Developmentrelevance: Violence against women is an obstacle to the achievement of the objectives of equality, development and peace. It both violates and impairs or nullifies the enjoyment by women of their human rights and fundamental freedoms. Tolerance and experience of domestic violence are significant barriers to the empowerment of women and it has a negative health consequences for victims, especially with respect to the reproductive health of women and the physical, emotional, and mental health of their children.

IndicatorName: Women who initiated sexual intercourse by age 15 (% of women ages 20-24)

Limitationsandexceptions: Collecting valid, reliable, and ethical data on domestic violence poses particular challenges because what constitutes violence or abuse varies across cultures and among individuals. In addition, a culture of silence usually surrounds domestic violence and can affect reporting.

Longdefinition: Percentage of women ages 20-24 who initiated sexual intercourse by age 15.

Statisticalconceptandmethodology:
Demographic and Health Surveys (DHS) are nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition. The surveys use model quesionnaires that contain a core set of questions that span all questionnaires, in addition to country-specific questions. Surveys have large sample sizes (usually between 5,000 and 30,000 households) and are typically conducted about every 5 years, to allow comparisons over time. The time to complete a survey depends on survey type, survey instruments, and sample size. Eligible households and individuals are usually obtained in a sampling frame from the National Statistics Office of the country. The time it takes to conduct all interviews is on average 18-20 months.

Data on domestic violence in DHS surveys comes from an optional module of questions. Thus, indicators in this chapter are available for some, but not all countries. Additionally, The DHS Program, in accordance with the WHO guidelines “Putting Women First: Ethical and Safety Recommendations for Research on Domestic Violence against Women” World Health Organization, 2001, randomly selects only one woman per household among all eligible women in the household selected for the individual questionnaire for this module. Thus, the number of women who have information for domestic violence will always be less than the number of women selected for the complete DHS individual interview.

 A large part of the domestic violence module asks about violence perpetrated by the current husband/partner for women who are currently married and the most recent husband/partner for women who are currently divorced, separated or widowed. Thus, women who have been ever-married are asked many more questions about their experience of violence than women who have never been married. Note also that ever-married women are women who self-report as being married, divorced, separated, or widowed, or living with or having ever lived with a man as if married. Thus, a “partner” is a man with whom the respondent lives with or lived with as if married. A previous husband/partner is a husband/partner other than the current husband/partner for currently married women and the most recent husband/partner for divorced, separated, or widowed women.


IndicatorName: Men who initiated sexual intercourse by age 15 (% of men ages 20-24)

License_Type: CC BY-4.0

Longdefinition: Percentage of men ages 20-24 who initiated sexual intercourse by age 15.

Periodicity: Annual

Source: Demographic and Health Surveys (DHS)

Topic: Violence

Unitofmeasure: Percent


IndicatorName: Women who initiated sexual intercourse before age 15 (% of women ages 15-19)

Longdefinition: Percentage of women ages 15-19 who initiated sexual intercourse before age 15.


IndicatorName: Men who initiated sexual intercourse before age 15 (% of men ages 15-19)

Longdefinition: Percentage of men ages 15-19 who initiated sexual intercourse before age 15.


Developmentrelevance: Women often spend disproportionately more time on unpaid domestic and care work than men.  This unequal division of responsibilities is correlated with gender differences in economic opportunities, includign low female labor force participation, occupational sex segregation, and earnings diffrentials.  The need for a gender balance  in the distribution of unpaid domestic and care work has been increasingly recognized and the Sustainable Development Goals address the issue in the target 5.4.

Generalcomments: This is the Sustainable Development Goal indicator 5.4.1[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Proportion of time spent on unpaid domestic and care work, female (% of 24 hour day)

Limitationsandexceptions: Data may not be strictly comparable across countries as the methods and sampling involved for data collection may differ.

Longdefinition: The average time women spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.

Source: National statistical offices or national database and publications compiled by United Nations Statistics Division.  The data were downloaded on April 4, 2024, from the Global SDG  API: https://unstats.un.org/sdgs/UNSDGAPIV5/swagger/index.html

Statisticalconceptandmethodology: Proportion of time spent on unpaid domestic and care work is calculated by dividing the daily average number of hours spent on unpaid domestic and care work by 24 hours.  Data presented for this indicator are expressed as a proportion of time in a day. Weekly data is averaged over seven days of the week to obtain the daily average time.

Topic: Employment and Time Use


IndicatorName: Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day)

Longdefinition: The average time men spend on household provision of services for own consumption.  Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others.

Source: National statistical offices or national database and publications compiled by United Nations Statistics Division. The data were downloaded on April 4, 2024, from the Global SDG  API: https://unstats.un.org/sdgs/UNSDGAPIV5/swagger/index.html


Aggregationmethod: Weighted average

Developmentrelevance: Violence against women is an obstacle to the achievement of the objectives of equality, development and peace. It both violates and impairs or nullifies the enjoyment by women of their human rights and fundamental freedoms. Tolerance and experience of domestic violence are significant barriers to the empowerment of women and it has a negative health consequences for victims, especially with respect to the reproductive health of women and the physical, emotional, and mental health of their children

IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 15-19)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 15-19 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.

Source: The United Nations Inter-Agency Working Group on Violence Against Women Estimation and Data (VAW-IAWGED)  (WHO, UN Women, UNICEF, UNSD, UNFPA, UNODC)

Statisticalconceptandmethodology:
The United Nations Inter-Agency Working Group on Violence Against Women Estimation and Data (VAW-IAWGED) generated prevalence estimates of intimate partner violence against women and non-partner sexual violence against women using a multilevel regression model.

The main sources of data on violence against women are: (i) specialized surveys on violence against women, for example surveys using the WHO multi-country study instrument and methodology or the European Union (EU)-wide survey on violence and (ii) modules on violence against women within larger national health surveys, such as the DHS and RHS. A small number of data points came from other surveys such as national crime victimization surveys or MICS.

This assessment harmonized data for these two forms of violence by including all available surveys that met the following WHO study criteria: (1) population-based, (2) representative at a national or subnational level, (3) conducted between 2000 and 2018, and available by 2019, and (4) used acts-based measures. The assessment adjusted for age groups and differences in definition of violence to make them comparable. The country-level, regional, and global estimates are presented as 2018 data, but are derived from surveys spanning the period 2000 to 2018.

Please refer to details of the methodology in the report: “Violence against women prevalence estimates, 2018: global, regional and national prevalence estimates for intimate partner violence against women and global and regional prevalence estimates for non-partner sexual violence against women”. Geneva: World Health Organization; 2021.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 15-19)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 15-19 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 15-49)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 15-49 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 15-49)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 15-49 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


Generalcomments: This is the Sustainable Development Goal indicator 5.2.1[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (% of ever-partnered women ages 15-49)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women age 15-49 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.

Source: United Nations Statistics Division (UNSD)


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 15+)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 15+ who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 15+)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 15+  who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 20-24)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 20-24 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 20-24)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 20-24 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 25-29)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women age 25-29 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 25-29)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 25-29 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 30-34)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 30-34 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 30-34)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 30-34 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 35-44)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 35-44 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 35-44)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 35-44 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 45-54)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 45-54 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 45-54)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 45-54 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 55-64)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 55-64 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 55-64)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 55-64 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced intimate partner violence (modeled estimate, % of ever partnered women ages 65+)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever partnered women ages 65+ who are subjected to physical violence, sexual violence or both by a current or former intimate partner in their lifetime.


IndicatorName: Proportion of women subjected to physical and/or sexual violence in the last 12 months (modeled estimate, % of ever partnered women ages 65+)

Longdefinition: Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women ages 65+ who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.


IndicatorName: Proportion of women who have ever experienced any form of sexual violence (% of women ages 15-49)

Longdefinition: Proportion of women who have ever experienced any form of sexual violence is the percentage of women ages 15-49 who ever experienced sexual violence.

Source: Demographic and Health Surveys (DHS) Statcompiler (https://www.statcompiler.com/)

Statisticalconceptandmethodology:
Demographic and Health Surveys (DHS) are nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators in the areas of population, health, and nutrition. The surveys use model quesionnaires that contain a core set of questions that span all questionnaires, in addition to country-specific questions. Surveys have large sample sizes (usually between 5,000 and 30,000 households) and are typically conducted about every 5 years, to allow comparisons over time. The time to complete a survey depends on survey type, survey instruments, and sample size. Eligible households and individuals are usually obtained in a sampling frame from the National Statistics Office of the country. The time it takes to conduct all interviews is on average 18-20 months.

Data on domestic violence in DHS surveys comes from an optional module of questions. Thus, indicators in this chapter are available for some, but not all countries. Additionally, The DHS Program, in accordance with the WHO guidelines “Putting Women First: Ethical and Safety Recommendations for Research on Domestic Violence against Women” World Health Organization, 2001, randomly selects only one woman per household among all eligible women in the household selected for the individual questionnaire for this module. Thus, the number of women who have information for domestic violence will always be less than the number of women selected for the complete DHS individual interview.


IndicatorName: Women who believe a husband is justified in beating his wife when she argues with him (%): Q1 (lowest)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she argues with him. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.

Source: Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other surveys


IndicatorName: Women who believe a husband is justified in beating his wife when she argues with him (%): Q2


IndicatorName: Women who believe a husband is justified in beating his wife when she argues with him (%): Q3


IndicatorName: Women who believe a husband is justified in beating his wife when she argues with him (%): Q4


IndicatorName: Women who believe a husband is justified in beating his wife when she argues with him (%): Q5 (highest)


IndicatorName: Women who believe a husband is justified in beating his wife when she argues with him (%)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she argues with him.


IndicatorName: Women who believe a husband is justified in beating his wife when she burns the food (%): Q1 (lowest)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she burns the food. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.


IndicatorName: Women who believe a husband is justified in beating his wife when she burns the food (%): Q2


IndicatorName: Women who believe a husband is justified in beating his wife when she burns the food (%): Q3


IndicatorName: Women who believe a husband is justified in beating his wife when she burns the food (%): Q4


IndicatorName: Women who believe a husband is justified in beating his wife when she burns the food (%): Q5 (highest)


IndicatorName: Women who believe a husband is justified in beating his wife when she burns the food (%)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she burns the food.


IndicatorName: Women who believe a husband is justified in beating his wife when she goes out without telling him (%): Q1 (lowest)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she goes out without telling him. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.


IndicatorName: Women who believe a husband is justified in beating his wife when she goes out without telling him (%): Q2


IndicatorName: Women who believe a husband is justified in beating his wife when she goes out without telling him (%): Q3


IndicatorName: Women who believe a husband is justified in beating his wife when she goes out without telling him (%): Q4


IndicatorName: Women who believe a husband is justified in beating his wife when she goes out without telling him (%): Q5 (highest)


IndicatorName: Women who believe a husband is justified in beating his wife when she goes out without telling him (%)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she goes out without telling him.


IndicatorName: Women who never sought help to stop violence, and never told anyone  (% of ever-married women ages 15-49 who have ever experienced any physical or sexual violence)

Longdefinition: Percentage of ever-married women ages 15-49 who have ever experienced any physical or sexual violence who never sought help to stop violence, and never told anyone


IndicatorName: Women who never sought help to stop violence, but told someone (% of ever-married women ages 15-49 who have ever experienced any physical or sexual violence)

Longdefinition: Percentage of ever-married women ages 15-49 who have ever experienced any physical or sexual violence who never sought help to stop violence, but told someone


IndicatorName: Proportion of women who have sought help to stop physical or sexual violence (% of ever-married women ages 15-49)

Longdefinition: Proportion of women who have sought help to stop physical or sexual violence is the percentage of ever-married women ages 15-49 who have ever experienced any physical or sexual violence who have sought help to stop violence.


IndicatorName: Women who have experienced injuries resulting from spousal violence (% of ever-married women ages 15-49 who have ever experienced any physical or sexual violence)

Longdefinition: Percentage of ever-married women ages 15-49 who have ever experienced spousal physical or sexual violence suffered one or more of these injuries: deep wounds, broken bones, broken teeth, eye injuries, sprains, dislocations, or burns, cuts, bruises or aches.


IndicatorName: Women whose husband or partner has never demonstrated controlling behaviors (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 whose husband or partner never demonstrated controlling behaviors


IndicatorName: Women whose husband or partner has ever demonstrated controlling behaviors (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 whose husband or partner has ever demonstrated 3 or more of the specific behaviors from the following: jealous or angry if she talks to other men; accuses her of being unfaithful; not permit her to meet her female friends; tries to limit her contact with her family;  insists on knowing where she is at all times; does not trust her with any money


IndicatorName: Women who have ever experienced emotional violence committed by their husband/partner  (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 who have ever experienced emotional violence committed by their husband or partner


IndicatorName: Women who have experienced emotional violence committed by their husband/partner in the 12 months (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 who have experienced emotional violence committed by their husband/partner in the 12 months preceding the survey


IndicatorName: Women who have ever experienced physical violence committed by their husband/partner (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 who have ever experienced physical violence committed by their husband or partner


IndicatorName: Women who have experienced physical violence committed by their husband/partner in the 12 months (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 who have experienced physical violence committed by their husband/partner in the 12 months preceding the survey


IndicatorName: Women who have ever experienced  sexual violence committed by their husband/partner  (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 who have ever experienced sexual violence committed by their husband or partner


IndicatorName: Women who have experienced sexual violence committed by their husband/partner in the 12 months (% of ever-married women ages 15-49)

Longdefinition: Percentage of ever-married women ages 15-49 who have experienced sexual violence committed by their husband/partner in the 12 months preceding the survey


IndicatorName: Women whose first experience of spousal physical or sexual violence was before marriage  (% of currently married women age 15-49 who have been married only once)

Longdefinition: Percentage of currently married women ages 15-49 who have been married only once whose first experience of spousal physical or sexual violence was before marriage


IndicatorName: Women whose first experience of spousal physical or sexual violence was within ten years of marriage  (% of currently married women age 15-49 who have been married only once)

Longdefinition: Percentage of currently married women ages 15-49 who have been married only once whose first experience of spousal physical or sexual violence was within ten years of marriage


IndicatorName: Women whose first experience of spousal physical or sexual violence was within two years of marriage  (% of currently married women age 15-49 who have been married only once)

Longdefinition: Percentage of currently married women ages 15-49 who have been married only once whose first experience of spousal physical or sexual violence was within two years of marriage


IndicatorName: Women whose first experience of spousal physical or sexual violence was within five years of marriage  (% of currently married women age 15-49 who have been married only once)

Longdefinition: Percentage of currently married women ages 15-49 who have been married only once whose first experience of spousal physical or sexual violence was within five years of marriage


IndicatorName: Women who have not experienced spousal physical or sexual violence (% of currently married women age 15-49 who have been married only once)

Longdefinition: Percentage of currently married women ages 15-49 who have been married only once and have not experienced spousal physical or sexual violence


IndicatorName: Proportion of women who have ever experienced intimate partner violence (% of ever-partnered women ages 15-49)

Longdefinition: Proportion of women who have ever experienced intimate partner violence is the percentage of ever-married women (ages 15 - 49) who have ever experienced physical or sexual violence committed by their husband or partner.


IndicatorName: Women who believe a husband is justified in beating his wife when she neglects the children (%): Q1 (lowest)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she neglects the children. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.


IndicatorName: Women who believe a husband is justified in beating his wife when she neglects the children (%): Q2


IndicatorName: Women who believe a husband is justified in beating his wife when she neglects the children (%): Q3


IndicatorName: Women who believe a husband is justified in beating his wife when she neglects the children (%): Q4


IndicatorName: Women who believe a husband is justified in beating his wife when she neglects the children (%): Q5 (highest)


IndicatorName: Women who believe a husband is justified in beating his wife when she neglects the children (%)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she neglects the children.


IndicatorName: Women who believe a husband is justified in beating his wife (any of five reasons) (%): Q1 (lowest)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner for any of the following five reasons: argues with him; refuses to have sex; burns the food; goes out without telling him; or when she neglects the children. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.


IndicatorName: Women who believe a husband is justified in beating his wife (any of five reasons) (%): Q2


IndicatorName: Women who believe a husband is justified in beating his wife (any of five reasons) (%): Q3


IndicatorName: Women who believe a husband is justified in beating his wife (any of five reasons) (%): Q4


IndicatorName: Women who believe a husband is justified in beating his wife (any of five reasons) (%): Q5 (highest)


IndicatorName: Women who believe a husband is justified in beating his wife (any of five reasons) (%)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner for any of the following five reasons: argues with him; refuses to have sex; burns the food; goes out without telling him; or when she neglects the children.


IndicatorName: Women who believe a husband is justified in beating his wife when she refuses sex with him (%): Q1 (lowest)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she refuses sex with him. Each wealth quintile represents one fifth of households with quintile 1 being the poorest 20 percent of households and quintile 5 being the richest 20 percent of households.


IndicatorName: Women who believe a husband is justified in beating his wife when she refuses sex with him (%): Q2


IndicatorName: Women who believe a husband is justified in beating his wife when she refuses sex with him (%): Q3


IndicatorName: Women who believe a husband is justified in beating his wife when she refuses sex with him (%): Q4


IndicatorName: Women who believe a husband is justified in beating his wife when she refuses sex with him (%): Q5 (highest)


IndicatorName: Women who believe a husband is justified in beating his wife when she refuses sex with him (%)

Longdefinition: Percentage of women ages 15-49 who believe a husband/partner is justified in hitting or beating his wife/partner when she refuses sex with him.


IndicatorName: Women who experienced first sexual violence before age 15 (% of women ages 15-49)

Longdefinition: Percentage of women ages 15-49 who first experienced sexual violence before exact age 15


IndicatorName: Women who experienced first sexual violence before age 18 (% of women ages 15-49)

Longdefinition: Percentage of women ages 15-49 who first experienced sexual violence before exact age 18


IndicatorName: Women who experienced first sexual violence before age 22 (% of women ages 15-49)

Longdefinition: Percentage of women ages 15-49 who first experienced sexual violence before exact age 22


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

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

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

Longdefinition: Total alcohol per capita consumption is defined as the total (sum of recorded and unrecorded alcohol) amount of alcohol consumed per person (15 years of age or older) over a calendar year, in litres of pure alcohol, adjusted for tourist consumption.

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

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

Topic: Health


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

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


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


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

Longdefinition: Prevalence of anemia among women of reproductive age refers to the combined prevalence of both non-pregnant with haemoglobin levels below 12 g/dL and pregnant women with haemoglobin levels below 11 g/dL.

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


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

Longdefinition: Prevalence of anemia, non-pregnant women, is the percentage of non-pregnant women whose hemoglobin level is less than 120 grams per liter at sea level.


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

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

Source: Demographic and Health Surveys, and UNAIDS.


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

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


Developmentrelevance: Measuring the number of deaths and their causes helps to improve health services and reduce preventable deaths.  Specifically, these data are used to monitor progress towards the health-related targets within the Sustainable Development Goals (SDGs). For example, SDG Target 3.4 calls for reducing premature mortality from non-communicable diseases. Disease burden from non-communicable diseases is becoming a serious problem in many low-and middle-income countries .                                                                                Assessing the cause of deaths data, disaggregated by age, sex and geographic location, is essential to identify inequities in health.

IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 0-4, female (% of female population ages 0-4)

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

Longdefinition: Number of female deaths ages 0-4 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all female deaths ages 0-4, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.

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

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


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 0-4, male (% of male population ages 0-4)

Longdefinition: Number of male deaths ages 0-4 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all male deaths ages 0-4, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 0-4 (% of population ages 0-4)

Longdefinition: Number of deaths ages 0-4 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all deaths ages 0-4, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 5-14, female (% of female population ages 5-14)

Longdefinition: Number of female deaths ages 5-14 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all female deaths ages 5-14, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 5-14, male (% of male population ages 5-14)

Longdefinition: Number of male deaths ages 5-14 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all male deaths ages 5-14, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 5-14 (% of population ages 5-14)

Longdefinition: Number of deaths ages 5-14 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all deaths ages 5-14, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 15-59, female (% of female population ages 15-59)

Longdefinition: Number of female deaths ages 15-59 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all female deaths ages 15-59, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 15-59, male (% of male population ages 15-59)

Longdefinition: Number of male deaths ages 15-59 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all male deaths ages 15-59, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 15-59 (% of population ages 15-59)

Longdefinition: Number of deaths ages 15-59 due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all deaths ages 15-59, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 60+, female (% of female population ages 60+)

Longdefinition: Number of female deaths ages 60+ due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all female deaths ages 60+, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 60+, male (% of male population ages 60+)

Longdefinition: Number of male deaths ages 60+ due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all male deaths ages 60+, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


IndicatorName: Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions, ages 60+ (% of population ages 60+)

Longdefinition: Number of deaths ages 60+ due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all deaths ages 60+, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


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

Longdefinition: Number of female deaths due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all female deaths, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


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

Longdefinition: Number of male deaths due to communicable diseases and maternal, prenatal and nutrition conditions divided by number of all male deaths, expressed by percentage. Communicable diseases and maternal, prenatal and nutrition conditions included infectious and parasitic diseases, respiratory infections, and nutritional deficiencies such as underweight and stunting.


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

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


Aggregationmethod: Sum

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

IndicatorName: Number of infant deaths

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

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

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


IndicatorName: Number of infant deaths, female

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


IndicatorName: Number of infant deaths, male

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


IndicatorName: Cause of death, by injury, ages 0-4, female (% of female population ages 0-4)

Longdefinition: Number of female deaths ages 0-4 due to injury divided by number of all female deaths ages 0-4, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 0-4, male (% of male population ages 0-4)

Longdefinition: Number of male deaths ages 0-4 due to injury divided by number of all male deaths ages 0-4, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 0-4 (% of population ages 0-4)

Longdefinition: Number of deaths ages 0-4 due to injury divided by number of all deaths ages 0-4, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 5-14, female (% of female population ages 5-14)

Longdefinition: Number of female deaths ages 5-14 due to injury divided by number of all female deaths ages 5-14, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 5-14, male (% of male population ages 5-14)

Longdefinition: Number of male deaths ages 5-14 due to injury divided by number of all male deaths ages 5-14, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 5-14 (% of population ages 5-14)

Longdefinition: Number of deaths ages 5-14 due to injury divided by number of all deaths ages 5-14, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 15-59, female (% of female population ages 15-59)

Longdefinition: Number of female deaths ages 15-59 due to injury divided by number of all female deaths ages 15-59, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 15-59, male (% of male population ages 15-59)

Longdefinition: Number of male deaths ages 15-59 due to injury divided by number of all male deaths ages 15-59, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 15-59 (% of population ages 15-59)

Longdefinition: Number of deaths ages 15-59 due to injury divided by number of all deaths ages 15-59, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 60+, female (% of female population ages 60+)

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

Longdefinition: Number of female deaths ages 60+ due to injury divided by number of all female deaths ages 60+, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 60+, male (% of male population ages 60+)

Longdefinition: Number of male deaths ages 60+ due to injury divided by number of all male deaths ages 60+, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, ages 60+ (% of population ages 60+)

Longdefinition: Number of deaths ages 60+ due to injury divided by number of all deaths ages 60+, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, female (% of female population)

Longdefinition: Number of female deaths due to injury divided by number of all female deaths, expressed by percentage. Injury includes unintentional and intentional injuries.


IndicatorName: Cause of death, by injury, male (% of male population)

Longdefinition: Number of male deaths ages due to injury divided by number of all male deaths ages, expressed by percentage. Injury includes unintentional and intentional injuries.


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

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

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


IndicatorName: Number of under-five deaths, female

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


IndicatorName: Number of under-five deaths, male

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


IndicatorName: Cause of death, by non-communicable diseases, ages 0-4, female (% of female population ages 0-4)

Longdefinition: Number of female deaths ages 0-4 due to non-communicable diseases divided by number of all female deaths ages 0-4, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 0-4, male (% of male population ages 0-4)

Longdefinition: Number of male deaths ages 0-4 due to non-communicable diseases divided by number of all male deaths ages 0-4, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 0-4 (% of population ages 0-4)

Longdefinition: Number of deaths ages 0-4 due to non-communicable diseases divided by number of all deaths ages 0-4, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 5-14, female (% of female population ages 5-14)

Longdefinition: Number of female deaths ages 5-14 due to non-communicable diseases divided by number of all female deaths ages 5-14, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 5-14, male (% of male population ages 5-14)

Longdefinition: Number of male deaths ages 5-14 due to non-communicable diseases divided by number of all male deaths ages 5-14, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 5-14 (% of population ages 5-14)

Longdefinition: Number of deaths ages 5-14 due to non-communicable diseases divided by number of all deaths ages 5-14, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 15-59, female (% of female population ages 15-59)

Longdefinition: Number of female deaths ages 15-59 due to non-communicable diseases divided by number of all female deaths ages 15-59, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 15-59, male (% of male population ages 15-59)

Longdefinition: Number of male deaths ages 15-59 due to non-communicable diseases divided by number of all male deaths ages 15-59, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 15-59 (% of population ages 15-59)

Longdefinition: Number of deaths ages 15-59 due to non-communicable diseases divided by number of all deaths ages 15-59 expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 60+, female (% of female population ages 60+)

Longdefinition: Number of female deaths ages 60+ due to non-communicable diseases divided by number of all female deaths ages 60+, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 60+, male (% of male population ages 60+)

Longdefinition: Number of male deaths ages 60+ due to non-communicable diseases divided by number of all male deaths ages 60+, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


IndicatorName: Cause of death, by non-communicable diseases, ages 60+ (% of population ages 60+)

Longdefinition: Number of deaths ages 60+ due to non-communicable diseases divided by number of all deaths ages 60+, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


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

Longdefinition: Number of female deaths due to non-communicable diseases divided by number of all female deaths, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


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

Longdefinition: Number of male deaths ages due to non-communicable diseases divided by number of all male deaths ages, expressed by percentage. Non-Communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.


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

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


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

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

IndicatorName: Number of stillbirths

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

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

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


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

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

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

Source: UNAIDS estimates.

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

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


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

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

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

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

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

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

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

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


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

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

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

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

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


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

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


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

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

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


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


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

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


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

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


Developmentrelevance: To decide freely and responsibly the number of and spacing between their children and to have the information on family planning has been internationally recognized as the basic right for couples and individuals.  Having knowledge about contraceptive methods helps couples and individuals to choose safe and effective methods.

IndicatorName: Knowledge of any modern method of contraception (% of all women ages 15-49)

Longdefinition: Percentage of all women ages 15-49 who know at least one of modern methods of contraception. Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception.

Notesfromoriginalsource: Breastfeeding, prolonged breastfeeding, prolonged abstinence are not considered contraceptive methods in themselves.

Source: Demographic and Health Surveys (DHS) (https://www.statcompiler.com/)


IndicatorName: Knowledge of any modern method of contraception  (% of all men)

Longdefinition: Percentage of all men who know at least one of modern methods of contraception. Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception. The age range of men depends on surveys.  In most DHS surveys, men ages 15-49, 15-54, or 15-59 are eligible for individual interviews.


IndicatorName: Knowledge of any modern method of contraception (% of married women ages 15-49)

Longdefinition: Percentage of currently married or in union women ages 15-49 who know at least one of modern methods of contraception. Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception.


IndicatorName: Knowledge of any modern method of contraception  (% of married men)

Longdefinition: Percentage of currently married or in union men who know at least one of modern methods of contraception. Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception. In most DHS surveys, men ages 15-49, 15-54, or 15-59 are eligible for individual interviews.


IndicatorName: Knowledge of any method of contraception (% of all women ages 15-49)

Longdefinition: Percentage of all women ages 15-49 who know any method of contraception.  Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception. Traditional methods includes periodic abstinence (rhythm, calendar method) and withdrawal.


IndicatorName: Knowledge of any method of contraception (% of all men)

Longdefinition: Percentage of all men who know any method of contraception. Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception. Traditional methods includes periodic abstinence (rhythm, calendar method) and withdrawal.  The age range of men depends on surveys.  In most DHS surveys, men ages 15-49, 15-54, or 15-59 are eligible for individual interviews.


IndicatorName: Knowledge of any method of contraception (% of married women ages 15-49)

Longdefinition: Percentage of currently married or in union women ages 15-49 who know any method of contraception. Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception. Traditional methods includes periodic abstinence (rhythm, calendar method) and withdrawal.


IndicatorName: Knowledge of any method of contraception (% of married men)

Longdefinition: Percentage of currently married or in union men who know any method of contraception.  Modern methods of contraception include female and male sterilization, contraceptive pills, intra-uterine device (IUD), injectables, implants, male and female condoms, diaphragm, contraceptive foam and contraceptive jelly female condom, lactational amenorrhea method (LAM), Standard days method (SDM), and emergency contraception. Traditional methods includes periodic abstinence (rhythm, calendar method) and withdrawal.  The age range of men depends on surveys.  In most DHS surveys, men ages 15-49, 15-54, or 15-59 are eligible for individual interviews.


Developmentrelevance: Fertility planning status categorizes births according to whether women reported wanting a pregnancy at the time of conceiving, wanting a pregnancy later, or not wanting any births. The data can help us to understand the level of contraceptive needs.  Access for all couples and individuals to their preferred contraceptive methods is a basic human right.  Also, use of contraception prevents pregnancy-related risks for women, especially for adolescent girls.

IndicatorName: Fertility planning status: mistimed pregnancy (% of births)

Longdefinition: The proportion of women ages 15-49 who reported the last birth in the five years preceding the survery was mistimed (wanted later).


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

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

Source: Demographic and Health Surveys.


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

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

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

Source: Demographic and Health Surveys (DHS).


IndicatorName: Fertility planning status: unwanted pregnancy (% of births)

Longdefinition: The proportion of women ages 15-49 who reported the last birth in the five years preceding the survery was unwanted.


IndicatorName: Fertility planning status: planned pregnancy (% of births)

Longdefinition: The proportion of women ages 15-49 who reported the last birth in the five years preceding the survery was planned (wanted then).


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

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

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


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

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

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


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

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


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.


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

Longdefinition: The percentage of adult females living with HIV who are receiving antiretroviral therapy.

Statisticalconceptandmethodology:
Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. For example, improved software was used to model the course of HIV epidemics and their impacts, making full use of information on HIV prevalence trends from surveillance data as well as survey data. The software explicitly includes the effect of antiretroviral therapy when calculating HIV incidence and models reduced infectivity among people receiving antiretroviral therapy, which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer. The software also allows for changes in urbanization over time - important because prevalence is higher in urban areas and because many countries have seen rapid urbanization over the past two decades.

Antiretroviral therapy has led to huge reductions in death and suffering of people with advanced HIV infection. Standard antiretroviral therapy consists of the use of at least three antiretroviral drugs to maximally suppress HIV and stop the progression of HIV disease. Data are collected through three international monitoring and reporting processes: country responses to the WHO; research by the Interagency Task Team on Prevention of HIV Infection in Women, Mothers and their Children; and country report to UNAIDS through the United Nations General Assembly Special Session Declaration of Commitment on HIV/AIDS.


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

Longdefinition: The percentage of adult males living with HIV who are receiving antiretroviral therapy.


Developmentrelevance: Despite the existence of effective medications and treatment, HIV is still a leading cause of death and public health threat in the world.  In Sub-Saharan Africa, women and girls are disproportinally affected by HIV.  The incidence rate provides a measure of progress toward preventing onward transmission of HIV.

Generalcomments: This is a sex-disaggregated Sustainable Development Goal inidcator 3.3.1 [https://unstats.un.org/sdgs/metadata/].

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

Longdefinition: Number of new HIV infections among uninfected female populations ages 15-49 expressed per 1,000 uninfected female population ages 15-49 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: Incidence of HIV, ages 15-49, male (per 1,000 uninfected male population ages 15-49)

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


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

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


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

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


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

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

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.


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

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

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


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

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


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

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


IndicatorName: 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).


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.

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)

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, 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.

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.

Topic: Economic and Social Context


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.


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: 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


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:
1. 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.
2. The 2024 Women, Business and the Law (WBL) report has introduced two distinct datasets, labeled as 1.0 and 2.0. The WBL data in the Gender database is based on the dataset 1.0.  This dataset maintains consistency with the indicators used in previous WBL reports from 2020 to 2023. In contrast, the WBL 2.0 dataset includes new areas of childcare and safety. For those interested in exploring the WBL 2.0 dataset, it is available on the WBL website at https://wbl.worldbank.org.

IndicatorName: Length of paid maternity leave (calendar days)

Limitationsandexceptions: The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research.

Longdefinition: The indicator refers to leave available only to the mother for the birth of a child to be taken just before, during and immediately after childbirth.

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 violence against women legislation, 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.