Population living in slums 2004
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 | 99.8 % |
2 | Sudan | 99.1 % |
3 | Lebanon | 92.4 % |
4 | Chad | 89.329 % |
5 | Madagascar | 86.633 % |
6 | Ethiopia | 85.981 % |
7 | Congo | 84.69 % |
8 | Mozambique | 83.068 % |
9 | Central African Republic | 80.281 % |
10 | Mauritania | 77.94 % |
11 | Burundi | 77.043 % |
12 | Uganda | 75.523 % |
13 | Liberia | 75.488 % |
14 | Mali | 75.487 % |
15 | Malawi | 74.383 % |
16 | Cambodia | 73.6 % |
17 | Tanzania | 72.813 % |
18 | Sierra Leone | 72.548 % |
19 | Djibouti | 72.357 % |
20 | Eritrea | 72.357 % |
21 | Mauritius | 72.357 % |
22 | Seychelles | 72.357 % |
23 | Somalia | 72.357 % |
24 | Congo, Democratic Republic of the | 71.914 % |
25 | Burkina Faso | 71.079 % |
26 | Benin | 71.079 % |
27 | Niger | 70.154 % |
28 | Nigeria | 69.082 % |
29 | Nicaragua | 69.074 % |
30 | Pakistan | 68.172 % |
31 | Cabo Verde | 66.263 % |
32 | Comoros | 65.678 % |
33 | Rwanda | 64.458 % |
34 | Côte d'Ivoire | 63.995 % |
35 | Togo | 62.785 % |
36 | Sao Tome and Principe | 61.4 % |
37 | Zambia | 60.679 % |
38 | Nepal | 60.526 % |
39 | Kenya | 60.092 % |
40 | Senegal | 60.045 % |
41 | Equatorial Guinea | 58.83 % |
42 | Cameroon | 58.825 % |
43 | Haiti | 58.672 % |
44 | Lesotho | 58.597 % |
45 | Yemen | 58.569 % |
46 | Ecuador | 57.8 % |
47 | Bangladesh | 57.023 % |
48 | Timor-Leste | 56.1 % |
49 | Bhutan | 55.974 % |
50 | Iran | 55.974 % |
51 | Sri Lanka | 55.974 % |
52 | Eswatini | 55.352 % |
53 | Botswana | 54.447 % |
54 | Gabon | 53.688 % |
55 | Ghana | 53.648 % |
56 | Bolivia | 53.417 % |
57 | Gambia | 53.315 % |
58 | Guatemala | 51.023 % |
59 | Mongolia | 49.659 % |
60 | El Salvador | 49.5 % |
61 | Laos | 47.5 % |
62 | Philippines | 47.161 % |
63 | Peru | 43.716 % |
64 | Honduras | 43.24 % |
65 | Guinea | 42.334 % |
66 | Namibia | 42.259 % |
67 | Libya | 41.595 % |
68 | Maldives | 41.535 % |
69 | Panama | 40.053 % |
70 | Azerbaijan | 38.933 % |
71 | Kyrgyzstan | 38.215 % |
72 | Iraq | 36.983 % |
73 | Paraguay | 36.033 % |
74 | Myanmar | 35.818 % |
75 | Vietnam | 35.429 % |
76 | Brunei Darussalam | 34.127 % |
77 | Indonesia | 31.817 % |
78 | Syrian Arab Republic | 31.306 % |
79 | Egypt | 31.206 % |
80 | State of Palestine | 30 % |
81 | Mexico | 28.733 % |
82 | Brazil | 28.126 % |
83 | Morocco | 27.579 % |
84 | South Africa | 26.848 % |
85 | Zimbabwe | 26.331 % |
86 | Venezuela | 25.7 % |
87 | Dominican Republic | 25.429 % |
88 | Guyana | 25.318 % |
89 | Uzbekistan | 23.972 % |
90 | Uruguay | 23.676 % |
91 | Albania | 23 % |
92 | Turkey | 21.793 % |
93 | Republic of Moldova | 20.8 % |
94 | Papua New Guinea | 19.75 % |
95 | Angola | 19.66 % |
96 | Kazakhstan | 18.89 % |
97 | Argentina | 18.841 % |
98 | Montenegro | 18.5 % |
99 | Colombia | 18.488 % |
100 | Belize | 15.757 % |
101 | Kiribati | 15.55 % |
102 | Fiji | 15 % |
103 | Georgia | 13.215 % |
104 | Hungary | 12.9 % |
105 | Armenia | 11.818 % |
106 | Trinidad and Tobago | 11.06 % |
107 | Costa Rica | 10.866 % |
108 | Turkmenistan | 10.508 % |
109 | Solomon Islands | 10.4 % |
110 | Suriname | 9.104 % |
111 | Chile | 7.324 % |
112 | Ireland | 6.7 % |
113 | Bosnia and Herzegovina | 5.1 % |
114 | Ukraine | 4.6 % |
115 | Samoa | 4.55 % |
116 | Vanuatu | 4.55 % |
117 | Saint Lucia | 4.5 % |
118 | Austria | 4.4 % |
119 | Tuvalu | 4.25 % |
120 | Cayman Islands | 4.15 % |
121 | Romania | 3.65 % |
122 | Oman | 3.55 % |
123 | Russia | 3.5 % |
124 | Lithuania | 3.3 % |
125 | British Virgin Islands | 2.871 % |
126 | Nauru | 2.75 % |
127 | Latvia | 2.4 % |
128 | Marshall Islands | 2.2 % |
129 | Cuba | 2.154 % |
130 | Tonga | 1.8 % |
131 | Palau | 1.7 % |
132 | Poland | 1.55 % |
133 | North Macedonia | 1.3 % |
134 | Portugal | 0.95 % |
135 | United Arab Emirates | 0.95 % |
136 | Serbia | 0.6 % |
137 | Croatia | 0.4 % |
138 | Canada | 0.25 % |
139 | Greece | 0.25 % |
140 | Sweden | 0.25 % |
141 | Cyprus | 0.2 % |
142 | United States | 0.2 % |
143 | Australia | 0.145 % |
144 | Bulgaria | 0.1 % |
145 | United Kingdom | 0.1 % |
146 | Czech Republic | 0.05 % |
147 | Estonia | 0.05 % |
148 | Slovakia | 0.05 % |
149 | Malta | 0.038 % |
150 | Bermuda | 0.033 % |
151 | Italy | 0.02 % |
152 | Luxembourg | 0.001 % |
153 | Andorra | 0 % |
154 | Aruba | 0 % |
155 | Belgium | 0 % |
156 | Denmark | 0 % |
157 | Finland | 0 % |
158 | France | 0 % |
159 | Germany | 0 % |
160 | Iceland | 0 % |
161 | Kuwait | 0 % |
162 | Monaco | 0 % |
163 | Netherlands | 0 % |
164 | New Zealand | 0 % |
165 | Norway | 0 % |
166 | Singapore | 0 % |
167 | Switzerland | 0 % |
↑Top 10 Countries
- #1
South Sudan
- #2
Sudan
- #3
Lebanon
- #4
Chad
- #5
Madagascar
- #6
Ethiopia
- #7
Congo
- #8
Mozambique
- #9
Central African Republic
- #10
Mauritania
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #167
Switzerland
- #166
Singapore
- #165
Norway
- #164
New Zealand
- #163
Netherlands
- #162
Monaco
- #161
Kuwait
- #160
Iceland
- #159
Germany
- #158
France
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The term Population living in slums refers to the percentage of a country's population residing in slums, which are typically characterized by inadequate access to safe water, sanitation, and other essential services. This metric is a crucial indicator of urban poverty and living conditions worldwide. In 2004, understanding the distribution and extent of slum populations provided valuable insights into housing challenges and the quality of life in urban areas.
Urban Challenges and Living Conditions
In 2004, the global landscape of urbanization highlighted significant challenges related to living conditions in slum areas. With an average of 32.90% of people living in slums across 167 countries, this statistic underscores the pressing issues of urban poverty. Countries like South Sudan and Sudan had exceptionally high percentages, with 99.8% and 99.1% of their populations living in slums, respectively. These figures reflect severe deficiencies in urban planning and infrastructure, necessitating urgent focus from international and local policymakers to improve living conditions.
Regional Discrepancies and Economic Links
Examining the data from 2004 reveals stark regional discrepancies in slum populations. African countries dominated the list of nations with high slum populations, with Chad (89.33%) and Madagascar (86.63%) among the top. This prevalence is often linked to economic factors, where lower-income nations struggle to provide adequate housing solutions due to limited resources and rapid urban growth. Conversely, countries like Iceland, Denmark, and Singapore reported 0% of their populations living in slums, reflecting robust economic structures and effective urban management strategies.
Historical Context and Trends
The historical context of slum development is rooted in rapid urbanization and industrial growth, often outpacing the capacity for adequate housing infrastructure. In 2004, this trend continued, with many developing nations experiencing an influx of rural-to-urban migration, which increased the demand for housing in urban areas. This migration often results in informal settlements as cities cannot expand their infrastructure quickly enough to accommodate the growing population. The median value of 26.85% indicates that nearly one in four people in many countries faced substandard living conditions, emphasizing the need for historical reflection to inform future urban development policies.
Policy Influences and Development Strategies
Global and local policies play a pivotal role in addressing the challenges posed by slum dwellings. In 2004, various initiatives aimed at slum upgrading were gaining traction. These included efforts to improve housing quality, provide access to basic services, and enhance livelihood opportunities. However, the impact of such policies varied significantly between regions. Countries with advanced governance models, like New Zealand and Norway, exhibited successful integration of policy measures that eradicated slum conditions. In contrast, less developed nations struggled with implementation due to financial and logistical constraints.
Future Prospects for Urban Living
Looking forward from 2004, addressing the issue of slum populations requires a multipronged approach that incorporates economic, social, and environmental strategies. Investment in sustainable urban planning, affordable housing projects, and inclusive economic policies are essential for reducing the percentage of populations living in slums. As global awareness and international cooperation grow, there is hope for significant improvements in urban living conditions. The data from 2004 serves as a benchmark for measuring progress and identifying areas in need of targeted intervention.
In summary, the Population living in slums metric in 2004 provides a lens through which urban poverty and living conditions can be assessed. By examining regional discrepancies, historical trends, and policy impacts, we gain a deeper understanding of the challenges and opportunities in improving the lives of those residing in slum areas. Continuous efforts and strategic interventions are vital to transforming urban landscapes into sustainable and habitable environments for all.
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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