This dataset contains monthly data for the current fiscal year for each WIC State agency. There are currently 90 WIC State agencies: the 50 geographic states, the District of Columbia, Puerto Rico, Guam, the Virgin Islands, American Samoa, Northern Marianas, and 34 Indian tribal organizations (ITO's). The dataset contains number of Pregnant Women, Breastfeeding Women, Postpartum Women, Total Women, Infants and children participating in the WIC program and the associated food and administrative cost.

The Women’s and Children’s Health Network (WCHN) is South Australia’s leading provider of specialty care and health services for babies, young people and women in South Australia. WCHN works in partnership with consumers and their families, the community, key partners and other service providers to promote, maintain and restore health. The service comprises the Women’s and Children’s Hospital and community based services, including Child and Adolescent Mental Health services, Child and Family Health Service, Child Protection Service, Children’s Disability Services, Youth Health Service, Women’s Health Service, Helen Mayo House and Yarrow Place Rape and Sexual Assault Service.

This dataset includes data on weight status for children aged 3 months to 4 years old from Women, Infant, and Children Participant and Program Characteristics (WIC-PC). This data is used for DNPAO's Data, Trends, and Maps database, which provides national and state specific data on obesity, nutrition, physical activity, and breastfeeding. For more information about WIC-PC visit https://www.fns.usda.gov/wic/national-survey-wic-participants.

About MCH Data Connect The MCH Data Connect provides public health professionals, researchers, practitioners, policy makers and students with a comprehensive catalog of maternal and child health data resources. Users can access a variety of databases, data sets, interactive tools, and maps related to their area of interest. Maternal and Child Health The MCH Data Connect uses a broad definition of Maternal and Child Health, including the influence of access to health care, health, health behaviors, education, violence, environmental conditions, demographics, and policy on the health of women, men, children, youth, families and communities. Topics Topics included in the MCH Data Connect: health care policy, experience of health care, family planning, sexual and reproductive health, economics, politics, social services, violence, and health behaviors, among others. Data Resources Data resources described in this catalog include data sets, statistics, interactive tables, interactive maps, and databases. Many of the data sources are available for public consumption, though specific databases may require th e user to purchase or apply for the dataset. Basic Search Locate the "Search Studies" highlighted box above the list of resource on the MCH Data Connect homepage. Leave "Cataloging Information" as the default basic search command. To search, enter the keyword, topic or area of interest in field box (next to "Cataloging Information") to obtain a list of resources that apply to your search. Access Resource Once the search is completed, a list of resources will appea r. The first line provides a brief summary. To get more information (including producer, background, user functionality and data sources) about the specific resource, click on the underlined/ blue hyperlinked title. Once the resource description is opened, click on the link that says “Click here to access data from site” to go directly to the resource's web page. Advanced Search Click on the "Advanced Search" link located in the "Search Studies" highlighted box above the list of resources on the MCH Data Connect homepage. From the Search Scope drop down lists, enter either Keyword or Abstract (these are the most detailed fields used by the MCH Data Connect). Enter multiple search terms to use the “and” searching criterion. For example, to search for resources related to diabetes and exercise, the user would select "Keyword" from the drop d own list, "contains" and then enter "diabetes" in the field box. The user would repeat the first two steps to enter "exercise" in the next field box. Collections The Topic Folders section provides a list of broad categories that include many resources found in the MCH Data Connect. The files of the Topic Folders are on the left side of the homepage. Clicking on a file folder will result in a list of the resources that are related to the topic. The Topic Folders offer a starting place for your search. You can narrow your search further by performing either of the previous two searching techniques within a collection. Qu estions or Comments? For questions, comments, or if you think we missed a useful information tool, please contact us via email at mchdataconnect@gmail.com. Glossary Some terms you will see on this website are unique to the cataloging service, Dataverse; The MCH Data Connect uses them differently. Please see below for a glossary of terms you will find at MCH Data Connect. Please note that interactive tools, datasets, and reports are referred to as “resources.” Te rms Dataverse, the program used to develop the MCH Data Connect Study, resource containing relevant public health data and/or information Collection, broad categories into which resources have been classified How to Cite, used as the resource title by MCH Data Connect Study Global ID, unique code given to each resource Producer, the agency or entity that produces and maintains the resource< /p> Deposit Date, date when resource was added to the MCH Data Connect Provenance, will always be MCH Data Connect Abstract and Scope, contains resource summary and geographic unit information Abstract, summary of the resource Background, information about the purpose and development of the resource User Functionality, what users can do with the data (i.e. download, customize charts) Dat a Notes, information about data sources, years and samples (if applicable) Abstract Date, month and year that resource was added to MCH Data Connect Keyword, specific variables, topics, or words that the resource addresses/encompasses Geographic Unit, level at which data is available Title, name of specific resource Keyword Vocabulary, “link:” clicking on “link” will take user to an external website relate d to the keyword term. The following terms are not used by the MCH Data Connect Dataverse: Topic Classification; Topic Classification Vocabulary; Other ID; Author; Distributor; Funding Agency; Production Date; Distribution Date; Time Period Covered Start; Time...

Description of the experiment setting: location, influential climatic conditions, controlled conditions (e.g. temperature, light cycle) In 1986, the Congress enacted Public Laws 99-500 and 99-591, requiring a biennial report on the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). In response to these requirements, FNS developed a prototype system that allowed for the routine acquisition of information on WIC participants from WIC State Agencies. Since 1992, State Agencies have provided electronic copies of these data to FNS on a biennial basis. FNS and the National WIC Association (formerly National Association of WIC Directors) agreed on a set of data elements for the transfer of information. In addition, FNS established a minimum standard dataset for reporting participation data. For each biennial reporting cycle, each State Agency is required to submit a participant-level dataset containing standardized information on persons enrolled at local agencies for the reference month of April. The 2016 Participant and Program Characteristics (PC2016) is the thirteenth data submission to be completed using the WIC PC reporting system. In April 2016, there were 90 State agencies: the 50 States, American Samoa, the District of Columbia, Guam, the Northern Mariana Islands, Puerto Rico, the American Virgin Islands, and 34 Indian tribal organizations. Processing methods and equipment used Specifications on formats (“Guidance for States Providing Participant Data”) were provided to all State agencies in January 2016. This guide specified 20 minimum dataset (MDS) elements and 11 supplemental dataset (SDS) elements to be reported on each WIC participant. Each State Agency was required to submit all 20 MDS items and any SDS items collected by the State agency.   Study date(s) and duration The information for each participant was from the participants’ most current WIC certification as of April 2016. Due to management information constraints, Connecticut provided data for a month other than April 2016, specifically August 16 – September 15, 2016. Study spatial scale (size of replicates and spatial scale of study area) In April 2016, there were 90 State agencies: the 50 States, American Samoa, the District of Columbia, Guam, the Northern Mariana Islands, Puerto Rico, the American Virgin Islands, and 34 Indian tribal organizations. Level of true replication Unknown Sampling precision (within-replicate sampling or pseudoreplication) State Agency Data Submissions. PC2016 is a participant dataset consisting of 8,815,472 active records. The records, submitted to USDA by the State Agencies, comprise a census of all WIC enrollees, so there is no sampling involved in the collection of this data. PII Analytic Datasets. State agency files were combined to create a national census participant file of approximately 8.8 million records. The census dataset contains potentially personally identifiable information (PII) and is therefore not made available to the public. National Sample Dataset. The public use SAS analytic dataset made available to the public has been constructed from a nationally representative sample drawn from the census of WIC participants, selected by participant category. The nationally representative sample is composed of 60,003 records. The distribution by category is 5,449 pregnant women, 4,661 breastfeeding women, 3,904 postpartum women, 13,999 infants, and 31,990 children. Level of subsampling (number and repeat or within-replicate sampling) The proportionate (or self-weighting) sample was drawn by WIC participant category: pregnant women, breastfeeding women, postpartum women, infants, and children. In this type of sample design, each WIC participant has the same probability of selection across all strata. Sampling weights are not needed when the data are analyzed. In a proportionate stratified sample, the largest stratum accounts for the highest percentage of the analytic sample. Study design (before–after, control–impacts, time series, before–after-control–impacts) None – Non-experimental Description of any data manipulation, modeling, or statistical analysis undertaken Each entry in the dataset contains all MDS and SDS information submitted by the State agency on the sampled WIC participant. In addition, the file contains constructed variables used for analytic purposes. To protect individual privacy, the public use file does not include State agency, local agency, or case identification numbers. Description of any gaps in the data or other limiting factors Due to management information constraints, Connecticut provided data for a month other than April 2016, specifically August 16 – September 15, 2016.   Outcome measurement methods and equipment used None Resources in this dataset:Resource Title: WIC Participant and Program Characteristics 2016. File Name: wicpc_2016_public.csvResource Description: The 2016 Participant and Program Characteristics (PC2016) is the thirteenth data submission to be completed using the WIC PC reporting system. In April 2016, there were 90 State agencies: the 50 States, American Samoa, the District of Columbia, Guam, the Northern Mariana Islands, Puerto Rico, the American Virgin Islands, and 34 Indian tribal organizations.Resource Software Recommended: SAS, version 9.4,url: https://www.sas.com/en_us/software/sas9.html Resource Title: WIC Participant and Program Characteristics 2016 Codebook. File Name: WICPC2016_PUBLIC_CODEBOOK.xlsxResource Software Recommended: SAS, version 9.4,url: https://www.sas.com/en_us/software/sas9.html Resource Title: WIC Participant and Program Characteristics 2016 - Zip File with SAS, SPSS and STATA data. File Name: WIC_PC_2016_SAS_SPSS_STATA_Files.zipResource Description: WIC Participant and Program Characteristics 2016 - Zip File with SAS, SPSS and STATA data

This dataset is about book series. It has 1 row and is filtered where the books is Who cares? : a new deal for mothers and their small children. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Analysis of the employment trends and characteristics of working mothers, compared to women without children and working fathers. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: Mothers in the Labour Market

Archived as of 5/30/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. This dataset provides information related to mothers with a live birth during the time period 07/2016 to 07/2020 and their claims 2 years prior and 2 years post delivery. It contains information about the overall number of claims and overall total dollar amount, total claims prebirthing and postbirthing, and total dollar amount prebirthing and postbirthing, by mother’s county of residence at the time of delivery. Maternal health claims are defined as claims with mothers diagnosed with at least one of the following ICD codes: 650, V270, V272, V273, V275, V276, V3000, V3100, V3200, V3300, V3400, V3500, V3600, V3700, V3900, O80, Z370, Z372, Z373, Z3750, Z3751, Z3752, Z3753, Z3754, Z3759, Z3760, Z3761, Z3762, Z3763, Z3764, Z3769, Z3800, Z382, Z385, Z3830, Z3830, Z3861, Z3863, Z3865, Z3868, Z388, V7242, V220, V239, V221, V222, V230, V232, V234, V2341, V2342, V724, V237, V279, V6511, V241, V242, V251, V723, V762, Z37, Z370, Z371, Z372, Z373, Z374, Z375, Z3750, Z3751, Z3752, Z3753, Z3754, Z3759, Z376, Z3760, Z3761, Z3762, Z3763, Z3764, Z3769, Z377, Z379, Z34, Z340, Z3400, Z3401, Z3402, Z3403, Z348, Z3480, Z3481, Z3482, Z3483, Z349, Z3490, Z3491, Z3492, Z3493, O09, O090, O0900, O0901, O0902, O0903, O091, O0910, O0911, O0912, O0913, O09A, O09A0, O09A1, O09A2, O09A3, O092, O0921, O09211, O09212, O09213, O09219, O0929, O09291, O09292, O09293, O09299, O093, O0930, O0931, O0932, O0933, O094, O0940, O0941, O0942, O0943, O095, O0951, O09511, O09512, O09513, O09519, O0952, O09521, O09522, O09523, O09529, O096, O0961, O09611, O09612, O09613, O09619, O0962, O09621, O09622, O09623, O09629, O097, O0970, O0971, O0972, O0973, O098, O0981, O09811, O09812, O09813, O09819, O0982, O09821, O09822, O09823, O09829, O0989, O09891, O09892, O09893, O09899, O099, O0990, O0991, O0992, O0993. A maternal health claim is also defined as claims with at least one of the following CPT codes: 59025, 59424, 59425, 59426, 76818, 88291, 59400, 59409, 59410, 59510, 59514, 59515, 59610, 59612, 59614, 59618, 59620, 59622, 57170, 58300, 59430, 88141, 88142, 88143, 88147, 88148, 88150, 88152, 88153, 88154, 88155, 88164, 88165, 88166, 88167, 88174, 88175. Prebirthing is restricted to claims with a service date within 2 years before to the delivery date of the child. Postbirthing is restricted to claims with a service date within 2 years after the delivery date of the child. This data is for research purposes and is not intended to be used for reporting. Due to differences in geographic aggregation, time period considerations, and units of analysis, these numbers may differ from those reported by FSSA.

PLEASE, CITE AS Kalabikhina IE, Kuznetsova PO, Zhuravleva SA (2024) Size and factors of the motherhood penalty in the labour market: A meta-analysis. Population and Economics 8(2): 178-205. https://doi.org/10.3897/popecon.8.e121438

Explanatory note 1: List of papers used in the meta-analysis - see the file "Meta_regression_analysis_papers".

The data is presented in WORD format.

Explanatory note 2: Set of data used in the meta-analysis - see the file "Meta_regression_analysis_table".

The data is presented in EXCEL format.

Description of table headers:

estimate_number - Number of the estimate

paper_number - Number of the paper

paper_name - Paper (year and first author)

paper_excluded - Paper was excluded from the final sample

survey - Data source

table_in_paper - Number of the table with the regression results in the paper

coeff - Regression coefficient for parenthood variable (estimate)

se - SE of the estimate

t - t-value of the estimate

ols - Estimate is obtained using the OLS method

fixed_effects - Estimate is obtained using the fixed effects method

panel - Model considers panel data (for several years)

quintile - Estimate is obtained using the quintile regression method

other - Estimate is obtained using other methods

selection_into_motherhood - Estimate is obtained allowing for selection into motherhood

hackman - Estimate is obtained allowing for selection into employment (Heckman procedure)

annual_earnings - Annual earnings are considered in the model

monthly_wage - Monthly wage is considered in the model

daily_wage - Daily wage is considered in the model

hourly_wage - Hourly wage is considered in the model

min_age_kid - Child's age (minimum)

max_age_kid - Child's age (maximum)

motherhood - Model uses a dummy variable of the presence of children

num_kids - Model uses a variable of the number of children

kid1 - Model uses a variable of the presence of one child

kid2p - Model uses a variable of the presence of two or more children

kid2 - Model uses a variable of the presence of two children

kid3p - Model uses a variable of the presence of three or more children

kid3 - Model uses a variable of the presence of three children

kid4p - Model uses a variable of the presence of three or more children

race/nationality - Model includes a race/ethnicity variable

age - Model includes the age variable

marstat - Model includes the marital status variable

oth_char_hh - Model includes any other variables of other household characteristics

settl_type - Model includes a variable of the type of settlement (urban, rural)

region - Model includes a variable of the region of the country

education - Model includes information on the level of education

experience - Model includes a variable of work experience

pot_experience - Model includes a variable of potential work experience, to be calculated from the data on age and number of years of education

tenure - Model includes a variable of the duration of employment at the current job

interruptions - Model includes a variable of employment interruptions (related to motherhood)

occupation - Model includes an occupation variable

industry - Model includes a variable of the industry of employment

union - Model includes a variable of trade union membership

friendly_conditions - Model includes a variable of the favourable working conditions for mothers (flexible schedule, possibility to work from home, etc.).

hours - Model includes a variable of the number of hours worked

sector - Model includes a variable of the type of employer ownership (public or private)

informal - Model includes a variable of informal employment

size_ent - Model includes a variable of the employer size

min_age_woman - Woman's age (minimum)

max_age_woman - Woman's age (maximum)

mean_age_woman - Woman's age (mean)

restricted - Sample is limited

private - Model considers only private sector employees

state - Model considers only public sector employees

full_time - Model considers only full-time workers

part_time - Model considers only part-time workers

better_educated - Model considers only women with a high level of education

lower_educated - Model considers only women with a low level of education

married - Model includes only married women

single - Model includes only single women

natives - Model includes only native women (born in the country)

immigrants - Model includes only immigrant women (born abroad)

race - Model includes only women of a particular race

min_year - Time period (minimum year)

max_year - Time period (maximum year)

journal - Type of publication

usa - Sample includes women from the USA

western_europe - Sample includes women from Western Europe (Belgium, France, Germany, Luxembourg, the Netherlands, Switzerland)

north_europe - Sample includes women from Northern Europe (Denmark, Finland, Norway, Sweden)

south_europe - Sample includes women from Southern Europe (Greece, Italy, Portugal, Spain)

east_centre_europe - Sample includes women from Central or Eastern Europe (Czechia, Hungary, Poland, Russia, Serbia, Ukraine)

china - Sample includes women from China

Russia - Sample includes women from Russia

others - Sample includes women from other countries

country - Country name

The annual list of first names of newborns is a simple and popular dataset. These data, from the register of civil status, shall contain the following essential data: sex of the newborn, first name of the newborn, number of occurrences of the first name for the corresponding year, year of survey. The dataset consists of the list of first names of children born in Nancy since 2016, in CSV format, with the number of occurrences of each given name, classified by year and sex.

The first names declared below an occurrence of five are not published, with a view to protecting personal data. The standardisation of this dataset follows the recommendations of Opendata France following the work around the Common Socle des Data Locales.

Definition of headers COLL_NOM: name of the municipality COLL_INSEE: Insee code of the municipality where the first names are registered in the civil status of the place of birth. Note that the place of birth may be different from the place of residence of the parents. CHILD_SEX: Gender corresponding to first name: M or F respectively for men or women CHILD_PRENOM: first name of new born(s) recorded as first name in the civil status documents of the corresponding year. NUMBER_OCCURENCES: occurrence of first name YEAR: year of birth

Total births reported to the City of Nancy 2018 Total number of births: 5135 Total number of births of girls: 2692 Total number of births of boys: 2443

2017 Total number of births: 5483 Total number of births of girls: 2704 Total number of births of boys: 2779

2016 Total number of births: 5544 Total number of births of girls: 2692 Total number of births of boys: 2852

The 1992 Malawi Demographic and Health Survey (MDHS) was a nationally representative sample survey designed to provide information on levels and trends in fertility, early childhood mortality and morbidity, family planning knowledge and use, and maternal and child health. The survey was implemented by the National Statistical Office during September to November 1992. In 5323 households, 4849 women age 15-49 years and 1151 men age 20-54 years were interviewed. The Malawi Demographic and Health Survey (MDHS) was a national sample survey of women and men of reproductive age designed to provide, among other things, information on fertility, family planning, child survival, and health of mothers and children. Specifically, the main objectives of the survey were to: Collect up-to-date information on fertility, infant and child mortality, and family planning Collect information on health-related matters, including breastleeding, antenatal and maternity services, vaccinations, and childhood diseases and treatment Assess the nutritional status of mothers and children Collect information on knowledge and attitudes regarding AIDS Collect information suitable for the estimation of mortality related to pregnancy and childbearing Assess the availability of health and family planning services. MAIN FINDINGS The findings indicate that fertility in Malawi has been declining over the last decade; at current levels a woman will give birth to an average of 6.7 children during her lifetime. Fertility in rural areas is 6.9 children per woman compared to 5.5 children in urban areas. Fertility is higher in the Central Region (7.4 children per woman) than in the Northem Region (6.7) or Southern Region (6.2). Over the last decade, the average age at which a woman first gives birth has risen slightly over the last decade from 18.3 to 18.9 years. Still, over one third of women currently under 20 years of age have either already given birlh to at least one child or are currently pregnant. Although 58 percent of currently married women would like to have another child, only 19 percent want one within the next two years. Thirty-seven percent would prefer to walt two or more years. Nearly one quarter of married women want no more children than they already have. Thus, a majority of women (61 percent) want either to delay their next birth or end childbearing altogether. This represents the proportion of women who are potentially in need of family planning. Women reported an average ideal family size of 5.7 children (i.e., wanted fertility), one child less than the actual fertility level measured in the surveyfurther evidence of the need for family planning methods. Knowledge of contraceptive methods is high among all age groups and socioeconomic strata of women and men. Most women and men also know of a source to obtain a contraceptive method, although this varies by the type of method. The contraceptive pill is the most commonly cited method known by women; men are most familiar with condoms. Despite widespread knowledge of family planning, current use of contraception remains quite low. Only 7 percent of currently married women were using a modem method and another 6 percent were using a traditional method of family planning at the time of the survey. This does, however, represent an increase in the contraceptive prevalence rate (modem methods) from about 1 percent estimated from data collected in the 1984 Family Formation Survey. The modem methods most commonly used by women are the pill (2.2 percent), female sterilisation (1.7 percent), condoms (1.7 percent), and injections (1.5 percent). Men reported higher rates of contraceptive use (13 percent use of modem methods) than women. However, when comparing method-specific use rates, nearly all of the difference in use between men and women is explained by much higher condom use among men. Early childhood mortality remains high in Malawi; the under-five mortality rate currently stands at 234 deaths per 1000 live births. The infant mortality rate was estimated at 134 per 10130 live births. This means that nearly one in seven children dies before his first birthday, and nearly one in four children does not reach his fifth birthday. The probability of child death is linked to several factors, most strikingly, low levels of maternal education and short intervals between births. Children of uneducated women are twice as likely to die in the first five years of life as children of women with a secondary education. Similarly, the probablity of under-five mortality for children with a previous birth interval of less than 2 years is two times greater than for children with a birth interval of 4 or more years. Children living in rural areas have a higher rate ofunder-fwe mortality than urban children, and children in the Central Region have higher mortality than their counterparts in the Northem and Southem Regions. Data were collected that allow estimation ofmatemalmortality. It is estimated that for every 100,000 live births, 620 women die due to causes related to pregnancy and childbearing. The height and weight of children under five years old and their mothers were collected in the survey. The results show that nearly one half of children under age five are stunted, i.e., too short for their age; about half of these are severely stunted. By age 3, two-thirds of children are stunted. As with childhood mortality, chronic undernutrition is more common in rural areas and among children of uneducated women. The duration of breastfeeding is relatively long in Malawi (median length, 21 months), but supplemental liquids and foods are introduced at an early age. By age 2-3 months, 76 percent of children are already receiving supplements. Mothers were asked to report on recent episodes of illness among their young children. The results indicate that children age 6-23 months are the most vulnerable to fever, acute respiratory infection (ARI), and diarrhea. Over half of the children in this age group were reported to have had a fever, about 40 percent had a bout with diarrhea, and 20 percent had symptoms indicating ARI in the two-week period before the survey. Less than half of recently sick children had been taken to a health facility for treatment. Sixty-three percent of children with diarrhea were given rehydration therapy, using either prepackaged rehydration salts or a home-based preparation. However, one quarter of children with diarrhea received less fluid than normal during the illness, and for 17 percent of children still being breastfed, breastfeeding of the sick child was reduced. Use of basic, preventive maternal and child health services is generally high. For 90 percent of recent births, mothers had received antenatal care from a trained medical person, most commonly a nurse or trained midwife. For 86 percent of births, mothers had received at least one dose of tetanus toxoid during pregnancy. Over half of recent births were delivered in a health facility. Child vaccination coverage is high; 82 percent of children age 12-23 months had received the full complement of recommended vaccines, 67 percent by exact age 12 months. BCG coverage and first dose coverage for DPT and polio vaccine were 97 percent. However, 9 percent of children age 12-23 months who received the first doses of DPT and polio vaccine failed to eventually receive the recommended third doses. Information was collected on knowledge and attitudes regarding AIDS. General knowledge of AIDS is nearly universal in Malawi; 98 percent of men and 95 percent of women said they had heard of AIDS. Further, the vast majority of men and women know that the disease is transmitted through sexual intercourse. Men tended to know more different ways of disease transmission than women, and were more likely to mention condom use as a means to prevent spread of AIDS. Women, especially those living in rural areas, are more likely to hold misconceptions about modes of disease transmission. Thirty percent of rural women believe that AIDS can not be prevented.

The WIC Infant and Toddler Feeding Practices Study–2 (WIC ITFPS-2) (also known as the “Feeding My Baby Study”) is a national, longitudinal study that captures data on caregivers and their children who participated in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) around the time of the child’s birth. The study addresses a series of research questions regarding feeding practices, the effect of WIC services on those practices, and the health and nutrition outcomes of children on WIC. Additionally, the study assesses changes in behaviors and trends that may have occurred over the past 20 years by comparing findings to the WIC Infant Feeding Practices Study–1 (WIC IFPS-1), the last major study of the diets of infants on WIC. This longitudinal cohort study has generated a series of reports. These datasets include data from caregivers and their children during the prenatal period and during the children’s first five years of life (child ages 1 to 60 months). A full description of the study design and data collection methods can be found in Chapter 1 of the Second Year Report (https://www.fns.usda.gov/wic/wic-infant-and-toddler-feeding-practices-st...). A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-IT...). Processing methods and equipment used Data in this dataset were primarily collected via telephone interview with caregivers. Children’s length/height and weight data were objectively collected while at the WIC clinic or during visits with healthcare providers. The study team cleaned the raw data to ensure the data were as correct, complete, and consistent as possible. Study date(s) and duration Data collection occurred between 2013 and 2019. Study spatial scale (size of replicates and spatial scale of study area) Respondents were primarily the caregivers of children who received WIC services around the time of the child’s birth. Data were collected from 80 WIC sites across 27 State agencies. Level of true replication Unknown Sampling precision (within-replicate sampling or pseudoreplication) This dataset includes sampling weights that can be applied to produce national estimates. A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-IT...). Level of subsampling (number and repeat or within-replicate sampling) A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-IT...). Study design (before–after, control–impacts, time series, before–after-control–impacts) Longitudinal cohort study. Description of any data manipulation, modeling, or statistical analysis undertaken Each entry in the dataset contains caregiver-level responses to telephone interviews. Also available in the dataset are children’s length/height and weight data, which were objectively collected while at the WIC clinic or during visits with healthcare providers. In addition, the file contains derived variables used for analytic purposes. The file also includes weights created to produce national estimates. The dataset does not include any personally-identifiable information for the study children and/or for individuals who completed the telephone interviews. Description of any gaps in the data or other limiting factors Please refer to the series of annual WIC ITFPS-2 reports (https://www.fns.usda.gov/wic/infant-and-toddler-feeding-practices-study-2-fourth-year-report) for detailed explanations of the study’s limitations. Outcome measurement methods and equipment used The majority of outcomes were measured via telephone interviews with children’s caregivers. Dietary intake was assessed using the USDA Automated Multiple Pass Method (https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-h...). Children’s length/height and weight data were objectively collected while at the WIC clinic or during visits with healthcare providers. Resources in this dataset:Resource Title: ITFP2 Year 5 Enroll to 60 Months Public Use Data CSV. File Name: itfps2_enrollto60m_publicuse.csvResource Description: ITFP2 Year 5 Enroll to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Enroll to 60 Months Public Use Data Codebook. File Name: ITFPS2_EnrollTo60m_PUF_Codebook.pdfResource Description: ITFP2 Year 5 Enroll to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Enroll to 60 Months Public Use Data SAS SPSS STATA R Data. File Name: ITFP@_Year5_Enroll60_SAS_SPSS_STATA_R.zipResource Description: ITFP2 Year 5 Enroll to 60 Months Public Use Data SAS SPSS STATA R DataResource Title: ITFP2 Year 5 Ana to 60 Months Public Use Data CSV. File Name: ampm_1to60_ana_publicuse.csvResource Description: ITFP2 Year 5 Ana to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Tot to 60 Months Public Use Data Codebook. File Name: AMPM_1to60_Tot Codebook.pdfResource Description: ITFP2 Year 5 Tot to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Ana to 60 Months Public Use Data Codebook. File Name: AMPM_1to60_Ana Codebook.pdfResource Description: ITFP2 Year 5 Ana to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Ana to 60 Months Public Use Data SAS SPSS STATA R Data. File Name: ITFP@_Year5_Ana_60_SAS_SPSS_STATA_R.zipResource Description: ITFP2 Year 5 Ana to 60 Months Public Use Data SAS SPSS STATA R DataResource Title: ITFP2 Year 5 Tot to 60 Months Public Use Data CSV. File Name: ampm_1to60_tot_publicuse.csvResource Description: ITFP2 Year 5 Tot to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Tot to 60 Months Public Use SAS SPSS STATA R Data. File Name: ITFP@_Year5_Tot_60_SAS_SPSS_STATA_R.zipResource Description: ITFP2 Year 5 Tot to 60 Months Public Use SAS SPSS STATA R DataResource Title: ITFP2 Year 5 Food Group to 60 Months Public Use Data CSV. File Name: ampm_foodgroup_1to60m_publicuse.csvResource Description: ITFP2 Year 5 Food Group to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Food Group to 60 Months Public Use Data Codebook. File Name: AMPM_FoodGroup_1to60m_Codebook.pdfResource Description: ITFP2 Year 5 Food Group to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Food Group to 60 Months Public Use SAS SPSS STATA R Data. File Name: ITFP@_Year5_Foodgroup_60_SAS_SPSS_STATA_R.zipResource Title: WIC Infant and Toddler Feeding Practices Study-2 Data File Training Manual. File Name: WIC_ITFPS-2_DataFileTrainingManual.pdf

Abstract copyright UK Data Service and data collection copyright owner. The Avon Longitudinal Study of Parents and Children (ALSPAC, and also known as the 'Children of the 90s' study), which is based at the University of Bristol, is an ongoing longitudinal study of a population of children born to mothers resident in one geographic area in England. The overall objectives of the study are to understand the ways in which the physical and social environments interact over time with genetic inheritance to affect health, behaviour and development in infancy, childhood and then into adulthood. Information has been collected at regular and frequent intervals from pregnancy and throughout childhood concerning the child's physical environments, parental characteristics (including economic and educational indicators), social circumstances, and family relationships. ALSPAC recruited more than 14,000 pregnant women with estimated dates of delivery between April 1991 and December 1992, who were living in the Avon Health Authority area, to take part in the study. These women, the children arising from the index pregnancy and the women's partners have been followed up since then and detailed data collected throughout childhood. The datasets held at the UKDA are sampler datasets, and have been compiled using various questionnaire and assessment data from the ALSPAC study. Further information may be found in the documentation, and for the wider study, on the ALSPAC web site. Main Topics: The ALSPAC study collects data using a variety of methods, including:self-completion questionnaires completed by the child's motherself-completion questionnaires completed by the mother’s partnerassays of biological samples, including geneticsmedical recordseducational recordsinformation from teachers and head teachersself-completion questionnaires completed by the study childhands-on assessmentsFor the UKDA sampler datasets I-IV and VI (covering household, neighbourhood, housing, social/economic and employment/occupational information), data from the mothers' and partners' questionnaires were used, and for dataset V (height), data from the hands-on assessments were included. These files include data gathered between 1990 and 2003 only. Further details may be found in the documentation, and the ALSPAC questionnaires may be found on the study web site.

The dataset contains state-wise National Family Health Survey (NFHS) compiled data on various family planning, childbirth, population, medical, health and other parameters which provide statistical indicators data on family profile and health status in India. There are 100+ indicators covered in the survey which broadly fall in the following categories: Health and Wellness, Maternal and Child Health, Family Planning and Reproductive Health, Disease Screening and Prevention, Social and Economic Factors, General Healthcare and Treatment

The different types of health data contained in the dataset include Anaemia among women and children, blood sugar levels and hypertension among men and women, tobacco and alcohol consumption among adults, delivery care and child feeding practices of women, quality of family planning services, screening of cancer among women, marriage and family, maternity care, nutritional status of women, child vaccinations and vitamin A supplementation, treatment of childhood diseases, etc.

Within these categories of health data, the dataset contains indicators data such as births attended by skilled health care professionals and caesarean section, number of children with under and heavy weight, stunted growth, their different vaccations status, male and female sterilization, consumption of iron folic acid among mothers, mother who had antenatal, postnatal, neonatal services, women who are obese and at the risk of weight to hip ratio, educational status among women and children, sanitation, birth and sex ratio, etc.

All of the data is compiled from the NFHS 4th and 5th survey reports. The The NFHS is a collaborative project of the International Institute for Population Sciences(IIPS), aimed at providing health data to strengthen India's health policies and programmes.

There are 100+ indicators covered in the survey which broadly fall in the following categories: Health and Wellness, Maternal and Child Health, Family Planning and Reproductive Health, Disease Screening and Prevention, Social and Economic Factors, General Healthcare and Treatment

A summary of current WIC policy and regulatory citations that are specifically relevant to WIC Program operation during disaster situations, usually hurricanes, in which WIC participants have been evacuated from their homes and relocated to other areas within their home States, or to another State.

Number of children 0 to 5 years and 6 to 12 years with employed mothers, Canada, provinces.

Background: In 1986, the Congress enacted Public Laws 99-500 and 99-591, requiring a biennial report on the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). In response to these requirements, FNS developed a prototype system that allowed for the routine acquisition of information on WIC participants from WIC State Agencies. Since 1992, State Agencies have provided electronic copies of these data to FNS on a biennial basis.FNS and the National WIC Association (formerly National Association of WIC Directors) agreed on a set of data elements for the transfer of information. In addition, FNS established a minimum standard dataset for reporting participation data. For each biennial reporting cycle, each State Agency is required to submit a participant-level dataset containing standardized information on persons enrolled at local agencies for the reference month of April. The 2020 Participant and Program Characteristics (PC2020) is the 17th to be completed using the prototype PC reporting system. In April 2020, there were 89 State agencies: the 50 States, American Samoa, the District of Columbia, Guam, the Northern Mariana Islands, Puerto Rico, the U.S. Virgin Islands, and 33 Indian Tribal Organizations (ITOs).Processing methods and equipment used: Specifications on formats (“Guidance for States Providing Participant Data”) were provided to all State agencies in January 2020. This guide specified 20 minimum dataset (MDS) elements and 11 supplemental dataset (SDS) elements to be reported on each WIC participant. Each State Agency was required to submit all 20 MDS items and any SDS items collected by the State agency. Study date(s) and duration The information for each participant was from the participants’ most current WIC certification as of April 2020.Study spatial scale (size of replicates and spatial scale of study area): In April 2020, there were 89 State agencies: the 50 States, American Samoa, the District of Columbia, Guam, the Northern Mariana Islands, Puerto Rico, the U.S. Virgin Islands, and 33 Indian Tribal Organizations (ITOs).Level of true replication: UnknownSampling precision (within-replicate sampling or pseudoreplication):State Agency Data Submissions. PC2020 is a participant dataset consisting of 7,036,867 active records. The records, submitted to USDA by the State Agencies, comprise a census of all WIC enrollees, so there is no sampling involved in the collection of this data.PII Analytic Datasets. State agency files were combined to create a national census participant file of approximately 7 million records. The census dataset contains potentially personally identifiable information (PII) and is therefore not made available to the public.National Sample Dataset. The public use SAS analytic dataset made available to the public has been constructed from a nationally representative sample drawn from the census of WIC participants, selected by participant category. The national sample consists of 1 percent of the total number of participants, or 70,368 records. The distribution by category is 5,469 pregnant women, 6,131 breastfeeding women, 4,373 postpartum women, 16,817 infants, and 37,578 children.Level of subsampling (number and repeat or within-replicate sampling): The proportionate (or self-weighting) sample was drawn by WIC participant category: pregnant women, breastfeeding women, postpartum women, infants, and children. In this type of sample design, each WIC participant has the same probability of selection across all strata. Sampling weights are not needed when the data are analyzed. In a proportionate stratified sample, the largest stratum accounts for the highest percentage of the analytic sample.Study design (before–after, control–impacts, time series, before–after-control–impacts): None – Non-experimentalDescription of any data manipulation, modeling, or statistical analysis undertaken: Each entry in the dataset contains all MDS and SDS information submitted by the State agency on the sampled WIC participant. In addition, the file contains constructed variables used for analytic purposes. To protect individual privacy, the public use file does not include State agency, local agency, or case identification numbers.Description of any gaps in the data or other limiting factors: All State agencies provided data on a census of their WIC participants.Resources in this dataset:Resource Title: WIC PC 2020 National Sample File Public Use Codebook.; File Name: PC2020 National Sample File Public Use Codebook.docx; Resource Description: WIC PC 2020 National Sample File Public Use CodebookResource Title: WIC PC 2020 Public Use CSV Data.; File Name: wicpc2020_public_use.csv; Resource Description: WIC PC 2020 Public Use CSV DataResource Title: WIC PC 2020 Data Set SAS, R, SPSS, Stata.; File Name: PC2020 Ag Data Commons.zipResource; Description: WIC PC 2020 Data Set SAS, R, SPSS, Stata One dataset in multiple formats

Background:The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will requireto provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)to collect information on previously neglected topics, such as fathers' involvement in children's care and developmentto focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may beto emphasise intergenerational links including those back to the parents' own childhoodto investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when availableAdditional objectives subsequently included for MCS were:to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of EnglandFurther information about the MCS can be found on the Centre for Longitudinal Studies web pages.The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old.End User Licence versions of MCS studies:The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.Sub-sample studies:Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).Release of Sweeps 1 to 4 to Long Format (Summer 2020)To support longitudinal research and make it easier to compare data from different time points, all data from across all sweeps is now in a consistent format. The update affects the data from sweeps 1 to 4 (from 9 months to 7 years), which are updated from the old/wide to a new/long format to match the format of data of sweeps 5 and 6 (age 11 and 14 sweeps). The old/wide formatted datasets contained one row per family with multiple variables for different respondents. The new/long formatted datasets contain one row per respondent (per parent or per cohort member) for each MCS family. Additional updates have been made to all sweeps to harmonise variable labels and enhance anonymisation. How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.Secure Access datasets:Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).Secure Access versions of the MCS include:detailed sensitive variables not available under EUL.

Families of tax filers; Census families with children by age of children and children by age groups (final T1 Family File; T1FF).