Population living in slums 2013
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 | 94.201 % |
2 | Chad | 84.256 % |
3 | Sudan | 81.291 % |
4 | Madagascar | 75.826 % |
5 | Congo, Democratic Republic of the | 75.599 % |
6 | Guinea-Bissau | 73.443 % |
7 | Ethiopia | 72.053 % |
8 | Niger | 70.415 % |
9 | Benin | 69.309 % |
10 | Central African Republic | 68.913 % |
11 | Afghanistan | 68.468 % |
12 | Liberia | 68.348 % |
13 | Comoros | 68.342 % |
14 | Mozambique | 67.257 % |
15 | Uganda | 63.423 % |
16 | Mauritania | 62.745 % |
17 | Equatorial Guinea | 61.902 % |
18 | Pakistan | 61.311 % |
19 | Djibouti | 60.85 % |
20 | Eritrea | 60.85 % |
21 | Mauritius | 60.85 % |
22 | Seychelles | 60.85 % |
23 | Somalia | 60.85 % |
24 | Sierra Leone | 60.228 % |
25 | Malawi | 58.57 % |
26 | Ecuador | 57.8 % |
27 | Nigeria | 57.776 % |
28 | Côte d'Ivoire | 57.062 % |
29 | Congo | 56.647 % |
30 | Mali | 56.61 % |
31 | Sao Tome and Principe | 55.551 % |
32 | Cabo Verde | 55.199 % |
33 | Bangladesh | 54.124 % |
34 | Zambia | 53.692 % |
35 | Tanzania | 53.653 % |
36 | Kenya | 53.133 % |
37 | Burundi | 52.912 % |
38 | Haiti | 52.797 % |
39 | Bhutan | 52.569 % |
40 | Iran | 52.569 % |
41 | Sri Lanka | 52.569 % |
42 | Myanmar | 50.258 % |
43 | Rwanda | 48.793 % |
44 | Cambodia | 48.2 % |
45 | Togo | 48.19 % |
46 | Nepal | 47.512 % |
47 | Angola | 47.252 % |
48 | Yemen | 46.772 % |
49 | Bolivia | 46.626 % |
50 | Peru | 46.568 % |
51 | Guinea | 46.088 % |
52 | Burkina Faso | 46.032 % |
53 | Gabon | 45.268 % |
54 | Gambia | 45.203 % |
55 | Botswana | 44.895 % |
56 | Cameroon | 44.114 % |
57 | Senegal | 44.047 % |
58 | Timor-Leste | 44 % |
59 | Iraq | 43.933 % |
60 | Namibia | 41.588 % |
61 | Guatemala | 40.958 % |
62 | Philippines | 40.834 % |
63 | Lesotho | 40.01 % |
64 | Ghana | 38.527 % |
65 | Maldives | 38.19 % |
66 | Honduras | 32.71 % |
67 | Laos | 32.1 % |
68 | Mongolia | 31.783 % |
69 | Algeria | 26.934 % |
70 | Brunei Darussalam | 26.171 % |
71 | Venezuela | 25.7 % |
72 | El Salvador | 25.481 % |
73 | South Africa | 25.134 % |
74 | Syrian Arab Republic | 24.782 % |
75 | Indonesia | 24.373 % |
76 | Zimbabwe | 23.652 % |
77 | Azerbaijan | 23.025 % |
78 | Paraguay | 22.546 % |
79 | State of Palestine | 22.398 % |
80 | Libya | 22.277 % |
81 | Eswatini | 21.944 % |
82 | Papua New Guinea | 21.475 % |
83 | Mexico | 21.015 % |
84 | Panama | 20.651 % |
85 | Kyrgyzstan | 18.091 % |
86 | Guyana | 17.906 % |
87 | Belize | 15.739 % |
88 | Argentina | 15.569 % |
89 | Turkey | 15.52 % |
90 | Morocco | 15.033 % |
91 | Brazil | 14.897 % |
92 | Dominican Republic | 14.794 % |
93 | Vietnam | 13.182 % |
94 | Montenegro | 13 % |
95 | Suriname | 12.871 % |
96 | Colombia | 12.438 % |
97 | Albania | 11.6 % |
98 | Uzbekistan | 11.443 % |
99 | Fiji | 10.9 % |
100 | Lebanon | 10.793 % |
101 | Kiribati | 9.975 % |
102 | Georgia | 9.763 % |
103 | Armenia | 9.617 % |
104 | Tunisia | 9.394 % |
105 | Turkmenistan | 9.382 % |
106 | Republic of Moldova | 7.95 % |
107 | Ireland | 7.85 % |
108 | Trinidad and Tobago | 7.72 % |
109 | Hungary | 7.55 % |
110 | Chile | 7.309 % |
111 | Uruguay | 6.91 % |
112 | Cuba | 6.872 % |
113 | Nicaragua | 6.821 % |
114 | Costa Rica | 6.748 % |
115 | Egypt | 6.41 % |
116 | Kazakhstan | 6.362 % |
117 | South Korea | 5.85 % |
118 | Bosnia and Herzegovina | 4.15 % |
119 | Cayman Islands | 4.15 % |
120 | Vanuatu | 4.075 % |
121 | Solomon Islands | 3.875 % |
122 | Russia | 3.075 % |
123 | Antigua and Barbuda | 2.646 % |
124 | Romania | 2.525 % |
125 | Austria | 2.495 % |
126 | Saint Lucia | 1.9 % |
127 | British Virgin Islands | 1.639 % |
128 | Samoa | 1.5 % |
129 | Ukraine | 1.45 % |
130 | Lithuania | 1.325 % |
131 | Latvia | 1.175 % |
132 | Tonga | 1.025 % |
133 | Marshall Islands | 0.875 % |
134 | Tuvalu | 0.778 % |
135 | Oman | 0.75 % |
136 | Palau | 0.75 % |
137 | Nauru | 0.725 % |
138 | Canada | 0.6 % |
139 | North Macedonia | 0.575 % |
140 | Serbia | 0.475 % |
141 | United Arab Emirates | 0.45 % |
142 | Croatia | 0.3 % |
143 | Cyprus | 0.25 % |
144 | Portugal | 0.2 % |
145 | United States | 0.2 % |
146 | Bulgaria | 0.175 % |
147 | Poland | 0.15 % |
148 | Sweden | 0.15 % |
149 | Bermuda | 0.1 % |
150 | Estonia | 0.1 % |
151 | United Kingdom | 0.1 % |
152 | Australia | 0.055 % |
153 | Czech Republic | 0.05 % |
154 | Slovakia | 0.05 % |
155 | Malta | 0.038 % |
156 | Greece | 0.025 % |
157 | Italy | 0.02 % |
158 | Luxembourg | 0.012 % |
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 | Qatar | 0 % |
174 | Singapore | 0 % |
175 | Switzerland | 0 % |
- #1
South Sudan
- #2
Chad
- #3
Sudan
- #4
Madagascar
- #5
Congo, Democratic Republic of the
- #6
Guinea-Bissau
- #7
Ethiopia
- #8
Niger
- #9
Benin
- #10
Central African Republic
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
- #175
Switzerland
- #174
Singapore
- #173
Qatar
- #172
Norway
- #171
New Zealand
- #170
Netherlands
- #169
Monaco
- #168
Kuwait
- #167
Iceland
- #166
Germany
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
In 2013, South Sudan had the highest Population living in slums at 94.20%, while several countries, including Denmark and Monaco, reported 0%. The global range highlights the stark contrast in urban living conditions. The average percentage of populations residing in slums globally was 25.91%, providing a baseline for understanding the extent of urban poverty worldwide.
Economic and Political Drivers of Slum Populations
The prevalence of slum populations often correlates with economic and political instability. Countries like South Sudan and Chad, with slum populations of 94.20% and 84.26% respectively, face significant challenges such as ongoing conflict and underdeveloped infrastructure. These conditions exacerbate urban poverty, limiting access to adequate housing.
In contrast, wealthier nations with stable governance, such as Denmark and Switzerland, report 0% of their population living in slums. These countries benefit from robust social safety nets and effective urban planning policies, which prevent the formation of slums by ensuring access to affordable housing and essential services.
Geographical and Environmental Influences
Geographical factors also play a crucial role in the concentration of slum populations. In Madagascar and the Democratic Republic of the Congo, where slum populations are 75.83% and 75.60% respectively, the challenging terrain and frequent natural disasters hinder infrastructure development. These environmental challenges make it difficult to provide sustainable urban housing solutions.
Conversely, countries like Monaco and Qatar benefit from advantageous geographical locations and resource wealth, allowing them to invest heavily in urban infrastructure. This investment reduces the likelihood of slum development, as seen in their 0% slum population statistics.
Year-Over-Year Trends and Policy Implications
The year-over-year changes in slum populations offer insights into the effectiveness of policies and economic conditions. Lebanon saw a significant decrease of 36.8% in its slum population, reflecting successful policy interventions and possibly international aid efforts. Similarly, Azerbaijan and Eswatini experienced reductions of 14.5%, indicating improvements in housing policies or economic conditions.
In contrast, Angola experienced a 6.9% increase in its slum population, highlighting the challenges of rapid urbanization without corresponding infrastructure development. Similarly, Myanmar and Afghanistan saw increases of 3.3% and 1.8%, respectively, suggesting ongoing struggles with political instability and economic development.
Addressing Urban Poverty Through Strategic Initiatives
Understanding the factors that contribute to high slum populations is crucial for developing effective strategies to combat urban poverty. Countries with high percentages, such as Niger at 70.41% and Benin at 69.31%, require targeted interventions that address both immediate housing needs and long-term economic development.
Successful approaches often include investments in affordable housing, improvements in urban infrastructure, and policies that stimulate economic growth. Additionally, international cooperation and aid can play a pivotal role in supporting countries with limited resources to address these challenges effectively.
By examining the data and understanding the underlying causes, policymakers and global organizations can tailor their efforts to reduce the proportion of populations living in slums, ultimately improving the quality of life for millions worldwide.
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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