Developmentrelevance: Having a child during the teenage years limits girls' opportunities for better education, jobs, and income. Pregnancy is more likely to be unintended during the teenage years, and births are more likely to be premature and are associated with greater risks of complications during delivery and of death. In many countries maternal mortality is a leading cause of death among women of reproductive age, although most of those deaths are preventable. Infants of adolescent mothers are also more likely to have low birth weight, which can have a long-term impact on their health and development. Complications from pregnancy and childbirth are the leading cause of death among girls aged 15-19 years in many low- and middle-income countries.

IndicatorName: Teenage mothers (% of women ages 15-19 who have had children or are currently pregnant)

Longdefinition: Teenage mothers are the percentage of women ages 15-19 who already have children or are currently pregnant.


Aggregationmethod: Sum

IndicatorName: Population ages 00-04, female

License_Type: CC BY-4.0

Longdefinition: Female population between the ages 0 to 4.

Periodicity: Annual

Source: World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2024 Revision.

Topic: Health: Population: Structure


IndicatorName: Population ages 00-04, female (% of female population)

Longdefinition: Female population between the ages 0 to 4 as a percentage of the total female population.

Source: United Nations Population Division. World Population Prospects: 2024 Revision.


IndicatorName: Population ages 00-04, male

Longdefinition: Male population between the ages 0 to 4.


IndicatorName: Population ages 00-04, male (% of male population)

Longdefinition: Male population between the ages 0 to 4 as a percentage of the total male population.


Generalcomments: Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

IndicatorName: Population ages 0-14, female

Longdefinition: Female population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


Aggregationmethod: Weighted average

IndicatorName: Population ages 0-14, female (% of female population)

Longdefinition: Female population between the ages 0 to 14 as a percentage of the total female population. Population is based on the de facto definition of population.


IndicatorName: Population ages 0-14, male

Longdefinition: Male population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 0-14, male (% of male population)

Longdefinition: Male population between the ages 0 to 14 as a percentage of the total male population. Population is based on the de facto definition of population.


IndicatorName: Population ages 0-14, total

Longdefinition: Total population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


Developmentrelevance:
Patterns of development in a country are partly determined by the age composition of its population. Different age groups have different impacts on both the environment and on infrastructure needs.  Therefore the age structure of a population is useful for analyzing resource use and formulating future policy and planning goals  with regards infrastructure and development.

This indicator is used for calculating age dependency ratio (percent of working-age population). The age dependency ratio is the ratio of the sum of the population aged 0-14 and the population aged 65 and above to the population aged 15-64. In many developing countries, the once rapidly growing population group of the under-15 population is shrinking. As a result, high fertility rates, together with declining mortality rates, are now reflected in the larger share of the 65 and older population.

IndicatorName: Population ages 0-14 (% of total population)

Longdefinition: Population between the ages 0 to 14 as a percentage of the total population. Population is based on the de facto definition of population.

Statisticalconceptandmethodology:
Age structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source.

Total population is based on the de facto population including all residents regardless of legal status or citizenship. The values shown are midyear estimates. For more information see metadata for total population (SP.POP.TOTL).


IndicatorName: Population ages 05-09, female

Longdefinition: Female population between the ages 5 to 9.


IndicatorName: Population ages 05-09, female (% of female population)

Longdefinition: Female population between the ages 5 to 9 as a percentage of the total female population.


IndicatorName: Population ages 05-09, male

Longdefinition: Male population between the ages 5 to 9.


IndicatorName: Population ages 05-09, male (% of male population)

Longdefinition: Male population between the ages 5 to 9 as a percentage of the total male population.


IndicatorName: Population ages 10-14, female

Longdefinition: Female population between the ages 10 to 14.


IndicatorName: Population ages 10-14, female (% of female population)

Longdefinition: Female population between the ages 10 to 14 as a percentage of the total female population.


IndicatorName: Population ages 10-14, male

Longdefinition: Male population between the ages 10 to 14.


IndicatorName: Population ages 10-14, male (% of male population)

Longdefinition: Male population between the ages 10 to 14 as a percentage of the total male population.


IndicatorName: Population ages 15-19, female

Longdefinition: Female population between the ages 15 to 19.


IndicatorName: Population ages 15-19, female (% of female population)

Longdefinition: Female population between the ages 15 to 19 as a percentage of the total female population.


IndicatorName: Population ages 15-19, male

Longdefinition: Male population between the ages 15 to 19.


IndicatorName: Population ages 15-19, male (% of male population)

Longdefinition: Male population between the ages 15 to 19 as a percentage of the total male population.


IndicatorName: Population ages 15-64, female

Longdefinition: Female population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 15-64, female (% of female population)

Longdefinition: Female population between the ages 15 to 64 as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 15-64, male

Longdefinition: Male population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 15-64, male (% of male population)

Longdefinition: Male population between the ages 15 to 64 as a percentage of the total male population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 15-64, total

Longdefinition: Total population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 15-64 (% of total population)

Longdefinition: Total population between the ages 15 to 64 as a percentage of the total population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 20-24, female

Longdefinition: Female population between the ages 20 to 24.


IndicatorName: Population ages 20-24, female (% of female population)

Longdefinition: Female population between the ages 20 to 24 as a percentage of the total female population.


IndicatorName: Population ages 20-24, male

Longdefinition: Male population between the ages 20 to 24.


IndicatorName: Population ages 20-24, male (% of male population)

Longdefinition: Male population between the ages 20 to 24 as a percentage of the total male population.


IndicatorName: Population ages 25-29, female

Longdefinition: Female population between the ages 25 to 29.


IndicatorName: Population ages 25-29, female (% of female population)

Longdefinition: Female population between the ages 25 to 29 as a percentage of the total female population.


IndicatorName: Population ages 25-29, male

Longdefinition: Male population between the ages 25 to 29.


IndicatorName: Population ages 25-29, male (% of male population)

Longdefinition: Male population between the ages 25 to 29 as a percentage of the total male population.


IndicatorName: Population ages 30-34, female

Longdefinition: Female population between the ages 30 to 34.


IndicatorName: Population ages 30-34, female (% of female population)

Longdefinition: Female population between the ages 30 to 34 as a percentage of the total female population.


IndicatorName: Population ages 30-34, male

Longdefinition: Male population between the ages 30 to 34.


IndicatorName: Population ages 30-34, male (% of male population)

Longdefinition: Male population between the ages 30 to 34 as a percentage of the total male population.


IndicatorName: Population ages 35-39, female

Longdefinition: Female population between the ages 35 to 39.


IndicatorName: Population ages 35-39, female (% of female population)

Longdefinition: Female population between the ages 35 to 39 as a percentage of the total female population.


IndicatorName: Population ages 35-39, male

Longdefinition: Male population between the ages 35 to 39.


IndicatorName: Population ages 35-39, male (% of male population)

Longdefinition: Male population between the ages 35 to 39 as a percentage of the total male population.


IndicatorName: Population ages 40-44, female

Longdefinition: Female population between the ages 40 to 44.


IndicatorName: Population ages 40-44, female (% of female population)

Longdefinition: Female population between the ages 40 to 44 as a percentage of the total female population.


IndicatorName: Population ages 40-44, male

Longdefinition: Male population between the ages 40 to 44.


IndicatorName: Population ages 40-44, male (% of male population)

Longdefinition: Male population between the ages 40 to 44 as a percentage of the total male population.


IndicatorName: Population ages 45-49, female

Longdefinition: Female population between the ages 45 to 49.


IndicatorName: Population ages 45-49, female (% of female population)

Longdefinition: Female population between the ages 45 to 49 as a percentage of the total female population.


IndicatorName: Population ages 45-49, male

Longdefinition: Male population between the ages 45 to 49.


IndicatorName: Population ages 45-49, male (% of male population)

Longdefinition: Male population between the ages 45 to 49 as a percentage of the total male population.


IndicatorName: Population ages 50-54, female

Longdefinition: Female population between the ages 50 to 54.


IndicatorName: Population ages 50-54, female (% of female population)

Longdefinition: Female population between the ages 50 to 54 as a percentage of the total female population.


IndicatorName: Population ages 50-54, male

Longdefinition: Male population between the ages 50 to 54.


IndicatorName: Population ages 50-54, male (% of male population)

Longdefinition: Male population between the ages 50 to 54 as a percentage of the total male population.


IndicatorName: Population ages 55-59, female

Longdefinition: Female population between the ages 55 to 59.


IndicatorName: Population ages 55-59, female (% of female population)

Longdefinition: Female population between the ages 55 to 59 as a percentage of the total female population.


IndicatorName: Population ages 55-59, male

Longdefinition: Male population between the ages 55 to 59.


IndicatorName: Population ages 55-59, male (% of male population)

Longdefinition: Male population between the ages 55 to 59 as a percentage of the total male population.


IndicatorName: Population ages 60-64, female

Longdefinition: Female population between the ages 60 to 64.


IndicatorName: Population ages 60-64, female (% of female population)

Longdefinition: Female population between the ages 60 to 64 as a percentage of the total female population.


IndicatorName: Population ages 60-64, male

Longdefinition: Male population between the ages 60 to 64.


IndicatorName: Population ages 60-64, male (% of male population)

Longdefinition: Male population between the ages 60 to 64 as a percentage of the total male population.


IndicatorName: Population ages 65-69, female

Longdefinition: Female population between the ages 65 to 69.


IndicatorName: Population ages 65-69, female (% of female population)

Longdefinition: Female population between the ages 65 to 69 as a percentage of the total female population.


IndicatorName: Population ages 65-69, male

Longdefinition: Male population between the ages 65 to 69.


IndicatorName: Population ages 65-69, male (% of male population)

Longdefinition: Male population between the ages 65 to 69 as a percentage of the total male population.


IndicatorName: Population ages 65 and above, female

Longdefinition: Female population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 65 and above, female (% of female population)

Longdefinition: Female population 65 years of age or older as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 65 and above, male

Longdefinition: Male population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 65 and above, male (% of male population)

Longdefinition: Male population 65 years of age or older as a percentage of the total male population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 65 and above, total

Longdefinition: Total population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


IndicatorName: Population ages 65 and above (% of total population)

Longdefinition: Population ages 65 and above as a percentage of the total population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Statisticalconceptandmethodology: Age structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source. Total population is based on the de facto population including all residents regardless of legal status or citizenship. The values shown are midyear estimates. For more information see metadata for total population (SP.POP.TOTL).


IndicatorName: Population ages 70-74, female

Longdefinition: Female population between the ages 70 to 74.


IndicatorName: Population ages 70-74, female (% of female population)

Longdefinition: Female population between the ages 70 to 74 as a percentage of the total female population.


IndicatorName: Population ages 70-74, male

Longdefinition: Male population between the ages 70 to 74.


IndicatorName: Population ages 70-74, male (% of male population)

Longdefinition: Male population between the ages 70 to 74 as a percentage of the total male population.


IndicatorName: Population ages 75-79, female

Longdefinition: Female population between the ages 75 to 79.


IndicatorName: Population ages 75-79, female (% of female population)

Longdefinition: Female population between the ages 75 to 79 as a percentage of the total female population.


IndicatorName: Population ages 75-79, male

Longdefinition: Male population between the ages 75 to 79.


IndicatorName: Population ages 75-79, male (% of male population)

Longdefinition: Male population between the ages 75 to 79 as a percentage of the total male population.


IndicatorName: Population ages 80 and above, female

Longdefinition: Female population between the ages 80 and above.


IndicatorName: Population ages 80 and above, female (% of female population)

Longdefinition: Female population between the ages 80 and above as a percentage of the total female population.


IndicatorName: Population ages 80 and above, male

Longdefinition: Male population between the ages 80 and above.


IndicatorName: Population ages 80 and above, male (% of male population)

Longdefinition: Male population between the ages 80 and above as a percentage of the total male population.


IndicatorName: Age population, age 00, female

Longdefinition: Age population, female refers to female population at the specified age level. The geographical areas included in the data are the same as the data source.


IndicatorName: Age population, age 00, male

Longdefinition: Age population, male refers to male population at the specified age level. The geographical areas included in the data are the same as the data source.


IndicatorName: Age population, age 01, female

Shortdefinition: Age population, female refers to female population at the specified age level.


IndicatorName: Age population, age 01, male

Shortdefinition: Age population, male refers to male population at the specified age level.


IndicatorName: Age population, age 02, female


IndicatorName: Age population, age 02, male


IndicatorName: Age population, age 03, female


IndicatorName: Age population, age 03, male


IndicatorName: Age population, age 04, female


IndicatorName: Age population, age 04, male


IndicatorName: Age population, age 05, female


IndicatorName: Age population, age 05, male


IndicatorName: Age population, age 06, female


IndicatorName: Age population, age 06, male


IndicatorName: Age population, age 07, female


IndicatorName: Age population, age 07, male


IndicatorName: Age population, age 08, female


IndicatorName: Age population, age 08, male


IndicatorName: Age population, age 09, female


IndicatorName: Age population, age 09, male


IndicatorName: Age population, age 10, female


IndicatorName: Age population, age 10, male


IndicatorName: Age population, age 11, female


IndicatorName: Age population, age 11, male


IndicatorName: Age population, age 12, female


IndicatorName: Age population, age 12, male


IndicatorName: Age population, age 13, female


IndicatorName: Age population, age 13, male


IndicatorName: Age population, age 14, female


IndicatorName: Age population, age 14, male


IndicatorName: Age population, age 15, female


IndicatorName: Age population, age 15, male


IndicatorName: Age population, age 16, female


IndicatorName: Age population, age 16, male


IndicatorName: Age population, age 17, female


IndicatorName: Age population, age 17, male


IndicatorName: Age population, age 18, female


IndicatorName: Age population, age 18, male


IndicatorName: Age population, age 19, female


IndicatorName: Age population, age 19, male


IndicatorName: Age population, age 20, female


IndicatorName: Age population, age 20, male


IndicatorName: Age population, age 21, female


IndicatorName: Age population, age 21, male


IndicatorName: Age population, age 22, female


IndicatorName: Age population, age 22, male


IndicatorName: Age population, age 23, female


IndicatorName: Age population, age 23, male


IndicatorName: Age population, age 24, female


IndicatorName: Age population, age 24, male


IndicatorName: Age population, age 25, female


IndicatorName: Age population, age 25, male


IndicatorName: Sex ratio at birth (male births per female births)

Longdefinition: Sex ratio at birth refers to male births per female births.


Developmentrelevance: Patterns of development in a country are partly determined by the age composition of its population. Different age groups have different impacts on both the environment and on infrastructure needs.  Therefore the age structure of a population is useful for analyzing resource use and formulating future policy and planning goals  with regards infrastructure and development.

Generalcomments: Relevance to gender indicator: this indicator implies the dependency burden that the working-age population bears in relation to children and the elderly. Many times single or widowed women who are the sole caregiver of a household have a high dependency ratio.

IndicatorName: Age dependency ratio (% of working-age population)

Longdefinition: Age dependency ratio is the ratio of dependents--people younger than 15 or older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.

Source: World Bank staff estimates based on age distributions of United Nations Population Division's World Population Prospects: 2024 Revision.

Statisticalconceptandmethodology:
Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in the population that imply the dependency burden that the working-age population bears in relation to children and the elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.

Age structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects. For more information, see the original source.

Topic: Health: Population: Dynamics


IndicatorName: Age dependency ratio, old (% of working-age population)

Longdefinition: Age dependency ratio, old, is the ratio of older dependents--people older than 64--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.


IndicatorName: Age dependency ratio, young (% of working-age population)

Longdefinition: Age dependency ratio, young, is the ratio of younger dependents--people younger than 15--to the working-age population--those ages 15-64. Data are shown as the proportion of dependents per 100 working-age population.


IndicatorName: Population growth (annual %)

Longdefinition: Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Shortdefinition: Annual population growth rate. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Source: Derived from total population. Population 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:
Total population growth rates are calculated on the assumption that rate of growth is constant between two points in time. The growth rate is computed using the exponential growth formula:

r = ln(pn/p0)/n,

where r is the exponential rate of growth, ln() is the natural logarithm, pn is the end period population, p0 is the beginning period population, and n is the number of years in between. Note that this is not the geometric growth rate used to compute compound growth over discrete periods.

For information on total population from which the growth rates are calculated, see total population (SP.POP.TOTL).


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.


IndicatorName: Population, female

Longdefinition: Female population is based on the de facto definition of population, which counts all female residents regardless of legal status or citizenship.


Developmentrelevance: Females comprise almost one-half of the world population.  Female population relative to male population is a primary demographic indicator, reflecting historical events such as wars and the socio-demographic and ethno-cultural characteristics of the population.

IndicatorName: Population, female (% of total population)

Longdefinition: Female population is the percentage of the population that is female. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Source: World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2024 Revision.

Statisticalconceptandmethodology: Population structure by age and sex in the World Bank's estimates is based on the population structure by age and sex in United Nations Population Division's World Population Prospects. For more information, see the original source.


IndicatorName: Population, male

Longdefinition: Male population is based on the de facto definition of population, which counts all male residents regardless of legal status or citizenship.


IndicatorName: Population, male (% of total population)

Longdefinition: Male population is the percentage of the population that is male. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.


Developmentrelevance: Society typically first acknowledges a child’s existence and identity through birth registration. The right to be recognized as a person before the law is a critical step in ensuring lifelong protection and is a prerequisite for exercising all other rights. A birth certificate, issued following birth registration, is an important identity document for children. Birth registration also serves a statistical purpose. Universal birth registration is an essential part of a system of vital statistics, which tracks the major milestones in a person’s life - from birth to marriage and death. Such data are essential for planning and implementing development policies and programs, particularly in health, education, housing, water and sanitation, employment, agriculture and industrial production. The proportion of children under 5 years of age whose births have been registered with a civil authority is the official indicator for SDG Target 16.9, which sets out to “By 2030, provide legal identity for all, including birth registration”.

Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 16.9.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Completeness of birth registration, female (%)

Limitationsandexceptions:
Data on the prevalence of birth registration is collected mainly through censuses, civil registration systems (CRVS) and household surveys. Civil registration systems that are functioning effectively compile vital statistics that are used to compare the estimated total number of births in a country with the absolute number of registered births during a given period. However, the systematic recording of births in many countries remains a serious challenge. In the absence of reliable administrative data, household surveys have become a key source of data to monitor levels and trends in birth registration. In most low- and middle-income countries, such surveys represent the sole source of this information.

Substantial differences can exist between CRVS coverage and birth registration levels as captured by household surveys. The differences are primarily because data from CRVS typically refer to the percentage of all births that have been registered (often within a specific timeframe) whereas household surveys often represent the percentage of children under age five whose births are registered. The latter (the level of registration among children under 5) is specified in the SDG indicator (16.9).

Longdefinition: Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.

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

Statisticalconceptandmethodology:
Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.

Birth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).


IndicatorName: Completeness of birth registration, male (%)


IndicatorName: Completeness of birth registration, rural (%)


Generalcomments: This is a disaggregated indicator (residence) for Sustainable Development Goal 16.9.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Completeness of birth registration, urban (%)


Generalcomments: This is the Sustainable Development Goal indicator 16.9.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Completeness of birth registration (%)


IndicatorName: Completeness of death registration with cause-of-death information (%)

Longdefinition: Completeness of death registration is the estimated percentage of deaths that are registered with their cause of death information in the vital registration system of a country.

Source: World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).


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

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

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

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

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

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

IndicatorName: Rural population

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

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

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

Longdefinition: Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population. Aggregation of urban and rural population may not add up to total population because of different country coverages.

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

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

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

Topic: Environment: Density & urbanization


IndicatorName: Rural population growth (annual %)

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


IndicatorName: Rural population (% of total population)


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

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

IndicatorName: Urban population growth (annual %)

Limitationsandexceptions:
There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.

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

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

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

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

Statisticalconceptandmethodology:
Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.

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


IndicatorName: Urban population

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

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

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

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

Longdefinition: Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.


IndicatorName: Urban population (% of total population)

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

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

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

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

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


Generalcomments: Unmet need for contraception measures the capacity women have in achieving their desired family size and birth spacing. Many couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects.

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

Longdefinition: Unmet need for contraception is the percentage of fertile, married women of reproductive age who do not want to become pregnant and are not using contraception.

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

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

Many couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects. This indicator excludes women not exposed to the risk of unintended pregnancy because of menopause, infertility, or postpartum anovulation.

Topic: Health: Reproductive health


Developmentrelevance:
Maintaining reliable and secure electricity services while seeking to rapidly decarbonize power systems is a key challenge for countries throughout the world. More and more countries are becoming increasing dependent on reliable and secure electricity supplies to underpin economic growth and community prosperity. This reliance is set to grow as more efficient and less carbon intensive forms of power are developed and deployed to help decarbonize economies.

Energy is necessary for creating the conditions for economic growth. It is impossible to operate a factory, run a shop, grow crops or deliver goods to consumers without using some form of energy. Access to electricity is particularly crucial to human development as electricity is, in practice, indispensable for certain basic activities, such as lighting, refrigeration and the running of household appliances, and cannot easily be replaced by other forms of energy. Individuals' access to electricity is one of the most clear and un-distorted indication of a country's energy poverty status.

Electricity access is increasingly at the forefront of governments' preoccupations, especially in the developing countries. As a consequence, a lot of rural electrification programs and national electrification agencies have been created in these countries to monitor more accurately the needs and the status of rural development and electrification.

Use of energy is important in improving people's standard of living. But electricity generation also can damage the environment. Whether such damage occurs depends largely on how electricity is generated. For example, burning coal releases twice as much carbon dioxide - a major contributor to global warming - as does burning an equivalent amount of natural gas.

IndicatorName: Access to electricity (% of population)

Longdefinition: Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.

Source: World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.

Statisticalconceptandmethodology: Data for access to electricity are collected among different sources: mostly data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Given the low frequency and the regional distribution of some surveys, a number of countries have gaps in available data. To develop the historical evolution and starting point of electrification rates, a simple modeling approach was adopted to fill in the missing data points - around 1990, around 2000, and around 2010. Therefore, a country can have a continuum of zero to three data points. There are 42 countries with zero data point and the weighted regional average was used as an estimate for electrification in each of the data periods. 170 countries have between one and three data points and missing data are estimated by using a model with region, country, and time variables. The model keeps the original observation if data is available for any of the time periods. This modeling approach allowed the estimation of electrification rates for 212 countries over these three time periods (Indicated as "Estimate"). Notation "Assumption" refers to the assumption of universal access in countries classified as developed by the United Nations. Data begins from the year in which the first survey data is available for each country.

Topic: Environment: Energy production & use


Developmentrelevance:
Carbon dioxide (CO2) is naturally occurring gas fixed by photosynthesis into organic matter. A byproduct of fossil fuel combustion and biomass burning, it is also emitted from land use changes and other industrial processes. It is the principal anthropogenic greenhouse gas that affects the Earth's radiative balance. It is the reference gas against which other greenhouse gases are measured, thus having a Global Warming Potential of 1.

Burning of carbon-based fuels since the industrial revolution has rapidly increased concentrations of atmospheric carbon dioxide, increasing the rate of global warming and causing anthropogenic climate change. It is also a major source of ocean acidification since it dissolves in water to form carbonic acid.

The addition of man-made greenhouse gases to the Atmosphere disturbs the earth's radiative balance. This is leading to an increase in the earth's surface temperature and to related effects on climate, sea level rise and world agriculture. Emissions of CO2 are from burning oil, coal and gas for energy use, burning wood and waste materials, and from industrial processes such as cement production.

The carbon dioxide emissions of a country are only an indicator of one greenhouse gas. For a more complete idea of how a country influences climate change, gases such as methane and nitrous oxide should be taken into account. This is particularly important in agricultural economies.

Emission intensity is the average emission rate of a given pollutant from a given source relative to the intensity of a specific activity. Emission intensities are also used to compare the environmental impact of different fuels or activities. The related terms - emission factor and carbon intensity - are often used interchangeably.

The environmental effects of carbon dioxide are of significant interest. Carbon dioxide (CO2) makes up the largest share of the greenhouse gases contributing to global warming and climate change. Converting all other greenhouse gases (methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6)) to carbon dioxide (or CO2) equivalents makes it possible to compare them and to determine their individual and total contributions to global warming. The Kyoto Protocol, an environmental agreement adopted in 1997 by many of the parties to the United Nations Framework Convention on Climate Change (UNFCCC), is working towards curbing CO2 emissions globally.

IndicatorName: CO2 emissions (metric tons per capita)

Limitationsandexceptions:
The U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) calculates annual anthropogenic emissions from data on fossil fuel consumption (from the United Nations Statistics Division's World Energy Data Set) and world cement manufacturing (from the U.S. Department of Interior's Geological Survey, USGS 2011). Although estimates of global carbon dioxide emissions are probably accurate within 10 percent (as calculated from global average fuel chemistry and use), country estimates may have larger error bounds. Trends estimated from a consistent time series tend to be more accurate than individual values.

Each year the CDIAC recalculates the entire time series since 1949, incorporating recent findings and corrections. Estimates exclude fuels supplied to ships and aircraft in international transport because of the difficulty of apportioning the fuels among benefiting countries.

Longdefinition: Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.

Source: Data for up to 1990 are sourced from Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, Tennessee, United States. Data from 1990 are CAIT data: Climate Watch. 2020. GHG Emissions. Washington, DC: World Resources Institute. Available at: https://www.climatewatchdata.org/ghg-emissions. See SP.POP.TOTL for the denominator's source.

Statisticalconceptandmethodology: Carbon dioxide emissions, largely by-products of energy production and use, account for the largest share of greenhouse gases, which are associated with global warming. Anthropogenic carbon dioxide emissions result primarily from fossil fuel combustion and cement manufacturing. In combustion different fossil fuels release different amounts of carbon dioxide for the same level of energy use: oil releases about 50 percent more carbon dioxide than natural gas, and coal releases about twice as much. Cement manufacturing releases about half a metric ton of carbon dioxide for each metric ton of cement produced. Data for carbon dioxide emissions include gases from the burning of fossil fuels and cement manufacture, but excludes emissions from land use such as deforestation.

Topic: Environment: Emissions


Developmentrelevance: Air pollution places a major burden on world health. In many places, including cities but also in rural areas, exposure to air pollution is the main environmental threat to health, responsible for 6.5 million deaths per year, about one every 5 seconds. Around 40 percent of the world’s people rely on household burning of wood, charcoal, dung, crop waste, or coal to meet basic energy needs. Cooking and heating with solid fuels create harmful smoke and particles that fill homes and the surrounding environment. Household air pollution from cooking and heating with solid fuels is responsible for 2.9 million deaths a year. Long-term exposure to high levels of fine particles in the air contributes to a range of health effects, including respiratory diseases, lung cancer, and heart disease, resulting in 4.2 million deaths annually. Not only does exposure to air pollution affect the health of the world’s people, it also carries huge economic costs and represents a drag on development, particularly for low and middle income countries and vulnerable segments of the population such as children and the elderly.

IndicatorName: PM2.5 air pollution, population exposed to levels exceeding WHO guideline value (% of total)

Limitationsandexceptions: Pollutant concentrations are sensitive to local conditions, and even monitoring sites in the same city may register different levels. Direct monitoring of PM2.5 is still rare in most parts of the world, and measurement protocols and standards are not the same for all countries. These data should be considered only a general indication of air quality, intended to inform cross-country comparisons of the health risks due to particulate matter pollution. The guideline set by the World Health Organization (WHO) for PM2.5 is that annual mean concentrations should not exceed 10 micrograms per cubic meter, representing the lower range over which adverse health effects have been observed. The WHO has also recommended guideline values for emissions of PM2.5 from burning fuels in households.

Longdefinition: Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

Source: Brauer, M. et al. 2017, for the Global Burden of Disease Study 2017.

Statisticalconceptandmethodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, "Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors," Environ. Sci. Technol 50, no. 7 (2016): 3762–3772; GBD 2017 Risk Factors Collaborators, "Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017," Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Prüss-Üstün A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.


Developmentrelevance:
Deforestation is the removal of a forest or stand of trees where the land is thereafter is converted to a non-forest use, such as farms, ranches, or urban use. As threats to biodiversity mount, the international community is increasingly focusing on conserving diversity. Deforestation is a major cause of loss of biodiversity, and habitat conservation is vital for stemming this loss. Conservation efforts have focused on protecting areas of high biodiversity.

Destruction of rainforests remains a significant environmental problem - up to 90 percent of West Africa's coastal rainforests have disappeared since 1900. Much of what remains of the world's rainforests is in the Amazon basin, where the Amazon Rainforest covers approximately 4 million square kilometers. Large-scale planting of trees is significantly reducing the net loss of forest area globally, and afforestation and natural expansion of forests in some countries and regions have reduced the net loss of forest area significantly at the global level.

Forests cover more than 31 percent of total land area of the world; the world's total forest area is just over 4 billion hectares. On a global average, more than one-third of all forest is primary forest, i.e. forest of native species where there are no clearly visible indications of human activities and the ecological processes have not been significantly disturbed. Primary forests, in particular tropical moist forests, include the most species-rich, diverse terrestrial ecosystems.

National parks, game reserves, wilderness areas and other legally established protected areas cover more than 10 percent of the total forest area in most countries and regions. FAO estimates that around 10 million people are employed in forest management and conservation - but many more are directly dependent on forests for their livelihoods. Also, 80 about percent of the world's forests are publicly owned, but ownership and management of forests by communities, individuals and private companies is on the rise.

Close to 1.2 billion hectares of forest are managed primarily for the production of wood and non-wood forest products. An additional 25 percent of forest area is designated for multiple uses - in most cases including the production of wood and non-wood forest products. The area designated primarily for productive purposes has decreased by more than 50 million hectares since 1990 as forests have been designated for other purposes.

Generalcomments: This is a period growth rate indicator for online table use only.

IndicatorName: Annual deforestation (% of change)

Limitationsandexceptions:
The national figures in the database are reported by the countries themselves, thus eliminating any discrepancies between global and national figures. The reporting format ensures that countries provide the full reference for original data sources as well as national definitions and terminology. Separate sections in the reporting format (country reports) deal with the analysis of data; calibration of data to the official land area as held by FAO; and reclassification of data to the classes used in FAO's Global Forest Resources Assessments.

FAO has been collecting and analyzing data on forest area since 1946. This is done at intervals of 5-10 years as part of the Global Forest Resources Assessment (FRA). FAO reports data for 229 countries and territories; for the remaining 56 small island states and territories where no information is provided, a report is prepared by FAO using existing information and a literature search. The data are aggregated at sub-regional, regional and global levels by the FRA team at FAO, and estimates are produced by straight summation.

The lag between the reference year and the actual production of data series as well as the frequency of data production varies between countries. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.

Longdefinition: Average annual deforestation refers to the permanent conversion of natural forest area to other uses, including shifting cultivation, permanent agriculture, ranching, settlements, and infrastructure development. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.

Source: Food and Agriculture Organization, Global Forest Resources Assessment.

Statisticalconceptandmethodology:
Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.

Data includes areas with bamboo and palms; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters; plantations primarily used for forestry or protective purposes, such as rubber-wood plantations and cork oak stands. Data excludes tree stands in agricultural production systems, such as fruit plantations and agroforestry systems. Forest area also excludes trees in urban parks and gardens. The proportion of forest area to total land area is calculated and changes in the proportion are computed to identify trends.

The Food and Agricultural Organization (FAO) provides detail information on forest cover, and adjusted estimates of forest cover. The current survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, this indictor data does not reflect that breakdown. Thus the deforestation data may underestimate the rate at which natural forest is disappearing in some countries.

Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.

Topic: Environment: Land use


Developmentrelevance:
While some countries have an abundant supply of fresh water, others do not have as much. UN estimates that many areas of the world are already experiencing stress on water availability. Due to the accelerated pace of population growth and an increase in the amount of water a single person uses, it is expected that this situation will continue to get worse. The ability of developing countries to make more water available for domestic, agricultural, industrial and environmental uses will depend on better management of water resources and more cross-sectorial planning and integration. According to World Water Council, by 2020, water use is expected to increase by 40 percent, and 17 percent more water will be required for food production to meet the needs of the growing population. The three major factors causing increasing water demand over the past century are population growth, industrial development and the expansion of irrigated agriculture.

There is now ample evidence that increased hydrologic variability and change in climate has and will continue to have a profound impact on the water sector through the hydrologic cycle, water availability, water demand, and water allocation at the global, regional, basin, and local levels. Properly managed water resources are a critical component of growth, poverty reduction and equity. The livelihoods of the poorest are critically associated with access to water services. A shortage of water in the future would be detrimental to the human population as it would affect everything from sanitation, to overall health and the production of grain.

Freshwater use by continents is partly based on several socio-economic development factors, including population, physiography, and climatic characteristics. It is estimated that in the coming decades the most intensive growth of water withdrawal is expected to occur in Africa and South America (increasing by 1.5-1.6 times), while the smallest growth will take place in Europe and North America (1.2 times).

IndicatorName: Annual freshwater withdrawals, total (% of internal resources)

Limitationsandexceptions:
A common perception is that most of the available freshwater resources are visible (on the surfaces of lakes, reservoirs and rivers). However, this visible water represents only a tiny fraction of global freshwater resources, as most of it is stored in aquifers, with the largest stocks stored in solid form in the Antarctic and in Greenland's ice cap.

The data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently, they may hide significant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger countries and countries with greater rainfall.

Caution should also be used in comparing data on annual freshwater withdrawals, which are subject to variations in collection and estimation methods. In addition, inflows and outflows are estimated at different times and at different levels of quality and precision, requiring caution in interpreting the data, particularly for water-short countries, notably in the Middle East and North Africa.

The data are based on surveys and estimates provided by governments to the Joint Monitoring Programme of the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF). The coverage rates are based on information from service users on actual household use rather than on information from service providers, which may include nonfunctioning systems.

Longdefinition: Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.

Source: Food and Agriculture Organization, AQUASTAT data.

Statisticalconceptandmethodology: Annual freshwater withdrawals are total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.

Topic: Environment: Freshwater


Aggregationmethod: Unweighted average

Developmentrelevance: Statistical Capacity is a nation’s ability to collect, analyze, and disseminate high-quality data about its population and economy. Quality statistics are essential for all stages of evidence-based decision-making, including: Monitoring social and economic indicators, Allocating political representation and government resources, Guiding private sector investment, as well as Informing the international donor community for program design and policy formulation.

IndicatorName: Overall level of statistical capacity (scale 0 - 100)

Longdefinition: The Statistical Capacity Indicator is a composite score assessing the capacity of a country’s statistical system. It is based on a diagnostic framework assessing the following areas: methodology; data sources; and periodicity and timeliness. Countries are scored against 25 criteria in these areas, using publicly available information and/or country input. The overall Statistical Capacity score is then calculated as a simple average of all three area scores on a scale of 0-100.

Source: World Bank, Bulletin Board on Statistical Capacity (http://bbsc.worldbank.org).

Statisticalconceptandmethodology: The Statistical Capacity Indicator score is calculated as the average of the scores of the 3 dimensions, i.e. Availability, Collection, Practice.

Topic: Public Sector: Policy & institutions


Developmentrelevance:
The LPI measures on-the-ground trade logistics performance, helping national leaders, key policymakers, and private sector traders understand the challenges they and their trading partners face in reducing logistical barriers to international commerce.

As the backbone of international trade, logistics encompasses freight transportation, warehousing, border clearance, payment systems, and many other functions. These functions are performed mostly by private service providers for private traders and owners of goods, but logistics is also important for the public policies of national governments and regional and international organizations. Because global supply chains are so varied and complex, the efficiency of logistics depends on government services, investments, and policies. Building infrastructure, developing a regulatory regime for transport services, and designing and implementing efficient customs clearance procedures are all areas where governments play an important role. The improvements in global logistics over the past two decades have been driven by innovation and a great increase in global trade. While policies and investments that enable good logistics practices help modernize the best-performing countries, logistics still lags in many developing countries. Indeed, the "logistics gap" evident in the first two editions of this report remains.

The tremendous importance of logistics performance for economic growth, diversification, and poverty reduction has long been widely recognized. National governments can facilitate trade through investments in both "hard" and "soft" infrastructure. Countries have improved their logistics performance by implementing strategic and sustained interventions, mobilizing actors across traditional sector silos, and involving the private sector. Logistics is also increasingly important for sustainability. A focus on the environmental impacts of logistics practices was recently included in the LPI.

IndicatorName: Logistics performance index: Overall (1=low to 5=high)

Limitationsandexceptions:
The Logistics Performance Index is an interactive benchmarking tool created to help countries identify the challenges and opportunities they face in their performance on trade logistics and what they can do to improve their performance. Feedback from operators is supplemented with quantitative data on the performance of key components of the logistics chain in the country of work. Thus, the LPI consists of both qualitative and quantitative measures.

In addition, despite being the most comprehensive data source for country logistics and trade facilitation, the LPI has two important limitations. First, the experience of international freight forwarders might not represent the broader logistics environment in poor countries, which often rely on traditional operators. And the international and traditional operators might differ in their interactions with government agencies - and in their service levels. Second, for landlocked countries and small-island states, the LPI might reflect access problems outside the country assessed, such as transit difficulties. The low rating of a landlocked country might not adequately reflect its trade facilitation efforts, which depend on the workings of complex international transit systems. Landlocked countries cannot eliminate transit inefficiencies with domestic reforms.

Longdefinition: Logistics Performance Index overall score reflects perceptions of a country's logistics based on efficiency of customs clearance process, quality of trade- and transport-related infrastructure, ease of arranging competitively priced shipments, quality of logistics services, ability to track and trace consignments, and frequency with which shipments reach the consignee within the scheduled time. The index ranges from 1 to 5, with a higher score representing better performance. Data are from Logistics Performance Index surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. 2009 round of surveys covered more than 5,000 country assessments by nearly 1,000 international freight forwarders. Respondents evaluate eight markets on six core dimensions on a scale from 1 (worst) to 5 (best). The markets are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. Scores for the six areas are averaged across all respondents and aggregated to a single score using principal components analysis. Details of the survey methodology and index construction methodology are in Arvis and others' Connecting to Compete 2010: Trade Logistics in the Global Economy (2010).

Source: World Bank and Turku School of Economics, Logistic Performance Index Surveys. Data are available online at : http://www.worldbank.org/lpi. Summary results are published in Arvis and others' Connecting to Compete: Trade Logistics in the Global Economy, The Logistics Performance Index and Its Indicators report.

Statisticalconceptandmethodology:
The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.

The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and at the main express carriers. The 2012 LPI data are based on the 2011 survey, which was administered to nearly 1,000 respondents at international logistics companies in 143 countries (domestic performance indicators). The international LPI covers 155 countries. The LPI assesses both large companies and small and medium enterprises. Most of the responses are from small and medium enterprises, with large companies (those with 250 employees or more) accounting for roughly 18 percent of responses. The respondents include groups of professionals who are directly involved in day-today operations, from company headquarters and from country offices such as senior executives, area or country managers, and department managers. Many of the respondents are at corporate or regional headquarters or at country branch offices. The rest are at local branch offices or independent firms. The majority of respondents are involved in providing most logistics services as their main line of work such as warehousing and distribution, customer-tailored logistics solutions, courier services, bulk or break bulk cargo transport, and less-than-full container, full-container, or full-trailer load transport.

Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5. The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets. The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.

The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores on questions 10-15, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.

Topic: Private Sector & Trade: Trade facilitation


IndicatorName: GDP per capita growth (annual %)

Longdefinition: Annual percentage growth rate of GDP per capita based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.

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

Statisticalconceptandmethodology: For more information, see the metadata for constant U.S. dollar GDP (NY.GDP.MKTP.KD) and total population (SP.POP.TOTL).

Topic: Economic Policy & Debt: National accounts: Growth rates


Generalcomments: For aggregate data, each economy is classified based on the classification of World Bank Group's fiscal year 2021 (July 1, 2020-June 30, 2021).

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

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

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

Longdefinition: Lower secondary education completion rate is measured as the gross intake ratio to the last grade of lower secondary education (general and pre-vocational). It is calculated as the number of new entrants in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.

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

Statisticalconceptandmethodology:
Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.

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

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

Topic: Education: Outcomes


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


IndicatorName: Gross enrollment rate (%), lower secondary, total

Longdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown.

Topic: Education: Participation


IndicatorName: Gross enrollment rate (%), lower secondary, female

Shortdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown.


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

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

Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

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

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

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

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.

Topic: Health: Mortality


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

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

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

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

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

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

Longdefinition: The percentage of people using at least basic water services.  This indicator encompasses both people using basic water services as well as those using safely managed water services.  Basic drinking water services is defined as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip.  Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.

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

Statisticalconceptandmethodology: Data on drinking water, sanitation and hygiene are produced by the Joint Monitoring Programme of the World Health Organization (WHO) and United Nations Children's Fund (UNICEF) based on administrative sources, national censuses and nationally representative household surveys.  WHO/UNICEF defines a basic drinking water service as drinking water from an improved source, provided collection time is not more than 30 minutes for a round trip.  Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.

Topic: Health: Disease prevention


Developmentrelevance: Despite the existence of effective medications and treatment, HIV/AIDS is still a leading cause of death and public health threat in the world.  Low and middle income countries continue to bear a disproportionate share of the global burden of HIV/AIDS. The incidence rate provides a measure of progress toward preventing onward transmission of HIV. Also, the identification of newly infected persons will allow for interventions to reduce the risk of HIV transmission.

Generalcomments: This is the Sustainable Development Goal indicator 3.3.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Incidence of HIV, ages 15-49 (per 1,000 uninfected population ages 15-49)

Longdefinition: Number of new HIV infections among uninfected populations ages 15-49 expressed per 1,000 uninfected population in the year before the period.

Source: UNAIDS estimates.

Statisticalconceptandmethodology: Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used (the Spectrum software). The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.

Topic: Health: Risk factors