Population living in slums 2003
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 | 89.893 % |
5 | Madagascar | 87.833 % |
6 | Ethiopia | 87.529 % |
7 | Congo | 86.248 % |
8 | Mozambique | 84.825 % |
9 | Central African Republic | 81.702 % |
10 | Mauritania | 79.628 % |
11 | Burundi | 78.372 % |
12 | Mali | 77.584 % |
13 | Uganda | 76.868 % |
14 | Cambodia | 76.4 % |
15 | Malawi | 76.14 % |
16 | Liberia | 75.488 % |
17 | Tanzania | 74.942 % |
18 | Burkina Faso | 73.862 % |
19 | Djibouti | 73.559 % |
20 | Eritrea | 73.559 % |
21 | Mauritius | 73.559 % |
22 | Seychelles | 73.559 % |
23 | Somalia | 73.559 % |
24 | Sierra Leone | 73.224 % |
25 | Congo, Democratic Republic of the | 71.914 % |
26 | Benin | 71.276 % |
27 | Nigeria | 70.339 % |
28 | Niger | 70.125 % |
29 | Nicaragua | 69.705 % |
30 | Pakistan | 68.935 % |
31 | Cabo Verde | 67.446 % |
32 | Rwanda | 66.199 % |
33 | Comoros | 65.382 % |
34 | Côte d'Ivoire | 64.766 % |
35 | Togo | 64.407 % |
36 | Nepal | 61.972 % |
37 | Senegal | 61.822 % |
38 | Zambia | 61.456 % |
39 | Kenya | 60.865 % |
40 | Lesotho | 60.662 % |
41 | Cameroon | 60.46 % |
42 | Yemen | 59.88 % |
43 | Equatorial Guinea | 59.461 % |
44 | Haiti | 59.325 % |
45 | Ecuador | 57.824 % |
46 | Bangladesh | 57.345 % |
47 | Bhutan | 56.383 % |
48 | Iran | 56.383 % |
49 | Sri Lanka | 56.383 % |
50 | Botswana | 55.508 % |
51 | Eswatini | 55.352 % |
52 | Ghana | 55.328 % |
53 | Gabon | 54.623 % |
54 | Bolivia | 54.549 % |
55 | Gambia | 54.216 % |
56 | Guatemala | 52.141 % |
57 | Mongolia | 51.645 % |
58 | El Salvador | 49.5 % |
59 | Laos | 49.25 % |
60 | Philippines | 47.864 % |
61 | Peru | 44.64 % |
62 | Honduras | 43.82 % |
63 | Libya | 43.428 % |
64 | Namibia | 42.333 % |
65 | Panama | 42.209 % |
66 | Azerbaijan | 41.935 % |
67 | Guinea | 41.917 % |
68 | Kyrgyzstan | 40.451 % |
69 | Vietnam | 37.901 % |
70 | Paraguay | 37.531 % |
71 | Iraq | 36.211 % |
72 | Brunei Darussalam | 34.958 % |
73 | Myanmar | 34.213 % |
74 | Egypt | 33.961 % |
75 | Indonesia | 32.644 % |
76 | Syrian Arab Republic | 31.686 % |
77 | State of Palestine | 30 % |
78 | Brazil | 29.779 % |
79 | Mexico | 29.59 % |
80 | Morocco | 28.973 % |
81 | South Africa | 27.038 % |
82 | Zimbabwe | 26.629 % |
83 | Dominican Republic | 26.61 % |
84 | Venezuela | 26.053 % |
85 | Guyana | 25.709 % |
86 | Uzbekistan | 25.352 % |
87 | Albania | 24.25 % |
88 | Uruguay | 23.688 % |
89 | Turkey | 22.49 % |
90 | Republic of Moldova | 22.25 % |
91 | Kazakhstan | 20.282 % |
92 | Papua New Guinea | 19.75 % |
93 | Angola | 19.68 % |
94 | Argentina | 19.203 % |
95 | Colombia | 19.16 % |
96 | Montenegro | 18.8 % |
97 | Kiribati | 16.175 % |
98 | Belize | 15.759 % |
99 | Fiji | 15 % |
100 | Hungary | 13.55 % |
101 | Georgia | 13.407 % |
102 | Armenia | 12.062 % |
103 | Costa Rica | 11.323 % |
104 | Trinidad and Tobago | 11.06 % |
105 | Turkmenistan | 10.504 % |
106 | Solomon Islands | 10.4 % |
107 | Chile | 9.147 % |
108 | Suriname | 8.686 % |
109 | Ireland | 6.55 % |
110 | Bosnia and Herzegovina | 5.1 % |
111 | Ukraine | 4.8 % |
112 | Saint Lucia | 4.675 % |
113 | Samoa | 4.55 % |
114 | Vanuatu | 4.55 % |
115 | Austria | 4.4 % |
116 | Tuvalu | 4.25 % |
117 | Cayman Islands | 4.15 % |
118 | Oman | 3.775 % |
119 | Romania | 3.65 % |
120 | Russia | 3.525 % |
121 | Lithuania | 3.5 % |
122 | British Virgin Islands | 3.019 % |
123 | Nauru | 2.95 % |
124 | Latvia | 2.575 % |
125 | Marshall Islands | 2.2 % |
126 | Cuba | 2.154 % |
127 | Palau | 1.825 % |
128 | Tonga | 1.8 % |
129 | Poland | 1.675 % |
130 | North Macedonia | 1.3 % |
131 | Portugal | 1.025 % |
132 | United Arab Emirates | 0.95 % |
133 | Serbia | 0.625 % |
134 | Croatia | 0.4 % |
135 | Canada | 0.25 % |
136 | Greece | 0.25 % |
137 | Sweden | 0.25 % |
138 | Cyprus | 0.2 % |
139 | United States | 0.2 % |
140 | Australia | 0.155 % |
141 | Bulgaria | 0.1 % |
142 | United Kingdom | 0.1 % |
143 | Czech Republic | 0.05 % |
144 | Estonia | 0.05 % |
145 | Slovakia | 0.05 % |
146 | Malta | 0.038 % |
147 | Bermuda | 0.028 % |
148 | Italy | 0.02 % |
149 | Luxembourg | 0 % |
150 | Andorra | 0 % |
151 | Aruba | 0 % |
152 | Belgium | 0 % |
153 | Denmark | 0 % |
154 | Finland | 0 % |
155 | France | 0 % |
156 | Germany | 0 % |
157 | Iceland | 0 % |
158 | Kuwait | 0 % |
159 | Monaco | 0 % |
160 | Netherlands | 0 % |
161 | New Zealand | 0 % |
162 | Norway | 0 % |
163 | Singapore | 0 % |
164 | Switzerland | 0 % |
- #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.
- #164
Switzerland
- #163
Singapore
- #162
Norway
- #161
New Zealand
- #160
Netherlands
- #159
Monaco
- #158
Kuwait
- #157
Iceland
- #156
Germany
- #155
France
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
In 2003, South Sudan had the highest Population living in slums at 99.8%, while several countries, including Finland and Netherlands, reported a rate of 0%. This disparity highlights significant global differences in urban living conditions. The average percentage of populations living in slums globally was 33.14%, indicating that a substantial portion of urban populations faced inadequate housing conditions.
Factors Influencing High Slum Populations
The prevalence of slum populations is often driven by rapid urbanization, economic challenges, and inadequate infrastructure. In South Sudan and Sudan, with slum populations at 99.8% and 99.1% respectively, civil conflict and economic instability have exacerbated urban poverty. These countries face challenges such as insufficient housing policies and lack of investment in urban infrastructure.
In Lebanon, where 92.4% of the population lived in slums, geopolitical tensions and the influx of refugees have strained urban resources, leading to overcrowded and underdeveloped living areas. Similarly, in Chad and Madagascar, slum populations of 89.89% and 87.83% reflect a combination of economic constraints and limited governmental capacity to provide adequate housing.
Low Slum Populations: Effective Urban Planning
Countries with low slum populations, such as Finland, Netherlands, and Kuwait, all reporting 0%, benefit from robust urban planning and strong economic frameworks. These nations have implemented effective housing policies and possess the economic resources necessary to maintain quality urban infrastructure. The political stability and efficient governance in these countries further support sustainable urban development, reducing the likelihood of slum formation.
In regions like Singapore and Denmark, strategic investments in public housing and urban development have created environments where slums are virtually nonexistent. These countries exemplify how targeted policies and investment can lead to improved living conditions and the elimination of urban poverty pockets.
Year-over-Year Trends and Changes
Globally, there was an average year-over-year decrease of 0.66% in slum populations, marking a positive trend towards improved urban conditions. Azerbaijan experienced the most significant decrease at -3.00%, reflecting successful governmental initiatives to improve housing and urban infrastructure. Similarly, Cambodia and Burkina Faso saw reductions of -2.80% and -2.78% respectively, suggesting effective policy interventions.
Conversely, some countries saw increases in slum populations. Myanmar experienced a rise of 1.60%, largely due to ongoing political and economic challenges that have hindered urban development. Increases in Iraq and Suriname by 0.77% and 0.42% highlight how conflict and economic volatility can reverse progress in urban housing conditions.
Implications for Policy and Development
The data from 2003 underscores the need for comprehensive urban development policies that address housing shortages and improve living conditions. Countries with high slum populations require targeted interventions, including investment in affordable housing, infrastructure development, and poverty alleviation programs. These efforts are essential to reducing urban inequality and enhancing the quality of life for millions living in slums.
For countries with low slum populations, maintaining effective urban planning and economic stability is crucial to sustaining their success. Sharing best practices and fostering international cooperation can aid countries struggling with slum issues, promoting global progress towards sustainable urban environments.
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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