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

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

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


Aggregationmethod: Weighted average

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

License_Type: CC BY-4.0

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

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

Periodicity: Annual

Source: UNAIDS estimates.

Statisticalconceptandmethodology:
Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS.

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

Topic: Health: Risk factors


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 indicator is related to Sustainable Development Goal 3.3.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Adults (ages 15-49) newly infected with HIV

Longdefinition: Number of adults (ages 15-49) newly infected with HIV.


IndicatorName: Children (ages 0-14) newly infected with HIV

Longdefinition: Number of children (ages 0-14) newly infected with HIV.


Generalcomments: This is an age-disaggregated indicator for Sustainable Development Goal 3.3.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Incidence of HIV, ages 50+ (per 1,000 uninfected population ages 50+)

Longdefinition: Number of new HIV infections among uninfected populations ages 50+ expressed per 1,000 uninfected population ages 50+ in the year before the period.

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.


IndicatorName: Adults (ages 15+) and children (ages 0-14) newly infected with HIV

Longdefinition: Number of adults (ages 15+) and children (ages 0-14) newly infected with HIV.


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

IndicatorName: Incidence of HIV, all (per 1,000 uninfected population)

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


IndicatorName: Young people (ages 15-24) newly infected with HIV

Longdefinition: Number of young people (ages 15-24) newly infected with HIV.


IndicatorName: Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24)

Longdefinition: Number of new HIV infections among uninfected populations ages 15-24 expressed per 1,000 uninfected population ages 15-24 in the year before the period.


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.


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

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

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

Topic: Health: Disease prevention


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

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


IndicatorName: Children orphaned by HIV/AIDS

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


IndicatorName: Antiretroviral therapy coverage for PMTCT (% of pregnant women living with HIV)

Longdefinition: Percentage of pregnant women with HIV who receive antiretroviral medicine for prevention of mother-to-child transmission (PMTCT).


IndicatorName: Adults (ages 15+) and children (0-14 years) living with HIV

Longdefinition: Adults and children living with HIV refers to the number of people ages 0-49 (adult ages 15-49 and children ages 0-14) who are infected with HIV.


Developmentrelevance:
Hypertension significantly increases the risk of heart, brain, and kidney diseases and is one of the leading causes of death and disease worldwide. While it can be easily detected by measuring blood pressure and can often be treated effectively with medications at low cost, the number of people with hypertension has increased for the past decades.  Many people with hypertension are not aware of their condition or are not receiving the treatment that they need.

The WHO points out that the burden of hypertension has shifted from high-income countries to low- and middle-income countries. The prevalence rate of hypertension has decreased in high-income countries, while it has increased in many low- or middle-income countries.

IndicatorName: Prevalence of hypertension, female (% of female adults ages 30-79)

Longdefinition: Prevalence of hypertension, female, is the percentage of female adults ages 30-79 with hypertension (defined as having systolic blood pressure =140 mmHg, diastolic blood pressure =90 mmHg, or taking medication for hypertension).	The data is age-standardized.

Source: World Health Organization's Global Health Observatory Data Repository

Statisticalconceptandmethodology: Based on the population-representative studies with measurement of blood pressure and data on blood pressure treatment, a Bayesian hierarchical model was used to estimate the prevalence of hypertension and the proportion of people who were taking medication for hypertension.


IndicatorName: Prevalence of hypertension, male (% of male adults ages 30-79)

Longdefinition: Prevalence of hypertension, male, is the percentage of male adults ages 30-79 with hypertension (defined as having systolic blood pressure =140 mmHg, diastolic blood pressure =90 mmHg, or taking medication for hypertension).	The data is age-standardized.


IndicatorName: Prevalence of hypertension (% of adults ages 30-79)

Longdefinition: Prevalence of hypertension is the percentage of adults ages 30-79 with hypertension (defined as having systolic blood pressure =140 mmHg, diastolic blood pressure =90 mmHg, or taking medication for hypertension).	The data is age-standardized.


IndicatorName: Treatment for hypertension, female (% of female adults ages 30-79 with hypertension)

Longdefinition: Treatment for hypertension is the percentage of adults ages 30-79 with hypertension who were taking medicine for hypertension.  Hypertension is defined as having systolic blood pressure =140 mmHg, diastolic blood pressure =90 mmHg, or taking medication for hypertension.


IndicatorName: Treatment for hypertension, male (% of male adults ages 30-79 with hypertension)

Longdefinition: Treatment for hypertension, male, is the percentage of adults ages 30-79 with hypertension who were taking medicine for hypertension.  Hypertension is defined as having systolic blood pressure =140 mmHg, diastolic blood pressure =90 mmHg, or taking medication for hypertension.


IndicatorName: Treatment for hypertension (% of adults ages 30-79 with hypertension)


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

IndicatorName: Immunization, HepB3 (% of one-year-old children)

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

Longdefinition: Child immunization rate, hepatitis B is the percentage of children ages 12-23 months who received hepatitis B vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized after three doses.

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

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

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


IndicatorName: Immunization, Hib3 (% of children ages 12-23 months)

Longdefinition: Child immunization, Hib3, measures the percentage of children ages 12-23 months who received Hib3 vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized against Hib3 after receiving three doses of Haemophilus influenzae type b vaccine.


IndicatorName: Immunization, BCG (% of one-year-old children)

Longdefinition: Child immunization rate, BCG is the percentage of children ages 12-23 months who received vaccinations before 12 months or at any time before the survey for BCG. A child is considered adequately immunized after one dose.


Generalcomments: This is the Sustainable Development Goal indicator 3.b.1 [https://unstats.un.org/sdgs/metadata/].

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

Longdefinition: Child immunization, DPT, measures the percentage of children ages 12-23 months who received DPT vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized against diphtheria, pertussis (or whooping cough), and tetanus (DPT) after receiving three doses of vaccine.


IndicatorName: Immunization, measles second dose (% of children by the nationally recommended age)

Longdefinition: Child immunization, measles second dose, measures the percentage of children who received two dose of measles containing vaccine according to nationally recommended schedule through routine immunization services in a given year.


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

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


IndicatorName: Immunization, Pol3 (% of one-year-old children)

Longdefinition: Child immunization rate, polio, is the percentage of children ages 12-23 months who received polio vaccinations before 12 months or at any time before the survey. A child is considered adequately immunized after three doses.


IndicatorName: Hospital beds (per 1,000 people)

Limitationsandexceptions: Depending on the source and means of monitoring, data may not be exactly comparable across countries. For more information, see the original source.

Longdefinition: Hospital beds include inpatient beds available in public, private, general, and specialized hospitals and rehabilitation centers. In most cases beds for both acute and chronic care are included.

Notesfromoriginalsource: Depending on the source and means of monitoring, data may not be exactly comparable across countries. See listed source for country-specific details.

Source: Data are from the World Health Organization, supplemented by country data.

Statisticalconceptandmethodology:
Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.

Availability and use of health services, such as hospital beds per 1,000 people, reflect both demand- and supply-side factors. In the absence of a consistent definition this is a crude indicator of the extent of physical, financial, and other barriers to health care.

Topic: Health: Health systems


Developmentrelevance: The WHO estimates that at least 2.5 medical staff (physicians, nurses and midwives) per 1,000 people are needed to provide adequate coverage with primary care interventions (WHO, World Health Report 2006).

IndicatorName: Community health workers (per 1,000 people)

Limitationsandexceptions: The WHO compiles data from household and labor force surveys, censuses, and administrative records. Data comparability is limited by differences in definitions and training of medical personnel varies. In addition, human resources tend to be concentrated in urban areas, so that average densities do not provide a full picture of health personnel available to the entire population.

Longdefinition: Community health workers include various types of community health aides, many with country-specific occupational titles such as community health officers, community health-education workers, family health workers, lady health visitors and health extension package workers.

Source: World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.

Statisticalconceptandmethodology:
Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.

Data on health worker (physicians, nurses and midwives, and community health workers) density show the availability of medical personnel.


Generalcomments: This is the Sustainable Development Goal indicator 3.c.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Nurses and midwives (per 1,000 people)

Longdefinition: Nurses and midwives include professional nurses, professional midwives, auxiliary nurses, auxiliary midwives, enrolled nurses, enrolled midwives and other associated personnel, such as dental nurses and primary care nurses.


IndicatorName: Physicians (per 1,000 people)

Longdefinition: Physicians include generalist and specialist medical practitioners.


IndicatorName: Specialist surgical workforce (per 100,000 population)

Longdefinition: Specialist surgical workforce is the number of specialist surgical, anaesthetic, and obstetric (SAO) providers who are working in each country per 100,000 population.

Source: Data collected by the Lancet Commission on Global Surgery (www.lancetglobalsurgery.org); Data collected by WHO Collaborating Centre for Surgery and Public Health at Lund University from various sources including Ministries of Health or equivalent national regulatory bodies, national official entities such as medical councils, Eurostat, OECD, WHO Euro Health For All Database, WHO EURO Technical resources for health Database; BMJ Glob Health.


Generalcomments: This is the Sustainable Development Goal indicator 3.3.3[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Incidence of malaria (per 1,000 population at risk)

Longdefinition: Incidence of malaria is the number of new cases of malaria in a year per 1,000 population at risk.

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


Developmentrelevance: Malaria infection during pregnancy is a serious public health concern. It carries substantial risks for the mother, her fetus and the neonate including anaemia, severe malaria, spontaneous abortion, stillbirth, prematurity, neonatal mortality and low birthweight. Intermittent preventive treatment of malaria in pregnancy is a full therapeutic course of antimalarial medicine given to pregnant women at routine antenatal care visits, regardless of whether the recipient is infected with malaria. IPTp reduces maternal malaria episodes, maternal and fetal anaemia, placental parasitaemia, low birth weight, and neonatal mortality.

IndicatorName: Intermittent preventive treatment (IPT) of malaria in pregnancy (% of pregnant women)

Longdefinition: Percentage of women aged 15 - 49 with a live birth in the recent years preceding the survey who received 3+ doses of sulfadoxine-pyrimethamine (SP/Fansidar), at least one during an antenatal care visit. Intermittent Preventive Treatment (IPT) is preventive treatment with SP/Fansidar during an antenatal care (ANC) visit treatment with a dose of sulfadoxine-pyrimethamine (SP/Fansidar) to pregnant women at each scheduled antenatal visit after the first trimester, but not more frequently than once a month.

Source: UNICEF Global Databases [data.unicef.org], Multiple Indicator Cluster Surveys, Demographic and Health Surveys.


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

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

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

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


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

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

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


Aggregationmethod: Sum

IndicatorName: Number of maternal deaths

Longdefinition: A maternal death refers to the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes.

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

Topic: Health: Reproductive health


Developmentrelevance: The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business.

Generalcomments: For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/).  For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases.

IndicatorName: Length of paid maternity leave (days)

Longdefinition: The indicator represents the duration of paid leave available to mothers.

Notesfromoriginalsource: This indicator is additional to the 35 scored indicators, and associated to the following indicator "Paid leave of at least 14 weeks is available to women (1=yes; 0=no)" (SH.MMR.LEVE.AL).

Source: World Bank: Women, Business and the Law. https://wbl.worldbank.org/

Statisticalconceptandmethodology: Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score.

Topic: Gender: Public life & decision making


IndicatorName: Lifetime risk of maternal death (1 in: rate varies by country)

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

Longdefinition: Life time risk of maternal death is the probability that a 15-year-old female will die eventually from a maternal cause assuming that current levels of fertility and mortality (including maternal mortality) do not change in the future, taking into account competing causes of death.

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

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

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

In countries with a high risk of maternal death, many girls die before reaching reproductive age. Lifetime risk of maternal mortality refers to the probability that a 15-year-old girl will eventually die due to a maternal cause.


IndicatorName: Lifetime risk of maternal death (%)


IndicatorName: Maternal leave benefits (% of wages paid)

Longdefinition: Maternity leave benefits refers to the total percentage of wages covered by all sources during paid maternity leave.

Source: World Bank, Women, Business and the Law.


IndicatorName: Prevalence of anemia among pregnant women (%)

Limitationsandexceptions:
Data should be used with caution because surveys differ in quality, coverage, age group interviewed, and treatment of missing values across countries and over time.

Data on anemia are compiled by the WHO based mainly on nationally representative surveys, which measure hemoglobin in the blood. WHO's hemoglobin thresholds are then used to determine anemia status based on age, sex, and physiological status.

Longdefinition: Prevalence of anemia, pregnant women, is the percentage of pregnant women whose hemoglobin level is less than 110 grams per liter at sea level.

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

Statisticalconceptandmethodology: Anemia is a condition in which the number of red blood cells or their oxygen-carrying capacity is insufficient to meet physiologic needs, which vary by age, sex, altitude, smoking status, and pregnancy status. In its severe form it is associated with fatigue, weakness, dizziness, and drowsiness. Children under age 5 and pregnant women have the highest risk for anemia.

Topic: Health: Nutrition


IndicatorName: Prevalence of syphilis (% of women attending antenatal care)

Longdefinition: Percentage of women attending antenatal care seropositive for syphilis


Generalcomments:
This is the Sustainable Development Goal indicator 3.a.1 [https://unstats.un.org/sdgs/metadata/].

Previous indicator name: Smoking prevalence, total (ages 15+)
The previous indicator excluded smokeless tobacco use, while the current indicator includes. The indicator name and definition were updated in December, 2020.

IndicatorName: Prevalence of current tobacco use (% of adults)

Limitationsandexceptions: Estimates for countries with irregular surveys or many data gaps have large uncertainty ranges, and such results should be interpreted with caution.

Longdefinition: The percentage of the population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), “e-cigars”, “e-hookahs”, JUUL and “e-pipes”. The rates are age-standardized to the WHO Standard Population.

Periodicity: Biennial

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

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

A statistical model based on a Bayesian negative binomial meta-regression is used to model prevalence of current tobacco use for each country, separately for men and women.

The model has two main components: (a) adjusting for missing indicators and age groups, and (b) generating an estimate of trends over time as well as the 95% credible interval around the estimate.
Depending on the completeness/comprehensiveness of survey data from a particular country, the model at times makes use of data from other countries to fill information gaps. When a country has fewer than two nationally representative population-based surveys in different years, no attempt is made to fill data gaps and no estimates are calculated. To fill data gaps, information is “borrowed” from countries in the same UN subregion. The resulting trend lines are used to derive estimates for single years, so that a number can be reported even if the country did not run a survey in that year. In order to make the results comparable between countries, the prevalence rates are age-standardized to the WHO Standard Population. A full description of the method is available as a peer-reviewed article in The Lancet, volume 385, No. 9972, p966–976 (2015).


Generalcomments:
This is the Sustainable Development Goal indicator 3.a.1 [https://unstats.un.org/sdgs/metadata/].

Previous indicator name: Smoking prevalence, females (% of adults)
The previous indicator excluded smokeless tobacco use, while the current indicator includes it. The indicator name and definition were updated in December, 2020.

IndicatorName: Prevalence of current tobacco use, females (% of female adults)

Longdefinition: The percentage of the female population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), “e-cigars”, “e-hookahs”, JUUL and “e-pipes”. The rates are age-standardized to the WHO Standard Population.


Generalcomments:
This is the Sustainable Development Goal indicator 3.a.1 [https://unstats.un.org/sdgs/metadata/].

Previous indicator name: Smoking prevalence, males (% of adults)
The previous indicator excluded smokeless tobacco use, while the current indicator includes it. The indicator name and definition were updated in December, 2020.

IndicatorName: Prevalence of current tobacco use, males (% of male adults)

Longdefinition: The percentage of the male population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), “e-cigars”, “e-hookahs”, JUUL and “e-pipes”. The rates are age-standardized to the WHO Standard Population.

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

Smoking is the most common form of tobacco use and the prevalence of smoking is therefore a good measure of the tobacco epidemic. (Corrao MA, Guindon GE, Sharma N, Shokoohi  DF (eds). Tobacco Control Country Profiles, 2000, American Cancer Society, Atlanta.) Tobacco use causes heart and other vascular diseases and cancers of the lung and other organs. Given the long delay between starting to smoke and the onset of disease, the health impact of smoking will increase rapidly only in the next few decades. The data presented are age-standardized rates for adults ages 15 and older from the WHO.


IndicatorName: Risk of catastrophic expenditure for surgical care (% of people at risk)

Longdefinition: The proportion of population at risk of catastrophic expenditure when surgical care is required. Catastrophic expenditure is defined as direct out of pocket payments for surgical and anaesthesia care exceeding 10% of total income.

Source: The Program in Global Surgery and Social Change (PGSSC) at Harvard Medical School (https://www.pgssc.org/)


IndicatorName: Risk of impoverishing expenditure for surgical care (% of people at risk)

Longdefinition: The proportion of population at risk of impoverishing expenditure when surgical care is required. Impoverishing expenditure is defined as direct out of pocket payments for surgical and anaesthesia care which drive people below a poverty threshold (using a threshold of $2.15 PPP/day).


IndicatorName: Number of surgical procedures (per 100,000 population)

Longdefinition: The number of procedures undertaken in an operating theatre per 100,000 population per year in each country. A procedure is defined as the incision, excision, or manipulation of tissue that needs regional or general anaesthesia, or profound sedation to control pain.

Source: Data from various sources compiled by the Lancet Commission on Global Surgery (www.lancetglobalsurgery.org) and the Center for Health Equity in Surgery and Anesthesia at UCSF Medical Center.


Developmentrelevance: Air pollution is one of the biggest environmental risks to health.  According to the World Health Organization, the combined effects of ambient (outdoor) and household air pollution cause about 7 million premature deaths every year.  Most deaths occur due to increased mortality from stroke, heart disease, chronic obstructive pulmonary disease, lung cancer and acute respiratory infections.  The majority of the burden is borne by populations in low and middle income countries.

Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 3.9.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate attributed to household and ambient air pollution, age-standardized, female (per 100,000 female population)

Limitationsandexceptions: Estimates of the joint effects of air pollution are constrained by limited knowledge on the distribution of the population exposed to both household and ambient air pollution, correlation of exposures at individual level as household air pollution is a contributor to ambient air pollution, and non-linear interactions

Longdefinition: Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized.  Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).

Statisticalconceptandmethodology: Burden of disease (or in the present case attributable mortality) is calculated by first combining information on the increased (or relative) risk of a disease resulting from exposure, with information on how widespread the exposure is in the population (e.g.  the annual mean concentration of particulate matter to which the population is exposed). This allows calculation of the 'population attributable fraction' (PAF), which is the fraction of disease seen in a given population that can be attributed  to the exposure (e.g in this case the annual mean concentration of particulate matter). Applying this fraction to the total burden of disease (e.g. cardiopulmonary disease expressed as deaths or DALYs), gives the total number of deaths or DALYs that results from exposure to that particular risk factor (in the example given above, to ambient air pollution). To estimate the combined effects of risk factors, a joint population attributable fraction is calculated, as described in Ezzati et al (2003).

Topic: Health: Mortality


IndicatorName: Mortality rate attributed to household and ambient air pollution, age-standardized, male (per 100,000 male population)


Generalcomments: This is the Sustainable Development Goal indicator 3.9.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate attributed to household and ambient air pollution, age-standardized (per 100,000 population)


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

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

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

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

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

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


IndicatorName: Pregnant women receiving prenatal care (%)

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


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

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

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


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

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

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

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

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

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

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

Longdefinition: The percentage of people using at least basic sanitation services, that is, improved sanitation facilities that are not shared with other households.  This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services.   Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.

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 basic sanitation facilities as improved sanitation facilities that are not shared with other households.  Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines; ventilated improved pit latrines, compositing toilets or pit latrines with slabs.


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


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


Developmentrelevance: For optimal infant and young child feeding, mothers initiate breastfeeding within one hour of birth, breastfeed exclusively for the first six months, and continue to breastfeed for two years or more while providing nutritionally adequate, safe, and age-appropriate solid, semisolid, and soft foods. Breast milk alone contains all the nutrients, antibodies, hormones, and antioxidants an infant needs to thrive. It protects babies from diarrhea and acute respiratory infections, stimulates their immune systems and response to vaccination, and may confer cognitive benefits.

IndicatorName: Exclusive breastfeeding (% of children under 6 months)

Limitationsandexceptions: Most of the data on breastfeeding are derived from household surveys. For the data that are from household surveys, the year refers to the survey year.

Longdefinition: Exclusive breastfeeding refers to the percentage of children less than six months old who are fed breast milk alone (no other liquids) in the past 24 hours.


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

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

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

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

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

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


Developmentrelevance:
Low birth-weight, which is associated with maternal malnutrition, raises the risk of infant mortality and stunts growth in infancy and childhood. There is also emerging evidence that low-birth-weight babies are more prone to non-communicable diseases such as diabetes and cardiovascular diseases. Low birth-weight can arise as a result of a baby being born too soon or too small for gestational age. Babies born prematurely, who are also small for their gestational age, have the worst prognosis.

In low- and middle-income countries low birth-weight stems primarily from poor maternal health and nutrition. Three factors have the most impact: poor maternal nutritional status before conception, mother's short stature (due mostly to under-nutrition and infections during childhood), and poor nutrition during pregnancy (UNICEF Data, https://data.unicef.org/).

IndicatorName: Low-birthweight babies (% of births)

Longdefinition: Low-birthweight babies are newborns weighing less than 2,500 grams, with the measurement taken within the first hour of life, before significant postnatal weight loss has occurred.

Source: UNICEF-WHO Low birthweight estimates [data.unicef.org]


Developmentrelevance: Diabetes, an important cause of ill health and a risk factor for other diseases in developed countries, is spreading rapidly in developing countries. Highest among the elderly, prevalence rates are rising among younger and productive populations in developing countries. Economic development has led to the spread of Western lifestyles and diet to developing countries, resulting in a substantial increase in diabetes. Without effective prevention and control programs, diabetes will likely continue to increase.

IndicatorName: Diabetes prevalence (% of population ages 20 to 79)

Longdefinition: Diabetes prevalence refers to the percentage of people ages 20-79 who have type 1 or type 2 diabetes. It is calculated by adjusting to a standard population age-structure.

Source: International Diabetes Federation, Diabetes Atlas.


Developmentrelevance: Hygiene is closely correlated with human health.   Target 6.2 of the Sustainable Development Goals recognizes that access to facilities allowing good hygiene and sanitation should be universal, and especially important to women and girls, and those in vulnerable situations.   Of the range of hygiene behaviors considered important for health, hand washing with soap and water is a top priority in all settings, and is considered one of the most cost-effective interventions to prevent diarrheal diseases. The availability of a basic handwashing facility is a prerequisite for basic hygiene facilities on premises,  and is a useful proxy for hygienic behavior.

Generalcomments: This is a disaggregated indicator for Sustainable Development Goal 6.2.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: People with basic handwashing facilities including soap and water, rural (% of rural population)

Limitationsandexceptions: Presence of a handwashing station with soap and water does not guarantee that household members consistently wash hands at key times, but is accepted as the most suitable proxy.  Data on handwashing facilities are available for a growing number of low- and middle-income countries after hygiene questions were standardized in international surveys. However, this type of information is not available from most high-income countries, where access to basic handwashing facilities is assumed to be nearly universal.

Longdefinition: The percentage of people living in households that have a handwashing facility with soap and water available on the premises. Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents.

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 handwashing facility as a device to contain, transport or regulate the flow of water to facilitate handwashing with soap and water in the household.


IndicatorName: People with basic handwashing facilities including soap and water, urban (% of urban population)


Generalcomments: This is the Sustainable Development Goal indicator 6.2.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: People with basic handwashing facilities including soap and water (% of population)


IndicatorName: Infant and young child feeding practices, all 3 IYCF (% children ages 6-23 months)

Longdefinition: Percentage of children age 6-23 months fed in accordance with all three infant and young child feeding (IYCF) practices (food diversity, feeding frequency, and consumption of breast milk or milk)

Source: Demographic and Health Surveys


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

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

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

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

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

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

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

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

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


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

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


Aggregationmethod: Linear mixed-effect model estimates

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

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


IndicatorName: Malaria cases reported

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

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

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


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

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

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

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

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

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

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

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


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

Limitationsandexceptions: Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. The ratios cannot be assumed to provide an exact estimate of maternal mortality. Some of the figures shown were adjusted by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) to enhance reliability, so that they may differ from the published figures from sources such as household surveys.

Longdefinition: Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births.

Source: The country data compiled, adjusted and used in the estimation model by the Maternal Mortality Estimation Inter-Agency Group (MMEIG). The country data were compiled from the following sources:  civil registration and vital statistics; specialized studies on maternal mortality; population based surveys and censuses; other available data sources including data from surveillance sites.

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

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

The national estimates of maternal mortality ratios are based on national surveys, vital registration records, and surveillance data or are derived from community and hospital records.


IndicatorName: People practicing open defecation, rural (% of rural population)

Longdefinition: People practicing open defecation refers to the percentage of the population defecating in the open, such as in fields, forest, bushes, open bodies of water, on beaches, in other open spaces or disposed of with solid waste.


IndicatorName: People practicing open defecation, urban (% of urban population)


IndicatorName: People practicing open defecation (% of population)


Developmentrelevance: Most diarrhea-related deaths are due to dehydration, and many of these deaths can be prevented with the use of oral rehydration salts at home.

IndicatorName: Diarrhea treatment (% of children under 5 receiving oral rehydration and continued feeding)

Limitationsandexceptions: Recommendations for the use of oral rehydration therapy have changed over time based on scientific progress, so it is difficult to accurately compare use rates across countries. Until the current recommended method for home management of diarrhea is adopted and applied in all countries, the data should be used with caution. Also, the prevalence of diarrhea may vary by season. Since country surveys are administered at different times, data comparability is further affected.

Longdefinition: Children with diarrhea who received oral rehydration and continued feeding refer to the percentage of children under age five with diarrhea in the two weeks prior to the survey who received either oral rehydration therapy or increased fluids, with continued feeding.


IndicatorName: Diarrhea treatment (% of children under 5 who received ORS packet)

Longdefinition: Percentage of children under age 5 with diarrhea in the two weeks preceding the survey who received oral rehydration salts (ORS packets or pre-packaged ORS fluids).


IndicatorName: Prevalence of overweight, female (% of female adults)

Longdefinition: Prevalence of overweight female adults is the percentage of females ages 18 and over whose Body Mass Index (BMI) is more than 25 kg/m2. Body Mass Index (BMI) is a simple index of weight-for-height, or the weight in kilograms divided by the square of the height in meters.


IndicatorName: Prevalence of overweight, male (% of male adults)

Longdefinition: Prevalence of overweight male adults is the percentage of males ages 18 and over whose Body Mass Index (BMI) is more than 25 kg/m2. Body Mass Index (BMI) is a simple index of weight-for-height, or the weight in kilograms divided by the square of the height in meters.


IndicatorName: Prevalence of overweight (% of adults)

Longdefinition: Prevalence of overweight adults is the percentage of adults ages 18 and over whose Body Mass Index (BMI) is more than 25 kg/m2. Body Mass Index (BMI) is a simple index of weight-for-height, or the weight in kilograms divided by the square of the height in meters.


Generalcomments: Estimates of overweight children are from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues.

IndicatorName: Prevalence of overweight, weight for height, female (% of children under 5)

Longdefinition: Prevalence of overweight, female, is the percentage of girls under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.


IndicatorName: Prevalence of overweight, weight for height, male (% of children under 5)

Longdefinition: Prevalence of overweight, male, is the percentage of boys under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.


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

Derivationmethod:
National estimates from primary sources (e.g., from household surveys) used to generate the JME global estimates are based on standardized methodology using the WHO Child Growth Standards as described in Recommendations for data collection, analysis and reporting on anthropometric indicators in children under 5 years old and WHO Anthro Survey Analyser (WHO, 2019). The JME global estimates are generated using smoothing techniques and covariates applied to quality-assured national data to derive trends and up-to-date estimates. Worldwide and regional estimates are derived as the respective country averages weighted by the countries’ under-five population estimates (UNPD-WPP latest available edition) using annual JME global estimates for 205
Countries and areas.

Generalcomments:
Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues.

Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.

IndicatorName: Prevalence of overweight (modeled estimate, % of children under 5)

Limitationsandexceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). The JME global estimates for overweight take into account estimates of sampling error around survey estimates. While non-sampling error cannot be accounted for or reviewed in full, when available, a data quality review of weight, height and age measurements from household surveys supports compilation of a time series that is comparable across countries and over time.

Longdefinition: Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's 2006 Child Growth Standards.

Otherweblinks:
McLain AC, Frongillo EA, Feng J, Borghi E. Prediction intervals for penalized longitudinal models with multisource summary measures: An application to childhood malnutrition. Stat Med. 2019 Mar 15;38(6):1002-1012. doi: 10.1002/sim.8024. Epub 2018 Nov 14. PMID: 30430613.

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

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

Periodicity: Every two years

Source: UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).


Aggregationmethod: See SH.STA.OWGH.ME.ZS for aggregation

IndicatorName: Prevalence of overweight, weight for height (% of children under 5)


IndicatorName: Postnatal care coverage (% mothers)

Longdefinition: Percentage of women with a postnatal checkup in the first two days after birth


Developmentrelevance: Mortality rates due to unintentional poisoning remains relatively high in low income countries.  This indicator implicates inadequate management of hazardous chemicals and pollution, and of the effectiveness of a country’s health system.

Generalcomments: This is the Sustainable Development Goal indicator 3.9.3[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate attributed to unintentional poisoning (per 100,000 population)

Limitationsandexceptions: Some countries do not have death registration data or sample registration systems.  The estimates on this indicator need to be completed with other type of information for these countries.

Longdefinition:
Mortality rate attributed to unintentional poisonings is the number of deaths from unintentional poisonings in a year per 100,000 population.  Unintentional poisoning can
be caused by household chemicals, pesticides, kerosene, carbon monoxide and medicines, or can be the result of environmental contamination or occupational chemical exposure.


Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 3.9.3[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate attributed to unintentional poisoning, female (per 100,000 female population)

Longdefinition: Mortality rate attributed to unintentional poisonings is the number of female deaths from unintentional poisonings in a year per 100,000 female population.  Unintentional poisoning can be caused by household chemicals, pesticides, kerosene, carbon monoxide and medicines, or can be the result of environmental contamination or occupational chemical exposure.


IndicatorName: Mortality rate attributed to unintentional poisoning, male (per 100,000 male population)

Longdefinition:
Mortality rate attributed to unintentional poisonings is the number of male deaths from unintentional poisonings in a year per 100,000 male population. Unintentional poisoning can
be caused by household chemicals, pesticides, kerosene, carbon monoxide and medicines, or can be the result of environmental contamination or occupational chemical exposure.


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

This is a disaggregated indicator for Sustainable Development Goal 6.2.1 [https://unstats.un.org/sdgs/metadata/].

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

Limitationsandexceptions: There are three main ways to meet the criteria for having a safely managed sanitation service (People should use improved sanitation facilities that are not shared with other households, and the excreta produced should either be: treated and disposed of in situ; stored temporality and then emptied, transported and treated off-site, or transported through a sewer with wastewater and then treated off-site).  Many countries lack information on either wastewater treatment or the management of on-site sanitation. A national estimate is produced if information is available for the dominant type of sanitation system.  If no information is available, it is assumed that 50 percent is safely managed.  Regional and income group estimates are made when data are available for at least 30 percent of the population.

Longdefinition: The percentage of people using improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite. Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.

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 safely managed sanitation facilities as improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite.  Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.


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


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

This is the Sustainable Development Goal indicator 6.2.1 [https://unstats.un.org/sdgs/metadata/].

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


IndicatorName: Prevalence of stunting, height for age, female (% of children under 5)

Longdefinition: Prevalence of stunting, female, is the percentage of girls under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.


IndicatorName: Prevalence of stunting, height for age, male (% of children under 5)

Longdefinition: Prevalence of stunting, male, is the percentage of boys under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.


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

Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.

IndicatorName: Prevalence of stunting, height for age (modeled estimate, % of children under 5)

Longdefinition: Prevalence of stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.


Aggregationmethod: See SH.STA.STNT.ME.ZS for aggregation

IndicatorName: Prevalence of stunting, height for age (% of children under 5)


Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 3.4.2[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Suicide mortality rate, female (per 100,000 female population)

Longdefinition: Suicide mortality rate is the number of suicide deaths in a year per 100,000 population. Crude suicide rate (not age-adjusted).


IndicatorName: Suicide mortality rate, male (per 100,000 male population)


Generalcomments: This is the Sustainable Development Goal indicator 3.4.2[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Suicide mortality rate (per 100,000 population)


Developmentrelevance: Road traffic injuries and deaths is a major global public health problem. Road traffic crashes are currently the leading cause of death for children and young adults in the world.  There is a strong association between the risk of road traffic death and the income level of countries.  The burden of road traffic deaths is disproportionately high among low- and middle-income countries.

Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 3.6.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality caused by road traffic injury, female (per 100,000 female population)

Longdefinition: Mortality caused by road traffic injury is estimated road traffic fatal injury deaths per 100,000 population.


IndicatorName: Mortality caused by road traffic injury, male (per 100,000 male population)


Generalcomments: This is the Sustainable Development Goal indicator 3.6.1 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality caused by road traffic injury (per 100,000 population)


Developmentrelevance: Unsafe drinking water, unsafe sanitation and lack of hygiene are important causes of death.  Most diarrheal deaths in the world are caused by unsafe water, sanitation or hygiene.  According to the World Health Organization, in addition to diarrea, the following diseases could be prevented if adequate WASH services are provided: malnutrition, intestinal nematode infections, lymphatic filariasis, trachoma, schistosomiasis and malaria.

Generalcomments: This is a sex-disaggregated indicator for Sustainable Development Goal 3.9.2 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene, female (per 100,000 female population)

Longdefinition: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.


IndicatorName: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene, male (per 100,000 male population)


Generalcomments: This is the Sustainable Development Goal indicator 3.9.2[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene (per 100,000 population)


IndicatorName: Prevalence of wasting, weight for height, female (% of children under 5)

Limitationsandexceptions: Survey estimates come with levels of uncertainty due to both sampling error and non-sampling error (e.g., measurement technical error, recording error etc.,). None of the two sources of errors have been fully taken into account for deriving estimates neither at country nor at regional or worldwide levels. Surveys are carried out in a specific period of the year, usually over a few months. However, this indicator can be affected by seasonality, factors related to food availability (e.g., pre-harvest periods), disease (e.g.,rainy season and diarrhoea, malaria, etc.), and natural disasters and conflicts. Hence, country-year estimates may not necessarily be comparable over time. Consequently, only latest estimates are provided.

Longdefinition: Prevalence of wasting, female, is the proportion of girls under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59 months.


IndicatorName: Prevalence of wasting, weight for height, male (% of children under 5)

Longdefinition: Prevalence of wasting, male, is the proportion of boys under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59 months.


IndicatorName: Prevalence of wasting, weight for height (% of children under 5)

Longdefinition: Prevalence of wasting is the proportion of children under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59 months.


IndicatorName: Prevalence of severe wasting, weight for height, female (% of children under 5)

Longdefinition: Prevalence of severe wasting, female, is the proportion of girls under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59 months.


IndicatorName: Prevalence of severe wasting, weight for height, male (% of children under 5)

Longdefinition: Prevalence of severe wasting, male, is the proportion of boys under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59 months.


IndicatorName: Prevalence of severe wasting, weight for height (% of children under 5)

Longdefinition: Prevalence of severe wasting is the proportion of children under age 5 whose weight for height is more than three standard deviations below the median for the international reference population ages 0-59 months.


Generalcomments: Aggregate data by groups are computed based on the groupings for the World Bank fiscal year in which the data was released by the World Health Organization.

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

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

Source: World Health Organization, Global Tuberculosis Report.

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


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

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

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

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


Generalcomments:
Aggregate data by groups are computed based on the groupings for the World Bank fiscal year in which the data was released by the World Health Organization.

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

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

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

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

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

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


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

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