Population living in slums 2002
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 | South Sudan | 99.8 % |
2 | Sudan | 99.1 % |
3 | Lebanon | 92.4 % |
4 | Chad | 90.457 % |
5 | Ethiopia | 89.076 % |
6 | Madagascar | 89.034 % |
7 | Congo | 87.806 % |
8 | Mozambique | 86.582 % |
9 | Central African Republic | 83.123 % |
10 | Mauritania | 81.317 % |
11 | Burundi | 79.7 % |
12 | Mali | 79.682 % |
13 | Cambodia | 79.2 % |
14 | Uganda | 78.212 % |
15 | Malawi | 77.897 % |
16 | Tanzania | 77.07 % |
17 | Burkina Faso | 76.645 % |
18 | Liberia | 75.488 % |
19 | Djibouti | 74.762 % |
20 | Eritrea | 74.762 % |
21 | Mauritius | 74.762 % |
22 | Seychelles | 74.762 % |
23 | Somalia | 74.762 % |
24 | Sierra Leone | 73.9 % |
25 | Congo, Democratic Republic of the | 71.914 % |
26 | Nigeria | 71.595 % |
27 | Benin | 71.472 % |
28 | Nicaragua | 70.336 % |
29 | Niger | 70.096 % |
30 | Pakistan | 69.697 % |
31 | Cabo Verde | 68.628 % |
32 | Rwanda | 67.939 % |
33 | Togo | 66.029 % |
34 | Côte d'Ivoire | 65.536 % |
35 | Comoros | 65.086 % |
36 | Senegal | 63.6 % |
37 | Nepal | 63.418 % |
38 | Lesotho | 62.727 % |
39 | Zambia | 62.232 % |
40 | Cameroon | 62.095 % |
41 | Kenya | 61.638 % |
42 | Yemen | 61.191 % |
43 | Equatorial Guinea | 60.093 % |
44 | Haiti | 59.978 % |
45 | Ecuador | 57.847 % |
46 | Bangladesh | 57.667 % |
47 | Ghana | 57.008 % |
48 | Bhutan | 56.792 % |
49 | Iran | 56.792 % |
50 | Sri Lanka | 56.792 % |
51 | Botswana | 56.57 % |
52 | Bolivia | 55.681 % |
53 | Gabon | 55.559 % |
54 | Eswatini | 55.352 % |
55 | Gambia | 55.118 % |
56 | Mongolia | 53.632 % |
57 | Guatemala | 53.259 % |
58 | Laos | 51 % |
59 | El Salvador | 49.5 % |
60 | Philippines | 48.568 % |
61 | Peru | 45.564 % |
62 | Libya | 45.262 % |
63 | Azerbaijan | 44.937 % |
64 | Honduras | 44.4 % |
65 | Panama | 44.365 % |
66 | Kyrgyzstan | 42.687 % |
67 | Namibia | 42.408 % |
68 | Guinea | 41.5 % |
69 | Vietnam | 40.373 % |
70 | Paraguay | 39.03 % |
71 | Egypt | 36.716 % |
72 | Brunei Darussalam | 35.789 % |
73 | Iraq | 35.439 % |
74 | Indonesia | 33.472 % |
75 | Myanmar | 32.608 % |
76 | Syrian Arab Republic | 32.066 % |
77 | Brazil | 31.433 % |
78 | Mexico | 30.448 % |
79 | Morocco | 30.367 % |
80 | State of Palestine | 30 % |
81 | Dominican Republic | 27.792 % |
82 | South Africa | 27.229 % |
83 | Zimbabwe | 26.926 % |
84 | Uzbekistan | 26.731 % |
85 | Venezuela | 26.407 % |
86 | Guyana | 26.1 % |
87 | Albania | 25.5 % |
88 | Republic of Moldova | 23.7 % |
89 | Uruguay | 23.7 % |
90 | Turkey | 23.187 % |
91 | Kazakhstan | 21.674 % |
92 | Colombia | 19.832 % |
93 | Papua New Guinea | 19.75 % |
94 | Angola | 19.7 % |
95 | Argentina | 19.566 % |
96 | Montenegro | 19.1 % |
97 | Kiribati | 16.8 % |
98 | Belize | 15.761 % |
99 | Fiji | 15 % |
100 | Hungary | 14.2 % |
101 | Georgia | 13.6 % |
102 | Armenia | 12.307 % |
103 | Costa Rica | 11.781 % |
104 | Trinidad and Tobago | 11.06 % |
105 | Chile | 10.97 % |
106 | Turkmenistan | 10.5 % |
107 | Solomon Islands | 10.4 % |
108 | Suriname | 8.267 % |
109 | Ireland | 6.4 % |
110 | Bosnia and Herzegovina | 5.1 % |
111 | Ukraine | 5 % |
112 | Saint Lucia | 4.85 % |
113 | Samoa | 4.55 % |
114 | Vanuatu | 4.55 % |
115 | Austria | 4.4 % |
116 | Tuvalu | 4.25 % |
117 | Cayman Islands | 4.15 % |
118 | Oman | 4 % |
119 | Lithuania | 3.7 % |
120 | Romania | 3.65 % |
121 | Russia | 3.55 % |
122 | British Virgin Islands | 3.166 % |
123 | Nauru | 3.15 % |
124 | Latvia | 2.75 % |
125 | Marshall Islands | 2.2 % |
126 | Cuba | 2.154 % |
127 | Palau | 1.95 % |
128 | Poland | 1.8 % |
129 | Tonga | 1.8 % |
130 | North Macedonia | 1.3 % |
131 | Portugal | 1.1 % |
132 | United Arab Emirates | 0.95 % |
133 | Serbia | 0.65 % |
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 | 0.165 % |
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 | 0.023 % |
148 | Italy | 0.02 % |
149 | Andorra | 0 % |
150 | Aruba | 0 % |
151 | Belgium | 0 % |
152 | Denmark | 0 % |
153 | Finland | 0 % |
154 | France | 0 % |
155 | Germany | 0 % |
156 | Iceland | 0 % |
157 | Kuwait | 0 % |
158 | Luxembourg | 0 % |
159 | Monaco | 0 % |
160 | Netherlands | 0 % |
161 | New Zealand | 0 % |
162 | Norway | 0 % |
163 | Singapore | 0 % |
164 | Switzerland | 0 % |
↑Top 10 Countries
- #1
South Sudan
- #2
Sudan
- #3
Lebanon
- #4
Chad
- #5
Ethiopia
- #6
Madagascar
- #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
- #164
Switzerland
- #163
Singapore
- #162
Norway
- #161
New Zealand
- #160
Netherlands
- #159
Monaco
- #158
Luxembourg
- #157
Kuwait
- #156
Iceland
- #155
Germany
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The statistic of "Population living in slums" measures the percentage of a population residing in inadequate housing conditions, often characterized by overcrowding, lack of access to basic services, and insecure tenure. This metric is a critical indicator of urban poverty and social inequality, highlighting the urgent need for improved housing policies and sustainable urban development. In 2002, the global landscape of slum populations presents a stark contrast between countries, offering insight into the socioeconomic and environmental challenges faced by diverse regions.
Global Context of Slum Living in 2002
In 2002, the world witnessed a myriad of economic and social changes impacting urban populations. As globalization accelerated, cities became magnets for those seeking better economic opportunities, resulting in rapid urbanization. However, this influx often exceeded the capacity of cities to provide adequate housing, leading to an increase in slum populations. According to data from 164 countries, the average percentage of populations living in slums was 33.73%. Notably, South Sudan reported the highest percentage, with an alarming 99.8% of its population living in slum conditions, illustrating the extreme challenges faced by impoverished nations.
Regional Disparities in Slum Populations
Regional disparities in slum populations were pronounced in 2002. Africa, particularly Sub-Saharan Africa, had some of the highest slum populations globally. Countries such as Chad (90.4565%) and Ethiopia (89.0763%) highlight the severe housing shortages and socioeconomic struggles in the region. In contrast, many developed countries reported negligible slum populations, with countries such as Germany, France, and Norway reporting 0%, reflecting advanced infrastructure and comprehensive housing policies. These disparities underscore the importance of targeted international aid and development programs to address the housing needs in underdeveloped regions.
Economic Implications of Slum Living
The economic implications of slum living in 2002 were significant. Slum conditions often result in a lack of access to education and healthcare, perpetuating cycles of poverty. The high slum population in countries like Mozambique (86.5818%) and the Central African Republic (83.1231%) can severely limit economic growth and development. Conversely, countries with minimal slum populations, such as New Zealand and Switzerland, benefit from a more stable and productive workforce. Addressing slum conditions is therefore essential not only for improving individual livelihoods but also for fostering broader economic development.
Policy Challenges and Solutions
In tackling the issue of slum populations in 2002, policymakers faced numerous challenges, including limited resources, political instability, and rapid urbanization. Efforts to reduce slum populations required comprehensive urban planning and investment in affordable housing. Successful policies often involved partnerships between governments, NGOs, and international organizations. For example, initiatives that focused on upgrading existing slum infrastructure rather than relocation proved more sustainable. The experiences of countries like Mauritania (81.3166%) and Madagascar (89.0341%) demonstrate that integrated approaches, including legal reforms and community participation, are crucial for effective slum reduction.
The environmental and social impacts of slum populations were profound in 2002. Slums are typically located in environmentally hazardous areas, increasing vulnerability to disasters such as floods and landslides. This was evident in populous slum regions like Lebanon (92.4%), where poor infrastructure exacerbated environmental degradation. Socially, slums can lead to increased crime rates and social instability, further entrenching poverty. However, slum communities often exhibit strong social networks and resilience, which can be leveraged in community-led development initiatives. These aspects highlight the need for holistic approaches in addressing the multifaceted challenges posed by slum living.
In summary, understanding the dynamics of slum populations in 2002 provides crucial insights into the broader challenges of urbanization and poverty. The disparities between countries, the economic and social implications, and the pressing need for effective policy interventions underscore the complexity of addressing slum living. Developing sustainable housing solutions remains a global priority, with lessons from 2002 serving as a foundation for future efforts to improve the quality of life for millions living in slums 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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