South Africa Health Statistics
South Africa ZA: People Practicing Open Defecation: Urban: % of Urban Population
ZA: People Practicing Open Defecation: Urban: % of Urban Population data was reported at 0.804 % in 2015. This records a decrease from the previous number of 0.936 % for 2014. ZA: People Practicing Open Defecation: Urban: % of Urban Population data is updated yearly, averaging 1.795 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 2.786 % in 2000 and a record low of 0.804 % in 2015. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 0.80 2015 | yearly | 2000 - 2015 |
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South Africa ZA: People Using At Least Basic Drinking Water Services: % of Population
ZA: People Using At Least Basic Drinking Water Services: % of Population data was reported at 84.697 % in 2015. This records an increase from the previous number of 84.244 % for 2014. ZA: People Using At Least Basic Drinking Water Services: % of Population data is updated yearly, averaging 81.063 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 84.697 % in 2015 and a record low of 76.980 % in 2000. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 84.70 2015 | yearly | 2000 - 2015 |
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South Africa ZA: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population
ZA: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population data was reported at 62.626 % in 2015. This records an increase from the previous number of 61.888 % for 2014. ZA: People Using At Least Basic Drinking Water Services: Rural: % of Rural Population data is updated yearly, averaging 57.090 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 62.626 % in 2015 and a record low of 51.554 % in 2000. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 62.63 2015 | yearly | 2000 - 2015 |
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South Africa ZA: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population
ZA: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population data was reported at 96.686 % in 2015. This records an increase from the previous number of 96.657 % for 2014. ZA: People Using At Least Basic Drinking Water Services: Urban: % of Urban Population data is updated yearly, averaging 96.466 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 96.686 % in 2015 and a record low of 96.246 % in 2000. ZA: 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 South Africa – Table ZA.World Bank.WDI: 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 |
|---|---|---|
| 96.69 2015 | yearly | 2000 - 2015 |
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South Africa ZA: People Using At Least Basic Sanitation Services: % of Population
ZA: People Using At Least Basic Sanitation Services: % of Population data was reported at 73.129 % in 2015. This records an increase from the previous number of 72.309 % for 2014. ZA: People Using At Least Basic Sanitation Services: % of Population data is updated yearly, averaging 66.641 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 73.129 % in 2015 and a record low of 59.387 % in 2000. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 73.13 2015 | yearly | 2000 - 2015 |
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South Africa ZA: People Using At Least Basic Sanitation Services: Rural: % of Rural Population
ZA: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data was reported at 68.672 % in 2015. This records an increase from the previous number of 67.066 % for 2014. ZA: People Using At Least Basic Sanitation Services: Rural: % of Rural Population data is updated yearly, averaging 56.623 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 68.672 % in 2015 and a record low of 44.575 % in 2000. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 68.67 2015 | yearly | 2000 - 2015 |
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South Africa ZA: People Using At Least Basic Sanitation Services: Urban: % of Urban Population
ZA: People Using At Least Basic Sanitation Services: Urban: % of Urban Population data was reported at 75.550 % in 2015. This records an increase from the previous number of 75.220 % for 2014. ZA: People Using At Least Basic Sanitation Services: Urban: % of Urban Population data is updated yearly, averaging 73.080 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 75.550 % in 2015 and a record low of 70.611 % in 2000. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 75.55 2015 | yearly | 2000 - 2015 |
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South Africa ZA: People Using Safely Managed Drinking Water Services: Urban: % of Urban Population
ZA: People Using Safely Managed Drinking Water Services: Urban: % of Urban Population data was reported at 85.025 % in 2015. This records a decrease from the previous number of 85.789 % for 2014. ZA: People Using Safely Managed Drinking Water Services: Urban: % of Urban Population data is updated yearly, averaging 90.437 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 90.543 % in 2001 and a record low of 85.025 % in 2015. ZA: People Using Safely Managed 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 South Africa – Table ZA.World Bank: Health Statistics. The percentage of people using drinking water from an improved source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. 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 |
|---|---|---|
| 85.02 2015 | yearly | 2000 - 2015 |
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South Africa ZA: Physicians: per 1000 People
ZA: Physicians: per 1000 People data was reported at 0.818 Ratio in 2016. This records an increase from the previous number of 0.767 Ratio for 2015. ZA: Physicians: per 1000 People data is updated yearly, averaging 0.720 Ratio from Dec 1965 (Median) to 2016, with 14 observations. The data reached an all-time high of 0.818 Ratio in 2016 and a record low of 0.488 Ratio in 1965. ZA: Physicians: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: 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 |
|---|---|---|
| 0.82 2016 | yearly | 1965 - 2016 |
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South Africa ZA: Pregnant Women Receiving Prenatal Care
ZA: Pregnant Women Receiving Prenatal Care data was reported at 93.700 % in 2016. This records a decrease from the previous number of 97.100 % for 2008. ZA: Pregnant Women Receiving Prenatal Care data is updated yearly, averaging 93.700 % from Dec 1995 (Median) to 2016, with 5 observations. The data reached an all-time high of 97.100 % in 2008 and a record low of 89.000 % in 1995. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 93.70 2016 | yearly | 1995 - 2016 |
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South Africa ZA: Prevalence of Anemia among Children: % of Children Under 5
ZA: Prevalence of Anemia among Children: % of Children Under 5 data was reported at 36.800 % in 2016. This records an increase from the previous number of 36.700 % for 2015. ZA: Prevalence of Anemia among Children: % of Children Under 5 data is updated yearly, averaging 36.700 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 38.000 % in 2007 and a record low of 33.800 % in 1994. ZA: 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 South Africa – Table ZA.World Bank: 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 |
|---|---|---|
| 36.80 2016 | yearly | 1990 - 2016 |
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South Africa ZA: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49
ZA: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49 data was reported at 25.700 % in 2016. This records an increase from the previous number of 25.400 % for 2015. ZA: Prevalence of Anemia among Non-Pregnant Women: % of Women Aged 15-49 data is updated yearly, averaging 31.400 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 38.400 % in 1990 and a record low of 25.200 % in 2014. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 25.70 2016 | yearly | 1990 - 2016 |
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South Africa ZA: Prevalence of Anemia among Pregnant Women: %
ZA: Prevalence of Anemia among Pregnant Women: % data was reported at 28.100 % in 2016. This records an increase from the previous number of 27.900 % for 2015. ZA: Prevalence of Anemia among Pregnant Women: % data is updated yearly, averaging 31.500 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 35.200 % in 1990 and a record low of 27.900 % in 2015. ZA: 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 South Africa – Table ZA.World Bank: 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 |
|---|---|---|
| 28.10 2016 | yearly | 1990 - 2016 |
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South Africa ZA: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49
ZA: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data was reported at 25.800 % in 2016. This records an increase from the previous number of 25.500 % for 2015. ZA: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data is updated yearly, averaging 31.400 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 38.200 % in 1990 and a record low of 25.300 % in 2014. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 25.80 2016 | yearly | 1990 - 2016 |
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South Africa ZA: Prevalence of HIV: Female: % Aged 15-24
ZA: Prevalence of HIV: Female: % Aged 15-24 data was reported at 10.400 % in 2016. This stayed constant from the previous number of 10.400 % for 2015. ZA: Prevalence of HIV: Female: % Aged 15-24 data is updated yearly, averaging 11.600 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 16.800 % in 2000 and a record low of 1.000 % in 1990. ZA: 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 South Africa – Table ZA.World Bank: 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 |
|---|---|---|
| 10.40 2016 | yearly | 1990 - 2016 |
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South Africa ZA: Prevalence of HIV: Male: % Aged 15-24
ZA: Prevalence of HIV: Male: % Aged 15-24 data was reported at 4.000 % in 2016. This records an increase from the previous number of 3.900 % for 2015. ZA: Prevalence of HIV: Male: % Aged 15-24 data is updated yearly, averaging 4.100 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 5.900 % in 2000 and a record low of 0.500 % in 1990. ZA: 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 South Africa – Table ZA.World Bank: 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 |
|---|---|---|
| 4.00 2016 | yearly | 1990 - 2016 |
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South Africa ZA: Prevalence of HIV: Total: % of Population Aged 15-49
ZA: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 18.900 % in 2016. This stayed constant from the previous number of 18.900 % for 2015. ZA: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 16.400 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 18.900 % in 2016 and a record low of 0.700 % in 1990. ZA: 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 South Africa – Table ZA.World Bank: 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 |
|---|---|---|
| 18.90 2016 | yearly | 1990 - 2016 |
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South Africa ZA: Prevalence of Overweight: Weight for Height: % of Children Under 5
ZA: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 13.300 % in 2016. This records a decrease from the previous number of 17.200 % for 2012. ZA: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 13.300 % from Dec 1995 (Median) to 2016, with 6 observations. The data reached an all-time high of 19.200 % in 2004 and a record low of 10.300 % in 1995. ZA: 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 South Africa – Table ZA.World Bank.WDI: 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 |
|---|---|---|
| 13.30 2016 | yearly | 1995 - 2016 |
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South Africa ZA: Prevalence of Severe Wasting: Weight for Height: % of Children under 5
ZA: Prevalence of Severe Wasting: Weight for Height: % of Children under 5 data was reported at 0.600 % in 2016. This records a decrease from the previous number of 3.100 % for 2012. ZA: Prevalence of Severe Wasting: Weight for Height: % of Children under 5 data is updated yearly, averaging 2.750 % from Dec 2004 (Median) to 2016, with 4 observations. The data reached an all-time high of 4.000 % in 2004 and a record low of 0.600 % in 2016. ZA: 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 South Africa – Table ZA.World Bank: 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 |
|---|---|---|
| 0.60 2016 | yearly | 2004 - 2016 |
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South Africa ZA: Prevalence of Stunting: Height for Age: % of Children Under 5
ZA: Prevalence of Stunting: Height for Age: % of Children Under 5 data was reported at 27.400 % in 2016. This records an increase from the previous number of 27.200 % for 2012. ZA: Prevalence of Stunting: Height for Age: % of Children Under 5 data is updated yearly, averaging 28.700 % from Dec 1994 (Median) to 2016, with 7 observations. The data reached an all-time high of 32.800 % in 2004 and a record low of 24.900 % in 2008. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 27.40 2016 | yearly | 1994 - 2016 |
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South Africa ZA: Prevalence of Undernourishment: % of Population
ZA: Prevalence of Undernourishment: % of Population data was reported at 4.600 % in 2015. This records an increase from the previous number of 4.000 % for 2014. ZA: Prevalence of Undernourishment: % of Population data is updated yearly, averaging 4.200 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 4.700 % in 2000 and a record low of 3.600 % in 2012. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 4.60 2015 | yearly | 2000 - 2015 |
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South Africa ZA: Prevalence of Underweight: Weight for Age: % of Children Under 5
ZA: Prevalence of Underweight: Weight for Age: % of Children Under 5 data was reported at 5.900 % in 2016. This records a decrease from the previous number of 8.500 % for 2012. ZA: Prevalence of Underweight: Weight for Age: % of Children Under 5 data is updated yearly, averaging 8.650 % from Dec 1995 (Median) to 2016, with 6 observations. The data reached an all-time high of 11.600 % in 2004 and a record low of 5.900 % in 2016. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 5.90 2016 | yearly | 1995 - 2016 |
View South Africa's South Africa ZA: Prevalence of Underweight: Weight for Age: % of Children Under 5 from 1995 to 2016 in the chart:
South Africa ZA: Prevalence of Wasting: Weight for Height: % of Children Under 5
ZA: Prevalence of Wasting: Weight for Height: % of Children Under 5 data was reported at 2.500 % in 2016. This records a decrease from the previous number of 5.600 % for 2012. ZA: Prevalence of Wasting: Weight for Height: % of Children Under 5 data is updated yearly, averaging 4.650 % from Dec 1995 (Median) to 2016, with 6 observations. The data reached an all-time high of 7.400 % in 2004 and a record low of 2.500 % in 2016. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 2.50 2016 | yearly | 1995 - 2016 |
View South Africa's South Africa ZA: Prevalence of Wasting: Weight for Height: % of Children Under 5 from 1995 to 2016 in the chart:
South Africa ZA: Probability of Dying at Age 10-14 Years: per 1000
ZA: Probability of Dying at Age 10-14 Years: per 1000 data was reported at 3.000 Ratio in 2019. This records a decrease from the previous number of 3.100 Ratio for 2018. ZA: Probability of Dying at Age 10-14 Years: per 1000 data is updated yearly, averaging 3.800 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 5.200 Ratio in 2008 and a record low of 2.400 Ratio in 1990. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 3.000 2019 | yearly | 1990 - 2019 |
View South Africa's South Africa ZA: Probability of Dying at Age 10-14 Years: per 1000 from 1990 to 2019 in the chart:
South Africa ZA: Probability of Dying at Age 15-19 Years: per 1000
ZA: Probability of Dying at Age 15-19 Years: per 1000 data was reported at 7.600 Ratio in 2019. This records a decrease from the previous number of 7.700 Ratio for 2018. ZA: Probability of Dying at Age 15-19 Years: per 1000 data is updated yearly, averaging 8.550 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 10.300 Ratio in 2004 and a record low of 7.600 Ratio in 2019. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 7.600 2019 | yearly | 1990 - 2019 |
View South Africa's South Africa ZA: Probability of Dying at Age 15-19 Years: per 1000 from 1990 to 2019 in the chart:
South Africa ZA: Probability of Dying at Age 20-24 Years: per 1000
ZA: Probability of Dying at Age 20-24 Years: per 1000 data was reported at 12.400 Ratio in 2019. This records a decrease from the previous number of 12.900 Ratio for 2018. ZA: Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 19.800 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 28.400 Ratio in 2004 and a record low of 12.400 Ratio in 2019. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 12.400 2019 | yearly | 1990 - 2019 |
View South Africa's South Africa ZA: Probability of Dying at Age 20-24 Years: per 1000 from 1990 to 2019 in the chart:
South Africa ZA: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5
ZA: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data was reported at 5.200 Ratio in 2016. This records a decrease from the previous number of 5.700 Ratio for 2015. ZA: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 data is updated yearly, averaging 8.300 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 10.500 Ratio in 1990 and a record low of 5.200 Ratio in 2016. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 5.20 2016 | yearly | 1990 - 2016 |
View South Africa's South Africa ZA: Probability of Dying at Age 5-14 Years: per 1000 Children Age 5 from 1990 to 2016 in the chart:
South Africa ZA: Probability of Dying at Age 5-9 Years: per 1000
ZA: Probability of Dying at Age 5-9 Years: per 1000 data was reported at 2.500 Ratio in 2019. This records a decrease from the previous number of 2.700 Ratio for 2018. ZA: Probability of Dying at Age 5-9 Years: per 1000 data is updated yearly, averaging 5.750 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 7.800 Ratio in 2005 and a record low of 2.500 Ratio in 2019. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 2.500 2019 | yearly | 1990 - 2019 |
View South Africa's South Africa ZA: Probability of Dying at Age 5-9 Years: per 1000 from 1990 to 2019 in the chart:
South Africa ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day
ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day data was reported at 15.900 % in 2010. This records an increase from the previous number of 15.000 % for 2000. ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day data is updated yearly, averaging 15.450 % from Dec 2000 (Median) to 2010, with 2 observations. The data reached an all-time high of 15.900 % in 2010 and a record low of 15.000 % in 2000. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 15.90 2010 | yearly | 2000 - 2010 |
View South Africa's South Africa ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Female: % of 24 Hour Day from 2000 to 2010 in the chart:
South Africa ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day
ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day data was reported at 6.740 % in 2010. This records an increase from the previous number of 5.760 % for 2000. ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day data is updated yearly, averaging 6.250 % from Dec 2000 (Median) to 2010, with 2 observations. The data reached an all-time high of 6.740 % in 2010 and a record low of 5.760 % in 2000. ZA: 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 South Africa – Table ZA.World Bank.WDI: 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 |
|---|---|---|
| 6.74 2010 | yearly | 2000 - 2010 |
View South Africa's South Africa ZA: Proportion of Time Spent on Unpaid Domestic and Care Work: Male: % of 24 Hour Day from 2000 to 2010 in the chart:
South Africa ZA: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk
ZA: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk data was reported at 15.000 % in 2017. This records an increase from the previous number of 14.800 % for 2016. ZA: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk data is updated yearly, averaging 15.400 % from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 23.000 % in 2005 and a record low of 14.500 % in 2012. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 25.50 2014 | yearly | 2014 - 2014 |
View South Africa's South Africa ZA: Risk of Catastrophic Expenditure for Surgical Care: % of People at Risk from 2014 to 2014 in the chart:
South Africa ZA: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk
ZA: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk data was reported at 27.100 % in 2017. This records a decrease from the previous number of 27.300 % for 2016. ZA: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk data is updated yearly, averaging 27.300 % from Dec 2003 (Median) to 2017, with 15 observations. The data reached an all-time high of 32.700 % in 2005 and a record low of 23.700 % in 2004. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 50.10 2014 | yearly | 2014 - 2014 |
View South Africa's South Africa ZA: Risk of Impoverishing Expenditure for Surgical Care: % of People at Risk from 2014 to 2014 in the chart:
South Africa ZA: Smoking Prevalence: Females: % of Adults
ZA: Smoking Prevalence: Females: % of Adults data was reported at 8.100 % in 2016. This records a decrease from the previous number of 8.300 % for 2015. ZA: Smoking Prevalence: Females: % of Adults data is updated yearly, averaging 8.700 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 11.100 % in 2000 and a record low of 8.100 % in 2016. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 8.10 2016 | yearly | 2000 - 2016 |
View South Africa's South Africa ZA: Smoking Prevalence: Females: % of Adults from 2000 to 2016 in the chart:
South Africa ZA: Smoking Prevalence: Males: % of Adults
ZA: Smoking Prevalence: Males: % of Adults data was reported at 33.200 % in 2016. This records a decrease from the previous number of 33.400 % for 2015. ZA: Smoking Prevalence: Males: % of Adults data is updated yearly, averaging 33.800 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 35.400 % in 2000 and a record low of 33.200 % in 2016. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 33.20 2016 | yearly | 2000 - 2016 |
View South Africa's South Africa ZA: Smoking Prevalence: Males: % of Adults from 2000 to 2016 in the chart:
South Africa ZA: Smoking Prevalence: Total: % of Adults: Aged 15+
ZA: Smoking Prevalence: Total: % of Adults: Aged 15+ data was reported at 20.300 % in 2016. This records a decrease from the previous number of 20.500 % for 2015. ZA: Smoking Prevalence: Total: % of Adults: Aged 15+ data is updated yearly, averaging 20.800 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 22.700 % in 2000 and a record low of 20.300 % in 2016. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 20.30 2016 | yearly | 2000 - 2016 |
View South Africa's South Africa ZA: Smoking Prevalence: Total: % of Adults: Aged 15+ from 2000 to 2016 in the chart:
South Africa ZA: Specialist Surgical Workforce: per 100,000 population
ZA: Specialist Surgical Workforce: per 100,000 population data was reported at 11.530 Number in 2014. ZA: Specialist Surgical Workforce: per 100,000 population data is updated yearly, averaging 11.530 Number from Dec 2014 (Median) to 2014, with 1 observations. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 11.53 2014 | yearly | 2014 - 2014 |
View South Africa's South Africa ZA: Specialist Surgical Workforce: per 100,000 population from 2014 to 2014 in the chart:
South Africa ZA: Suicide Mortality Rate: Female
ZA: Suicide Mortality Rate: Female data was reported at 4.700 NA in 2016. This records a decrease from the previous number of 4.800 NA for 2015. ZA: Suicide Mortality Rate: Female data is updated yearly, averaging 5.400 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 5.700 NA in 2000 and a record low of 4.700 NA in 2016. ZA: Suicide Mortality Rate: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.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 |
|---|---|---|
| 4.700 2016 | yearly | 2000 - 2016 |
View South Africa's South Africa ZA: Suicide Mortality Rate: Female from 2000 to 2016 in the chart:
South Africa ZA: Suicide Mortality Rate: Male
ZA: Suicide Mortality Rate: Male data was reported at 18.700 NA in 2016. This records a decrease from the previous number of 19.000 NA for 2015. ZA: Suicide Mortality Rate: Male data is updated yearly, averaging 18.700 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 19.200 NA in 2010 and a record low of 17.700 NA in 2000. ZA: Suicide Mortality Rate: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.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 |
|---|---|---|
| 18.700 2016 | yearly | 2000 - 2016 |
View South Africa's South Africa ZA: Suicide Mortality Rate: Male from 2000 to 2016 in the chart:
South Africa ZA: Suicide Mortality Rate: per 100,000 Population
ZA: Suicide Mortality Rate: per 100,000 Population data was reported at 11.600 Number in 2016. This records a decrease from the previous number of 11.800 Number for 2015. ZA: Suicide Mortality Rate: per 100,000 Population data is updated yearly, averaging 11.800 Number from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 12.200 Number in 2010 and a record low of 11.600 Number in 2016. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 11.60 2016 | yearly | 2000 - 2016 |
View South Africa's South Africa ZA: Suicide Mortality Rate: per 100,000 Population from 2000 to 2016 in the chart:
South Africa ZA: Survival To Age 65: Female: % of Cohort
ZA: Survival To Age 65: Female: % of Cohort data was reported at 63.429 % in 2016. This records an increase from the previous number of 61.858 % for 2015. ZA: Survival To Age 65: Female: % of Cohort data is updated yearly, averaging 56.159 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 65.275 % in 1992 and a record low of 43.496 % in 2007. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 63.43 2016 | yearly | 1960 - 2016 |
View South Africa's South Africa ZA: Survival To Age 65: Female: % of Cohort from 1960 to 2016 in the chart:
South Africa ZA: Survival To Age 65: Male: % of Cohort
ZA: Survival To Age 65: Male: % of Cohort data was reported at 47.350 % in 2016. This records an increase from the previous number of 45.721 % for 2015. ZA: Survival To Age 65: Male: % of Cohort data is updated yearly, averaging 42.397 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 48.679 % in 1992 and a record low of 30.857 % in 2007. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 47.35 2016 | yearly | 1960 - 2016 |
View South Africa's South Africa ZA: Survival To Age 65: Male: % of Cohort from 1960 to 2016 in the chart:
South Africa ZA: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+
ZA: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+ data was reported at 9.300 Number in 2016. ZA: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+ data is updated yearly, averaging 9.300 Number from Dec 2016 (Median) to 2016, with 1 observations. ZA: 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 South Africa – Table ZA.World Bank: 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 |
|---|---|---|
| 9.30 2016 | yearly | 2016 - 2016 |
View South Africa's South Africa ZA: Total Alcohol Consumption per Capita: Liters of Pure Alcohol: Projected Estimates: Aged 15+ from 2016 to 2016 in the chart:
South Africa ZA: Tuberculosis Case Detection Rate: All Forms
ZA: Tuberculosis Case Detection Rate: All Forms data was reported at 54.000 % in 2016. This records a decrease from the previous number of 64.000 % for 2015. ZA: Tuberculosis Case Detection Rate: All Forms data is updated yearly, averaging 64.000 % from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 75.000 % in 2011 and a record low of 48.000 % in 2001. ZA: 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 South Africa – Table ZA.World Bank.WDI: 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 |
|---|---|---|
| 54.00 2016 | yearly | 2000 - 2016 |
View South Africa's South Africa ZA: Tuberculosis Case Detection Rate: All Forms from 2000 to 2016 in the chart:
South Africa ZA: Tuberculosis Treatment Success Rate: % of New Cases
ZA: Tuberculosis Treatment Success Rate: % of New Cases data was reported at 81.000 % in 2015. This records an increase from the previous number of 78.000 % for 2014. ZA: Tuberculosis Treatment Success Rate: % of New Cases data is updated yearly, averaging 69.500 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 81.000 % in 2015 and a record low of 53.000 % in 2010. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 81.00 2015 | yearly | 2000 - 2015 |
View South Africa's South Africa ZA: Tuberculosis Treatment Success Rate: % of New Cases from 2000 to 2015 in the chart:
South Africa ZA: UHC Service Coverage Index
ZA: UHC Service Coverage Index data was reported at 67.000 % in 2015. ZA: UHC Service Coverage Index data is updated yearly, averaging 67.000 % from Dec 2015 (Median) to 2015, with 1 observations. ZA: UHC Service Coverage Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: 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 |
|---|---|---|
| 67.00 2015 | yearly | 2015 - 2015 |
View South Africa's South Africa ZA: UHC Service Coverage Index from 2015 to 2015 in the chart:
South Africa ZA: Unmet Need for Contraception: % of Married Women Aged 15-49
ZA: Unmet Need for Contraception: % of Married Women Aged 15-49 data was reported at 14.700 % in 2016. This records an increase from the previous number of 13.800 % for 2004. ZA: Unmet Need for Contraception: % of Married Women Aged 15-49 data is updated yearly, averaging 14.700 % from Dec 1998 (Median) to 2016, with 3 observations. The data reached an all-time high of 16.500 % in 1998 and a record low of 13.800 % in 2004. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 14.70 2016 | yearly | 1998 - 2016 |
View South Africa's South Africa ZA: Unmet Need for Contraception: % of Married Women Aged 15-49 from 1998 to 2016 in the chart:
South Africa ZA: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months
ZA: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months data was reported at 42.000 % in 2013. This records a decrease from the previous number of 44.000 % for 2011. ZA: Vitamin A Supplementation Coverage Rate: % of Children Aged 6-59 Months data is updated yearly, averaging 34.000 % from Dec 2004 (Median) to 2013, with 6 observations. The data reached an all-time high of 44.000 % in 2011 and a record low of 0.000 % in 2004. ZA: 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 South Africa – Table ZA.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 |
|---|---|---|
| 42.00 2013 | yearly | 2004 - 2013 |