Population living in slums 2018
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 | 94.2 % |
2 | Chad | 82 % |
3 | Congo, Democratic Republic of the | 77.902 % |
4 | Sudan | 73.7 % |
5 | Afghanistan | 73.3 % |
6 | Niger | 70.444 % |
7 | Madagascar | 69.822 % |
8 | Central African Republic | 68.913 % |
9 | Comoros | 68.6 % |
10 | Benin | 68.326 % |
11 | Equatorial Guinea | 64.674 % |
12 | Guinea-Bissau | 64.42 % |
13 | Ethiopia | 64.314 % |
14 | Liberia | 63.885 % |
15 | Angola | 62.581 % |
16 | Mozambique | 58.473 % |
17 | Myanmar | 58.281 % |
18 | Ecuador | 57.8 % |
19 | Pakistan | 57.499 % |
20 | Uganda | 56.701 % |
21 | Mauritania | 56 % |
22 | Sierra Leone | 53.384 % |
23 | Djibouti | 53.371 % |
24 | Eritrea | 53.371 % |
25 | Mauritius | 53.371 % |
26 | Seychelles | 53.371 % |
27 | Somalia | 53.371 % |
28 | Côte d'Ivoire | 53.211 % |
29 | Sao Tome and Principe | 52.6 % |
30 | Bangladesh | 52.513 % |
31 | Nigeria | 51.495 % |
32 | Kenya | 50.813 % |
33 | Bhutan | 50.665 % |
34 | Iran | 50.665 % |
35 | Sri Lanka | 50.665 % |
36 | Zambia | 49.811 % |
37 | Malawi | 49.785 % |
38 | Haiti | 49.533 % |
39 | Cabo Verde | 49.2 % |
40 | Guinea | 48.173 % |
41 | Iraq | 47.795 % |
42 | Bolivia | 46.626 % |
43 | Mali | 46.124 % |
44 | Gabon | 44.333 % |
45 | Peru | 44.218 % |
46 | Yemen | 44.2 % |
47 | Congo | 44.184 % |
48 | Tanzania | 43.009 % |
49 | Namibia | 41.4 % |
50 | Gambia | 40.696 % |
51 | Nepal | 40.282 % |
52 | Rwanda | 40.09 % |
53 | Togo | 40.082 % |
54 | Cambodia | 39.7 % |
55 | Botswana | 39.589 % |
56 | Burundi | 39.505 % |
57 | Guatemala | 37.6 % |
58 | Philippines | 37.319 % |
59 | Cameroon | 35.941 % |
60 | Maldives | 35.403 % |
61 | Senegal | 35.16 % |
62 | Timor-Leste | 33.9 % |
63 | Jordan | 33.9 % |
64 | Ghana | 33.487 % |
65 | Burkina Faso | 32.116 % |
66 | Honduras | 31.5 % |
67 | Lesotho | 29.684 % |
68 | Venezuela | 25.7 % |
69 | Syrian Arab Republic | 25.182 % |
70 | South Africa | 24.182 % |
71 | Laos | 23.6 % |
72 | Brunei Darussalam | 22.436 % |
73 | Papua New Guinea | 22.4 % |
74 | Zimbabwe | 22.164 % |
75 | Mongolia | 21.851 % |
76 | Indonesia | 20.238 % |
77 | State of Palestine | 19.5 % |
78 | Mexico | 17.6 % |
79 | Algeria | 17.17 % |
80 | El Salvador | 16.5 % |
81 | Libya | 16.382 % |
82 | Panama | 16.3 % |
83 | Belize | 15.729 % |
84 | Azerbaijan | 15.52 % |
85 | Paraguay | 15.053 % |
86 | Suriname | 14.963 % |
87 | Brazil | 14.897 % |
88 | Argentina | 14.5 % |
89 | Turkey | 14.126 % |
90 | Guyana | 13.787 % |
91 | Dominican Republic | 11.249 % |
92 | Morocco | 10.851 % |
93 | Eswatini | 10.808 % |
94 | Montenegro | 10 % |
95 | Colombia | 9.7 % |
96 | Cuba | 9.493 % |
97 | Fiji | 9.4 % |
98 | Turkmenistan | 8.757 % |
99 | Ireland | 8.5 % |
100 | Armenia | 8.395 % |
101 | Tunisia | 8.143 % |
102 | Trinidad and Tobago | 7.876 % |
103 | Georgia | 7.846 % |
104 | Chile | 7.317 % |
105 | Kyrgyzstan | 6.911 % |
106 | Kiribati | 6.85 % |
107 | South Korea | 6.8 % |
108 | Republic of Moldova | 6.5 % |
109 | Hungary | 5.87 % |
110 | Vietnam | 5.766 % |
111 | Nicaragua | 5.519 % |
112 | India | 5.41 % |
113 | Uzbekistan | 5.36 % |
114 | Albania | 5.3 % |
115 | Cayman Islands | 4.593 % |
116 | Lebanon | 4.5 % |
117 | Costa Rica | 4.461 % |
118 | Poland | 4.3 % |
119 | Vanuatu | 4.15 % |
120 | Bosnia and Herzegovina | 4 % |
121 | Russia | 2.85 % |
122 | Antigua and Barbuda | 2.646 % |
123 | Solomon Islands | 1.95 % |
124 | Romania | 1.85 % |
125 | Nauru | 1.797 % |
126 | Uruguay | 1.3 % |
127 | Austria | 1.135 % |
128 | Ukraine | 1.1 % |
129 | Tuvalu | 0.995 % |
130 | Egypt | 0.9 % |
131 | Canada | 0.8 % |
132 | Kazakhstan | 0.794 % |
133 | Latvia | 0.6 % |
134 | Tonga | 0.6 % |
135 | Saint Lucia | 0.45 % |
136 | Serbia | 0.4 % |
137 | Cyprus | 0.3 % |
138 | Palau | 0.3 % |
139 | Croatia | 0.25 % |
140 | Lithuania | 0.25 % |
141 | Samoa | 0.25 % |
142 | Bulgaria | 0.2 % |
143 | North Macedonia | 0.15 % |
144 | Oman | 0.15 % |
145 | United States | 0.15 % |
146 | British Virgin Islands | 0.136 % |
147 | Bermuda | 0.1 % |
148 | Estonia | 0.1 % |
149 | Marshall Islands | 0.1 % |
150 | Sweden | 0.1 % |
151 | United Arab Emirates | 0.1 % |
152 | United Kingdom | 0.1 % |
153 | Czech Republic | 0.05 % |
154 | Portugal | 0.05 % |
155 | Slovakia | 0.05 % |
156 | Tajikistan | 0.05 % |
157 | Spain | 0.049 % |
158 | Malta | 0.038 % |
159 | Australia | 0.035 % |
160 | Italy | 0.02 % |
161 | Luxembourg | 0.017 % |
162 | Belarus | 0.004 % |
163 | Andorra | 0 % |
164 | Aruba | 0 % |
165 | Bahrain | 0 % |
166 | Belgium | 0 % |
167 | Denmark | 0 % |
168 | Finland | 0 % |
169 | France | 0 % |
170 | Germany | 0 % |
171 | Iceland | 0 % |
172 | Kuwait | 0 % |
173 | Monaco | 0 % |
174 | Netherlands | 0 % |
175 | New Zealand | 0 % |
176 | Norway | 0 % |
177 | Qatar | 0 % |
178 | Singapore | 0 % |
179 | Switzerland | 0 % |
180 | Greece | -0.1 % |
↑Top 10 Countries
- #1
South Sudan
- #2
Chad
- #3
Congo, Democratic Republic of the
- #4
Sudan
- #5
Afghanistan
- #6
Niger
- #7
Madagascar
- #8
Central African Republic
- #9
Comoros
- #10
Benin
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #180
Greece
- #179
Switzerland
- #178
Singapore
- #177
Qatar
- #176
Norway
- #175
New Zealand
- #174
Netherlands
- #173
Monaco
- #172
Kuwait
- #171
Iceland
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" is a critical indicator of urban poverty and living conditions. In 2018, this metric shed light on the housing challenges faced by numerous countries around the globe, highlighting the urgent need for improvements in urban infrastructure and policies aimed at enhancing the quality of life for millions living in substandard conditions. This article delves into the patterns and implications of slum populations in 2018, offering insights into the socio-economic and environmental factors at play.
Global Contrast: The Spectrum of Slum Dwellings
In 2018, the disparity in slum populations across the globe was striking. While some countries, including Qatar, Finland, and Switzerland, reported a remarkable 0% of their population living in slums, others faced significant challenges. South Sudan topped the list with a staggering 94.2% of its population residing in slum conditions, followed by Chad at 82% and the Democratic Republic of the Congo at 77.9%. This vast range, spanning from 0% to over 90%, underscores the diverse socio-economic landscapes and the varying levels of urban development globally.
Economic Implications and Housing Conditions
The prevalence of slums is deeply intertwined with economic factors. Countries with high percentages of their population in slums often face issues like poverty, unemployment, and inadequate urban planning. For instance, nations like Afghanistan (73.3%) and Madagascar (69.8%) struggle with economic instability, which exacerbates the housing deficit and forces many into informal settlements. Conversely, affluent nations with robust economic structures, such as Singapore and Denmark, reported no slum populations in 2018, illustrating the correlation between economic prosperity and improved living standards.
Regional Disparities and Urbanization Rates
A closer examination reveals significant regional disparities in slum populations. Africa, with countries like South Sudan and Chad, displayed some of the highest percentages, reflecting the continent's rapid urbanization rates and often insufficient infrastructure development. The challenges in these regions are compounded by political instability and resource constraints, making it difficult to provide adequate housing solutions. In contrast, regions like Europe and parts of Asia have managed to mitigate the expansion of slums through effective urban policies and investment in sustainable housing projects.
Policy Impact and Future Directions
Addressing the issue of slum populations requires a multi-faceted policy approach. Governments and international organizations have recognized the need for comprehensive strategies that include improving access to affordable housing, enhancing infrastructure, and fostering economic opportunities. The data from 2018 suggests that countries with proactive housing policies have made strides in reducing slum populations. For example, Latin American countries have seen improvements through slum upgrading programs and the regularization of land tenure, providing a blueprint for other regions grappling with similar challenges.
Environmental Connections and Sustainability
The environmental impact of slum dwellings is profound, influencing factors such as waste management, water quality, and overall urban sustainability. In many high-slum-population areas, inadequate infrastructure leads to environmental degradation, which further diminishes the quality of life. Sustainable development goals emphasize the need to create resilient cities that can support burgeoning urban populations without compromising environmental integrity. The data from 2018 highlights the urgency for integrating sustainable practices into urban planning to mitigate the adverse effects on both the environment and the communities residing in slums.
In conclusion, the "Population living in slums" statistic for 2018 reveals a complex interplay of economic, social, and environmental factors. While some countries have successfully alleviated the prevalence of slums through targeted policies and economic growth, others continue to face significant challenges. A concerted global effort focused on sustainable urban development, policy innovation, and economic empowerment is essential to address the housing crisis and enhance living conditions for millions 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.
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