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
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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
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women
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The majorityWhen
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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.
All rights reserved.
ISSN 0085-8315
Photo credit, cover: © Jörg Dickmann, goZOOMA
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