Mali Health Statistics
Mali ML: Out-of-Pocket Health Expenditure: % of Current Health Expenditure
ML: Out-of-Pocket Health Expenditure: % of Current Health Expenditure data was reported at 46.307 % in 2015. This records a decrease from the previous number of 47.104 % for 2014. ML: Out-of-Pocket Health Expenditure: % of Current Health Expenditure data is updated yearly, averaging 64.714 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 73.722 % in 2000 and a record low of 46.307 % in 2015. ML: Out-of-Pocket Health Expenditure: % of Current Health Expenditure data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Share of out-of-pocket payments of total current health expenditures. Out-of-pocket payments are spending on health directly out-of-pocket by households.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 46.31 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: Out-of-Pocket Health Expenditure: % of Current Health Expenditure from 2000 to 2015 in the chart:
Mali ML: Out-of-Pocket Helath Expenditure Per Capita: Current PPP
ML: Out-of-Pocket Helath Expenditure Per Capita: Current PPP data was reported at 0.000 Intl $ mn in 2015. This records an increase from the previous number of 0.000 Intl $ mn for 2014. ML: Out-of-Pocket Helath Expenditure Per Capita: Current PPP data is updated yearly, averaging 0.000 Intl $ mn from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 0.000 Intl $ mn in 2009 and a record low of 0.000 Intl $ mn in 2001. ML: Out-of-Pocket Helath Expenditure Per Capita: Current PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Health expenditure through out-of-pocket payments per capita in international dollars at purchasing power parity (PPP).; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 0.00 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: Out-of-Pocket Helath Expenditure Per Capita: Current PPP from 2000 to 2015 in the chart:
Mali ML: People Practicing Open Defecation: % of Population
ML: People Practicing Open Defecation: % of Population data was reported at 8.053 % in 2015. This records a decrease from the previous number of 8.864 % for 2014. ML: People Practicing Open Defecation: % of Population data is updated yearly, averaging 14.461 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 21.527 % in 2000 and a record low of 8.053 % in 2015. ML: People Practicing Open Defecation: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 8.05 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Practicing Open Defecation: % of Population from 2000 to 2015 in the chart:
Mali ML: People Practicing Open Defecation: Rural: % of Rural Population
ML: People Practicing Open Defecation: Rural: % of Rural Population data was reported at 12.656 % in 2015. This records a decrease from the previous number of 13.696 % for 2014. ML: People Practicing Open Defecation: Rural: % of Rural Population data is updated yearly, averaging 20.459 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 28.263 % in 2000 and a record low of 12.656 % in 2015. ML: People Practicing Open Defecation: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 12.66 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Practicing Open Defecation: Rural: % of Rural Population from 2000 to 2015 in the chart:
Mali ML: People Practicing Open Defecation: Urban: % of Urban Population
ML: People Practicing Open Defecation: Urban: % of Urban Population data was reported at 1.126 % in 2015. This records a decrease from the previous number of 1.352 % for 2014. ML: People Practicing Open Defecation: Urban: % of Urban Population data is updated yearly, averaging 2.817 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 4.509 % in 2000 and a record low of 1.126 % in 2015. ML: People Practicing Open Defecation: Urban: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 1.13 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Practicing Open Defecation: Urban: % of Urban Population from 2000 to 2015 in the chart:
Mali ML: People Using At Least Basic Drinking Water Services: % of Population
ML: People Using At Least Basic Drinking Water Services: % of Population data was reported at 74.268 % in 2015. This records an increase from the previous number of 72.643 % for 2014. ML: People Using At Least Basic Drinking Water Services: % of Population data is updated yearly, averaging 61.887 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 74.268 % in 2015 and a record low of 49.224 % in 2000. ML: People Using At Least Basic Drinking Water Services: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people using at least basic water services. This indicator encompasses both people using basic water services as well as those using safely managed water services. Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 74.27 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Using At Least Basic Drinking Water Services: % of Population from 2000 to 2015 in the chart:
Mali ML: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population
ML: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population data was reported at 62.866 % in 2015. This records an increase from the previous number of 61.297 % for 2014. ML: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population data is updated yearly, averaging 51.100 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 62.866 % in 2015 and a record low of 39.334 % in 2000. ML: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people using at least basic water services. This indicator encompasses both people using basic water services as well as those using safely managed water services. Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 62.87 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population from 2000 to 2015 in the chart:
Mali ML: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population
ML: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population data was reported at 91.431 % in 2015. This records an increase from the previous number of 90.283 % for 2014. ML: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population data is updated yearly, averaging 82.822 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 91.431 % in 2015 and a record low of 74.212 % in 2000. ML: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people using at least basic water services. This indicator encompasses both people using basic water services as well as those using safely managed water services. Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 91.43 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population from 2000 to 2015 in the chart:
Mali ML: People Using At Least Basic Sanitation Services: % of Population
ML: People Using At Least Basic Sanitation Services: % of Population data was reported at 31.268 % in 2015. This records an increase from the previous number of 30.482 % for 2014. ML: People Using At Least Basic Sanitation Services: % of Population data is updated yearly, averaging 25.309 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 31.268 % in 2015 and a record low of 19.341 % in 2000. ML: People Using At Least Basic Sanitation Services: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households. This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 31.27 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Using At Least Basic Sanitation Services: % of Population from 2000 to 2015 in the chart:
Mali ML: People Using At Least Basic Sanitation Services: Rural: % of Rural Population
ML: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data was reported at 21.501 % in 2015. This records an increase from the previous number of 20.871 % for 2014. ML: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data is updated yearly, averaging 16.775 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 21.501 % in 2015 and a record low of 12.049 % in 2000. ML: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households. This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 21.50 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Using At Least Basic Sanitation Services: Rural: % of Rural Population from 2000 to 2015 in the chart:
Mali ML: People Using At Least Basic Sanitation Services: Urban: % of Urban Population
ML: People Using At Least Basic Sanitation Services: Urban: % of Urban Population data was reported at 45.971 % in 2015. This records an increase from the previous number of 45.424 % for 2014. ML: People Using At Least Basic Sanitation Services: Urban: % of Urban Population data is updated yearly, averaging 41.869 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 45.971 % in 2015 and a record low of 37.767 % in 2000. ML: People Using At Least Basic Sanitation Services: Urban: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households. This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 45.97 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: People Using At Least Basic Sanitation Services: Urban: % of Urban Population from 2000 to 2015 in the chart:
Mali ML: People with Basic Handwashing Facilities Including Soap and Water: % of Population
ML: People with Basic Handwashing Facilities Including Soap and Water: % of Population data was reported at 16.335 % in 2015. This records an increase from the previous number of 16.320 % for 2014. ML: People with Basic Handwashing Facilities Including Soap and Water: % of Population data is updated yearly, averaging 16.288 % from Dec 2009 (Median) to 2015, with 7 observations. The data reached an all-time high of 16.335 % in 2015 and a record low of 16.240 % in 2009. ML: People with Basic Handwashing Facilities Including Soap and Water: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. The percentage of people living in households that have a handwashing facility with soap and water available on the premises. Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; ;
| Last | Frequency | Range |
|---|---|---|
| 16.34 2015 | yearly | 2009 - 2015 |
View Mali's Mali ML: People with Basic Handwashing Facilities Including Soap and Water: % of Population from 2009 to 2015 in the chart:
Mali ML: People with Basic Handwashing Facilities Including Soap and Water: Rural: % of Rural Population
ML: People with Basic Handwashing Facilities Including Soap and Water: Rural: % of Rural Population data was reported at 15.534 % in 2015. This stayed constant from the previous number of 15.534 % for 2014. ML: People with Basic Handwashing Facilities Including Soap and Water: Rural: % of Rural Population data is updated yearly, averaging 15.534 % from Dec 2009 (Median) to 2015, with 7 observations. The data reached an all-time high of 15.534 % in 2015 and a record low of 15.534 % in 2015. ML: People with Basic Handwashing Facilities Including Soap and Water: Rural: % of Rural Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people living in households that have a handwashing facility with soap and water available on the premises. Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; ;
| Last | Frequency | Range |
|---|---|---|
| 15.53 2015 | yearly | 2009 - 2015 |
View Mali's Mali ML: People with Basic Handwashing Facilities Including Soap and Water: Rural: % of Rural Population from 2009 to 2015 in the chart:
Mali ML: People with Basic Handwashing Facilities Including Soap and Water: Urban: % of Urban Population
ML: People with Basic Handwashing Facilities Including Soap and Water: Urban: % of Urban Population data was reported at 17.541 % in 2015. This stayed constant from the previous number of 17.541 % for 2014. ML: People with Basic Handwashing Facilities Including Soap and Water: Urban: % of Urban Population data is updated yearly, averaging 17.541 % from Dec 2009 (Median) to 2015, with 7 observations. The data reached an all-time high of 17.541 % in 2015 and a record low of 17.541 % in 2015. ML: People with Basic Handwashing Facilities Including Soap and Water: Urban: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The percentage of people living in households that have a handwashing facility with soap and water available on the premises. Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents.; ; WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).; ;
| Last | Frequency | Range |
|---|---|---|
| 17.54 2015 | yearly | 2009 - 2015 |
View Mali's Mali ML: People with Basic Handwashing Facilities Including Soap and Water: Urban: % of Urban Population from 2009 to 2015 in the chart:
Mali ML: Physicians: per 1000 People
ML: Physicians: per 1000 People data was reported at 0.085 Ratio in 2010. This records an increase from the previous number of 0.076 Ratio for 2009. ML: Physicians: per 1000 People data is updated yearly, averaging 0.044 Ratio from Dec 1960 (Median) to 2010, with 19 observations. The data reached an all-time high of 0.085 Ratio in 2010 and a record low of 0.014 Ratio in 1960. ML: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Physicians include generalist and specialist medical practitioners.; ; World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 0.09 2010 | yearly | 1960 - 2010 |
View Mali's Mali ML: Physicians: per 1000 People from 1960 to 2010 in the chart:
Mali ML: Pregnant Women Receiving Prenatal Care
ML: Pregnant Women Receiving Prenatal Care data was reported at 47.900 % in 2015. This records a decrease from the previous number of 74.200 % for 2013. ML: Pregnant Women Receiving Prenatal Care data is updated yearly, averaging 47.900 % from Dec 1987 (Median) to 2015, with 7 observations. The data reached an all-time high of 74.200 % in 2013 and a record low of 31.400 % in 1987. ML: Pregnant Women Receiving Prenatal Care data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Pregnant women receiving prenatal care are the percentage of women attended at least once during pregnancy by skilled health personnel for reasons related to pregnancy.; ; UNICEF, State of the World's Children, Childinfo, and Demographic and Health Surveys.; Weighted average; Good prenatal and postnatal care improve maternal health and reduce maternal and infant mortality.
| Last | Frequency | Range |
|---|---|---|
| 47.90 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Pregnant Women Receiving Prenatal Care from 1987 to 2015 in the chart:
Mali ML: Prevalence of Anemia among Children: % of Children Under 5
ML: Prevalence of Anemia among Children: % of Children Under 5 data was reported at 83.400 % in 2016. This records an increase from the previous number of 83.300 % for 2015. ML: Prevalence of Anemia among Children: % of Children Under 5 data is updated yearly, averaging 83.400 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 86.900 % in 1990 and a record low of 82.000 % in 2008. ML: Prevalence of Anemia among Children: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of anemia, children under age 5, is the percentage of children under age 5 whose hemoglobin level is less than 110 grams per liter at sea level.; ; World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).; Weighted average; Anemia is defined as a low blood haemoglobin concentration. Anaemia may result from a number of causes, with the most significant contributor being iron deficiency. Anaemia resulting from iron deficiency adversely affects cognitive and motor development and causes fatigue and low productivity. Children under age 5 and pregnant women have the highest risk for anemia.
| Last | Frequency | Range |
|---|---|---|
| 83.40 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Prevalence of Anemia among Children: % of Children Under 5 from 1990 to 2016 in the chart:
Mali ML: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49
ML: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49 data was reported at 50.300 % in 2016. This records a decrease from the previous number of 51.100 % for 2015. ML: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49 data is updated yearly, averaging 62.200 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 64.600 % in 1991 and a record low of 50.300 % in 2016. ML: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Prevalence of anemia, non-pregnant women, is the percentage of non-pregnant women whose hemoglobin level is less than 120 grams per liter at sea level.; ; World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 50.30 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49 from 1990 to 2016 in the chart:
Mali ML: Prevalence of Anemia among Pregnant Women: %
ML: Prevalence of Anemia among Pregnant Women: % data was reported at 58.400 % in 2016. This records a decrease from the previous number of 58.900 % for 2015. ML: Prevalence of Anemia among Pregnant Women: % data is updated yearly, averaging 62.400 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 62.900 % in 1999 and a record low of 58.400 % in 2016. ML: Prevalence of Anemia among Pregnant Women: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of anemia, pregnant women, is the percentage of pregnant women whose hemoglobin level is less than 110 grams per liter at sea level.; ; World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 58.40 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Prevalence of Anemia among Pregnant Women: % from 1990 to 2016 in the chart:
Mali ML: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49
ML: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data was reported at 51.300 % in 2016. This records a decrease from the previous number of 52.000 % for 2015. ML: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data is updated yearly, averaging 62.200 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 64.300 % in 1994 and a record low of 51.300 % in 2016. ML: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Prevalence of anemia among women of reproductive age refers to the combined prevalence of both non-pregnant with haemoglobin levels below 12 g/dL and pregnant women with haemoglobin levels below 11 g/dL.; ; World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 51.30 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 from 1990 to 2016 in the chart:
Mali ML: Prevalence of HIV: Female: % Aged 15-24
ML: Prevalence of HIV: Female: % Aged 15-24 data was reported at 0.900 % in 2017. This stayed constant from the previous number of 0.900 % for 2016. ML: Prevalence of HIV: Female: % Aged 15-24 data is updated yearly, averaging 1.200 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 1.600 % in 1997 and a record low of 0.900 % in 2017. ML: Prevalence of HIV: Female: % Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of HIV, female is the percentage of females who are infected with HIV. Youth rates are as a percentage of the relevant age group.; ; UNAIDS estimates.; Weighted average; In many developing countries most new infections occur in young adults, with young women especially vulnerable.
| Last | Frequency | Range |
|---|---|---|
| 0.60 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Prevalence of HIV: Female: % Aged 15-24 from 1990 to 2016 in the chart:
Mali ML: Prevalence of HIV: Male: % Aged 15-24
ML: Prevalence of HIV: Male: % Aged 15-24 data was reported at 0.400 % in 2017. This stayed constant from the previous number of 0.400 % for 2016. ML: Prevalence of HIV: Male: % Aged 15-24 data is updated yearly, averaging 0.500 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 0.600 % in 1999 and a record low of 0.400 % in 2017. ML: Prevalence of HIV: Male: % Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of HIV, male is the percentage of males who are infected with HIV. Youth rates are as a percentage of the relevant age group.; ; UNAIDS estimates.; Weighted average; In many developing countries most new infections occur in young adults, with young women being especially vulnerable.
| Last | Frequency | Range |
|---|---|---|
| 0.30 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Prevalence of HIV: Male: % Aged 15-24 from 1990 to 2016 in the chart:
Mali ML: Prevalence of HIV: Total: % of Population Aged 15-49
ML: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 1.200 % in 2017. This records a decrease from the previous number of 1.300 % for 2016. ML: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 1.400 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 1.600 % in 1999 and a record low of 1.000 % in 1990. ML: Prevalence of HIV: Total: % of Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.; ; UNAIDS estimates.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 1.00 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Prevalence of HIV: Total: % of Population Aged 15-49 from 1990 to 2016 in the chart:
Mali ML: Prevalence of Overweight: Weight for Height: % of Children Under 5
ML: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 1.900 % in 2015. This records an increase from the previous number of 1.000 % for 2010. ML: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 2.100 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 4.700 % in 2006 and a record low of 0.500 % in 1987. ML: Prevalence of Overweight: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues
| Last | Frequency | Range |
|---|---|---|
| 1.90 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Prevalence of Overweight: Weight for Height: % of Children Under 5 from 1987 to 2015 in the chart:
Mali ML: Prevalence of Severe Wasting: Weight for Height: % of Children under 5
ML: Prevalence of Severe Wasting: Weight for Height: % of Children under 5 data was reported at 3.400 % in 2015. This records an increase from the previous number of 1.900 % for 2010. ML: Prevalence of Severe Wasting: Weight for Height: % of Children under 5 data is updated yearly, averaging 3.800 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 9.800 % in 1996 and a record low of 1.900 % in 2010. ML: Prevalence of Severe Wasting: Weight for Height: % of Children under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of severe wasting is the proportion of children under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.
| Last | Frequency | Range |
|---|---|---|
| 3.40 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Prevalence of Severe Wasting: Weight for Height: % of Children under 5 from 1987 to 2015 in the chart:
Mali ML: Prevalence of Stunting: Height for Age: % of Children Under 5
ML: Prevalence of Stunting: Height for Age: % of Children Under 5 data was reported at 30.400 % in 2015. This records an increase from the previous number of 27.800 % for 2010. ML: Prevalence of Stunting: Height for Age: % of Children Under 5 data is updated yearly, averaging 37.150 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 42.700 % in 2001 and a record low of 27.800 % in 2010. ML: Prevalence of Stunting: Height for Age: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.
| Last | Frequency | Range |
|---|---|---|
| 30.40 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Prevalence of Stunting: Height for Age: % of Children Under 5 from 1987 to 2015 in the chart:
Mali ML: Prevalence of Undernourishment: % of Population
ML: Prevalence of Undernourishment: % of Population data was reported at 4.000 % in 2015. This records a decrease from the previous number of 4.900 % for 2014. ML: Prevalence of Undernourishment: % of Population data is updated yearly, averaging 8.350 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 14.600 % in 2000 and a record low of 4.000 % in 2015. ML: Prevalence of Undernourishment: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Population below minimum level of dietary energy consumption (also referred to as prevalence of undernourishment) shows the percentage of the population whose food intake is insufficient to meet dietary energy requirements continuously. Data showing as 5 may signify a prevalence of undernourishment below 5%.; ; Food and Agriculture Organization (http://www.fao.org/publications/en/).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 4.00 2015 | yearly | 2000 - 2015 |
View Mali's Mali ML: Prevalence of Undernourishment: % of Population from 2000 to 2015 in the chart:
Mali ML: Prevalence of Underweight: Weight for Age: % of Children Under 5
ML: Prevalence of Underweight: Weight for Age: % of Children Under 5 data was reported at 25.000 % in 2015. This records an increase from the previous number of 18.900 % for 2010. ML: Prevalence of Underweight: Weight for Age: % of Children Under 5 data is updated yearly, averaging 28.250 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 37.700 % in 1996 and a record low of 18.900 % in 2010. ML: Prevalence of Underweight: Weight for Age: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Prevalence of underweight children is the percentage of children under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.
| Last | Frequency | Range |
|---|---|---|
| 25.00 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Prevalence of Underweight: Weight for Age: % of Children Under 5 from 1987 to 2015 in the chart:
Mali ML: Prevalence of Wasting: Weight for Height: % of Children Under 5
ML: Prevalence of Wasting: Weight for Height: % of Children Under 5 data was reported at 13.500 % in 2015. This records an increase from the previous number of 8.900 % for 2010. ML: Prevalence of Wasting: Weight for Height: % of Children Under 5 data is updated yearly, averaging 13.050 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 22.000 % in 1996 and a record low of 8.900 % in 2010. ML: Prevalence of Wasting: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Prevalence of wasting is the proportion of children under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.
| Last | Frequency | Range |
|---|---|---|
| 13.50 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Prevalence of Wasting: Weight for Height: % of Children Under 5 from 1987 to 2015 in the chart:
Mali ML: Probability of Dying at Age 10-14 Years: per 1000
ML: Probability of Dying at Age 10-14 Years: per 1000 data was reported at 8.400 Ratio in 2019. This records a decrease from the previous number of 8.500 Ratio for 2018. ML: Probability of Dying at Age 10-14 Years: per 1000 data is updated yearly, averaging 9.950 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 12.000 Ratio in 1990 and a record low of 8.400 Ratio in 2019. ML: Probability of Dying at Age 10-14 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Probability of dying between age 10-14 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.
| Last | Frequency | Range |
|---|---|---|
| 8.400 2019 | yearly | 1990 - 2019 |
View Mali's Mali ML: Probability of Dying at Age 10-14 Years: per 1000 from 1990 to 2019 in the chart:
Mali ML: Probability of Dying at Age 15-19 Years: per 1000
ML: Probability of Dying at Age 15-19 Years: per 1000 data was reported at 10.000 Ratio in 2019. This records a decrease from the previous number of 10.200 Ratio for 2018. ML: Probability of Dying at Age 15-19 Years: per 1000 data is updated yearly, averaging 12.600 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 17.900 Ratio in 1990 and a record low of 10.000 Ratio in 2019. ML: Probability of Dying at Age 15-19 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Probability of dying between age 15-19 years of age expressed per 1,000 adolescents age 15, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.
| Last | Frequency | Range |
|---|---|---|
| 10.000 2019 | yearly | 1990 - 2019 |
View Mali's Mali ML: Probability of Dying at Age 15-19 Years: per 1000 from 1990 to 2019 in the chart:
Mali ML: Probability of Dying at Age 20-24 Years: per 1000
ML: Probability of Dying at Age 20-24 Years: per 1000 data was reported at 11.900 Ratio in 2019. This records a decrease from the previous number of 12.100 Ratio for 2018. ML: Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 15.000 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 18.800 Ratio in 1990 and a record low of 11.900 Ratio in 2019. ML: Probability of Dying at Age 20-24 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Probability of dying between age 20-24 years of age expressed per 1,000 youths age 20, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.
| Last | Frequency | Range |
|---|---|---|
| 11.900 2019 | yearly | 1990 - 2019 |
View Mali's Mali ML: Probability of Dying at Age 20-24 Years: per 1000 from 1990 to 2019 in the chart:
Mali ML: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5
ML: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data was reported at 23.500 Ratio in 2016. This records a decrease from the previous number of 24.200 Ratio for 2015. ML: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data is updated yearly, averaging 28.300 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 46.700 Ratio in 1990 and a record low of 23.500 Ratio in 2016. ML: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Probability of dying between age 5-14 years of age expressed per 1,000 children aged 5, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 23.50 2016 | yearly | 1990 - 2016 |
View Mali's Mali ML: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 from 1990 to 2016 in the chart:
Mali ML: Probability of Dying at Age 5-9 Years: per 1000
ML: Probability of Dying at Age 5-9 Years: per 1000 data was reported at 13.800 Ratio in 2019. This records a decrease from the previous number of 14.200 Ratio for 2018. ML: Probability of Dying at Age 5-9 Years: per 1000 data is updated yearly, averaging 19.850 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 28.600 Ratio in 1990 and a record low of 13.800 Ratio in 2019. ML: Probability of Dying at Age 5-9 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Probability of dying between age 5-9 years of age expressed per 1,000 children aged 5, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.
| Last | Frequency | Range |
|---|---|---|
| 13.800 2019 | yearly | 1990 - 2019 |
View Mali's Mali ML: Probability of Dying at Age 5-9 Years: per 1000 from 1990 to 2019 in the chart:
Mali ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day
ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day data was reported at 20.420 % in 2008. ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day data is updated yearly, averaging 20.420 % from Dec 2008 (Median) to 2008, with 1 observations. ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The average time women spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.; ; National statistical offices or national database and publications compiled by United Nations Statistics Division; ;
| Last | Frequency | Range |
|---|---|---|
| 20.42 2008 | yearly | 2008 - 2008 |
View Mali's Mali ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day from 2008 to 2008 in the chart:
Mali ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day
ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day data was reported at 2.500 % in 2008. ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day data is updated yearly, averaging 2.500 % from Dec 2008 (Median) to 2008, with 1 observations. ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The average time men spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.; ; National statistical offices or national database and publications compiled by United Nations Statistics Division; ;
| Last | Frequency | Range |
|---|---|---|
| 2.50 2008 | yearly | 2008 - 2008 |
View Mali's Mali ML: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day from 2008 to 2008 in the chart:
Mali ML: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk
ML: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk data was reported at 62.200 % in 2017. This records a decrease from the previous number of 66.900 % for 2016. ML: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk data is updated yearly, averaging 81.100 % from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 87.800 % in 2003 and a record low of 62.200 % in 2017. ML: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The proportion of population at risk of catastrophic expenditure when surgical care is required. Catastrophic expenditure is defined as direct out of pocket payments for surgical and anaesthesia care exceeding 10% of total income.; ; The Program in Global Surgery and Social Change (PGSSC) at Harvard Medical School (https://www.pgssc.org/); Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 80.60 2014 | yearly | 2014 - 2014 |
View Mali's Mali ML: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk from 2014 to 2014 in the chart:
Mali ML: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk
ML: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk data was reported at 55.400 % in 2017. This records a decrease from the previous number of 63.200 % for 2016. ML: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk data is updated yearly, averaging 67.400 % from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 76.400 % in 2003 and a record low of 55.400 % in 2017. ML: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. The proportion of population at risk of impoverishing expenditure when surgical care is required. Impoverishing expenditure is defined as direct out of pocket payments for surgical and anaesthesia care which drive people below a poverty threshold (using a threshold of $1.25 PPP/day).; ; The Program in Global Surgery and Social Change (PGSSC) at Harvard Medical School (https://www.pgssc.org/); Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 77.70 2014 | yearly | 2014 - 2014 |
View Mali's Mali ML: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk from 2014 to 2014 in the chart:
Mali ML: Smoking Prevalence: Females: % of Adults
ML: Smoking Prevalence: Females: % of Adults data was reported at 1.600 % in 2016. This records a decrease from the previous number of 1.700 % for 2015. ML: Smoking Prevalence: Females: % of Adults data is updated yearly, averaging 2.000 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 4.300 % in 2000 and a record low of 1.600 % in 2016. ML: Smoking Prevalence: Females: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of smoking, female is the percentage of women ages 15 and over who currently smoke any tobacco product on a daily or non-daily basis. It excludes smokeless tobacco use. The rates are age-standardized.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 1.60 2016 | yearly | 2000 - 2016 |
View Mali's Mali ML: Smoking Prevalence: Females: % of Adults from 2000 to 2016 in the chart:
Mali ML: Smoking Prevalence: Males: % of Adults
ML: Smoking Prevalence: Males: % of Adults data was reported at 23.000 % in 2016. This records an increase from the previous number of 22.900 % for 2015. ML: Smoking Prevalence: Males: % of Adults data is updated yearly, averaging 22.700 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 23.000 % in 2016 and a record low of 22.000 % in 2000. ML: Smoking Prevalence: Males: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Prevalence of smoking, male is the percentage of men ages 15 and over who currently smoke any tobacco product on a daily or non-daily basis. It excludes smokeless tobacco use. The rates are age-standardized.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 23.00 2016 | yearly | 2000 - 2016 |
View Mali's Mali ML: Smoking Prevalence: Males: % of Adults from 2000 to 2016 in the chart:
Mali ML: Smoking Prevalence: Total: % of Adults: Aged 15+
ML: Smoking Prevalence: Total: % of Adults: Aged 15+ data was reported at 12.300 % in 2016. This stayed constant from the previous number of 12.300 % for 2015. ML: Smoking Prevalence: Total: % of Adults: Aged 15+ data is updated yearly, averaging 12.400 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 13.000 % in 2000 and a record low of 12.300 % in 2016. ML: Smoking Prevalence: Total: % of Adults: Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Prevalence of smoking is the percentage of men and women ages 15 and over who currently smoke any tobacco product on a daily or non-daily basis. It excludes smokeless tobacco use. The rates are age-standardized.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 12.30 2016 | yearly | 2000 - 2016 |
View Mali's Mali ML: Smoking Prevalence: Total: % of Adults: Aged 15+ from 2000 to 2016 in the chart:
Mali ML: Specialist Surgical Workforce: per 100,000 population
ML: Specialist Surgical Workforce: per 100,000 population data was reported at 1.050 Number in 2014. ML: Specialist Surgical Workforce: per 100,000 population data is updated yearly, averaging 1.050 Number from Dec 2014 (Median) to 2014, with 1 observations. ML: Specialist Surgical Workforce: per 100,000 population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Specialist surgical workforce is the number of specialist surgical, anaesthetic, and obstetric (SAO) providers who are working in each country per 100,000 population.; ; The Lancet Commission on Global Surgery (www.lancetglobalsurgery.org).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 1.05 2014 | yearly | 2014 - 2014 |
View Mali's Mali ML: Specialist Surgical Workforce: per 100,000 population from 2014 to 2014 in the chart:
Mali ML: Suicide Mortality Rate: Female
ML: Suicide Mortality Rate: Female data was reported at 2.700 NA in 2016. This stayed constant from the previous number of 2.700 NA for 2015. ML: Suicide Mortality Rate: Female data is updated yearly, averaging 2.700 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 3.200 NA in 2000 and a record low of 2.700 NA in 2016. ML: Suicide Mortality Rate: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 2.700 2016 | yearly | 2000 - 2016 |
View Mali's Mali ML: Suicide Mortality Rate: Female from 2000 to 2016 in the chart:
Mali ML: Suicide Mortality Rate: Male
ML: Suicide Mortality Rate: Male data was reported at 6.900 NA in 2016. This stayed constant from the previous number of 6.900 NA for 2015. ML: Suicide Mortality Rate: Male data is updated yearly, averaging 7.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 7.800 NA in 2000 and a record low of 6.900 NA in 2016. ML: Suicide Mortality Rate: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 6.900 2016 | yearly | 2000 - 2016 |
View Mali's Mali ML: Suicide Mortality Rate: Male from 2000 to 2016 in the chart:
Mali ML: Suicide Mortality Rate: per 100,000 Population
ML: Suicide Mortality Rate: per 100,000 Population data was reported at 4.800 Number in 2016. This stayed constant from the previous number of 4.800 Number for 2015. ML: Suicide Mortality Rate: per 100,000 Population data is updated yearly, averaging 4.800 Number from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 5.500 Number in 2000 and a record low of 4.800 Number in 2016. ML: Suicide Mortality Rate: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 4.80 2016 | yearly | 2000 - 2016 |
View Mali's Mali ML: Suicide Mortality Rate: per 100,000 Population from 2000 to 2016 in the chart:
Mali ML: Survival To Age 65: Female: % of Cohort
ML: Survival To Age 65: Female: % of Cohort data was reported at 58.105 % in 2016. This records an increase from the previous number of 57.342 % for 2015. ML: Survival To Age 65: Female: % of Cohort data is updated yearly, averaging 41.265 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 58.105 % in 2016 and a record low of 18.237 % in 1960. ML: Survival To Age 65: Female: % of Cohort data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Survival to age 65 refers to the percentage of a cohort of newborn infants that would survive to age 65, if subject to age specific mortality rates of the specified year.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 58.10 2016 | yearly | 1960 - 2016 |
View Mali's Mali ML: Survival To Age 65: Female: % of Cohort from 1960 to 2016 in the chart:
Mali ML: Survival To Age 65: Male: % of Cohort
ML: Survival To Age 65: Male: % of Cohort data was reported at 55.110 % in 2016. This records an increase from the previous number of 54.383 % for 2015. ML: Survival To Age 65: Male: % of Cohort data is updated yearly, averaging 38.390 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 55.110 % in 2016 and a record low of 14.525 % in 1960. ML: Survival To Age 65: Male: % of Cohort data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Survival to age 65 refers to the percentage of a cohort of newborn infants that would survive to age 65, if subject to age specific mortality rates of the specified year.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 55.11 2016 | yearly | 1960 - 2016 |
View Mali's Mali ML: Survival To Age 65: Male: % of Cohort from 1960 to 2016 in the chart:
Mali ML: Teenage Mothers
ML: Teenage Mothers data was reported at 37.700 % in 2015. This records a decrease from the previous number of 39.300 % for 2013. ML: Teenage Mothers data is updated yearly, averaging 39.850 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 50.600 % in 1987 and a record low of 35.500 % in 2006. ML: Teenage Mothers data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Teenage mothers are the percentage of women ages 15-19 who already have children or are currently pregnant.; ; Demographic and Health Surveys.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 37.70 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Teenage Mothers from 1987 to 2015 in the chart:
Mali ML: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+
ML: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+ data was reported at 1.300 Number in 2016. ML: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+ data is updated yearly, averaging 1.300 Number from Dec 2016 (Median) to 2016, with 1 observations. ML: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Total alcohol per capita consumption is defined as the total (sum of recorded and unrecorded alcohol) amount of alcohol consumed per person (15 years of age or older) over a calendar year, in litres of pure alcohol, adjusted for tourist consumption.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 1.30 2016 | yearly | 2016 - 2016 |
View Mali's Mali ML: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+ from 2016 to 2016 in the chart:
Mali ML: Tuberculosis Case Detection Rate: All Forms
ML: Tuberculosis Case Detection Rate: All Forms data was reported at 68.000 % in 2016. This stayed constant from the previous number of 68.000 % for 2015. ML: Tuberculosis Case Detection Rate: All Forms data is updated yearly, averaging 56.000 % from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 71.000 % in 2009 and a record low of 50.000 % in 2000. ML: Tuberculosis Case Detection Rate: All Forms data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Tuberculosis case detection rate (all forms) is the number of new and relapse tuberculosis cases notified to WHO in a given year, divided by WHO's estimate of the number of incident tuberculosis cases for the same year, expressed as a percentage. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.; ; World Health Organization, Global Tuberculosis Report.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 68.00 2016 | yearly | 2000 - 2016 |
View Mali's Mali ML: Tuberculosis Case Detection Rate: All Forms from 2000 to 2016 in the chart:
Mali ML: Tuberculosis Treatment Success Rate: % of New Cases
ML: Tuberculosis Treatment Success Rate: % of New Cases data was reported at 77.000 % in 2015. This records an increase from the previous number of 73.000 % for 2014. ML: Tuberculosis Treatment Success Rate: % of New Cases data is updated yearly, averaging 75.000 % from Dec 2001 (Median) to 2015, with 15 observations. The data reached an all-time high of 93.000 % in 2012 and a record low of 50.000 % in 2002. ML: Tuberculosis Treatment Success Rate: % of New Cases data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Tuberculosis treatment success rate is the percentage of all new tuberculosis cases (or new and relapse cases for some countries) registered under a national tuberculosis control programme in a given year that successfully completed treatment, with or without bacteriological evidence of success ('cured' and 'treatment completed' respectively).; ; World Health Organization, Global Tuberculosis Report.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 77.00 2015 | yearly | 2001 - 2015 |
View Mali's Mali ML: Tuberculosis Treatment Success Rate: % of New Cases from 2001 to 2015 in the chart:
Mali ML: UHC Service Coverage Index
ML: UHC Service Coverage Index data was reported at 32.000 % in 2015. ML: UHC Service Coverage Index data is updated yearly, averaging 32.000 % from Dec 2015 (Median) to 2015, with 1 observations. ML: UHC Service Coverage Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Coverage index for essential health services (based on tracer interventions that include reproductive, maternal, newborn and child health, infectious diseases, noncommunicable diseases and service capacity and access). It is presented on a scale of 0 to 100. Values greater than or equal to 80 are presented as 80 as the index does not provide fine resolution at high values.; ; Hogan et al. An index of the coverage of essential health services for monitoring UHC within the SDGs, Lancet Global Health 2017.; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 32.00 2015 | yearly | 2015 - 2015 |
View Mali's Mali ML: UHC Service Coverage Index from 2015 to 2015 in the chart:
Mali ML: Unmet Need for Contraception: % of Married Women Aged 15-49
ML: Unmet Need for Contraception: % of Married Women Aged 15-49 data was reported at 17.200 % in 2015. This records a decrease from the previous number of 26.000 % for 2013. ML: Unmet Need for Contraception: % of Married Women Aged 15-49 data is updated yearly, averaging 26.750 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 29.600 % in 2001 and a record low of 17.200 % in 2015. ML: Unmet Need for Contraception: % of Married Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Unmet need for contraception is the percentage of fertile, married women of reproductive age who do not want to become pregnant and are not using contraception.; ; Household surveys, including Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Largely compiled by United Nations Population Division.; Weighted Average; Unmet need for contraception measures the capacity women have in achieving their desired family size and birth spacing. Many couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects.
| Last | Frequency | Range |
|---|---|---|
| 17.20 2015 | yearly | 1987 - 2015 |
View Mali's Mali ML: Unmet Need for Contraception: % of Married Women Aged 15-49 from 1987 to 2015 in the chart:
Mali ML: Use of Insecticide-Treated Bed Nets: % of Under-5 Population
ML: Use of Insecticide-Treated Bed Nets: % of Under-5 Population data was reported at 71.200 % in 2015. This records an increase from the previous number of 69.000 % for 2013. ML: Use of Insecticide-Treated Bed Nets: % of Under-5 Population data is updated yearly, averaging 45.600 % from Dec 2003 (Median) to 2015, with 5 observations. The data reached an all-time high of 71.200 % in 2015 and a record low of 8.400 % in 2003. ML: Use of Insecticide-Treated Bed Nets: % of Under-5 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Use of insecticide-treated bed nets refers to the percentage of children under age five who slept under an insecticide-treated bednet to prevent malaria.; ; UNICEF, State of the World's Children, Childinfo, and Demographic and Health Surveys.; Weighted average;
| Last | Frequency | Range |
|---|---|---|
| 71.20 2015 | yearly | 2003 - 2015 |
View Mali's Mali ML: Use of Insecticide-Treated Bed Nets: % of Under-5 Population from 2003 to 2015 in the chart:
Mali ML: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months
ML: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months data was reported at 88.000 % in 2015. This records a decrease from the previous number of 98.000 % for 2013. ML: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months data is updated yearly, averaging 91.000 % from Dec 1999 (Median) to 2015, with 14 observations. The data reached an all-time high of 100.000 % in 1999 and a record low of 10.000 % in 2000. ML: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Vitamin A supplementation refers to the percentage of children ages 6-59 months old who received at least two doses of vitamin A in the previous year.; ; United Nations Children's Fund, State of the World's Children.; Weighted average; Vitamin A is essential for optimal functioning of the immune system. Vitamin A deficiency, a leading cause of blindness, also causes a greater risk of dying from a range of childhood ailments such as measles, malaria, and diarrhea. In low- and middle-income countries, where vitamin A is consumed largely in fruits and vegetables, daily per capita intake is often insufficient to meet dietary requirements. Providing young children with two high-dose vitamin A capsules a year is a safe, cost-effective, efficient strategy for eliminating vitamin A deficiency and improving child survival. Giving vitamin A to new breastfeeding mothers helps protect their children during the first few months of life. Food fortification with vitamin A is being introduced in many developing countries.
| Last | Frequency | Range |
|---|---|---|
| 88.00 2015 | yearly | 1999 - 2015 |
View Mali's Mali ML: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months from 1999 to 2015 in the chart:
Mali ML: Wanted Fertility Rate: Births per Woman
ML: Wanted Fertility Rate: Births per Woman data was reported at 5.300 Ratio in 2013. This records a decrease from the previous number of 6.000 Ratio for 2006. ML: Wanted Fertility Rate: Births per Woman data is updated yearly, averaging 6.000 Ratio from Dec 1987 (Median) to 2013, with 5 observations. The data reached an all-time high of 6.600 Ratio in 1987 and a record low of 5.300 Ratio in 2013. ML: Wanted Fertility Rate: Births per Woman data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Wanted fertility rate is an estimate of what the total fertility rate would be if all unwanted births were avoided.; ; Demographic and Health Surveys.; Weighted Average;
| Last | Frequency | Range |
|---|---|---|
| 5.30 2013 | yearly | 1987 - 2013 |
View Mali's Mali ML: Wanted Fertility Rate: Births per Woman from 1987 to 2013 in the chart:
Mali ML: Women Making Their Own Informed Decisions Regarding Sexual Relations, Contraceptive Use and Reproductive Health Care: % Aged 15-49
ML: Women Making Their Own Informed Decisions Regarding Sexual Relations, Contraceptive Use and Reproductive Health Care: % Aged 15-49 data was reported at 6.500 % in 2013. ML: Women Making Their Own Informed Decisions Regarding Sexual Relations, Contraceptive Use and Reproductive Health Care: % Aged 15-49 data is updated yearly, averaging 6.500 % from Dec 2013 (Median) to 2013, with 1 observations. ML: Women Making Their Own Informed Decisions Regarding Sexual Relations, Contraceptive Use and Reproductive Health Care: % Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Proportion of women ages 15-49 years (married or in union) who make their own decision on all three selected areas i.e. can say no to sexual intercourse with their husband or partner if they do not want; decide on use of contraception; and decide on their own health care. Only women who provide a “yes” answer to all three components are considered as women who “make her own decisions regarding sexual and reproductive”.; ; Demographic and Health Surveys compiled by United Nations Population Fund; ;
| Last | Frequency | Range |
|---|---|---|
| 6.50 2013 | yearly | 2013 - 2013 |
View Mali's Mali ML: Women Making Their Own Informed Decisions Regarding Sexual Relations, Contraceptive Use and Reproductive Health Care: % Aged 15-49 from 2013 to 2013 in the chart:
Mali ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49
ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data was reported at 8.900 % in 2013. This records a decrease from the previous number of 11.300 % for 2006. ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data is updated yearly, averaging 8.900 % from Dec 2001 (Median) to 2013, with 3 observations. The data reached an all-time high of 11.300 % in 2006 and a record low of 8.200 % in 2001. ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Women participating in the three decisions (own health care, major household purchases, and visiting family) is the percentage of currently married women aged 15-49 who say that they alone or jointly have the final say in all of the three decisions (own health care, large purchases and visits to family, relatives, and friends).; ; Demographic and Health Surveys (DHS); ;
| Last | Frequency | Range |
|---|---|---|
| 8.90 2013 | yearly | 2001 - 2013 |
View Mali's Mali ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 from 2001 to 2013 in the chart:
Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: Any of Five Reasons
ML: Women Who Believe a Husband is Justified in Beating His Wife: Any of Five Reasons data was reported at 76.300 % in 2013. This records a decrease from the previous number of 87.200 % for 2010. ML: Women Who Believe a Husband is Justified in Beating His Wife: Any of Five Reasons data is updated yearly, averaging 81.750 % from Dec 2001 (Median) to 2013, with 4 observations. The data reached an all-time high of 88.800 % in 2001 and a record low of 75.200 % in 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: Any of Five Reasons data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner for any of the following five reasons: argues with him; refuses to have sex; burns the food; goes out without telling him; or when she neglects the children.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other surveys: STATcompiler (http://www.statcompiler.com/) as of November 22, 2016, UNICEF global databases (http://www.data.unicef.org/) as of November 2015. MICS Compiler (http://www.micscompiler.org/) as of June 12, 2016.; ;
| Last | Frequency | Range |
|---|---|---|
| 76.30 2013 | yearly | 2001 - 2013 |
View Mali's Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: Any of Five Reasons from 2001 to 2013 in the chart:
Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Argues with Him
ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Argues with Him data was reported at 58.400 % in 2013. This records an increase from the previous number of 49.100 % for 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Argues with Him data is updated yearly, averaging 58.400 % from Dec 2001 (Median) to 2013, with 3 observations. The data reached an all-time high of 61.700 % in 2001 and a record low of 49.100 % in 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Argues with Him data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she argues with him.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other surveys: STATcompiler (http://www.statcompiler.com/) as of November 22, 2016, UNICEF global databases (http://www.data.unicef.org/) as of November 2015. MICS Compiler (http://www.micscompiler.org/) as of June 12, 2016.; ;
| Last | Frequency | Range |
|---|---|---|
| 58.40 2013 | yearly | 2001 - 2013 |
View Mali's Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Argues with Him from 2001 to 2013 in the chart:
Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Burns the Food
ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Burns the Food data was reported at 26.300 % in 2013. This records an increase from the previous number of 23.400 % for 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Burns the Food data is updated yearly, averaging 26.300 % from Dec 2001 (Median) to 2013, with 3 observations. The data reached an all-time high of 33.600 % in 2001 and a record low of 23.400 % in 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Burns the Food data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she burns the food.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other surveys: STATcompiler (http://www.statcompiler.com/) as of November 22, 2016, UNICEF global databases (http://www.data.unicef.org/) as of November 2015. MICS Compiler (http://www.micscompiler.org/) as of June 12, 2016.; ;
| Last | Frequency | Range |
|---|---|---|
| 26.30 2013 | yearly | 2001 - 2013 |
View Mali's Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Burns the Food from 2001 to 2013 in the chart:
Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Goes Out without Telling Him
ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Goes Out without Telling Him data was reported at 55.000 % in 2013. This records a decrease from the previous number of 60.300 % for 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Goes Out without Telling Him data is updated yearly, averaging 60.300 % from Dec 2001 (Median) to 2013, with 3 observations. The data reached an all-time high of 74.900 % in 2001 and a record low of 55.000 % in 2013. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Goes Out without Telling Him data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she goes out without telling him.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other surveys: STATcompiler (http://www.statcompiler.com/) as of November 22, 2016, UNICEF global databases (http://www.data.unicef.org/) as of November 2015. MICS Compiler (http://www.micscompiler.org/) as of June 12, 2016.; ;
| Last | Frequency | Range |
|---|---|---|
| 55.00 2013 | yearly | 2001 - 2013 |
View Mali's Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Goes Out without Telling Him from 2001 to 2013 in the chart:
Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Neglects the Children
ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Neglects the Children data was reported at 48.700 % in 2013. This records a decrease from the previous number of 52.600 % for 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Neglects the Children data is updated yearly, averaging 52.600 % from Dec 2001 (Median) to 2013, with 3 observations. The data reached an all-time high of 71.300 % in 2001 and a record low of 48.700 % in 2013. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Neglects the Children data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she neglects the children.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other surveys: STATcompiler (http://www.statcompiler.com/) as of November 22, 2016, UNICEF global databases (http://www.data.unicef.org/) as of November 2015. MICS Compiler (http://www.micscompiler.org/) as of June 12, 2016.; ;
| Last | Frequency | Range |
|---|---|---|
| 48.70 2013 | yearly | 2001 - 2013 |
View Mali's Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Neglects the Children from 2001 to 2013 in the chart:
Mali ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Refuses Sex with Him
ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Refuses Sex with Him data was reported at 58.900 % in 2013. This records an increase from the previous number of 56.800 % for 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Refuses Sex with Him data is updated yearly, averaging 58.900 % from Dec 2001 (Median) to 2013, with 3 observations. The data reached an all-time high of 73.500 % in 2001 and a record low of 56.800 % in 2006. ML: Women Who Believe a Husband is Justified in Beating His Wife: When She Refuses Sex with Him data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she refuses sex with him.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other surveys: STATcompiler (http://www.statcompiler.com/) as of November 22, 2016, UNICEF global databases (http://www.data.unicef.org/) as of November 2015. MICS Compiler (http://www.micscompiler.org/) as of June 12, 2016.; ;
| Last | Frequency | Range |
|---|---|---|
| 58.90 2013 | yearly | 2001 - 2013 |