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)

License_Type: CC BY-4.0

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.

Periodicity: Annual

Topic: Health: Disease prevention


Aggregationmethod: Weighted average

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

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

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, male is the percentage of males who are infected with HIV. Youth rates are as a percentage of the relevant age group.

Source: UNAIDS estimates.

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.

Topic: Health: Risk factors


IndicatorName: Antiretroviral therapy coverage (% of people living with HIV)

Longdefinition: Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.

Statisticalconceptandmethodology:
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.

Antiretroviral therapy has led to huge reductions in death and suffering of people with advanced HIV infection.


IndicatorName: Comprehensive correct knowledge of HIV/AIDS, ages 15-49, female (2 prevent ways and reject 3 misconceptions)

Longdefinition: Knowledge of HIV, female, is the percentage of female respondents 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.


IndicatorName: Comprehensive correct knowledge of HIV/AIDS, ages 15-49, male (2 prevent ways and reject 3 misconceptions)

Longdefinition: Knowledge of HIV, male, is the percentage of male respondents 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.


IndicatorName: Children orphaned by HIV/AIDS

Longdefinition: Number of children orphaned by HIV/AIDS is the estimated number of children who have lost their mother or both parents to AIDS before age 15 since the epidemic began. Some of the orphaned children included in this cumulative total are no longer alive; others are no longer under age 15.


Developmentrelevance: Immunization is one of the most cost-effective public health interventions, and ??is an essential component for reducing under-five mortality. Immunization coverage estimates are used to monitor coverage of immunization services and to guide disease eradication and elimination efforts.

IndicatorName: Immunization, measles (% of children ages 12-23 months)

Limitationsandexceptions: In many developing countries a lack of precise information on the size of the cohort of one-year-old children makes immunization coverage difficult to estimate from program statistics.

Longdefinition: Child immunization, measles, measures the percentage of children ages 12-23 months who received the measles vaccination before 12 months or at any time before the survey. A child is considered adequately immunized against measles after receiving one dose of vaccine.

Source: WHO and UNICEF (http://www.who.int/immunization/monitoring_surveillance/en/).

Statisticalconceptandmethodology:
Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package. The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year.

Notes on regional and global aggregates: When the vaccine is not introduced in a national immunization schedule, the missing value is assumed zero (or close to zero) in the relevant groups' averages.


IndicatorName: Use of insecticide-treated bed nets (% of under-5 population)

Longdefinition: Use of insecticide-treated bed nets refers to the percentage of children under age five who slept under an insecticide-treated bednet to prevent malaria.

Source: UNICEF, State of the World's Children, Childinfo, and Demographic and Health Surveys.

Statisticalconceptandmethodology: Malaria is endemic to the poorest countries in the world, mainly in tropical and subtropical regions of Africa, Asia, and the Americas. Insecticide-treated nets, properly used and maintained, are one of the most important malaria-preventive strategies to limit human-mosquito contact.


IndicatorName: Children with fever receiving antimalarial drugs (% of children under age 5 with fever)

Longdefinition: Malaria treatment refers to the percentage of children under age five who were ill with fever in the last two weeks and received any appropriate (locally defined) anti-malarial drugs.

Statisticalconceptandmethodology: Malaria is endemic to the poorest countries in the world, mainly in tropical and subtropical regions of Africa, Asia, and the Americas. Prompt and effective treatment of malaria is a critical element of malaria control. It is vital that sufferers, especially children under age 5, start treatment within 24 hours of the onset of symptoms, to prevent progression - often rapid - to severe malaria and death. Data on malaria are from national-level surveys, including Multiple Indicator Cluster Surveys, Demographic and Health Surveys, and Malaria Indicator Surveys.


Developmentrelevance:
Sanitation is fundamental to human development. Many international organizations use hygienic sanitation facilities as a measure for progress in the fight against poverty, disease, and death. Access to proper sanitation is also considered to be a human right, not a privilege, for every man, woman, and child.

Sanitation generally refers to the provision of facilities and services for the safe disposal of human urine and feces. Inadequate sanitation is a major cause of disease world-wide and improving sanitation is known to have a significant beneficial impact on people's health. Improved sanitation can reduce diarrheal disease, and can significantly lessen the adverse health impacts of other disorders responsible for death and disease among millions of children. Diarrhea and worm infections weaken children and make them more susceptible to malnutrition and opportunistic infections like pneumonia, measles and malaria.

The combined effects of inadequate sanitation, unsafe water supply and poor personal hygiene are responsible for many of childhood deaths. Every year, the failure to tackle these deficits results in severe welfare losses - wasted time, reduced productivity, ill health, impaired learning, environmental degradation and lost opportunities. Fundamental behavior changes are required before the use of improved facilities and services can be integrated into daily life. Many hygiene behaviors and habits are formed in childhood and, therefore, school health and hygiene education programs are an important part of water and sanitation improvements.

Most basic sanitation technologies are not expensive to implement. However, those facing the problems of inadequate sanitation are rarely aware of either the origin of their ills, or the true costs of their deficit. As a result, in most of the developing countries those without sanitation are hard to convince of the need to invest scarce resources in sanitation facilities, or of the critical importance of changing long-held habits and unhygienic behaviors. Consequently, the people's representatives - governments and elected political leaders - rarely give sanitation or hygiene improvements the priority that is needed in order to tackle the massive sanitation deficit faced by the developing world.

Children bear the brunt of sanitation-related impacts - their health, nutrition, growth, education, self-respect, and life opportunities suffers as a result of inadequate sanitation. Without improved sanitation, many of the current generation of children in developing countries are unlikely to develop to their full potential. Countries that don't take urgent action to redress sanitation deficiencies will find their future development and prosperity impaired.

IndicatorName: Improved sanitation facilities (% of population with access)

Limitationsandexceptions:
Please note that the data for this indicator have not been updated since 2015.  The WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation has introduced updated water and sanitation indicators.  For the most recent data on access to sanitation facilities, please see the following indicators: People using safely managed sanitation services (% of population) (SH.STA.SMSS.ZS) and People using basic sanitation services (% of population) (SH.STA.BASS.ZS).

The data are derived by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on national censuses and nationally representative household surveys. The coverage rates for sanitation are based on information from service users on the facilities their households actually use rather than on information from service providers, which may include nonfunctioning systems.

Longdefinition: Access to improved sanitation facilities refers to the percentage of the population using improved sanitation facilities. Improved sanitation facilities are likely to ensure hygienic separation of human excreta from human contact. They include flush/pour flush (to piped sewer system, septic tank, pit latrine), ventilated improved pit (VIP) latrine, pit latrine with slab, and composting toilet.

Source: WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply and Sanitation (http://www.wssinfo.org/).

Statisticalconceptandmethodology:
Data on access to sanitation are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on national censuses and nationally representative household surveys. The coverage rates for water and sanitation are based on information from service users on the facilities their households actually use rather than on information from service providers, which may include nonfunctioning systems.

An improved sanitation facility is defined as one that hygienically separates human excreta from human contact. Improved sanitation facilities range from simple but protected pit latrines to flush toilets with a sewerage connection. To be effective, facilities must be correctly constructed and properly maintained.


Generalcomments: Good prenatal and postnatal care improve maternal health and reduce maternal and infant mortality.

IndicatorName: Pregnant women receiving prenatal care of at least four visits (% of pregnant women)

Limitationsandexceptions: For the indicators that are from household surveys, the year refers to the survey year. For more information, consult the original sources.

Longdefinition: Pregnant women receiving prenatal care, at least four times, are the percentage of women attended at least four times during pregnancy by skilled health personnel for reasons related to pregnancy.

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.

Good prenatal and postnatal care improves maternal health and reduces maternal and infant mortality. However, indicators on use of antenatal care services provide no information on the content or quality of the services. Data on antenatal care are obtained mostly from household surveys, which ask women who have had a live birth whether and from whom they received antenatal care.

Topic: Health: Reproductive health


IndicatorName: Pregnant women receiving prenatal care (%)

Longdefinition: Pregnant women receiving prenatal care are the percentage of women attended at least once during pregnancy by skilled health personnel for reasons related to pregnancy.


IndicatorName: ARI treatment (% of children under 5 taken to a health provider)

Longdefinition: Children with acute respiratory infection (ARI) who are taken to a health provider refers to the percentage of children under age five with ARI in the last two weeks who were taken to an appropriate health provider, including hospital, health center, dispensary, village health worker, clinic, and private physician.

Statisticalconceptandmethodology: Acute respiratory infection continues to be a leading cause of death among young children. Data are drawn mostly from household health surveys in which mothers report on number of episodes and treatment for acute respiratory infection.


Developmentrelevance:
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.

The share of births attended by skilled health staff is an indicator of a health system's ability to provide adequate care for pregnant women.

Generalcomments:
Assistance by trained professionals during birth reduces the incidence of maternal deaths during childbirth. The share of births attended by skilled health staff is an indicator of a health system’s ability to provide adequate care for pregnant women.

This is the Sustainable Development Goal indicator 3.1.2[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Births attended by skilled health staff (% of total)

Longdefinition: Births attended by skilled health staff are the percentage of deliveries attended by personnel trained to give the necessary supervision, care, and advice to women during pregnancy, labor, and the postpartum period; to conduct deliveries on their own; and to care for newborns.


Aggregationmethod: Linear mixed-effect model estimates

DataQuality: UNICEF, WHO and the World Bank undertake a joint review for each potential primary data source included in the joint database. The group conducts a review when (at minimum) a final report with full methodological details and results are available, as well as (ideally) a data quality assessment flagging potential limitation. When the raw data are available, they are analysed using the Anthro Survey Analyzer software to produce a standard set of results and data quality outputs against which the review is conducted. Comments are documented in a standard review template extracting methodological details (e.g., sampling procedures, description of anthropometrical equipment), data quality outputs (e.g., weight and height distributions, percentage of cases that were flagged as implausible according to the WHO Child Growth Standards) and the malnutrition prevalence estimates from the data source under review generated based on the standard recommended methodology. These estimates are compared against the reported values, as well as against those from other data sources already included in the JME dataset, to assess the plausibility of the trend before including the new point. Reports that are preliminary, or that lack key details on methodology or results, cannot be reviewed and are left pending until full information is available.

Derivationmethod: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described in Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old and WHO Anthro Survey Analyser.

Generalcomments: Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF). Estimates are from national survey data. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

IndicatorName: Prevalence of underweight, weight for age (% of children under 5)

Limitationsandexceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels.

Longdefinition: Prevalence of underweight children is the percentage of children under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's 2006 Child Growth Standards.

Otherweblinks:
Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old. Geneva: World Health Organization and the United Nations Children’s Fund (UNICEF), 2019. Licence: CC BY-NC-SA 3.0 IGO.
https://data.unicef.org/resources/data-collection-analysis-reporting-on-anthropometric-indicators-in-children-under-5/
https://www.who.int/publications/i/item/9789241515559

WHO Anthro Survey Analyzer - https://www.who.int/tools/child-growth-standards/software

Source: UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.

Topic: Health: Nutrition


IndicatorName: Malaria cases reported

Longdefinition: Reported cases of malaria are the number of confirmed cases of malaria (confirmed by slide examination or RDT).

Notesfromoriginalsource: In endemic countries where health information system is weak and diagnosis is limited, national malaria control programmes (NMCPs) often collect data on the number of suspected cases, those tested and those confirmed. Probable or unconfirmed cases are calculated by subtracting the number tested from the number suspected.

Source: World Health Organization, World malaria report and Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/ghodata/). WHO compiles data on reported cases of malaria, submitted by the national malaria control programmes (NMCPs).


Generalcomments: This indicator represents the risk associated with each pregnancy and is also a Sustainable Development Goal Indicator (3.1.1) for monitoring maternal health.

IndicatorName: Maternal mortality ratio (modeled estimate, per 100,000 live births)

Limitationsandexceptions: The methodology differs from that used for previous estimates, so data should not be compared historically. Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. The ratios cannot be assumed to provide an exact estimate of maternal mortality.

Longdefinition: Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP measured using purchasing power parities (PPPs).

Notesfromoriginalsource: Estimates of maternal mortality are presented along with upper and lower  limits of intervals (see footnote) designed to depict the uncertainty of estimates. The intervals are the product of a detailed probabilistic evaluation of the uncertainty attributable to the various components of the estimation process. For estimates derived from the multilevel regression model, the components of uncertainty were divided into two groups: those reflected within the regression model (internal sources), and those due to assumptions or calculations that occur outside the model (external sources). Estimates of the total uncertainty reflect a combination of these various sources.

Source: WHO, UNICEF, UNFPA, World Bank Group, and UNDESA/Population Division. Trends in Maternal Mortality 2000 to 2020. Geneva, World Health Organization, 2023

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.

Maternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.

The estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.


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 World Health Organization.

IndicatorName: Tuberculosis treatment success rate (% of new cases)

Longdefinition: Tuberculosis treatment success rate is the percentage of all new tuberculosis cases (or new and relapse cases for some countries) registered under a national tuberculosis control programme in a given year that successfully completed treatment, with or without bacteriological evidence of success ("cured" and "treatment completed" respectively).

Source: World Health Organization, Global Tuberculosis Report.

Statisticalconceptandmethodology: Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. Data on the success rate of tuberculosis treatment are provided for countries that have submitted data to the WHO. The treatment success rate for tuberculosis provides a useful indicator of the quality of health services. A low rate suggests that infectious patients may not be receiving adequate treatment. An important complement to the tuberculosis treatment success rate is the case detection rate, which indicates whether there is adequate coverage by the recommended case detection and treatment strategy.


IndicatorName: Tuberculosis case detection rate (%, all forms)

Longdefinition: Tuberculosis case detection rate (all forms) is the number of new and relapse tuberculosis cases notified to WHO in a given year, divided by WHO's estimate of the number of incident tuberculosis cases for the same year, expressed as a percentage. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.

Notesfromoriginalsource: Estimates are presented with uncertainty intervals (see footnote). When ranges are presented, the lower and higher numbers correspond to the 2.5th and 97.5th centiles of the outcome distributions (generally produced by simulations). For more detailed information, see the original source.

Statisticalconceptandmethodology: Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. This indicator shows the tuberculosis detection rate for all detection methods. Editions before 2010 included the tuberculosis detection rates by DOTS, the internationally recommended strategy for tuberculosis control. Thus data on the case detection rate from 2010 onward cannot be compared with data in previous editions.


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 World Health Organization.

This is the Sustainable Development Goal indicator 3.3.2[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Incidence of tuberculosis (per 100,000 people)

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.

Uncertainty bounds for the incidence are available at http://data.worldbank.org

Longdefinition: Incidence of tuberculosis is the estimated number of new and relapse tuberculosis cases arising in a given year, expressed as the rate per 100,000 population. All forms of TB are included, including cases in people living with HIV. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.

Statisticalconceptandmethodology: Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. In developed countries tuberculosis has reemerged largely as a result of cases among immigrants. Since tuberculosis incidence cannot be directly measured, estimates are obtained by eliciting expert opinion or are derived from measurements of prevalence or mortality.


IndicatorName: Tuberculosis death rate (per 100,000 people)

Longdefinition: Tuberculosis death rate is the estimated number of deaths from tuberculosis among HIV-negative people, expressed as the rate per 100,000 population. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published previously.

Topic: Health: Mortality


Developmentrelevance: The World Bank Group's goal of promoting shared prosperity has been defined as fostering income growth of the bottom 40 per cent of the welfare distribution in every country. Income distribution measures are important background indicators for shared prosperity.

Generalcomments: The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

IndicatorName: Income share held by lowest 20%

Limitationsandexceptions:
Despite progress in the last decade, the challenges of measuring poverty remain. The timeliness, frequency, quality, and comparability of household surveys need to increase substantially, particularly in the poorest countries. The availability and quality of poverty monitoring data remains low in small states, countries with fragile situations, and low-income countries and even some middle-income countries. The low frequency and lack of comparability of the data available in some countries create uncertainty over the magnitude of poverty reduction.

Besides the frequency and timeliness of survey data, other data quality issues arise in measuring household living standards. The surveys ask detailed questions on sources of income and how it was spent, which must be carefully recorded by trained personnel. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of living standards. And income can vary over time even if living standards do not. But consumption data are not always available: the latest estimates reported here use consumption data for about two-thirds of countries.

However, even similar surveys may not be strictly comparable because of differences in timing or in the quality and training of enumerators. Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of the consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure but may not be. Most survey data now include valuations for consumption or income from own production, but valuation methods vary.

Longdefinition: Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.

Relatedsourcelinks: World Bank, Poverty and Inequality Platform: https://pip.worldbank.org/

Shortdefinition: Percentage share of income or consumption that accrues to the first (poorest) quintile.

Source: World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.

Statisticalconceptandmethodology:
Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.

Data on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.

The distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption.

The year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.

Percentage shares by quintile may not sum to 100 because of rounding.

Topic: Poverty: Income distribution


Developmentrelevance: The World Bank Group is committed to reducing extreme poverty to 3 percent or less, globally, by 2030. Monitoring poverty is important on the global development agenda as well as on the national development agenda of many countries. The World Bank produced its first global poverty estimates for developing countries for World Development Report 1990: Poverty (World Bank 1990) using household survey data for 22 countries (Ravallion, Datt, and van de Walle 1991). Since then there has been considerable expansion in the number of countries that field household income and expenditure surveys.

IndicatorName: Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population)

Longdefinition: Poverty headcount ratio at $2.15 a day is the percentage of the population living on less than $2.15 a day at 2017 purchasing power adjusted prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Shortdefinition: Poverty headcount ratio at $2.15 a day is the percentage of the population living on less than $2.15 a day at 2017 international prices.

Statisticalconceptandmethodology:
International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.

Since World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $2.15 as the international poverty line using the 2017 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.65 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $6.85 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.

Early editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2017 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $2.15 a day in 2017 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

The statistics reported here are based on consumption data or, when unavailable, on income surveys.

Topic: Poverty: Poverty rates


IndicatorName: Poverty gap at $2.15 a day (2017 PPP) (%)

Longdefinition: Poverty gap at $2.15 a day (2017 PPP) is the mean shortfall in income or consumption from the poverty line $2.15 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.


Generalcomments: This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

IndicatorName: Poverty gap at national poverty lines (%)

Longdefinition: Poverty gap at national poverty lines is the mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.

Source: World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.

Statisticalconceptandmethodology:
Poverty headcount ratio among the population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.

Poverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.

National poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.

Almost all national poverty lines are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years. The data is based on the two most recent years for which survey data are available.

Survey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.


Developmentrelevance: The poverty rate as defined by national poverty lines reflects the share of the population that fails to meet the standard a country thinks is necessarty to cover basic needs.

IndicatorName: Poverty headcount ratio at national poverty lines (% of population)

Longdefinition: National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.

Source: World Bank, Poverty and Inequality Platform. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.

Statisticalconceptandmethodology:
Poverty headcount ratio among the population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.

Poverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.

National poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.

Almost all national poverty lines in developing economies are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years.

This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year. For all other economies, the year reported is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which data collection started.


IndicatorName: Rural poverty gap at national poverty lines (%)

Longdefinition: Rural poverty gap at national poverty lines is the rural population's mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.

Statisticalconceptandmethodology:
Poverty headcount ratio among the rural population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.

Poverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.

National poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.

Almost all national poverty lines are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years. The data is based on the two most recent years for which survey data are available.

Survey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.


IndicatorName: Rural poverty headcount ratio at national poverty lines (% of rural population)

Longdefinition: Rural poverty headcount ratio is the percentage of the rural population living below the national poverty lines.


IndicatorName: Urban poverty gap at national poverty lines (%)

Longdefinition: Urban poverty gap at national poverty lines is the urban population's mean shortfall from the poverty lines (counting the nonpoor as having zero shortfall) as a percentage of the poverty lines. This measure reflects the depth of poverty as well as its incidence.

Statisticalconceptandmethodology:
Poverty headcount ratio among the urban population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.

Poverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.

National poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.

Almost all national poverty lines are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years. The data is based on the two most recent years for which survey data are available.

Survey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.


IndicatorName: Urban poverty headcount ratio at national poverty lines (% of urban population)

Longdefinition: Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.


Developmentrelevance: Four targets were added to the UN Millennium Declaration at the 2005 World Summit High-Level Plenary Meeting of the 60th Session of the UN General Assembly. One was full and productive employment and decent work for all, which is seen as the main route for people to escape poverty. Employment to population ratio is a key measure to monitor whether a country is on track to achieve the Millennium Development Goal of eradicating extreme poverty and hunger by 2015. And it continues to be a priority in the Sustainable Development Goal of promoting sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all.

Generalcomments: National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

IndicatorName: Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate)

Limitationsandexceptions:
Data on employment by status are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. The labor force survey is the most comprehensive source for internationally comparable employment, but there are still some limitations for comparing data across countries and over time even within a country.

Comparability of employment ratios across countries is affected by variations in definitions of employment and population. The biggest difference results from the age range used to define labor force activity. The population base for employment ratios can also vary. Most countries use the resident, non-institutionalized population of working age living in private households, which excludes members of the armed forces and individuals residing in mental, penal, or other types of institutions. But some countries include members of the armed forces in the population base of their employment ratio while excluding them from employment data.

The reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. Employment ratios tend to vary during the year as seasonal workers enter and leave.

This indicator also has a gender bias because women who do not consider their work employment or who are not perceived as working tend to be undercounted. This bias has different effects across countries and reflects demographic, social, legal, and cultural trends and norms.

Longdefinition: Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.

Notesfromoriginalsource: Given the exceptional situation, including the scarcity of relevant data, the  ILO modeled estimates and projections from 2020 onwards are subject to substantial uncertainty.

Source: International Labour Organization. “ILO Modelled Estimates and Projections database (ILOEST)” ILOSTAT. Accessed February 06, 2024. https://ilostat.ilo.org/data/.

Statisticalconceptandmethodology:
The employment-to-population ratio indicates how efficiently an economy provides jobs for people who want to work. A high ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be seen as a positive sign, especially for young people, if an increase in their education causes it.

The series is part of the "ILO modeled estimates database," including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/

Topic: Social Protection & Labor: Economic activity


IndicatorName: Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate)


IndicatorName: Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate)


Developmentrelevance:
Data on women in wage employment in the nonagricultural sector show the extent to which women have access to paid employment - which affects their integration into the monetary economy - and indicate the degree to which labor markets are open to women in industry and services - which affects not only equal employment opportunity for women, but also economic efficiency through flexibility of the labor market and the economy's capacity to adapt to changes over time.

In many developing countries nonagricultural wage employment accounts for only a small portion of total employment. As a result, the contribution of women to the national economy is underestimated and therefore misrepresented. The indicator is difficult to interpret without additional information on the share of women in total employment, which allows an assessment to be made of whether women are under- or overrepresented in nonagricultural wage employment. The indicator does not reveal differences in the quality of nonagricultural wage employment in terms of earnings, work conditions, or legal and social protection. The indicator also does not reflect whether women reap the economic benefits of such employment. Finally, female employment and the employment share of the agricultural sector for both men and women tend to be underreported.

Women's wage work is important for economic growth and the well-being of families. But women often face such obstacles as restricted access to credit markets, capital, land, and training and education; time constraints due to traditional family responsibilities; and labor market bias and discrimination. These obstacles force women to limit their full participation in paid economic activities, to be less productive, and to receive lower wages.

Generalcomments: Relevance to gender indicator: Women’s share in paid employment in the nonagricultural sector has risen marginally in some regions but remains less than 20 percent in South Asia and Sub-Saharan Africa. Women are also clearly segregated in sectors that are generally known to be lower paid. And in the sectors where women dominate, such as health care, women rarely hold upper-level management jobs.

IndicatorName: Share of women in wage employment in the nonagricultural sector (% of total nonagricultural employment)

Limitationsandexceptions:
There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.

Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.

The reference period of a census or survey is another important source of differences: in some countries data refer to people's status on the day of the census or survey or during a specific period before the inquiry date, while in others data are recorded without reference to any period. In developing countries, where the household is often the basic unit of production and all members contribute to output, but some at low intensity or irregularly, the estimated labor force may be much smaller than the numbers actually working.

Longdefinition: Share of women in wage employment in the nonagricultural sector is the share of female workers in wage employment in the nonagricultural sector (industry and services), expressed as a percentage of total employment in the nonagricultural sector. Industry includes mining and quarrying (including oil production), manufacturing, construction, electricity, gas, and water, corresponding to divisions 2-5 (ISIC revision 2) or tabulation categories C-F (ISIC revision 3). Services include wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services-corresponding to divisions 6-9 (ISIC revision 2) or tabulation categories G-Q (ISIC revision 3).

Source: International Labour Organization.

Statisticalconceptandmethodology:
Employment is defined as persons above a specified age who performed any work at all, in the reference period, for pay or profit (or pay in kind), or were temporarily absent from a job for such reasons as illness, maternity or parental leave, holiday, training or industrial dispute. Unpaid family workers who work for at least one hour should be included in the count of employment, although many countries use a higher hour limit in their definition.

Labor force statistics by gender is important to monitor gender disparities in employment patterns. Estimates of women in the labor force and employment are generally lower than those of men and are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.


Developmentrelevance:
Breaking down employment information by status in employment provides a statistical basis for describing workers' behaviour and conditions of work, and for defining an individual's socio-economic group. A high proportion of wage and salaried workers in a country can signify advanced economic development. If the proportion of own-account workers (self-employed without hired employees) is sizeable, it may be an indication of a large agriculture sector and low growth in the formal economy. A high proportion of contributing family workers — generally unpaid, although compensation might come indirectly in the form of family income — may indicate weak development, little job growth, and often a large rural economy.

Each status group faces different economic risks, and contributing family workers and own-account workers are the most vulnerable - and therefore the most likely to fall into poverty. They are the least likely to have formal work arrangements, are the least likely to have social protection and safety nets to guard against economic shocks, and often are incapable of generating sufficient savings to offset these shocks.

IndicatorName: Self-employed, female (% of female employment) (modeled ILO estimate)

Limitationsandexceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.

Longdefinition: Self-employed workers are those workers who, working on their own account or with one or a few partners or in cooperative, hold the type of jobs defined as a "self-employment jobs." i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced. Self-employed workers include four sub-categories of employers, own-account workers, members of producers' cooperatives, and contributing family workers.

Source: International Labour Organization. “ILO modelled estimates database” ILOSTAT. Accessed February 07, 2024. https://ilostat.ilo.org/data/.

Statisticalconceptandmethodology:
The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.

The series is part of the "ILO modeled estimates database," including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/


IndicatorName: Self-employed, male (% of male employment) (modeled ILO estimate)


IndicatorName: Self-employed, total (% of total employment) (modeled ILO estimate)


IndicatorName: Employment to population ratio, 15+, female (%) (modeled ILO estimate)

Longdefinition: Employment to population ratio is the proportion of a country's population that is employed. Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.


IndicatorName: Employment to population ratio, 15+, male (%) (modeled ILO estimate)


IndicatorName: Employment to population ratio, 15+, total (%) (modeled ILO estimate)


IndicatorName: Vulnerable employment, female (% of female employment) (modeled ILO estimate)

Longdefinition: Vulnerable employment is contributing family workers and own-account workers as a percentage of total employment.

Source: World Bank, World Development Indicators database. Estimates are based on data obtained from International Labour Organization, ILOSTAT at https://ilostat.ilo.org/data/.


IndicatorName: Vulnerable employment, male (% of male employment) (modeled ILO estimate)


IndicatorName: Vulnerable employment, total (% of total employment) (modeled ILO estimate)


IndicatorName: Contributing family workers, female (% of female employment) (modeled ILO estimate)

Longdefinition: Contributing family workers are those workers who hold "self-employment jobs" as own-account workers in a market-oriented establishment operated by a related person living in the same household.


IndicatorName: Contributing family workers, male (% of male employment) (modeled ILO estimate)


IndicatorName: Contributing family workers, total (% of total employment) (modeled ILO estimate)


Developmentrelevance:
Labor productivity is used to assess a country's economic ability to create and sustain decent employment opportunities with fair and equitable remuneration. Productivity increases obtained through investment, trade, technological progress, or changes in work organization can increase social protection and reduce poverty, which in turn reduce vulnerable employment and working poverty. Productivity increases do not guarantee these improvements, but without them - and the economic growth they bring - improvements are highly unlikely.

GDP per person employed is a key measure to monitor whether a country is on track to achieve the Sustainable Development Goal of promoting sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all. [SDG Indicator 8.2.1]

IndicatorName: GDP per person employed (constant 2021 PPP $)

Limitationsandexceptions: For comparability of individual sectors labor productivity is estimated according to national accounts conventions. However, there are still significant limitations on the availability of reliable data. Information on consistent series of output in both national currencies and purchasing power parity dollars is not easily available, especially in developing countries, because the definition, coverage, and methodology are not always consistent across countries. For example, countries employ different methodologies for estimating the missing values for the nonmarket service sectors and use different definitions of the informal sector.

Longdefinition: GDP per person employed is gross domestic product (GDP) divided by total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2021 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP that a U.S. dollar has in the United States.

Source: World Bank, World Development Indicators database. Estimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank.

Statisticalconceptandmethodology:
GDP per person employed represents labor productivity—output per unit of labor input. To compare labor productivity levels across countries, GDP is converted to international dollars using purchasing power parity rates which take account of differences in relative prices between countries.

Estimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank. The employment rates are part of the "ILO modeled estimates database," including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/


Developmentrelevance: Good nutrition is the cornerstone for survival, health and development. Well-nourished children perform better in school, grow into healthy adults and in turn give their children a better start in life. Well-nourished women face fewer risks during pregnancy and childbirth, and their children set off on firmer developmental paths, both physically and mentally (UNICEF www.childinfo.org).

Generalcomments: This is the Sustainable Development Goal indicator 2.1.1[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Prevalence of undernourishment (% of population)

Limitationsandexceptions: From a policy and program standpoint, this measure has its limits. First, food insecurity exists even where food availability is not a problem because of inadequate access of poor households to food. Second, food insecurity is an individual or household phenomenon, and the average food available to each person, even corrected for possible effects of low income, is not a good predictor of food insecurity among the population. And third, nutrition security is determined not only by food security but also by the quality of care of mothers and children and the quality of the household's health environment (Smith and Haddad 2000).

Longdefinition: Prevalence of undernourishments is the percentage of the population whose habitual food consumption is insufficient to provide the dietary energy levels that are required to maintain a normal active and healthy life. Data showing as 2.5 may signify a prevalence of undernourishment below 2.5%.

Source: Food and Agriculture Organization (http://www.fao.org/faostat/en/#home).

Statisticalconceptandmethodology: Data on undernourishment are from the Food and Agriculture Organization (FAO) of the United Nations and measure food deprivation based on average food available for human consumption per person, the level of inequality in access to food, and the minimum calories required for an average person.


Generalcomments: This is the Sustainable Development Goal indicator 3.7.2 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Adolescent fertility rate (births per 1,000 women ages 15-19)

Longdefinition: Adolescent fertility rate is the number of births per 1,000 women ages 15-19.

Source: United Nations Population Division, World Population Prospects.

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.

Adolescent fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without vital registration systems fertility rates are generally based on extrapolations from trends observed in censuses or surveys from earlier years.


Developmentrelevance:
Contraceptive prevalence among women of reproductive age is related to maternal and child health, as well as gender equality and HIV/AIDS.   Contraceptives enable women and men to make informed decisions on family planning – whether, when, and how many children they would have.

Preventing unwanted pregnancies is essential to reducing maternal deaths, especially in low- and middle- income countries where maternal mortality rate is high.  With effective contraception, life-threatening pregnancy complications can be reduced, and thus maternal deaths can be averted.

Using condoms (one of the modern contraceptive methods) can prevent pregnancy as well as sexually transmitted diseases, including HIV.

IndicatorName: Contraceptive prevalence, any method (% of married women ages 15-49)

Limitationsandexceptions:
While the data availability on contraceptive use has increased, in many countries the contraceptive use data are available only for married women.

The time frame used to assess contraceptive prevalence may vary. In many surveys, it is left to the respondent to determine what is meant by “currently using” a method of contraception.

Longdefinition: Contraceptive prevalence, any method is the percentage of married women ages 15-49 who are practicing, or whose sexual partners are practicing, any method of contraception (modern or traditional). Modern methods of contraception include female and male sterilization, oral hormonal pills, the intra-uterine device (IUD), the male condom, injectables, the implant (including Norplant), vaginal barrier methods, the female condom and emergency contraception. Traditional methods of contraception include rhythm (e.g., fertility awareness based methods, periodic abstinence), withdrawal and other traditional methods.

Othernotes: As of December 2021, for better consistency the contraceptive prevalence data only for currently married women or in union are included in this indicator. It means the data for the following categories are excluded from this indicator: ever-married women; all women; sexually active women; which data may have been included in this indicator before December 2021. In response to this, two new contraceptive prevalence indicators (any method and any modern method) for sexually active unmarried women 15-49 are added to the HealthStats database. https://databank.worldbank.org/source/health-nutrition-and-population-statistics

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

Statisticalconceptandmethodology:
Contraceptive prevalence rates are obtained mainly from nationally representative household surveys, including: Demographic and Health Surveys; Multiple Indicator Cluster Surveys; Contraceptive Prevalence Surveys; Gender and Generations Survey; Reproductive Health Surveys; and World Fertility Surveys.  Additional information was provided by other international survey programs and national surveys.

Married women refer to women who are married (defined in relation to the marriage laws or customs of a country) and to women in a union, which refers to women living with their partner in the same household (also referred to as cohabiting unions, consensual unions, unmarried unions, or “living together”).


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.

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

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: Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.

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.

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: Life expectancy at birth, total (years)

Longdefinition: Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.

Source: (1) United Nations Population Division. World Population Prospects: 2022 Revision; or derived from male and female life expectancy at birth from sources such as: (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics.

Statisticalconceptandmethodology:
Life expectancy at birth used here is the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. It reflects the overall mortality level of a population, and summarizes the mortality pattern that prevails across all age groups in a given year. It is calculated in a period life table which provides a snapshot of a population's mortality pattern at a given time. It therefore does not reflect the mortality pattern that a person actually experiences during his/her life, which can be calculated in a cohort life table.

High mortality in young age groups significantly lowers the life expectancy at birth. But if a person survives his/her childhood of high mortality, he/she may live much longer. For example, in a population with a life expectancy at birth of 50, there may be few people dying at age 50. The life expectancy at birth may be low due to the high childhood mortality so that once a person survives his/her childhood, he/she may live much longer than 50 years.


Developmentrelevance: 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.

Generalcomments: Relevance to gender indicator: it can indicate the status of women within households and a woman’s decision about the number and spacing of children.

IndicatorName: Fertility rate, total (births per woman)

Longdefinition: Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.

Source: (1) United Nations Population Division. World Population Prospects: 2022 Revision; (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics.

Statisticalconceptandmethodology: Total fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without reliable vital registration systems fertility rates are generally based on extrapolations from trends observed in censuses or surveys from earlier years.


Aggregationmethod: Sum

Developmentrelevance: Increases in human population, whether as a result of immigration or more births than deaths, can impact natural resources and social infrastructure.  This can place pressure on a country's sustainability.  A significant growth in population will negatively impact the availability of land for agricultural production, and will aggravate demand for food, energy, water, social services, and infrastructure. On the other hand, decreasing population size - a result of fewer births than deaths, and people moving out of a country - can impact a government's commitment to maintain services and infrastructure.

Generalcomments: Relevance to gender indicator: disaggregating the population composition by gender will help a country in projecting its demand for social services on a gender basis.

IndicatorName: Population, total

Limitationsandexceptions:
Current population estimates for developing countries that lack (i) reliable recent census data, and (ii) pre- and post-census estimates for countries with census data, are provided by the United Nations Population Division and other agencies.

The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in both the model and the data.

Because future trends cannot be known with certainty, population projections have a wide range of uncertainty.

Longdefinition: Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.

Source: (1) United Nations Population Division. World Population Prospects: 2024 Revision; (2) Statistical databases and publications from national statistical offices; (3) Eurostat: Demographic Statistics; (4) United Nations Statistics Division. Population and Vital Statistics Report (various years).

Statisticalconceptandmethodology:
Population estimates are usually based on national population censuses, and estimates of fertility, mortality and migration.

Errors and undercounting in census occur even in high-income countries.  In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census.

The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data.

The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census.

The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems.

International migration is the only other factor besides birth and death rates that directly determines a country's population change. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect.

Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant.

Topic: Health: Population: Structure


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.

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.


IndicatorName: Goods (excluding arms) admitted free of tariffs from developing countries (% total merchandise imports excluding arms)

Longdefinition: It is the proportion of duty free imports (excluding arms) into developed countries from developing and least developed countries. For the purpose of calculating this indicator, Japan in Asia, Canada and the United States in North America, Australia and New Zealand in Oceania and Iceland, Norway, Switzerland and the EU (25 countries included since 2004) in Europe are considered “developed” regions or areas, following the common accepted practice used for MDG indicators. Developing countries are those not listed as developed or transition countries. The list of least developed countries (LDCs) has been agreed by the General Assembly, on the recommendation of the Committee for Development Policy, Economic and Social Council.

Source: United Nations Conference on Trade and Development, World Trade Organization, and International Trade Center. Data are available online at: www.mdg-trade.org.

Topic: Private Sector & Trade: Imports


IndicatorName: Goods (excluding arms) admitted free of tariffs from least developed countries (% total merchandise imports excluding arms)


IndicatorName: Average tariffs imposed by developed countries on agricultural products from developing countries (%)

Longdefinition: It is the average tariffs imposed by developed countries on subsets of selected items (agricultural products, textile and clothing exports) that are deemed to be of interest to developing countries. For the purpose of calculating this indicator, Japan in Asia, Canada and the United States in North America, Australia and New Zealand in Oceania and Iceland, Norway, Switzerland and the EU (25 countries included since 2004) in Europe are considered “developed” regions or areas, following the common accepted practice used for MDG indicators. Developing countries are those not listed as developed or transition countries. The list of least developed countries (LDCs) has been agreed by the General Assembly, on the recommendation of the Committee for Development Policy, Economic and Social Council. Agricultural, clothing and textile groups follow the definition in WTO agreements based on the Harmonized System 1992, transposed to current versions by WTO Secretariat. Agricultural products correspond to Harmonized System 1992, chapters 01 to 24 less fish and fish products (chap. 03); in addition to parts of chapters 29, 33, 35, 38, 41, 43, 50 to 53. Textile is mainly covered in chapters 50 to 60. The bulk of clothing products are found in chapters 61-63.

Topic: Private Sector & Trade: Tariffs


IndicatorName: Average tariffs imposed by developed countries on agricultural products from least developed countries (%)


IndicatorName: Average tariffs imposed by developed countries on clothing products from developing countries (%)


IndicatorName: Average tariffs imposed by developed countries on clothing products from least developed countries (%)


IndicatorName: Average tariffs imposed by developed countries on textile products from developing countries (%)


IndicatorName: Average tariffs imposed by developed countries on textile products from least developed countries (%)


Generalcomments: Note: Data starting from 2005 are based on the sixth edition of the IMF's Balance of Payments Manual (BPM6).

IndicatorName: Foreign direct investment, net outflows (% of GDP)

Limitationsandexceptions:
FDI data do not give a complete picture of international investment in an economy. Balance of payments data on FDI do not include capital raised locally, an important source of investment financing in some developing countries. In addition, FDI data omit nonequity cross-border transactions such as intra-unit flows of goods and services.

The volume of global private financial flows reported by the World Bank generally differs from that reported by other sources because of differences in sources, classification of economies, and method used to adjust and disaggregate reported information. In addition, particularly for debt financing, differences may also reflect how some installments of the transactions and certain offshore issuances are treated.

Data on equity flows are shown for all countries for which data are available.

Longdefinition: Foreign direct investment refers to direct investment equity flows in an economy. It is the sum of equity capital, reinvestment of earnings, and other capital. Direct investment is a category of cross-border investment associated with a resident in one economy having control or a significant degree of influence on the management of an enterprise that is resident in another economy. Ownership of 10 percent or more of the ordinary shares of voting stock is the criterion for determining the existence of a direct investment relationship. This series shows net outflows of investment from the reporting economy to the rest of the world, and is divided by GDP.

Source: International Monetary Fund, Balance of Payments database, supplemented by data from the United Nations Conference on Trade and Development and official national sources.

Topic: Economic Policy & Debt: Balance of payments: Capital & financial account