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Zambia ZM: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data was reported at 32.300 % in 2024. This records an increase from the previous number of 32.000 % for 2023. Zambia ZM: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data is updated yearly, averaging 40.800 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 52.100 % in 2000 and a record low of 31.600 % in 2021. Zambia ZM: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zambia – Table ZM.World Bank.WDI: Social: 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 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).;Weighted average;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). 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. Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.
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This scatter chart displays health expenditure per capita (current US$) against date (year) in Zambia. The data is filtered where the date is 2021. The data is about countries per year.
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Zambia ZM: Newly Infected with HIV: Adults: Aged 15-24 data was reported at 15,000.000 Number in 2021. This records a decrease from the previous number of 17,000.000 Number for 2020. Zambia ZM: Newly Infected with HIV: Adults: Aged 15-24 data is updated yearly, averaging 27,500.000 Number from Dec 1990 to 2021, with 32 observations. The data reached an all-time high of 35,000.000 Number in 1993 and a record low of 15,000.000 Number in 2021. Zambia ZM: Newly Infected with HIV: Adults: Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zambia – Table ZM.World Bank.WDI: Health Statistics. Number of young people (ages 15-24) newly infected with HIV.; ; UNAIDS estimates.; ; This indicator is related to Sustainable Development Goal 3.3.1 [https://unstats.un.org/sdgs/metadata/].
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Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.
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This scatter chart displays male population (people) against health expenditure (% of GDP) in Zambia. The data is filtered where the date is 2021. The data is about countries per year.
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Zambia Exports of medical, surgical, dental or veterinary furniture to Ghana was US$431 during 2021, according to the United Nations COMTRADE database on international trade. Zambia Exports of medical, surgical, dental or veterinary furniture to Ghana - data, historical chart and statistics - was last updated on December of 2025.
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This bar chart displays health expenditure per capita (current US$) by region using the aggregation average, weighted by population in Zambia. The data is filtered where the date is 2021. The data is about countries per year.
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Belarus Exports of optical, photo, technical, medical apparatus to Zambia was US$6.6 Thousand during 2021, according to the United Nations COMTRADE database on international trade. Belarus Exports of optical, photo, technical, medical apparatus to Zambia - data, historical chart and statistics - was last updated on October of 2025.
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Zambia ZM: Prevalence of Severe Food Insecurity in the Population: % of population data was reported at 32.100 % in 2021. This records a decrease from the previous number of 32.600 % for 2020. Zambia ZM: Prevalence of Severe Food Insecurity in the Population: % of population data is updated yearly, averaging 26.200 % from Dec 2015 (Median) to 2021, with 7 observations. The data reached an all-time high of 32.600 % in 2020 and a record low of 22.400 % in 2015. Zambia ZM: Prevalence of Severe Food Insecurity in the Population: % of population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zambia – Table ZM.World Bank.WDI: Social: Health Statistics. The percentage of people in the population who live in households classified as severely food insecure. A household is classified as severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to several of the most severe experiences described in the FIES questions, such as to have been forced to reduce the quantity of the food, to have skipped meals, having gone hungry, or having to go for a whole day without eating because of a lack of money or other resources.;Food and Agriculture Organization of the United Nations (FAO);;
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TwitterThe GYTS is a school-based survey which uses a self-administered questionnaire to monitor tobacco use among youth and to guide the implementation and evaluation of tobacco prevention and control programmes.
National
Individuals
School-going adolescents aged 13-15 years.
Sample survey data [ssd]
GYTS uses a global standardized methodology that includes a two-stage sample design with schools selected with a probability proportional to enrollment size. The classes within selected schools are chosen randomly and all students in selected classes are eligible to participate in the survey.
A total of 6,499 eligible students in grades 7-9 completed the survey, of which 4,028 were aged 13-15 years.
self-administered
All data processing (scanning, cleaning, editing, and weighting) was conducted at the US Centers for Disease Control.
The overall response rate was 75.7%.
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This scatter chart displays life expectancy at birth (year) against health expenditure (% of GDP) in Zambia. The data is filtered where the date is 2021. The data is about countries per year.
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Zambia Exports of optical, photo, technical, medical apparatus to Panama was US$964 during 2021, according to the United Nations COMTRADE database on international trade. Zambia Exports of optical, photo, technical, medical apparatus to Panama - data, historical chart and statistics - was last updated on December of 2025.
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Zambia ZM: Incidence of HIV: per 1,000 Uninfected Population Aged 15-24 data was reported at 3.180 Ratio in 2022. This records a decrease from the previous number of 3.800 Ratio for 2021. Zambia ZM: Incidence of HIV: per 1,000 Uninfected Population Aged 15-24 data is updated yearly, averaging 10.980 Ratio from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 23.030 Ratio in 1991 and a record low of 3.180 Ratio in 2022. Zambia ZM: Incidence of HIV: per 1,000 Uninfected Population Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zambia – Table ZM.World Bank.WDI: Social: Health Statistics. Number of new HIV infections among uninfected populations ages 15-24 expressed per 1,000 uninfected population ages 15-24 in the year before the period.;UNAIDS estimates.;Weighted average;This is an age-disaggregated indicator for Sustainable Development Goal 3.3.1 [https://unstats.un.org/sdgs/metadata/].
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Zambia Percentage of Population Exposure to Icing Days data was reported at 0.000 % in 2021. This stayed constant from the previous number of 0.000 % for 2020. Zambia Percentage of Population Exposure to Icing Days data is updated yearly, averaging 0.000 % from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 0.000 % in 2021 and a record low of 0.000 % in 2021. Zambia Percentage of Population Exposure to Icing Days data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Zambia – Table ZM.OECD.GGI: Social: Air Quality and Health: Non OECD Member: Annual.
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Zambia Percentage of Population Exposure to Hot Days data was reported at 65.000 % in 2021. This records an increase from the previous number of 61.200 % for 2020. Zambia Percentage of Population Exposure to Hot Days data is updated yearly, averaging 58.250 % from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 78.000 % in 1999 and a record low of 28.100 % in 1991. Zambia Percentage of Population Exposure to Hot Days data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Zambia – Table ZM.OECD.GGI: Social: Air Quality and Health: Non OECD Member: Annual.
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This scatter chart displays individuals using the Internet (% of population) against health expenditure (% of GDP) in Zambia. The data is filtered where the date is 2021. The data is about countries per year.
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Zambia Imports from Estonia of Optical, photo, technical, medical apparatus was US$1.95 Thousand during 2021, according to the United Nations COMTRADE database on international trade. Zambia Imports from Estonia of Optical, photo, technical, medical apparatus - data, historical chart and statistics - was last updated on December of 2025.
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Zambia Imports of optical, photo, technical, medical apparatus from Albania was US$125 during 2021, according to the United Nations COMTRADE database on international trade. Zambia Imports of optical, photo, technical, medical apparatus from Albania - data, historical chart and statistics - was last updated on November of 2025.
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Zambia ZM: Prevalence of Current Tobacco Use: Males: % of Male Adults data was reported at 25.600 % in 2022. This records a decrease from the previous number of 25.900 % for 2021. Zambia ZM: Prevalence of Current Tobacco Use: Males: % of Male Adults data is updated yearly, averaging 27.500 % from Dec 2000 (Median) to 2022, with 8 observations. The data reached an all-time high of 30.300 % in 2000 and a record low of 25.600 % in 2022. Zambia ZM: Prevalence of Current Tobacco Use: Males: % of Male Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zambia – Table ZM.World Bank.WDI: Social: Health Statistics. The percentage of the male population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), “e-cigars”, “e-hookahs”, JUUL and “e-pipes”. The rates are age-standardized to the WHO Standard Population.;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.a.1 [https://unstats.un.org/sdgs/metadata/]. Previous indicator name: Smoking prevalence, males (% of adults) The previous indicator excluded smokeless tobacco use, while the current indicator includes it. The indicator name and definition were updated in December, 2020.
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Russia Exports of optical, photo, technical, medical apparatus to Zambia was US$27.6 Thousand during 2021, according to the United Nations COMTRADE database on international trade. Russia Exports of optical, photo, technical, medical apparatus to Zambia - data, historical chart and statistics - was last updated on December of 2025.
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Zambia ZM: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data was reported at 32.300 % in 2024. This records an increase from the previous number of 32.000 % for 2023. Zambia ZM: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data is updated yearly, averaging 40.800 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 52.100 % in 2000 and a record low of 31.600 % in 2021. Zambia ZM: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Zambia – Table ZM.World Bank.WDI: Social: 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 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).;Weighted average;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). 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. Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.