Crude birth rates, age-specific fertility rates and total fertility rates (live births), 2000 to most recent year.

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

The cyclical fertility index represents the number of children that 15-year-olds would give life before age 49 if they adopted fertility by age group observed during that period. The cyclical fertility index is calculated here over a 5-year period, starting from the fertility rates of women aged 15 to 49. It is the sum of fertility rates per five-year age group multiplied by 5. Fertility rates by age group reflect in the numerator the average annual number of live births for women in a given age group. The denominator is the average for the period analysed of the populations on 1 July of women in this same age group. The cyclical fertility index is an indicator of population renewal that is not influenced by the age structure of the population, unlike the crude birth rate. It is therefore an excellent comparative indicator of the fertility of a population. Population renewal is ensured if the number of girls in the child generation is equal to the number of women in the parent generation. In the absence of mortality, a woman must give birth to 2.05 children (2.05 and not 2 because she is born 105 boys per 100 girls) to replace a generation, either herself and the father.

Number of births per 1,000 women. Note:Teenage birth rates are calculated using the Australian female Estimated Resident Population (ERP) aged 15–19 as the denominator.

About this dataset

Context

The dataset tabulates the population of Oil City by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Oil City. The dataset can be utilized to understand the population distribution of Oil City by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Oil City. 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 Oil City.

Key observations

Largest age group (population): Male # 15-19 years (445) | Female # 35-39 years (416). 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 Oil City population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Oil City is shown in the following column.
• Population (Female): The female population in the Oil City 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 Oil City 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 Oil City Population by Gender. You can refer the same here

The Russian Fertility Database of the International Laboratory for Population and Health of HSE University contains fertility rates in Russia for the period from 1946 to 2022 and for women born in 1932-1988. The Russian Fertility Database is primarily oriented to the experts involved in demographic analysis. The data are presented in *.xlsx format.

All indicators presented in the database are calculated on the basis of population statistics data from the Federal State Statistics Service. Birth rates for 1946-1958 are calculated on the basis of the numbers of births by birth order and mother's age for 1946-1958 and population data for 1946-1958 presented in the book Andreev E.M., Darsky L.E., Kharkova T.L. (1998) Demographic History of Russia: 1927-1959. M.: Informatika. 187 p. Birth rates for 1959-2022 are calculated on the basis of the numbers of births by birth order and mother's age for 1959-2022 and data on the age distribution of the population for 1959-2023.

Live births by local authority of usual residence of mother, General Fertility Rates and Total Fertility Rates. The general fertility rate (GFR) is the number of live births per 1,000 women aged 15-44. Rates are based on the most up-to-date population estimates. The General Fertility Rate (GFR) is the number of live births per 1,000 women aged 15-44. The Total Fertility Rate (TFR) is the average number of live children that a group of women would bear if they experienced the age-specific fertility rates of the calendar year in question throughout their childbearing lifespan. The TFR has been calculated using the number of live births and the mid-year population estimates (sub-nationally) and the projections (nationally) for women by single year of age. This generally produces a better match of births to those at risk of having births. However, local authority level population estimates are only considered reliable in five-year age bands. Thus, especially in small local authorities, it should be noted that rates computed using single year of age data may produce spurious results. City of London has been grouped with Hackney after 2004. Read more on the ONS website ONS have also produces birth statistics for mid-year for small areas.

Fetal mortality occurs after 20 weeks of gestation and before labor. Infant mortality occurs before the first year of age and is a sum of Neonatal (the first 28 days after birth) and Postneonatal (from 28 days up to 1 year) mortality. Rates are calculated per every 1000 births; rates are not available for disaggregated race/ethnicities. Fetal and infant mortality values are available for given race/ethnicities. Connecticut Department of Public Health collects and reports data annually. CTData.org carries 1-, 3- and 5-Year aggregations.

Fetal mortality occurs after 20 weeks of gestation and before labor. Infant mortality occurs before the first year of age and is a sum of Neonatal (the first 28 days after birth) and Postneonatal (from 28 days up to 1 year) mortality. Rates are calculated per every 1000 births; rates are not available for disaggregated race/ethnicities. Fetal and infant mortality values are available for given race/ethnicities. Connecticut Department of Public Health collects and reports data annually. CTData.org carries 1-, 3- and 5-Year aggregations.

1. Database contents

The Russian Short-Term Mortality Fluctuations database (RusSTMF) contains a series of standardized and crude death rates for men, women and both sexes for Russia as a whole and its regions for the period from 2000 to 2021.

All the output indicators presented in the database are calculated based on data of deaths registered by the Vital Registry Office. The weekly death counts are calculated based on depersonalized individual data provided by the Russian Federal State Statistics Service (Rosstat) at the request of the HSE. Time coverage: 03.01.2000 (Week 1) – 31.12.2021 (Week 1148)

2. A brief description of the input data on deaths

Date of death: date of occurrence

Unit of time: week

First and last days of the week: Monday – Sunday

First and last week of the year: The weeks are organized according to ISO 8601:2004 guidelines. Each week of the year, including the first and last, contains 7 days. In order to get 7-day weeks, the days of previous years are included in this first week (if January 1 fell on Tuesday, Wednesday or Thursday) or in the last calendar week (if December 31 fell on Thursday, Friday or Saturday).

Age groups: the entire population

Sex: men, women, both sexes (men and women combined)

Restrictions and data changes: data on deaths in the Pskov region were excluded for weeks 9-13 of 2012

Note: Deaths with an unknown date of occurrence (unknown year, month, or day) account for about 0.3% of all deaths and are excluded from the calculation of week-age-specific and standardized death rates.

3. Description of the week-specific mortality rates data file

Week-specific standardized death rates for Russia as a whole and its regions are contained in a single data file presented in .csv format. The format of data allows its uploading into any system for statistical analysis. Each record (row) in the data file contains data for one calendar year, one week, one territory, one sex.

The decimal point is dot (.)

The first element of the row is the territory code ("PopCode" column), the second element is the year ("Year" column), the third element ("Week" column) is the week of the year, the fourth element ("Sex" column) is sex (F – female, M – male, B – both sexes combined). This is followed by a column "CDR" with the value of the crude death rate and "SDR" with the value of the standardized death rate. If the indicator cannot be calculated for some combination of year, sex, and territory, then the corresponding meaningful data elements in the data file are replaced with ".".

About this dataset

Context

The dataset tabulates the population of Oil Trough by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Oil Trough. The dataset can be utilized to understand the population distribution of Oil Trough by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Oil Trough. 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 Oil Trough.

Key observations

Largest age group (population): Male # 0-4 years (72) | Female # 15-19 years (16). 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 Oil Trough population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Oil Trough is shown in the following column.
• Population (Female): The female population in the Oil Trough 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 Oil Trough 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 Oil Trough Population by Gender. You can refer the same here

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update. The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates. The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used. Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical

This table contains national projections of immigrants population. Fertility of 1st generation immigrant mothers by the mother’s origin group.

Data available from: 2006 Frequency: discontinued as of 18 December 2008

Status of the figures All figures included in the table are forecast figures calculated.

Changes compared to the previous version 13 December 2006. The forecast has been adjusted on the basis of the most recent insights, the forecast period now runs from 2006 to 2050.

When are new figures coming? In December 2008, the new immigrant forecast came out.

Updates

• Notice of data discontinuation: Since the start of the pandemic, AP has reported case and death counts from data provided by Johns Hopkins University. Johns Hopkins University has announced that they will stop their daily data collection efforts after March 10. As Johns Hopkins stops providing data, the AP will also stop collecting daily numbers for COVID cases and deaths. The HHS and CDC now collect and visualize key metrics for the pandemic. AP advises using those resources when reporting on the pandemic going forward.

  • CDC Weekly case and death counts (national and state level)
  • CDC County level cases and deaths
  • HHS New hospital admissions
  • CDC NowCast COVID variant proportions (national and regional level)

• April 9, 2020

  • The population estimate data for New York County, NY has been updated to include all five New York City counties (Kings County, Queens County, Bronx County, Richmond County and New York County). This has been done to match the Johns Hopkins COVID-19 data, which aggregates counts for the five New York City counties to New York County.

• April 20, 2020

  • Johns Hopkins death totals in the US now include confirmed and probable deaths in accordance with CDC guidelines as of April 14. One significant result of this change was an increase of more than 3,700 deaths in the New York City count. This change will likely result in increases for death counts elsewhere as well. The AP does not alter the Johns Hopkins source data, so probable deaths are included in this dataset as well.

• April 29, 2020

  • The AP is now providing timeseries data for counts of COVID-19 cases and deaths. The raw counts are provided here unaltered, along with a population column with Census ACS-5 estimates and calculated daily case and death rates per 100,000 people. Please read the updated caveats section for more information.

• September 1st, 2020

  • Johns Hopkins is now providing counts for the five New York City counties individually.

• February 12, 2021

  • The Ohio Department of Health recently announced that as many as 4,000 COVID-19 deaths may have been underreported through the state’s reporting system, and that the "daily reported death counts will be high for a two to three-day period."
  • Because deaths data will be anomalous for consecutive days, we have chosen to freeze Ohio's rolling average for daily deaths at the last valid measure until Johns Hopkins is able to back-distribute the data. The raw daily death counts, as reported by Johns Hopkins and including the backlogged death data, will still be present in the new_deaths column.

• February 16, 2021

  - Johns Hopkins has reconciled Ohio's historical deaths data with the state.

  Overview

The AP is using data collected by the Johns Hopkins University Center for Systems Science and Engineering as our source for outbreak caseloads and death counts for the United States and globally.

The Hopkins data is available at the county level in the United States. The AP has paired this data with population figures and county rural/urban designations, and has calculated caseload and death rates per 100,000 people. Be aware that caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.

This data is from the Hopkins dashboard that is updated regularly throughout the day. Like all organizations dealing with data, Hopkins is constantly refining and cleaning up their feed, so there may be brief moments where data does not appear correctly. At this link, you’ll find the Hopkins daily data reports, and a clean version of their feed.

The AP is updating this dataset hourly at 45 minutes past the hour.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

Queries

Use AP's queries to filter the data or to join to other datasets we've made available to help cover the coronavirus pandemic

• Filter cases by state here

• Rank states by their status as current hotspots. Calculates the 7-day rolling average of new cases per capita in each state: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=481e82a4-1b2f-41c2-9ea1-d91aa4b3b1ac

• Find recent hotspots within your state by running a query to calculate the 7-day rolling average of new cases by capita in each county: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=b566f1db-3231-40fe-8099-311909b7b687&showTemplatePreview=true

• Join county-level case data to an earlier dataset released by AP on local hospital capacity here. To find out more about the hospital capacity dataset, see the full details.

• Pull the 100 counties with the highest per-capita confirmed cases here

• Rank all the counties by the highest per-capita rate of new cases in the past 7 days here. Be aware that because this ranks per-capita caseloads, very small counties may rise to the very top, so take into account raw caseload figures as well.

Interactive

The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.

@(https://datawrapper.dwcdn.net/nRyaf/15/)

Interactive Embed Code

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Caveats

• This data represents the number of cases and deaths reported by each state and has been collected by Johns Hopkins from a number of sources cited on their website.
• In some cases, deaths or cases of people who've crossed state lines -- either to receive treatment or because they became sick and couldn't return home while traveling -- are reported in a state they aren't currently in, because of state reporting rules.
• In some states, there are a number of cases not assigned to a specific county -- for those cases, the county name is "unassigned to a single county"
• This data should be credited to Johns Hopkins University's COVID-19 tracking project. The AP is simply making it available here for ease of use for reporters and members.
• Caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.
• Population estimates at the county level are drawn from 2014-18 5-year estimates from the American Community Survey.
• The Urban/Rural classification scheme is from the Center for Disease Control and Preventions's National Center for Health Statistics. It puts each county into one of six categories -- from Large Central Metro to Non-Core -- according to population and other characteristics. More details about the classifications can be found here.

Johns Hopkins timeseries data - Johns Hopkins pulls data regularly to update their dashboard. Once a day, around 8pm EDT, Johns Hopkins adds the counts for all areas they cover to the timeseries file. These counts are snapshots of the latest cumulative counts provided by the source on that day. This can lead to inconsistencies if a source updates their historical data for accuracy, either increasing or decreasing the latest cumulative count. - Johns Hopkins periodically edits their historical timeseries data for accuracy. They provide a file documenting all errors in their timeseries files that they have identified and fixed here

Attribution

This data should be credited to Johns Hopkins University COVID-19 tracking project

The 1997 the Kyrgyz Republic Demographic and Health Survey (KRDHS) is a nationally representative survey of 3,848 women age 15-49. Fieldwork was conducted from August to November 1997. The KRDHS was sponsored by the Ministry of Health (MOH), and was funded by the United States Agency for International Development. The Research Institute of Obstetrics and Pediatrics implemented the survey with technical assistance from the Demographic and Health Surveys (DHS) program. The purpose of the KRDHS was to provide data to the MOH on factors which determine the health status of women and children such as fertility, contraception, induced abortion, maternal care, infant mortality, nutritional status, and anemia. Some statistics presented in this report are currently available to the MOH from other sources. For example, the MOH collects and regularly publishes information on fertility, contraception, induced abortion and infant mortality. However, the survey presents information on these indices in a manner which is not currently available, i.e., by population subgroups such as those defined by age, marital duration, education, and ethnicity. Additionally, the survey provides statistics on some issues not previously available in the Kyrgyz Republic: for example, breastfeeding practices and anemia status of women and children. When considered together, existing MOH data and the KRDHS data provide a more complete picture of the health conditions in the Kyrgyz Republic than was previously available. A secondary objective of the survey was to enhance the capabilities of institutions in the Kyrgyz Republic to collect, process, and analyze population and health data. MAIN FINDINGS FERTILITY Fertility Rates. Survey results indicate a total fertility rate (TFR) for all of the Kyrgyz Republic of 3.4 children per woman. Fertility levels differ for different population groups. The TFR for women living in urban areas (2.3 children per woman) is substantially lower than for women living in rural areas (3.9). The TFR for Kyrgyz women (3.6 children per woman) is higher than for women of Russian ethnicity (1.5) but lower than Uzbek women (4.2). Among the regions of the Kyrgyz Republic, the TFR is lowest in Bishkek City (1.7 children per woman), and the highest in the East Region (4.3), and intermediate in the North and South Regions (3.1 and3.9, respectively). Time Trends. The KRDHS data show that fertility has declined in the Kyrgyz Republic in recent years. The decline in fertility from 5-9 to 0-4 years prior to the survey increases with age, from an 8 percent decline among 20-24 year olds to a 38 percent decline among 35-39 year olds. The declining trend in fertility can be seen by comparing the completed family size of women near the end of their childbearing years with the current TFR. Completed family size among women 40-49 is 4.6 children which is more than one child greater than the current TFR (3.4). Birth Intervals. Overall, 30 percent of births in the Kyrgyz Republic take place within 24 months of the previous birth. The median birth interval is 31.9 months. Age at Onset of Childbearing. The median age at which women in the Kyrgyz Republic begin childbearing has been holding steady over the past two decades at approximately 21.6 years. Most women have their first birth while in their early twenties, although about 20 percent of women give birth before age 20. Nearly half of married women in the Kyrgyz Republic (45 percent) do not want to have more children. Additional one-quarter of women (26 percent) want to delay their next birth by at least two years. These are the women who are potentially in need of some method of family planning. FAMILY PLANNING Ever Use. Among currently married women, 83 percent report having used a method of contraception at some time. The women most likely to have ever used a method of contraception are those age 30-44 (among both currently married and all women). Current Use. Overall, among currently married women, 60 percent report that they are currently using a contraceptive method. About half (49 percent) are using a modern method of contraception and another 11 percent are using a traditional method. The IUD is by far the most commonly used method; 38 percent of currently married women are using the IUD. Other modern methods of contraception account for only a small amount of use among currently married women: pills (2 percent), condoms (6 percent), and injectables and female sterilization (1 and 2 percent, respectively). Thus, the practice of family planning in the Kyrgyz Republic places high reliance on a single method, the IUD. Source of Methods. The vast majority of women obtain their contraceptives through the public sector (97 percent): 35 percent from a government hospital, and 36 percent from a women counseling center. The source of supply of the method depends on the method being used. For example, most women using IUDs obtain them at women counseling centers (42 percent) or hospitals (39 percent). Government pharmacies supply 46 percent of pill users and 75 percent of condom users. Pill users also obtain supplies from women counseling centers or (33 percent). Fertility Preferences. A majority of women in the Kyrgyz Republic (45 percent) indicated that they desire no more children. By age 25-29, 20 percent want no more children, and by age 30-34, nearly half (46 percent) want no more children. Thus, many women come to the preference to stop childbearing at relatively young ages-when they have 20 or more potential years of childbearing ahead of them. For some of these women, the most appropriate method of contraception may be a long-acting method such as female sterilization. However, there is a deficiency of use of this method in the Kyrgyz Republic. In the interests of providing a broad range of safe and effective methods, information about and access to sterilization should be increased so that individual women can make informed decisions about using this method. INDUCED ABORTION Abortion Rates. From the KRDHS data, the total abortion rate (TAR)-the number of abortions a woman will have in her lifetime based on the currently prevailing abortion rates-was calculated. For the Kyrgyz Republic, the TAR for the period from mid-1994 to mid-1997 is 1.6 abortions per woman. The TAR for the Kyrgyz Republic is lower than recent estimates of the TAR for other areas of the former Soviet Union such as Kazakhstan (1.8), and Yekaterinburg and Perm in Russia (2.3 and 2.8, respectively), but higher than for Uzbekistan (0.7). The TAR is higher in urban areas (2.1 abortions per woman) than in rural areas (1.3). The TAR in Bishkek City is 2.0 which is two times higher than in other regions of the Kyrgyz Republic. Additionally the TAR is substantially lower among ethnic Kyrgyz women (1.3) than among women of Uzbek and Russian ethnicities (1.9 and 2.2 percent, respectively). INFANT MORTALITY In the KRDHS, infant mortality data were collected based on the international definition of a live birth which, irrespective of the duration of pregnancy, is a birth that breathes or shows any sign of life (United Nations, 1992). Mortality Rates. For the five-year period before the survey (i.e., approximately mid-1992 to mid1997), infant mortality in the Kyrgyz Republic is estimated at 61 infant deaths per 1,000 births. The estimates of neonatal and postneonatal mortality are 32 and 30 per 1,000. The MOH publishes infant mortality rates annually but the definition of a live birth used by the MOH differs from that used in the survey. As is the case in most of the republics of the former Soviet Union, a pregnancy that terminates at less than 28 weeks of gestation is considered premature and is classified as a late miscarriage even if signs of life are present at the time of delivery. Thus, some events classified as late miscarriages in the MOH system would be classified as live births and infant deaths according to the definitions used in the KRDHS. Infant mortality rates based on the MOH data for the years 1983 through 1996 show a persistent declining trend throughout the period, starting at about 40 per 1,000 in the early 1980s and declining to 26 per 1,000 in 1996. This time trend is similar to that displayed by the rates estimated from the KRDHS. Thus, the estimates from both the KRDHS and the Ministry document a substantial decline in infant mortality; 25 percent over the period from 1982-87 to 1992-97 according to the KRDHS and 28 percent over the period from 1983-87 to 1993-96 according to the MOH estimates. This is strong evidence of improvements in infant survivorship in recent years in the Kyrgyz Republic. It should be noted that the rates from the survey are much higher than the MOH rates. For example, the KRDHS estimate of 61 per 1,000 for the period 1992-97 is twice the MOH estimate of 29 per 1,000 for 1993-96. Certainly, one factor leading to this difference are the differences in the definitions of a live birth and infant death in the KRDHS survey and in the MOH protocols. A thorough assessment of the difference between the two estimates would need to take into consideration the sampling variability of the survey's estimate. However, given the magnitude of the difference, it is likely that it arises from a combination of definitional and methodological differences between the survey and MOH registration system. MATERNAL AND CHILD HEALTH The Kyrgyz Republic has a well-developed health system with an extensive infrastructure of facilities that provide maternal care services. This system includes special delivery hospitals, the obstetrics and gynecology departments of general hospitals, women counseling centers, and doctor's assistant/midwife posts (FAPs). There is an extensive network of FAPs throughout the rural areas. Delivery. Virtually all births in the Kyrgyz Republic (96 percent) are delivered at health facilities: 95 percent in delivery hospitals and another 1 percent in either general hospitals

The 1995 Uganda Demographic and Health Survey (UDHS-II) is a nationally-representative survey of 7,070 women age 15-49 and 1,996 men age 15-54. The UDHS was designed to provide information on levels and trends of fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. Fieldwork for the UDHS took place from late-March to mid-August 1995. The survey was similar in scope and design to the 1988-89 UDHS. Survey data show that fertility levels may be declining, contraceptive use is increasing, and childhood mortality is declining; however, data also point to several remaining areas of challenge. The 1995 UDHS was a follow-up to a similar survey conducted in 1988-89. In addition to including most of the same questions included in the 1988-89 UDHS, the 1995 UDHS added more detailed questions on AIDS and maternal mortality, as well as incorporating a survey of men. The general objectives of the 1995 UDHS are to: provide national level data which will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; analyse the direct and indirect factors which determine the level and trends of fertility; measure the level of contraceptive knowledge and practice (of both women and men) by method, by urban-rural residence, and by region; collect reliable data on maternal and child health indicators; immunisation, prevalence, and treatment of diarrhoea and other diseases among children under age four; antenatal visits; assistance at delivery; and breastfeeding; assess the nutritional status of children under age four and their mothers by means of anthropometric measurements (weight and height), and also child feeding practices; and assess among women and men the prevailing level of specific knowledge and attitudes regarding AIDS and to evaluate patterns of recent behaviour regarding condom use. MAIN RESULTS Fertility: Fertility Trends. UDHS data indicate that fertility in Uganda may be starting to decline. The total fertility rate has declined from the level of 7.1 births per woman that prevailed over the last 2 decades to 6.9 births for the period 1992-94. The crude birth rate for the period 1992-94 was 48 live births per I000 population, slightly lower than the level of 52 observed from the 1991 Population and Housing Census. For the roughly 80 percent of the country that was covered in the 1988-89 UDHS, fertility has declined from 7.3 to 6.8 births per woman, a drop of 7 percent over a six and a half year period. Birth Intervals. The majority of Ugandan children (72 percent) are born after a "safe" birth interval (24 or more months apart), with 30 percent born at least 36 months after a prior birth. Nevertheless, 28 percent of non-first births occur less than 24 months after the preceding birth, with 10 percent occurring less than 18 months since the previous birth. The overall median birth interval is 29 months. Fertility Preferences. Survey data indicate that there is a strong desire for children and a preference for large families in Ugandan society. Among those with six or more children, 18 percent of married women want to have more children compared to 48 percent of married men. Both men and women desire large families. Family planning: Knowledge of Contraceptive Methods. Knowledge of contraceptive methods is nearly universal with 92 percent of all women age 15-49 and 96 percent of all men age 15-54 knowing at least one method of family planning. Increasing Use of Contraception. The contraceptive prevalence rate in Uganda has tripled over a six-year period, rising from about 5 percent in approximately 80 percent of the country surveyed in 1988-89 to 15 percent in 1995. Source of Contraception. Half of current users (47 percent) obtain their methods from public sources, while 42 percent use non-governmental medical sources, and other private sources account for the remaining 11 percent. Maternal and child health: High Childhood Mortality. Although childhood mortality in Uganda is still quite high in absolute terms, there is evidence of a significant decline in recent years. Currently, the direct estimate of the infant mortality rate is 81 deaths per 1,000 births and under five mortality is 147 per 1,000 births, a considerable decline from the rates of 101 and 180, respectively, that were derived for the roughly 80 percent of the country that was covered by the 1988-89 UDHS. Childhood Vaccination Coverage. One possible reason for the declining mortality is improvement in childhood vaccination coverage. The UDHS results show that 47 percent of children age 12-23 months are fully vaccinated, and only 14 percent have not received any vaccinations. Childhood Nutritional Status. Overall, 38 percent of Ugandan children under age four are classified as stunted (low height-for-age) and 15 percent as severely stunted. About 5 percent of children under four in Uganda are wasted (low weight-for-height); 1 percent are severely wasted. Comparison with other data sources shows little change in these measures over time. AIDS: Virtually all women and men in Uganda are aware of AIDS. About 60 percent of respondents say that limiting the number of sexual partners or having only one partner can prevent the spread of disease. However, knowledge of ways to avoid AIDS is related to respondents' education. Safe patterns of sexual behaviour are less commonly reported by respondents who have little or no education than those with more education. Results show that 65 percent of women and 84 percent of men believe that they have little or no chance of being infected. Availability of Health Services. Roughly half of women in Uganda live within 5 km of a facility providing antenatal care, delivery care, and immunisation services. However, the data show that children whose mothers receive both antenatal and delivery care are more likely to live within 5 km of a facility providing maternal and child health (MCH) services (70 percent) than either those whose mothers received only one of these services (46 percent) or those whose mothers received neither antenatal nor delivery care (39 percent).

Analysis of ‘COVID-19 Cases and Deaths by Race/Ethnicity’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3fdc6593-c708-4a6a-8073-5ca862caa279 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.

The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.

The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf

Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.

Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More infor

--- Original source retains full ownership of the source dataset ---

India fertility rate for 2025 is 2.11, a 0.8% decline from 2024.

<ul style='margin-top:20px;'>

<li>India fertility rate for 2024 was <strong>2.12</strong>, a <strong>7.44% increase</strong> from 2023.</li>
<li>India fertility rate for 2023 was <strong>1.98</strong>, a <strong>0.95% decline</strong> from 2022.</li>
<li>India fertility rate for 2022 was <strong>1.99</strong>, a <strong>0.99% decline</strong> from 2021.</li>
</ul>Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.

This is a publication on maternity activity in English NHS hospitals. This report examines data relating to delivery and birth episodes in 2022-23, and the booking appointments for these deliveries. This annual publication covers the financial year ending March 2023. Data is included from both the Hospital Episodes Statistics (HES) data warehouse and the Maternity Services Data Set (MSDS). HES contains records of all admissions, appointments and attendances for patients admitted to NHS hospitals in England. The HES data used in this publication are called 'delivery episodes'. The MSDS collects records of each stage of the maternity service care pathway in NHS-funded maternity services, and includes information not recorded in HES. The MSDS is a maturing, national-level dataset. In April 2019 the MSDS transitioned to a new version of the dataset. This version, MSDS v2.0, is an update that introduced a new structure and content - including clinical terminology, in order to meet current clinical practice and incorporate new requirements. It is designed to meet requirements that resulted from the National Maternity Review, which led to the publication of the Better Births report in February 2016. This is the fourth publication of data from MSDS v2.0 and data from 2019-20 onwards is not directly comparable to data from previous years. This publication shows the number of HES delivery episodes during the period, with a number of breakdowns including by method of onset of labour, delivery method and place of delivery. It also shows the number of MSDS deliveries recorded during the period, with breakdowns including the baby's first feed type, birthweight, place of birth, and breastfeeding activity; and the mothers' ethnicity and age at booking. There is also data available in a separate file on breastfeeding at 6 to 8 weeks. The count of Total Babies includes both live and still births, and previous changes to how Total Babies and Total Deliveries were calculated means that comparisons between 2019-20 MSDS data and later years should be made with care. Information on how all measures are constructed can be found in the HES Metadata and MSDS Metadata files provided below. In this publication we have also included an interactive Power BI dashboard to enable users to explore key NHS Maternity Statistics measures. The purpose of this publication is to inform and support strategic and policy-led processes for the benefit of patient care. This report will also be of interest to researchers, journalists and members of the public interested in NHS hospital activity in England. Any feedback on this publication or dashboard can be provided to enquiries@nhsdigital.nhs.uk, under the subject “NHS Maternity Statistics”.

The 1998 Philippines National Demographic and Health Survey (NDHS). is a nationally-representative survey of 13,983 women age 15-49. The NDHS was designed to provide information on levels and trends of fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. It was implemented by the National Statistics Office in collaboration with the Department of Health (DOH). Macro International Inc. of Calverton, Maryland provided technical assistance to the project, while financial assistance was provided by the U.S. Agency for International Development (USAID) and the DOH. Fieldwork for the NDHS took place from early March to early May 1998. The primary objective of the NDHS is to Provide up-to-date information on fertility levels; determinants of fertility; fertility preferences; infant and childhood mortality levels; awareness, approval, and use of family planning methods; breastfeeding practices; and maternal and child health. This information is intended to assist policy makers and program managers in evaluating and designing programs and strategies for improving health and family planning services in the country. MAIN RESULTS Survey data generally confirm patterns observed in the 1993 National Demographic Survey (NDS), showing increasing contraceptive use and declining fertility. FERTILITY Fertility Decline. The NDHS data indicate that fertility continues to decline gradually but steadily. At current levels, women will give birth an average of 3.7 children per woman during their reproductive years, a decline from the level of 4.1 recorded in the 1993 NDS. A total fertility rate of 3.7, however, is still considerably higher than the rates prevailing in neighboring Southeast Asian countries. Fertility Differentials. Survey data show that the large differential between urban and rural fertility levels is widening even further. While the total fertility rate in urban areas declined by about 15 percent over the last five years (from 3.5 to 3.0), the rate among rural women barely declined at all (from 4.8 to 4.7). Consequently, rural women give birth to almost two children more than urban women. Significant differences in fertility levels by region still exist. For example, fertility is more than twice as high in Eastern Visayas and Bicol Regions (with total fertility rates well over 5 births per woman) than in Metro Manila (with a rate of 2.5 births per woman). Fertility levels are closely related to women's education. Women with no formal education give birth to an average of 5.0 children in their lifetime, compared to 2.9 for women with at least some college education. Women with either elementary or high school education have intermediate fertility rates. Family Size Norms. One reason that fertility has not fallen more rapidly is that women in the Philippines still want moderately large families. Only one-third of women say they would ideally like to have one or two children, while another third state a desire for three children. The remaining third say they would choose four or more children. Overall, the mean ideal family size among all women is 3.2 children, identical to the mean found in 1993. Unplanned Fertility. Another reason for the relatively high fertility level is that unplanned pregnancies are still common in the Philippines. Overall, 45 percent of births in the five years prior to the survey were reported to be unplanned; 27 percent were mistimed (wanted later) and 18 percent were unwanted. If unwanted births could be eliminated altogether, the total fertility rate in the Philippines would be 2.7 births per woman instead of the actual level of 3.7. Age at First Birth. Fertility rates would be even higher if Filipino women did not have a pattem of late childbearing. The median age at first birth is 23 years in the Philippines, considerably higher than in most other countries. Another factor that holds down the overall level of fertility is the fact that about 9 or 10 percent of women never give birth, higher than the level of 3-4 percent found in most developing countries. FAMILY PLANNING Increasing Use of Contraception. A major cause of declining fertility in the Philippines has been the gradual but fairly steady increase in contraceptive use over the last three decades. The contraceptive prevalence rate has tripled since 1968, from 15 to 47 percent of married women. Although contraceptive use has increased since the 1993 NDS (from 40 to 47 percent of married women), comparison with the series of nationally representative Family Planning Surveys indicates that there has been a levelling-off in family planning use in recent years. Method Mix. Use of traditional methods of family planning has always accounted for a relatively high proportion of overall use in the Philippines, and data from the 1998 NDHS show the proportion holding steady at about 40 percent. The dominant changes in the "method mix" since 1993 have been an increase in use of injectables and traditional methods such as calendar rhythm and withdrawal and a decline in the proportions using female sterilization. Despite the decline in the latter, female sterilization still is the most widely used method, followed by the pill. Differentials in Family Planning Use. Differentials in current use of family planning in the 16 administrative regions of the country are large, ranging from 16 percent of married women in ARMM to 55 percent of those in Southern Mindanao and Central Luzon. Contraceptive use varies considerably by education of women. Only 15 percent of married women with no formal education are using a method, compared to half of those with some secondary school. The urban-rural gap in contraceptive use is moderate (51 vs. 42 percent, respectively). Knowledge of Contraception. Knowledge of contraceptive methods and supply sources has been almost universal in the Philippines for some time and the NDHS results indicate that 99 percent of currently married women age 15-49 have heard of at least one method of family planning. More than 9 in 10 married women know the pill, IUD, condom, and female sterilization, while about 8 in 10 have heard of injectables, male sterilization, rhythm, and withdrawal. Knowledge of injectables has increased far more than any other method, from 54 percent of married women in 1993 to 89 percent in 1998. Unmet Need for Family Planning. Unmet need for family planning services has declined since I993. Data from the 1993 NDS show that 26 percent of currently married women were in need of services, compared with 20 percent in the 1998 NDHS. A little under half of the unmet need is comprised of women who want to space their next birth, while just over half is for women who do not want any more children (limiters). If all women who say they want to space or limit their children were to use methods, the contraceptive prevalence rate could be increased from 47 percent to 70 percent of married women. Currently, about three-quarters of this "total demand" for family planning is being met. Discontinuation Rates. One challenge for the family planning program is to reduce the high levels of contraceptive discontinuation. NDHS data indicate that about 40 percent of contraceptive users in the Philippines stop using within 12 months of starting, almost one-third of whom stop because of an unwanted pregnancy (i.e., contraceptive failure). Discontinuation rates vary by method. Not surprisingly, the rates for the condom (60 percent), withdrawal (46 percent), and the pill (44 percent) are considerably higher than for the 1UD (14 percent). However, discontinuation rates for injectables are relatively high, considering that one dose is usually effective for three months. Fifty-two percent of injection users discontinue within one year of starting, a rate that is higher than for the pill. MATERNAL AND CHILD HEALTH Childhood Mortality. Survey results show that although the infant mortality rate remains unchanged, overall mortality of children under five has declined somewhat in recent years. Under-five mortality declined from 54 deaths per 1,000 births in 1988-92 to 48 for the period 1993-97. The infant mortality rate remained stable at about 35 per 1,000 births. Childhood Vaccination Coverage. The 1998 NDHS results show that 73 percent of children 12- 23 months are fully vaccinated by the date of the interview, almost identical to the level of 72 percent recorded in the 1993 NDS. When the data are restricted to vaccines received before the child's first birthday, however, only 65 percent of children age 12-23 months can be considered to be fully vaccinated. Childhood Health. The NDHS provides some data on childhood illness and treatment. Approximately one in four children under age five had a fever and 13 percent had respiratory illness in the two weeks before the survey. Of these, 58 percent were taken to a health facility for treatment. Seven percent of children under five were reported to have had diarrhea in the two weeks preceeding the survey. The fact that four-fifths of children with diarrhea received some type of oral rehydration therapy (fluid made from an ORS packet, recommended homemade fluid, or increased fluids) is encouraging. Breastfeeding Practices. Almost all Filipino babies (88 percent) are breastfed for some time, with a median duration of breastfeeding of 13 months. Although breastfeeding has beneficial effects on both the child and the mother, NDHS data indicate that supplementation of breastfeeding with other liquids and foods occurs too early in the Philippines. For example, among newborns less than two months of age, 19 percent were already receiving supplemental foods or liquids other than water. Maternal Health Care. NDHS data point to several areas regarding maternal health care in which improvements could be made. Although most Filipino mothers (86 percent) receive prenatal care from a doctor, nurse, or midwife, tetanus toxoid coverage is far from universal and