The average Women's Empowerment Index (WEI) score worldwide is 0.607, meaning that globally, women are only empowered to achieve 60 percent of their full potential. Australia and New Zealand have the highest scores out of each region, while Sub-Saharan Africa has the lowest. Participation in decision-making is the lowest-scoring area for each region, and overall, there is no region that has achieved a perfect score.

This report presents statistics on women’s smoking status at time of delivery, at Sub Integrated Care Board (Sub-ICB), Integrated Care Board (ICB), regional and national levels. This release includes provisional data for quarter 3 of 2024-25 using data from the Smoking at Time of Delivery data collection which is submitted by commissioners (presented as SATOD v1). Alongside this and for the third time, comparative data using the Maternity Services Dataset (MSDS) is also presented using data submitted by Trusts (presented as SATOD v2) as a time series from quarter 1 of 2022-23 to quarter 3 of 2024-25. This is available for the same geographical breakdowns and includes an additional breakdown for Local Authorities. This will be repeated for subsequent quarters in 2024-25 to see how the estimates from both data sources align with a view to retiring the Smoking at Time of Delivery data collection at the end of this financial year. Until then, SATOD v1 remains the primary data source for this publication. In 2024, a proposal for the data source for this publication to be changed to the Maternity Services Dataset was included in a wider consultation: Health and social care statistical outputs published by DHSC (including OHID), NHSBSA, UKHSA, ONS and NHS England. A link to this is in the Related Links below. If you would still like to feedback your views on the SATOD data collection retirement and replacement with MSDS, then please contact us on: england.maternityanalysis@nhs.net

Over the past decades, more and more women have entered the labor market around the world. Today, over 40 percent of the global workforce are women. However, only one third are in senior roles, and less than 30 percent work within science, technology, engineering, and mathematics (STEM). The Global Gender Index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2024, the leading country was Iceland .

A comprehensive list of data sources relating to violence against women and girls, bringing together a range of different sources from across government, academia and the voluntary sector.

Graph and download economic data for Unemployment Rate - Women (LNS14000002) from Jan 1948 to Feb 2025 about females, 16 years +, household survey, unemployment, rate, and USA.

United States US: Population: as % of Total: Female: Aged 65 and Above data was reported at 16.925 % in 2017. This records an increase from the previous number of 16.550 % for 2016. United States US: Population: as % of Total: Female: Aged 65 and Above data is updated yearly, averaging 14.035 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 16.925 % in 2017 and a record low of 10.023 % in 1960. United States US: Population: as % of Total: Female: Aged 65 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population 65 years of age or older as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

This comprehensive report chronicles the history of women in the military and as Veterans, profiles the characteristics of women Veterans in 2009, illustrates how women Veterans in 2009 utilized some of the major benefits and services offered by the Department of Veterans Affairs (VA), and discusses the future of women Veterans in relation to VA. The goal of this report is to gain an understanding of who our women Veterans are, how their military service affects their post-military lives, and how they can be better served based on these insights.

Contains data on women's smoking status at time of delivery at Sub-ICB, ICB, regional and national level. Data is available in Excel or CSV format. Latest data is for quarter 4 of 2023/24.

The goal of the Chicago Women's Health Risk Study (CWHRS) was to develop a reliable and validated profile of risk factors directly related to lethal or life-threatening outcomes in intimate partner violence, for use in agencies and organizations working to help women in abusive relationships. Data were collected to draw comparisons between abused women in situations resulting in fatal outcomes and those without fatal outcomes, as well as a baseline comparison of abused women and non-abused women, taking into account the interaction of events, circumstances, and interventions occurring over the course of a year or two. The CWHRS used a quasi-experimental design to gather survey data on 705 women at the point of service for any kind of treatment (related to abuse or not) sought at one of four medical sites serving populations in areas with high rates of intimate partner homicide (Chicago Women's Health Center, Cook County Hospital, Erie Family Health Center, and Roseland Public Health Center). Over 2,600 women were randomly screened in these settings, following strict protocols for safety and privacy. One goal of the design was that the sample would not systematically exclude high-risk but understudied populations, such as expectant mothers, women without regular sources of health care, and abused women in situations where the abuse is unknown to helping agencies. To accomplish this, the study used sensitive contact and interview procedures, developed sensitive instruments, and worked closely with each sample site. The CWHRS attempted to interview all women who answered "yes -- within the past year" to any of the three screening questions, and about 30 percent of women who did not answer yes, provided that the women were over age 17 and had been in an intimate relationship in the past year. In total, 705 women were interviewed, 497 of whom reported that they had experienced physical violence or a violent threat at the hands of an intimate partner in the past year (the abused, or AW, group). The remaining 208 women formed the comparison group (the non-abused, or NAW, group). Data from the initial interview sections comprise Parts 1-8. For some women, the AW versus NAW interview status was not the same as their screening status. When a woman told the interviewer that she had experienced violence or a violent threat in the past year, she and the interviewer completed a daily calendar history, including details of important events and each violent incident that had occurred the previous year. The study attempted to conduct one or two follow-up interviews over the following year with the 497 women categorized as AW. The follow-up rate was 66 percent. Data from this part of the clinic/hospital sample are found in Parts 9-12. In addition to the clinic/hospital sample, the CWHRS collected data on each of the 87 intimate partner homicides occurring in Chicago over a two-year period that involved at least one woman age 18 or older. Using the same interview schedule as for the clinic/hospital sample, CWHRS interviewers conducted personal interviews with one to three "proxy respondents" per case, people who were knowledgeable and credible sources of information about the couple and their relationship, and information was compiled from official or public records, such as court records, witness statements, and newspaper accounts (Parts 13-15). In homicides in which a woman was the homicide offender, attempts were made to contact and interview her. This "lethal" sample, all such homicides that took place in 1995 or 1996, was developed from two sources, HOMICIDES IN CHICAGO, 1965-1995 (ICPSR 6399) and the Cook County Medical Examiner's Office. Part 1 includes demographic variables describing each respondent, such as age, race and ethnicity, level of education, employment status, screening status (AW or NAW), birthplace, and marital status. Variables in Part 2 include details about the woman's household, such as whether she was homeless, the number of people living in the household and details about each person, the number of her children or other children in the household, details of any of her children not living in her household, and any changes in the household structure over the past year. Variables in Part 3 deal with the woman's physical and mental health, including pregnancy, and with her social support network and material resources. Variables in Part 4 provide information on the number and type of firearms in the household, whether the woman had experienced power, control, stalking, or harassment at the hands of an intimate partner in the past year, whether she had experienced specific types of violence or violent threats at the hands of an intimate partner in the past year, and whether she had experienced symptoms of Post-Traumatic Stress Disorder related to the incidents in the past month. Variables in Part 5 specify the partner or partners who were responsible for the incidents in the past year, record the type and length of the woman's relationship with each of these partners, and provide detailed information on the one partner she chose to talk about (called "Name"). Variables in Part 6 probe the woman's help-seeking and interventions in the past year. Variables in Part 7 include questions comprising the Campbell Danger Assessment (Campbell, 1993). Part 8 assembles variables pertaining to the chosen abusive partner (Name). Part 9, an event-level file, includes the type and the date of each event the woman discussed in a 12-month retrospective calendar history. Part 10, an incident-level file, includes variables describing each violent incident or threat of violence. There is a unique identifier linking each woman to her set of events or incidents. Part 11 is a person-level file in which the incidents in Part 10 have been aggregated into totals for each woman. Variables in Part 11 include, for example, the total number of incidents during the year, the number of days before the interview that the most recent incident had occurred, and the severity of the most severe incident in the past year. Part 12 is a person-level file that summarizes incident information from the follow-up interviews, including the number of abuse incidents from the initial interview to the last follow-up, the number of days between the initial interview and the last follow-up, and the maximum severity of any follow-up incident. Parts 1-12 contain a unique identifier variable that allows users to link each respondent across files. Parts 13-15 contain data from official records sources and information supplied by proxies for victims of intimate partner homicides in 1995 and 1996 in Chicago. Part 13 contains information about the homicide incidents from the "lethal sample," along with outcomes of the court cases (if any) from the Administrative Office of the Illinois Courts. Variables for Part 13 include the number of victims killed in the incident, the month and year of the incident, the gender, race, and age of both the victim and offender, who initiated the violence, the severity of any other violence immediately preceding the death, if leaving the relationship triggered the final incident, whether either partner was invading the other's home at the time of the incident, whether jealousy or infidelity was an issue in the final incident, whether there was drug or alcohol use noted by witnesses, the predominant motive of the homicide, location of the homicide, relationship of victim to offender, type of weapon used, whether the offender committed suicide after the homicide, whether any criminal charges were filed, and the type of disposition and length of sentence for that charge. Parts 14 and 15 contain data collected using the proxy interview questionnaire (or the interview of the woman offender, if applicable). The questionnaire used for Part 14 was identical to the one used in the clinic sample, except for some extra questions about the homicide incident. The data include only those 76 cases for which at least one interview was conducted. Most variables in Part 14 pertain to the victim or the offender, regardless of gender (unless otherwise labeled). For ease of analysis, Part 15 includes the same 76 cases as Part 14, but the variables are organized from the woman's point of view, regardless of whether she was the victim or offender in the homicide (for the same-sex cases, Part 15 is from the woman victim's point of view). Parts 14 and 15 can be linked by ID number. However, Part 14 includes five sets of variables that were asked only from the woman's perspective in the original questionnaire: household composition, Post-Traumatic Stress Disorder (PTSD), social support network, personal income (as opposed to household income), and help-seeking and intervention. To avoid redundancy, these variables appear only in Part 14. Other variables in Part 14 cover information about the person(s) interviewed, the victim's and offender's age, sex, race/ethnicity, birthplace, employment status at time of death, and level of education, a scale of the victim's and offender's severity of physical abuse in the year prior to the death, the length of the relationship between victim and offender, the number of children belonging to each partner, whether either partner tried to leave and/or asked the other to stay away, the reasons why each partner tried to leave, the longest amount of time each partner stayed away, whether either or both partners returned to the relationship before the death, any known physical or emotional problems sustained by victim or offender, including the four-item Medical Outcomes Study (MOS) scale of depression, drug and alcohol use of the victim and offender, number and type of guns in the household of the victim and offender, Scales of Power and Control (Johnson, 1996) or Stalking and Harassment (Sheridan, 1992) by either intimate partner in the year prior to the death, a modified version of the Conflict Tactics Scale (CTS)

This Data Set represents a 2011 monthly total of Outreach and Workshops for women and the number of Attendees

In 2022, women constituted 20 percent of executives worldwide. Female employees made up a far higher share of the workforce compared to CEOs, with 38 percent compared to only six percent, respectively.

Graph and download economic data for Infra-Annual Labor Statistics: Employment Rate Female: From 25 to 54 Years for United States (LREM25FEUSQ156S) from Q1 1977 to Q4 2024 about 25 to 54 years, employment-population ratio, females, employment, population, rate, and USA.

About this dataset

Context

The dataset tabulates the population of Wakefield by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Wakefield. The dataset can be utilized to understand the population distribution of Wakefield by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Wakefield. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Wakefield.

Key observations

Largest age group (population): Male # 5-9 years (105) | Female # 35-39 years (91). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Wakefield population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Wakefield is shown in the following column.
• Population (Female): The female population in the Wakefield is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Wakefield for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Wakefield Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Long Beach by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Long Beach. The dataset can be utilized to understand the population distribution of Long Beach by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Long Beach. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Long Beach.

Key observations

Largest age group (population): Male # 55-59 years (98) | Female # 60-64 years (125). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Long Beach population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Long Beach is shown in the following column.
• Population (Female): The female population in the Long Beach is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Long Beach for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Long Beach Population by Gender. You can refer the same here

Germany DE: Population: as % of Total: Female: Aged 15-64 data was reported at 61.528 % in 2023. This records a decrease from the previous number of 61.854 % for 2022. Germany DE: Population: as % of Total: Female: Aged 15-64 data is updated yearly, averaging 64.197 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 67.752 % in 1960 and a record low of 61.528 % in 2023. Germany DE: Population: as % of Total: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 15 to 64 as a percentage of the total female population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.;United Nations Population Division. World Population Prospects: 2024 Revision.;Weighted average;Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

United States US: Prevalence of Wasting: Weight for Height: Female: % of Children Under 5 data was reported at 0.700 % in 2012. This records an increase from the previous number of 0.500 % for 2009. United States US: Prevalence of Wasting: Weight for Height: Female: % of Children Under 5 data is updated yearly, averaging 0.550 % from Dec 1991 (Median) to 2012, with 6 observations. The data reached an all-time high of 0.800 % in 2005 and a record low of 0.100 % in 2001. United States US: Prevalence of Wasting: Weight for Height: Female: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Prevalence of wasting, female, is the proportion of girls under age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF, www.childinfo.org). Estimates of child malnutrition, based on prevalence of underweight and stunting, are from national survey data. The proportion of underweight children is the most common malnutrition indicator. Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition.

About this dataset

Context

The dataset tabulates the population of Windham town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Windham town. The dataset can be utilized to understand the population distribution of Windham town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Windham town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Windham town.

Key observations

Largest age group (population): Male # 40-44 years (1,078) | Female # 35-39 years (946). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Windham town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Windham town is shown in the following column.
• Population (Female): The female population in the Windham town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Windham town for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Windham town Population by Gender. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Jordan by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Jordan. The dataset can be utilized to understand the population distribution of Jordan by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Jordan. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Jordan.

Key observations

Largest age group (population): Male # 25-29 years (21) | Female # 75-79 years (24). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Jordan population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Jordan is shown in the following column.
• Population (Female): The female population in the Jordan is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Jordan for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Jordan Population by Gender. You can refer the same here

United States US: Population: Female: Ages 5-9: % of Female Population data was reported at 6.176 % in 2017. This records a decrease from the previous number of 6.267 % for 2016. United States US: Population: Female: Ages 5-9: % of Female Population data is updated yearly, averaging 7.009 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 10.134 % in 1964 and a record low of 6.176 % in 2017. United States US: Population: Female: Ages 5-9: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Population and Urbanization Statistics. Female population between the ages 5 to 9 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Thailand TH: Population: as % of Total: Female: Aged 0-14 data was reported at 16.431 % in 2017. This records a decrease from the previous number of 16.758 % for 2016. Thailand TH: Population: as % of Total: Female: Aged 0-14 data is updated yearly, averaging 30.729 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 43.593 % in 1968 and a record low of 16.431 % in 2017. Thailand TH: Population: as % of Total: Female: Aged 0-14 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 0 to 14 as a percentage of the total female population. Population is based on the de facto definition of population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; Weighted average; Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.