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Automatu Do Gier

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Automat Do Gier Aloha Cluster Pays Gra Za Darmo Bez Rejestracji
Automaty Do Gier Trójmiasto

Rozgrywka na automacie 2025 jest w pełni zoptymalizowana

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Note:

Each country’s estimate reflects the most recent available data for that country, while the world averages are ILO modelled estimates for 2023, as reported in the ILO World Social Protection Report 2024–26.

SDG 17 | Partnerships for the Goals

Individuals Using the Internet (% of population)

Fixed-Broadband Subscriptions (Per 100 population)

Asia-Pacific Region

Climate Finance and GSS+ Bond Issuance in the Asia-Pacific region ($ billion)

Climate Finance

* Green, social, sustainability and similar (GSS+) bonds

*91 per cent of total GSS+ issuance from 2021-2023 went to China, developed countries, and high-income developing countries.

SDG 14 | Life Below Water

Beach litter originating from national land-based sources that ends in the ocean (Tonnes) and exported beach litter originating from national land-based sources (Tonnes)

  • Beach Litter (Tonnes)
  • Exported Beach Litter (Tonnes)

SDG 13 | Climate Action

266 million

people are at risk of falling into poverty, mainly due to climate-related disasters by 2040.

The cost of reversing this increase:

6 – 9%

of GDP

High emissions scenario

17%

loss of GDP by 2070

Full decarbonisation: can create

180 million

jobs by 2050, contributing $47 trillion in economic value by 2070

$1.8 trillion

of climate financing gap per annum

SDG 8 | Decent Work and Economic Growth

Proportion of youth (15–24 years old) not in education, employment or training (NEET)

In South Asia, approximately one in four youth are NEET (2023: 26.4%), exceeding the global average (2023: 20.4%). The rate of young NEET women in 2023 (42.4%) was nearly four times as high as their young male counterparts (13%)

  • 2023: More than one in five young adults aged 15-24 years were NEET in the Asia-Pacific region.

Unemployment rate: percentage of labour force aged 15+

Proportion of youth (15–24 years old) not in education, employment or training (NEET)

SDG 5 | Gender Equality

Change in gender gap in labour force participation (female-to-male ratio) between 2015 and 2024, by subregion

  • Pacific
  • East and North-East Asia
  • North and Central Asia
  • South-East Asia
  • Asia-Pacific Region
  • South and South-West Asia

Seats held by women in national parliament (% of seats)

  • <20%
  • 20-25%
  • >25%

SDG 3 | Good Health and Well-being

Physicians density
(Per 10,000 population)

*Universal Health Coverage Service Coverage Index (UHC)

* The UHC Service Coverage Index measures the extent to which essential health services are covered within a country, ranging from 0 (no coverage) to 100 (full coverage).

Official development assistance to medical research and basic health sectors, total net disbursement (Million 2022 US dollars)

External funding for HIV programmes in the Asia-Pacific region*

Resource availability for HIV: $ 3.3 billion- 64% gap to meet UNAIDS’ 2025 target

* UNAIDS Asia-Pacific region: does not include all ESCAP member States

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Note:

The sectors in the legend correspond to categories from the International Standard Industrial Classification (ISIC) Revision 4. “Energy” corresponds to ISIC Division 35, which includes electricity, gas, steam, and air conditioning supply activities. “Fishing and Aquaculture” aligns with ISIC Division 03, covering fishing and aquaculture activities. “Transport” corresponds to ISIC Division 49, including land transport and transport via pipelines. “Waste Management” is represented by ISIC Division 38, encompassing waste collection, treatment, disposal activities, and materials recovery. Data are derived from national labour force surveys conducted in the following years: Armenia (2021), Australia (2023), Bangladesh (2022), Bhutan (2023), Brunei Darussalam (2023), Cambodia (2021), Fiji (2016), Georgia (2020), India (2023), Indonesia (2023), Japan (2022), Kiribati (2020), Kyrgyzstan (2022), Lao PDR (2022), Maldives (2019), Marshall Islands (2021), Mongolia (2023), Myanmar (2020), Nauru (2021), Nepal (2017), New Caledonia (2020), Niue (2022), Pakistan (2021), Palau (2020), Papua New Guinea (2022), Philippines (2022), Republic of Korea (2019), Samoa (2022), Singapore (2023), Sri Lanka (2022), Tajikistan (2016), Thailand (2023), Timor-Leste (2022), Tonga (2021), Tuvalu (2022), Türkiye (2023), Vanuatu (2020), and Viet Nam (2023).

Note:

The sectors in the legend correspond to categories from the International Standard Industrial Classification (ISIC) Revision 4. “Energy” corresponds to ISIC Division 35, which includes electricity, gas, steam, and air conditioning supply activities. “Fishing and Aquaculture” aligns with ISIC Division 03, covering fishing and aquaculture activities. “Transport” corresponds to ISIC Division 49, including land transport and transport via pipelines. “Waste Management” is represented by ISIC Division 38, encompassing waste collection, treatment, disposal activities, and materials recovery. Data are derived from national labour force surveys conducted in the following years: Australia (2023), Brunei Darussalam (2023), India (2023), Japan (2019), Mongolia (2023), and Viet Nam (2023).

Note:

Bangladesh (2022), Cook Islands (2019), Fiji (2016), India (2023), Indonesia (2023), Malaysia (2022), Maldives (2019), Nepal (2017), Pakistan (2021), Palau (2020), Philippines (2022), Sri Lanka (2022), Thailand (2023), and Viet Nam (2023).

Note:

Employment data were sourced from national labour force surveys, with survey years varying by country: Armenia (2015, 2021), Australia (2018, 2023), Bangladesh (2017, 2022), Brunei Darussalam (2017, 2023), Cambodia (2015, 2021), Cook Islands (2016, 2023), Georgia (2017, 2020), India (2018, 2023), Indonesia (2015, 2023), Iran (2015, 2022), Japan (2015, 2022), Kiribati (2015, 2020), Kyrgyzstan (2018, 2022), Lao PDR (2017, 2022), Maldives (2016, 2019), Myanmar (2015, 2020), New Caledonia (2017, 2020), Pakistan (2015, 2021), Philippines (2015, 2022), Samoa (2017, 2022), Sri Lanka (2015, 2022), Thailand (2015, 2023), Türkiye (2015, 2023), Tuvalu (2016, 2022), Viet Nam (2015, 2023).

Note:

The UHC Service Coverage Index measures the extent to which essential health services are covered within a country, ranging from 0 (no coverage) to 100 (full coverage). This index serves as a key indicator of a country’s ability to provide its population with access to comprehensive health services, crucial for achieving Sustainable Development Goal 3 (Good Health and Well-being). The index encompasses a broad range of services including reproductive, maternal, newborn and child health, infectious diseases, noncommunicable diseases, and service capacity and access. The Asia and the Pacific average is shown alongside the global average to highlight regional differences and guide targeted health policy interventions.

Note:

The regional breakdown follows the ILO’s Asia-Pacific classification based on ILO modelled estimates, which may differ from ESCAP’s regional definitions and classifications. Differences in methodologies and data sources account for these variations.

Note:

Afghanistan (2021), Armenia (2021), Australia (2023), Bangladesh (2022), Bhutan (2023), Brunei Darussalam (2023), Cambodia (2021), Cook Islands (2023), Fiji (2016), Georgia (2020), India (2023), Indonesia (2023), Iran (2022), Japan (2022), Kiribati (2020), Kyrgyzstan (2022), Lao PDR (2022), Maldives (2019), Marshall Islands (2021), Mongolia (2023), Myanmar (2020), Nauru (2021), Nepal (2017), New Caledonia (2020), Niue (2022), Palau (2020), Papua New Guinea (2022), Philippines (2022), Russian Federation (2023), Samoa (2022), Singapore (2023), Sri Lanka (2022), Thailand (2023), Timor-Leste (2022), Tonga (2021), Tuvalu (2022), Türkiye (2023), Uzbekistan (2020), and Vanuatu (2020).

Note:

Data depicted in this figure are modelled estimates sourced from the International Renewable Energy Agency (IRENA) and are intended as indicative rather than definitive representations of job distributions across renewable energy sectors. Users should interpret these figures with caution, acknowledging the inherent variability in modelling assumptions and the dynamic nature of technology and market developments. For comprehensive details on the methodologies and underlying data, refer to the IRENA Annual Review 2024.