Developmentrelevance:
The rural population is calculated using the urban share reported by the United Nations Population Division. There is no universal standard for distinguishing rural from urban areas, and any urban-rural dichotomy is an oversimplification.

 The two distinct images - isolated farm, thriving metropolis - represent poles on a continuum. Life changes along a variety of dimensions, moving from the most remote forest outpost through fields and pastures, past tiny hamlets, through small towns with weekly farm markets, into intensively cultivated areas near large towns and small cities, eventually reaching the center of a megacity. Along the way access to infrastructure, social services, and nonfarm employment increase, and with them population density and income.

A 2005 World Bank Policy Research Paper proposes an operational definition of rurality based on population density and distance to large cities (Chomitz, Buys, and Thomas 2005). The report argues that these criteria are important gradients along which economic behavior and appropriate development interventions vary substantially. Where population densities are low, markets of all kinds are thin, and the unit cost of delivering most social services and many types of infrastructure is high. Where large urban areas are distant, farm-gate or factory-gate prices of outputs will be low and input prices will be high, and it will be difficult to recruit skilled people to public service or private enterprises. Thus, low population density and remoteness together define a set of rural areas that face special development challenges.

Countries differ in the way they classify population as "urban" or "rural."

Most countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries.

Rural population methodology is defined by various national statistical offices. In the United States, for example, the US Census Bureau's urban-rural classification is fundamentally a delineation of geographical areas, identifying both individual urban areas and the rural areas of the nation. "Rural" encompasses all population, housing, and territory not included within an urban area.

IndicatorName: Rural population (% of total population)

Limitationsandexceptions:
Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.

Estimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.

Because the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.

Longdefinition: Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.

Source: World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.

Statisticalconceptandmethodology:
Rural population is calculated as the difference between the total population and the urban population. Rural population is approximated as the midyear nonurban population. While a practical means of identifying the rural population, it is not a precise measure.

The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data.


IndicatorName: Urban population, female (% of total)

License_Type: CC BY-4.0

Limitationsandexceptions: Because the urban and rural population by sex is based on the 2014 revision of World Urbanization Prospects (WUP) for urban and rural population and the 2012 revision of World Population Prospects (WPP) for total population by age and sex, the data for urban and rural population by sex is not comparable and consistent with the total population data presented in the World Development Indicators database which is based on the 2015 World Population Prospects

Longdefinition: Female urban population is the percentage of females who live in urban areas to total population.

Periodicity: Annual

Source: The United Nations Population Division's World Urbanization Prospects.

Statisticalconceptandmethodology: Estimates of the United Nations urban and rural population by sex is based on the 2014 revision of World Urbanization Prospects (WUP) for urban and rural population and the 2012 revision of World Population Prospects (WPP) for total population by age and sex for all countries or territories in the world.

Topic: Population


Aggregationmethod: Weighted average

Developmentrelevance:
Explosive growth of cities globally signifies the demographic transition from rural to urban, and is associated with shifts from an agriculture-based economy to mass industry, technology, and service.

In principle, cities offer a more favorable setting for the resolution of social and environmental problems than rural areas. Cities generate jobs and income, and deliver education, health care and other services. Cities also present opportunities for social mobilization and women's empowerment.

IndicatorName: Urban population (% of total population)

Limitationsandexceptions:
Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.

Most countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries.

Estimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.

Because the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution.

Longdefinition: Urban population refers to people living in urban areas as defined by national statistical offices. The data are collected and smoothed by United Nations Population Division.

Source: United Nations Population Division. World Urbanization Prospects: 2018 Revision.

Statisticalconceptandmethodology:
Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects.

Percentages urban are the numbers of persons residing in an area defined as ''urban'' per 100 total population. Particular caution should be used in interpreting the figures for percentage urban for different countries.

Countries differ in the way they classify population as "urban" or "rural." The population of a city or metropolitan area depends on the boundaries chosen.


IndicatorName: Urban population, male (% of total)

Longdefinition: Male urban population is the percentage of males who live in urban areas to total population.


Generalcomments: 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.

IndicatorName: Unmet need for contraception (% of married women ages 15-49)

Longdefinition: 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.

Source: Household surveys, including Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Largely compiled by United Nations Population Division.

Statisticalconceptandmethodology:
Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.

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. This indicator excludes women not exposed to the risk of unintended pregnancy because of menopause, infertility, or postpartum anovulation.

Topic: Health


IndicatorName: Percentage of students in lower secondary vocational education who are female (%)

Longdefinition: Number of female vocational education students at the lower secondary level expressed as a percentage of the total number of vocational education students (male and female) at the lower secondary level in a given school year.

Source: UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of March 2020.

Topic: Education


IndicatorName: Percentage of students in upper secondary vocational education who are female (%)

Longdefinition: Number of female vocational education students at the upper secondary level expressed as a percentage of the total number of vocational education students (male and female) at the upper secondary level in a given school year.


IndicatorName: Percentage of students in post-secondary non-tertiary vocational education who are female (%)

Longdefinition: Number of female vocational education students at the post-secondary non-tertiary level expressed as a percentage of the total number of vocational education students (male and female) at the post-secondary non-tertiary level in a given school year.


IndicatorName: Female share of graduates in Business, Administration and Law programmes, tertiary (%)

Longdefinition: Female share of graduates in the given field of education, tertiary is the number of female graduates expressed as a percentage of the total number of graduates in the given field of education from tertiary education.

Statisticalconceptandmethodology:
Percentage of female graduates by field of study in tertiary education is calculated by dividing the number of female graduates in a given field of education from tertiary education by the total number of graduates in the same field, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Female share of graduates in Information and Communication Technologies programmes, tertiary (%)


IndicatorName: Female share of graduates in other fields than Science, Technology, Engineering and Mathematics programmes, tertiary (%)


IndicatorName: Share of all students in lower secondary education enrolled in vocational programmes (%)

Longdefinition: Total number of students enrolled in vocational programmes at the lower secondary education level, expressed as a percentage of the total number of students enrolled in all programmes (vocational and general) at the lower secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.

Source: UNESCO Institute for Statistics


IndicatorName: Percentage of female students in lower secondary education enrolled in vocational programmes, female (%)

Longdefinition: Total number of female students enrolled in vocational programmes at the lower secondary education level, expressed as a percentage of the total number of female students enrolled in all programmes (vocational and general) at the lower secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Percentage of male students in lower secondary education enrolled in vocational programmes, male (%)

Longdefinition: Total number of male students enrolled in vocational programmes at the lower secondary education level, expressed as a percentage of the total number of male students enrolled in all programmes (vocational and general) at the lower secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Share of all students in upper secondary education enrolled in vocational programmes (%)

Longdefinition: Total number of students enrolled in vocational programmes at the upper secondary education level, expressed as a percentage of the total number of students enrolled in all programmes (vocational and general) at the upper secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Percentage of female students in upper secondary education enrolled in vocational programmes, female (%)

Longdefinition: Total number of female students enrolled in vocational programmes at the upper secondary education level, expressed as a percentage of the total number of female students enrolled in all programmes (vocational and general) at the upper secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Percentage of male students in upper secondary education enrolled in vocational programmes, male (%)

Longdefinition: Total number of male students enrolled in vocational programmes at the upper secondary education level, expressed as a percentage of the total number of male students enrolled in all programmes (vocational and general) at the upper secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Share of all students in post-secondary non-tertiary education enrolled in vocational programmes (%)

Longdefinition: Total number of students enrolled in vocational programmes at the post-secondary non-tertiary education level, expressed as a percentage of the total number of students enrolled in all programmes (vocational and general) at the post-secondary non-tertiary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Percentage of female students in post-secondary non-tertiary education enrolled in vocational programmes, female (%)

Longdefinition: Total number of female students enrolled in vocational programmes at the post-secondary non-tertiary education level, expressed as a percentage of the total number of female students enrolled in all programmes (vocational and general) at the post-secondary non-tertiary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Percentage of male students in post-secondary non-tertiary education enrolled in vocational programmes, male (%)

Longdefinition: Total number of male students enrolled in vocational programmes at the post-secondary non-tertiary education level, expressed as a percentage of the total number of male students enrolled in all programmes (vocational and general) at the post-secondary non-tertiary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.


IndicatorName: Youth illiterate population, 15-24 years, both sexes (number)

Longdefinition: Total number of youth between age 15 and age 24 who cannot both read and write with understanding a short simple statement on their everyday life.


IndicatorName: Youth illiterate population, 15-24 years, female (number)

Longdefinition: Total number of females between age 15 and age 24 who cannot both read and write with understanding a short simple statement on their everyday life.

Source: UNESCO Institute for Statistics (http://uis.unesco.org/)


IndicatorName: Youth illiterate population, 15-24 years, male (number)

Longdefinition: Total number of males between age 15 and age 24 who cannot both read and write with understanding a short simple statement on their everyday life.


IndicatorName: Youth illiterate population, 15-24 years, % female

Longdefinition: Share of the youth illiterate population that is female.


IndicatorName: Rate of out-of-school youth of upper secondary school age, female (%)

Longdefinition: Number of females of official upper secondary school age who are not enrolled in upper secondary school expressed as a percentage of the female population of official upper secondary school age.


IndicatorName: Rate of out-of-school youth of upper secondary school age, male (%)

Longdefinition: Number of males of official upper secondary school age who are not enrolled in upper secondary school expressed as a percentage of the male population of official upper secondary school age.


Developmentrelevance:
In some regions, organized crime, drug trafficking and the violent cultures of youth gangs are predominantly responsible for the high levels of homicide. There has been a sharp increase in homicides in some countries, particularly in Central America, are making the activities of organized crime and drug trafficking more visible. Greater use of firearms is often associated with the illicit activities of organized criminal groups, which are often linked to drug trafficking.

Knowledge of the patterns and causes of violent crime are crucial to forming preventive strategies. Young males are the group most affected by violent crime in all regions, particularly in the Americas. Yet women of all ages are the victims of intimate partner and family-related violence in all regions and countries. Indeed, in many of them, it is within the home where a woman is most likely to be killed.

Data on intentional homicides are from the United Nations Office on Drugs and Crime (UNODC), which uses a variety of national and international sources on homicides - primarily criminal justice sources as well as public health data from the World Health Organization (WHO) and the Pan American Health Organization - and the United Nations Survey of Crime Trends and Operations of Criminal Justice Systems to present accurate and comparable statistics. The UNODC defines homicide as "unlawful death purposefully inflicted on a person by another person." This definition excludes deaths arising from armed conflict.

IndicatorName: Intentional homicides, female (per 100,000 female)

Limitationsandexceptions:
Statistics reported to the United Nations in the context of its various surveys on crime levels and criminal justice trends are incidents of victimization that have been reported to the authorities in any given country. That means that this data is subject to the problems of accuracy of all official crime data. The survey results provide an overview of trends and interrelationships between various parts of the criminal justice system to promote informed decision-making in administration, nationally and internationally.

The degree to which different societies apportion the level of culpability to acts resulting in death is also subject to variation. Consequently, the comparison between countries and regions of "intentional homicide", or unlawful death purposefully inflicted on a person by another person, is also a comparison of the extent to which different countries deem that a killing be classified as such, as well as the capacity of their legal systems to record it. Caution should therefore be applied when evaluating and comparing homicide data.

Longdefinition: Intentional homicides, female are estimates of unlawful female homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.

Source: UN Office on Drugs and Crime's International Homicide Statistics database.

Statisticalconceptandmethodology:
The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data are adjusted to conform to the total number of victims of intentional homicide. The adjustment is carried out by applying the sex ratio of reported victims to the total number of victims of intentional homicide.

The intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.

Criminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).

The inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.

As a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.

Topic: Violence


IndicatorName: Intentional homicides, male (per 100,000 male)

Longdefinition: Intentional homicides, male are estimates of unlawful male homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.


IndicatorName: Intentional homicides (per 100,000 people)

Longdefinition: Intentional homicides are estimates of unlawful homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.

Statisticalconceptandmethodology:
The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data included in the dataset correspond to the original value provided by the source of origin, since no statistical procedure or modeling was used to change collected values or to create new or revised figures.

The intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.

Criminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).

The inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.

As a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.


Longdefinition: The consumer price index reflects the change in prices for the average consumer of a constant basket of consumer goods. Data is not seasonally adjusted.

Source: World Bank staff calculations based on Datastream data.


Longdefinition: Median inflation rate calculated for geographical aggregates (regions, world, etc) of the annual percent change of the CPI. Data is seasonally adjusted.


Longdefinition: The consumer price index reflects the change in prices for the average consumer of a constant basket of consumer goods. Data is in nominal terms and seasonally adjusted.


Longdefinition: The consumer price index reflects the change in prices for the average consumer of a constant basket of consumer goods. Data is in nominal percentage terms, measured on a year-on-year basis, and seasonally adjusted.


Longdefinition: Merchandise (goods) imports, cost, insurance and freight basis (c.i.f.), in current US$ millions, not seasonally adjusted.

Source: World Bank staff calculations based on Datastream and IMF International Finance Statistics data.


Longdefinition: Merchandise (goods) imports, cost, insurance and freight basis (c.i.f.), in constant US$ millions, not seasonally adjusted. The base year is 2005.


Longdefinition: The price index of Merchandise (goods) imports, cost, insurance and freight basis (c.i.f.), in constant US$ millions, not seasonally adjusted. The base year is 2005.


Longdefinition: Merchandise (goods) imports, cost, insurance and freight basis (c.i.f.), in current US$ millions, seasonally adjusted.


Longdefinition: Merchandise (goods) exports, cost, insurance and freight basis (c.i.f.), in constant US$ millions, seasonally adjusted. The base year is 2005.


Longdefinition: The price index of Merchandise (goods) imports, cost, insurance and freight basis (c.i.f.), in constant US$ millions, seasonally adjusted. The base year is 2005.


Longdefinition: Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).


Longdefinition: Local currency units (LCU) per U.S. dollar, with values prior to the currency's introduction presented in the new currency's terms


Longdefinition: Local currency units (LCU) per U.S. dollar, with values after a new currency's introduction presented in the old currency's terms


Longdefinition: Local equity market index valued in US$ terms


Longdefinition: Local equity market index valued in local currency unit (LCU) terms


Longdefinition: Merchandise (goods) exports,  free on board (f.o.b.), in current US$ millions, not seasonally adjusted.


Longdefinition: Merchandise (goods) exports,  free on board (f.o.b.), in constant US$ millions not seasonally adjusted. The base year is 2005.


Longdefinition: The price index of Merchandise (goods) exports,  free on board (f.o.b.), in currrent US$ millions. Not seasonally adjusted.


Longdefinition: Merchandise (goods) exports,  free on board (f.o.b.), in current US$ millions, seasonally adjusted.


Longdefinition: Merchandise (goods) exports,  free on board (f.o.b.), in constant US$ millions, seasonally adjusted. The base year is 2005.


Longdefinition: The price index of Merchandise (goods) exports,  free on board (f.o.b.), in US$ seasonally adjusted.


Longdefinition: The stock of international reserves is expressed as the number of months of financing-coverage it represents for the given country's imports of merchandise goods.


Longdefinition: An economic indicator that measures changes in output for the industrial sector of the economy. The industrial sector includes manufacturing, mining, and utilities. Data is in constant US$, and not seasonally adjusted. The base year is 2005.


Longdefinition: An economic indicator that measures changes in output for the industrial sector of the economy. The industrial sector includes manufacturing, mining, and utilities. Data is in constant US$, seasonally adjusted. The base year is 2005.


Longdefinition: A measure of the value of a currency against a weighted average of several foreign currencies


Longdefinition: Real effective exchange rate is the nominal effective exchange rate (a measure of the value of a currency against a weighted average of several foreign currencies) divided by a price deflator or index of costs.


Longdefinition: The terms of trade effect equals capacity to import less exports of goods and services.


Longdefinition: Total reserves comprise holdings of monetary gold, special drawing rights, reserves of IMF members held by the IMF, and holdings of foreign exchange under the control of monetary authorities.


IndicatorName: Human capital index (HCI) (scale 0-1)

Longdefinition: The HCI calculates the contributions of health and education to worker productivity. The final index score ranges from zero to one and measures the productivity as a future worker of child born today relative to the benchmark of full health and complete education.

Relatedindicators: Please visit the Human Capital Index (HCI) database (http://databank.worldbank.org/data/source/human-capital-index) for each of the components of the Human Capital Index as well as for the overall index, disaggregated by gender.

Source: World Bank staff calculations based on the methodology described in World Bank (2018). https://openknowledge.worldbank.org/handle/10986/30498

Topic: Public Sector: Policy & institutions


IndicatorName: Human capital index (HCI), female (scale 0-1)


IndicatorName: Human capital index (HCI), lower bound (scale 0-1)

Longdefinition: The HCI lower bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.


IndicatorName: Human capital index (HCI), female, lower bound (scale 0-1)


IndicatorName: Human capital index (HCI), male, lower bound (scale 0-1)


IndicatorName: Human capital index (HCI), male (scale 0-1)


IndicatorName: Human capital index (HCI), upper bound (scale 0-1)

Longdefinition: The HCI upper bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.


IndicatorName: Human capital index (HCI), female, upper bound (scale 0-1)


IndicatorName: Human capital index (HCI), male, upper bound (scale 0-1)


IndicatorName: GNI per capita, Atlas method (current US$)

Longdefinition: GNI per capita (formerly GNP per capita) is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the midyear population. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.

Source: World Bank national accounts data, and OECD National Accounts data files.

Statisticalconceptandmethodology: The World Bank uses Atlas method GNI per capita in U.S. dollars to classify countries for analytical purposes and to determine borrowing eligibility. For more information, see the metadata for Atlas method GNI in current U.S. dollars (NY.GNP.ATLS.CD) and total population (SP.POP.TOTL).

Topic: Economic Policy & Debt: National accounts: Atlas GNI & GNI per capita


Developmentrelevance:
Literacy rate is an outcome indicator to evaluate educational attainment. This data can predict the quality of future labor force and can be used in ensuring policies for life skills for men and women.

It can be also used as a proxy instrument to see the effectiveness of education system; a high literacy rate suggests the capacity of an education system to provide a large population with opportunities to acquire literacy skills. The accumulated achievement of education is fundamental for further intellectual growth and social and economic development, although it doesn't necessarily ensure the quality of education.

The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around. Eliminating gender disparities in education would help increase the status and capabilities of women. Literate women implies that they can seek and use information for the betterment of the health, nutrition and education of their household members. Literate women are also empowered to play a meaningful role.

IndicatorName: Literacy rate, youth (ages 15-24), gender parity index (GPI)

Limitationsandexceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.

Longdefinition: Gender parity index for youth literacy rate is the ratio of females to males ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.

Source: UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed September 30, 2024. https://apiportal.uis.unesco.org/bdds.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female youth literacy rate by male youth literacy rate.

Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.

Data on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.

Topic: Education: Outcomes


Developmentrelevance:
Literacy rate is an outcome indicator to evaluate educational attainment. This data can predict the quality of future labor force and can be used in ensuring policies for life skills for men and women.

It can be also used as a proxy instrument to see the effectiveness of education system; a high literacy rate suggests the capacity of an education system to provide a large population with opportunities to acquire literacy skills. The accumulated achievement of education is fundamental for further intellectual growth and social and economic development, although it doesn't necessarily ensure the quality of education.

Literate women implies that they can seek and use information for the betterment of the health, nutrition and education of their household members. Literate women are also empowered to play a meaningful role.

IndicatorName: Literacy rate, youth male (% of males ages 15-24)

Longdefinition: Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.

Statisticalconceptandmethodology:
Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.

Data on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.


IndicatorName: Literacy rate, youth total (% of people ages 15-24)


IndicatorName: Literacy rate, adult female (% of females ages 15 and above)

Longdefinition: Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.


IndicatorName: Literacy rate, adult male (% of males ages 15 and above)


IndicatorName: Literacy rate, adult total (% of people ages 15 and above)


IndicatorName: Ratio of school attendance of orphans to school attendance of non-orphans ages 10-14

Longdefinition: Ratio of school attendance of orphans to school attendance of non orphans is the ratio of school attendance of orphans to school attendance of non orphans ages 10-14.

Source: Household surveys such as Demographic and Health Surveys (DHS) , Multiple Indicator Cluster Surveys (MICS), Reproductive Health Surveys (RHS) and AIDS Indicator Surveys (AIS), maintained in UNICEF Global Databases.

Topic: Education: Participation


Developmentrelevance: The World Bank and the UNESCO Institute for Statistics jointly developed the primary completion rate indicator. Increasingly used as a core indicator of an education system's performance, it reflects an education system's coverage and the educational attainment of students.

IndicatorName: Primary completion rate, female (% of relevant age group)

Limitationsandexceptions:
Data limitations preclude adjusting for students who drop out during the final year of primary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual primary completion rate.

There are many reasons why the primary completion rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of primary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of primary education.

Longdefinition: Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.

Statisticalconceptandmethodology:
Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Primary completion rate, male (% of relevant age group)


IndicatorName: Primary completion rate, total (% of relevant age group)


Developmentrelevance: Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system. The net enrollment rate excludes overage and underage students and more accurately captures the system's coverage and internal efficiency. Differences between the gross enrollment ratio and the net enrollment rate show the incidence of overage and underage enrollments.

IndicatorName: School enrollment, primary (% gross)

Limitationsandexceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.

Longdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.

Statisticalconceptandmethodology:
Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, primary, female (% gross)


IndicatorName: School enrollment, primary, male (% gross)


IndicatorName: School enrollment, primary (% net)

Longdefinition: Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.

Source: UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of February 2020.

Statisticalconceptandmethodology:
Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, primary, female (% net)


IndicatorName: School enrollment, primary, male (% net)


IndicatorName: School enrollment, secondary (% gross)

Longdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.

Statisticalconceptandmethodology:
Gross enrollment ratio for secondary school is calculated by dividing the number of students enrolled in secondary education regardless of age by the population of the age group which officially corresponds to secondary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, secondary, female (% gross)


IndicatorName: School enrollment, secondary, male (% gross)


IndicatorName: School enrollment, secondary (% net)

Longdefinition: Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.

Statisticalconceptandmethodology:
Net enrollment rate for secondary school is calculated by dividing the number of students of official school age enrolled in secondary education by the population of the age group which officially corresponds to secondary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, secondary, female (% net)


IndicatorName: School enrollment, secondary, male (% net)


IndicatorName: School enrollment, tertiary (% gross)

Longdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Tertiary education, whether or not to an advanced research qualification, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level.

Statisticalconceptandmethodology:
Gross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, tertiary, female (% gross)


Aggregationmethod: Median

Developmentrelevance: The percentage of government expenditure on education to GDP is useful to compare education expenditure between countries and/or over time in relation to the size of their economy; A high percentage to GDP suggests a high priority for education and a capacity of raising revenues for public spending. Note that government expenditure appears lower in some countries where the private sector and/or households have a large share in total funding for education.

Limitationsandexceptions: Data may refer to spending by the ministry of education only (excluding spending on educational activities by other ministries).

Longdefinition: General government expenditure on education (current, capital, and transfers) is expressed as a percentage of GDP. It includes expenditure funded by transfers from international sources to government. General government usually refers to local, regional and central governments.

Statisticalconceptandmethodology:
Government expenditure on education, total (% of GDP) is calculated by dividing total government expenditure for all levels of education by the GDP, and multiplying by 100. Aggregate data are based on World Bank estimates.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. GDP data come from the World Bank.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).

Topic: Education: Inputs


Developmentrelevance: Acoording to the World Health Organization, alcohol consumption is a causal factor in more than 200 disease and injury conditions. In the world, an estimated 3 million deaths are from harmful use of alcohols every year.   Drinking alcohol is associated with a risk of developing health problems such as mental and behavioural disorders, including alcohol dependence, major noncommunicable diseases such as liver cirrhosis, some cancers and cardiovascular diseases, as well as injuries resulting from violence and road clashes and collisions.

Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 3.5.2 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Total alcohol consumption per capita, female (liters of pure alcohol, projected estimates, female 15+ years of age)

Longdefinition: 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.

Source: World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).

Statisticalconceptandmethodology: The estimates for the total alcohol consumption are produced by summing up the 3-year average per capita (15+) recorded alcohol consumption and an estimate of per capita (15+) unrecorded alcohol consumption for a calendar year. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries.

Topic: Health: Risk factors


Generalcomments: This is the Sustainable Development Goal indicator 3.5.2[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Total alcohol consumption per capita (liters of pure alcohol, projected estimates, 15+ years of age)


IndicatorName: Total alcohol consumption per capita, male (liters of pure alcohol, projected estimates, male 15+ years of age)


IndicatorName: Prevalence of anemia among women of reproductive age (% of women ages 15-49)

Longdefinition: 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.

Source: World Health Organization, Global Health Observatory Data Repository/World Health Statistics.

Topic: Health: Nutrition


Generalcomments: 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.

IndicatorName: Prevalence of anemia among children (% of children ages 6-59 months)

Limitationsandexceptions: Data for blood haemoglobin concentrations are still limited, compared to other nutritional indicators such as hild anthropometry. As a result, the estimates may not capture the full variation across countries and regions.

Longdefinition: Prevalence of anemia, children ages 6-59 months, is the percentage of children ages 6-59 months whose hemoglobin level is less than 110 grams per liter, adjusted for altitude.

Statisticalconceptandmethodology: Data on anemia are compiled by the WHO, and a statistical model was used to estimate trends. WHO’s hemoglobin threshold concentration in blood was used.


IndicatorName: Prevalence of anemia among non-pregnant women (% of women ages 15-49)

Longdefinition: 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.


IndicatorName: Condom use, population ages 15-24, female (% of females ages 15-24)

Longdefinition: Condom use, female is the percentage of the female population ages 15-24 who used a condom at last intercourse in the last 12 months.

Source: Demographic and Health Surveys, and UNAIDS.

Topic: Health: Disease prevention


IndicatorName: Condom use, population ages 15-24, male (% of males ages 15-24)

Longdefinition: Condom use, male is the percentage of the male population ages 15-24 who used a condom at last intercourse in the last 12 months.


IndicatorName: Condom use at last high-risk sex, adult female (% ages 15-49)

Longdefinition: Condom use at last high-risk sex, female is the percentage of the female population ages 15-49 who used a condom at last intercourse with a non-marital and non-cohabiting sexual partner in the last 12 months.


IndicatorName: Condom use at last high-risk sex, adult male (% ages 15-49)

Longdefinition: Condom use at last high-risk sex, male is the percentage of the male population ages 15-49 who used a condom at last intercourse with a non-marital and non-cohabiting sexual partner in the last 12 months.


Aggregationmethod: Sum

Generalcomments: 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.

IndicatorName: Number of deaths ages 5-9 years

Limitationsandexceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.

Longdefinition: Number of deaths of children ages 5-9 years

Source: Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.

Topic: Health: Mortality


IndicatorName: Number of deaths ages 5-9 years, female

Longdefinition: Number of deaths of female children ages 5-9 years


IndicatorName: Number of deaths ages 5-9 years, male

Longdefinition: Number of deaths of male children ages 5-9 years


IndicatorName: Number of deaths ages 10-14 years

Longdefinition: Number of deaths of adolescents ages 10-14 years


IndicatorName: Number of deaths ages 10-14 years, female

Longdefinition: Number of deaths of female adolescents ages 10-14 years


IndicatorName: Number of deaths ages 10-14 years, male

Longdefinition: Number of deaths of male adolescents ages 10-14 years


IndicatorName: Number of deaths ages 10-19 years

Longdefinition: Number of deaths of adolescents ages 10-19 years


IndicatorName: Number of deaths ages 10-19 years, female

Longdefinition: Number of deaths of female adolescents ages 10-19 years


IndicatorName: Number of deaths ages 10-19  years, male

Longdefinition: Number of deaths of male adolescents ages 10-19 years


IndicatorName: Number of deaths ages 15-19 years

Longdefinition: Number of deaths of adolescents ages 15-19 years


IndicatorName: Number of deaths ages 15-19 years, female

Longdefinition: Number of deaths of female adolescents ages 15-19 years


IndicatorName: Number of deaths ages 15-19 years, male

Longdefinition: Number of deaths of male adolescents ages 15-19 years


IndicatorName: Number of deaths ages 20-24 years

Longdefinition: Number of deaths of youths ages 20-24 years


IndicatorName: Number of deaths ages 20-24 years, female

Longdefinition: Number of deaths of female youths ages 20-24 years


IndicatorName: Number of deaths ages 20-24 years, male

Longdefinition: Number of deaths of male youths ages 20-24 years


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total)

Limitationsandexceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.

Longdefinition: Cause of death refers to the share of all deaths for all ages by underlying causes. Communicable diseases and maternal, prenatal and nutrition conditions include infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.

Source: Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death

Statisticalconceptandmethodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in undercovered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.


IndicatorName: Number of infant deaths

Longdefinition: Number of infants dying before reaching one year of age.


IndicatorName: Number of infant deaths, female

Longdefinition: Number of female infants dying before reaching one year of age.


IndicatorName: Number of infant deaths, male

Longdefinition: Number of male infants dying before reaching one year of age.


IndicatorName: Cause of death, by injury (% of total)

Longdefinition: Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.

Statisticalconceptandmethodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in under-covered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.


IndicatorName: Number of under-five deaths

Longdefinition: Number of children dying before reaching age five.


IndicatorName: Number of under-five deaths, female

Longdefinition: Number of female children dying before reaching age five.


IndicatorName: Number of under-five deaths, male

Longdefinition: Number of male children dying before reaching age five.


IndicatorName: Cause of death, by non-communicable diseases (% of total)

Longdefinition: Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


Generalcomments:
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.

This indicator is related to Sustainable Development Goal 3.2.2 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Number of neonatal deaths

Longdefinition: Number of neonates dying before reaching 28 days of age.


Developmentrelevance:
Stillbirths are an important but often neglected global health problem. Sub-Saharan Africa and South Asia bear the greatest burden of these deaths.

The costs of stillbirths go beyond the loss of life and include psychological cost such as maternal depression, financial costs to parents as well as long-term economic costs to society. The burden on families, especially women, is severe and long lasting, yet stigma and taboo hide this burden even in high-income countries. The progress in lowering the stillbirth rate in the past two decades is much slower than the reduction in mortality of children aged under 5 years old. This could be due to a variety of reasons including absence or poor quality of care during pregnancy and birth, lack of investment in preventative interventions and the health workforce, lack of social recognition of stillbirths as a burden on families, challenges with measurements and major data gaps, absence of global and national leadership, and no established global targets.

IndicatorName: Number of stillbirths

Limitationsandexceptions: Data availability and data quality is uneven among countries.  Adequate stillbirth data are lacking in many low and middle-income countries.  These countries do not have a functioning health information system or civil registration vital statistics (CRVS) system to count or capture stillbirths, and in others stillbirths are excluded from routine registration despite the existence of functioning systems. In such settings, household surveys provide important information on child mortality, but most surveys have substantial data quality issues for stillbirth.

Longdefinition: Number of fetal deaths at 28 weeks or more of gestation

Statisticalconceptandmethodology:
The UN IGME’s approach to estimate stillbirth rates (SBR) includes the following steps:
1.	Compile all available stillbirth data at a country level, derived from administrative sources, household surveys or population-based studies.
2.	Evaluate data in accordance with the data quality criteria and produce adjustment or recalculation by applying standardized definitions.
3.	Estimate global and country-specific trends of stillbirth rates using a smoothing time series model, supplemented with covariates associated with stillbirth rates. This process averages empirical data on stillbirths derived from the different sources for a given country. In the case of countries with sparse or no data, the identified covariates associated with stillbirth will inform the trend in stillbirth rate.


Developmentrelevance: Mortality rates for different age groups (infants, children, adolescents, youth and adults) and overall mortality indicators (life expectancy at birth or survival to a given age) are important indicators of health status in a country. Because data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across countries.

IndicatorName: Probability of dying among children ages 5-9 years (per 1,000)

Longdefinition: 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.

Statisticalconceptandmethodology:
The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A "complete" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.

Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.


IndicatorName: Probability of dying among children ages 5-9 years, female (per 1,000)

Longdefinition: Probability of dying among female children between age 5-9 years of age expressed per 1,000 female children aged 5, if subject to female age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among children ages 5-9 years, male (per 1,000)

Longdefinition: Probability of dying among male children between age 5-9 years of age expressed per 1,000 male children aged 5, if subject to male age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among adolescents ages 10-14 years (per 1,000)

Longdefinition: 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.


IndicatorName: Probability of dying among adolescents ages 10-14 years, female (per 1,000)

Longdefinition: Probability of dying among female adolescents between age 10-14 years of age expressed per 1,000 female adolescents age 10, if subject to female age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among adolescents ages 10-14 years, male (per 1,000)

Longdefinition: Probability of dying among male adolescents between age 10-14 years of age expressed per 1,000 male adolescents age 10, if subject to male age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among adolescents ages 10-19 years (per 1,000)

Longdefinition: Probability of dying between age 10-19 years of age expressed per 1,000 adolescents age 10, if subject to age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among adolescents ages 10-19 years, female (per 1,000)

Longdefinition: Probability of dying among female adolescents between age 10-19 years of age expressed per 1,000 female adolescents age 10, if subject to female age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among adolescents ages 10-19 years, male (per 1,000)

Longdefinition: Probability of dying among male adolescents between age 10-19 years of age expressed per 1,000 male adolescents age 10, if subject to male age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among adolescents ages 15-19 years (per 1,000)

Longdefinition: 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.


IndicatorName: Probability of dying among adolescents ages 15-19 years, female (per 1,000)

Longdefinition: Probability of dying female adolescents between age 15-19 years of age expressed per 1,000 female adolescents age 15, if subject to female age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among adolescents ages 15-19 years, male (per 1,000)

Longdefinition: Probability of dying male adolescents between age 15-19 years of age expressed per 1,000 male adolescents age 15, if subject to male age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among youth ages 20-24 years (per 1,000)

Longdefinition: 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.


IndicatorName: Probability of dying among youth ages 20-24 years, female (per 1,000)

Longdefinition: Probability of dying among female youths between age 20-24 years of age expressed per 1,000 female youths age 20, if subject to female age-specific mortality rates of the specified year.


IndicatorName: Probability of dying among youth ages 20-24 years, male (per 1,000)

Longdefinition: Probability of dying among male youths between age 20-24 years of age expressed per 1,000 male youths age 20, if subject to male age-specific mortality rates of the specified year.


IndicatorName: Adults (ages 15+) living with HIV

Longdefinition: Adults living with HIV refers to the number of people ages 15-49 who are infected with HIV.

Source: UNAIDS estimates.


IndicatorName: AIDS estimated deaths (UNAIDS estimates)

Longdefinition: AIDS deaths are the estimated number of adults and children who died due to AIDS-related causes.


IndicatorName: Women's share of population ages 15+ living with HIV (%)

Limitationsandexceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.

Longdefinition: Prevalence of HIV is the percentage of people who are infected with HIV. Female rate is as a percentage of the total population ages 15+ who are living with HIV.

Statisticalconceptandmethodology:
HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.

Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.


IndicatorName: Prevalence of HIV, total (% of population ages 15-49)

Longdefinition: Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.


Developmentrelevance: Mortality rates for different age groups (infants, children, and adults) and overall mortality indicators (life expectancy at birth or survival to a given age) are important indicators of health status in a country. Because data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across countries.

Generalcomments:
Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

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.

This is the Sustainable Development Goal indicator 3.2.1[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate, under-5 (per 1,000 live births)

Longdefinition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.


Generalcomments:
Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

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.

This is a sex-disaggregated indicator for Sustainable Development Goal 3.2.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate, under-5, female (per 1,000 live births)

Longdefinition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female age-specific mortality rates of the specified year.


IndicatorName: Mortality rate, under-5, male (per 1,000 live births)

Longdefinition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male age-specific mortality rates of the specified year.


Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 3.4.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70, female (%)

Longdefinition: Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes,  or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).


IndicatorName: Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70, male (%)


Generalcomments: This is the Sustainable Development Goal indicator 3.4.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70 (%)


Generalcomments:
Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries.

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.

This is the Sustainable Development Goal indicator 3.2.2 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate, neonatal (per 1,000 live births)

Longdefinition: Neonatal mortality rate is the number of neonates dying before reaching 28 days of age, per 1,000 live births in a given year.


IndicatorName: Stillbirth rate (per 1,000 total births)

Longdefinition: Stillbirth rate is the number of fetal deaths at 28 weeks or more of gestation per 1,000 total births. Total birth is the sum of stillbirths (as just defined) and live births.


IndicatorName: Demand for family planning satisfied by any methods (% of married women with demand for family planning)

Longdefinition: Demand for family planning satisfied by any methods refers to the percentage of married women ages 15-49 whose need for family planning is satisfied.

Source: Demographic and Health Surveys.

Topic: Health: Reproductive health


Generalcomments: This is the Sustainable Development Goal indicator 3.7.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Demand for family planning satisfied by modern methods (% of married women with demand for family planning)

Longdefinition: Demand for family planning satisfied by modern methods refers to the percentage of married women ages 15-49 years whose need for family planning is satisfied with modern methods.

Source: Demographic and Health Surveys (DHS).


Developmentrelevance:
Water is considered to be the most important resource for sustaining ecosystems, which provide life-supporting services for people, animals, and plants. Global access to safe water and proper hygiene education can reduce illness and death from disease, leading to improved health, poverty reduction, and socio-economic development. However, many countries are challenged to provide these basic necessities to their populations, leaving people at risk for water, sanitation, and hygiene (WASH)-related diseases. Because contaminated water is a major cause of illness and death, water quality is a determining factor in human poverty, education, and economic opportunities.

Lack of access to adequate drinking water services contributes to deaths and illness, especially in children. Water based disease transmission by drinking contaminated water is responsible for significant outbreaks of diseases such as cholera and typhoid and includes diarrheal diseases, viral hepatitis A, cholera, dysentery and dracunculiasis (Guineaworm disease). Improving access to clean drinking water is a crucial element in the reduction of under-five mortality and morbidity and there is evidence that ensuring higher levels of drinking water services has a greater impact.

Women and children spend millions of hours each year fetching water. The chore diverts their time from other important activities (for example attending school, caring for children, participating in the economy). When water is not available on premises and has to be collected, women and girls are almost two and a half times more likely than men and boys to be the main water carriers for their families.

Many international organizations use access to safe drinking water and hygienic sanitation facilities as a measure for progress in the fight against poverty, disease, and death. Access to safe drinking water is also considered to be a human right, not a privilege, for every man, woman, and child. Economic benefits of safe drinking water services include higher economic productivity, more education, and health-care savings.

IndicatorName: People using at least basic drinking water services, rural (% of rural population)

Limitationsandexceptions: National, regional and income group estimates are made when data are available for at least 50 percent of the population.

Longdefinition: 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.

Source: WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene (washdata.org).

Statisticalconceptandmethodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys.  WHO/UNICEF defines a basic drinking water service 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.


IndicatorName: People using at least basic drinking water services, urban (% of urban population)


IndicatorName: People using at least basic drinking water services (% of population)


Generalcomments:
Aggregate data by groups are computed based on the groupings for the World Bank fiscal year in which the data was released by the WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene.

This is a disaggregated indicator for Sustainable Development Goal 6.1.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: People using safely managed drinking water services, rural (% of rural population)

Limitationsandexceptions: In order to meet the criteria for a safely managed drinking water service, an improved water source should meet three criteria: it should be accessible on the premises (accessibility), water should be available when needed (availability), and the water supplied should be free from contamination (quality).  Many countries lack data on one or more elements of safely managed drinking water.  The WHO/UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (JMP) provide national estimates only when data are available on drinking water quality and at least one of the other criteria (accessibility and availability).  Regional and income group estimates are made when data are available for at least 30 percent of the population.

Longdefinition: 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.

Statisticalconceptandmethodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys.  WHO/UNICEF defines a safely managed drinking water as an improved water 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.


IndicatorName: People using safely managed drinking water services, urban (% of urban population)


Generalcomments:
Aggregate data by groups are computed based on the groupings for the World Bank fiscal year in which the data was released by the WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene.

This is the Sustainable Development Goal indicator 6.1.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: People using safely managed drinking water services (% of population)


IndicatorName: Children (0-14) living with HIV

Longdefinition: Children living with HIV refers to the number of children ages 0-14 who are infected with HIV.


Generalcomments: In many developing countries most new infections occur in young adults, with young women especially vulnerable.

IndicatorName: Prevalence of HIV, female (% ages 15-24)

Longdefinition: 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.


IndicatorName: Comprehensive correct knowledge of HIV/AIDS, ages 15-24, female (2 prevent ways and reject 3 misconceptions)

Longdefinition: The percent of female respondents ages 15-24 who correctly identify the two major ways of preventing the sexual transmission of HIV (using condoms and limiting sex to one faithful, uninfected partner), who reject the two most common local misconceptions about HIV transmission, and who know that a healthy-looking person can have HIV.

Source: Household surveys such as Demographic and Health Surveys and Multiple Indicator Cluster Surveys.  Largely compiled by UNICEF.


IndicatorName: Comprehensive correct knowledge of HIV/AIDS, ages 15-24, male (2 prevent ways and reject 3 misconceptions)

Longdefinition: The percent of male respondents ages 15-24 who correctly identify the two major ways of preventing the sexual transmission of HIV (using condoms and limiting sex to one faithful, uninfected partner), who reject the two most common local misconceptions about HIV transmission, and who know that a healthy-looking person can have HIV.