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TwitterWomen's health funding by the NIH was around *** billion U.S. dollars during fiscal year 2023. This graph shows the actual women's health funding by the National Institutes for Health (NIH) from FY 2013 to FY 2023 and estimates for FY 2024 and FY 2025.
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TwitterThe 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)
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TwitterThis statistic shows the percentage of women in the U.S. who reported their mental health as poor from 2015 to 2017, by state. During this time, around 41 percent of women in West Virginia reported their mental health was "not good" between one and 30 days in the past 30 days.
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Twitterhttps://www.icpsr.umich.edu/web/ICPSR/studies/28762/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/28762/terms
The Study of Women's Health Across the Nation (SWAN), is a multi-site longitudinal, epidemiologic study designed to examine the health of women during their middle years. The study examines the physical, biological, psychological, and social changes during this transitional period. The goal of SWAN's research is to help scientists, health care providers, and women learn how mid-life experiences affect health and quality of life during aging. The data include questions about doctor visits, medical conditions, medications, treatments, medical procedures, relationships, smoking, and menopause related information such as age at pre-, peri- and post-menopause, self-attitudes, feelings, and common physical problems associated with menopause.The study is co-sponsored by the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), the National Institutes of Health (NIH), and the NIH Office of Research on Women's Health. The study began in 1994. Between 1996 and 1997, 3,302 participants joined SWAN through 7 designated research centers. The research centers are located in the following communities: Detroit, MI; Boston, MA; Chicago, IL; Oakland and Los Angeles, CA; Newark, NJ; and Pittsburgh, PA. SWAN participants represent five racial/ethnic groups and a variety of backgrounds and cultures. This is the next phase of data collection after the original collection of the screening data (ICPSR 4368).
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TwitterThis blog post was posted by Winifred Rossi on May 6, 201.
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TwitterBy City of Chicago [source]
This public health dataset contains a comprehensive selection of indicators related to natality, mortality, infectious disease, lead poisoning, and economic status from Chicago community areas. It is an invaluable resource for those interested in understanding the current state of public health within each area in order to identify any deficiencies or areas of improvement needed.
The data includes 27 indicators such as birth and death rates, prenatal care beginning in first trimester percentages, preterm birth rates, breast cancer incidences per hundred thousand female population, all-sites cancer rates per hundred thousand population and more. For each indicator provided it details the geographical region so that analyses can be made regarding trends on a local level. Furthermore this dataset allows various stakeholders to measure performance along these indicators or even compare different community areas side-by-side.
This dataset provides a valuable tool for those striving toward better public health outcomes for the citizens of Chicago's communities by allowing greater insight into trends specific to geographic regions that could potentially lead to further research and implementation practices based on empirical evidence gathered from this comprehensive yet digestible selection of indicators
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- 🚨 Your notebook can be here! 🚨!
In order to use this dataset effectively to assess the public health of a given area or areas in the city: - Understand which data is available: The list of data included in this dataset can be found above. It is important to know all that are included as well as their definitions so that accurate conclusions can be made when utilizing the data for research or analysis. - Identify areas of interest: Once you are familiar with what type of data is present it can help to identify which community areas you would like to study more closely or compare with one another. - Choose your variables: Once you have identified your areas it will be helpful to decide which variables are most relevant for your studies and research specific questions regarding these variables based on what you are trying to learn from this data set.
- Analyze the Data : Once your variables have been selected and clarified take right into analyzing the corresponding values across different community areas using statistical tests such as t-tests or correlations etc.. This will help answer questions like “Are there significant differences between two outputs?” allowing you to compare how different Chicago Community Areas stack up against each other with regards to public health statistics tracked by this dataset!
- Creating interactive maps that show data on public health indicators by Chicago community area to allow users to explore the data more easily.
- Designing a machine learning model to predict future variations in public health indicators by Chicago community area such as birth rate, preterm births, and childhood lead poisoning levels.
- Developing an app that enables users to search for public health information in their own community areas and compare with other areas within the city or across different cities in the US
If you use this dataset in your research, please credit the original authors. Data Source
See the dataset description for more information.
File: public-health-statistics-selected-public-health-indicators-by-chicago-community-area-1.csv | Column name | Description | |:-----------------------------------------------|:--------------------------------------------------------------------------------------------------| | Community Area | Unique identifier for each community area in Chicago. (Integer) | | Community Area Name | Name of the community area in Chicago. (String) | | Birth Rate | Number of live births per 1,000 population. (Float) | | General Fertility Rate | Number of live births per 1,000 women aged 15-44. (Float) ...
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TwitterNote: This dataset is historical only and STI surveillance data do not change once finalized. For the most recent STI data, please refer to the CDPH Health Atlas (chicagohealthatlas.org), the annual HIV/STI surveillance report, and the Getting to Zero Illinois HIV Dashboard (gtzillinois.hiv).
The annual number of newly reported, laboratory-confirmed cases of gonorrhea (Neisseria gonorrhoeae) among females aged 15-44 years and annual gonorrhea incidence rate (cases per 100,000 females aged 15-44 years) with corresponding 95% confidence intervals by Chicago community area, for years 2000 – 2014. See the full description by clicking on the maroon "About" button on the right-hand side of the screen, and click on the PDF under "Attachments".
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ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data was reported at 8.900 % in 2013. This records a decrease from the previous number of 11.300 % for 2006. ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data is updated yearly, averaging 8.900 % from Dec 2001 (Median) to 2013, with 3 observations. The data reached an all-time high of 11.300 % in 2006 and a record low of 8.200 % in 2001. ML: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Women participating in the three decisions (own health care, major household purchases, and visiting family) is the percentage of currently married women aged 15-49 who say that they alone or jointly have the final say in all of the three decisions (own health care, large purchases and visits to family, relatives, and friends).; ; Demographic and Health Surveys (DHS); ;
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TwitterAccording to a survey of women carried out in the United Kingdom in 2022, ** percent of respondents had experienced not being taken seriously by a healthcare provider. Furthermore, around ** percent of women felt that when accessing healthcare, there was a lack of understanding of women's lives and experiences, while over a ***** reported a lack of understanding of women's bodies was an issue for them when accessing healthcare.
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Twitterhttps://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Women Employees, Private Education and Health Services (CES6500000010) from Jan 1964 to Sep 2025 about females, health, establishment survey, education, services, employment, and USA.
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Benin BJ: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data was reported at 36.300 % in 2018. This records a decrease from the previous number of 48.300 % for 2012. Benin BJ: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data is updated yearly, averaging 35.950 % from Dec 2001 (Median) to 2018, with 4 observations. The data reached an all-time high of 48.300 % in 2012 and a record low of 17.200 % in 2001. Benin BJ: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Benin – Table BJ.World Bank.WDI: Social: Health Statistics. Women participating in the three decisions (own health care, major household purchases, and visiting family) is the percentage of currently married women aged 15-49 who say that they alone or jointly have the final say in all of the three decisions (own health care, large purchases and visits to family, relatives, and friends).;Demographic and Health Surveys (DHS);;
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CV: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data was reported at 33.300 % in 2016. This records an increase from the previous number of 32.500 % for 2015. CV: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data is updated yearly, averaging 33.300 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 44.600 % in 1990 and a record low of 30.900 % in 2010. CV: Prevalence of Anemia among Women of Reproductive Age: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cabo Verde – Table CV.World Bank: Health Statistics. 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.; ; World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).; Weighted Average;
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Bolivia BO: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data was reported at 74.100 % in 2008. This records an increase from the previous number of 67.000 % for 2003. Bolivia BO: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data is updated yearly, averaging 70.550 % from Dec 2003 (Median) to 2008, with 2 observations. The data reached an all-time high of 74.100 % in 2008 and a record low of 67.000 % in 2003. Bolivia BO: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Social: Health Statistics. Women participating in the three decisions (own health care, major household purchases, and visiting family) is the percentage of currently married women aged 15-49 who say that they alone or jointly have the final say in all of the three decisions (own health care, large purchases and visits to family, relatives, and friends).;Demographic and Health Surveys (DHS);;
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Average annual maternal mortality rate** (2001–2011) and trends (JoinPoint Analyses for 2001–2011) pregnant women who gave birth in Wuhan.*Average annual maternal mortality rate are per 100,000.**APC = Annual percent change calculated by using joinpoint regression analysis.∧APC is significantly different from zero (two-side p
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TwitterFinancial overview and grant giving statistics of Health Center for Women
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TwitterAs of 2023, ** percent of women had employer-sponsored insurance and the percentage of uninsured women stood at *** percent. This statistic depicts the percentage of health insurance coverage among women in the United States from 2018 to 2023.
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Twitterhttps://digital.nhs.uk/about-nhs-digital/terms-and-conditionshttps://digital.nhs.uk/about-nhs-digital/terms-and-conditions
This report presents statistics on mother’s smoking status at time of delivery, at Clinical Commissioning Group (CCG), Sustainability and Transformation Partnership (STP), Region and national levels. This release includes provisional data for quarter 2 of 2020-21. Due to the coronavirus illness (COVID-19) disruption, it would seem that this is now starting to affect the quality and coverage of some of our statistics, such as an increase in non-submissions for some datasets. For the SATOD collection, there is a noticeable difference in the percentage of mothers who were smokers at the time of delivery in 20/21 from the previous year (from 10.4% to 9.8%). Therefore, data should be interpreted with care over the COVID-19 period. Please see data DQ table 1 for details of coverage issues given by submitters for this collection.
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TwitterThis dataset includes live births, birth rates, and fertility rates by Hispanic origin of mother in the United States since 1989. National data on births by Hispanic origin exclude data for Louisiana, New Hampshire, and Oklahoma in 1989; New Hampshire and Oklahoma in 1990; and New Hampshire in 1991 and 1992. Birth and fertility rates for the Central and South American population includes other and unknown Hispanic. Information on reporting Hispanic origin is detailed in the Technical Appendix for the 1999 public-use natality data file (see ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Dataset_Documentation/DVS/natality/Nat1999doc.pdf). SOURCES NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/). REFERENCES National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf. Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf. National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf. Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf. Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.
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From 1996 to 2000, the SWHS recruited close to 75,000 adult Chinese women from selected urban communities in Shanghai, China, with a 92% response rate. The study collected data on incidence rates of major cancers, as well as distributions of age, sex, educational level, and occupation, similar to those in the general population of urban Shanghai. All participants completed a detailed baseline survey and anthropometrics. This cohort of women is being followed via biennial in-person re-contact and periodic linkage to cancer and vital statistics registries.
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TwitterThis dataset includes percent distribution of births for females by age group in the United States since 1933.
The number of states in the reporting area differ historically. In 1915 (when the birth registration area was established), 10 states and the District of Columbia reported births; by 1933, 48 states and the District of Columbia were reporting births, with the last two states, Alaska and Hawaii, added to the registration area in 1959 and 1960, when these regions gained statehood. Reporting area information is detailed in references 1 and 2 below. Trend lines for 1909–1958 are based on live births adjusted for under-registration; beginning with 1959, trend lines are based on registered live births.
SOURCES
NCHS, National Vital Statistics System, birth data (see https://www.cdc.gov/nchs/births.htm); public-use data files (see https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm); and CDC WONDER (see http://wonder.cdc.gov/).
REFERENCES
National Office of Vital Statistics. Vital Statistics of the United States, 1950, Volume I. 1954. Available from: https://www.cdc.gov/nchs/data/vsus/vsus_1950_1.pdf.
Hetzel AM. U.S. vital statistics system: major activities and developments, 1950-95. National Center for Health Statistics. 1997. Available from: https://www.cdc.gov/nchs/data/misc/usvss.pdf.
National Center for Health Statistics. Vital Statistics of the United States, 1967, Volume I–Natality. 1969. Available from: https://www.cdc.gov/nchs/data/vsus/nat67_1.pdf.
Martin JA, Hamilton BE, Osterman MJK, et al. Births: Final data for 2015. National vital statistics reports; vol 66 no 1. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr66/nvsr66_01.pdf.
Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Drake P. Births: Final data for 2016. National Vital Statistics Reports; vol 67 no 1. Hyattsville, MD: National Center for Health Statistics. 2018. Available from: https://www.cdc.gov/nvsr/nvsr67/nvsr67_01.pdf.
Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Births: Final data for 2018. National vital statistics reports; vol 68 no 13. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_13.pdf.
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TwitterWomen's health funding by the NIH was around *** billion U.S. dollars during fiscal year 2023. This graph shows the actual women's health funding by the National Institutes for Health (NIH) from FY 2013 to FY 2023 and estimates for FY 2024 and FY 2025.