Population living in slums 2010
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 | 97.004 % |
2 | Sudan | 88.918 % |
3 | Chad | 85.947 % |
4 | Madagascar | 79.428 % |
5 | Ethiopia | 76.695 % |
6 | Guinea-Bissau | 75.2 % |
7 | Congo, Democratic Republic of the | 74.217 % |
8 | Mozambique | 72.527 % |
9 | Central African Republic | 71.755 % |
10 | Liberia | 71.025 % |
11 | Niger | 70.328 % |
12 | Benin | 69.899 % |
13 | Mauritania | 67.81 % |
14 | Uganda | 67.457 % |
15 | Comoros | 67.454 % |
16 | Nicaragua | 67.2 % |
17 | Congo | 65.995 % |
18 | Djibouti | 64.82 % |
19 | Eritrea | 64.82 % |
20 | Mauritius | 64.82 % |
21 | Seychelles | 64.82 % |
22 | Somalia | 64.82 % |
23 | Afghanistan | 64.808 % |
24 | Sierra Leone | 64.335 % |
25 | Malawi | 63.841 % |
26 | Pakistan | 63.598 % |
27 | Mali | 62.903 % |
28 | Nigeria | 61.545 % |
29 | Burundi | 60.956 % |
30 | Equatorial Guinea | 60.601 % |
31 | Tanzania | 60.04 % |
32 | Côte d'Ivoire | 59.373 % |
33 | Cabo Verde | 58.954 % |
34 | Sao Tome and Principe | 58.459 % |
35 | Ecuador | 57.8 % |
36 | Cambodia | 56.6 % |
37 | Zambia | 56.021 % |
38 | Kenya | 55.453 % |
39 | Bangladesh | 55.09 % |
40 | Haiti | 54.755 % |
41 | Burkina Faso | 54.381 % |
42 | Rwanda | 54.015 % |
43 | Bhutan | 53.698 % |
44 | Iran | 53.698 % |
45 | Sri Lanka | 53.698 % |
46 | Togo | 53.056 % |
47 | Nepal | 51.85 % |
48 | Yemen | 50.705 % |
49 | Timor-Leste | 50 % |
50 | Senegal | 49.38 % |
51 | Cameroon | 49.018 % |
52 | Botswana | 48.079 % |
53 | Gabon | 48.075 % |
54 | Gambia | 47.907 % |
55 | Bolivia | 46.626 % |
56 | Lesotho | 46.206 % |
57 | Myanmar | 45.445 % |
58 | Guinea | 44.836 % |
59 | Guatemala | 44.313 % |
60 | Ghana | 43.567 % |
61 | Philippines | 42.943 % |
62 | Lebanon | 42.194 % |
63 | Namibia | 41.812 % |
64 | Iraq | 41.617 % |
65 | Maldives | 39.863 % |
66 | Peru | 38.169 % |
67 | Angola | 38.055 % |
68 | Mongolia | 37.741 % |
69 | Laos | 37.3 % |
70 | Honduras | 36.22 % |
71 | El Salvador | 34.486 % |
72 | Eswatini | 33.08 % |
73 | Algeria | 30.8 % |
74 | Brunei Darussalam | 28.772 % |
75 | Libya | 27.872 % |
76 | Panama | 27.119 % |
77 | Paraguay | 27.041 % |
78 | Syrian Arab Republic | 26.998 % |
79 | Azerbaijan | 26.927 % |
80 | Indonesia | 26.855 % |
81 | South Africa | 25.706 % |
82 | Venezuela | 25.7 % |
83 | State of Palestine | 25.258 % |
84 | Kyrgyzstan | 24.799 % |
85 | Zimbabwe | 24.545 % |
86 | Mexico | 23.588 % |
87 | Papua New Guinea | 20.9 % |
88 | Vietnam | 20.598 % |
89 | Guyana | 20.376 % |
90 | Morocco | 19.215 % |
91 | Dominican Republic | 18.339 % |
92 | Brazil | 18.204 % |
93 | Turkey | 17.611 % |
94 | Argentina | 16.664 % |
95 | Belize | 15.745 % |
96 | Uzbekistan | 15.63 % |
97 | Albania | 15.4 % |
98 | Montenegro | 14.9 % |
99 | Egypt | 14.675 % |
100 | Colombia | 14.455 % |
101 | Fiji | 12.5 % |
102 | Uruguay | 12.499 % |
103 | Republic of Moldova | 12.3 % |
104 | Kiribati | 11.8 % |
105 | Suriname | 11.615 % |
106 | Georgia | 10.914 % |
107 | Kazakhstan | 10.538 % |
108 | Armenia | 10.351 % |
109 | Tunisia | 10.144 % |
110 | Turkmenistan | 9.757 % |
111 | South Korea | 9.3 % |
112 | Hungary | 9.1 % |
113 | Trinidad and Tobago | 8.72 % |
114 | Costa Rica | 8.121 % |
115 | Ireland | 7.5 % |
116 | Chile | 7.303 % |
117 | Solomon Islands | 6.05 % |
118 | Cuba | 5.299 % |
119 | Bosnia and Herzegovina | 4.5 % |
120 | Vanuatu | 4.25 % |
121 | Cayman Islands | 4.15 % |
122 | Austria | 3.312 % |
123 | Russia | 3.2 % |
124 | Romania | 2.95 % |
125 | Saint Lucia | 2.75 % |
126 | Antigua and Barbuda | 2.646 % |
127 | Samoa | 2.55 % |
128 | Ukraine | 2.5 % |
129 | Lithuania | 2 % |
130 | British Virgin Islands | 1.988 % |
131 | Oman | 1.65 % |
132 | Latvia | 1.6 % |
133 | Tuvalu | 1.45 % |
134 | Marshall Islands | 1.35 % |
135 | Nauru | 1.35 % |
136 | Tonga | 1.25 % |
137 | Palau | 1.05 % |
138 | North Macedonia | 0.8 % |
139 | United Arab Emirates | 0.65 % |
140 | Poland | 0.55 % |
141 | Canada | 0.5 % |
142 | Serbia | 0.5 % |
143 | Portugal | 0.4 % |
144 | Croatia | 0.35 % |
145 | Cyprus | 0.25 % |
146 | United States | 0.2 % |
147 | Bulgaria | 0.15 % |
148 | Sweden | 0.15 % |
149 | Bermuda | 0.1 % |
150 | Estonia | 0.1 % |
151 | Greece | 0.1 % |
152 | United Kingdom | 0.1 % |
153 | Australia | 0.085 % |
154 | Czech Republic | 0.05 % |
155 | Slovakia | 0.05 % |
156 | Malta | 0.038 % |
157 | Italy | 0.02 % |
158 | Luxembourg | 0.008 % |
159 | Belarus | 0.004 % |
160 | Andorra | 0 % |
161 | Aruba | 0 % |
162 | Belgium | 0 % |
163 | Denmark | 0 % |
164 | Finland | 0 % |
165 | France | 0 % |
166 | Germany | 0 % |
167 | Iceland | 0 % |
168 | Kuwait | 0 % |
169 | Monaco | 0 % |
170 | Netherlands | 0 % |
171 | New Zealand | 0 % |
172 | Norway | 0 % |
173 | Singapore | 0 % |
174 | Switzerland | 0 % |
↑Top 10 Countries
- #1
South Sudan
- #2
Sudan
- #3
Chad
- #4
Madagascar
- #5
Ethiopia
- #6
Guinea-Bissau
- #7
Congo, Democratic Republic of the
- #8
Mozambique
- #9
Central African Republic
- #10
Liberia
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #174
Switzerland
- #173
Singapore
- #172
Norway
- #171
New Zealand
- #170
Netherlands
- #169
Monaco
- #168
Kuwait
- #167
Iceland
- #166
Germany
- #165
France
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The statistic of "Population living in slums" serves as a critical indicator of urban poverty and living conditions worldwide. In 2010, this measure not only highlighted the socio-economic disparities among nations but also underscored the urgent need for sustainable urban development and effective housing policies. With data collected from 169 countries, this metric reveals a stark picture of global urbanization challenges, where the average percentage of populations residing in slums stood at 28.79%, with values ranging from 0% in several developed nations to a staggering 97% in South Sudan.
Global Slum Distribution in 2010
The distribution of populations living in slums in 2010 presents a significant geographical divide. The top ten countries with the highest percentages were predominantly in Africa, with South Sudan leading at 97.0038%, followed by Sudan (88.9183%), and Chad (85.9474%). This concentration highlights the acute urban challenges faced by African nations, where rapid urbanization often outpaces infrastructure development. Conversely, countries such as Denmark, Iceland, and Singapore reported 0% of their populations living in slums, reflecting robust urban planning and economic stability. This stark contrast underscores the disparities in urban living conditions and the need for targeted interventions in high-slum-population areas.
Socio-Economic Implications of Slum Living
Living in slums is often associated with inadequate access to basic services, such as clean water, sanitation, and electricity, which exacerbates poverty and limits economic opportunities. In nations like Madagascar (79.4279%) and Ethiopia (76.6954%), a significant portion of the urban populace resides in such conditions, impacting public health and economic productivity. The prevalence of slum living can hinder human capital development by affecting education and health outcomes, thereby perpetuating cycles of poverty. Addressing these socio-economic challenges requires integrated policies that not only improve housing but also enhance access to essential services and economic opportunities.
Regional Comparisons and Trends
Analyzing regional trends in 2010, Africa emerges as the continent with the highest proportion of slum dwellers, which is reflective of its urbanization pressures and economic disparities. The Democratic Republic of the Congo (74.2171%) and Mozambique (72.5272%) exemplify countries where political instability and economic constraints contribute to high slum populations. Meanwhile, Latin America, while improving, still faces challenges in countries like Bolivia and Guatemala, although not as pronounced as in African nations. These regional variations suggest that while the issue of slums is prevalent globally, its intensity and underlying causes vary, necessitating tailored regional strategies.
Policy and Development Strategies
Addressing the challenges posed by slum populations requires comprehensive policy frameworks and development strategies. In 2010, various international organizations and governments prioritized slum upgrading as part of their urban development agendas. Strategies ranged from improving infrastructure and housing conditions to promoting inclusive economic growth and social integration. For instance, the UN's focus on Sustainable Development Goals has emphasized the importance of making cities inclusive, safe, and resilient. In countries like India and Brazil, slum upgrading projects coupled with economic development initiatives have shown some success, although challenges remain in scalability and sustainability.
Future Outlook and Challenges
The persistence of slum populations in 2010 highlights the ongoing challenges in achieving sustainable urbanization. With global urban populations continuing to rise, the demand for affordable housing and infrastructure will only intensify. Future strategies must account for demographic trends, economic shifts, and environmental considerations to effectively curtail the expansion of slums. Innovations in urban planning, policy integration, and international cooperation will be crucial in transforming slums into sustainable urban communities. As nations strive towards these goals, monitoring and analyzing slum population trends will remain a vital component of global urban development efforts.
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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