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.

157 data pointsWorldUN Habitat

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Complete Data Rankings

Rank
1
Ethiopia flag
Ethiopia
92.172 %
2
Chad flag
Chad
91.584 %
3
Madagascar flag
Madagascar
91.436 %
4
Mozambique flag
Mozambique
90.096 %
5
Congo flag
Congo
87.806 %
6
Central African Republic flag
Central African Republic
85.965 %
7
Cambodia flag
Cambodia
84.8 %
8
Mauritania flag
Mauritania
84.693 %
9
Mali flag
Mali
83.876 %
10
Burkina Faso flag
Burkina Faso
82.212 %
11
Malawi flag
Malawi
81.411 %
12
Tanzania flag
Tanzania
81.328 %
13
Uganda flag
Uganda
80.901 %
14
Burundi flag
Burundi
79.7 %
15
Djibouti flag
Djibouti
76.738 %
16
Eritrea flag
Eritrea
76.738 %
17
Mauritius flag
Mauritius
76.738 %
18
Seychelles flag
Seychelles
76.738 %
19
Somalia flag
Somalia
76.738 %
20
Nigeria flag
Nigeria
74.107 %
21
Sierra Leone flag
Sierra Leone
73.9 %
22
Benin flag
Benin
71.866 %
23
Nicaragua flag
Nicaragua
71.598 %
24
Rwanda flag
Rwanda
71.421 %
25
Pakistan flag
Pakistan
71.222 %
26
Cabo Verde flag
Cabo Verde
70.867 %
27
Niger flag
Niger
70.038 %
28
Togo flag
Togo
69.272 %
29
Senegal flag
Senegal
67.155 %
30
Côte d'Ivoire flag
Côte d'Ivoire
67.077 %
31
Nepal flag
Nepal
66.31 %
32
Cameroon flag
Cameroon
65.364 %
33
Comoros flag
Comoros
64.495 %
34
Yemen flag
Yemen
63.812 %
35
Zambia flag
Zambia
63.785 %
36
Kenya flag
Kenya
63.185 %
37
Lesotho flag
Lesotho
62.727 %
38
Haiti flag
Haiti
61.283 %
39
Ghana flag
Ghana
60.368 %
40
Botswana flag
Botswana
58.692 %
41
Bangladesh flag
Bangladesh
58.311 %
42
Bolivia flag
Bolivia
57.945 %
43
Mongolia flag
Mongolia
57.604 %
44
Bhutan flag
Bhutan
57.601 %
45
Iran flag
Iran
57.601 %
46
Sri Lanka flag
Sri Lanka
57.601 %
47
Gabon flag
Gabon
57.43 %
48
Ecuador flag
Ecuador
57.413 %
49
Gambia flag
Gambia
56.921 %
50
Guatemala flag
Guatemala
55.496 %
51
Eswatini flag
Eswatini
55.352 %
52
Laos flag
Laos
54.4 %
53
Equatorial Guinea flag
Equatorial Guinea
52.916 %
54
Azerbaijan flag
Azerbaijan
50.94 %
55
Philippines flag
Philippines
49.974 %
56
Panama flag
Panama
48.676 %
57
Peru flag
Peru
47.413 %
58
Kyrgyzstan flag
Kyrgyzstan
47.158 %
59
Vietnam flag
Vietnam
45.317 %
60
Honduras flag
Honduras
44.4 %
61
Namibia flag
Namibia
42.557 %
62
Egypt flag
Egypt
42.226 %
63
Paraguay flag
Paraguay
42.027 %
64
Guinea flag
Guinea
40.665 %
65
Libya flag
Libya
39.145 %
66
Brunei Darussalam flag
Brunei Darussalam
37.411 %
67
Indonesia flag
Indonesia
35.126 %
68
Brazil flag
Brazil
34.74 %
69
Iraq flag
Iraq
33.894 %
70
Morocco flag
Morocco
33.155 %
71
Mexico flag
Mexico
32.163 %
72
Syrian Arab Republic flag
Syrian Arab Republic
30.702 %
73
Dominican Republic flag
Dominican Republic
30.156 %
74
Uzbekistan flag
Uzbekistan
29.456 %
75
Myanmar flag
Myanmar
29.399 %
76
Albania flag
Albania
28.1 %
77
Venezuela flag
Venezuela
27.82 %
78
South Africa flag
South Africa
27.61 %
79
Zimbabwe flag
Zimbabwe
27.522 %
80
Republic of Moldova flag
Republic of Moldova
26.5 %
81
Guyana flag
Guyana
26.1 %
82
Turkey flag
Turkey
24.581 %
83
Kazakhstan flag
Kazakhstan
24.458 %
84
Uruguay flag
Uruguay
23.7 %
85
Sudan flag
Sudan
21.764 %
86
Colombia flag
Colombia
21.177 %
87
Argentina flag
Argentina
20.292 %
88
Papua New Guinea flag
Papua New Guinea
19.75 %
89
Angola flag
Angola
19.7 %
90
Montenegro flag
Montenegro
19.1 %
91
Kiribati flag
Kiribati
18.1 %
92
Belize flag
Belize
15.8 %
93
Hungary flag
Hungary
15.4 %
94
Chile flag
Chile
14.616 %
95
Georgia flag
Georgia
13.6 %
96
Armenia flag
Armenia
12.796 %
97
Costa Rica flag
Costa Rica
12.696 %
98
Trinidad and Tobago flag
Trinidad and Tobago
11.06 %
99
Turkmenistan flag
Turkmenistan
10.5 %
100
Solomon Islands flag
Solomon Islands
10.4 %
101
Suriname flag
Suriname
7.43 %
102
Ireland flag
Ireland
6.2 %
103
Bosnia and Herzegovina flag
Bosnia and Herzegovina
5.1 %
104
Ukraine flag
Ukraine
5 %
105
Saint Lucia flag
Saint Lucia
4.85 %
106
Samoa flag
Samoa
4.55 %
107
Vanuatu flag
Vanuatu
4.55 %
108
Austria flag
Austria
4.5 %
109
Oman flag
Oman
4.25 %
110
Lithuania flag
Lithuania
4.15 %
111
Russia flag
Russia
3.65 %
112
Nauru flag
Nauru
3.6 %
113
British Virgin Islands flag
British Virgin Islands
3.46 %
114
Latvia flag
Latvia
2.85 %
115
Fiji flag
Fiji
2.218 %
116
Tuvalu flag
Tuvalu
2.178 %
117
Cuba flag
Cuba
2.154 %
118
Palau flag
Palau
2.15 %
119
Poland flag
Poland
2.1 %
120
El Salvador flag
El Salvador
1.904 %
121
Tonga flag
Tonga
1.8 %
122
North Macedonia flag
North Macedonia
1.3 %
123
Portugal flag
Portugal
1.25 %
124
United Arab Emirates flag
United Arab Emirates
0.703 %
125
Serbia flag
Serbia
0.65 %
126
Croatia flag
Croatia
0.4 %
127
Sweden flag
Sweden
0.3 %
128
Canada flag
Canada
0.25 %
129
Greece flag
Greece
0.25 %
130
Cyprus flag
Cyprus
0.2 %
131
United States flag
United States
0.2 %
132
Australia flag
Australia
0.165 %
133
United Kingdom flag
United Kingdom
0.1 %
134
Bulgaria flag
Bulgaria
0.05 %
135
Czech Republic flag
Czech Republic
0.05 %
136
Estonia flag
Estonia
0.05 %
137
Slovakia flag
Slovakia
0.05 %
138
Malta flag
Malta
0.038 %
139
Italy flag
Italy
0.02 %
140
Bermuda flag
Bermuda
0.013 %
141
Andorra flag
Andorra
0 %
142
Aruba flag
Aruba
0 %
143
Belgium flag
Belgium
0 %
144
Denmark flag
Denmark
0 %
145
Finland flag
Finland
0 %
146
France flag
France
0 %
147
Germany flag
Germany
0 %
148
Iceland flag
Iceland
0 %
149
Kuwait flag
Kuwait
0 %
150
Luxembourg flag
Luxembourg
0 %
151
Monaco flag
Monaco
0 %
152
Netherlands flag
Netherlands
0 %
153
New Zealand flag
New Zealand
0 %
154
Norway flag
Norway
0 %
155
Romania flag
Romania
0 %
156
Singapore flag
Singapore
0 %
157
Switzerland flag
Switzerland
0 %

Top 10 Countries

  1. #1Ethiopia flagEthiopia
  2. #2Chad flagChad
  3. #3Madagascar flagMadagascar
  4. #4Mozambique flagMozambique
  5. #5Congo flagCongo
  6. #6Central African Republic flagCentral African Republic
  7. #7Cambodia flagCambodia
  8. #8Mauritania flagMauritania
  9. #9Mali flagMali
  10. #10Burkina Faso flagBurkina Faso

Analysis: These countries represent the highest values in this dataset, showcasing significant scale and impact on global statistics.

Bottom 10 Countries

  1. #157Switzerland flagSwitzerland
  2. #156Singapore flagSingapore
  3. #155Romania flagRomania
  4. #154Norway flagNorway
  5. #153New Zealand flagNew Zealand
  6. #152Netherlands flagNetherlands
  7. #151Monaco flagMonaco
  8. #150Luxembourg flagLuxembourg
  9. #149Kuwait flagKuwait
  10. #148Iceland flagIceland

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.

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Historical Data by Year

Explore Population living in slums data across different years. Compare trends and see how statistics have changed over time.

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