Population living in slums 2000
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.
Interactive Map
Complete Data Rankings
Rank | ||
|---|---|---|
1 | Ethiopia | 92.172 % |
2 | Chad | 91.584 % |
3 | Madagascar | 91.436 % |
4 | Mozambique | 90.096 % |
5 | Congo | 87.806 % |
6 | Central African Republic | 85.965 % |
7 | Cambodia | 84.8 % |
8 | Mauritania | 84.693 % |
9 | Mali | 83.876 % |
10 | Burkina Faso | 82.212 % |
11 | Malawi | 81.411 % |
12 | Tanzania | 81.328 % |
13 | Uganda | 80.901 % |
14 | Burundi | 79.7 % |
15 | Djibouti | 76.738 % |
16 | Eritrea | 76.738 % |
17 | Mauritius | 76.738 % |
18 | Seychelles | 76.738 % |
19 | Somalia | 76.738 % |
20 | Nigeria | 74.107 % |
21 | Sierra Leone | 73.9 % |
22 | Benin | 71.866 % |
23 | Nicaragua | 71.598 % |
24 | Rwanda | 71.421 % |
25 | Pakistan | 71.222 % |
26 | Cabo Verde | 70.867 % |
27 | Niger | 70.038 % |
28 | Togo | 69.272 % |
29 | Senegal | 67.155 % |
30 | Côte d'Ivoire | 67.077 % |
31 | Nepal | 66.31 % |
32 | Cameroon | 65.364 % |
33 | Comoros | 64.495 % |
34 | Yemen | 63.812 % |
35 | Zambia | 63.785 % |
36 | Kenya | 63.185 % |
37 | Lesotho | 62.727 % |
38 | Haiti | 61.283 % |
39 | Ghana | 60.368 % |
40 | Botswana | 58.692 % |
41 | Bangladesh | 58.311 % |
42 | Bolivia | 57.945 % |
43 | Mongolia | 57.604 % |
44 | Bhutan | 57.601 % |
45 | Iran | 57.601 % |
46 | Sri Lanka | 57.601 % |
47 | Gabon | 57.43 % |
48 | Ecuador | 57.413 % |
49 | Gambia | 56.921 % |
50 | Guatemala | 55.496 % |
51 | Eswatini | 55.352 % |
52 | Laos | 54.4 % |
53 | Equatorial Guinea | 52.916 % |
54 | Azerbaijan | 50.94 % |
55 | Philippines | 49.974 % |
56 | Panama | 48.676 % |
57 | Peru | 47.413 % |
58 | Kyrgyzstan | 47.158 % |
59 | Vietnam | 45.317 % |
60 | Honduras | 44.4 % |
61 | Namibia | 42.557 % |
62 | Egypt | 42.226 % |
63 | Paraguay | 42.027 % |
64 | Guinea | 40.665 % |
65 | Libya | 39.145 % |
66 | Brunei Darussalam | 37.411 % |
67 | Indonesia | 35.126 % |
68 | Brazil | 34.74 % |
69 | Iraq | 33.894 % |
70 | Morocco | 33.155 % |
71 | Mexico | 32.163 % |
72 | Syrian Arab Republic | 30.702 % |
73 | Dominican Republic | 30.156 % |
74 | Uzbekistan | 29.456 % |
75 | Myanmar | 29.399 % |
76 | Albania | 28.1 % |
77 | Venezuela | 27.82 % |
78 | South Africa | 27.61 % |
79 | Zimbabwe | 27.522 % |
80 | Republic of Moldova | 26.5 % |
81 | Guyana | 26.1 % |
82 | Turkey | 24.581 % |
83 | Kazakhstan | 24.458 % |
84 | Uruguay | 23.7 % |
85 | Sudan | 21.764 % |
86 | Colombia | 21.177 % |
87 | Argentina | 20.292 % |
88 | Papua New Guinea | 19.75 % |
89 | Angola | 19.7 % |
90 | Montenegro | 19.1 % |
91 | Kiribati | 18.1 % |
92 | Belize | 15.8 % |
93 | Hungary | 15.4 % |
94 | Chile | 14.616 % |
95 | Georgia | 13.6 % |
96 | Armenia | 12.796 % |
97 | Costa Rica | 12.696 % |
98 | Trinidad and Tobago | 11.06 % |
99 | Turkmenistan | 10.5 % |
100 | Solomon Islands | 10.4 % |
101 | Suriname | 7.43 % |
102 | Ireland | 6.2 % |
103 | Bosnia and Herzegovina | 5.1 % |
104 | Ukraine | 5 % |
105 | Saint Lucia | 4.85 % |
106 | Samoa | 4.55 % |
107 | Vanuatu | 4.55 % |
108 | Austria | 4.5 % |
109 | Oman | 4.25 % |
110 | Lithuania | 4.15 % |
111 | Russia | 3.65 % |
112 | Nauru | 3.6 % |
113 | British Virgin Islands | 3.46 % |
114 | Latvia | 2.85 % |
115 | Fiji | 2.218 % |
116 | Tuvalu | 2.178 % |
117 | Cuba | 2.154 % |
118 | Palau | 2.15 % |
119 | Poland | 2.1 % |
120 | El Salvador | 1.904 % |
121 | Tonga | 1.8 % |
122 | North Macedonia | 1.3 % |
123 | Portugal | 1.25 % |
124 | United Arab Emirates | 0.703 % |
125 | Serbia | 0.65 % |
126 | Croatia | 0.4 % |
127 | Sweden | 0.3 % |
128 | Canada | 0.25 % |
129 | Greece | 0.25 % |
130 | Cyprus | 0.2 % |
131 | United States | 0.2 % |
132 | Australia | 0.165 % |
133 | United Kingdom | 0.1 % |
134 | Bulgaria | 0.05 % |
135 | Czech Republic | 0.05 % |
136 | Estonia | 0.05 % |
137 | Slovakia | 0.05 % |
138 | Malta | 0.038 % |
139 | Italy | 0.02 % |
140 | Bermuda | 0.013 % |
141 | Andorra | 0 % |
142 | Aruba | 0 % |
143 | Belgium | 0 % |
144 | Denmark | 0 % |
145 | Finland | 0 % |
146 | France | 0 % |
147 | Germany | 0 % |
148 | Iceland | 0 % |
149 | Kuwait | 0 % |
150 | Luxembourg | 0 % |
151 | Monaco | 0 % |
152 | Netherlands | 0 % |
153 | New Zealand | 0 % |
154 | Norway | 0 % |
155 | Romania | 0 % |
156 | Singapore | 0 % |
157 | Switzerland | 0 % |
↑Top 10 Countries
- #1
Ethiopia
- #2
Chad
- #3
Madagascar
- #4
Mozambique
- #5
Congo
- #6
Central African Republic
- #7
Cambodia
- #8
Mauritania
- #9
Mali
- #10
Burkina Faso
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #157
Switzerland
- #156
Singapore
- #155
Romania
- #154
Norway
- #153
New Zealand
- #152
Netherlands
- #151
Monaco
- #150
Luxembourg
- #149
Kuwait
- #148
Iceland
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The turn of the millennium in 2000 presented a vivid snapshot of global urban poverty through the lens of the population living in slums—a crucial metric highlighting the stark realities of urban living conditions. This statistic, expressed in percentage terms, provides invaluable insight into the challenges and dynamics of housing and urban environments worldwide. Understanding the distribution and implications of slum populations is essential for formulating effective policies aimed at improving housing quality and reducing urban poverty.
Urban Challenges and the Prevalence of Slums in 2000
As cities across the globe expanded rapidly in 2000, the strain on urban infrastructure became increasingly evident. Countries like Ethiopia, where a staggering 92.17% of the population lived in slums, highlighted the severity of urban housing inadequacies. Similarly, Chad (91.58%) and Madagascar (91.44%) exhibited alarmingly high slum populations, underscoring the pressing need for sustainable urban development and effective housing policies. These statistics reflect a broader narrative of economic disparity and insufficient urban planning that characterized many countries at the time.
Regional Discrepancies in Slum Populations
The data from 2000 presents a clear geographic divide between regions in terms of slum populations. African countries disproportionately populated the higher end of the spectrum, with several nations reporting slum populations exceeding 80%. In stark contrast, European countries such as Germany, Finland, and France reported 0% of their population living in slums, demonstrating the benefits of robust infrastructure and comprehensive social policies. These regional discrepancies reveal not only the varying levels of economic development but also the differing efficacy of urban governance and planning strategies implemented across continents.
Interplay of Economic Factors and Environmental Conditions
The prevalence of slum populations in 2000 was intrinsically linked to a country's economic landscape and environmental conditions. Nations with limited economic resources struggled to provide adequate housing, resulting in widespread slum settlements. Countries such as Mozambique (90.10%) and the Central African Republic (85.97%) faced economic challenges that were exacerbated by environmental factors like land degradation and climate change, which further strained urban resources. Understanding this interplay is crucial for developing targeted interventions that address both economic and environmental dimensions of slum living.
Policy Interventions and Future Directions
Addressing the high percentage of populations living in slums requires comprehensive policy interventions focusing on urban infrastructure development, affordable housing, and economic empowerment. As demonstrated by countries with lower slum populations, such as the Netherlands and Norway, investment in housing, healthcare, and education can significantly reduce slum prevalence. Moving forward, international collaboration and sustainable development goals should prioritize urban poverty alleviation, ensuring that future urbanization leads to inclusive and resilient cities. By learning from the experiences of 2000, policymakers can craft solutions that not only improve living conditions but also foster sustainable urban growth.
Historical Perspective and Prospects for Change
Reflecting on the statistics from 2000 provides a historical perspective on the evolution of urban poverty and housing challenges. The data illustrates how deeply rooted issues such as economic inequality and inadequate urban planning contributed to the proliferation of slums. The lessons learned from this period underscore the importance of proactive policy measures and the need for continuous monitoring of urban development indicators. As the world progresses, adopting an integrated approach that considers economic, social, and environmental factors will be essential in reducing slum populations and improving quality of life for urban dwellers worldwide.
In conclusion, the year 2000 painted a complex picture of global disparities in slum populations, driven by a multitude of factors including economic conditions, regional differences, and policy frameworks. By addressing these underlying issues with targeted strategies, the international community can work towards a future where urban poverty is significantly reduced, and all people have access to safe and sustainable living 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.
Visit Data SourceHistorical Data by Year
Explore Population living in slums data across different years. Compare trends and see how statistics have changed over time.
More People and Society Facts
Currently married (Percent)
The percentage of currently married individuals by country highlights societal trends in family structure and relationships. Understanding these statistics can provide insights into cultural norms and demographic shifts, influencing policies and social programs.
View dataBrowse All People and Society
Explore more facts and statistics in this category
All Categories
Discover more categories with comprehensive global data