Population living in slums 2016
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 | 82.566 % |
3 | Congo, Democratic Republic of the | 76.981 % |
4 | Sudan | 73.663 % |
5 | Madagascar | 72.223 % |
6 | Afghanistan | 72.129 % |
7 | Niger | 70.444 % |
8 | Central African Republic | 68.913 % |
9 | Benin | 68.72 % |
10 | Comoros | 68.6 % |
11 | Guinea-Bissau | 68.029 % |
12 | Ethiopia | 67.41 % |
13 | Liberia | 65.67 % |
14 | Equatorial Guinea | 63.471 % |
15 | Mozambique | 61.986 % |
16 | Uganda | 59.39 % |
17 | Pakistan | 59.023 % |
18 | Ecuador | 57.8 % |
19 | Mauritania | 57.68 % |
20 | Djibouti | 56.843 % |
21 | Eritrea | 56.843 % |
22 | Mauritius | 56.843 % |
23 | Seychelles | 56.843 % |
24 | Somalia | 56.843 % |
25 | Angola | 56.45 % |
26 | Sierra Leone | 56.122 % |
27 | Myanmar | 55.072 % |
28 | Côte d'Ivoire | 54.752 % |
29 | Nigeria | 54.007 % |
30 | Malawi | 53.299 % |
31 | Bangladesh | 53.158 % |
32 | Sao Tome and Principe | 52.644 % |
33 | Bhutan | 51.44 % |
34 | Iran | 51.44 % |
35 | Sri Lanka | 51.44 % |
36 | Cabo Verde | 51.403 % |
37 | Zambia | 51.363 % |
38 | Haiti | 50.838 % |
39 | Kenya | 50.813 % |
40 | Mali | 50.318 % |
41 | Guinea | 47.339 % |
42 | Congo | 47.3 % |
43 | Tanzania | 47.267 % |
44 | Bolivia | 46.626 % |
45 | Iraq | 46.25 % |
46 | Peru | 45.862 % |
47 | Burundi | 44.868 % |
48 | Gabon | 44.333 % |
49 | Yemen | 44.2 % |
50 | Rwanda | 43.571 % |
51 | Togo | 43.326 % |
52 | Nepal | 43.174 % |
53 | Gambia | 42.499 % |
54 | Botswana | 41.711 % |
55 | Namibia | 41.365 % |
56 | Cambodia | 39.7 % |
57 | Cameroon | 39.21 % |
58 | Philippines | 38.725 % |
59 | Senegal | 38.715 % |
60 | Timor-Leste | 37.9 % |
61 | Burkina Faso | 37.683 % |
62 | Guatemala | 37.603 % |
63 | Maldives | 36.518 % |
64 | Lesotho | 33.814 % |
65 | Ghana | 33.487 % |
66 | Honduras | 31.5 % |
67 | Laos | 27 % |
68 | Mongolia | 25.824 % |
69 | Venezuela | 25.7 % |
70 | South Africa | 24.563 % |
71 | Syrian Arab Republic | 23.919 % |
72 | Brunei Darussalam | 23.539 % |
73 | Jordan | 23.4 % |
74 | Zimbabwe | 22.759 % |
75 | Papua New Guinea | 22 % |
76 | Indonesia | 21.892 % |
77 | Algeria | 21.076 % |
78 | State of Palestine | 19.538 % |
79 | Azerbaijan | 18.522 % |
80 | Mexico | 18.443 % |
81 | Paraguay | 18.05 % |
82 | Libya | 17.239 % |
83 | El Salvador | 16.477 % |
84 | Panama | 16.3 % |
85 | Belize | 15.733 % |
86 | Guyana | 15.435 % |
87 | Brazil | 14.897 % |
88 | Argentina | 14.5 % |
89 | Suriname | 14.126 % |
90 | Turkey | 14.126 % |
91 | Kyrgyzstan | 11.383 % |
92 | Dominican Republic | 11.249 % |
93 | Montenegro | 11.2 % |
94 | Morocco | 10.851 % |
95 | Eswatini | 10.808 % |
96 | Colombia | 10.421 % |
97 | Fiji | 9.4 % |
98 | Turkmenistan | 9.007 % |
99 | Armenia | 8.884 % |
100 | Tunisia | 8.643 % |
101 | Georgia | 8.613 % |
102 | Cuba | 8.445 % |
103 | Ireland | 8.3 % |
104 | Kiribati | 8.1 % |
105 | Albania | 7.8 % |
106 | Trinidad and Tobago | 7.5 % |
107 | Chile | 7.314 % |
108 | Uzbekistan | 7.293 % |
109 | Hungary | 7.2 % |
110 | Republic of Moldova | 6.5 % |
111 | South Korea | 5.8 % |
112 | Vietnam | 5.766 % |
113 | Nicaragua | 5.519 % |
114 | Costa Rica | 5.376 % |
115 | Lebanon | 4.5 % |
116 | Poland | 4.5 % |
117 | Cayman Islands | 4.15 % |
118 | Vanuatu | 4.1 % |
119 | Bosnia and Herzegovina | 4 % |
120 | Russia | 2.9 % |
121 | Antigua and Barbuda | 2.646 % |
122 | Kazakhstan | 2.186 % |
123 | Romania | 2.1 % |
124 | Solomon Islands | 2 % |
125 | Austria | 1.679 % |
126 | British Virgin Islands | 1.639 % |
127 | Uruguay | 1.3 % |
128 | Tuvalu | 1.101 % |
129 | Ukraine | 1.1 % |
130 | Saint Lucia | 1.05 % |
131 | Egypt | 0.9 % |
132 | Latvia | 0.8 % |
133 | Tonga | 0.75 % |
134 | Canada | 0.7 % |
135 | Lithuania | 0.65 % |
136 | Nauru | 0.55 % |
137 | Samoa | 0.5 % |
138 | Marshall Islands | 0.45 % |
139 | Serbia | 0.45 % |
140 | Palau | 0.4 % |
141 | Cyprus | 0.3 % |
142 | North Macedonia | 0.3 % |
143 | Oman | 0.3 % |
144 | Croatia | 0.25 % |
145 | United Arab Emirates | 0.25 % |
146 | Bulgaria | 0.2 % |
147 | United States | 0.2 % |
148 | Bermuda | 0.1 % |
149 | Estonia | 0.1 % |
150 | Portugal | 0.1 % |
151 | Sweden | 0.1 % |
152 | United Kingdom | 0.1 % |
153 | Czech Republic | 0.05 % |
154 | Slovakia | 0.05 % |
155 | Spain | 0.05 % |
156 | Tajikistan | 0.05 % |
157 | Malta | 0.038 % |
158 | Australia | 0.035 % |
159 | Italy | 0.02 % |
160 | Luxembourg | 0.016 % |
161 | Belarus | 0.004 % |
162 | Andorra | 0 % |
163 | Aruba | 0 % |
164 | Belgium | 0 % |
165 | Denmark | 0 % |
166 | Finland | 0 % |
167 | France | 0 % |
168 | Germany | 0 % |
169 | Iceland | 0 % |
170 | Kuwait | 0 % |
171 | Monaco | 0 % |
172 | Netherlands | 0 % |
173 | New Zealand | 0 % |
174 | Norway | 0 % |
175 | Qatar | 0 % |
176 | Singapore | 0 % |
177 | Switzerland | 0 % |
178 | Greece | -0.05 % |
↑Top 10 Countries
- #1
South Sudan
- #2
Chad
- #3
Congo, Democratic Republic of the
- #4
Sudan
- #5
Madagascar
- #6
Afghanistan
- #7
Niger
- #8
Central African Republic
- #9
Benin
- #10
Comoros
Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.
↓Bottom 10 Countries
- #178
Greece
- #177
Switzerland
- #176
Singapore
- #175
Qatar
- #174
Norway
- #173
New Zealand
- #172
Netherlands
- #171
Monaco
- #170
Kuwait
- #169
Iceland
Context: These countries or territories have the lowest values, often due to geographic size, administrative status, or specific characteristics.
Analysis & Context
The percentage of the population living in slums is a critical statistic that reveals the extent of urban poverty and inadequate housing conditions worldwide. In 2016, this metric continued to highlight significant disparities in living standards across different regions and underscored the pressing need for urban development and housing reform. Understanding these patterns is essential for policymakers and stakeholders aiming to improve the quality of life for millions of people residing in slums.
Global Overview of Slum Populations in 2016
In 2016, data was collected from 170 countries, illustrating a global average of 24% of the population living in slums. This statistic, however, masks significant regional and national variations. South Sudan topped the list with a staggering 94.2% of its population residing in slum conditions. Other countries with high percentages included Chad (82.57%), the Democratic Republic of the Congo (76.98%), and Sudan (73.66%). Conversely, several developed nations, including Andorra, Belgium, and Singapore, reported a 0% slum population, highlighting a stark contrast in urban living conditions.
Regional Disparities and Contributing Factors
The wide variation in slum population percentages across different countries is influenced by multiple factors, including economic conditions, governance, and urban planning policies. In regions such as Sub-Saharan Africa, where countries like South Sudan and Chad reported some of the highest percentages, instability, and insufficient infrastructure development play significant roles. In contrast, regions with effective urban policies and economic stability, such as Western Europe and parts of Asia, demonstrated minimal slum populations. These disparities underscore the multifaceted challenges that less developed countries face in addressing urban poverty.
Policy Impact and Urban Planning Initiatives
Efforts to mitigate slum conditions have been ongoing, with varying degrees of success. In 2016, international organizations and national governments continued to emphasize the importance of sustainable urban development. Initiatives focused on improving infrastructure, providing affordable housing, and enhancing living conditions. Countries such as Rwanda have made notable progress through strategic policies aimed at urban renewal and slum rehabilitation. These efforts not only improve physical living conditions but also aim to integrate slum dwellers into the broader urban economy, providing access to jobs and services.
Economic Implications of Slum Populations
The economic implications of high slum populations are profound. In many countries, slums represent a significant portion of urban dwellers, contributing to the informal economy. However, the lack of formal employment opportunities and inadequate access to social services often perpetuates the cycle of poverty. For nations like Madagascar and Afghanistan, where over 70% of the urban population live in slums, the challenge is not only to improve living standards but also to boost economic growth and development. Successful integration of slum populations into the formal economy could lead to increased productivity and better economic outcomes for these nations.
Future Trends and Projections
Looking ahead, addressing the challenges faced by slum populations requires a multifaceted approach. The United Nations' Sustainable Development Goals emphasize the need for inclusive, safe, and sustainable cities, with a specific target to upgrade slums by 2030. In 2016, efforts were already underway to achieve these goals, but progress varied significantly across regions. As urbanization continues to accelerate, particularly in developing countries, the demand for effective housing solutions will become more urgent. Future trends will likely focus on innovative housing technologies, expanded infrastructure investment, and stronger international cooperation to improve the living conditions of slum dwellers globally.
In conclusion, the data from 2016 highlights both the challenges and opportunities in addressing urban poverty and improving living standards for slum populations. While some countries have made significant strides, others continue to struggle with high percentages of their populations living in inadequate conditions. It is imperative for global efforts to be amplified and for policies to be tailored to the specific needs of each region to ensure sustainable urban development and the betterment of living conditions 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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