This data collection consists of three data files, which can be used to determine infant mortality rates. The first file provides linked records of live births and deaths of children born in the United States in 1990 (residents and nonresidents). This file is referred to as the "Numerator" file. The second file consists of live births in the United States in 1990 and is referred to as the "Denominator-Plus" file. Variables include year of birth, state and county of birth, characteristics of the infant (age, sex, race, birth weight, gestation), characteristics of the mother (origin, race, age, education, marital status, state of birth), characteristics of the father (origin, race, age, education), pregnancy items (prenatal care, live births), and medical data. Beginning in 1989, a number of items were added to the U.S. Standard Certificate of Birth. These changes and/or additions led to the redesign of the linked file record layout for this series and to other changes in the linked file. In addition, variables from the numerator file have been added to the denominator file to facilitate processing, and this file is now called the "Denominator-Plus" file. The additional variables include age at death, underlying cause of death, autopsy, and place of accident. Other new variables added are infant death identification number, exact age at death, day of birth and death, and month of birth and death. The third file, the "Unlinked" file, consists of infant death records that could not be linked to their corresponding birth records.

This data presents national-level provisional maternal mortality rates based on a current flow of mortality and natality data in the National Vital Statistics System. Provisional rates which are an early estimate of the number of maternal deaths per 100,000 live births, are shown as of the date specified and may not include all deaths and births that occurred during a given time period (see Technical Notes).

A maternal death is the death of a woman while pregnant or within 42 days of termination of pregnancy irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes. In this data visualization, maternal deaths are those deaths with an underlying cause of death assigned to International Statistical Classification of Diseases, 10th Revision (ICD-10) code numbers A34, O00–O95, and O98–O99.

The provisional data include reported 12 month-ending provisional maternal mortality rates overall, by age, and by race and Hispanic origin. Provisional maternal mortality rates presented in this data visualization are for “12-month ending periods,” defined as the number of maternal deaths per 100,000 live births occurring in the 12-month period ending in the month indicated. For example, the 12-month ending period in June 2020 would include deaths and births occurring from July 1, 2019, through June 30, 2020. Evaluation of trends over time should compare estimates from year to year (June 2020 and June 2021), rather than month to month, to avoid overlapping time periods. In the visualization and in the accompanying data file, rates based on death counts less than 20 are suppressed in accordance with current NCHS standards of reliability for rates. Death counts between 1-9 in the data file are suppressed in accordance with National Center for Health Statistics (NCHS) confidentiality standards.

Provisional data presented on this page will be updated on a quarterly basis as additional records are received. Previously released estimates are revised to include data and record updates received since the previous release. As a result, the reliability of estimates for a 12-month period ending with a specific month will improve with each quarterly release and estimates for previous time periods may change as new data and updates are received.

This dataset of U.S. mortality trends since 1900 highlights the differences in age-adjusted death rates and life expectancy at birth by race and sex. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Life expectancy data are available up to 2017. Due to changes in categories of race used in publications, data are not available for the black population consistently before 1968, and not at all before 1960. More information on historical data on age-adjusted death rates is available at https://www.cdc.gov/nchs/nvss/mortality/hist293.htm. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.

For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.

ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

Geographic coverage

National Coverage

Universe

The target population is all births recorded on the NPR between 1998 and 2010 for South African citizens and permanent residents, regardless of which year the birth occurred. All births that occurred in South Africa with parents being non-South African citizens or not permanent residents were excluded.

Sampling procedure

The registration of births in South Africa is governed by the Births and Deaths Registration Act, 1992 (Act No. 51 of 1992), as amended, and is administered by the Department of Home Affairs (DHA) using Form DHA-24 (Notice of birth), which recently replaced Form BI-24 that was previously used. Notice of the birth must be given by one of the parents or; if neither parent is available to do so, the person having charge of the child or a person requested by the parents to do so. The person requested to register the birth must have a written mandate from the child's parents which must also include the reasons why neither of the parents is in a position to register the birth. The birth of a child outside the country; where at least one parent is a South African citizen; can be registered at any South African Mission abroad.Documentary proof in the form of a birth certificate of the foreign country must accompany the Notice of Birth.

The Act states that a child must be registered within 30 days of birth. Where the notice of a birth is given after the expiration of 30 days from the date of the birth, the Director-General may demand that reasons for the late notice be furnished and that the fingerprints be taken of the person whose notice of birth is given. Where the notice of a birth is given for a person aged 15 years and older, the birth shall be registered if it complies with the prescribed requirements for a late registration of birth.

Following the registration of a birth, a birth certificate is issued by the DHA. Citizens and permanent residents receive computer-printed abridged birth certificates and non-citizens receive handwritten certificates. The information of South African citizens and permanent residents is captured on the National Population Register (NPR).

The following persons and particulars are eligible to be included on the NPR:

• All children born of South African citizens and permanent residents when the notice of the birth is given within one year after the birth of the child.

• All children born of South African citizens and permanent residents when the notice of the birth is given one year after the birth of the child; together with the prescribed requirement for a late registration of birth.

• All South African citizens and permanent residents who, upon attainment of the age of 16, applied for and were granted identification cards (or books).

• All South African citizens and permanent residents who die at any age after birth.

• All South African citizens and permanent residents who depart permanently from South Africa.

The DHA captures information on places based on magisterial districts using the twelfth edition of the Standard Code List of Areas (Central Statistics Services, 1995). Stats SA then recodes the magisterial districts into district councils (DCs), metropolitan areas (metros) and provinces based on the 2011 municipal boundaries. The data sets for 1998 to 2010 have all been recoded according to the 2011 municipal boundaries.

It should be noted that the distribution of births by DCs, metros and provinces are approximate figures; as there was no perfect match of magisterial districts for all DCs, metros and provinces since some magisterial districts are situated in more than one DC, metro or province. Such magisterial districts were allocated to the district council where the majority of the land area falls (see the folder on maps). The only exception was with Nigel in Gauteng province. The majority of the land area of Nigel magisterial district is in Sedibeng district council (which is mainly farm areas and therefore sparsely populated) while the majority of the population lives in Ekurhuleni metropolitan area. As such, Nigel was classified to Ekurhuleni and not Sedibeng.

Magisterial district of birth refers to the district of birth occurrence for births registered before 15 years of age. For those that were registered from 15 years of age, district refers to the district of birth registration. Furthermore, from 2009, the processing of late birth registrations from age 15 were centralised at the DHA head office in Pretoria. As such, the late birth registrations processed in Pretoria from 15 years have a district code of Pretoria; even if they occurred in other areas. There were a few exceptional cases which were registered in Pretoria; but were not captured using the Pretoria code.

Mode of data collection

Other [oth]

Research instrument

NOTICE OF BIRTH - [Births and Deaths Registration Act 51 of 1992]

A. DETAILS OF THE CHILD

B. DETAILS OF FATHER (PARENT A)

C. DETAILS OF MOTHER (PARENT B)

D. ACKNOWLEDGEMENT OF PATERNITY OF A CHILD BORN OUT OF WEDLOCK

E. DETAILS OF THE LEGAL GUARDIAN/SOCIAL WORKER*

F. DECLARATION

G. FOR OFFICIAL USE ONLY - OFFICE OF ORIGIN

Cleaning operations

Data capturing of information on births is done by DHA officials. The data is captured directly onto the Population Register Database at Nucleus Bureau. These transactions are used to update the database of the NPR and the population register database. As soon as the DHA has captured the data; the data is made available on the mainframe. The data is then downloaded via ftp; or collected from the State Information Technology Agency (SITA) written on a CD by Stats SA. For the purpose of producing vital statistics, the following system is followed: all the civil transactions carried out at all DHA offices are written onto a cassette every day. At the end of every month, a combined set of cassettes is created containing all the transactions done for the month. These transactions are downloaded and the birth transactions are extracted for processing at Stats SA. The year in which the births are registered is the registration year. Using this information, Stats SA provides a breakdown of the registered births according to the year in which the births occurred.

While birth information sent to Stats SA is the same as that in the population register, there is a difference in the format between the two. On one hand, Stats SA’s data are based on births registered during the year (registration-based), while on the other hand, entries in the population register reflect the date of birth.

Data appraisal

Users are cautioned on the following limitations of the data:

• Father’s age had a high percentage of cases where information was unspecified or unknown for all the years.
• Data for 1998 and 1999 have incorrect information on month of birth, which could not be resolved.

Note: - Unknown : refers to cases where the answer provided is not correct or not possible given the options available. - Unspecified: refers to cases where no response was given.

Early Prenatal Care - This indicator shows the percentage of pregnant women who receive prenatal care beginning in the first trimester. Inadequate prenatal care services have been linked to higher rates of infant mortality, low birth weight and pre-term deliveries. While Maryland as a whole ranks better than the National average and the Healthy People 2020 Target, disparities still exist. Due to the change in methodology for collecting information on the Maryland birth certificate, data collected in 2010 and after are not comparable to data collected in earlier years.

This administrative dataset provides descriptive information about the families and children served through the federal Child Care and Development Fund (CCDF). CCDF dollars are provided to states, territories, and tribes to provide assistance to low-income families receiving or in transition from temporary public assistance, to obtain quality child care so they can work, or depending on their state's policy, to attend training or receive education. The Personal Responsibility and Work Opportunity Act of 1996 requires states and territories to collect information on all family units receiving assistance through the CCDF and to submit monthly case-level data to the Office of Child Care. States are permitted to report case-level data for the entire population, or a sample of the population, under approved sampling guidelines. The Summary Records file contains monthly state-level summary information including the number of families served. The Family Records file contains family-level data including single parent status of the head of household, monthly co-payment amount, date on which child care assistance began, reasons for care (e.g., employment, training/education, protective services, etc.), income used to determine eligibility, source of income, and the family size on which eligibility is based. The Child Records file contains child-level data including ethnicity, race, and date of birth. The Setting Records file contains information about the type of child care setting, the total amount paid to the provider, and the total number of hours of care received by the child. The Pooling Factor file provides state-level data on the percentage of child care funds that is provided through the CCDF, the federal Head Start region the grantee (state) is in and is monitored by, and the state FIPS code for the grantee. Units of Response: United States and Territories, CCDF Family Recipients, CCDF Children Recipients Type of Data: Administrative Tribal Data: No Periodicity: Annual Demographic Indicators: Ethnicity;Household Income;Household Size;Race SORN: Not Applicable Data Use Agreement: Not Applicable Data Use Agreement Location: https://www.icpsr.umich.edu/rpxlogin Granularity: Family;Individual Spatial: United States Geocoding: Tribe

This data collection provides net migration estimates by age, race, and sex for counties of the United States. Population data are included along with absolute net migration data and net migration ratios (rates) for the period 1970-1980. Summary records for states, divisions, regions and the United States are also supplied. Several data categories are presented in the collection. Vital Statistics data tabulate births by sex and race (white and non white) for the periods 1970-1974 and 1975-1979 and deaths by race from 1970-1979 as well as adjusted total population for 1970 and 1980 by race. The Enumerated and Adjusted 1970 and 1980 Population categories offer population totals by race and sex and further subdivide these totals into 16 5-year age ranges. Net Migration Estimates and Net Migration Rates are available also, with totals by sex and race presented along with the 16 age divisions.

Introduction This report presents projections of population from 2015 to 2025 by age and sex for Illinois, Chicago and Illinois counties produced for the Certificate of Need (CON) Program. As actual future population trends are unknown, the projected numbers should not be considered a precise prediction of the future population; rather, these projections, calculated under a specific set of assumptions, indicate the levels of population that would result if our assumptions about each population component (births, deaths and net migration) hold true. The assumptions used in this report, and the details presented below, generally assume a continuation of current trends. Methodology These projections were produced using a demographic cohort-component projection model. In this model, each component of population change – birth, death and net migration – is projected separately for each five-year birth cohort and sex. The cohort – component method employs the following basic demographic balancing equation: P1 = P0 + B – D + NM Where: P1 = Population at the end of the period; P0 = Population at the beginning of the period; B = Resident births during the period; D = Resident deaths during the period; and NM = Net migration (Inmigration – Outmigration) during the period. The model roughly works as follows: for every five-year projection period, the base population, disaggregated by five-year age groups and sex, is “survived” to the next five-year period by applying the appropriate survival rates for each age and sex group; next, net migrants by age and sex are added to the survived population. The population under 5 years of age is generated by applying age specific birth rates to the survived females in childbearing age (15 to 49 years). Base Population These projections began with the July 1, 2010 population estimates by age and sex produced by the U.S. Census Bureau. The most recent census population of April 1, 2010 was the base for July 1, 2010 population estimates. Special Populations In 19 counties, the college dormitory population or adult inmates in correctional facilities accounted for 5 percent or more of the total population of the county; these counties were considered as special counties. There were six college dorm counties (Champaign, Coles, DeKalb, Jackson, McDonough and McLean) and 13 correctional facilities counties (Bond, Brown, Crawford, Fayette, Fulton, Jefferson, Johnson, Lawrence, Lee, Logan, Montgomery, Perry and Randolph) that qualified as special counties. When projecting the population, these special populations were first subtracted from the base populations for each special county; then they were added back to the projected population to produce the total population projections by age and sex. The base special population by age and sex from the 2010 population census was used for this purpose with the assumption that this population will remain the same throughout each projection period. Mortality Future deaths were projected by applying age and sex specific survival rates to each age and sex specific base population. The assumptions on survival rates were developed on the basis of trends of mortality rates in the individual life tables constructed for each level of geography for 1989-1991, 1999-2001 and 2009-2011. The application of five-year survival rates provides a projection of the number of persons from the initial population expected to be alive in five years. Resident deaths data by age and sex from 1989 to 2011 were provided by the Illinois Center for Health Statistics (ICHS), Illinois Department of Public Health. Fertility Total fertility rates (TFRs) were first computed for each county. For most counties, the projected 2015 TFRs were computed as the average of the 2000 and 2010 TFRs. 2010 or 2015 rates were retained for 2020 projections, depending on the birth trend of each county. The age-specific birth rates (ASBR) were next computed for each county by multiplying the 2010 ASBR by each projected TFR. Total births were then projected for each county by applying age-specific birth rates to the projected female population of reproductive ages (15 to 49 years). The total births were broken down by sex, using an assumed sex-ratio at birth. These births were survived five years applying assumed survival ratios to get the projected population for the age group 0-4. For the special counties, special populations by age and sex were taken out before computing age-specific birth rates. The resident birth data used to compute age-specific birth rates for 1989-1991, 1999-2001 and 2009-2011 came from ICHS. Births to females younger than 15 years of age were added to those of the 15-19 age group and births to women older than 49 years of age were added to the 45-49 age group. Net Migration Migration is the major component of population change in Illinois, Chicago and Illinois counties. The state is experiencing a significant loss of population through internal (domestic migration within the U.S.) net migration. Unlike data on births and deaths, migration data based on administrative records are not available on a regular basis. Most data on migration are collected through surveys or indirectly from administrative records (IRS individual tax returns). For this report, net migration trends have been reviewed using data from different sources and methods (such as residual method) from the University of Wisconsin, Madison, Illinois Department of Public Health, individual exemptions data from the Internal Revenue Service, and survey data from the U.S. Census Bureau. On the basis of knowledge gained through this review and of levels of net migration from different sources, assumptions have been made that Illinois will have annual net migrants of -40, 000, -35,000 and -30,000 during 2010-2015, 2015-2020 and 2020-2025, respectively. These figures have been distributed among the counties, using age and sex distribution of net migrants during 1995-2000. The 2000 population census was the last decennial census, which included the question “Where did you live five years ago?” The age and sex distribution of the net migrants was derived, using answers to this question. The net migration for Chicago has been derived independently, using census survival method for 1990-2000 and 2000-2010 under the assumption that the annual net migration for Chicago will be -40,000, -30,000 and -25,000 for 2010-2015, 2015-2020 and 2020-2025, respectively. The age and sex distribution from the 2000-2010 net migration was used to distribute the net migrants for the projection periods. Conclusion These projections were prepared for use by the Certificate of Need (CON) Program; they are produced using evidence-based techniques, reasonable assumptions and the best available input data. However, as assumptions of future demographic trends may contain errors, the resulting projections are unlikely to be free of errors. In general, projections of small areas are less reliable than those for larger areas, and the farther in the future projections are made, the less reliable they may become. When possible, these projections should be regularly reviewed and updated, using more recent birth, death and migration data.

The leading causes of death by sex and ethnicity in New York City in since 2007. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City.

Abstract (en): This data collection provides net migration estimates by age, race, and sex for counties of the United States. Population data are included along with absolute net migration data and net migration ratios (rates) for the period 1970-1980. Summary records for states, divisions, regions and the United States are also supplied. Several data categories are presented in the collection. Vital Statistics data tabulate births by sex and race (white and non white) for the periods 1970-1974 and 1975-1979 and deaths by race from 1970-1979 as well as adjusted total population for 1970 and 1980 by race. The Enumerated and Adjusted 1970 and 1980 Population categories offer population totals by race and sex and further subdivide these totals into 16 5-year age ranges. Net Migration Estimates and Net Migration Rates are available also, with totals by sex and race presented along with the 16 age divisions. Total United States population. Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. Center for Population Research (HD18739).

This administrative dataset provides descriptive information about the families and children served through the federal Child Care and Development Fund (CCDF). CCDF dollars are provided to states, territories, and tribes to provide assistance to low-income families receiving or in transition from temporary public assistance, to obtain quality child care so they can work, or depending on their state's policy, to attend training or receive education. The Personal Responsibility and Work Opportunity Act of 1996 requires states and territories to collect information on all family units receiving assistance through the CCDF and to submit monthly case-level data to the Office of Child Care. States are permitted to report case-level data for the entire population, or a sample of the population, under approved sampling guidelines. The Summary Records file contains monthly state-level summary information including the number of families served. The Family Records file contains family-level data including single parent status of the head of household, monthly co-payment amount, date on which child care assistance began, reasons for care (e.g., employment, training/education, protective services, etc.), income used to determine eligibility, source of income, and the family size on which eligibility is based. The Child Records file contains child-level data including ethnicity, race, gender, and date of birth. The Setting Records file contains information about the type of child care setting, the total amount paid to the provider, and the total number of hours of care received by the child. The Pooling Factor file provides state-level data on the percentage of child care funds that is provided through the CCDF, the federal Head Start region the grantee (state) is in and is monitored by, and the state FIPS code for the grantee.