Population living in slums 2006

This statistic measures the percentage of a country's population living in slums, highlighting urban poverty and living conditions. Understanding slum populations is crucial for addressing housing challenges and improving the quality of life.

171 data pointsWorldUN Habitat

Interactive Map

Complete Data Rankings

Rank
1
South Sudan flag
South Sudan
99.8 %
2
Sudan flag
Sudan
99.088 %
3
Lebanon flag
Lebanon
92.41 %
4
Chad flag
Chad
88.202 %
5
Madagascar flag
Madagascar
84.231 %
6
Ethiopia flag
Ethiopia
82.886 %
7
Mozambique flag
Mozambique
79.555 %
8
Congo flag
Congo
78.458 %
9
Central African Republic flag
Central African Republic
77.439 %
10
Liberia flag
Liberia
74.596 %
11
Mauritania flag
Mauritania
74.563 %
12
Uganda flag
Uganda
72.835 %
13
Congo, Democratic Republic of the flag
Congo, Democratic Republic of the
72.375 %
14
Burundi flag
Burundi
71.681 %
15
Mali flag
Mali
71.292 %
16
Malawi flag
Malawi
70.869 %
17
Benin flag
Benin
70.686 %
18
Niger flag
Niger
70.212 %
19
Djibouti flag
Djibouti
69.894 %
20
Eritrea flag
Eritrea
69.894 %
21
Mauritius flag
Mauritius
69.894 %
22
Seychelles flag
Seychelles
69.894 %
23
Somalia flag
Somalia
69.894 %
24
Sierra Leone flag
Sierra Leone
69.81 %
25
Tanzania flag
Tanzania
68.555 %
26
Cambodia flag
Cambodia
67.9 %
27
Nicaragua flag
Nicaragua
67.812 %
28
Pakistan flag
Pakistan
66.647 %
29
Nigeria flag
Nigeria
66.57 %
30
Comoros flag
Comoros
66.27 %
31
Burkina Faso flag
Burkina Faso
65.513 %
32
Cabo Verde flag
Cabo Verde
63.83 %
33
Afghanistan flag
Afghanistan
63.6 %
34
Côte d'Ivoire flag
Côte d'Ivoire
62.455 %
35
Sao Tome and Principe flag
Sao Tome and Principe
61.4 %
36
Rwanda flag
Rwanda
60.977 %
37
Togo flag
Togo
59.542 %
38
Equatorial Guinea flag
Equatorial Guinea
59.172 %
39
Zambia flag
Zambia
59.127 %
40
Kenya flag
Kenya
58.545 %
41
Ecuador flag
Ecuador
57.8 %
42
Nepal flag
Nepal
57.634 %
43
Haiti flag
Haiti
57.366 %
44
Senegal flag
Senegal
56.49 %
45
Bangladesh flag
Bangladesh
56.378 %
46
Timor-Leste flag
Timor-Leste
56.1 %
47
Yemen flag
Yemen
55.948 %
48
Cameroon flag
Cameroon
55.556 %
49
Bhutan flag
Bhutan
55.273 %
50
Iran flag
Iran
55.273 %
51
Sri Lanka flag
Sri Lanka
55.273 %
52
Lesotho flag
Lesotho
54.466 %
53
Botswana flag
Botswana
52.325 %
54
Gabon flag
Gabon
51.817 %
55
Gambia flag
Gambia
51.512 %
56
Bolivia flag
Bolivia
51.153 %
57
Ghana flag
Ghana
50.288 %
58
Guatemala flag
Guatemala
48.786 %
59
Eswatini flag
Eswatini
47.928 %
60
El Salvador flag
El Salvador
46.491 %
61
Philippines flag
Philippines
45.755 %
62
Mongolia flag
Mongolia
45.687 %
63
Laos flag
Laos
44.1 %
64
Guinea flag
Guinea
43.168 %
65
Namibia flag
Namibia
42.11 %
66
Peru flag
Peru
41.867 %
67
Maldives flag
Maldives
41.535 %
68
Honduras flag
Honduras
40.9 %
69
Myanmar flag
Myanmar
39.027 %
70
Iraq flag
Iraq
38.528 %
71
Panama flag
Panama
35.742 %
72
Libya flag
Libya
35.168 %
73
Kyrgyzstan flag
Kyrgyzstan
33.743 %
74
Paraguay flag
Paraguay
33.036 %
75
Azerbaijan flag
Azerbaijan
32.93 %
76
Brunei Darussalam flag
Brunei Darussalam
32.359 %
77
Algeria flag
Algeria
30.8 %
78
Vietnam flag
Vietnam
30.485 %
79
Syrian Arab Republic flag
Syrian Arab Republic
30.437 %
80
Indonesia flag
Indonesia
30.163 %
81
State of Palestine flag
State of Palestine
29.071 %
82
Mexico flag
Mexico
27.018 %
83
South Africa flag
South Africa
26.467 %
84
Angola flag
Angola
25.792 %
85
Zimbabwe flag
Zimbabwe
25.736 %
86
Venezuela flag
Venezuela
25.7 %
87
Egypt flag
Egypt
25.696 %
88
Brazil flag
Brazil
24.818 %
89
Morocco flag
Morocco
24.791 %
90
Guyana flag
Guyana
23.671 %
91
Dominican Republic flag
Dominican Republic
23.066 %
92
Uzbekistan flag
Uzbekistan
21.187 %
93
Albania flag
Albania
20.5 %
94
Turkey flag
Turkey
20.399 %
95
Papua New Guinea flag
Papua New Guinea
20.1 %
96
Uruguay flag
Uruguay
19.95 %
97
Argentina flag
Argentina
18.115 %
98
Republic of Moldova flag
Republic of Moldova
18 %
99
Montenegro flag
Montenegro
17.3 %
100
Colombia flag
Colombia
17.144 %
101
Kazakhstan flag
Kazakhstan
16.106 %
102
Belize flag
Belize
15.753 %
103
Fiji flag
Fiji
14.5 %
104
Kiribati flag
Kiribati
14.35 %
105
South Korea flag
South Korea
12.8 %
106
Georgia flag
Georgia
12.448 %
107
Hungary flag
Hungary
11.6 %
108
Armenia flag
Armenia
11.329 %
109
Tunisia flag
Tunisia
10.4 %
110
Trinidad and Tobago flag
Trinidad and Tobago
10.28 %
111
Turkmenistan flag
Turkmenistan
10.257 %
112
Costa Rica flag
Costa Rica
9.951 %
113
Suriname flag
Suriname
9.941 %
114
Solomon Islands flag
Solomon Islands
8.95 %
115
Chile flag
Chile
7.3 %
116
Ireland flag
Ireland
6.9 %
117
Bosnia and Herzegovina flag
Bosnia and Herzegovina
4.9 %
118
Vanuatu flag
Vanuatu
4.45 %
119
Austria flag
Austria
4.4 %
120
Cayman Islands flag
Cayman Islands
4.15 %
121
Saint Lucia flag
Saint Lucia
3.9 %
122
Samoa flag
Samoa
3.9 %
123
Ukraine flag
Ukraine
3.9 %
124
Tuvalu flag
Tuvalu
3.75 %
125
Romania flag
Romania
3.5 %
126
Russia flag
Russia
3.35 %
127
Cuba flag
Cuba
3.202 %
128
Oman flag
Oman
2.9 %
129
Lithuania flag
Lithuania
2.85 %
130
British Virgin Islands flag
British Virgin Islands
2.577 %
131
Nauru flag
Nauru
2.25 %
132
Latvia flag
Latvia
2.15 %
133
Marshall Islands flag
Marshall Islands
2 %
134
Tonga flag
Tonga
1.65 %
135
Palau flag
Palau
1.5 %
136
Poland flag
Poland
1.25 %
137
North Macedonia flag
North Macedonia
1.15 %
138
United Arab Emirates flag
United Arab Emirates
0.95 %
139
Portugal flag
Portugal
0.75 %
140
Serbia flag
Serbia
0.6 %
141
Croatia flag
Croatia
0.35 %
142
Canada flag
Canada
0.3 %
143
Cyprus flag
Cyprus
0.25 %
144
Sweden flag
Sweden
0.25 %
145
Greece flag
Greece
0.2 %
146
United States flag
United States
0.2 %
147
Australia flag
Australia
0.125 %
148
Bermuda flag
Bermuda
0.1 %
149
Bulgaria flag
Bulgaria
0.1 %
150
Estonia flag
Estonia
0.1 %
151
United Kingdom flag
United Kingdom
0.1 %
152
Czech Republic flag
Czech Republic
0.05 %
153
Slovakia flag
Slovakia
0.05 %
154
Malta flag
Malta
0.038 %
155
Italy flag
Italy
0.02 %
156
Luxembourg flag
Luxembourg
0.003 %
157
Andorra flag
Andorra
0 %
158
Aruba flag
Aruba
0 %
159
Belgium flag
Belgium
0 %
160
Denmark flag
Denmark
0 %
161
Finland flag
Finland
0 %
162
France flag
France
0 %
163
Germany flag
Germany
0 %
164
Iceland flag
Iceland
0 %
165
Kuwait flag
Kuwait
0 %
166
Monaco flag
Monaco
0 %
167
Netherlands flag
Netherlands
0 %
168
New Zealand flag
New Zealand
0 %
169
Norway flag
Norway
0 %
170
Singapore flag
Singapore
0 %
171
Switzerland flag
Switzerland
0 %

Top 10 Countries

  1. #1South Sudan flagSouth Sudan
  2. #2Sudan flagSudan
  3. #3Lebanon flagLebanon
  4. #4Chad flagChad
  5. #5Madagascar flagMadagascar
  6. #6Ethiopia flagEthiopia
  7. #7Mozambique flagMozambique
  8. #8Congo flagCongo
  9. #9Central African Republic flagCentral African Republic
  10. #10Liberia flagLiberia

Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.

Bottom 10 Countries

  1. #171Switzerland flagSwitzerland
  2. #170Singapore flagSingapore
  3. #169Norway flagNorway
  4. #168New Zealand flagNew Zealand
  5. #167Netherlands flagNetherlands
  6. #166Monaco flagMonaco
  7. #165Kuwait flagKuwait
  8. #164Iceland flagIceland
  9. #163Germany flagGermany
  10. #162France flagFrance

Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.

Analysis & Context

In 2006, the global issue of urban poverty was starkly highlighted by the statistic measuring the percentage of the population living in slums. This metric provides a critical lens through which to assess living conditions, economic disparities, and environmental impacts on urban communities worldwide. By analyzing this data, stakeholders can better understand the challenges and opportunities for improving housing policies and enhancing the quality of life for vulnerable populations.

The Urban Poverty Landscape in 2006

In 2006, the prevalence of slum living was a pressing concern, with an average of 31.55% of the population across 171 countries residing in such conditions. This situation is emblematic of the broader issues associated with urbanization, such as inadequate infrastructure, economic inequality, and insufficient public services. South Sudan stood at the forefront with a staggering 99.8% of its population living in slums, followed closely by Sudan at 99.0883%. These figures underscore the severe housing deficits and the urgent need for comprehensive urban planning and resource allocation to uplift these communities.

Regional Disparities and Influencing Factors

The data from 2006 reveals significant regional disparities in slum populations. African nations overwhelmingly dominated the top of the list, as evidenced by countries like Chad (88.2019%), Madagascar (84.231%), and Ethiopia (82.8858%). In contrast, many European and some Middle Eastern countries, including Iceland, Kuwait, and Monaco, reported a 0% slum population, showcasing the stark contrast between different parts of the world. These regional variations can be attributed to a range of factors, including the historical development of cities, governance structures, and economic policies that either mitigate or exacerbate urban poverty.

Economic Implications of Slum Populations

The economic ramifications of high slum populations are profound. Countries with substantial slum populations often grapple with high rates of unemployment and underemployment, which further perpetuates the cycle of poverty. In 2006, nations like Mozambique (79.5545%) and Congo (78.4582%) faced significant economic challenges, limiting their capacity to invest in necessary infrastructure and public services. The presence of slums often indicates a mismatch between rapid urbanization and economic growth, necessitating targeted policies to stimulate job creation and economic development while improving living conditions within these urban areas.

Policy Responses and Success Stories

Several countries have made strides in addressing the issue of slums through innovative policy responses. Successful interventions often include integrated approaches that combine upgrading informal settlements with providing access to essential services like clean water, sanitation, and education. In 2006, countries such as Brazil and South Africa were noted for implementing policies that aimed to reduce slums by investing in infrastructure and promoting inclusive urban development. These efforts demonstrate the potential for transformative change when governments prioritize housing and quality of life improvements for their most vulnerable citizens.

Future Directions for Global Slum Reduction

Moving forward from 2006, the goal of reducing slum populations remains a critical target for international development agendas. The data signifies the necessity for global cooperation and sustained investment in urban planning and development. Addressing the root causes of slum growth, such as economic disparities and rapid urbanization, is imperative. As nations strive to meet the Sustainable Development Goals set by the United Nations, prioritizing sustainable urbanization and improving living conditions in slums will be vital to fostering equitable and resilient cities worldwide.

In conclusion, the 2006 statistics on populations living in slums underscore a significant global challenge that affects various aspects of society, from economic stability to environmental sustainability. By understanding these patterns and implementing comprehensive policies, the global community can work towards reducing slum populations and enhancing the quality of life for millions living in urban poverty.

Data Source

UN Habitat

The Data and Analytics Section (DAS) is the specialized statistics unit within UN-Habitat. The data section is responsible for overall data oversight across all urban monitoring domains within UN-Habitat, methodological developments, supporting member states in their monitoring efforts around global agenda such as the SDGs, implementing direct data collection and compilation, providing data to UN-Habitat global reports, and publicly and openly disseminating urban data through its urban indicators programme.

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Historical Data by Year

Explore Population living in slums data across different years. Compare trends and see how statistics have changed over time.

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