Population living in slums 2007
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 | 99.803 % |
2 | Sudan | 96.546 % |
3 | Chad | 87.638 % |
4 | Madagascar | 83.03 % |
5 | Ethiopia | 81.338 % |
6 | Lebanon | 79.856 % |
7 | Mozambique | 77.798 % |
8 | Central African Republic | 76.018 % |
9 | Congo | 75.342 % |
10 | Liberia | 73.703 % |
11 | Mauritania | 72.875 % |
12 | Congo, Democratic Republic of the | 72.835 % |
13 | Uganda | 71.49 % |
14 | Benin | 70.489 % |
15 | Niger | 70.241 % |
16 | Mali | 69.195 % |
17 | Malawi | 69.112 % |
18 | Burundi | 68.999 % |
19 | Djibouti | 68.65 % |
20 | Eritrea | 68.65 % |
21 | Mauritius | 68.65 % |
22 | Seychelles | 68.65 % |
23 | Somalia | 68.65 % |
24 | Sierra Leone | 68.441 % |
25 | Nicaragua | 67.506 % |
26 | Comoros | 66.566 % |
27 | Tanzania | 66.426 % |
28 | Pakistan | 65.885 % |
29 | Nigeria | 65.313 % |
30 | Cambodia | 65.1 % |
31 | Afghanistan | 63.6 % |
32 | Burkina Faso | 62.73 % |
33 | Cabo Verde | 62.63 % |
34 | Côte d'Ivoire | 61.684 % |
35 | Sao Tome and Principe | 60.899 % |
36 | Equatorial Guinea | 59.514 % |
37 | Rwanda | 59.236 % |
38 | Zambia | 58.35 % |
39 | Togo | 57.92 % |
40 | Ecuador | 57.8 % |
41 | Kenya | 57.772 % |
42 | Haiti | 56.714 % |
43 | Nepal | 56.188 % |
44 | Bangladesh | 56.056 % |
45 | Timor-Leste | 55.05 % |
46 | Bhutan | 54.874 % |
47 | Iran | 54.874 % |
48 | Sri Lanka | 54.874 % |
49 | Senegal | 54.712 % |
50 | Yemen | 54.637 % |
51 | Cameroon | 53.922 % |
52 | Lesotho | 52.401 % |
53 | Botswana | 51.263 % |
54 | Gabon | 50.881 % |
55 | Gambia | 50.611 % |
56 | Bolivia | 50.021 % |
57 | Ghana | 48.608 % |
58 | Guatemala | 47.668 % |
59 | Philippines | 45.052 % |
60 | Eswatini | 44.216 % |
61 | Mongolia | 43.7 % |
62 | Guinea | 43.585 % |
63 | El Salvador | 43.49 % |
64 | Laos | 42.4 % |
65 | Namibia | 42.035 % |
66 | Maldives | 41.256 % |
67 | Peru | 40.942 % |
68 | Myanmar | 40.631 % |
69 | Honduras | 39.73 % |
70 | Iraq | 39.3 % |
71 | Panama | 33.586 % |
72 | Libya | 33.076 % |
73 | Paraguay | 31.537 % |
74 | Kyrgyzstan | 31.507 % |
75 | Brunei Darussalam | 31.464 % |
76 | Algeria | 30.8 % |
77 | Azerbaijan | 29.928 % |
78 | Syrian Arab Republic | 29.486 % |
79 | Indonesia | 29.336 % |
80 | Angola | 28.858 % |
81 | State of Palestine | 28.118 % |
82 | Vietnam | 28.013 % |
83 | South Africa | 26.277 % |
84 | Mexico | 26.16 % |
85 | Venezuela | 25.7 % |
86 | Zimbabwe | 25.438 % |
87 | Morocco | 23.397 % |
88 | Brazil | 23.165 % |
89 | Egypt | 22.941 % |
90 | Guyana | 22.847 % |
91 | Dominican Republic | 21.884 % |
92 | Papua New Guinea | 20.3 % |
93 | Uzbekistan | 19.8 % |
94 | Turkey | 19.702 % |
95 | Albania | 19.2 % |
96 | Uruguay | 18.087 % |
97 | Argentina | 17.752 % |
98 | Montenegro | 16.7 % |
99 | Republic of Moldova | 16.55 % |
100 | Colombia | 16.471 % |
101 | Belize | 15.751 % |
102 | Kazakhstan | 14.714 % |
103 | Fiji | 14 % |
104 | Kiribati | 13.725 % |
105 | Georgia | 12.064 % |
106 | South Korea | 11.925 % |
107 | Armenia | 11.084 % |
108 | Hungary | 11 % |
109 | Tunisia | 10.4 % |
110 | Suriname | 10.36 % |
111 | Turkmenistan | 10.132 % |
112 | Trinidad and Tobago | 9.89 % |
113 | Costa Rica | 9.493 % |
114 | Solomon Islands | 8.225 % |
115 | Chile | 7.3 % |
116 | Ireland | 7.05 % |
117 | Bosnia and Herzegovina | 4.8 % |
118 | Vanuatu | 4.4 % |
119 | Cayman Islands | 4.15 % |
120 | Austria | 4.128 % |
121 | Cuba | 3.727 % |
122 | Saint Lucia | 3.625 % |
123 | Samoa | 3.55 % |
124 | Ukraine | 3.55 % |
125 | Romania | 3.375 % |
126 | Russia | 3.325 % |
127 | Tuvalu | 3.15 % |
128 | Lithuania | 2.625 % |
129 | Oman | 2.6 % |
130 | British Virgin Islands | 2.43 % |
131 | Nauru | 2.05 % |
132 | Latvia | 2 % |
133 | Marshall Islands | 1.825 % |
134 | Tonga | 1.55 % |
135 | Palau | 1.4 % |
136 | North Macedonia | 1.075 % |
137 | Poland | 1.05 % |
138 | United Arab Emirates | 0.875 % |
139 | Portugal | 0.65 % |
140 | Serbia | 0.575 % |
141 | Canada | 0.375 % |
142 | Croatia | 0.35 % |
143 | Cyprus | 0.25 % |
144 | Sweden | 0.225 % |
145 | United States | 0.2 % |
146 | Greece | 0.175 % |
147 | Bulgaria | 0.125 % |
148 | Australia | 0.115 % |
149 | Bermuda | 0.1 % |
150 | Estonia | 0.1 % |
151 | United Kingdom | 0.1 % |
152 | Czech Republic | 0.05 % |
153 | Slovakia | 0.05 % |
154 | Malta | 0.038 % |
155 | Italy | 0.02 % |
156 | Luxembourg | 0.005 % |
157 | Andorra | 0 % |
158 | Aruba | 0 % |
159 | Belgium | 0 % |
160 | Denmark | 0 % |
161 | Finland | 0 % |
162 | France | 0 % |
163 | Germany | 0 % |
164 | Iceland | 0 % |
165 | Kuwait | 0 % |
166 | Monaco | 0 % |
167 | Netherlands | 0 % |
168 | New Zealand | 0 % |
169 | Norway | 0 % |
170 | Singapore | 0 % |
171 | Switzerland | 0 % |
- #1
South Sudan
- #2
Sudan
- #3
Chad
- #4
Madagascar
- #5
Ethiopia
- #6
Lebanon
- #7
Mozambique
- #8
Central African Republic
- #9
Congo
- #10
Liberia
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
- #171
Switzerland
- #170
Singapore
- #169
Norway
- #168
New Zealand
- #167
Netherlands
- #166
Monaco
- #165
Kuwait
- #164
Iceland
- #163
Germany
- #162
France
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
In 2007, South Sudan had the highest percentage of its population living in slums at 99.80%, while Singapore, Andorra, and several other countries reported 0%. The global range for "Population living in slums" in 2007 spanned from 0% to 99.80%. The average percentage of populations living in slums across 171 countries was 30.80%, with a median of 25.44%.
Economic and Geographic Drivers of Slum Populations
The stark differences in slum populations across countries can often be attributed to economic conditions and geographic factors. For example, countries like Sudan and Chad, with slum populations of 96.55% and 87.64% respectively, face significant economic challenges, including high poverty rates and limited infrastructure development. These conditions are exacerbated by political instability and lack of investment in urban planning, which contribute to the proliferation of slums.
In contrast, countries such as Singapore and Switzerland, with 0% of their populations living in slums, benefit from robust economies and well-developed urban infrastructures. These nations have implemented effective housing policies and urban planning strategies that prevent the emergence of slum conditions. The geographic concentration of resources and efficient governance in these countries further supports sustainable urban living conditions.
Urbanization and Its Impact on Slum Growth
Rapid urbanization is a significant factor influencing slum growth, particularly in African and Asian countries. Madagascar and Ethiopia, with slum populations of 83.03% and 81.34%, respectively, are examples where urban expansion has outpaced the capacity of cities to provide adequate housing and services. This mismatch often leads to the formation of slums as migrants from rural areas seek opportunities in urban centers.
In Lebanon, where 79.86% of the population lived in slums, rapid urbanization coupled with regional conflicts has strained housing resources, leading to an increase in slum settlements. The lack of affordable housing options in rapidly growing cities forces many to reside in informal settlements.
Trends in Slum Population Changes
Between years, countries have seen varying trends in slum population changes. Notably, Lebanon experienced a significant decrease of 12.55% in its slum population, a reduction of 13.6%. This decline can be attributed to international aid and domestic efforts to improve housing conditions and infrastructure.
Conversely, Angola saw an increase of 3.07% in its slum population, marking an 11.9% rise. This increase may be linked to ongoing urbanization pressures and economic factors that limit the development of formal housing. Similarly, Myanmar and Iraq experienced rises in slum populations by 1.60% and 0.77%, respectively, highlighting the challenges in managing urban growth and ensuring adequate housing.
Policy Implications and Future Outlook
The data on slum populations underscores the need for targeted policy interventions to address urban poverty and improve living conditions. Countries with high slum populations, like South Sudan and Sudan, require comprehensive strategies that include investment in affordable housing, infrastructure development, and socioeconomic support to uplift urban populations.
For nations with negligible slum populations, maintaining effective urban planning and housing policies remains crucial to prevent future slum growth. The global average of 30.80% signifies a substantial portion of the world's population living in substandard conditions, highlighting the ongoing challenge of urbanization and the need for sustainable development practices. Addressing these issues is essential for improving quality of life and achieving equitable urban growth 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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