Early Marriage Fall, Particularly Among Those Under 15

Women Post Uneven Gains in Household Decisionmaking Power

U.S. Gender Gap in College Completion Eases; Earnings Gap Persists

Early marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health risks of early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past 20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As girls educational attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls elopment priority. also can help delay marriages. In Bangladesh, expanded employment in the garment industry is linked to notably lower rates of marriage among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest nd leverage their potential brides tend to postpone marriage by only a few years. The majority of Bangladeshi girls continue to marry before age 18.

Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases.

Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types of important decisions. For example, in Nepal, only 66 percent of women have a say about their own health care decisions. The same percentage of Zambian women have the opportunity to make decisions about large household purchases.

Educational attainment in the United States has risen substantially over the last four decades. Between 1970 and 2014, the share of men dual uses an ages 25(numbers and older with atAge least a college degree climbed from 14 percent to 32 percent, while theWomen shareWho of Have adulta Say women with About at least Percent of Young Women Married by Age 15 in white) and 18 (numbers in black) Percent of Currently Married in Decisions ThisaTopic en with such college degree quadrupled from 8 percent to 32 percent.

For ages 25 to 29 only, the share of women with a bachelor’s degree or higher cases, and most Own Health actually started outpacing the share for men in 1991. But women still lag behind men in earnings. Among full-time, year-round workers al services available 100 ages 25 and older in 2013, women’s median earnings were about 79 percent of men’s, up from 71 percent in 1993 (see table). This gender n are currently using 90 earnings gap persists across all educational levels. For bachelor’s degree holders, one factor may be that women are less likely to get83 83 84 76 adults ages 25 and older with a bachelor’s degree, 73 degrees in higher-earning fields such as science and engineering. In 2013, among 80 74 74 79 only 65 26 percent of women had a degree in science and engineering, compared with 44 percent of men. However, even among full-time, 75 72 70 65 year-round workers with engineering degrees, women’s median earnings in 2011 were only 83 percent of men’s.

66 nancial

Percent Who Have Completed College, by Age

Other Formal 47 Financial Institution

94

40 29

28

12

35

23 17 15

Women 25+ Men 25+ 19

30 19

18

20

16 10

2012

1993 – 1994

Niger

2011

Bangladesh 25

2000

2011

Ethiopia

3

2

1992

2014

3

1991– 1992

Egypt

2012

Peru

15

1990

1994

1998

89

77 71 64

37

Female-to-Male Median Earnings Ratio 27 Among Full-Time Year-Round Workers Ages 25 and Older by Education

2012– 2013

2001

2006

2011

High School Nepal

2001– 2002

1993

2007

2013– 2014

Zambia 71

2013

2000

2004 – 2012 2006

70

74

Bachelor’s Degree

73

75

Acceptance of Wife Beating Recedes

2002

76 Peru

Some College, No Degree

Source: ICF International, Demographic and Health Surveys.

2007

2012

Jordan

Bachelor’s Degree

Violence against women poses a serious challenge to women’s empowerment.

70 Combating such 73violence often requires changing the attitudes and beliefs of or bothMore men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife who goes out on her own without telling the husband. It is encouraging that71 these beliefs appear All Levels 79to be moderating in most countries.

For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global Note: Ratios are expressed as a percent. tolerance of this harmful practice.

“Demand for family planning satisfied with modern 10 methods” has emerged as a key indicator of contraceptive availability and use. The indicator measures the proportion of women who want to delay or limit childbearing and who are using modern methods of contraception.

Family planning experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two decades, a significant number of less developed countries have seen increases in the share of demand satisfied with modern methods, 5 75 percent benchmark. They will need to accelerate progress over the coming decade but many countries remain far below the proposed so that increased contraceptive use can translate into improved maternal and child health, slower population growth, increased economic well-being, and environmental sustainability.

0

18

Mali

Family Planning Needs 15 Increasingly Met by Modern Methods, but More Progress Needed

99

18

2001 2006

20

Percent of Demand for Family Planning Satisfi ed by 1974 Modern Contraceptive 1970 1978 1982Methods 1986

17

20

91

56

0

Source: ICF International, Demographic and Health Surveys.

97

17

88

42

32

27 Women 25-29 Men 25-29 17

7

57

47

40

30 1992

53

50

41

47

66

60

49

Large Purchases

2002

2006

Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him

2010

2014

Men

Women

80

99 71 64 Egypt

52

Source: U.S. Census Bureau: 1970 to 2002 March Current Population Survey; 2003 to 2014 Annual Social Supplement to the Current Population 40 and Economic 38 32 58 26 Survey; American Community Survey Brief 11-10 (Oct. 2012); and PRB analysis of data from the 2013 American Community Survey.

19

25 13

52

41

Jordan

Kenya

40 © 2015 Population Reference Bureau 36

Philippines

43

47 31

2006

2011

Uganda

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

9

WO R L D P O P U L AT I O N H I G H L I G H T S FOCUS ON WOMEN’S EMPOWERMENT

Rates of Early Marriage Fall, Particularly Among Those Under 15

Women Post Uneven Gains in Household Decisionmaking Power

Early marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health risks of early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past 20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As girls educational attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls also can help delay marriages. In Bangladesh, expanded employment in the garment industry is linked to notably lower rates of marriage among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest potential brides tend to postpone marriage by only a few years. The majority of Bangladeshi girls continue to marry before age 18.

Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases.

Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types of important decisions. For example, in Nepal, only 66 percent of women have a say about their own health care decisions. The same percentage of Zambian women have the opportunity to make decisions about large household purchases.

Percent of Young Women Married by Age 15 (numbers in white) and Age 18 (numbers in black)

Percent of Currently Married Women Who Have a Say in Decisions About This Topic

83

9.8 3,339 BILLION

76

73

Population per square kilometer of arable land in South Korea.

65

Projected 2050 world population, up 2.5 billion 49 from 2015.

47

47

52%

12

100 90 80

Own Health

88

Infant mortality rate per 70 1,000 live births in Kosovo, 60 the highest rate in Europe.53

19

18

20

16 10

1992

2012

1993 – 1994

2011

28

Niger

Bangladesh

2000

2011

Ethiopia

Source: ICF International, Demographic and Health Surveys.

7

2

1992

2014

3

3

1991– 1992

Peru

Family Planning Needs Increasingly Met by Modern Methods, The percentage of women but More Progress The numberNeeded of maternal in Swaziland ages 15-24 mortality deaths per 100,000 live births in the United States, up from 12 in 1990.

17

20 18

64

27

18 15

0

2012

15.5% Egypt

17

77 71

37

30 17

89

42

32

27 29 19

57

47

40

28

74 The74percentage of 79 75 72 married women ages 66 15-49 in Peru who use 56 modern contraception.

65

66

91

84

83

50

41

Large Purchases

infected with HIV/AIDS, vs. 7.2% for men in same age group.

“Demand for family planning satisfied with modern methods” has emerged as a key indicator of contraceptive availability and use. The indicator measures the proportion of women who want to delay or limit childbearing and who are using modern methods of contraception.

Family planning experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two decades, a significant number of less developed countries have seen increases in the share of demand satisfied with modern methods, but many countries remain far below the proposed 75 percent benchmark. They will need to accelerate progress over the coming decade so that increased contraceptive use can translate into improved maternal and child health, slower population growth, increased economic well-being, and environmental sustainability.

2001 2006

2012– 2013

2001

2006

2011

4.4 Mali

2001– 2002

Nepal

2007

2013– 2014

2000

Source: ICF International, Demographic and Health Surveys.

2004 – 2012 2006

2002

58%

Zambia

Peru

2007

2012

Jordan

Acceptance of Wife Beating Recedes

The percentage of Rwanda’s parliament members who are women—the world’s highest percentage.

Violence against women poses a serious challenge to women’s empowerment. Combating such violence often requires changing the attitudes and beliefs of both men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife who goes out on her own without telling the husband. It is encouraging that these beliefs appear to be moderating in most countries.

For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global tolerance of this harmful practice.

The total fertility rate (lifetime births per woman) in Yemen.

Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him

Percent of Demand for Family Planning Satisfied by Modern Contraceptive Methods

Men

Women

80 71 64 Egypt

52 40

58

38

26

32

41

Jordan

Kenya

40 © 2015 Population Reference Bureau 36

Philippines

43

47 31

2006

2011

Uganda

25

19

52

13

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

10

POPULATION, HEALTH, AND ENVIRONMENT DATA AND ESTIMATES FOR THE COUNTRIES AND REGIONS OF THE WORLD

WORLD MORE DEVELOPED LESS DEVELOPED LESS DEVELOPED (Excl. China) LEAST DEVELOPED AFRICA SUB-SAHARAN AFRICA NORTHERN AFRICA Algeria Egypt Libya Morocco Sudan Tunisia Western Saharae WESTERN AFRICA Benin Burkina Faso Cape Verde Côte d’Ivoire Gambia Ghana Guinea Guinea-Bissau Liberia Mali Mauritania Niger Nigeria Senegal Sierra Leone Togo EASTERN AFRICA Burundi Comoros Djibouti Eritrea Ethiopia Kenya Madagascar Malawi Mauritius Mayotte Mozambique Reunion Rwanda Seychelles Somalia South Sudan Tanzania © 2015 Population Reference Bureau Uganda Zambia

Population mid-2015 (millions) 7,336 1,254 6,082 4,702 938 1,171 949 222 39.9 89.1 6.3 34.1 40.9 11.0 0.6 349 10.6 18.5 0.5 23.3 2.0 27.7 11.0 1.8 4.5 16.7 3.6 18.9 181.8 14.7 6.5 7.2 388 10.7 0.8 0.9 5.2 98.1 44.3 23.0 17.2 1.3 0.2 25.7 0.9 11.3 0.09 11.1 12.2 52.3 40.1 15.5

Births per 1,000 Population 20 11 22 24 34 36 38 29 26 31 21 22 38 19 20 39 37 44 21 37 42 33 38 37 36 44 34 50 39 37 37 38 36 43 33 27 37 31 31 34 37 11 31 45 17 31 17 44 36 39 40 43

Deaths per 1,000 Population 8 10 7 7 9 10 11 6 6 6 4 6 9 6 6 12 10 11 6 14 10 8 12 13 9 15 9 11 14 8 14 11 9 10 9 9 7 8 8 7 11 8 2 13 5 8 8 12 12 9 9 13

Net Migration Rate per 1,000 — 2 -1 -0 -1 -0 -0 -1 -1 0 -11 -2 -2 -1 9 -1 0 -1 -2 0 -1 -2 0 -1 -1 -4 -1 0 -0 -1 -1 0 -0 0 -3 -3 -5 0 0 0 0 -1 -5 0 -3 -1 6 -7 11 -1 -1 0

Population Infant mid-2030 mid-2050 Mortality Ratea (millions) (millions) 8,505 9,804 37 1,295 1,310 5 7,210 8,495 40 5,779 7,120 44 1,300 1,887 62 1,658 2,473 59 1,369 2,081 64 289 392 29 49.9 60.4 21 117.9 162.4 22 7.5 8.4 14 38.7 41.9 26 61.7 105.0 52 12.3 12.9 16 0.8 0.8 37 509 784 64 15.1 21.5 67 28.4 46.6 69 0.6 0.7 22 32.0 46.3 74 3.1 5.0 47 37.7 52.6 41 16.0 24.2 67 2.5 3.5 92 54 6.4 9.4 26.1 43.6 56 5.0 7.1 72 33.8 68.0 60 261.7 396.5 69 21.5 32.3 33 8.3 10.6 92 10.5 16.3 49 562 841 52 17.2 30.4 65 1.0 1.3 36 1.1 1.2 58 7.3 10.4 46 130.5 165.1 49 60.1 81.4 39 34.3 52.8 38 24.7 36.6 53 1.3 1.2 14.5 0.3 0.5 4 41.0 72.9 83 1.0 1.2 8 15.8 21.0 32 0.1 0.1 12.7 16.9 27.1 79 17.3 24.8 77 79.4 129.4 37 See page 21 54 63.4notes on 104.1 23.7 42.0 75

Total Fertility Rateb 2.5 1.7 2.6 3.0 4.3 4.7 5.0 3.4 3.0 3.5 2.4 2.5 5.2 2.1 2.4 5.4 4.9 6.0 2.4 4.9 5.6 4.2 5.1 4.9 4.7 5.9 4.2 7.6 5.5 5.0 4.9 4.8 4.8 6.2 4.3 3.4 4.4 4.1 3.9 4.4 5.0 1.4 4.1 5.9 2.4 4.2 2.4 6.6 6.9 5.2 5.9 5.6

Percent of Population Age <15 26 16 28 32 40 41 43 31 28 31 29 25 43 23 26 43 45 45 31 41 46 39 42 43 42 47 40 52 43 42 41 42 43 46 41 34 43 41 41 41 44 20 44 45 24 41 22 47 42 45 48 46

Age 65+ 8 17 6 5 4 4 3 5 6 4 5 6 3 8 3 3 3 2 6 3 2 5 3 3 3 3 3 4 3 4 3 3 3 3 3 4 2 4 3 3 3 9 3 3 10 3 8 3 3 3 2 3

GNI per Capita ($US) 2014c 15,030 39,020 9,870 8,740 2,270 4,720 3,480 9,740 13,540 11,020 16,190 7,180 3,980 10,600 — 4,040 1,850 1,660 6,320 3,350 1,580 3,960 1,140 1,430 820 1,660 3,700 950 5,680 2,290 1,830 1,310 1,930 790 1,530 — 1,180 1,500 2,890 1,400 780 18,290 — 1,170 — 1,530 24,630 — 2,030 2,530 1,690 3,860

Percent of Married Women 15-49 Using Life Expectancy Population Contraceptiond at Birth (years) per Square Percent Kilometer All Modern Both Urban of Arable Land Methods Methods Sexes Males Fe 53 523 62 56 71 69 77 238 67 59 79 76 48 696 61 55 69 68 46 612 54 46 68 66 29 521 37 32 62 60 40 487 35 29 60 58 38 484 30 25 57 56 51 500 51 46 71 69 73 524 56 48 74 72 43 3,196 59 57 71 70 78 359 42 20 71 69 60 425 67 57 74 73 33 193 12 12 62 60 68 388 63 50 76 74 82 — — — 68 66 45 402 16 12 55 54 45 393 18 13 59 58 27 308 18 18 56 56 62 1,090 61 57 75 71 50 805 18 13 51 50 57 459 9 8 59 58 51 588 27 22 61 60 36 366 6 5 60 58 49 594 16 14 54 53 47 899 20 19 60 59 39 245 10 10 53 53 59 883 11 10 63 62 22 118 14 12 60 59 50 520 15 10 52 52 45 439 22 20 65 63 41 375 17 16 50 50 38 273 20 17 57 56 24 560 41 35 61 59 10 977 22 18 59 57 28 868 19 14 61 60 77 38,827 19 18 62 60 21 981 8 7 63 60 17 641 42 40 64 62 24 794 58 53 62 60 33 660 40 33 65 64 16 458 59 57 61 60 41 1,663 76 39 74 71 50 — — — 79 76 31 455 12 11 54 52 94 — 67 64 80 77 28 959 53 48 65 63 54 9,173 — — 73 69 38 985 15 1 55 53 17 — 4 1 55 54 30 360 34 26 62 60 POPULATION DATA 18 2015 WORLD 582 27 26 SHEET59 11 58 40 408 49 45 53 51

Ethiopia Kenya Madagascar Malawi Mauritius Mayotte Mozambique Reunion Rwanda Seychelles WORLD Somalia MORE DEVELOPED South Sudan LESS DEVELOPED Tanzania LESS DEVELOPED (Excl. China) Uganda LEAST ZambiaDEVELOPED AFRICA Zimbabwe SUB-SAHARAN MIDDLE AFRICAAFRICA NORTHERN AFRICA Angola Algeria Cameroon Egypt African Republic Central Libya Chad Morocco Congo Sudan Congo, Dem. Rep. Tunisia Equatorial Guinea Western Gabon Saharae WESTERN Sao Tome AFRICA and Principe Benin SOUTHERN AFRICA Burkina Faso Botswana Cape Verde Lesotho Côte d’Ivoire Namibia Gambia South Africa Ghana Swaziland Guinea AMERICAS Guinea-Bissau NORTHERN AMERICA Liberia Canada Mali United States Mauritania LATIN AMERICA AND THE CARIBBEAN Niger CENTRAL AMERICA Nigeria Belize Senegal Costa Rica Sierra Leone El Salvador Togo Guatemala EASTERN Honduras AFRICA Burundi Mexico Comoros Nicaragua Djibouti Panama Eritrea CARIBBEAN Ethiopia and Barbuda Antigua Kenya Bahamas Madagascar Barbados Malawi Cuba Mauritius Curaçao Mayotte Dominica Mozambique Dominican Republic Reunion Grenada Rwanda Guadeloupe Seychelles Haiti Somalia Jamaica South Sudan Martinique Tanzania Puerto Rico © 2015 Population Reference Bureau Uganda St. Kitts-Nevis Zambia St. Lucia

98.1 31 8 0 130.5 165.1 49 4.1 41 4 1,500 17 641 42 40 64 62 44.3 31 8 0 60.1 81.4 39 3.9 41 3 2,890 24 794 58 53 62 60 23.0 34 7 0 34.3 52.8 38 4.4 41 3 1,400 33 660 40 33 65 64 17.2 37 HEALTH, 11 AND ENVIRONMENT 0 24.7 DATA 36.6 53 5.0 FOR44THE COUNTRIES 3 780 16 458 59 WORLD 57 61 60 POPULATION, AND ESTIMATES AND REGIONS OF THE 1.3 11 8 -1 1.3 1.2 14.5 1.4 20 9 18,290 41 1,663 76 39 74 71 Percent 0.2 31 2 -5 0.3 0.5 4 4.1 44 3 — 50 — — of Married — 79 76 Women Using Percent 3 25.7 45 13 41.0 72.9 83 5.9 45 1,170 31 455 12 15-49 11 54 Life Expectancy 52 Net0 Population GNI per d Population 1.2 Contraception of24 Population 0.9 17 5 -3 1.0 8 2.4 10 — 94 — 67 64 80 at Birth 77 (years) Population Births Deaths Migration Infant Total per Square Capita mid-2015 per31 1,000 per 1,000 Rate-1per Fertility Kilometer mid-2030 mid-2050 Age Age ($US) All Modern Both 11.3 8 15.8 21.0 Mortality 32 4.2 41 3 1,530 Percent 28 959 53 48 65 63 a (millions) Population 1,000 Rate Rate Urban of Arable (millions) (millions) <15 65+ 2014c Methods Sexes Males Fe 0.09 Population 17 8 6 0.1 0.1 12.7 2.4b 22 8 24,630 54 9,173Land Methods — — 73 69 7,336 20 8 — 8,505 9,804 37 2.5 26 8 15,030 53 523 62 56 71 69 11.1 44 12 -7 16.9 27.1 79 6.6 47 3 — 38 985 15 1 55 53 1,254 11 10 2 1,295 1,310 5 1.7 16 17 39,020 77 238 67 59 79 76 12.2 36 12 11 17.3 24.8 77 6.9 42 3 2,030 17 — 4 1 55 54 6,082 22 7 -1 7,210 8,495 40 2.6 28 6 9,870 48 696 61 55 69 68 52.3 39 9 79.4 129.4 37 5.2 45 3 2,530 30 360 34 26 62 60 4,702 24 7 -0 5,779 7,120 44 3.0 32 5 8,740 46 612 54 46 68 66 40.1 40 9 -1 63.4 104.1 54 5.9 48 2 1,690 18 582 27 26 59 58 938 34 9 -1 1,300 1,887 62 4.3 40 4 2,270 29 521 37 32 62 60 51 15.5 43 13 0 23.7 42.0 75 5.6 46 3 3,860 40 408 49 45 53 1,171 36 10 -0 1,658 2,473 59 4.7 41 4 4,720 40 487 35 29 60 58 17.4 33 9 -3 25.2 37.5 55 4.3 43 3 1,710 33 436 67 67 61 60 949 38 11 1,369 2,081 64 5.0 43 3,480 38 484 30 25 57 56 149 44 14 -0 229 378 96 6.1 46 3 2,680 46 569 20 10 52 50 222 29 6 -1 289 392 29 3.4 31 5 9,740 51 500 51 46 71 69 25.0 46 14 1 39.4 65.5 95 6.1 47 2 7,150 62 421 18 12 52 50 39.9 26 6 -1 49.9 60.4 21 3.0 28 6 13,540 73 524 56 48 74 72 23.7 37 11 -0 34.4 51.9 57 4.9 43 3 2,940 52 383 23 14 57 56 89.1 31 6 117.9 162.4 22 3.5 31 4 11,020 43 3,196 59 57 71 70 5.6 45 16 0 8.5 13.9 109 6.2 45 3 610 39 307 15 9 50 48 6.3 21 4 -11 7.5 8.4 14 2.4 29 5 16,190 78 359 42 20 71 69 13.7 48 14 1 21.8 37.4 95 6.5 48 2 2,130 22 279 5 2 51 50 34.1 22 6 -2 38.7 41.9 26 2.5 25 6 7,180 60 425 67 57 74 73 4.8 37 10 -8 6.7 10.2 61 4.8 41 3 5,120 64 870 45 20 58 57 40.9 38 9 -2 61.7 105.0 52 5.2 43 3 3,980 33 193 12 12 62 60 73.3 46 16 -0 114.9 193.6 108 6.6 46 700 42 1,044 20 8 50 48 11.0 19 6 -1 12.3 12.9 16 2.1 23 8 10,600 68 388 63 50 76 74 0.8 37 13 5 1.2 1.8 70 5.1 39 3 22,480 39 667 13 10 57 56 0.6 20 6 9 0.8 0.8 37 2.4 26 3 — 82 — — — 68 66 1.8 32 9 1 2.4 3.3 43 4.1 38 5 16,500 86 523 31 19 63 62 349 39 12 -1 509 784 64 5.4 43 3 4,040 45 402 16 12 55 54 0.2 36 7 -6 0.3 0.4 43 4.3 42 4 3,030 67 2,239 38 33 66 64 10.6 37 0 15.1 21.5 67 4.9 45 3 1,850 45 393 18 13 59 58 63 23 10 3 69 77 36 2.7 31 5 12,290 59 464 60 59 61 59 18.5 44 11 -1 28.4 46.6 69 6.0 45 2 1,660 27 308 18 18 56 56 2.1 26 8 2 2.3 2.5 31 2.9 33 5 17,460 57 755 53 51 64 62 0.5 21 6 -2 0.6 0.7 22 2.4 31 6 6,320 62 1,090 61 57 75 71 5 3,260 27 682 60 60 44 43 1.9 31 20 -5 2.3 3.0 59 3.3 36 23.3 37 14 32.0 46.3 74 4.9 41 3 3,350 50 805 18 13 51 50 2.5 29 7 0 3.3 4.7 39 3.6 35 4 9,880 46 301 56 55 64 62 2.0 42 -1 3.1 5.0 47 5.6 46 2 1,580 57 459 9 8 59 58 55.0 22 10 3 59.8 65.2 34 2.6 30 6 12,700 62 458 60 60 61 59 27.7 33 8 -2 37.7 52.6 41 4.2 39 5 3,960 51 588 27 22 61 60 1.3 30 14 -1 1.5 1.8 50 3.3 37 4 5,940 21 733 66 66 49 50 11.0 38 12 0 16.0 24.2 67 5.1 42 3 1,140 36 366 6 5 60 58 987 16 7 1 1,116 1,221 14 2.0 24 10 29,900 80 266 73 68 76 74 1.8 37 13 -1 2.5 3.5 92 4.9 43 3 1,430 49 594 16 14 54 53 357 12 8 3 401 445 6 1.8 19 15 54,620 81 178 74 68 79 77 54 4.7 42 3 820 47 899 20 19 60 59 4.5 36 9 -1 6.4 9.4 35.8 11 7 6 41.0 46.9 4.8 1.6 16 16 43,400 80 79 74 72 81 79 16.7 44 15 -4 26.1 43.6 56 5.9 47 3 1,660 39 245 10 10 53 53 321.2 13 8 3 359.4 398.3 6.0 1.9 19 15 55,860 81 207 74 68 79 76 3.6 34 9 5.0 7.1 72 4.2 40 3 3,700 59 883 11 10 63 62 630 18 6 -1 716 776 17 2.1 27 7 15,260 80 371 73 67 75 72 18.9 50 11 0 33.8 68.0 60 7.6 52 4 950 22 118 14 12 60 59 173 20 5 -2 205 231 14 2.4 29 6 14,420 74 585 71 65 75 72 181.8 39 14 -0 261.7 396.5 69 5.5 43 3 5,680 50 520 15 10 52 52 0.4 21 4 4 0.5 0.5 13 2.4 36 4 7,870 44 475 55 52 74 71 14.7 37 8 -1 21.5 32.3 33 5.0 42 4 2,290 45 439 22 20 65 63 4.8 15 4 2 5.6 6.1 8.1 1.9 23 7 13,900 73 1,972 76 75 79 77 6.5 37 14 -1 8.3 10.6 92 4.9 41 3 1,830 41 375 17 16 50 50 6.4 18 5 -8 6.8 6.8 17 2.0 31 7 7,720 67 904 72 68 73 68 7.2 38 11 0 10.5 16.3 49 4.8 42 3 1,310 38 273 20 17 57 56 16.2 25 5 -1 21.4 27.5 19 3.1 40 5 7,260 52 1,056 54 44 73 69 388 36 9 -0 562 841 52 4.8 43 3 1,930 24 560 41 35 61 59 8.3 24 5 -2 10.2 11.7 22 2.7 34 5 4,120 54 819 73 64 74 72 10.7 43 10 0 17.2 30.4 65 6.2 46 3 790 10 977 22 18 59 57 127.0 19 5 -2 148.1 163.8 13 2.3 28 7 16,710 79 526 73 66 75 73 0.8 33 9 -3 1.0 1.3 36 4.3 41 3 1,530 28 868 19 14 61 60 6.3 23 5 -4 7.4 8.4 16 2.4 32 5 4,670 59 416 80 77 75 72 0.9 27 9 -3 1.1 1.2 58 3.4 34 4 — 77 38,827 19 18 62 60 4.0 19 5 2 4.9 5.8 17 2.7 28 8 19,630 78 744 63 60 78 75 5.2 37 7 -5 7.3 10.4 46 4.4 43 2 1,180 21 981 8 7 63 60 43 18 8 -4 47 50 28 2.3 26 9 12,800 68 793 62 59 73 70 98.1 31 8 130.5 165.1 49 4.1 41 4 1,500 17 641 42 40 64 62 0.09 14 6 0 0.1 0.1 16 1.5 24 8 21,120 30 2,248 — — 77 74 44.3 31 8 0 60.1 81.4 39 3.9 41 3 2,890 24 794 58 53 62 60 0.4 15 6 1 0.4 0.5 14 1.9 26 7 22,310 85 4,708 — — 74 71 23.0 34 7 0 34.3 52.8 38 4.4 41 3 1,400 33 660 40 33 65 64 0.3 12 9 2 0.3 0.3 19 1.7 20 13 14,750 46 2,525 59 55 75 73 17.2 37 11 0 24.7 36.6 53 5.0 44 3 780 16 458 59 57 61 60 11.1 11 8 -2 11.2 10.6 4.2 1.7 17 13 18,710 75 348 74 72 78 77 1.3 11 8 -1 1.3 1.2 14.5 1.4 20 9 18,290 41 1,663 76 39 74 71 0.2 13 1 0.2 0.2 8.7 2.1 19 15 — — — — — 78 75 0.2 31 2 -5 0.3 0.5 4 4.1 44 3 — 50 — — — 79 76 0.07 14 9 0.07 0.06 20 2.1 22 10 10,300 68 1,133 75 72 25.7 45 13 0 41.0 72.9 83 5.9 45 3 1,170 31 455 12 11 54 52 10.5 21 6 -3 11.3 12.2 31 2.5 31 6 12,450 72 1,310 70 68 73 70 0.9 17 5 -3 1.0 1.2 8 2.4 24 10 — 94 — 67 64 80 77 0.1 8 -2 0.1 0.1 15 2.1 26 7 11,650 41 3,710 — — 76 74 11.3 31 8 -1 15.8 21.0 32 4.2 41 3 1,530 28 959 53 48 65 63 0.4 13 7 -2 0.4 0.4 8.7 2.2 21 14 — 98 — — — 81 78 0.09 17 8 6 0.1 0.1 12.7 2.4 22 8 24,630 54 9,173 — — 73 69 10.9 28 9 -3 13.6 16.9 42 3.2 35 4 1,750 59 1,092 35 31 64 61 11.1 44 12 -7 16.9 27.1 79 6.6 47 3 — 38 985 15 1 55 53 2.7 18 7 -5 2.9 2.7 21 2.3 24 9 8,490 52 2,268 73 68 74 70 12.2 36 12 11 17.3 24.8 77 6.9 42 3 2,030 17 1 55 54 0.4 11 8 -10 0.4 0.4 8 1.9 19 17 — 89 — —4 — 82 79 52.3 39 9 -1 79.4 129.4 37 5.2 45 3 2,530 30 360 34 26 62 60 3.5 10 8 -15 3.5 3.4 7.2 1.5 18 17 23,960 99 5,806 84 72 79 76 See notes on page POPULATION DATA 40.1 40 9 -1 63.4 104.1 54 5.9 48 2 1,690 18 2015 WORLD 582 27 26 59 12 73 58 0.05 14 8 1 0.05 0.06 21 13 1.8 21 8 21,990 32 921 — — SHEET75 15.5 43 13 23.7 42.0 75 5.6 46 3 3,860 40 408 49 45 53 51 0.2 12 6 0 0.2 0.2 18 1.5 22 9 10,230 15 5,855 56 52 79 75

Barbados Cuba Curaçao Dominica Dominican Republic Grenada Guadeloupe Haiti Jamaica Martinique Puerto Rico WORLD St. Kitts-Nevis MORE DEVELOPED St. Lucia LESS DEVELOPED St. Vincent and the(Excl.

Grenadines LESS DEVELOPED China) Trinidad and Tobago LEAST DEVELOPED SOUTH AFRICA AMERICA Argentina SUB-SAHARAN AFRICA Bolivia NORTHERN AFRICA Brazil Algeria Chile Egypt Colombia Libya Ecuador Morocco French Sudan Guiana Guyana Tunisia Paraguay Western Saharae Peru WESTERN AFRICA Suriname Benin UruguayFaso Burkina Venezuela Cape Verde ASIA Côte d’Ivoire ASIA (Excl. China) Gambia WESTERN ASIA Ghana Guinea Armenia Guinea-Bissau Azerbaijan Liberia Bahrain Mali Cyprus Mauritania Georgia Niger Iraq Nigeria Israel Senegal Jordan Sierra Leone Kuwait Togo Lebanon EASTERN AFRICA Oman Burundi Palestinian Territory Comoros Qatar Djibouti Saudi Arabia Eritrea Syria Ethiopia Turkey Kenya United Arab Emirates Madagascar Yemen Malawi CENTRAL ASIA SOUTH Mauritius ASIA CENTRAL Mayotte Kazakhstan Mozambique Kyrgyzstan Reunion Tajikistan Rwanda Turkmenistan Seychelles Uzbekistan SomaliaASIA SOUTH South Sudan Afghanistan Tanzania Bangladesh © 2015 Population Reference Bureau Uganda Bhutan Zambia India

0.3 12 9 2 0.3 0.3 19 1.7 20 13 14,750 46 2,525 59 55 75 73 11.1 11 8 -2 11.2 10.6 4.2 1.7 17 13 18,710 75 348 74 72 78 77 0.2 13 8 1 0.2 0.2 8.7 2.1 19 15 — — — — — 78 75 0.07 14 HEALTH,9 AND ENVIRONMENT -5 0.07 DATA0.06 20 2.1 FOR22THE10 10,300 68 1,133 — WORLD — 75 72 POPULATION, AND ESTIMATES COUNTRIES AND REGIONS OF THE 10.5 21 6 -3 11.3 12.2 31 2.5 31 6 12,450 72 1,310 70 68 73 70 0.1 17 8 -2 0.1 0.1 15 2.1 26 7 11,650 41 3,710 — of Married — 76 74 Percent Women Percent 0.4 13 7 -2 0.4 0.4 8.7 2.2 21 14 98 — — 15-49 Using — 81 Life Expectancy 78 Net Population GNI—per d Population 16.9 Contraception of35 Population 10.9 28 9 -3 13.6 42 3.2 4 1,750 59 1,092 35 31 64 at Birth 61 (years) Population Births Deaths Migration Infant Total per Square Capita 2.7 7 2.9 2.7 Mortality 21 2.3 24 9 8,490 Percent 52 2,268 73 68 74 70 mid-2015 per18 1,000 per 1,000 Rate-5per Fertility Kilometer mid-2030 mid-2050 Age Age ($US) All Modern Both (millions) Population Population 1,000 Rate Rate Urban of Arable (millions) (millions) <15 65+ 2014 Methods Sexes Males Fe 0.4 11 8 -10 0.4 0.4 8a 1.9b 19 17 —c 89 — Land Methods — — 82 79 3.5 10 -15 3.5 3.4 7.2 1.5 18 17 23,960 99 5,806 84 72 79 76 7,336 20 8 — 8,505 9,804 37 2.5 26 8 15,030 53 523 62 56 71 69 0.05 14 8 1 0.05 1,310 0.06 13 1.8 21 8 21,990 32 921 — — 75 73 1,254 11 10 2 1,295 5 1.7 16 17 39,020 77 238 67 59 79 76 0.2 12 6 0 0.2 0.2 18 1.5 22 9 10,230 15 5,855 56 52 79 75 6,082 22 7 -1 7,210 8,495 40 2.6 28 6 9,870 48 696 61 55 69 68 0.1 17 8 -8 0.1 0.1 20 2.0 25 6 10,610 51 2,204 — — 71 70 4,702 24 7 -0 5,779 7,120 44 3.0 32 5 8,740 46 612 54 46 68 66 1.4 14 8 -1 1.3 1.2 13 1.7 21 9 26,220 15 5,375 43 38 75 71 938 34 9 1,300 1,887 62 4.3 40 4 2,270 29 521 37 32 62 60 414 17 6 -0 464 496 18 2.0 26 8 14,850 84 309 75 69 75 72 1,171 36 10 1,658 2,473 59 4.7 41 4 4,720 40 487 35 29 60 58 42.4 18 8 0 49.4 58.4 10.8 2.2 24 11 — 93 108 55 53 77 73 949 38 11 -0 1,369 2,081 64 5.0 43 3 3,480 38 484 30 25 57 56 10.5 26 7 13.0 15.8 39 3.2 6 6,130 69 242 61 34 67 65 222 29 6 -1 289 392 29 3.4 31 5 9,740 51 500 51 46 71 69 204.5 15 6 0 223.1 226.3 19 1.8 24 7 15,900 86 281 80 77 75 71 39.9 26 -1 49.9 60.4 21 3.0 28 6 13,540 73 524 56 48 74 72 18.0 14 6 2 19.6 20.2 7.4 1.8 21 10 21,570 90 1,347 61 — 79 76 89.1 31 0 117.9 162.4 22 3.5 31 4 11,020 43 3,196 59 57 71 70 48.2 19 6 -1 53.2 54.9 16 1.9 27 7 12,600 76 3,104 79 73 75 72 6.3 21 4 -11 7.5 8.4 14 2.4 29 5 16,190 78 359 42 20 71 69 16.3 21 5 0 19.8 23.4 17 2.6 31 7 11,120 70 1,425 73 59 75 72 34.1 22 6 -2 38.7 41.9 26 2.5 25 6 7,180 60 425 67 57 74 73 0.3 26 3 5 0.4 0.6 9 3.5 34 5 — 77 — — — 80 77 40.9 38 9 -2 61.7 105.0 52 5.2 43 3 3,980 33 193 12 12 62 60 0.7 21 7 -7 0.8 0.7 32 2.6 27 6 6,930 29 180 34 33 66 64 11.0 19 6 -1 12.3 12.9 16 2.1 23 8 10,600 68 388 63 50 76 74 7.0 23 -1 8.5 10.1 29 2.8 33 5 8,010 64 159 79 70 72 70 0.6 20 6 9 0.8 0.8 37 2.4 26 3 — 82 — — — 68 66 31.2 20 5 35.9 40.1 17 2.5 29 6 11,510 79 761 75 52 75 72 349 39 12 -1 509 784 64 5.4 43 3 4,040 45 402 16 12 55 54 0.6 18 7 -2 0.7 0.7 17 2.3 28 6 15,960 71 923 48 47 71 68 10.6 37 10 0 15.1 21.5 67 4.9 45 3 1,850 45 393 18 13 59 58 3.6 14 10 3.7 3.8 8.9 1.9 21 14 20,220 93 204 77 75 77 73 18.5 44 11 -1 28.4 46.6 69 6.0 45 2 1,660 27 308 18 18 56 56 30.6 20 5 0 36.1 40.5 13.3 2.5 28 17,140 94 1,120 70 62 72 0.5 21 6 -2 0.6 0.7 22 2.4 31 6 6,320 62 1,090 61 57 75 71 4,397 18 7 -0 4,939 5,324 33 2.2 25 8 11,450 47 938 66 60 72 70 23.3 37 14 0 32.0 46.3 74 4.9 41 3 3,350 50 805 18 13 51 50 3,017 21 7 -0 3,507 3,949 38 2.4 28 6 10,480 44 832 57 48 70 68 2.0 42 10 -1 3.1 5.0 47 5.6 46 2 1,580 57 459 9 8 59 58 257 22 5 3 321 387 22 2.9 30 5 25,130 71 705 54 37 74 71 27.7 33 8 -2 37.7 52.6 41 4.2 39 3,960 51 588 27 22 61 60 11.0 38 12 0 16.0 24.2 67 5.1 42 3 1,140 36 366 6 5 60 58 3.0 14 9 -6 2.9 2.5 9 1.5 19 11 8,550 63 675 55 26 75 72 1.8 37 13 -1 2.5 3.5 92 4.9 43 3 1,430 49 594 16 14 54 53 9.7 18 6 0 11.0 12.1 11 2.2 22 6 16,910 53 510 51 13 74 72 54 4.7 42 3 820 47 899 20 19 60 59 4.5 36 9 -1 6.4 9.4 1.4 15 2 5 1.7 1.9 8 2.1 21 2 38,140 100 88,490 62 31 76 75 16.7 44 15 -4 26.1 43.6 56 5.9 47 3 1,660 39 245 10 10 53 53 1.2 12 6 -12 1.3 1.4 5 1.4 17 12 29,800 67 1,260 — — 80 78 3.6 34 9 -1 5.0 7.1 72 4.2 40 3 3,700 59 883 11 10 63 62 3.8 14 12 -2 4.9 4.7 10 1.7 17 14 7,510 54 944 53 35 75 71 18.9 50 11 0 33.8 68.0 60 7.6 52 4 950 22 118 14 12 60 59 37.1 31 4 2 53.4 76.5 37 4.2 41 3 14,670 71 1,080 53 33 69 67 181.8 39 14 -0 261.7 396.5 69 5.5 43 3 5,680 50 520 15 10 52 52 8.4 21 5 1 10.6 13.9 3.0 3.3 28 11 32,550 91 2,846 — — 82 80 14.7 37 8 -1 21.5 32.3 33 5.0 42 4 2,290 45 439 22 20 65 63 8.1 28 6 3 9.0 11.4 17 3.5 37 3 11,910 83 3,810 61 42 74 73 6.5 37 14 -1 8.3 10.6 92 4.9 41 3 1,830 41 375 17 16 50 50 3.8 17 2 22 5.0 6.1 8 2.3 23 2 87,700 98 35,893 52 39 74 73 7.2 38 11 0 10.5 16.3 49 4.8 42 3 1,310 38 273 20 17 57 56 6.2 15 5 31 5.5 5.6 8 1.7 26 6 17,330 87 2,993 58 34 77 76 388 36 9 -0 562 841 52 4.8 43 3 1,930 24 560 41 35 61 59 4.2 21 3 45 5.2 5.7 10 2.9 22 3 36,240 75 13,574 24 15 77 75 10.7 43 10 0 17.2 30.4 65 6.2 46 3 790 10 977 22 18 59 57 4.5 32 4 -2 6.6 9.2 18 4.1 40 5,080 83 9,925 57 44 73 72 0.8 33 9 -3 1.0 1.3 36 4.3 41 3 1,530 28 868 19 14 61 60 2.4 12 1 28 2.8 3.0 7 2.0 15 1 133850 100 18,750 38 34 78 78 0.9 27 9 -3 1.1 1.2 58 3.4 34 4 — 77 38,827 19 18 62 60 31.6 20 4 5 39.0 47.1 16 2.9 30 3 53,760 81 979 24 — 74 73 5.2 37 -5 7.3 10.4 46 4.4 43 2 1,180 21 981 8 7 63 60 17.1 23 7 -26 26.1 31.2 16 2.8 33 4 — 54 366 54 38 70 64 98.1 31 8 0 130.5 165.1 49 4.1 41 4 1,500 17 641 42 40 64 62 78.2 17 5 3 88.4 93.5 11 2.2 24 8 19,040 77 381 74 47 77 75 44.3 31 8 0 60.1 81.4 39 3.9 41 3 2,890 24 794 58 53 62 60 9.6 14 1 8 12.3 15.5 6 1.8 16 1 63,750 83 19,093 28 24 77 76 23.0 34 0 34.3 52.8 38 1,400 33 660 40 33 64 26.7 33 7 1 35.7 46.1 43 4.4 41 3 3,820 34 2,110 34 29 65 62 17.2 37 11 0 24.7 36.6 53 5.0 44 3 780 16 458 59 57 61 60 1,903 22 7 -1 2,227 2,526 45 2.5 30 5 6,010 34 776 54 46 68 66 1.3 11 8 1.3 1.2 14.5 1.4 20 9 18,290 41 1,663 76 39 74 71 69 25 6 -1 82 96 37 2.9 29 5 9,930 47 219 54 50 69 65 0.2 31 2 -5 0.3 0.5 4 4.1 44 3 — 50 — — — 79 76 17.5 25 8 0 20.7 24.6 25 3.0 25 7 21,580 53 76 51 50 70 66 25.7 45 13 0 41.0 72.9 83 5.9 45 3 1,170 31 455 12 11 54 52 66 6.0 27 6 -1 8.2 11.6 24 4.0 32 4 3,220 36 463 42 40 70 0.9 17 5 -3 1.0 1.2 8 2.4 24 10 — 94 — 67 64 80 77 8.5 33 7 11.2 14.8 40 3.8 36 3 2,630 27 990 28 26 67 64 11.3 31 15.8 21.0 32 4.2 41 3 1,530 28 959 53 48 63 5.4 21 8 -1 6.2 6.6 46 2.3 28 4 14,520 50 279 48 46 65 61 0.09 17 8 6 0.1 0.1 12.7 22 8 24,630 54 9,173 — — 73 69 31.3 23 5 -1 36.0 38.3 44 2.4 28 4 5,840 51 721 65 59 68 65 11.1 44 12 -7 16.9 27.1 79 6.6 47 3 — 38 985 15 1 55 53 1,834 22 7 -1 2,145 2,430 45 2.5 30 5 5,870 33 857 54 46 68 66 12.2 36 12 11 17.3 24.8 77 6.9 42 3 2,030 17 — 4 1 55 54 60 32.2 34 8 2 45.8 64.3 74 4.9 45 2 1,980 25 415 21 20 61 52.3 39 9 -1 79.4 129.4 37 5.2 45 3 2,530 30 360 34 26 62 60 160.4 20 6 -3 185.1 201.9 38 2.3 33 5 3,340 23 2,089 62 54 71 70 See page POPULATION DATA 40.1 40 9 -1 63.4 104.1 54 5.9 48 2 1,690 18 2015 WORLD 582 27 26 SHEET68 59 13 68 58 0.8 18 7 2 0.9notes on 1.1 21 47 2.2 31 5 7,560 38 764 66 65 15.5 43 13 0 23.7 42.0 75 5.6 46 3 3,860 40 408 49 45 53 51 1,314.1 21 7 -1 1,512.9 1,660.1 42 2.3 29 5 5,760 32 842 54 47 68 66

Yemen SOUTH CENTRAL ASIA CENTRAL ASIA Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan SOUTH ASIA Afghanistan Bangladesh WORLD BhutanDEVELOPED MORE IndiaDEVELOPED LESS Iran DEVELOPED (Excl. China) LESS Maldives LEAST DEVELOPED Nepal AFRICA Pakistan SUB-SAHARAN AFRICA Sri Lanka NORTHERN AFRICA SOUTHEAST ASIA Algeria Brunei Egypt Cambodia Libya Indonesia Morocco Laos Sudan Malaysia Tunisia MyanmarSaharae Western PhilippinesAFRICA WESTERN Singapore Benin Thailand Burkina Faso Timor-Leste Cape Verde Viet CôteNam d’Ivoire EAST ASIA Gambia China Ghana China, GuineaHong Kong SARf China, Macao SARf Guinea-Bissau Japan Liberia Korea, Mali North Korea, South Mauritania Mongolia Niger Taiwan Nigeria EUROPE Senegal EUROPEAN Sierra LeoneUNION NORTHERN EUROPE Togo Channel Islands EASTERN AFRICA Denmark Burundi Estonia Comoros Finland Djibouti Iceland Eritrea Ireland Ethiopia Latvia Kenya Lithuania Madagascar Norway Malawi Sweden Mauritius United Kingdom Mayotte WESTERN EUROPE Mozambique Austria Reunion Belgium Rwanda France Seychelles Germany Somalia Liechtenstein South Sudan Luxembourg Tanzania © 2015 Population Reference Bureau Monaco Uganda Netherlands Zambia Switzerland

26.7 33 7 1 35.7 46.1 43 4.4 41 3 3,820 34 2,110 34 29 65 62 1,903 22 7 -1 2,227 2,526 45 2.5 30 5 6,010 34 776 54 46 68 66 69 25 6 -1 82 96 37 2.9 29 5 9,930 47 219 54 50 69 65 17.5 25 HEALTH,8 AND ENVIRONMENT 0 20.7 DATA 24.6 25 3.0 FOR25THE COUNTRIES 7 21,580 53 76 51 WORLD 50 70 66 POPULATION, AND ESTIMATES AND REGIONS OF THE 66 6.0 27 6 -1 8.2 11.6 24 4.0 32 4 3,220 36 463 42 40 70 8.5 33 7 -3 11.2 14.8 40 3.8 36 3 2,630 27 990 28 of Married 26 67 64 Percent Women Using Percent 4 5.4 21 8 -1 6.2 6.6 46 2.3 28 14,520 50 279 48 15-49 46 65 Life Expectancy 61 Net Population GNI per d Population 38.3 Contraception of28 Population 31.3 23 5 -1 36.0 44 2.4 4 5,840 51 65 59 68 at Birth 65 (years) Population Births Deaths Migration Infant Total per 721 Square Capita 1,834 7 2,145 2,430 45 2.5 30 5 5,870 33 857 54 46 68 66 mid-2015 per22 1,000 per 1,000 Rate-1per Mortality Fertility Percent Kilometer mid-2030 mid-2050 Age Age ($US) All Modern Both c (millions) Population Population 1,000 Rate Rate Urban of Arable (millions) (millions) <15 65+ 2014 Methods Sexes Males Fe 60 32.2 34 8 2 45.8 64.3 74 a 4.9b 45 2 1,980 25 415Land Methods 21 20 61 160.4 6 -3 185.1 201.9 38 2.3 33 5 3,340 23 2,089 54 70 7,336 20 8 — 8,505 9,804 37 2.5 26 8 15,030 53 523 62 56 71 69 0.8 18 7 0.9 1.1 47 2.2 31 5 7,560 38 764 66 65 68 68 1,254 11 10 2 1,295 1,310 5 1.7 16 17 39,020 77 238 67 59 79 76 1,314.1 21 1,512.9 1,660.1 42 2.3 29 5 5,760 32 842 54 47 68 66 6,082 22 7 -1 7,210 8,495 40 2.6 28 6 9,870 48 696 61 55 69 68 78.5 19 5 -1 90.2 99.3 15 1.8 24 16,080 71 442 82 60 74 72 4,702 24 7 -0 5,779 7,120 44 3.0 32 5 8,740 46 612 54 46 68 66 0.3 22 3 0 0.4 0.6 9 2.2 26 5 12,770 45 11,565 35 27 74 73 938 34 9 -1 1,300 1,887 62 4.3 40 4 2,270 29 521 37 32 62 60 28.0 22 7 -1 32.4 36.0 33 2.4 33 6 2,420 18 1,322 50 47 67 66 1,171 36 10 -0 1,658 2,473 59 4.7 41 4 4,720 40 487 35 29 60 58 199.0 30 7 -2 254.7 344.0 69 3.8 36 4 5,100 38 939 35 26 66 66 949 38 11 -0 1,369 2,081 64 5.0 43 3 3,480 484 30 25 57 56 20.9 18 -4 22.5 23.0 9 2.3 25 8 10,270 18 1,672 68 53 74 71 222 29 6 -1 289 392 29 3.4 31 5 9,740 51 500 51 46 71 69 628 20 7 -0 737 839 28 2.4 27 6 10,720 47 906 62 54 71 68 39.9 26 6 -1 49.9 60.4 21 3.0 28 13,540 73 524 56 48 74 72 0.4 17 3 1 0.5 0.5 4 1.6 25 5 71,020 77 9,796 — — 79 77 89.1 31 6 0 117.9 162.4 22 3.5 31 4 11,020 43 3,196 59 57 71 70 15.4 24 6 -2 18.1 21.3 28 2.7 31 6 3,080 21 376 56 39 64 61 6.3 21 4 -11 7.5 8.4 14 2.4 29 5 16,190 78 359 42 20 71 69 255.7 21 -1 307.6 366.5 31 2.6 29 5 10,250 54 1,086 62 58 71 69 34.1 22 6 -2 38.7 41.9 26 2.5 25 6 7,180 60 425 67 57 74 73 6.9 27 6 -3 8.8 10.6 68 3.1 37 4 4,910 38 475 50 42 68 67 40.9 38 9 -2 61.7 105.0 52 5.2 43 3 3,980 33 193 12 12 62 60 30.8 17 5 3 36.0 42.3 7 2.0 26 6 23,850 74 3,231 49 32 75 73 11.0 19 6 -1 12.3 12.9 16 2.1 23 8 10,600 68 388 63 50 76 74 52.1 19 9 -1 56.5 56.5 62 2.3 24 5 34 481 46 46 65 63 0.6 20 6 9 0.8 0.8 37 2.4 26 3 — 82 — — — 68 66 103.0 23 6 127.8 157.1 23 2.9 34 4 8,300 44 1,857 55 38 69 65 349 39 12 -1 509 784 64 5.4 43 3 4,040 45 402 16 12 55 54 100 879,543 62 55 83 80 5.5 10 5 14 6.5 7.0 1.8 1.3 16 11 80,270 10.6 37 10 0 15.1 21.5 67 4.9 45 3 1,850 45 393 18 13 59 58 65.1 12 8 0 69.8 66.1 11 1.6 18 11 13,950 49 393 79 77 75 72 18.5 44 11 -1 28.4 46.6 69 6.0 45 2 1,660 27 308 18 18 56 56 1.2 36 8 -9 1.8 2.8 45 5.7 42 5 5,680 32 775 22 21 68 66 0.5 21 6 -2 0.6 0.7 22 2.4 31 6 6,320 62 1,090 61 57 75 71 91.7 17 7 0 103.2 108.2 16 2.4 24 7 5,350 33 1,436 76 57 73 71 23.3 37 14 32.0 46.3 74 4.9 41 3 3,350 50 805 18 13 51 50 1,609 12 7 0 1,654 1,572 11 1.6 17 12 16,040 59 1,380 82 81 76 74 2.0 42 10 -1 3.1 5.0 47 5.6 46 2 1,580 57 459 9 8 59 58 1,371.9 12 7 -0 1,422.5 1,365.7 12 1.7 17 10 13,130 55 1,293 85 84 75 73 27.7 33 8 -2 37.7 52.6 41 4.2 39 5 3,960 51 588 27 22 61 60 7.3 9 6 3 8.1 8.6 1.6 1.2 11 15 56,570 100 231,314 80 75 84 81 11.0 38 12 0 16.0 24.2 67 5.1 42 3 1,140 36 366 6 5 60 58 0.7 12 3 11 0.7 0.8 3 1.2 11 8 100 — — — 83 80 1.8 37 13 -1 2.5 3.5 92 4.9 43 3 118460 1,430 49 594 16 14 54 53 126.9 8 10 1 116.6 96.9 2.1 1.4 13 26 37,920 93 3,000 54 44 83 80 54 4.7 42 3 820 47 899 20 19 60 59 4.5 36 9 -1 6.4 9.4 25.0 14 9 0 26.7 27.0 25 2.0 22 10 — 61 1,064 71 65 70 66 16.7 44 15 -4 26.1 43.6 56 5.9 47 3 1,660 39 245 10 10 53 53 50.7 9 5 3 52.2 48.1 3.0 1.2 14 13 34,620 82 3,339 80 70 82 79 3.6 34 9 -1 5.0 7.1 72 4.2 40 3 3,700 59 883 11 10 63 62 3.0 28 6 -1 3.7 4.4 21 3.1 27 4 11,230 68 487 55 50 69 65 18.9 50 11 0 33.8 68.0 60 7.6 52 950 22 118 14 12 60 59 23.5 9 7 1 23.4 20.4 3.9 1.2 14 12 — 73 — 71 — 80 77 181.8 39 14 -0 261.7 396.5 69 5.5 43 3 5,680 50 520 15 10 52 52 742 11 11 2 744 728 6 1.4 16 17 31,650 73 269 70 61 78 74 14.7 37 8 -1 21.5 32.3 33 5.0 42 4 2,290 45 439 22 20 65 63 510 10 10 2 520 518 4 1.6 16 19 36,280 73 470 72 64 81 78 6.5 37 14 -1 8.3 10.6 92 4.9 41 3 1,830 41 375 17 16 50 50 103 12 9 4 112 120 4 1.8 18 17 40,340 79 522 81 78 81 78 7.2 38 11 0 10.5 16.3 49 4.8 42 3 1,310 38 273 20 17 57 56 0.2 10 7 3 0.2 0.2 2.9 1.7 16 16 — 31 3,819 — — 82 80 388 36 9 -0 562 841 52 4.8 43 3 1,930 24 560 41 35 61 59 5.7 10 9 7 6.0 6.3 4 1.7 17 19 46,160 87 235 — — 81 79 10.7 43 10 0 17.2 30.4 65 6.2 46 3 790 10 977 22 18 59 57 1.3 10 12 -1 1.3 1.2 2.8 1.5 16 19 25,690 68 212 63 58 77 73 0.8 33 9 -3 1.0 1.3 36 4.3 41 3 1,530 28 868 19 14 61 60 5.5 10 10 3 5.8 6.1 2.2 1.7 16 20 40,000 85 244 77 75 81 78 0.9 27 9 -3 1.1 1.2 58 3.4 34 4 — 77 38,827 19 18 62 60 0.3 13 6 3 0.4 0.4 1.7 1.9 20 14 42,530 95 275 —8 — 82 81 5.2 37 7 -5 7.3 10.4 46 4.4 43 2 1,180 21 981 7 63 60 4.6 15 6 -5 5.2 5.8 3.7 2.0 22 13 40,820 60 395 65 61 81 79 98.1 31 8 0 130.5 165.1 49 4.1 41 4 1,500 17 641 42 40 64 62 2.0 11 14 -4 1.6 1.4 3.5 1.6 15 19 23,150 68 168 68 56 74 70 44.3 31 8 0 60.1 81.4 39 3.9 41 3 2,890 24 794 58 53 62 60 2.9 11 14 -4 2.7 2.4 3.8 1.7 15 18 25,390 67 129 63 50 74 69 23.0 34 7 0 34.3 52.8 38 4.4 41 3 1,400 33 660 40 33 65 64 5.2 12 8 7 5.9 6.7 2.4 1.8 18 16 65,970 80 646 88 82 82 80 17.2 37 11 0 24.7 36.6 53 5.0 44 3 780 16 458 59 57 61 60 9.8 12 9 8 11.4 12.4 2.2 1.9 17 20 46,710 84 376 75 65 82 80 1.3 11 8 -1 1.3 1.2 14.5 1.4 20 9 18,290 41 1,663 76 39 74 71 65.1 12 9 4 71.0 77.0 3.9 1.9 18 17 38,370 80 1,047 84 84 81 79 0.2 31 2 -5 0.3 0.5 4 4.1 44 3 — 50 — — — 79 76 191 10 10 4 198 199 3 1.7 16 19 44,790 77 566 71 68 81 79 25.7 45 13 0 41.0 72.9 83 5.9 45 3 1,170 31 455 12 11 54 52 8.6 10 9 6 9.2 9.5 3 1.5 14 18 45,040 67 638 70 68 81 78 0.9 17 5 -3 1.0 1.2 8 2.4 24 10 — 94 — 67 64 80 77 11.2 11 10 5 12.3 13.1 3.8 1.8 17 18 43,030 99 1,397 70 69 80 78 11.3 31 8 -1 15.8 21.0 32 4.2 41 3 1,530 28 959 53 48 65 63 64.3 12 8 0 68.5 72.3 3.5 2.0 19 18 39,720 78 352 76 74 82 79 0.09 17 6 0.1 0.1 12.7 2.4 22 8 24,630 54 9,173 — — 73 69 81.1 8 11 5 81.1 76.4 3.3 1.5 13 21 46,840 73 685 66 62 80 78 11.1 44 12 -7 16.9 27.1 79 6.6 47 3 — 38 985 15 1 55 53 0.04 9 7 4 0.04 0.05 3.3 1.5 15 16 — 15 1,249 —4 — 82 81 12.2 36 12 11 17.3 24.8 77 6.9 42 3 2,030 17 — 1 55 54 0.6 11 7 19 0.7 0.7 3.1 1.5 17 14 57,830 90 908 — — 82 80 52.3 39 9 -1 79.4 129.4 37 5.2 45 3 2,530 30 360 34 26 62 60 See notes on page POPULATION DATA 0.04 6 7 13 0.04 0.05 21 — 1.4 13 24 — 100 — — — SHEET— 40.1 40 9 -1 63.4 104.1 54 5.9 48 2 1,690 18 2015 WORLD 582 27 26 59 14 — 58 16.9 10 9 2 17.6 17.9 3.8 1.7 17 17 47,660 90 1,675 69 67 81 79 15.5 43 13 0 23.7 42.0 75 5.6 46 3 3,860 40 408 49 45 53 51 8.3 10 8 11 8.7 9.0 3.9 1.5 15 18 59,600 74 2,057 82 78 83 81

Lithuania Norway Sweden United Kingdom WESTERN EUROPE Austria Belgium France Germany Liechtenstein Luxembourg WORLD Monaco MORE DEVELOPED Netherlands LESS DEVELOPED Switzerland LESS DEVELOPED (Excl. China) EASTERN EUROPE LEAST DEVELOPED Belarus AFRICA Bulgaria SUB-SAHARAN AFRICA Czech Republic NORTHERN AFRICA Hungary Algeria Moldova Egypt Poland Libya Romania Morocco Russia Sudang Slovakia Tunisia Ukraine Westerng Saharae SOUTHERN EUROPE WESTERN AFRICA Albania Benin Andorra Burkina Faso Bosnia-Herzegovina Cape Verde Croatia Côte d’Ivoire Greece Gambia Italy Ghana Kosovo Guinea h i Macedonia Guinea-Bissau Malta Liberia Montenegro Mali Portugal Mauritania San Marino Niger Serbia Nigeria Slovenia Senegal Spain Sierra Leone OCEANIA Togo Australia AFRICA EASTERN Federated Burundi States of Micronesia Fiji Comoros French DjiboutiPolynesia Guam Eritrea Kiribati Ethiopia Marshall Kenya Islands Nauru Madagascar New Caledonia Malawi New Zealand Mauritius Palau Mayotte Papua New Guinea Mozambique Samoa Reunion Solomon Rwanda Islands Tonga Seychelles Tuvalu Somalia Vanuatu South Sudan Tanzania © 2015 Population Reference Bureau Uganda Zambia

2.9 11 14 -4 2.7 2.4 3.8 1.7 15 18 25,390 67 129 63 50 74 69 5.2 12 8 7 5.9 6.7 2.4 1.8 18 16 65,970 80 646 88 82 82 80 9.8 12 9 8 11.4 12.4 2.2 1.9 17 20 46,710 84 376 75 65 82 80 65.1 12 HEALTH,9 AND ENVIRONMENT 4 71.0 DATA 77.0 3.9 1.9 FOR18THE17 38,370 80 1,047 84 WORLD 84 81 79 POPULATION, AND ESTIMATES COUNTRIES AND REGIONS OF THE 191 10 10 4 198 199 3 1.7 16 19 44,790 77 566 71 68 81 79 Percent 8.6 10 9 6 9.2 9.5 3 1.5 14 18 45,040 67 638 70 of Married 68 81 78 Women Using Percent 11.2 11 10 12.3 13.1 3.8 1.8 17 18 43,030 99 1,397 70 15-49 69 80 Life Expectancy 78 Net5 Population GNI per d Population 72.3 Contraception of19 Population 64.3 12 8 0 68.5 3.5 2.0 18 39,720 78 76 74 82 at Birth 79 (years) Population Births Deaths Migration Infant Total per 352 Square Capita 81.1 8 81.1 76.4 Mortality 3.3 1.5 13 21 46,840 73 685 66 62 80 78 mid-2015 per 1,000 per11 1,000 Rate 5per Fertility Percent Kilometer mid-2030 mid-2050 Age Age ($US) All Modern Both a (millions) Population 1,000 Rate Rate Urban of Arable (millions) <15 65+ 2014 Methods Sexes Males Fe 0.04 Population 9 7 4 0.04 (millions) 0.05 3.3 1.5b 15 16 —c 15 1,249Land Methods — — 82 81 0.6 11 7 19 0.7 0.7 3.1 1.5 17 14 57,830 90 908 — — 82 80 7,336 20 8 — 8,505 9,804 37 2.5 26 8 15,030 53 523 62 56 71 69 0.04 6 7 13 0.04 1,310 0.05 —5 1.4 13 24 — 100 — — — — — 1,254 11 10 2 1,295 1.7 16 17 39,020 77 238 67 59 79 76 16.9 10 9 2 17.6 17.9 3.8 1.7 17 17 47,660 90 1,675 69 67 81 79 6,082 22 7 -1 7,210 8,495 40 2.6 28 6 9,870 48 696 61 55 69 68 8.3 10 8 11 8.7 9.0 3.9 1.5 15 18 59,600 74 2,057 82 78 83 81 4,702 24 7 -0 5,779 7,120 44 3.0 32 5 8,740 46 612 54 46 68 66 292 12 13 1 280 260 8 1.6 16 14 21,130 69 153 69 57 73 68 938 34 9 -1 1,300 1,887 62 4.3 40 4 2,270 29 521 37 32 62 60 9.5 13 13 2 9.1 8.7 4.4 1.7 16 14 17,610 76 173 63 51 73 67 1,171 36 10 -0 1,658 2,473 59 4.7 41 4 4,720 40 487 35 29 60 58 7.2 9 15 -0 6.6 5.8 7.6 1.5 14 20 15,850 73 216 69 40 75 71 949 38 11 1,369 2,081 64 5.0 43 3 3,480 38 484 30 25 57 56 10.6 10 10 2 10.8 11.1 2.4 1.5 15 17 26,970 74 334 86 78 79 76 222 29 6 -1 289 392 29 3.4 31 5 9,740 51 500 51 46 71 69 18 15 23,830 69 224 81 71 9.8 9 13 -3 9.7 9.4 4.6 1.4 76 72 39.9 26 6 -1 49.9 60.4 21 3.0 28 6 13,540 73 524 56 48 74 4.1 11 11 -1 3.7 2.9 10 1.3 16 10 5,480 42 227 60 42 72 68 89.1 31 6 0 117.9 162.4 22 3.5 31 4 11,020 43 3,196 59 57 71 70 38.5 10 10 -0 37.2 34.0 4.2 1.3 15 15 24,090 60 352 — — 78 74 6.3 21 4 -11 7.5 8.4 14 2.4 29 5 16,190 78 359 42 20 71 69 19.8 9 13 -4 18.6 16.4 8.8 1.3 16 17 19,030 54 226 70 51 75 71 34.1 22 6 -2 38.7 41.9 26 2.5 25 6 7,180 60 425 67 57 74 73 144.3 13 13 2 140.4 134.2 9.3 1.8 16 13 24,710 74 121 68 55 71 65 40.9 38 9 -2 61.7 105.0 52 5.2 43 3 3,980 33 193 12 12 62 60 5.4 10 9 0 5.4 5.0 6.0 1.4 15 14 25,970 54 389 80 66 76 73 11.0 19 6 -1 12.3 12.9 16 2.1 23 8 10,600 68 388 63 50 74 42.8 11 15 1 38.2 32.3 9.6 1.5 15 15 8,560 69 132 68 61 71 66 0.6 20 6 9 0.8 0.8 37 2.4 26 3 — 82 — — — 68 156 9 10 -0 154 149 4 1.4 15 19 29,730 68 517 66 48 81 79 349 39 12 -1 509 784 64 5.4 43 3 4,040 45 402 16 12 55 54 2.9 12 7 -6 3.0 2.8 7.9 1.8 19 12 10,260 56 467 69 10 78 76 10.6 37 10 0 15.1 21.5 67 4.9 45 3 1,850 45 393 18 13 59 58 0.08 9 4 -7 0.08 0.07 3.4 1.3 15 18 — 86 3,254 — — — — 18.5 44 11 -1 28.4 46.6 69 6.0 45 2 1,660 27 308 18 18 56 56 1.2 3.7 7 9 0 3.5 3.2 5 15 16 10,020 40 363 46 12 75 72 0.5 21 6 -2 0.6 0.7 22 2.4 31 6 6,320 62 1,090 61 57 71 4.2 9 12 -2 4.0 3.6 4.1 1.5 15 18 20,560 56 468 — — 77 74 23.3 37 14 0 32.0 46.3 74 4.9 41 3 3,350 50 805 18 13 51 50 11.5 9 10 -1 11.1 9.7 3.7 1.3 15 21 26,130 78 454 76 46 81 78 2.0 42 3.1 5.0 47 5.6 46 2 1,580 57 459 9 8 59 58 62.5 8 10 2 63.5 63.5 2.9 1.4 14 22 34,710 68 878 63 41 83 80 27.7 33 8 -2 37.7 52.6 41 4.2 39 5 3,960 51 588 27 22 61 60 1.8 13 4 -12 1.9 1.9 12 2.3 28 7 9,410 38 — 66 14 77 74 11.0 38 12 0 16.0 24.2 67 5.1 42 3 1,140 36 366 6 5 60 58 2.1 11 10 0 2.0 1.8 10 1.5 17 13 12,600 57 500 40 27 75 73 1.8 37 13 -1 2.5 3.5 92 4.9 43 3 1,430 49 594 16 14 54 53 0.4 10 8 3 0.4 0.4 5.5 1.4 15 16 27,020 95 4,799 86 46 82 80 54 4.7 42 3 820 47 899 20 19 60 59 4.5 36 9 -1 6.4 9.4 0.6 12 10 -1 0.7 0.8 4.4 1.6 18 14 14,510 64 362 23 15 77 74 16.7 44 15 -4 26.1 43.6 56 5.9 47 3 1,660 39 245 10 10 53 53 10.3 8 10 -3 9.9 9.1 2.8 1.2 14 19 28,010 61 950 87 83 80 77 3.6 34 9 -1 5.0 7.1 72 4.2 40 3 3,700 59 883 11 10 63 62 0.03 9 8 5 0.03 0.03 2.2 1.5 15 18 — 94 3,293 — — 87 84 18.9 50 11 0 33.8 68.0 60 7.6 52 4 950 22 118 14 12 60 59 7.1 9 14 -2 6.8 6.1 5.7 1.6 14 18 12,150 60 216 58 18 75 73 181.8 39 -0 261.7 396.5 69 5.5 43 3 5,680 50 520 15 10 52 52 2.1 10 9 0 2.1 2.0 2.1 1.6 15 18 28,650 50 1,206 79 63 81 78 14.7 37 8 -1 21.5 32.3 33 5.0 42 4 2,290 45 439 22 20 65 63 46.4 9 9 -2 45.4 43.7 2.9 1.3 15 18 32,860 77 373 66 62 83 80 6.5 37 14 -1 8.3 10.6 92 4.9 41 3 1,830 41 375 17 16 50 50 40 18 7 6 48 59 22 2.5 24 12 31,600 70 82 62 58 77 75 7.2 38 11 0 10.5 16.3 49 4.8 42 3 1,310 38 273 20 17 57 56 23.9 13 7 8 28.5 34.0 3.6 1.9 19 15 42,880 89 51 72 68 82 80 388 36 9 -0 562 841 52 4.8 43 3 1,930 24 560 41 35 61 59 0.1 24 5 -14 0.1 0.1 29 3.5 34 4 3,680 22 5,074 — 70 70 69 10.7 43 10 0 17.2 30.4 65 6.2 46 3 790 10 977 22 18 59 57 0.9 21 8 -6 0.9 1.0 15 3.1 29 5 8,030 51 527 29 — 70 67 0.8 33 9 -3 1.0 1.3 36 4.3 41 3 1,530 28 868 19 14 61 60 0.3 16 5 0 0.3 0.3 6.0 2.0 24 7 — 56 10,265 — — 77 75 0.9 27 9 -3 1.1 1.2 58 3.4 34 4 77 38,827 19 18 62 60 0.2 21 6 -6 0.2 0.2 13.3 2.9 26 8 — 93 17,953 67 58 79 76 5.2 37 7 -5 7.3 10.4 46 4.4 43 2 1,180 21 981 8 7 63 60 0.1 30 9 -1 0.2 0.2 45 3.8 36 4 2,580 54 5,600 22 18 65 63 98.1 31 8 0 130.5 165.1 49 4.1 41 1,500 17 641 42 40 64 62 0.06 30 4 -17 0.06 0.07 26 4.1 41 3 4,630 74 2,753 45 42 72 70 44.3 31 8 0 60.1 81.4 39 3.9 2,890 24 794 58 53 62 60 0.01 35 8 -9 0.01 0.02 33 3.9 37 1 — 100 — 36 23 66 62 23.0 34 7 0 34.3 52.8 38 4.4 41 3 1,400 33 660 40 33 65 64 0.3 15 6 4 0.3 0.3 5 2.3 24 9 — 70 4,959 — — 77 74 17.2 37 11 0 24.7 36.6 53 5.0 44 3 780 16 458 59 57 61 60 4.6 13 7 11 5.2 5.7 5.7 1.9 20 15 33,760 86 794 75 72 81 80 1.3 11 8 -1 1.3 1.2 14.5 1.4 9 18,290 41 1,663 76 39 74 71 0.02 13 11 0 0.02 0.02 13 1.7 20 6 14,280 84 1,779 33 30 72 69 0.2 31 2 -5 0.3 0.5 4 4.1 44 3 — 50 — — — 79 76 7.7 33 10 0 10.5 14.2 47 4.3 39 3 2,510 13 2,443 32 24 62 60 25.7 45 13 41.0 72.9 83 5.9 45 1,170 31 455 12 11 54 52 0.2 29 5 -28 0.2 0.2 16 4.7 39 5 5,600 19 2,451 29 27 74 73 0.9 17 -3 1.0 1.2 8 2.4 24 10 — 94 — 67 64 80 77 0.6 30 5 0 0.9 1.4 26 4.1 39 3 2,020 20 3,276 35 27 70 67 11.3 31 8 -1 15.8 21.0 32 4.2 41 1,530 28 959 53 48 65 63 0.1 27 7 -19 0.1 0.1 17 3.9 37 6 5,300 23 646 34 28 76 74 0.09 17 8 6 12.7 2.4 22 8 24,630 54 9,173 — — 73 69 0.01 25 9 0 0.01 0.02 10 3.2 33 5 5,260 59 — 31 22 70 67 11.1 44 12 -7 16.9 27.1 79 6.6 47 3 — 38 985 15 1 55 53 0.3 33 5 0 0.4 0.5 28 4.2 39 4 2,870 24 1,423 49 36 71 70 12.2 36 12 11 17.3 24.8 77 6.9 42 3 2,030 17 — 4 1 55 54 52.3 39 per 9 -1 79.4 129.4 37 5.2 45 3 2,530 30 360 34 26 62 60 mid-2050 Infant Total Age Age GNI per Percent Population All Modern Both Males Fe mid-2030 Population Births Deaths Net See on page 21 DATA 40.1 40 9 -1 63.4notes(millions) 104.1 54 5.9 48 2 1,690 Urban 18 2015 582 27 26 SHEET 59 15 58 Mortality Fertility <15 65+ Capita perWORLD Square POPULATION Methods Methods Sexes (millions) mid-2015 1,000 per 1,000 Migration Rate Rate ($US) Kilometer (millions) Population Population Rate 0per 15.5 43 13 23.7 42.0 75a 5.6b 46 3 3,860 40 408 49 45 53 51 Population Percent of Percent of Married Life Expectancy 2014c of Arable Land 1,000

POPULATION, HEALTH, AND ENVIRONMENT DATA AND ESTIMATES FOR THE COUNTRIES AND REGIONS OF THE WORLD Percent of Married GNI per Capita ($US) 2014c 15,030 39,020 9,870 8,740 2,270 4,720 3,480 9,740 13,540 11,020 16,190 7,180 3,980 10,600 — 4,040 1,850 1,660 6,320 3,350 1,580 3,960 1,140 1,430 820 1,660 3,700 950 5,680 2,290 1,830 1,310 1,930 790 1,530 — 1,180 1,500 2,890 1,400 780 18,290 — 1,170 — 1,530 24,630 — 2,030 2,530 1,690 3,860

Women 15-49 Using Population Contraceptiond per Square Percent Kilometer All Modern Urban of Arable Land Methods Methods 53 WORLD 523 62 56 77 MORE DEVELOPED 238 67 59 48 LESS DEVELOPED 696 61 55 46 LESS DEVELOPED 612 (Excl.

54China) 46 29 LEAST DEVELOPED 521 37 32 40 AFRICA 487 35 29 38 SUB-SAHARAN 484 AFRICA 30 25 51 NORTHERN 500 AFRICA 51 46 73Algeria 524 56 48 43Egypt 3,196 59 57 78Libya 359 42 20 60Morocco 425 67 57 33Sudan 193 12 12 68Tunisia 388 63 50 82Western Sahara — e — — 45 WESTERN402 AFRICA 16 12 45Benin 393 18 13 27Burkina Faso 308 18 18 62Cape Verde 1,090 61 57 50Côte d’Ivoire 805 18 13 57Gambia 459 9 8 51Ghana 588 27 22 36Guinea 366 6 5 49Guinea-Bissau 594 16 14 47Liberia 899 20 19 39Mali 245 10 10 59Mauritania883 11 10 22Niger 118 14 12 50Nigeria 520 15 10 45Senegal 439 22 20 41Sierra Leone 375 17 16 38Togo 273 20 17 24 EASTERN 560 AFRICA 41 35 10Burundi 977 22 18 28Comoros 868 19 14 77Djibouti 38,827 19 18 21Eritrea 981 8 7 17Ethiopia 641 42 40 24Kenya 794 58 53 33Madagascar 660 40 33 16Malawi 458 59 57 41Mauritius 1,663 76 39 50Mayotte — — — 31Mozambique 455 12 11 94Reunion — 67 64 28Rwanda 959 53 48 54Seychelles 9,173 — — 38Somalia 985 15 1 17South Sudan — 4 1 30Tanzania 360 34 26 ©18 2015 Population Uganda 582 Reference 27Bureau 26 40Zambia 408 49 45

Life Expectancy at Birth (years) Population Births mid-2015 per 1,000 Both (millions)MalesPopulation Sexes Females 7,336 71 69 20 73 1,254 79 76 11 82 6,082 69 68 22 72 4,702 68 66 24 70 62 938 60 34 63 1,171 60 58 36 61 57 949 56 38 59 71 222 69 29 72 74 39.9 72 26 77 71 89.1 70 31 73 71 6.3 69 21 74 74 34.1 73 22 75 62 40.9 60 38 64 76 11.0 74 19 78 68 0.6 66 20 70 55 349 54 39 56 59 10.6 58 37 61 56 18.5 56 44 57 75 0.5 71 21 80 51 23.3 50 37 52 59 2.0 58 42 60 61 27.7 60 33 63 60 11.0 58 38 61 54 1.8 53 37 56 60 4.5 59 36 61 53 16.7 53 44 53 63 3.6 62 34 64 60 18.9 59 50 61 52181.8 52 39 53 65 14.7 63 37 67 50 6.5 50 37 51 57 7.2 56 38 57 61 388 59 36 63 59 10.7 57 43 61 61 0.8 60 33 62 62 0.9 60 27 63 63 5.2 60 37 65 64 98.1 62 31 65 62 44.3 60 31 65 65 23.0 64 34 66 61 17.2 60 37 62 74 1.3 71 11 78 79 0.2 76 31 83 54 25.7 52 45 56 80 0.9 77 17 84 65 11.3 63 31 66 73 0.0969 17 78 55 11.1 53 44 57 55 12.2 54 36 56 62 52.3 60 39 63 59 40.1 58 40 60 53 15.5 51 43 56

Percent of Married Tertiary Gender Ratio of Female Share of Female Share Women 15-49 Using School GenderPercent Labor Force of Parliament Life Expectancy Population GNI per Nonagricultural Parity Index of Population ParticipationCapita Rates Wage Earners MembersContraceptiond at Birth (years) Total per Square Mortality Percent Kilometer mid-2030 Females mid-2050 Males Females Fertility Age Age ($US) All Modern Both b Ratea Rate Urban of Arable Land2015Methods Methods Sexes Males Fe (millions) 2014 2008/2014 (millions) 2008/2014 2008/2014 <15 65+2013 2014c 2008/2013 8,505 — 9,804 78 3776 2.51.03 26 8 0.66 15,030 53 34 523 20 62 56 71 69 1,295 — 1,310 104 104 5 1.71.27 16 17 0.79 39,020 77 48 238 23 67 59 79 76 7,210 — 8,495 74 4071 2.60.99 28 6 0.639,870 48 28 696 19 61 55 69 68 5,779 0.7 7,120 69 4466 3.00.94 32 5 0.568,740 46 28 612 17 54 46 68 66 1,300 0.8 1,887 46 6240 4.30.66 40 4 0.792,270 29 27 521 22 37 32 62 60 1,658 1.5 2,473 54 5949 4.7— 41 4 0.734,720 40 30 487 21 35 29 60 58 1,369 1.9 2,081 49 6442 5.0— 43 3 0.843,480 38 35 484 21 30 25 57 56 289 <0.1 392 78 2975 3.41.09 31 5 0.329,740 51 20 500 — 51 46 71 69 <0.1 49.9 60.4 96 21 100 3.01.51 28 6 0.2113,540 73 18 524 26 56 48 74 72 117.9 <0.1 162.4 90 2288 3.50.89 31 4 0.3211,020 43 19 3,196 — 59 57 71 70 7.5 14 2.4 — 29 5 0.3916,190 78 — 359 20 71 69 — —8.4 — 16 42 <0.1 38.7 41.9 74 2663 2.50.89 25 6 0.35 7,180 60 22 425 11 67 57 74 73 61.7 0.2 105.0 43 5239 5.21.12 43 3 0.41 3,980 33 — 193 — 12 12 62 60 <0.1 12.3 12.9 89 1693 2.11.62 23 8 0.3510,600 68 28 388 31 63 50 76 74 — 0.8 —0.8 37 — 2.4 — 26 3 — — 82 — — — — — 68 66 509 1.0 784 47 6440 5.4— 43 3 0.764,040 45 — 402 10 16 12 55 54 15.1 0.4 21.5 65 6743 4.90.27 45 3 0.86 1,850 45 26 393 7 18 13 59 58 28.4 0.5 46.6 31 6926 6.00.49 45 2 0.86 1,660 27 — 308 13 18 18 56 56 0.3 0.6 89 0.7 22 103 2.41.46 31 6 0.62 6,320 62 — 1,090 21 61 57 75 71 32.0 1.4 46.3 46 7432 4.90.62 41 3 0.64 3,350 50 21 805 9 18 13 51 50 0.7 3.1 59 5.0 4756 5.6 — 46 2 0.87 1,580 57 — 459 9 9 8 59 58 37.7 0.6 52.6 69 4165 4.20.63 39 5 0.94 3,960 51 32 588 11 27 22 61 60 16.0 0.7 24.2 47 6729 5.10.44 42 3 0.84 1,140 36 18 366 22 6 5 60 58 1.5 2.5 —3.5 92 — 4.9 — 43 3 0.87 1,430 49 — 594 14 16 14 54 53 0.4 42 5433 4.70.63 42 3 0.90 820 47 24 899 11 20 19 60 59 6.4 9.4 26.1 0.7 43.6 50 5640 5.90.43 47 3 0.62 1,660 39 — 245 9 10 10 53 53 0.4 5.0 30 7.1 7229 4.20.44 40 3 0.36 3,700 59 — 883 22 11 10 63 62 33.8 0.2 68.0 22 6015 7.60.34 52 4 0.45 950 22 36 118 13 14 12 60 59 261.7 1.3 396.5 46 6941 5.5 — 43 3 0.76 5,680 50 — 520 5 15 10 52 52 21.5 0.1 32.3 43 3339 5.00.59 42 4 0.75 2,290 45 27 439 43 22 20 65 63 0.4 8.3 10.6 48 9242 4.9 — 41 3 0.95 1,830 41 — 375 12 17 16 50 50 10.5 0.8 — 16.3 49 — 4.80.39 42 3 0.99 1,310 38 — 273 18 20 17 57 56 562 1.9 841 41 5238 4.8— 43 3 0.921,930 24 36 560 28 41 35 61 59 17.2 0.4 30.4 37 6529 6.20.42 46 3 1.02 790 10 — 977 35 22 18 59 57 — 1.0 63 1.3 3665 4.30.86 41 3 0.44 1,530 28 — 868 3 19 14 61 60 0.8 1.1 53 1.2 5843 3.40.68 34 4 0.54 — 77 — 38,827 13 19 18 62 60 0.3 7.3 — 10.4 46 — 4.40.50 43 2 0.89 1,180 21 — 981 22 8 7 63 60 130.5 0.6 165.1 — 49 — 4.1 — 41 4 0.88 1,500 17 39 641 26 42 40 64 62 60.1 — 81.4 69 3965 3.90.70 41 3 0.86 2,890 24 36 794 21 58 53 62 60 34.3 0.1 52.8 39 3838 4.40.94 41 3 0.96 1,400 33 37 660 21 40 33 65 64 24.7 4.1 36.6 38 5335 5.00.65 44 3 1.04 780 16 — 458 17 59 57 61 60 0.2 1.3 94 1.2 14.5 98 1.41.22 20 9 0.5918,290 41 38 1,663 12 76 39 74 71 — 0.3 —0.5 — 4 4.1 — 44 3 — — 50 — — — — — 79 76 41.0 — 72.9 27 8325 5.90.69 45 3 1.03 1,170 31 — 455 40 12 11 54 52 — 1.0 —1.2 — 8 2.4 — 24 10 — — 94 — — — 67 64 80 77 15.8 1.3 21.0 31 3234 4.20.75 41 3 1.01 1,530 28 34 959 58 53 48 65 63 — 0.1 69 0.1 12.7 75 2.42.20 22 8 — 24,630 54 53 9,173 44 — — 73 69 16.9 0.2 — 27.1 79 — 6.6 — 47 3 0.49 — 38 — 985 14 15 1 55 53 17.3 1.3 — 24.8 77 — 6.9 — 42 3 — 2,030 17 — — 24 4 1 55 54 79.4 2.1 129.4 34 3732 5.20.54 45 3 0.98 2,530 30 33 360 36 34 26 62 60 See page 21 5425 POPULATION DATA 63.4 3.7notes on 104.1 29 5.90.78 48 2 0.96 1,690 18 352015 WORLD 582 35 27 26 SHEET59 16 58 23.7 4.2 — 42.0 75 — 5.6 — 46 3 0.85 3,860 40 — 408 13 49 45 53 51

Maternal Percent Ages Deaths per Net 15-24 With Secondary School 100,000 Births Ratio Deaths MigrationHIV/AIDS PopulationEnrollment Infant per 1,000 Rate per Males Population 1990 2013 1,0002014 269 8 136 — — 10 25 15 2 — 338 7 159 -1 — 443 7 200 -0 0.4 900 9 384 -1 0.5 801 10 412 -0 0.9 964 11 488 -0 1.1 242 6 118 -1<0.1 160 6 89 -1<0.1 120 6 45 0<0.1 4 31 15 -11 — 310 6 120 -2<0.1 720 9 360 -2 0.1 91 6 46 -1<0.1 —6 — 9 — 1,053 12 539 -1 0.6 600 10 340 0 0.2 770 11 400 -1 0.4 230 6 53 -2 0.8 740 14 720 0 0.9 710 10 430 -1 0.4 760 8 380 -2 0.4 1,100 12 650 0 0.4 930 13 560 -1 0.8 1,200 640 -1 0.3 9 1,100 15 550 -4 0.5 630 9 320 -1 0.2 1,000 11 630 0<0.1 1,200 14 560 -0 0.7 530 8 320 -1 0.1 2,300 14 1,100 -1 0.2 660 11 450 0 0.5 1,034 9 440 -0 1.3 1,300 10 740 0 0.3 630 9 350 -3 — 400 9 230 -3 0.5 1,700 7 380 -5 0.2 1,400 8 420 0 0.5 490 8 400 0 — 740 7 440 0 0.2 1,100 11 510 0 2.4 70 8 73 -1 0.2 —2 — -5 — 1,300 13 480 0 — —5 — -3 — 1,400 8 320 -1 1.0 —8 — 6 — 1,300 12 850 -7 0.2 1,800 12 730 11 0.7 910 9 410 -1 1.4 780 9 360 -1 2.3 580 13 280 0 3.3

1,500 2,890 1,400 780 18,290 — 1,170 GNI per — Capita ($US) 1,530 2014c 24,630 15,030 — 39,020 2,030 9,870 2,530 8,740 1,690 2,270 3,860 4,720 1,710 3,480 2,680 9,740 7,150 13,540 2,940 11,020 610 16,190 2,130 7,180 5,120 3,980 700 10,600 22,480 — 16,500 4,040 3,030 1,850 12,290 1,660 17,460 6,320 3,260 3,350 9,880 1,580 12,700 3,960 5,940 1,140 29,900 1,430 54,620 820 43,400 1,660 55,860 3,700 15,260 950 14,420 5,680 7,870 2,290 13,900 1,830 7,720 1,310 7,260 1,930 4,120 790 16,710 1,530 4,670 — 19,630 1,180 12,800 1,500 21,120 2,890 22,310 1,400 14,750 780 18,710 18,290 — — 10,300 1,170 12,450 — 11,650 1,530 — 24,630 1,750 — 8,490 2,030 — 2,530 23,960 1,690 21,990 3,860 10,230

31 65 8 165.1 49 4.1 — 41 4 0.88 1,500 17 39 641 40 64 26 42 17Ethiopia 641 42 40 64 98.1 62 1,400 420 0 0.5 130.5 0.6 — — 31 65 8 60.1 81.4 3965 3.90.70 41 3 0.86 2,890 24 36 794 53 62 24Kenya 794 58 53 62 44.3 60 490 400 0 — — 69 21 58 34 66 7 34.3 52.8 3838 4.40.94 41 3 0.96 1,400 33 37 660 33 65 33Madagascar 660 40 33 65 23.0 64 740 440 0 0.2 0.1 39 21 40 37HEALTH, 11 24.7 36.6 5335 FOR 5.00.65 3 1.04 AND 780 REGIONS 16 — OF458 57 61 16Malawi 458 59 57 61 17.2 60 62 1,100 510 0 2.4 4.1 38 ESTIMATES 17 59 POPULATION, AND ENVIRONMENT DATA AND THE 44 COUNTRIES THE WORLD 11 78 8 1.3 1.2 14.5 1.41.22 20 9 0.5918,290 41 38 1,663 39 74 41Mauritius 1,663 76 39 74 1.3 71 70 73 -1 0.2 0.2 94 98 12 76 Percent Ages Tertiary Ratio—of Female Share of — Female 31 83 2 -5 Percent 0.3 4 4.1 3 — 50 — — — 79 50Mayotte — — of Married — 79 0.2 76 —Maternal — — — —0.5 — — 44 Gender —Share Women Using Life Expectancy Deaths per 15-24 With Secondary School School Gender Labor Force 45 56 13 41.0 72.9 8325 5.90.69 45 3 1.03 1,170 Nonagricultural 31 — 455of Parliament 11 54 31Mozambique 455 12 15-49 11 54 25.7 52 1,300 480 0 — — 27 40 12 Population d Contraception Birth 100,000 Births Enrollment Ratio Parity Wage Earners — Members 0.9 17 84 -3 —HIV/AIDS— 1.0 8 2.4 —Index24 Participation 10 — Rates — 94 — 64 80 94Reunion — 67 64 80 at 77 (years) —5 — —1.2 — — 67 per Square Percent All Modern Both Males Females 31 66 8 15.8 21.0 3234 4.20.75 41 3 1.01 1,530 28 34 959 48 65 28RwandaKilometer 959 53 48 65 11.3 63 1,400 320 -1Males 1.0 Females 1.3 31 58 53 Urban of Arable Methods Sexes Males Females 1990 2013 2014 2008/2014 2008/2014 2008/2014 2008/2013 17 62014 0.1 0.1 12.7 2.42.20 22 8 2013 54 53 9,173 2015 — 73 54Seychelles 9,173Land Methods — — 73 0.09 69 78 —8 — — — 69 75 — 24,630 44 — 53 62 56 71 269 136 — 78 76 20 44 73 12 16.9 27.1 79 6.61.03 3 0.66 38 34 985 1 55 38Somalia 523 985 15 1 55 11.1 69 53 57 1,300 850 -7 — 0.2 0.2 — — — 47 0.49 — — 14 15 77 238 67 59 79 25 15 11 — — 104 104 23 36 82 12 17.3 24.8 77 6.91.27 3 0.79 17 48 — 4 1 55 17South Sudan — 4 1 55 12.2 76 54 56 1,800 730 0.7 1.3 — — — 42 — 2,030 — 24 48 61 55 69 338 159 — 74 19 39 72 9 79.4 129.4 3771 5.20.99 3 0.63 30 28 360 26 62 30Tanzania 696 360 34 26 62 52.3 68 60 63 910 410 -1 — 1.4 2.1 34 32 0.54 45 0.98 2,530 33 36 34 46 54 46 68 443 200 0.7 69 17 40 70 9 63.4 104.1 5466 5.90.94 2 0.56 18 28 582 26 59 18Uganda 612 582 27 26 59 40.1 66 58 60 780 360 -1 0.4 2.3 3.7 29 25 0.78 48 0.96 1,690 35 35 27 29 37 32 62 900 384 0.8 46 40 22 43 63 13 23.7 42.0 75 5.60.66 3 0.79 40 27 408 45 53 51 56 580 280 0 0.5 3.3 4.2 — — — 46 0.85 3,860 — 13 49 40Zambia 521 408 49 45 53 15.5 60 40 35 29 60 801 412 1.5 54 — 43 21 33 61 9 25.2 37.5 5549 4.30.85 3 0.73 33 30 436 67 61 33Zimbabwe487 436 67 67 61 17.4 58 60 62 520 470 -3 0.9 4.8 7.0 48 47 0.93 1,710 34 35 67 38 484 30 25 57 56 59 964 488 -0 0.6 1.1 229 1.9 49 42 — 46 0.842,680 21 20 MIDDLE AFRICA 149 50 44 54 14 378 9632 6.10.48 3 0.90 46 35 569 10 52 46 569 20 10 52 1,061 672 1.0 48 — 17 51 51 46 71 242 118 <0.1 78 — 46 72 14 39.4 65.5 9575 6.11.09 2 0.32 62 20 421 12 52 62Angola 500 421 18 12 52 25.0 69 50 53 1,400 460 1<0.1 0.6 1.1 38 25 0.37 47 0.82 7,150 — 37 18 73Cameroon383 524 56 48 74 23.7 56 72 77 160 89 -0 <0.1 <0.1 96 100 1.51 43 0.21 2,940 18 26 23 37 58 11 34.4 51.9 57 4.90.73 3 0.83 52 26 383 14 57 52 23 14 57 720 590 1.2 2.1 56 48 27 43Central African 3,196 59 57 71 5.6 48 70 73 120 45 0 <0.1 <0.1 90 88 0.89 45 0.32 610 19 45 52 16 8.5 13.9 10912 6.20.36 3 0.85 39 — 307 9 50 39 307 Republic 15 9 50 1,200 880 1.4 2.0 24 — 15 78Chad 359 42 20 71 13.7 50 69 31 15 1 — — — — — 48 16 48 74 14 21.8 37.4 95 6.50.24 2 0.39 22 — 279 5 2 51 22 279 5 2 51 52 1,700 980 0.6 1.0 31 14 0.81 2,130 15 60 67 57 74 310 120 <0.1 74 22 11 37 75 10 6.7 10.2 6163 4.80.89 3 0.35 64 — 870 20 58 64Congo 425 870 45 20 58 4.8 73 57 59 670 410 -8<0.1 0.9 1.4 57 50 0.75 41 0.94 5,120 12 45 33 193 Rep. 12 12 62 720 360 0.2 43 —8 20 Dem. 46 64 16 193.6 10839 6.61.12 3 0.41 42 — 1,044 8 50 42Congo, 1,044 20 8 50 73.3 60 48 52 1,000 730 -0 0.1 0.3 114.9 0.5 54 33 0.45 46 0.97 700 68 63 50 76 91 46 5<0.1 <0.1 89 93 28 31 Guinea 37 78 13 1.2 1.8 70 5.11.62 3 0.35 39 — 667 10 57 39Equatorial388 667 13 10 57 0.8 74 56 59 1,600 290 1.3 2.5 — — — 39 0.8822,480 20 13 82 — — — 68 — — — —3.3 — — 16,500 — 32 70 9 1 — 2.4 43 4.1 — 38 5 0.86 86 — 523 19 63 86Gabon 523 31 19 63 1.8 66 62 64 380 240 0.6 1.3 35 16 31 45 402 12 55 1,053 539 1.0 47 — 42 10 and Principe16 36 56 7 0.3 0.4 4340 4.30.86 4 0.76 67 — 2,239 33 66 67Sao Tome 2,239 38 33 66 0.2 54 64 68 410 210 -6 0.6 0.2 0.2 76 85 0.58 3,030 18 38 45 393 18 13 59 63 59 58 61 600 340 3 4.2 0.2 0.4 65 43 0.27 31 0.86 26 7 60 SOUTHERN AFRICA 60 23 63 10 69 77 36 2.71.36 5 0.75 12,290 59 45 464 59 61 59 464 59 61 190 156 8.3 102 109 39 27 18 18 56 770 400 0.5 31 13 26 57 8 2.3 2.5 3126 2.90.49 5 0.86 57 — 755 51 64 57Botswana 308 755 53 51 64 2.1 56 62 67 360 170 2 0.4 5.7 8.9 79 84 1.25 33 0.8817,460 41 10 53 62Lesotho1,090 61 57 75 1.9 43 71 80 230 53 -5 5.9 0.8 0.3 89 103 0.62 3,260 21 60 5 0.80 27 — 682 60 44 31 46 20 2.3 3.0 59 3.31.46 36 27 682 60 60 44 720 490 10.2 45 62 25 50Namibia 301 805 18 13 51 2.5 62 50 52 740 720 0 2.9 0.9 1.4 46 32 0.62 35 0.64 9,880 21 9 56 29 67 7 3.3 4.7 39 3.61.28 4 0.86 46 43 301 55 64 46 56 55 64 320 130 5.0 — — 38 57South Africa 459 9 8 59 55.0 59 58 60 710 430 3 4.0 0.4 0.7 59 56 — 30 0.8712,700 9 60 22 63 10 59.8 65.2 34 2.61.37 6 0.74 62 — 458 60 61 62 458 60 60 61 150 140 8.1 107 114 46 41 51Swaziland733 588 27 22 61 1.3 50 60 63 760 380 -1 7.2 0.4 0.6 69 65 0.63 37 0.94 5,940 32 11 66 30 48 14 1.5 1.8 5060 3.31.05 4 0.61 21 — 733 66 49 21 66 66 49 550 310 15.5 61 15 36 366 6 5 60 58 61 1,100 650 0.4 1,116 0.7 47 29 0.84 18 AMERICAS266 987 74 16 79 7 1,221 1493 2.00.44 10 0.73 29,900 80 45 266 68 76 80 73 68 76 83 61 1 — — 90 — 24 22 73 49 594 16 14 54 53 56 930 560 0.8 401 1.5 — — — 19 0.87 — 14 74 NORTHERN AMERICA 74 357 77 12 81 8 445 6 1.81.37 15 0.82 54,620 81 48 178 68 79 81 178 68 79 11 26 3 — — 96 95 21 47 20 19 60 1,200 640 0.3 0.4 42 33 11 11 61 76 41.0 46.9 4.8 1.60.63 16 0.90 80 24 79 72 81 80Canada 899 79 74 72 81 35.8 59 79 84 11 6 — — 112 111 — 16 0.8743,400 50 28 74 39 245 10 10 53 1,100 550 0.5 359.4 0.7 50 40 9 74 13 53 8 398.3 6.0 1.90.43 15 0.62 81 — 207 68 79 81United States 207 74 68 79321.2 53 76 81 12 28 3 — — 94 94 1.37 19 0.8255,860 48 20 59 883 AND THE 11 CARIBBEAN 10 63630 72 62 64 630 320 0.4 30 29 0.36 — 22 73 LATIN AMERICA 18 78 6 776 1792 2.10.44 7 0.67 15,260 80 44 371 67 75 80 371 73 67 75 130 79 -1 0.2 716 0.1 87 — 27 23 22 118 14 12 60173 72 59 61 1,000 630 0.2 22 15 0.34 29 0.45 36 13 71 CENTRAL 585 AMERICA 71 20 78 5 231 1486 2.41.02 6 0.56 14,420 74 40 585 65 75 74 65 75 111 63 -2<0.1 0.1 205 <0.1 80 34 50 520 15 10 52 1,200 560 1.3 46 — 36 5 55 21 53 4 0.5 0.5 1341 2.41.68 4 0.76 44 — 475 52 74 44Belize 475 55 52 74 0.4 52 71 77 75 45 4 0.7 0.3 0.4 83 89 0.60 7,870 13 45 439 22 20 65 530 320 0.1 43 39 43 15 67 4 5.6 6.1 8.1 1.90.59 7 0.75 73 27 1,972 75 79 73Costa Rica 1,972 76 75 79 4.8 63 77 82 38 38 2 0.1 <0.1 105 113 1.24 23 0.5913,900 43 33 76 41 375 17 16 50 2,300 0.4 48 — 31 12 18 51 5 1,100 6.8 6.8 1742 2.01.13 7 0.95 67 — 904 68 73 67El Salvador 904 72 68 73 6.4 50 68 77 110 69 -8 0.2 0.2 70 71 0.61 7,720 33 32 72 38 273 20 17 57 660 450 0.8 — — 18 25 57 5 21.4 27.5 19 3.10.39 5 0.99 52 — 1,056 44 73 52Guatemala 1,056 54 44 73 16.2 56 69 76 270 140 -1 0.5 0.2 0.2 68 62 1.04 40 0.56 7,260 37 13 54 24 41 35 61 1,034 440 1.9 41 — 34 28 24 63 5 10.2 11.7 2238 2.71.38 5 0.92 54 36 819 64 74 54Honduras560 819 73 64 74 8.3 59 72 76 290 120 -2 1.3 0.2 0.2 64 78 0.52 4,120 — 26 73 10Mexico 526 977 22 18 59127.0 73 57 61 1,300 740 0.3 148.1 0.4 37 29 0.42 28 1.0216,710 35 73 19 78 5 163.8 1391 2.30.96 7 0.56 79 — 526 66 75 79 73 66 75 88 49 -2 0.1 <0.1 84 40 37 28Nicaragua416 868 19 14 61 6.3 72 60 62 630 350 -4 — — 63 65 0.44 4,670 3 80 23 78 5 7.4 8.4 1672 2.40.86 5 0.59 59 — 416 77 75 59 80 77 75 170 100 0.2 <0.1 66 — 32 39 77Panama 38,827 19 18 62 4.0 75 60 63 400 230 0.5 0.8 53 43 0.68 28 0.5419,630 13 63 19 80 5 4.9 5.8 1776 2.71.56 8 0.60 78 — 744 60 78 78 744 63 60 78 98 85 2 0.2 0.1 71 44 19 21 981 8 7 63 43 70 60 65 1,700 380 -4 0.4 0.2 0.3 — — 0.89 — 22 62 CARIBBEAN 18 76 8 47 50 28 2.30.50 9 0.70 12,800 68 45 793 59 73 68 793 62 59 73 242 169 0.5 80 85 — 26 24 17Antigua 2,248 641Barbuda — 42 40 64 0.0974 62 65 1,400 420 0.5 0.6 — — — 24 26 — and 14 80 0 — 0.1 0.1 16 1.52.07 8 0.88 30 39 2,248 — 77 30 — 77 —6 — — 98 113 — 21,120 51 24 794 58 53 62 490 400 — 69 21 15 65 6 0.4 0.5 1465 1.90.70 7 0.86 85 36 4,708 — 74 85Bahamas4,708 — — 74 0.4 60 71 77 43 37 1 — 90 95 — 26 0.8722,310 52 17 — 33 660 40 33 65 740 440 0.2 0.1 39 38 21 12 66 9 0.3 0.3 19 1.70.94 13 0.96 46 37 2,525 55 75 46Barbados 2,525 59 55 75 0.3 64 73 78 120 52 2 — — 99 111 2.45 20 0.8614,750 52 20 59 16 458 59 57 61 1,100 510 4.1 38 35 17 11 62 8 11.2 10.6 4.2 1.70.65 13 1.04 75 — 348 72 78 75Cuba 348 74 72 78 11.1 60 77 80 63 80 -2 2.4 0.2 <0.1 92 92 1.65 17 0.6218,710 45 49 74 41Curaçao1,663 76 39 74 73 1 — 0.2 0.2 94 98 38 12 — 13 78 8 0.2 8.7 2.11.22 15 0.59 — — — — 78 — — — — 78 0.2 71 75 81 —70 — — 83 89 2.20 19 — — — 50 — — — 79 —9 — — — — — 14 83 -5 — 0.07 0.06 20 2.1 — 22 10 — 10,300 68 — 1,133 — 75 68Dominica 1,133 75 0.0776 72 77 93 100 22 — 31 455 11 54 1,300 480 — 27 40 Republic 12 21 56 6 11.3 12.2 3125 2.50.69 6 1.03 72 — 1,310 68 73 72Dominican 1,310 70 68 73 10.5 52 70 77 240 100 -3 — 0.4 0.4 72 80 1.60 31 0.6512,450 42 19 70 94 — 67 64 80 —34 — — —0.1 — — 26 — 17 84 8 0.1 15 2.11.36 7 — 11,650 41 — 3,710 — 76 41Grenada3,710 — — 76 0.1 77 74 79 23 -2 — 102 100 25 — 28 959 53 48 65 1,400 320 1.0 1.3 31 34 34 58 — 13 66 -2 — 0.4 0.4 8.7 2.20.75 14 1.01 98 54 — — 81 98Guadeloupe — — — 81 0.4 63 78 84 —7 — — — — — 21 — — — 54Haiti 9,173 — — 73 10.9 61 69 78 — — — 69 75 — 1,750 53 44 28 65 9 -3 — 13.6 16.9 42 3.22.20 4 0.86 59 — 1,092 31 64 59 1,092 35 31 64 670 380 0.5 0.8 — — — 35 3 35 38Jamaica2,268 985 15 1 55 2.7 70 53 57 1,300 850 0.2 0.2 — — — 24 0.49 8,490 — 14 73 18 78 7 2.9 2.7 21 2.32.29 9 0.79 52 48 2,268 68 74 52 73 68 74 98 80 -5 0.8 0.6 76 79 17 17Martinique— 1 55 0.4 79 54 56 1,800 730 0.7 1.3 — 24 — 11 85 0.4 8 1.9 — 19 17 — — 89 51 — — 82 89 —4 — 82 —8 — -10 — — —0.4 — — 30Puerto Rico 360 34 26 62 3.5 76 60 63 910 410 1.4 2.1 34 32 0.54 18 0.9823,960 33 36 84 10 83 8 3.5 3.4 7.2 1.51.43 17 0.66 99 46 5,806 72 79 99 5,806 84 72 79 — — -15 — — 78 83 — ©32 2015 Population See notes on 93 page POPULATION DATA 18 582 Reference 27Bureau 26 59 0.0573 58 60 780 360 2.3 3.7 29 25 0.78 21 352015 WORLD 35 — St. Kitts-Nevis 14 78 8 1 — 0.05 0.06 21 13 1.82.09 8 0.96 32 — 921 — SHEET75 17 921 — — 75 — — — 110 — 21,990 14 40St. Lucia5,855 408 49 45 53 0.2 51 580 280 3.3 4.2 — — — 22 13 12 56 6 0.2 0.2 18 1.52.00 9 0.85 15 — 5,855 52 79 15 56 52 79 75 83 60 34 0 — — 88 88 0.8210,230 21 56

62 60 64 60 71 76 52 77 63 69 53 54 60 58 51 60 50 50 56 48 50 57 48 56 62 64 59 62 43 62 59 50 74 77 79 76 72 72 71 77 68 69 72 73 72 75 70 74 71 73 77 75 72 70 74 78 61 70 79 76 73 75

14,750 18,710 — 10,300 12,450 11,650 GNI—per Capita 1,750 ($US) 8,490 c 2014 — 15,030 23,960 39,020 21,990 9,870 10,230 8,740 10,610 2,270 26,220 4,720 14,850 3,480 — 9,740 6,130 13,540 15,900 11,020 21,570 16,190 12,600 7,180 11,120 3,980 — 10,600 6,930 — 8,010 4,040 11,510 1,850 15,960 1,660 20,220 6,320 17,140 3,350 11,450 1,580 10,480 3,960 25,130 1,140 8,550 1,430 16,910 820 38,140 1,660 29,800 3,700 7,510 950 14,670 5,680 32,550 2,290 11,910 1,830 87,700 1,310 17,330 1,930 36,240 790 5,080 1,530 133850 — 53,760 1,180 — 1,500 19,040 2,890 63,750 1,400 3,820 780 6,010 18,290 9,930 — 21,580 1,170 3,220 — 2,630 1,530 14,520 24,630 5,840 — 5,870 2,030 1,980 2,530 3,340 1,690 7,560 3,860 5,760

46Barbados 2,525 59 55 75Cuba 348 74 72 —Curaçao — — — 68Dominica 1,133 — — Republic 70 72Dominican 1,310 68 Percent 41Grenada3,710 — of Married — Women 98Guadeloupe — — 15-49 Using — Population d Contraception Square 59Haiti per 1,092 35 31 Percent All Modern 52JamaicaKilometer 2,268 73 68 Urban of Arable Methods 89Martinique — Land Methods — — 53 523 62 56 99Puerto Rico 5,806 84 72 77 238 67 59 32St. Kitts-Nevis 921 — — 48 696 61 55 15St. Lucia5,855 56 52 46 612 54 46 and the Grenadines 51St. Vincent 2,204 — — 29 521Tobago 37 32 and 15Trinidad5,375 43 38 40 487 35 29 SOUTH AMERICA 84 309 75 69 38 30 25 93Argentina484 108 55 53 51 51 46 69Bolivia 500 242 61 34 73Brazil 524 56 48 86 281 80 77 43Chile 1,347 3,196 59 57 90 61 — 78Colombia 359 42 20 76 3,104 79 73 60 425 67 57 70Ecuador1,425 73 59 33 193 12 12 77French Guiana — — — 68 63 50 29Guyana 388 180 34 33 82 — — — 64Paraguay 159 79 70 45 402 16 12 79Peru 761 75 52 45 18 13 71Suriname 393 923 48 47 27 18 18 93Uruguay 308 204 77 75 62 1,090 61 57 94Venezuela 1,120 70 62 50 805 18 13 ASIA 47 938 66 60 57 459 9 8 ASIA (Excl.832 China) 44 57 48 51 588 27 22 WESTERN705 ASIA 71 54 37 36 6 5 63Armenia 366 675 55 26 49 16 14 53Azerbaijan594 510 51 13 47Bahrain88,490 899 20 19 100 62 31 39 245 10 10 67Cyprus 1,260 — — 59 11 10 54Georgia 883 944 53 35 22 118 14 12 71Iraq 1,080 53 33 50 520 15 10 91Israel 2,846 — — 45 439 22 20 83Jordan 3,810 61 42 41 375 17 16 98Kuwait35,893 52 39 38 273 20 17 87Lebanon2,993 58 34 24 560 41 35 75Oman 13,574 24 15 10 977 22 18 Territory 83Palestinian 9,925 57 44 28Qatar 18,750 868 19 14 100 38 34 77 38,827 19 18 81Saudi Arabia 979 24 — 21 981 8 7 54Syria 366 54 38 17 641 42 40 77Turkey 381 74 47 24United19,093 794Emirates 28 58 53 Arab 83 24 33Yemen 2,110 660 40 33 34 34 29 16 458 59 57 SOUTH CENTRAL ASIA54 34 776 46 41 1,663 76 39 CENTRAL 219 ASIA 47 54 50 50Kazakhstan— — — 53 76 51 50 31Kyrgyzstan463 455 12 11 36 42 40 94Tajikistan 990 — 67 64 27 28 26 28Turkmenistan 959 53 48 50 279 48 46 54Uzbekistan 9,173 — — 51 721 65 59 38 985 15 1 SOUTH ASIA 33 857 54 46 17 — 4 1 25Afghanistan 415 21 20 30Bangladesh 360 34 26 23 2,089 62 54 ©18 2015 Population 582 Reference 27Bureau 65 26 38Bhutan 764 66 40 408 49 45 32India 842 54 47

12 78 9 0.3 0.3 19 1.72.45 20 13 0.8614,750 46 52 2,525 55 75 75 0.3 73 120 52 2 — — 99 111 20 59 11 80 8 11.2 10.6 4.2 1.71.65 17 13 0.6218,710 75 45 348 72 78 78 11.1 77 63 80 -2 0.2 <0.1 92 92 49 74 13 81 1 — 0.2 0.2 8.7 2.12.20 19 15 — — — — — — 78 78 0.2 75 —8 — — 83 89 — — 14HEALTH, 9 -5 — 0.07 0.06 20 2.1THE 10 — 10,300 68 — OF 1,133 — 75 75 0.0772 77 — — — 93 100 FOR — 22 22 — POPULATION, AND ENVIRONMENT DATA AND ESTIMATES COUNTRIES AND REGIONS THE WORLD 21 77 6 11.3 12.2 3180 2.51.60 31 6 0.6512,450 72 42 1,310 68 73 73 10.5 70 240 100 -3 0.4 0.4 72 19 70 Maternal Ages Tertiary Ratio of Female Share of 17 79 8 0.1 0.1 15 2.1 7 — 11,650 41 — 3,710Female — — 76 76 0.1 74 34 23 -2 Percent — — 102 100 1.36 26 Gender 25Share Deaths per 15-24 With Secondary School School Labor Nonagricultural 0.4Expectancy 13 84 7 -2 — 0.4 8.7 2.2 —Gender 21 14 —Force — 98 54 — of Parliament — 81 81 Life 78 — — — —0.4 — — — at Birth 100,000 Births HIV/AIDS Enrollment Ratio Parity Rates Wage Earners1,092 Members 28 65 9 13.6 16.9 42 3.2 —Index35 Participation 4 0.86 1,750 59 — 31 64 64 10.9 61 (years) 670 380 -3 0.5 0.8 — — 3 35 Both Males Females 18 78 7 2.9 2.7 2179 2.32.29 24 9 0.79 8,490 52 48 2,268 68 74 74 2.7 70 98 80 -5Males 0.8 Females 0.6 76 17 73 Sexes Females 1990 2013 2014 2008/2014 2008/2014 2008/2014 2008/2013 2015 11 0.4 8 1.9 — 19 17 2013 89 51 — — 82 82 0.4Males 79 85 —8 — -102014 — — —0.4 — — — — — 71 269 136 — 78 76 20 10 73 3.5 3.4 7.2 1.51.03 17 0.6623,960 99 34 5,806 72 79 79 3.5 69 76 83 —8 — -15 — 83 1.43 18 46 — 84 79 15 1 — — 104 104 23 14 82 8 0.05 0.06 13 1.81.27 8 0.79 32 48 921 — 75 75 0.0576 73 78 —25 — 93 110 2.09 21 — 21,990 — 14 — 69 338 159 74 19 12 72 6 0.2 0.2 1871 1.50.99 9 0.63 15 28 5,855 52 79 79 0.2 68 75 83 60 34 0 — — 88 88 2.00 22 0.8210,230 — 21 56 68 443 200 0.4 0.7 69 66 17 17 70 8 0.1 0.1 20 2.00.94 6 0.56 51 28 2,204 — 71 71 0.1 66 70 74 48 45 -8 — — 105 101 — 25 0.7110,610 — 13 — 62 900 384 0.5 0.8 46 40 22 14 63 8 1.3 1.2 13 1.70.66 9 0.79 15 27 5,375 38 75 75 1.4 60 71 78 89 84 -1 — — — — — 21 0.7026,220 46 25 43 60 58 61 801 412 0.9 464 1.5 54 49 0.73 30 21 75 414 72 17 78 6 496 1898 2.0 — 26 8 0.71 14,850 84 45 309 69 75 75 126 78 -0 0.2 0.1 93 18 57 964 488 1.9 49 42 — 24 21 18 59 8 49.4 58.4 10.8 2.21.57 11 0.84 93 35 108 53 77 77 42.4 56 73 80 71 69 0 1.1 0.2 0.1 103 112 0.63 — 42 37 55 71 242 118 <0.1 78 — 26 72 7 13.0 15.8 3975 3.21.09 6 0.32 69 20 242 34 67 67 10.5 69 65 69 510 200 -1<0.1 0.2 0.1 80 80 — 31 0.79 6,130 37 52 61 74204.5 71 72 77 160 89 0<0.1 <0.1 96 100 0.2115,900 18 26 80 15 79 6 223.1 226.3 19 1.81.51 7 0.74 86 47 281 77 75 75 120 69 — — — — — 24 11 71 18.0 76 70 73 120 45 2<0.1 90 88 0.89 21 0.3221,570 19 — 14 81 6 19.6 20.2 7.4 1.81.11 10 0.66 90 39 1,347 — 79 79 55 22 0.2 <0.1 99 100 16 61 71 48.2 72 69 74 31 15 -1 — — — — — 27 0.3912,600 16 19 79 6 53.2 54.9 16 1.91.14 7 0.70 76 — 3,104 73 75 75 100 83 0.2 0.1 89 97 46 21 79 74 310 120 <0.1 74 63 11 21 75 5 19.8 23.4 17 2.60.89 7 0.35 70 22 1,425 59 75 75 16.3 73 72 78 160 87 0<0.1 0.2 101 106 1.31 31 0.6611,120 38 42 73 62 720 360 0.1 0.2 43 — — 26 64 3 5 — 0.4 0.6 939 3.51.12 5 0.41 77 — — — 80 80 0.3 60 77 83 — — — — — — 34 — — 46 76 91 46 -7<0.1 <0.1 89 93 28 31 34 21 78 7 0.8 0.7 32 2.61.62 6 0.35 29 — 180 33 66 66 0.7 74 64 69 210 250 0.7 1.2 94 109 2.14 27 0.53 6,930 68 — — — — — — 33 — 8,010 — 23 70 6 -1 — 8.5 10.1 29 2.81.40 5 0.66 64 — 159 70 72 72 7.0 66 70 74 130 110 0.3 0.2 73 78 44 17 79 55 1,053 539 1.0 47 — 29 10 20 56 5 35.9 40.1 1740 2.51.09 6 0.76 79 — 761 52 75 75 31.2 54 72 78 250 89 -1 0.6 0.1 0.1 95 93 0.8111,510 37 22 75 59 600 340 0.4 65 7 48 18 61 7 0.7 0.7 1743 2.30.27 6 0.86 71 26 923 47 71 71 0.6 58 68 74 84 130 -2 0.2 0.3 0.5 66 86 — 28 0.5915,960 36 12 56 770 400 0.5 31 26 13 14 57 10 3.7 3.8 8.9 1.90.49 14 0.86 93 — 204 75 77 77 3.6 56 73 80 42 14 -1 0.4 0.1 85 96 1.73 21 0.7220,220 49 12 77 75 30.6 71 230 53 0 0.8 0.3 89 103 21 20 80 5 36.1 40.5 13.3 2.51.46 6 0.62 94 — 1,120 62 75 72 78 93 110 0.2 0.2 97 1.69 28 0.6517,140 44 17 70 51 50 52 740 720 -0 — 0.9 4,939 1.4 46 32 0.62 25 0.64 21 9 66 4,397 18 74 7 5,324 3377 2.21.01 8 0.60 11,450 47 25 938 60 72 72 70 272 108 — 78 18 59 58 60 710 430 -0 — 0.4 3,507 0.7 59 56 — 28 0.87 — 9 57 3,017 21 72 7 3,949 3870 2.40.95 6 0.48 10,480 44 25 832 48 70 70 68 382 145 — 73 15 61257 71 60 63 760 380 0.4 321 0.6 69 65 0.63 30 0.94 32 11 54 22 76 5 387 2285 2.91.00 5 0.39 25,130 71 22 705 37 74 74 89 54 3 — — 89 16 60 1,100 650 0.7 47 22 14 61 9 2.9 2.5 929 1.50.44 11 0.84 63 18 675 26 75 75 3.0 58 72 78 47 29 -6 0.4 0.2 <0.1 91 104 1.51 19 0.75 8,550 44 11 55 54 930 560 1.5 — — — 22 14 18 56 6 11.0 12.1 11 2.21.05 6 0.87 53 — 510 13 74 74 9.7 53 72 77 60 26 0 0.8 0.1 <0.1 101 100 0.9016,910 43 16 51 60 1.4 75 59 61 1,200 640 0.3 0.4 42 33 0.63 21 0.9038,140 24 88,490 11 62 15 76 2 1.7 1.9 899 2.12.18 2 0.45 100 21 31 76 76 21 22 5 — — 104 15 53 1.2 78 53 53 1,100 550 0.5 0.7 50 40 0.43 17 0.6229,800 9 — 12 82 6 1.3 1.4 596 1.41.18 12 0.79 67 — 1,260 — 80 80 18 10 -12 — — 94 52 13 63 630 320 0.4 30 29 22 14 64 12 4.9 4.7 10 1.70.44 14 0.36 54 — 944 35 75 75 3.8 62 71 79 50 41 -2 0.2 0.3 <0.1 100 101 1.26 17 0.75 7,510 47 11 53 60 1,000 630 0.2 22 15 13 31 61 4 53.4 76.5 37 4.20.34 3 0.45 71 36 1,080 33 69 69 37.1 59 67 71 110 67 2<0.1 — — — — — 41 0.2114,670 12 27 53 52 1,200 560 0.7 1.3 46 41 — 28 5 — 21 53 5 10.6 13.9 3.0 3.31.34 11 0.76 91 — 2,846 — 82 82 8.4 52 80 84 12 2 1 — — 101 103 0.8432,550 51 24 65 530 320 0.1 0.1 43 43 28 67 6 9.0 11.4 1739 3.50.59 3 0.75 83 27 3,810 42 74 74 8.1 63 73 77 86 50 3 — — 87 89 1.15 37 0.2311,910 16 12 61 50 2,300 0.2 0.4 48 — 23 12 17 51 2 1,100 5.0 6.1 842 2.32.24 2 0.95 98 — 39 74 74 3.8 50 73 76 12 14 22 — — — — 0.5287,700 — 35,893 2 52 57 660 450 0.5 0.8 — — 18 15 57 5 5.5 5.6 875 1.70.39 6 0.99 87 — 2,993 34 77 77 6.2 56 76 79 64 16 31<0.1 <0.1 75 1.09 26 0.3317,330 — 3 58 61 1,034 440 1.3 1.9 41 — 22 28 21 63 3 5.2 5.7 1038 2.91.45 3 0.92 75 36 15 77 77 4.2 59 75 79 48 11 45<0.1 <0.1 85 99 0.3536,240 — 13,574 10 24 59 1,300 740 0.3 0.4 37 35 57 32 61 -2 — 6.6 9.2 1829 4.10.42 3 1.02 83 — 9,925 44 73 73 4.5 57 72 75 —4 — — 79 86 1.50 40 — 5,080 16 — 61 630 350 — 63 3 12 62 1 2.8 3.0 765 2.00.86 1 0.44 133850 100 — 34 78 78 2.4 60 78 79 11 6 28 — — — 107 117 6.66 15 0.53 13 18,750 0 38 62 400 230 0.5 0.8 53 43 13 20 63 4 39.0 47.1 16 2.90.68 3 0.54 81 — 979 — 74 74 31.6 60 73 75 41 16 5 — — 127 120 1.04 30 0.2653,760 14 20 24 63 1,700 380 0.2 0.3 — — 22 23 65 7 26.1 31.2 16 2.80.50 4 0.89 54 — 366 38 70 70 17.1 60 64 76 130 49 -26<0.1 <0.1 48 48 1.01 33 0.19 — 16 12 54 64 1,400 420 0.5 0.6 — — — 24 26 17 65 5 88.4 93.5 11 2.20.86 8 0.88 77 39 381 47 77 77 78.2 62 75 79 48 20 3 — — 104 101 0.4219,040 26 14 74 62 9.6 76 60 65 490 400 — — 69 0.8663,750 36 19,093 21 28 14 78 1 12.3 15.5 665 1.80.70 1 0.51 83 20 24 77 77 16 8 8 — — — — — 16 18 65 26.7 62 64 66 740 440 1<0.1 0.2 0.1 39 38 0.94 41 0.96 3,820 37 21 33 67 7 35.7 46.1 4340 4.40.44 3 0.35 34 12 2,110 29 65 65 460 270 <0.1 58 0 34 61 60 62 1,100 510 -1 — 2.4 2,227 4.1 38 35 0.65 30 1.046,010 — 17 54 1,903 22 70 7 2,526 4565 2.50.91 5 0.38 34 19 776 46 68 68 66 507 174 — 69 14 74 69 65 71 78 70 73 -1<0.1 0.2 0.2 94 98 1.22 29 0.599,930 38 12 54 25 72 6 82 96 3797 2.90.87 5 0.71 47 — 219 50 69 69 76 40 <0.1 100 18 79 17.5 66 76 83 —91 — — — — — — 25 — 21,580 — 25 75 8 20.7 24.6 25 3.01.30 7 0.87 53 — 76 50 70 70 26 0<0.1 <0.1 100 101 51 20 51 54 6.0 66 52 56 1,300 480 — — 27 25 0.69 32 1.03 3,220 40 42 27 74 6 8.2 11.6 2488 4.01.61 4 0.70 36 — 463 40 70 70 85 75 -1<0.1 <0.1 88 42 23 80 8.5 64 77 84 —68 — — — — — 36 — 2,630 — 33 71 7 11.2 14.8 40 3.80.61 3 0.76 27 — 990 26 67 67 44 -3 — 0.1 0.1 92 82 29 15 28 65 5.4 61 63 66 1,400 320 1.0 1.3 31 34 0.75 28 1.0114,520 34 58 48 21 70 8 6.2 6.6 4684 2.30.64 4 0.61 50 — 279 46 65 65 66 61 -1 — — 87 26 73 31.3 65 69 78 —66 — — — 69 75 2.20 28 — 5,840 53 44 65 23 72 5 36.0 38.3 44 2.40.65 4 0.64 51 — 721 59 68 68 36 -1<0.1 <0.1 106 104 16 55 53 57 1,300 850 -1 — 0.2 2,145 0.2 — — — 30 0.495,870 — 14 54 1,834 22 70 7 2,430 45 2.50.91 5 0.37 33 19 857 46 68 68 66 525 179 — 68 64 14 55 32.2 60 54 56 1,800 730 2<0.1 0.7 1.3 — — — 45 — 1,980 24 21 34 62 8 45.8 64.3 74 4.90.33 2 0.20 25 — 415 20 61 61 1,200 400 <0.1 70 38 18 25 62160.4 70 60 63 910 410 -3<0.1 1.4 185.1 2.1 34 32 0.54 33 0.98 3,340 33 36 62 20 71 6 201.9 3857 2.30.72 5 0.68 23 18 2,089 54 71 71 550 170 <0.1 50 20 See notes on page 21 2015 WORLD POPULATION DATA SHEET 18 59 0.8 68 58 60 780 360 2 — 2.3 3.7 29 25 0.78 31 0.96 7,560 35 35 18 69 7 0.9 1.1 4780 2.20.74 5 0.86 38 26 764 65 68 68 900 120 — 75 8 66 53 51 56 580 280 3.3 4.2 — — — 0.85 — 13 1,314.1 21 69 7 1,660.1 4269 2.30.92 29 5 0.34 5,760 32 19 842 47 68 68 66 560 190 -1 — 1,512.9 — 73 12 54

73 77 75 72 70 74 78 61 70 79 76 73 75 70 71 72 73 65 71 76 72 72 77 64 70 72 68 73 72 70 68 71 72 72 75 78 71 67 80 73 73 76 75 72 78 73 64 75 76 62 66 65 66 66 64 61 65 66 60 70 68 66

3,820 6,010 9,930 21,580 3,220 2,630 14,520 GNI per 5,840 Capita ($US) 5,870 c 2014 1,980 15,030 3,340 39,020 7,560 9,870 5,760 8,740 16,080 2,270 12,770 4,720 2,420 3,480 5,100 9,740 10,270 13,540 10,720 11,020 71,020 16,190 3,080 7,180 10,250 3,980 4,910 10,600 23,850 — 4,040 8,300 1,850 80,270 1,660 13,950 6,320 5,680 3,350 5,350 1,580 16,040 3,960 13,130 1,140 56,570 1,430 118460 820 37,920 1,660 — 3,700 34,620 950 11,230 5,680 — 2,290 31,650 1,830 36,280 1,310 40,340 1,930 — 790 46,160 1,530 25,690 — 40,000 1,180 42,530 1,500 40,820 2,890 23,150 1,400 25,390 780 65,970 18,290 46,710 — 38,370 1,170 44,790 — 45,040 1,530 43,030 24,630 39,720 — 46,840 2,030 — 2,530 57,830 1,690 — 3,860 47,660

34Yemen 2,110 34 29 SOUTH CENTRAL ASIA54 34 776 46 CENTRAL 219 ASIA 47 54 50 53Kazakhstan76 51 50 36Kyrgyzstan463 42 40 Percent 27Tajikistan 990 28 of Married 26 Women Using 50Turkmenistan 279 48 15-49 46 Population d Contraception 51Uzbekistan 721 65 59 per Square

Percent All Modern SOUTH Kilometer ASIA 33 857 54 46 Urban of Arable Methods 25Afghanistan 415Land Methods 21 20 53 523 62 56 23Bangladesh 2,089 54 77 67 59 38Bhutan 238 764 66 65 48 696 61 55 32India 842 54 47 46 612 54 46 71Iran 442 82 60 29 521 37 32 45Maldives 11,565 35 27 40 487 35 29 18Nepal 1,322 50 47 38Pakistan 484 30 25 939 35 26 51 500 51 46 18Sri Lanka1,672 68 53 73 524ASIA 56 48 SOUTHEAST 47 906 62 54 43Brunei 9,796 3,196 59 57 77 — — 78Cambodia376 359 42 20 21 56 39 60 425 67 57 54Indonesia 1,086 62 58 33 193 12 12 38Laos 475 50 42 68 388 63 50 74Malaysia3,231 49 32 82 — — — 34Myanmar 481 46 46 45 402 16 12 44Philippines 1,857 55 38 45Singapore 393 18 13 100 879,543 62 55 27Thailand 393 308 18 18 49 79 77 62Timor-Leste 1,090 61 57 32 775 22 21 50Viet Nam 805 18 13 33 1,436 76 57 57 459 9 8 EAST ASIA 59 1,380 82 81 51China 1,293 588 27 22 55 85 84 f6 36China,231,314 366Kong SAR80 5 Hong 100 75 49China, Macao 594 16 14 100 — SARf — — 47 899 20 19 93Japan 3,000 54 44 39 245 10 10 61Korea, North 1,064 71 65 59 883 11 10 82Korea, South 3,339 80 70 22 14 12 68Mongolia 118 487 55 50 50 15 10 73Taiwan 520 — 71 — 45 439 22 20 EUROPE 269 73 70 61 41 375 17 16 EUROPEAN UNION 72 73 470 64 38 273 20 17 NORTHERN EUROPE 81 79 522 78 24 560 41 35 Islands 31Channel3,819 — — 10Denmark 235 977 22 18 87 — — 28Estonia 212 868 19 14 68 63 58 77Finland38,827 19 18 85 244 77 75 21Iceland 275 981 7 95 —8 — 17Ireland 395 641 42 40 60 65 61 24 794 58 53 68Latvia 168 68 56 33 40 33 67Lithuania 660 129 63 50 16 59 57 80Norway 458 646 88 82 41 76 39 84Sweden1,663 376 75 65 50 — — — 80United Kingdom 1,047 84 84 31 455 12 11 WESTERN566 EUROPE 71 77 68 94Austria 638 — 67 64 67 70 68 28Belgium1,397 959 53 48 99 70 69 54France 9,173 — — 78 352 76 74 38Germany 685 985 15 1 73 66 62 17Liechtenstein — 1 15 1,249 —4 — 30Luxembourg 360 34 26 90 908 — — © 2015 Population 18 582 27Bureau 26 Monaco 100 — Reference — — 40Netherlands 408 49 45 90 1,675 69 67

33 67 7 35.7 46.1 4340 4.40.44 41 3 0.35 3,820 34 12 2,110 29 65 65 26.7 62 460 270 1<0.1 <0.1 58 0 34 1,903 22 70 7 2,526 4565 2.50.91 30 5 0.386,010 34 19 776 46 68 68 66 507 174 -1 — 2,227 — 69 14 54 25 72 6 82 96 3797 2.90.87 29 5 0.719,930 47 — 219 50 69 69 69 65 76 40 -1<0.1 <0.1 100 18 54 25HEALTH, 8 20.7 24.6ESTIMATES 25 3.01.30 7 0.8721,580 53 51 OF 76 50 70 70 17.5 66 75 91 26 0<0.1 <0.1 100 101 FOR 20 51 POPULATION, AND ENVIRONMENT DATA AND THE 25 COUNTRIES AND REGIONS THE WORLD 27 74 6 8.2 11.6 2488 4.01.61 32 4 0.70 3,220 36 42 463 40 70 70 6.0 66 85 75 -1<0.1 <0.1 88 23 42 Maternal Tertiary Ratio of Female Share of 990Female 33 71 7 11.2 14.8 4082 3.8 3 0.76 2,630 27 29 28 26 67 67 8.5 64 68 44 -3 Percent 0.1 Ages 0.1 92 0.61 36 Gender 15Share Deaths per61 -1 — 15-24 With Secondary School School Gender Labor Force 5.4Expectancy 21 70 8 6.2 6.6 4684 2.30.64 28 4 0.61 14,520 Nonagricultural 50 — 279of Parliament 46 65 65 Life 61 66 — 87 26 48 at Birth 100,000 Births HIV/AIDS Enrollment Ratio Parity Index28 Participation Rates Wage Earners 721 Members 23 72 5 36.0 38.3 44 2.40.65 4 0.64 5,840 51 — 59 68 68 31.3 65 (years) 66 36 -1<0.1 <0.1 106 104 16 65 Both Females Males Females 1,834 22 70 7 2,430 4564 2.50.91 30 5 0.375,870 33 19 857 46 68 68 66 525 179 -1Males — 2,145 — 68 14 54 Sexes Females 1990 2013 2014 2008/2014 2008/2014 2008/2014 2008/2013 60 62 34 8 45.8 64.3 7438 4.90.33 45 2 2013 25 18 415 2015 20 61 61 32.2Males 1,200 400 22014 <0.1 <0.1 70 0.20 1,980 25 21 71160.4 69 269 136 — — 78 20 62 20 73 6 185.1 201.9 3876 2.31.03 5 0.66 23 34 2,089 54 71 70 71 550 170 -3<0.1 <0.1 50 57 0.72 33 0.68 3,340 18 79 25 15 2 — — 104 104 23 18 82 7 0.9 1.1 47 2.21.27 5 0.79 38 48 764 65 68 68 0.8 76 68 69 900 120 75 80 0.74 31 0.86 7,560 26 8 66 69 68 338 159 — 74 19 1,314.1 21 72 7 1,660.1 4271 2.30.99 5 0.63 32 28 842 47 68 68 66 69 560 190 -1 — 1,512.9 73 69 0.92 29 0.34 5,760 19 12 54 68 443 200 0.4 0.7 69 17 19 70 5 90.2 99.3 1566 1.80.94 24 5 0.56 71 28 442 60 74 74 78.5 66 72 76 83 23 -1<0.1 <0.1 89 83 0.2316,080 15 3 82 62 900 384 0.5 0.8 46 22 22 63 3 0.4 0.6 940 2.20.66 5 0.79 45 27 27 74 74 0.3 60 73 75 430 31 0 — — — — 1.13 26 0.7312,770 41 11,565 6 35 60 801 412 0.9 1.5 54 — 33 21 22 61 7 32.4 36.0 3349 2.40.81 6 0.73 18 30 1,322 47 67 67 28.0 58 66 69 790 190 -1<0.1 <0.1 65 69 0.92 2,420 — 30 50 57 964 488 1.1 254.7 1.9 49 — 36 21 30 59 7 344.0 6942 3.80.98 4 0.84 38 35 939 26 66 66199.0 56 66 67 400 170 -2<0.1 <0.1 44 32 0.30 5,100 13 20 35 71 242 118 <0.1 78 —6 68 18 72 6 22.5 23.0 975 2.31.09 8 0.32 18 20 1,672 53 74 74 20.9 69 71 77 49 29 -4<0.1 96 102 1.60 25 0.4610,270 32 74 72 77 160 89 -0 <0.1 <0.1 96 100 1.51 27 0.21 18 26 62 628 68 20 73 7 839 28 2.41.09 6 0.72 10,720 47 39 906 54 71 71 306 131 0.3 737 0.3 78 78 17 71 0.4 77 70 73 120 45 1 <0.1 <0.1 90 0.89 25 0.3271,020 19 17 80 3 0.5 0.5 488 1.61.82 5 0.70 77 — 9,796 — 79 79 26 27 — — 105 107 — — 71 15.4 61 69 31 15 -2 — — — — — 31 16 24 74 6 18.1 21.3 28 2.70.61 6 0.39 21 — 376 39 64 64 66 1,200 170 0.1 0.2 49 41 0.91 3,080 41 19 56 74 310 120 <0.1 74 11 21 75 6 366.5 3163 2.60.89 5 0.35 54 22 1,086 58 71 71255.7 73 69 73 430 190 -1<0.1 0.4 307.6 0.4 84 82 1.03 29 0.6110,250 35 17 62 62 720 360 0.2 43 — 27 64 6 8.8 10.6 6839 3.11.12 4 0.41 38 — 475 42 68 68 6.9 60 67 70 1,100 220 -3 0.1 53 48 0.88 37 0.96 4,910 35 25 50 76 91 46 <0.1 89 31 17 78 5 36.0 42.3 793 2.01.62 6 0.35 74 28 3,231 32 75 75 30.8 74 73 77 56 29 3<0.1 0.1 73 69 1.21 26 0.5923,850 39 14 49 68 — — — — — — 24 — — —5 46 19 70 9 -1 — 56.5 56.5 62 2.31.23 5 0.91 34 — 481 46 65 65 52.1 66 63 67 580 200 0.4 0.3 49 51 55 1,053 539 0.6 127.8 1.0 47 — 34 10 23 56 6 157.1 2340 2.91.26 4 0.76 44 — 1,857 38 69 69103.0 54 65 72 110 120 -1<0.1 <0.1 83 88 0.64 8,300 42 27 55 59 5.5 80 58 61 600 340 0.2 0.4 65 43 0.8680,270 26 879,543 7 62 10 85 58 6.5 7.0 1.8 1.30.27 11 0.76 100 47 55 83 83 6 14 — — — — — 16 25 56 65.1 72 56 57 770 400 0.4 0.5 31 26 0.49 18 0.8613,950 13 12 78 8 69.8 66.1 1189 1.61.34 11 0.80 49 — 393 77 75 75 42 26 0 0.3 0.2 83 45 6 79 75 1.2 66 71 80 230 53 -9 — 0.8 0.3 89 103 1.46 42 0.62 5,680 21 22 36 69 8 1.8 2.8 45 5.70.73 5 0.48 32 — 775 21 68 68 1,200 270 — 56 57 23 38 51 91.7 71 50 52 740 720 0.9 103.2 1.4 46 32 0.62 24 0.64 5,350 21 9 76 17 76 7 108.2 16 2.40.90 7 0.89 33 41 1,436 57 73 73 140 49 0 0.3 0.2 — — 24 59 58 60 710 430 0.4 1,654 0.7 59 56 — 17 0.87 9 82 1,609 12 79 7 1,572 1195 1.61.13 12 0.81 16,040 59 — 1,380 81 76 76 74 87 31 0 — — 92 23 61 60 63 760 380 0.4 1,422.5 0.6 69 65 0.63 17 0.9413,130 32 11 85 1,371.9 12 78 7 1,365.7 1294 1.71.15 10 0.82 55 — 1,293 84 75 75 73 97 32 -0 — — 91 24 60 7.3 81 58 61 1,100 650 0.4 0.7 47 29 0.44 11 0.8456,570 18 231,314 22 80 9 87 3 — 8.1 8.6 1.6 1.21.13 15 0.76 100 50 75 84 84 —6 — — 101 98 — 54 0.7 80 53 56 930 560 0.8 1.5 — — — 11 0.87 — 14 — 12 86 3 0.7 0.8 395 1.21.28 8 0.85 118460 100 48 — — 83 83 — — 11 — — 97 — 60 1,200 640 0.3 116.6 0.4 42 33 11 8 61 10 96.9 2.1 1.40.63 26 0.90 93 24 3,000 44 83 83126.9 59 80 87 14 6 1 — — 102 102 0.90 13 0.6937,920 43 12 54 53 1,100 550 0.5 0.7 50 40 9 71 14 53 9 26.7 27.0 25 2.00.43 10 0.62 61 — 1,064 65 70 70 25.0 53 66 74 85 87 0 — — — — — 22 0.86 — 16 63 630 320 0.2 0.4 30 29 22 9 64 5 52.2 48.1 3.0 1.20.44 13 0.36 82 — 3,339 70 82 82 50.7 62 79 85 18 27 3 — — 100 98 0.75 14 0.6934,620 43 16 80 60 1,000 630 0.2 22 13 28 61 6 3.7 4.4 2115 3.10.34 4 0.45 68 36 487 50 69 69 3.0 59 65 75 100 68 -1<0.1 — — 88 95 1.42 27 0.8211,230 50 15 55 52 1,200 560 0.7 1.3 46 41 9 53 1 — 23.4 20.4 3.9 1.2 — 14 12 0.76 73 — — — 80 80 23.5 52 77 83 —7 — — — — — — —5 71 65 63 67 530 320 0.1 744 0.1 43 0.59 16 0.75 27 43 70 742 74 11 81 11 728 639 1.41.26 17 0.79 31,650 73 48 269 61 78 78 33 12 2 — — 109 108 25 50 50 51 2,300 0.2 520 0.4 48 — 16 0.95 — 12 72 510 78 10 83 10 518 442 1.61.27 19 0.79 36,280 73 48 470 64 81 81 20 1,100 8 2 — — 113 114 29 57 56 57 660 450 0.5 112 0.8 — — 0.39 18 0.99 — 18 81 103 78 12 83 9 120 4 1.81.37 17 0.83 40,340 79 50 522 78 81 81 12 7 4 — — 125 130 28 61 1,034 440 1.3 1.9 41 38 28 10 63 3 — 0.2 0.2 2.9 1.7 — 16 16 0.92 31 36 3,819 — 82 82 0.2 59 80 85 —7 — — — — — — — — — 59 5.7 79 57 61 1,300 740 0.3 0.4 37 0.42 17 1.0246,160 35 — 10 83 99 6.0 6.3 429 1.71.38 19 0.88 87 — 235 — 81 81 5 7 <0.1 <0.1 130 133 50 38 61 1.3 73 60 62 630 350 63 65 0.86 16 0.4425,690 3 63 10 81 12 1.3 1.2 2.8 1.51.48 19 0.82 68 — 212 58 77 77 48 11 -1 — — 105 104 52 24 62 5.5 78 60 63 400 230 0.5 0.8 53 43 0.68 16 0.5440,000 13 77 10 84 106 5.8 6.1 2.2 1.71.21 20 0.87 85 — 244 75 81 81 4 3 — — 137 150 52 42 63 0.3 81 60 65 1,700 380 0.2 0.3 —0.4 — 0.50 20 0.8942,530 22 — 13 84 67 0.4 1.7 1.91.72 14 0.91 95 — 275 — 82 82 4 3 — — 113 111 51 41 64 4.6 79 62 65 1,400 420 0.5 0.6 —5.8 — — 22 0.8840,820 26 15 83 66 5.2 3.7 2.01.03 13 0.78 60 39 395 61 81 81 9 -5 0.1 <0.1 118 120 52 20 65 62 490 400 — 69 65 21 11 65 14 1.6 1.4 3.5 1.60.70 19 0.86 68 36 168 56 74 74 2.0 60 70 79 57 13 -4 — 109 105 1.49 15 0.8123,150 53 18 68 65 740 440 0.2 0.1 39 38 21 11 66 14 2.7 2.4 3.8 1.70.94 18 0.96 67 37 129 50 74 74 2.9 64 69 79 34 11 -4 — — 111 105 1.45 15 0.8325,390 53 23 63 61 1,100 510 2.4 4.1 38 35 17 12 62 89 5.9 6.7 2.4 1.80.65 16 1.04 80 — 646 82 82 82 5.2 60 80 84 4 7 <0.1 <0.1 115 111 1.50 18 0.8965,970 49 40 88 74 70 73 0.2 0.2 94 98 12 12 78 96 11.4 12.4 2.2 1.91.22 20 0.59 84 38 376 65 82 82 9.8 71 80 84 4 8 <0.1 <0.1 121 137 1.56 17 0.8946,710 50 44 75 79 —10 —8 4 — — — — — 18 — 38,370 — 12 83 9 71.0 77.0 3.9 1.91.35 17 0.81 80 — 1,047 84 81 81 65.1 76 79 126 132 49 24 84 54191 79 52 56 1,300 480 — 27 0.69 16 1.03 — 40 71 10 84 10 198 199 325 1.71.10 19 0.82 44,790 77 49 566 68 81 81 12 7 4 — 111 110 33 80 8.6 78 77 —10 —4 6 — —9.5 — — 14 — 45,040 — 10 84 9 9.2 397 1.51.20 18 0.81 67 — 638 68 81 81 — 101 48 30 70 65 11.2 78 63 66 1,400 320 1.0 1.3 31 34 0.75 17 1.0143,030 34 58 70 11 83 10 12.3 13.1 3.8 1.81.30 18 0.80 99 48 1,397 69 80 80 10 6 5 — — 155 176 42 73 64.3 79 69 78 —12 —9 0 — 69 75 2.20 19 — 39,720 53 44 76 12 85 8 68.5 72.3 3.5 2.01.25 18 0.82 78 50 352 74 82 82 — 108 110 26 55 81.1 78 53 57 1,300 850 0.2 0.2 — — — 13 0.4946,840 14 66 8 83 11 81.1 76.4 3.3 1.50.93 21 0.81 73 — 685 62 80 80 13 7 5 — — 104 98 48 37 55 0.0481 54 56 1,800 730 0.7 1.3 —0.05 — — 15 24 — 9 84 4 — 0.04 3.3 1.50.55 16 — — 15 — 1,249 — 82 82 —7 — — 119 101 44 20 62 0.6 80 60 63 910 410 1.4 2.1 34 32 0.54 17 0.9857,830 33 36 — 11 84 76 0.7 0.7 3.1 1.51.13 14 0.78 90 45 908 — 82 82 11 19 — — 98 102 28 See notes on— page POPULATION DATA 59 0.04— 58 60 780 360 2.3 3.7 29 25 352015 WORLD 35 — 6 — 7 0.04 0.05 21 —— 1.40.78 24 0.96 100 — — — SHEET— 19 — — — 13 — — — 13 — — 21 53 16.9 51 580 280 3.3 4.2 — — — 17 13 10 56 9 17.6 17.9 3.8 1.71.10 17 0.85 90 — 1,675 67 81 81 79 83 11 6 2 — — 131 130 0.8347,660 49 37 69

62 66 65 66 66 64 61 65 66 60 70 68 66 72 73 66 66 71 68 77 61 69 67 73 63 65 80 72 66 71 74 73 81 80 80 66 79 65 77 74 78 78 80 79 73 78 81 79 70 69 80 80 79 79 78 78 79 78 81 80 — 79

25,390 65,970 46,710 38,370 44,790 45,040 43,030 GNI per 39,720 Capita ($US) 46,840 c 2014 — 15,030 57,830 39,020 — 9,870 47,660 8,740 59,600 2,270 21,130 4,720 17,610 3,480 15,850 9,740 26,970 13,540 23,830 11,020 5,480 16,190 24,090 7,180 19,030 3,980 24,710 10,600 25,970 — 8,560 4,040 29,730 1,850 10,260 1,660 — 6,320 10,020 3,350 20,560 1,580 26,130 3,960 34,710 1,140 9,410 1,430 12,600 820 27,020 1,660 14,510 3,700 28,010 950 — 5,680 12,150 2,290 28,650 1,830 32,860 1,310 31,600 1,930 42,880 790 3,680 1,530 8,030 — 1,180 — 1,500 2,580 2,890 4,630 1,400 — 780 — 18,290 33,760 — 14,280 1,170 2,510 — 5,600 1,530 2,020 24,630 5,300 — 5,260 2,030 2,870 2,530 GNI per 1,690 Capita 3,860 ($US) c

67Lithuania 129 63 50 80Norway 646 88 82 84Sweden 376 75 65 80United Kingdom 1,047 84 84 77 WESTERN566 EUROPE 71 68 Percent 67Austria 638 70 of Married 68 Women Using 99Belgium 1,397 70 15-49 69 Population d Contraception 78Franceper 352 76 74 Square Percent Kilometer All Modern 73Germany 685 66 62 Urban of Arable Methods 15Liechtenstein 1,249Land Methods — — 53 523 62 56 90Luxembourg 908 — — 77Monaco 238 67 59 100 — — — 48 696 61 55 90Netherlands 1,675 69 67 46 612 54 46 74Switzerland 2,057 82 78 29 37 32 69 EASTERN 521 153 EUROPE 69 57 40 35 29 76Belarus 487 173 63 51 38 30 25 73Bulgaria 484 216 69 40 51 500 51 46 74Czech Republic 334 86 78 73 56 48 69Hungary 524 224 81 71 43Moldova3,196 59 57 42 227 60 42 78Poland 352 359 42 20 60 — — 60 67 57 54Romania 425 226 70 51 33Russiag 121 193 12 12 74 68 55 68Slovakia 389 388 63 50 54 80 66 82Ukraineg 132 — — — 69 68 61 45 402 16 12 68 SOUTHERN 517 EUROPE 66 48 45 18 13 56Albania 393 467 69 10 27 308 18 18 86Andorra3,254 — — 62 1,090 61 57 40Bosnia-Herzegovina 363 46 12 50 18 13 56Croatia 805 468 — — 57 9 8 78Greece 459 454 76 46 51 588 27 22 68Italy 878 63 41 36Kosovoh 366 6 5 38 — 66 14 i 49Macedonia 594 16 14 57 500 40 27 47 899 20 19 95Malta 4,799 86 46 39 245 10 10 64Montenegro 362 23 15 59 11 10 61Portugal 883 950 87 83 22 118 14 12 94San Marino 3,293 — — 50 520 15 10 60Serbia 216 58 18 45 439 22 20 50Slovenia1,206 79 63 41 375 17 16 77Spain 373 66 62 38 20 17 70 OCEANIA 273 82 62 58 24 41 35 89Australia 560 51 72 68 10 977 22 18 22Federated 5,074 States of Micronesia — 70 28 868 19 14 51Fiji 527 29 — 77 19 18 56French38,827 10,265 Polynesia — — 21Guam 17,953 981 8 7 93 67 58 17Kiribati 5,600 641 42 40 54 22 18 24 794 58 53 74Marshall2,753 Islands 45 42 33Nauru 660 40 33 100 — 36 23 16 458 59 57 70New Caledonia 4,959 — — 41 1,663 76 39 86New Zealand 794 75 72 50 — — — 84Palau 1,779 33 30 31Papua New 455 12 11 13 2,443 Guinea 32 24 94Samoa 2,451 — 67 64 19 29 27 28Solomon3,276 959 53 48 20 Islands 35 27 54Tonga 9,173 — — 23 646 34 28 38Tuvalu 985 15 1 59 — 31 22 17Vanuatu1,423 — 4 1 24 49 36 30 360 34 26 Percent Population All Modern © 2015 Population 18 27BureauMethods 26 Urban per 582 SquareReference Methods 40 408 49 45 Kilometer Percent of Married

74 2.9 69 11 79 14 34 11 -4 — — 2.7 111 2.4 105 3.8 1.71.45 15 18 0.8325,390 82 5.2 80 12 84 89 4 7 <0.1 <0.1 5.9 115 6.7 111 2.4 1.81.50 18 16 0.8965,970 82 9.8 80 12 84 96 4 8 <0.1 <0.1 11.4 121 12.4 137 2.2 1.91.56 17 20 0.8946,710 81 65.1 79 12HEALTH, 83 10 9 8 4 — 71.0 — 126 77.0ESTIMATES 132 3.9 FOR 1.91.35 17 0.8138,370 POPULATION, AND ENVIRONMENT DATA AND THE 18 COUNTRIES AND 81 191 79 10 84 10 12 7 4 — 198 — 199 111 110 3 1.71.10 16 19 0.82 44,790 Maternal Ages Tertiary Ratio of 81 8.6 78 10 84 10 9 4 6 Percent — — 9.2 101 9.5 397 1.5 1.20 14 Gender 18 0.81 45,040 Life Expectancy Deaths 15-24 With Secondary School School Gender Labor Force 80 11.2 78 11 83 10 10 per 6 5 — 12.3 — 155 13.1 176 3.8 1.81.30 17 18 0.80 43,030 at Birth 100,000 Births Enrollment Ratio Parity Index19 Participation Rates 82 64.3 79 (years) 12 85 12 8 9 0 —HIV/AIDS 68.5 — 108 72.3 110 3.5 2.01.25 18 0.8239,720 Both Females Males Females 80 81.1 78 8 83 11 13 7 5Males — 81.1 — 104 76.4 3.3 98 1.50.93 13 21 0.8146,840 Sexes Males Females 1990 2013 2014 2008/2014 82 0.04 81 9 84 —7 — 42014 — — 0.04 2008/2014 119 0.05 2008/2014 101 3.3 1.50.55 15 16 2013 — — 71 269 136 — 78 76 82 0.6 69 80 11 73 84 76 11 19 — 0.7 98 0.7 102 3.1 1.51.03 1.13 17 14 0.66 0.7857,830 79 0.04— 76 82 15 13 — — 104 104 — 6 — —25 7 — 0.04 —0.05 — — 1.41.27 — 13 24 0.79 — — 69 338 159 — 74 71 81 16.9 68 79 10 72 83 11 9 6 2 — 17.6 131 17.9 130 3.8 1.70.99 1.10 17 17 0.63 0.8347,660 68 443 200 0.4 0.7 69 66 83 8.3 66 81 10 70 85 88 6 11 — — 8.7 98 9.0 3.9 95 1.50.94 1.00 15 18 0.56 0.8359,600 62 900 384 0.5 280 0.8 46 73 292 60 68 12 63 78 13 62 19 1 — — 260 101 840 98 1.60.66 1.31 16 14 0.79 0.78 21,130 60 801 412 1.5 54 49 — 16 73 9.5 58 67 13 61 78 13 37 1 2 0.9 0.1 0.2 9.1 106 8.7 104 4.4 1.71.35 14 0.73 0.7917,610 57 964 488 1.1 1.9 49 42 — 14 75 7.2 56 71 9 59 78 15 24 5 -0 — — 6.6 101 5.8 7.6 96 1.51.27 20 0.84 0.8115,850 71 242 118 <0.1 78 75 79 10.6 69 76 10 72 82 10 15 5 2<0.1 — 10.8 — 103 11.1 104 2.4 1.51.09 1.43 15 17 0.32 0.7526,970 74 9.8 72 77 160 89 -3<0.1 <0.1 96 100 1.51 15 0.2123,830 18 0.75 9 79 13 9.7 9.4 4.6 1.41.28 76 23 14 — — 108 108 71 4.1 68 70 73 120 45 -1 <0.1 <0.1 90 88 0.89 16 0.32 5,480 72 11 76 11 61 21 — — 3.7 88 2.9 1089 1.31.29 10 0.85 71 38.5 74 69 31 15 — — — — — 15 78 10 74 82 10 17 3 -0 <0.1 <0.1 37.2 111 34.0 107 4.2 1.31.55 15 0.39 0.7524,090 74 310 120 <0.1 74 63 75 19.8 73 71 9 75 78 170 13 33 -4<0.1 — 18.6 — 16.4 96 8.8 94 1.30.89 1.33 16 17 0.35 0.7519,030 62144.3 65 60 64 720 360 0.1 140.4 0.2 43 39 1.12 16 0.4124,710 71 13 76 13 74 24 2 — — 134.2 98 9.3 96 1.81.26 13 0.80 74 78 91 46 89 1.62 15 0.3525,970 76 5.4 73 10 80 15 9 7 0 <0.1 <0.1 5.4 92 5.0 6.0 93 1.41.54 14 0.74 68 42.8 66 70 — — — — — — 15 — 8,560 71 11 76 15 49 23 1 — 0.2 38.2 0.6 100 32.3 9.6 97 1.51.19 15 0.80 55 54 56 1,053 539 0.6 154 1.0 47 — 15 0.76 81 156 79 9 84 10 11 6 -0 — — 149 109 109 440 1.41.30 19 0.73 29,730 59 600 340 0.2 0.4 65 43 78 2.9 58 76 12 61 80 31 7 21 -6 — — 3.0 84 2.8 7.9 80 1.80.27 1.30 19 12 0.86 0.6910,260 56 0.08— 56 57 770 400 0.4 0.5 31 26 — 9 — — 4 — -7 — — 0.08 — 0.07 — 3.4 1.30.49 — 15 18 0.86 — — 75 3.7 71 230 53 0.8 0.3 89 103 1.21.46 72 7 80 78 19 9 8 0 — — 3.5 — 3.2 — 5 — 15 16 0.62 0.6010,020 51 740 720 0.9 1.4 46 32 77 4.2 50 74 9 52 81 128 13 -2 — — 4.0 97 3.6 100 4.1 1.50.62 1.36 15 18 0.64 0.7720,560 59 710 430 0.4 0.7 59 56 — 15 81 11.5 58 78 9 60 83 106 5 -1 — 11.1 — 110 9.7 107 3.7 1.31.02 21 0.87 0.7126,130 61 760 380 0.4 0.6 69 65 83 62.5 60 80 8 63 85 10 10 4 2 — 63.5 — 100 63.5 2.9 98 1.40.63 1.42 14 22 0.94 0.6734,710 60 1.8 74 58 61 1,100 650 0.4 0.7 47 29 77 13 79 —4 — -12 — — 1.9 — 1.9 12 — 2.30.44 — 28 7 0.84 — 9,410 54 2.1 73 53 56 930 560 0.8 1.5 — — — 17 0.8712,600 75 11 77 10 15 7 0 — — 2.0 83 1.8 10 82 1.51.20 13 0.64 60 1,200 640 0.3 0.4 42 33 82 0.4 59 80 10 61 84 12 8 9 3 — — 85 0.4 5.5 88 1.40.63 1.32 15 16 0.90 0.5727,020 53 1,100 550 0.5 0.7 50 40 77 0.6 53 74 12 53 79 108 7 -1 — — 91 0.8 4.4 91 1.60.43 1.27 18 14 0.62 0.7514,510 63 630 320 0.2 0.4 30 29 80 10.3 62 77 8 64 83 10 15 8 -3 — — 9.9 123 9.1 123 2.8 1.20.44 1.18 14 19 0.36 0.8328,010 60 1,000 630 0.2 22 15 87 0.0359 84 9 61 89 —8 — 5<0.1 — — 0.03 93 0.03 2.2 96 1.50.34 1.38 15 18 0.45 — — 52 1,200 560 0.7 1.3 46 41 — 14 75 7.1 52 73 9 53 78 14 18 16 -2 — — 6.8 93 6.1 5.7 96 1.61.33 18 0.76 0.7312,150 65 530 320 0.1 0.1 43 39 81 2.1 63 78 10 67 84 11 9 7 0 <0.1 <0.1 2.1 110 2.0 110 2.1 1.60.59 1.46 15 18 0.75 0.8328,650 50 2,300 0.2 0.4 48 42 — 15 83 46.4 50 80 9 51 86 97 1,100 4 -2 — 45.4 — 130 43.7 131 2.9 1.31.22 18 0.95 0.8032,860 57 40 75 56 57 660 450 0.5 0.8 — — 0.99 77 18 80 84 7 54 6 — 48 — 106 59 22 98 2.50.39 — 24 12 0.83 31,600 61 1,034 440 1.3 1.9 41 38 — 19 82 23.9 59 80 13 63 84 77 6 8 — 28.5 — 141 34.0 130 3.6 1.91.37 15 0.92 0.8242,880 59 1,300 740 0.3 0.4 37 29 70 0.1 57 69 24 61 72 170 5 96 -14 — — 0.1 — 0.1 29 — 3.50.42 — 34 4 1.02 — 3,680 61 630 350 — — 63 70 0.9 60 67 21 62 73 89 8 59 -6 <0.1 <0.1 0.9 84 1.0 1565 93 3.10.86 — 29 5 0.44 0.52 8,030 62 400 230 0.5 0.8 53 43 0.54 — — — — — 24 77 0.3 60 75 16 63 79 — 5 — 0 — 0.3 0.3 6.0 2.00.68 7 0.73 63 0.2 76 60 65 1,700 380 0.2 0.3 0.89 — 79 21 82 —6 — -6 — — 0.2 —0.2 13.3 — 2.90.50 — 26 8 0.80 64 0.1 63 62 65 1,400 420 -1 — 0.5 0.6 — — 65 30 68 250 9 130 — 0.2 82 0.2 45 91 3.8 — 36 4 0.88 — 2,580 62 490 400 — 69 65 72 0.0660 70 30 65 75 — 4 — -17 — 0.06 101 0.07 26 104 4.10.70 0.92 41 3 0.86 — 4,630 65 740 440 0.2 0.1 39 66 0.0164 62 35 66 70 — 8 — -9 — — 0.01 81 0.02 3338 77 3.90.94 — 37 1 0.96 — — 61 1,100 510 2.4 4.1 38 77 0.3 60 74 15 62 81 —6 — 4 — — 0.3 — 0.3 — 535 2.30.65 — 24 9 1.04 0.68 — 74 70 73 0.2 0.2 94 98 81 4.6 71 80 13 78 83 18 7 8 11 — — 5.2 116 5.7 122 5.7 1.91.22 1.45 20 15 0.59 0.8433,760 79 — — — —0.02 — — 20 72 0.0276 69 13 83 76 11 0 — 0.02 111 13 117 1.71.55 6 — 14,280 54 7.7 60 52 56 1,300 480 0 — — 27 25 1.03 2,510 62 33 65 470 10 220 0.2 10.5 0.2 14.2 46 4734 4.30.69 — 39 3 0.95 80 0.2 73 77 84 — — — — — 5,600 74 29 76 150 5 58 -28 — — 0.2 81 0.2 16 90 4.7 — 39 5 0.40 65 0.6 67 63 66 1,400 320 0 — 1.0 1.3 31 34 1.01 2,020 70 30 74 320 5 130 — 0.9 50 1.4 2647 4.10.75 — 39 3 0.68 73 0.1 74 69 78 —71 — -19 — 69 75 — 5,300 76 27 77 7 120 — 0.1 100 0.1 17 104 3.92.20 — 37 6 0.72 55 0.0167 53 57 1,300 850 0.2 0.2 — — 70 25 72 —9 — 0 — — 0.01 85 0.02 10 106 3.2 — 33 5 0.49 — 5,260 55 0.3 70 54 56 1,800 730 0.7 1.3 — — — 2,870 71 33 73 170 5 86 0 — — 0.4 60 0.5 28 59 4.2 — 39 4 0.77 62 60 BirthsFemales 63 910 2013 410 NetMales 1.4 mid-2030 2.1 34 32 0.54 Age 0.98GNI per Both Males 1990 Females mid-2050 Males Infant Females Total 2008/2014 Age2013 Population per Deaths See on 29 page 21 59 58 1,00060 2.3 (millions) 3.7notes2008/2014 25 0.78 <15 Sexes 2014 2014 (millions) Mortality 2008/2014 Fertility 65+0.96Capita mid-2015 per780 1,000 360 Migration 53 51 Population 56 580 280Rate per3.3 4.2 — —a 0.85 ($US) Rate Rateb— (millions) Population Life Expectancy Maternal Percent Ages 15-24 Population Secondary School Tertiary School PercentGender of Ratio c

67 53 129 23 63 50 74 69 80 49 646 40 88 82 82 80 84 50 376 44 75 65 82 80 80 49 OF 1,047 24 84 84 81 79 REGIONS THE WORLD 77 49 566 33 71 68 81 79 Female Share of 638Female 67 48 30Share 70 68 81 78 Nonagricultural 99 48 1,397of Parliament 42 70 69 80 78 Wage Earners 352 Members 78 50 26 76 74 82 79 73 48 685 37 66 62 80 78 2008/2013 15 44 1,249 2015 20 — — 82 81 20 90 34 45 908 28 — — 82 80 23 100 48 — — 21 — — — — 19 90 28 49 1,675 37 69 67 81 79 17 74 28 48 2,057 28 82 78 83 81 22 69 27 49 153 16 69 57 73 68 21 76 30 51 173 29 63 51 73 67 21 73 35 50 216 20 69 40 75 71 — 74 20 46 334 20 86 78 79 76 18 26 81 69 48 224 71 10 76 72 19 — 42 55 227 22 60 42 72 68 16 60 — 47 352 22 — — 78 74 11 54 22 46 226 12 70 51 75 71 — 74 — 50 121 15 68 55 71 65 28 31 80 54 48 389 19 66 76 73 — 69 — 49 132 12 68 61 71 66 — 10 68 46 517 32 66 48 81 79 7 69 56 26 41 467 21 10 78 76 13 86 — 47 3,254 39 — — — — 21 40 — 38 363 19 46 12 75 72 9 — 56 21 48 468 26 — 77 74 9 76 78 — 43 454 23 46 81 78 11 68 32 46 878 30 63 41 83 80 18 22 66 38 — — — 14 77 74 — 14 40 57 42 500 33 27 75 73 11 95 24 41 4,799 13 86 46 82 80 9 23 64 — 47 362 17 15 77 74 22 61 — 50 950 31 87 83 80 77 13 94 36 43 3,293 17 — — 87 84 5 58 60 — 45 216 34 18 75 73 43 50 27 47 1,206 28 79 63 81 78 12 77 — 47 373 38 66 62 83 80 — 18 62 70 47 82 25 58 77 75 28 89 36 47 51 31 72 68 82 80 35 22 — 5,074 0 — 70 70 69 3 29 51 — 527 14 — 70 67 — 10,265 13 — — 56 45 — 77 75 — 17,953 22 67 93 44 — 58 79 76 26 54 39 44 5,600 9 22 18 65 63 36 21 74 — 2,753 3 45 42 72 70 37 21 100 — — 5 36 23 66 62 17 — 70 — 4,959 — — 77 74 12 86 38 47 794 31 75 72 81 80 — 84 — 1,779 10 33 30 72 69 40 13 — 2,443 3 32 24 62 60 —6 29 19 — 37 2,451 27 74 73 34 58 20 — 3,276 2 35 27 70 67 53 44 23 — 646 0 34 28 76 74 14 59 — — 7 31 22 70 67 24 24 — 37 1,423 0 49 36 71 70 33 Population 2015 36 All Percent 2008/2013 Modern Both Males Fe DATA SHEET 35Methods Methods Urban352015 perWORLD Square POPULATION Sexes 20 — Kilometer 13 Female Share of Female Share Percent of Married Life Expectancy

WO R L D P O P U L AT I O N H I G H L I G H T S FOCUS ON WOMEN’S EMPOWERMENT

Rates of Early Marriage Fall, Particularly Among Those Under 15

Women Post Uneven Gains in Household Decisionmaking Power

Early marriage (before age 18) undermines the rights and livelihood opportunities of adolescent girls by leaving them vulnerable to the health risks of early pregnancy and childbearing, and prematurely ending their schooling. Rates of early marriage have declined broadly in the past 20 years, particularly among girls who are under age 15. Part of the overall decline reflects improvements in girls’ access to education: As girls educational attainment improves, the proportion marrying early tends to fall. Better employment opportunities for women and girls also can help delay marriages. In Bangladesh, expanded employment in the garment industry is linked to notably lower rates of marriage among rural migrants under age 15. The percentage of Bangladeshi girls married by age 18 has declined much more slowly as the youngest potential brides tend to postpone marriage by only a few years. The majority of Bangladeshi girls continue to marry before age 18.

Married women in many countries are increasingly likely to have a say in household decisions, but these gains do not necessarily apply to every type of decision. When women are included in decisions about household spending, more money tends to be spent for the benefit of women and children. And when women are able to make decisions about their health care, they are less vulnerable to preventable diseases.

Progress in these areas has varied by country, and even in countries showing notable gains, many women still do not engage in all types of important decisions. For example, in Nepal, only 66 percent of women have a say about their own health care decisions. The same percentage of Zambian women have the opportunity to make decisions about large household purchases.

Percent of Young Women Married by Age 15 (numbers in white) and Age 18 (numbers in black)

Percent of Currently Married Women Who Have a Say in Decisions About This Topic

NOTES (—) 83

Own Health 100

Indicates data unavailable or inapplicable.

90

A date range indicates the most recent data point during 73 that time period.

76

80

65

a Infant deaths per 1,000 live births. Rates shown with decimals indicate national statistics reported as completely registered, 49 41 while those without are estimates from the sources cited on 47 the reverse. Rates shown in italics are based on fewer than 27 50 annual 29 infant deaths, so the figure is estimated from an 19 18 17 average of the previous three years.

19

47

28

16

1992

b Average number of children born to a7 woman during 2 her 1993 –lifetime.

2011 2000 2011 1992 2014

2012

1994

Bangladesh Ethiopia c Data prior to 2014 are shown in italics. Egypt

Niger

70 60

Large Purchases

e The status of Western Sahara is disputed by Morocco.

88

f Special Administrative Region.

91

89

84

83 74

74 g Does not include the population of Crimea, estimated 75 72 65 66 at 2.3 million.

66

79

77 71 64

53 57 h Kosovo declared independence from56 Serbia on Feb. 17, 2008.

50 42 Serbia has not recognized Kosovo’s independence.

47 40 30 20

32 i The former Yugoslav Republic.

37

20 27 and sources, see reverse side.

For notes 18 17 additional

18 17 15 Data prepared

by PRB demographers Toshiko Kaneda and Kristin Bietsch.

0

10 3

3

1991– 1992

2012

2001 2006

2012–

2001

2006

2011

2001–

2007

2013–

2000

2004 – 2012

2002 Bureau.

2014 All rights 2006 © August2013 2015. Population Reference reserved.

Peru

Mali

d Data prior to 2009 are shown in italics.

Source: ICF International, Demographic and Health Surveys.

Nepal

Zambia

2002

Peru

2007

2012

Jordan

Source: ICF International, Demographic and Health Surveys.

Family Planning Needs Increasingly Met by Modern Methods, but More Progress Needed

Acceptance of Wife Beating Recedes

“Demand for family planning satisfied with modern methods” has emerged as a key indicator of contraceptive availability and use. The indicator measures the proportion of women who want to delay or limit childbearing and who are using modern methods of contraception.

Family planning experts have urged countries to strive for meeting at least 75 percent of demand with modern methods. Over the past two decades, a significant number of less developed countries have seen increases in the share of demand satisfied with modern methods, but many countries remain far below the proposed 75 percent benchmark. They will need to accelerate progress over the coming decade so that increased contraceptive use can translate into improved maternal and child health, slower population growth, increased economic well-being, and environmental sustainability.

Violence against women poses a serious challenge to women’s empowerment. Combating such violence often requires changing the attitudes and beliefs of both men and women. In fact, in some countries, substantial percentages of women actually agree that a husband has the right to beat a wife under certain circumstances. Many of these women believe a husband is justified in hitting a wife who goes out on her own without telling the husband. It is encouraging that these beliefs appear to be moderating in most countries.

For example, in 2013, 13 percent of Nigerian men and 25 percent of Nigerian women viewed a wife leaving home without telling the husband as justification for wife beating, down from 19 percent and 32 percent, respectively, in 2008. Zambia also showed notable drops for both men and women between 2007 and 2013-2014. Globally, however, there is still a long path to achieve zero global tolerance of this harmful practice.

Percent Who Agree That Husband Is Justified Beating Wife if She Leaves the House Without Informing Him

Percent of Demand for Family Planning Satisfied by Modern Contraceptive Methods

Men

Women

80 71 64 Egypt

52 40

58

38

26

32

41

Jordan

Kenya

40 © 2015 Population Reference Bureau 36

Philippines

43

47 31

2006

2011

Uganda

25

19

52

13

2008

2013

Nigeria

2015 WORLD POPULATION DATA SHEET

21

Acknowledgments, Notes, Sources, and Definitions ACKNOWLEDGMENTS The authors gratefully acknowledge the valuable assistance of PRB senior consultant, Carl Haub; PRB staff members John May, Kelvin Pollard, Donna Clifton, Carolyn Lamere, Heather Randall, and Nicole LaGrone; PRB interns Heather Zaccaro, Adaeze Ezeofor, and Kimberly Rightor; and staff of the International Programs Center of the U.S. Census Bureau; the United Nations (UN) Population Division; and the Institut national d’etudes démographiques (INED), Paris, in the preparation of this year’s World Population Data Sheet.

This publication is funded by the William and Flora Hewlett Foundation, the David and Lucile Packard Foundation, the U.S. Agency for International Development (IDEA Project, No. AID0AA-A-10-00009), and supporters. The contents are the responsibility of the Population Reference Bureau and do not necessarily reflect the views of USAID or the United States government.

NOTES The Data Sheet lists all geopolitical entities with populations of 150,000 or more and all members of the UN. These include sovereign states, dependencies, overseas departments, and some territories whose status or boundaries may be undetermined or in dispute. More developed regions, following the UN classification, comprise all of Europe and North America, plus Australia, Japan, and New Zealand. All other regions and countries are classified as less developed. The least developed countries consist of 48 countries with especially low incomes, high economic vulnerability, and poor human development indicators; 34 of these countries are in sub-Saharan Africa, 13 in Asia, and one in the Caribbean. The criteria and list of countries, as defined by the UN, can be found at http://unohrlls.org/about-ldcs/.

Sub-Saharan Africa: All countries of Africa except the northern African countries of Algeria, Egypt, Libya, Morocco, Sudan, Tunisia, and Western Sahara.

World and Regional Totals: Regional population totals are independently rounded and include small countries or areas not shown.

Regional and world rates and percentages are weighted averages of countries for which data are available. For most indicators, regional averages are shown when data or estimates are available for at least three-quarters of the region’s population. For Secondary School Enrollment Ratios, HIV Prevalence Rates, and Female Share of Nonagricultural Wage Earners, regional averages are shown when data or estimates are available for at least half of the region’s population.

World Population Data Sheets from different years should not be used as a time series. Fluctuations in values from year to year often reflect revisions based on new data or estimates rather than actual changes in levels. Additional information on likely trends and consistent time series can be obtained from PRB, and are also available from UN and U.S. Census Bureau publications and websites.

SOURCES The rates and figures are primarily compiled from the following sources: official country statistical yearbooks, bulletins, and websites; the UN Demographic Yearbook, 2013; and Population and Vital Statistics Report of the UN Statistics Division; World Population Prospects: The 2015 Revision of the UN Population Division; and the International Data Base of the International Programs Center, U.S.

Census Bureau. Other sources include recent demographic surveys such as the Demographic and Health Surveys, Multiple Indicator Cluster Surveys, special studies, and direct communication with demographers and statistical bureaus in the United States and abroad. Specific data sources may be obtained by contacting the authors of the 2015 World Population Data Sheet. For countries with complete registration of births and deaths, rates are those most recently reported. For more developed countries, nearly all vital rates refer to 2014 or 2013.

DEFINITIONS Mid-2015 Population Estimates are based on a recent census, official national data, or PRB, UN, and U.S. Census Bureau projections. The effects of refugee movements, large numbers of foreign workers, and population shifts due to contemporary political events are taken into account to the extent possible.

Birth and Death Rate The annual number of births and deaths per 1,000 total population.

These rates are often referred to as “crude rates” since they do not take a population’s age structure into account. Thus, crude death rates in more developed countries with a relatively large proportion of high-mortality older population are often higher than those in less developed countries with lower life expectancy.

Net Migration The estimated rate of net immigration (immigration minus emigration) per 1,000 population for a recent year based upon the official national rate or derived as a residual from estimated birth, death, and population growth rates. Migration rates can vary substantially from year to year for any particular country, as can the definition of an immigrant.

Projected Population, 2030 and 2050 Projected populations based on reasonable assumptions on the future course of fertility, mortality, and migration. Projections are based on official country projections, series issued by the UN or the U.S. Census Bureau, or PRB projections.

Infant Mortality Rate The annual number of deaths of infants under age 1 per 1,000 live births. Rates shown with decimals indicate national statistics reported as completely registered, while those without are estimates from the sources cited above. Rates shown in italics are based upon fewer than 50 annual infant deaths and, as a result, are subject to considerable yearly variability; rates shown for such countries are averages for a multiple-year period.

Total Fertility Rate (TFR) The average number of children a woman would have assuming that current age-specific birth rates remain constant throughout her childbearing years (usually considered to be ages 15 to 49).

Population Under Age 15/Age 65+ The percentage of the total population in those ages, which are often considered the “dependent ages.”

GNI PPP per Capita, 2014 (US$) GNI PPP per capita is gross national income in purchasing power parity (PPP) divided by mid-year population. GNI PPP refers to

gross national income converted to “international” dollars using a purchasing power parity conversion factor. PPP adjusts exchange rates to relative purchasing power in different countries, providing a more accurate basis of comparison for GNI. Data are from the World Bank. Figures in italics are for 2013, 2012, or 2011.

Percent Urban Percentage of the total population living in areas termed “urban” by that country or by the UN. Countries define urban in many different ways, from population centers of 100 or more dwellings to only the population living in national and provincial capitals.

Population per Square Kilometer of Arable Land The mid-year 2015 population divided by the square kilometers of arable land. Arable land is defined by the UN Food and Agriculture Organization (FAO) to include “the land under temporary agricultural crops (multiple-cropped areas are counted only once), temporary meadows for mowing or pasture, land under market and kitchen gardens and land temporarily fallow (less than five years).” Data for the percent of land that is arable and the square kilometers in a country are from the FAO.

Contraceptive Use The percentage of currently married or “in union” women of reproductive age who are currently using any form of contraception.

Modern methods include clinic and supply methods such as the pill, IUD, condom, and sterilization. Data are from the most recently available national-level surveys, such as Demographic and Health Surveys, Reproductive Health Surveys, Multiple Indicator Cluster Surveys, regional survey programs, national surveys, and the UN Population Division World Contraceptive Use 2014. Data prior to 2009 are shown in italics.

Life Expectancy at Birth The average number of years a newborn infant can expect to live under current mortality rates.

Maternal Deaths per 100,000 Births Maternal deaths in a time period divided by the number of live births in the same period, expressed per 100,000 live births. A maternal death is defined by the World Health Organization (WHO) as “the death of a woman while pregnant or within 42 days of the termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause to or aggravated by the pregnancy or its management but not from accidental or incidental causes.” Data are from the 2014 report Trends in Maternal Mortality: 1990 to 2013 that compiles estimates by WHO, UNICEF, UNFPA, the World Bank, and the UN Population Division.

HIV Prevalence The proportion of the population living with HIV regardless of the time of infection, knowledge of the infection, or stage of the disease. Data are from UNAIDS.

Secondary School Enrollment Ratio The number of students enrolled in secondary education divided by the secondary-school-age population (Gross Enrollment Ratio).

The ratio can be over 100 when there are students enrolled who are older or younger than the age expected for secondary school students. Data are from UNESCO for 2008-2014.

Tertiary School Gender Parity Index The tertiary education gross enrollment ratio for women divided by the tertiary gross enrollment ratio for men. An index less than one indicates that men are more represented in higher education than women, while an index greater than one indicates that women are more represented. Data are from UNESCO for 2008-2014.

Gender Ratio of Labor Force Participation Rates The ratio of the female labor force participation rate over the male rate. The labor force participation rate is defined as the proportion of the population ages 15 years and older who are economically active, including those employed and unemployed. A ratio less than one indicates that the male labor force participation rate is greater than the female rate while a ratio of more than one indicates that the female rate is greater than the male rate. Data are from the World Bank for 2013.

Female Share of Nonagricultural Wage Earners The percent of workers in wage employment in the nonagricultural sector who are women. In a small number of countries the definition of the sector is one of the following: the economically active population in nonagriculture, total employment, total employment in nonagriculture, total paid employment, and employment in the public sector. Data are from the UN from 2008-2013.

Female Share of Parliament Members The percentage of seats in a country’s single chamber, combined higher and lower chambers of the national parliament, or other national legislature held by women. Data are from the InterParliamentary Union from May 1, 2015.

PRB’s 2015 World Population Data Sheet is available in English, French, and Spanish at www.prb.org.

Also online: • A customized Data Dashboard where users can view multiple indicators for regions or countries.

• A video focusing on what the data say about the state of women’s empowerment.

• An interactive world map illustrating key demographic variables by country and region.

To order PRB publications (discounts available for bulk orders): • Online at www.prb.org.

• E-mail: popref@prb.org.

• Call toll-free: 800-877-9881.

• Fax: 202-328-3937.

• Mail: 1875 Connecticut Ave., NW, Suite 520, Washington, DC 20009.

Data prepared by PRB demographers Toshiko Kaneda and Kristin Bietsch. © August 2015.

Population Reference Bureau.

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