Population living in slums 2022
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.
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Complete Data Rankings
Rank | ||
|---|---|---|
1 | South Sudan | 94.2 % |
2 | Mali | 92.497 % |
3 | Burkina Faso | 87.882 % |
4 | Sao Tome and Principe | 82.393 % |
5 | Chad | 82 % |
6 | Congo, Democratic Republic of the | 78.362 % |
7 | Congo | 75.342 % |
8 | Sudan | 73.7 % |
9 | Afghanistan | 71.589 % |
10 | Niger | 70.444 % |
11 | Tanzania | 70.086 % |
12 | Central African Republic | 68.913 % |
13 | Madagascar | 65.717 % |
14 | Equatorial Guinea | 64.687 % |
15 | Ethiopia | 64.314 % |
16 | Benin | 64.011 % |
17 | Angola | 62.7 % |
18 | Liberia | 60.477 % |
19 | Guinea-Bissau | 59 % |
20 | Mauritania | 58.56 % |
21 | Myanmar | 58.281 % |
22 | Ecuador | 57.8 % |
23 | Pakistan | 55.974 % |
24 | Mozambique | 54.959 % |
25 | Jordan | 54.9 % |
26 | Zimbabwe | 54.883 % |
27 | Laos | 54.84 % |
28 | Uganda | 52.681 % |
29 | Bangladesh | 51.508 % |
30 | Haiti | 51.059 % |
31 | Tuvalu | 50.899 % |
32 | Iraq | 49.339 % |
33 | Sierra Leone | 49.279 % |
34 | Djibouti | 48.686 % |
35 | Eritrea | 48.686 % |
36 | Mauritius | 48.686 % |
37 | Seychelles | 48.686 % |
38 | Somalia | 48.686 % |
39 | Comoros | 48.502 % |
40 | Nigeria | 48.497 % |
41 | Côte d'Ivoire | 48.261 % |
42 | Zambia | 48.258 % |
43 | Bolivia | 46.626 % |
44 | Senegal | 46.412 % |
45 | Cabo Verde | 46.412 % |
46 | Peru | 45.058 % |
47 | Bhutan | 44.69 % |
48 | Iran | 44.69 % |
49 | Sri Lanka | 44.69 % |
50 | Yemen | 44.2 % |
51 | Guinea | 43.957 % |
52 | Cambodia | 42.27 % |
53 | Namibia | 41.4 % |
54 | Syrian Arab Republic | 41.126 % |
55 | Kenya | 40.496 % |
56 | Nepal | 40.055 % |
57 | Botswana | 39.6 % |
58 | Gabon | 38.773 % |
59 | Togo | 38.461 % |
60 | Rwanda | 38.349 % |
61 | Malawi | 37.974 % |
62 | Guatemala | 37.6 % |
63 | Gambia | 37.081 % |
64 | Burundi | 36.752 % |
65 | Philippines | 35.874 % |
66 | Maldives | 34.845 % |
67 | Samoa | 34.585 % |
68 | Timor-Leste | 33.921 % |
69 | Ghana | 33.487 % |
70 | Cameroon | 32.672 % |
71 | Vietnam | 32.5 % |
72 | Honduras | 28.2 % |
73 | China | 26.321 % |
74 | Venezuela | 25.7 % |
75 | Lesotho | 25.553 % |
76 | South Africa | 24.2 % |
77 | North Korea | 23.036 % |
78 | Papua New Guinea | 22.269 % |
79 | Brunei Darussalam | 21.597 % |
80 | Indonesia | 19.411 % |
81 | Mongolia | 17.879 % |
82 | State of Palestine | 17.773 % |
83 | Mexico | 17.6 % |
84 | Eswatini | 17.006 % |
85 | Libya | 16.582 % |
86 | El Salvador | 16.477 % |
87 | Panama | 16.3 % |
88 | Suriname | 15.8 % |
89 | Belize | 15.725 % |
90 | Paraguay | 15.1 % |
91 | Brazil | 14.897 % |
92 | Argentina | 14.5 % |
93 | Turkey | 14.126 % |
94 | Algeria | 13.246 % |
95 | Guyana | 11.304 % |
96 | Dominican Republic | 11.249 % |
97 | Cuba | 11.041 % |
98 | Morocco | 10.851 % |
99 | Colombia | 9.7 % |
100 | Azerbaijan | 9.517 % |
101 | Fiji | 9.4 % |
102 | Montenegro | 8.769 % |
103 | Trinidad and Tobago | 8.627 % |
104 | Ireland | 8.5 % |
105 | Armenia | 8.395 % |
106 | Turkmenistan | 8.382 % |
107 | Tunisia | 7.643 % |
108 | Chile | 7.324 % |
109 | Uzbekistan | 7.1 % |
110 | Georgia | 7.079 % |
111 | Kiribati | 5.934 % |
112 | Cayman Islands | 5.479 % |
113 | India | 5.41 % |
114 | Nicaragua | 4.737 % |
115 | Lebanon | 4.531 % |
116 | South Korea | 4.5 % |
117 | Poland | 4.218 % |
118 | Hungary | 4.21 % |
119 | Egypt | 3.839 % |
120 | Costa Rica | 3.546 % |
121 | Vanuatu | 3.064 % |
122 | Sint Maarten (Dutch part) | 2.888 % |
123 | Saint Vincent and the Grenadines | 2.755 % |
124 | Albania | 2.7 % |
125 | Antigua and Barbuda | 2.646 % |
126 | Russia | 2.619 % |
127 | Romania | 2.52 % |
128 | Republic of Moldova | 2.44 % |
129 | Kyrgyzstan | 2.439 % |
130 | Marshall Islands | 2.375 % |
131 | Japan | 2 % |
132 | Thailand | 2 % |
133 | Solomon Islands | 1.95 % |
134 | French Polynesia | 1.5 % |
135 | Serbia | 1.415 % |
136 | Uruguay | 1.3 % |
137 | Canada | 1.096 % |
138 | United States Virgin Islands | 1.096 % |
139 | Jamaica | 0.884 % |
140 | Kazakhstan | 0.794 % |
141 | Turks and Caicos Islands | 0.631 % |
142 | Palau | 0.618 % |
143 | Nauru | 0.597 % |
144 | Latvia | 0.593 % |
145 | Guam | 0.552 % |
146 | Saudi Arabia | 0.55 % |
147 | Croatia | 0.527 % |
148 | Slovenia | 0.527 % |
149 | Lithuania | 0.509 % |
150 | Saint Lucia | 0.441 % |
151 | Estonia | 0.345 % |
152 | Sweden | 0.336 % |
153 | Bosnia and Herzegovina | 0.313 % |
154 | Tonga | 0.308 % |
155 | North Macedonia | 0.278 % |
156 | Cyprus | 0.272 % |
157 | New Caledonia | 0.25 % |
158 | Northern Mariana Islands | 0.2 % |
159 | Malaysia | 0.2 % |
160 | Bulgaria | 0.197 % |
161 | United Kingdom | 0.163 % |
162 | British Virgin Islands | 0.136 % |
163 | Ukraine | 0.12 % |
164 | United Arab Emirates | 0.113 % |
165 | United States | 0.093 % |
166 | Bermuda | 0.078 % |
167 | Slovakia | 0.066 % |
168 | Portugal | 0.059 % |
169 | Tajikistan | 0.05 % |
170 | Austria | 0.047 % |
171 | Spain | 0.046 % |
172 | Malta | 0.038 % |
173 | Australia | 0.035 % |
174 | Czech Republic | 0.027 % |
175 | Italy | 0.02 % |
176 | Luxembourg | 0.017 % |
177 | Belarus | 0.004 % |
178 | Andorra | 0 % |
179 | Aruba | 0 % |
180 | Belgium | 0 % |
181 | Denmark | 0 % |
182 | Finland | 0 % |
183 | France | 0 % |
184 | Germany | 0 % |
185 | Iceland | 0 % |
186 | Kuwait | 0 % |
187 | Monaco | 0 % |
188 | Netherlands | 0 % |
189 | New Zealand | 0 % |
190 | Norway | 0 % |
191 | Oman | 0 % |
192 | Qatar | 0 % |
193 | Singapore | 0 % |
194 | Switzerland | 0 % |
195 | Bahrain | 0 % |
196 | Greece | -0.2 % |
↑Top 10 Countries
- #1
South Sudan
- #2
Mali
- #3
Burkina Faso
- #4
Sao Tome and Principe
- #5
Chad
- #6
Congo, Democratic Republic of the
- #7
Congo
- #8
Sudan
- #9
Afghanistan
- #10
Niger
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #196
Greece
- #195
Bahrain
- #194
Switzerland
- #193
Singapore
- #192
Qatar
- #191
Oman
- #190
Norway
- #189
New Zealand
- #188
Netherlands
- #187
Monaco
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The statistic "Population living in slums" in 2022 provides a critical lens into the global urban landscape, revealing the extent of urban poverty and inadequate living conditions across different countries. As urban areas continue to expand, understanding the proportion of populations residing in slums is vital for policymakers and development organizations aiming to address housing challenges and improve urban living standards.
Global Urbanization Trends
In 2022, the global pattern of urbanization has been markedly uneven, with substantial disparities in living conditions within urban areas. The percentage of populations living in slums can highlight these discrepancies. The global average stands at 23.68%, indicating that nearly a quarter of the urban population in the surveyed 181 countries resides in slum conditions. Countries like South Sudan and Mali exhibit alarmingly high percentages, with 94.2% and 92.497% of their urban populations living in slums, respectively. These figures underscore significant challenges in urban planning and resource allocation in these regions.
Regional Variations and Influences
The data from 2022 demonstrates stark regional differences in slum population percentages. Africa, represented by countries such as Burkina Faso (87.8817%) and Chad (82%), shows some of the highest slum dwelling rates. These high percentages reflect broader socio-economic challenges, including rapid urbanization, inadequate infrastructure, and limited access to affordable housing. In contrast, many developed nations such as Oman, France, and Finland report a 0% slum population, illustrating effective urban management and housing policies.
Policy and Governance Impact
Effective governance and policy interventions play a crucial role in reducing slum populations. Developed countries often benefit from robust urban policies and substantial investments in public housing, contributing to their low slum percentages. Meanwhile, nations like the Democratic Republic of the Congo (78.3623%) and Sudan (73.7%) may struggle with political instability and insufficient policy frameworks to adequately address urban poverty. Strengthening governance structures and international cooperation can be pivotal for these countries in achieving sustainable urban development.
Economic Drivers and Challenges
Economic factors are a significant driver behind the prevalence of slums. In developing nations, rapid urban migration driven by the search for better economic opportunities often surpasses the capacity of cities to provide adequate housing. Countries like Afghanistan (71.589%) and Niger (70.444%) face economic constraints that limit urban infrastructure development and housing quality. Addressing these economic barriers through targeted investment and economic reform is essential to improving living conditions.
Future Prospects for Urban Populations
Looking forward, addressing the challenges of urban slums requires a multifaceted approach. Investments in affordable housing, infrastructure development, and the implementation of sustainable urban policies are crucial. Additionally, international collaboration and support can help nations with high slum populations to develop comprehensive strategies to tackle urban poverty. Understanding the intricate dynamics of urbanization and its impact on living conditions will be essential in creating inclusive and sustainable cities for the future.
The 2022 data on populations living in slums underscores the critical need for global attention to urban poverty. By examining regional variations, policy impacts, and economic challenges, stakeholders can better strategize to mitigate the adverse effects of slums, ultimately enhancing the quality of life for millions residing in these conditions.
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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