Single-parent Families reports the percent of families with children that are headed by a single parent, per race/ethnicity of the householder. Dimensions Year;Measure.Type;Variable Full Description Children are all persons under the age of 18 years, living in families, and related as children by birth, marriage, or adoption to the householder. Children living with married step-parents are not included. Single-parent families may include unmarried couples. This data originates from the American Community Survey (ACS) 5-Year estimates, table B11003. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. At this time only state-level annual data are available on CTdata.org. Town-level data aggregated from the five-year datasets (considered to be more accurate for geographic areas that are the size of a county or smaller) can be produced using Census tables currently available on the Census website.

About the dataset This dataset uses information from the DWP benefit system to provide estimates of children living in poverty for wards in London. In order to be counted in this dataset, a family must have claimed Child Benefit and at least one other household benefit (Universal Credit, tax credits or Housing Benefit) during the year. The numbers are calibrated to the Households Below Average Income (HBAI) dataset used to provide the government's headline poverty statistics. The definition of relative low income is living in a household with equivalised* income before housing costs (BHC) below 60% of contemporary national median income. The income measure includes contributions from earnings, state support and pensions. Further detail on the estimates of dependent children living in relative low income, including alternative geographical breakdowns and additional variables, such as age of children, family type and work status are available from DWP's statistical tabulation tool Stat-Xplore. Minor adjustments to the data have been applied to guard against the identification of individual claimants. This dataset replaced the DWP children in out-of-work benefit households and HMRC children in low income families local measure releases. This dataset includes estimates for all wards in London of numbers of dependent children living in relative low income families for each financial year from 2014/15 to the latest available (2022/23). The figures for the latest year are provisional and are subject to minor revision when the next dataset is released by DWP. Headlines Number of children The number of dependent children living in relative low income across London, rose from below 310,000 in the financial year ending 2015 to over 420,000 in the financial year ending 2020, but has decreased since then to below 350,000, which is well below the number for financial year ending 2018. While many wards in London have followed a similar pattern, the numbers of children in low income families in some wards have fallen more sharply, while the numbers in other wards have continued to grow. Proportion of children in each London ward Ward population sizes vary across London, the age profile of that population also varies and both the size and make-up of the population can change over time, so in order to make more meaningful comparisons between wards or over time, DWP have also published rates, though see note below regarding caution when using these figures. A dependent child is anyone aged under 16; or aged 16 to 19 in full-time non-advanced education or in unwaged government training. Ward level estimates for the total number of dependent children are not available, so percentages cannot be derived. Ward level estimates for the percentage of children under 16 living in low income families are usually published by DWP but, in its latest release, ward-level population estimates were not available at the time, so no rates were published. To derive the rates in this dataset, the GLA has used the ONS's latest ward-level population estimates (official statistics in development). Percentages for 2021/22 are calculated using the 2021 mid year estimates, while percentages for 2022/23 are calculated using the 2022 mid year estimates. As these are official statistics in development, rates therefore need to be treated with some caution. Notes *equivalised income is adjusted for household size and composition in order to compare living standards between households of different types.

Statewide, DCYF estimates that families of about 305,000 children, age B-5, are not yet in school and need child care. Only about 34% of those children are enrolled in licensed child care or preschool. The percent of need met for child care and preschool for young children varies widely across the state.

This is the proportion of children aged under 16 (0-15) living in families in absolute low income during the year. The figures are based on the count of children aged under 16 (0-15) living in the area derived from ONS mid-year population estimates. The count of children refers to the age of the child at 30 June of each year.

Low income is a family whose equivalised income is below 60 per cent of median household incomes. Gross income measure is Before Housing Costs (BHC) and includes contributions from earnings, state support, and pensions. Equivalisation adjusts incomes for household size and composition, taking an adult couple with no children as the reference point. For example, the process of equivalisation would adjust the income of a single person upwards, so their income can be compared directly to the standard of living for a couple.

Absolute low income is income Before Housing Costs (BHC) in the reference year in comparison with incomes in 2010/11 adjusted for inflation. A family must have claimed one or more of Universal Credit, Tax Credits, or Housing Benefit at any point in the year to be classed as low income in these statistics. Children are dependent individuals aged under 16; or aged 16 to 19 in full-time non-advanced education. The count of children refers to the age of the child at 31 March of each year.

Data are calibrated to the Households Below Average Income (HBAI) survey regional estimates of children in low income but provide more granular local area information not available from the HBAI. For further information and methodology on the construction of these statistics, visit this link. Totals may not sum due to rounding.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

🔗 Check out my notebook here: Link

This dataset includes malnutrition indicators and some of the features that might impact malnutrition. The detailed description of the dataset is given below:

• Percentage-of-underweight-children-data: Percentage of children aged 5 years or below who are underweight by country.

• Prevalence of Underweight among Female Adults (Age Standardized Estimate): Percentage of female adults whos BMI is less than 18.

• GDP per capita (constant 2015 US$): GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 U.S. dollars.

• Domestic general government health expenditure (% of GDP): Public expenditure on health from domestic sources as a share of the economy as measured by GDP.

• Maternal mortality ratio (modeled estimate, per 100,000 live births): Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP measured using purchasing power parities (PPPs).

• Mean-age-at-first-birth-of-women-aged-20-50-data: Average age at which women of age 20-50 years have their first child.

• School enrollment, secondary, female (% gross): Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.

The Pakistan Demographic and Health Survey (PDHS) was fielded on a national basis between the months of December 1990 and May 1991. The survey was carried out by the National Institute of Population Studies with the objective of assisting the Ministry of Population Welfare to evaluate the Population Welfare Programme and maternal and child health services. The PDHS is the latest in a series of surveys, making it possible to evaluate changes in the demographic status of the population and in health conditions nationwide. Earlier surveys include the Pakistan Contraceptive Prevalence Survey of 1984-85 and the Pakistan Fertility Survey of 1975. The primary objective of the Pakistan Demographic and Health Survey (PDHS) was to provide national- and provincial-level data on population and health in Pakistan. The primary emphasis was on the following topics: fertility, nuptiality, family size preferences, knowledge and use of family planning, the potential demand for contraception, the level of unwanted fertility, infant and child mortality, breastfeeding and food supplementation practices, maternal care, child nutrition and health, immunisations and child morbidity. This information is intended to assist policy makers, administrators and researchers in assessing and evaluating population and health programmes and strategies. The PDHS is further intended to serve as a source of demographic data for comparison with earlier surveys, particularly the 1975 Pakistan Fertility Survey (PFS) and the 1984-85 Pakistan Contraceptive Prevalence Survey (PCPS). MAIN RESULTS Until recently, fertility rates had remained high with little evidence of any sustained fertility decline. In recent years, however, fertility has begun to decline due to a rapid increase in the age at marriage and to a modest rise in the prevalence of contraceptive use. The lotal fertility rate is estimated to have fallen from a level of approximately 6.4 children in the early 1980s to 6.0 children in the mid-1980s, to 5.4 children in the late 1980s. The exact magnitude of the change is in dispute and will be the subject of further research. Important differentials of fertility include the degree ofurbanisation and the level of women's education. The total fertility rate is estimated to be nearly one child lower in major cities (4.7) than in rural areas (5.6). Women with at least some secondary schooling have a rate of 3.6, compared to a rate of 5.7 children for women with no formal education. There is a wide disparity between women's knowledge and use of contraceptives in Pakistan. While 78 percent of currently married women report knowing at least one method of contraception, only 21 percent have ever used a method, and only 12 percent are currently doing so. Three-fourths of current users are using a modem method and one-fourth a traditional method. The two most commonly used methods are female sterilisation (4 percent) and the condom (3 percent). Despite the relatively low level of contraceptive use, the gain over time has been significant. Among married non-pregnant women, contraceptive use has almost tripled in 15 years, from 5 percent in 1975 to 14 percent in 1990-91. The contraceptive prevalence among women with secondary education is 38 percent, and among women with no schooling it is only 8 percent. Nearly one-third of women in major cities arc current users of contraception, but contraceptive use is still rare in rural areas (6 percent). The Government of Pakistan plays a major role in providing family planning services. Eighty-five percent of sterilised women and 81 percent of IUD users obtained services from the public sector. Condoms, however, were supplied primarily through the social marketing programme. The use of contraceptives depends on many factors, including the degree of acceptability of the concept of family planning. Among currently married women who know of a contraceptive method, 62 percent approve of family planning. There appears to be a considerable amount of consensus between husbands and wives about family planning use: one-third of female respondents reported that both they and their husbands approve of family planning, while slightly more than one-fifth said they both disapprove. The latter couples constitute a group for which family planning acceptance will require concerted motivational efforts. The educational levels attained by Pakistani women remain low: 79 percent of women have had no formal education, 14 percent have studied at the primary or middle school level, and only 7 percent have attended at least some secondary schooling. The traditional social structure of Pakistan supports a natural fertility pattern in which the majority of women do not use any means of fertility regulation. In such populations, the proximate determinants of fertility (other than contraception) are crucial in determining fertility levels. These include age at marriage, breastfeeding, and the duration of postpartum amenorrhoea and abstinence. The mean age at marriage has risen sharply over the past few decades, from under 17 years in the 1950s to 21.7 years in 1991. Despite this rise, marriage remains virtually universal: among women over the age of 35, only 2 percent have never married. Marriage patterns in Pakistan are characterised by an unusually high degree of consangninity. Half of all women are married to their first cousin and an additional 11 percent are married to their second cousin. Breasffeeding is important because of the natural immune protection it provides to babies, and the protection against pregnancy it gives to mothers. Women in Pakistan breastfeed their children for an average of20months. Themeandurationofpostpartumamenorrhoeais slightly more than 9 months. After tbebirth of a child, women abstain from sexual relations for an average of 5 months. As a result, the mean duration of postpartum insusceptibility (the period immediately following a birth during which the mother is protected from the risk of pregnancy) is 11 months, and the median is 8 months. Because of differentials in the duration of breastfeeding and abstinence, the median duration of insusceptibility varies widely: from 4 months for women with at least some secondary education to 9 months for women with no schooling; and from 5 months for women residing in major cities to 9 months for women in rural areas. In the PDHS, women were asked about their desire for additional sons and daughters. Overall, 40 percent of currently married women do not want to have any more children. This figure increases rapidly depending on the number of children a woman has: from 17 percent for women with two living children, to 52 percent for women with four children, to 71 percent for women with six children. The desire to stop childbearing varies widely across cultural groupings. For example, among women with four living children, the percentage who want no more varies from 47 percent for women with no education to 84 percent for those with at least some secondary education. Gender preference continues to be widespread in Pakistan. Among currently married non-pregnant women who want another child, 49 percent would prefer to have a boy and only 5 percent would prefer a girl, while 46 percent say it would make no difference. The need for family planning services, as measured in the PDHS, takes into account women's statements concerning recent and future intended childbearing and their use of contraceptives. It is estimated that 25 percent of currently married women have a need for family planning to stop childbearing and an additional 12 percent are in need of family planning for spacing children. Thus, the total need for family planning equals 37 percent, while only 12 percent of women are currently using contraception. The result is an unmet need for family planning services consisting of 25 percent of currently married women. This gap presents both an opportunity and a challenge to the Population Welfare Programme. Nearly one-tenth of children in Pakistan die before reaching their first birthday. The infant mortality rate during the six years preceding the survey is estimaled to be 91 per thousand live births; the under-five mortality rate is 117 per thousand. The under-five mortality rates vary from 92 per thousand for major cities to 132 for rural areas; and from 50 per thousand for women with at least some secondary education to 128 for those with no education. The level of infant mortality is influenced by biological factors such as mother's age at birth, birth order and, most importantly, the length of the preceding birth interval. Children born less than two years after their next oldest sibling are subject to an infant mortality rate of 133 per thousand, compared to 65 for those spaced two to three years apart, and 30 for those born at least four years after their older brother or sister. One of the priorities of the Government of Pakistan is to provide medical care during pregnancy and at the time of delivery, both of which are essential for infant and child survival and safe motherhood. Looking at children born in the five years preceding the survey, antenatal care was received during pregnancy for only 30 percent of these births. In rural areas, only 17 percent of births benefited from antenatal care, compared to 71 percent in major cities. Educational differentials in antenatal care are also striking: 22 percent of births of mothers with no education received antenatal care, compared to 85 percent of births of mothers with at least some secondary education. Tetanus, a major cause of neonatal death in Pakistan, can be prevented by immunisation of the mother during pregnancy. For 30 percent of all births in the five years prior to the survey, the mother received a tetanus toxoid vaccination. The differentials are about the same as those for antenatal care generally. Eighty-five percent of the births occurring during the five years preceding the survey were delivered

SUMMARY This table contains data about women, ages 15 to 50, pregnant people, infants, children, and youths, up to age 24. It contains information about a wide range of health topics, including medical conditions, nutrition, dehydration, oral health, mental health, safety, access to health care, and basic needs, like housing. Local, county-level prevalence rates, time trends, and health disparities about national public health priorities, including preterm birth, infant death, childhood obesity, adolescent depression and substance use, and high blood pressure, diabetes, and kidney disease in young adults. The population data is from the 2023-2024 San Francisco Maternal Child and Adolescent Health needs assessment and is published on the Open Data Portal to share with community partners, plan services, and promote health. For more information see: Maternal, Child, and Adolescent Health Homepage Maternal, Child, and Adolescent Health Reports HOW THE DATASET IS CREATED The Maternal, Child, and Adolescent Health (MCAH) Needs Assessment for San Francisco included review of a wide range of citywide population data covering a ten-year span, from 2014 to 2023. Data from over 83,000 birth records, 59,000 death records, 261,000 emergency room visits, 66,000 hospital admissions, and 90,000 newborn screening discharges were gathered, along with citywide data from child welfare records, health screenings in childcare and schools, DMV records of first-time drivers, school surveys, and a state-run mailed survey of recent births (California Department of Public Health MIHA survey). The datasets provided information about approximately 700 health conditions. Each health condition was described in terms of the number of people affected or cases, and the rate affected, stratified by age, sex, race-ethnicity, insurance status, zip code, and time period. Rates were calculated by dividing the number of people or events by the population group estimate (e.g., total births or census estimates), then multiplying by 100 or 1,000 depending on the measure. Each rate was presented with its 95% confidence interval to support users to compare any two rates, either between groups or over time. Two rates differ “significantly” if their 95% confidence intervals do not overlap. The present dataset summarizes the group-level results for any age-, sex-, race-, insurance-, zip code-, and/or period-specific group that included at least 20 people or cases. Causes of death, health conditions that affected over 1000 people in the time frame, problems that got worse over time, and health disparities by insurance, race-ethnicity and/or zip code were flagged for the MCAH Needs Assessment. UPDATE PROCESS The dataset will be updated manually, bi-annually, each December and June. HOW TO USE THIS DATASET Population data from the MCAH needs assessment are shared in several formats, including aggregated datasets on DataSF.gov, downloadable PDF summary reports by age group, interactive online visualizations, data tables, trend graphs, and maps. Information about each variable is available in a linked data dictionary. The definition of each numerator and denominator depends on data source, life stage, and time. Health conditions may not be directly comparable across life stage, if the numerator definition includes age- or pregnancy-specific diagnosis codes (e.g. diabetes hospitalization). For small groups or rare conditions, consider combining time periods and/or groups. Data are suppressed if fewer than 20 cases happened in the group and period. Group-specific rates are available if the matched group-specific census estimates (denominator) were available. Census estim

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

About this dataset

Context

The dataset tabulates the Lack township population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Lack township. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 - 64 years with a poulation of 377 (56.95% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Lack township population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Lack township is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Lack township is shown in the following column.

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 Lack township Population by Age. You can refer the same here

I’ve also shown the change in rich countries on the chart. From this way of looking at the data, it might seem that child mortality is no longer an issue in rich countries. Their rates are very low and barely visible compared to many other countries. It also looks like almost no progress has been made in the last 30 years: mortality was low and is still low.

But I think both of these conclusions are wrong. Countries in the European Union, Japan, South Korea, the United Kingdom — the list goes on — have made childhood much safer in my own 30-year lifetime.1 It’s just something we rarely hear about. I also don’t think that this is a “solved problem”; it is still too common for parents to see their children die, and there’s a lot more that we can do to save their lives.

We have this perception because we compare countries by their absolute reduction in child mortality. Many low- and middle-income countries have reduced these rates by 5, 10, or 20 percentage points over the last 30 years. Of course, that would be impossible for many richer countries: the child mortality rate in the European Union (EU) was around 1% in 1990, so the maximum reduction it could achieve in absolute terms would be one percentage point.

It’s only when we look at the relative reduction in child mortality that we see that rich countries have also made impressive progress.

The chart below shows these same countries — or groups of countries — plotted as the change in mortality rates since 1990. All of them have halved child mortality rates or more.

In the previous chart, progress in the EU looked a little underwhelming. But, in fact, rates have fallen by 69%. Even in Japan, one of the safest countries to be born in, child mortality rates have dropped by almost two-thirds. Those are not small reductions. Children are much less likely to die than they were in 1990.

This dataset is imported from the US Department of Commerce, National Telecommunications and Information Administration (NTIA) and its "Data Explorer" site. The underlying data comes from the US Census

1. dataset: Specifies the month and year of the survey as a string, in "Mon YYYY" format. The CPS is a monthly survey, and NTIA periodically sponsors Supplements to that survey.

2. variable: Contains the standardized name of the variable being measured. NTIA identified the availability of similar data across Supplements, and assigned variable names to ease time-series comparisons.

3. description: Provides a concise description of the variable.

4. universe: Specifies the variable representing the universe of persons or households included in the variable's statistics. The specified variable is always included in the file. The only variables lacking universes are isPerson and isHouseholder, as they are themselves the broadest universes measured in the CPS.

5. A large number of *Prop, *PropSE, *Count, and *CountSE columns comprise the remainder of the columns. For each demographic being measured (see below), four statistics are produced, including the estimated proportion of the group for which the variable is true (*Prop), the standard error of that proportion (*PropSE), the estimated number of persons or households in that group for which the variable is true (*Count), and the standard error of that count (*CountSE).

DEMOGRAPHIC CATEGORIES

1. us: The usProp, usPropSE, usCount, and usCountSE columns contain statistics about all persons and households in the universe (which represents the population of the fifty states and the District and Columbia). For example, to see how the prevelance of Internet use by Americans has changed over time, look at the usProp column for each survey's internetUser variable.

2. age: The age category is divided into five ranges: ages 3-14, 15-24, 25-44, 45-64, and 65+. The CPS only includes data on Americans ages 3 and older. Also note that household reference persons must be at least 15 years old, so the age314* columns are blank for household-based variables. Those columns are also blank for person-based variables where the universe is "isAdult" (or a sub-universe of "isAdult"), as the CPS defines adults as persons ages 15 or older. Finally, note that some variables where children are technically in the univese will show zero values for the age314* columns. This occurs in cases where a variable simply cannot be true of a child (e.g. the workInternetUser variable, as the CPS presumes children under 15 are not eligible to work), but the topic of interest is relevant to children (e.g. locations of Internet use).

3. work: Employment status is divided into "Employed," "Unemployed," and "NILF" (Not in the Labor Force). These three categories reflect the official BLS definitions used in official labor force statistics. Note that employment status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by work status, even if they are otherwise considered part of the universe for the variable of interest.

4. income: The income category represents annual family income, rather than just an individual person's income. It is divided into five ranges: below $25K, $25K-49,999, $50K-74,999, $75K-99,999, and $100K or more. Statistics by income group are only available in this file for Supplements beginning in 2010; prior to 2010, family income range is available in public use datasets, but is not directly comparable to newer datasets due to the 2010 introduction of the practice of allocating "don't know," "refused," and other responses that result in missing data. Prior to 2010, family income is unkown for approximately 20 percent of persons, while in 2010 the Census Bureau began imputing likely income ranges to replace missing data.

5. education: Educational attainment is divided into "No Diploma," "High School Grad," "Some College," and "College Grad." High school graduates are considered to include GED completers, and those with some college include community college attendees (and graduates) and those who have attended certain postsecondary vocational or technical schools--in other words, it signifies additional education beyond high school, but short of attaining a bachelor's degree or equivilent. Note that educational attainment is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by education, even if they are otherwise considered part of the universe for the variable of interest.

6. sex: "Male" and "Female" are the two groups in this category. The CPS does not currently provide response options for intersex individuals.

7. race: This category includes "White," "Black," "Hispanic," "Asian," "Am Indian," and "Other" groups. The CPS asks about Hispanic origin separately from racial identification; as a result, all persons identifying as Hispanic are in the Hispanic group, regardless of how else they identify. Furthermore, all non-Hispanic persons identifying with two or more races are tallied in the "Other" group (along with other less-prevelant responses). The Am Indian group includes both American Indians and Alaska Natives.

8. disability: Disability status is divided into "No" and "Yes" groups, indicating whether the person was identified as having a disability. Disabilities screened for in the CPS include hearing impairment, vision impairment (not sufficiently correctable by glasses), cognitive difficulties arising from physical, mental, or emotional conditions, serious difficulty walking or climbing stairs, difficulty dressing or bathing, and difficulties performing errands due to physical, mental, or emotional conditions. The Census Bureau began collecting data on disability status in June 2008; accordingly, this category is unavailable in Supplements prior to that date. Note that disability status is only recorded in the CPS for individuals ages 15 and older. As a result, children are excluded from the universe when calculating statistics by disability status, even if they are otherwise considered part of the universe for the variable of interest.

9. metro: Metropolitan status is divided into "No," "Yes," and "Unkown," reflecting information in the dataset about the household's location. A household located within a metropolitan statistical area is assigned to the Yes group, and those outside such areas are assigned to No. However, due to the risk of de-anonymization, the metropolitan area status of certain households is unidentified in public use datasets. In those cases, the Census Bureau has determined that revealing this geographic information poses a disclosure risk. Such households are tallied in the Unknown group.

10. scChldHome:

Adults report more willingness to help siblings over close friends when the stakes are extremely high, such as when deciding whether to donate a kidney or risk injury to rescue someone in peril. When dividing plentiful, low-value resources, in contrast, children expect people to share equally with friends and siblings. Even when distributing limited resources—one instead of many—and distributing to their own social partners rather than fictional characters, children share more with kin and friends than with strangers but do not favor kin over friends until 5.5 years of age. However, no study has tested whether children would preferentially benefit kin if the rewards require that children incur a higher personal cost of their own time and effort. In the present experiment, therefore, we asked if children would work harder for kin over non-kin when playing a challenging geometry game that allowed them to earn rewards for others. We found that 4.5-year-old children calibrated their time and effort in the game differently according to who received the rewards—they played for more trials and answered more trials correctly for kin over non-kin, but 5.5-year-old children did not. The older children may have found the task easier and less costly or may have different social experiences affecting their efforts to benefit others. Nonetheless, 4.5-year-old children’s social decisions favored kin as recipients of their generosity.

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

Dear Partners,

This month, the Administration for Children and Families (ACF) observed World Day Against Child Labor by spotlighting and encouraging those, who could, to join the Within and Beyond Our Borders: Collective Action to Address Hazardous Child Labor organized by the U.S. Department of Labor (DOL) on June 12, 2023. If you missed it, or would like to rewatch it, you can find it here

.

Since 2018, the DOL has seen a 69 percent increase in children being employed illegally by companies. In the last fiscal year, the department found that 835 companies it investigated had employed more than 3,800 children in violation of labor laws. There has been a 26 percent increase in children employed in hazardous occupations. These numbers tell us that we have work to do as the human services sector to learn more and become engaged in preventing unlawful child labor and supporting youth.

As I have said before, child labor exploitation can disrupt a youth’s health, safety, education, and overall well-being, which are unacceptable consequences for any child. The Administration for Children and Families (ACF) supports a broad network of resources for vulnerable youth. We know that migrant and immigrant youth are especially vulnerable to exploitation, and it is often youth in or exiting the child welfare system who are targeted for various forms of exploitation. Child labor exploitation can impact children and youth across demographics.

On March 24, 2023, the DOL and the U.S. Department of Health and Human Services (HHS) announced a Memorandum of Agreement - PDF

to advance ongoing efforts to address child labor exploitation. In addition, DOL and HHS are collaborating on training and educational materials.

As we expand this work, we know how important our partners throughout the country are in this effort. The Administration for Children and Families (ACF) is committed to addressing the increased presence of child labor exploitation through a variety of actions including equipping partners with materials and educational resources to build knowledge about child labor laws and rights, and remedies. This information is important for our human services sector and the children and families who may be most at risk.

Please join ACF in increasing awareness and distributing resources to address child labor exploitation including the following:

ACF resources may be also useful when working with a youth who has concerns about their safety. This includes the Family and Youth Services Bureau (FYSB)’s program on Runaway and Homeless Youth which provides a hotline for youth, concerned adults, and providers to access resources. At, www.1800runaway.org

, their 24/7 crisis connection allows for calls, texts, live chat, and email to get information and resources.

In addition, ACF’s Office of Trafficking In-Persons (OTIP) is an important resource for identifying and supporting survivors of trafficking. The National Human Trafficking Hotline

provides a 24/7, confidential, multilingual hotline for victims, survivors, and witnesses of human trafficking. While labor exploitation should not be conflated with labor trafficking, in some cases labor exploitation may rise to meet the legal definitions of trafficking. The OTIP website

contains many resources for grantees and communities on labor trafficking.

Again, I hope you will continue to build awareness for yourself, your organization, or your community on child labor exploitation. It takes a whole community effort to support our children and youth.

Most sincerely,

January Contreras

Metadata-only record linking to the original dataset. Open original dataset below.

The Active Lives Children and Young People Survey, which was established in September 2017, provides a world-leading approach to gathering data on how children engage with sport and physical activity. This school-based survey is the first and largest established physical activity survey with children and young people in England. It gives anyone working with children aged 5-16 key insight to help understand children's attitudes and behaviours around sport and physical activity. The results will shape and influence local decision-making as well as inform government policy on the PE and Sport Premium, Childhood Obesity Plan and other cross-departmental programmes. More general information about the study can be found on the Sport England Active Lives Survey webpage and the Active Lives Online website, including reports and data tables.

Due to the closure of school sites during the coronavirus pandemic, the Active Lives Children and Young People survey was adapted to allow at-home completion. This approach was retained into the academic year 2022-23 to help maximise response numbers. The at-home completion approach was actively offered for secondary school pupils, and allowed but not encouraged for primary pupils.

The adaptions involved minor questionnaire changes (e.g., to ensure the wording was appropriate for those not attending school and enabling completion at home) and communication changes. For further details on the survey changes, please see the accompanying User Guide document. Academic years 2020-21, 2021-22 and 2022-23 saw a more even split of responses by term across the year, compared to 2019-20, which had a reduced proportion of summer term responses due to the disruption caused by Covid-19.

The survey identifies how participation varies across different activities and sports, by regions of England, between school types and terms, and between different demographic groups in the population. The survey measures levels of activity (active, fairly active and less active), attitudes towards sport and physical activity, swimming capability, the proportion of children and young people that volunteer in sport, sports spectating, and wellbeing measures such as happiness and life satisfaction. The questionnaire was designed to enable analysis of the findings by a broad range of variables, such as gender, family affluence and school year.

The following datasets have been provided:

1) Main dataset: this file includes responses from children and young people from school years 3 to 11, as well as responses from parents of children in years 1-2. The parents of children in years 1-2 provide behavioural answers about their child’s activity levels; they do not provide attitudinal information. Using this main dataset, full analyses can be carried out into sports and physical activity participation, levels of activity, volunteering (years 5 to 11), etc. Weighting is required when using this dataset (wt_gross / wt_gross - Csplan files are available for SPSS users who can utilise them).

2) Year 1-2 dataset: This file includes responses directly from children in school years 1-2, providing their attitudinal responses (e.g., whether they like playing sport and find it easy). Analysis can also be carried out into feelings towards swimming, enjoyment of being active, happiness, etc. Weighting is required when using this dataset (wt_gross / wt_gross - Csplan files are available for SPSS users who can utilise them).

3) Teacher dataset: This file includes responses from the teachers at schools selected for the survey. Analysis can be carried out to determine school facilities available, the length of PE lessons, whether swimming lessons are offered, etc. Since December 2023, Sport England has provided weighting for the teacher data (‘wt_teacher’ weighting variable).

For further information, please read the supporting documentation before using the datasets.

SUMMARYLevels of inactivity within children and young people (school years 1-11, aged 5-16) during the 2018/19 academic year. A child or young person was deemed to have been inactive if they carried out less than an average of 30 mins exercise a day (less than 210 mins a week) during this period.ANALYSIS METHODOLOGYEach district was given a relative score between 1 and 0 (1 = worst, 0 = best) based on:A) the NUMBER of children who are inactive and;B) the PERCENTAGE of children who are inactive.An average of scores A & B was taken, and converted to a relative score between 1 and 0 (1= worst, 0 = best). The closer to 1 the score, the greater both the number and percentage of children who are inactive within that district, compared to other districts. In other words, those are areas where a large number of children are inactive, and where those children make up a large percentage of the childhood population, indicating there is a real issue with childhood inactivity within the population and the investment of resources to address this issue could have the greatest benefits.DATA SOURCESActive Lives Survey 2019: Sport and Physical Activity Levels amongst children and young people in school years 1-11 (aged 5-16). © Sport England 2020.Administrative boundaries: Boundary-LineTM: Contains Ordnance Survey data © Crown copyright and database right 2021. Contains public sector information licensed under the Open Government Licence v3.0.COPYRIGHT NOTICEBased on data © Sport England 2020. Contains Ordnance Survey data © Crown copyright and database right 2021. Contains public sector information licensed under the Open Government Licence v3.0. Data analysed and published by Ribble Rivers Trust © 2021.CaBA HEALTH & WELLBEING EVIDENCE BASEThis dataset forms part of the wider CaBA Health and Wellbeing Evidence Base.

The 1993 Turkish Demographic and Health Survey (TDHS) is a nationally representative survey of ever-married women less than 50 years old. The survey was designed to provide information on fertility levels and trends, infant and child mortality, family planning, and maternal and child health. The TDHS was conducted by the Hacettepe University Institute of Population Studies under a subcontract through an agreement between the General Directorate of Mother and Child Health and Family Planning, Ministry of Health and Macro International Inc. of Calverton, Maryland. Fieldwork was conducted from August to October 1993. Interviews were carried out in 8,619 households and with 6,519 women. The Turkish Demographic and Health Survey (TDHS) is a national sample survey of ever-married women of reproductive ages, designed to collect data on fertility, marriage patterns, family planning, early age mortality, socioeconomic characteristics, breastfeeding, immunisation of children, treatment of children during episodes of illness, and nutritional status of women and children. The TDHS, as part of the international DHS project, is also the latest survey in a series of national-level population and health surveys in Turkey, which have been conducted by the Institute of Population Studies, Haeettepe University (HIPS). More specifically, the objectives of the TDHS are to: Collect data at the national level that will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; Analyse the direct and indirect factors that determine levels and trends in fertility and childhood mortality; Measure the level of contraceptive knowledge and practice by method, region, and urban- rural residence; Collect data on mother and child health, including immunisations, prevalence and treatment of diarrhoea, acute respiratory infections among children under five, antenatal care, assistance at delivery, and breastfeeding; Measure the nutritional status of children under five and of their mothers using anthropometric measurements. The TDHS information is intended to assist policy makers and administrators in evaluating existing programs and in designing new strategies for improving family planning and health services in Turkey. MAIN RESULTS Fertility in Turkey is continuing to decline. If Turkish women maintain current fertility rates during their reproductive years, they can expect to have all average of 2.7 children by the end of their reproductive years. The highest fertility rate is observed for the age group 20-24. There are marked regional differences in fertility rates, ranging from 4.4 children per woman in the East to 2.0 children per woman in the West. Fertility also varies widely by urban-rural residence and by education level. A woman living in rural areas will have almost one child more than a woman living in an urban area. Women who have no education have almost one child more than women who have a primary-level education and 2.5 children more than women with secondary-level education. The first requirement of success ill family planning is the knowledge of family planning methods. Knowledge of any method is almost universal among Turkish women and almost all those who know a method also know the source of the method. Eighty percent of currently married women have used a method sometime in their life. One third of currently married women report ever using the IUD. Overall, 63 percent of currently married women are currently using a method. The majority of these women are modern method users (35 percent), but a very substantial proportion use traditional methods (28 percent). the IUD is the most commonly used modern method (I 9 percent), allowed by the condom (7 percent) and the pill (5 percent). Regional differences are substantial. The level of current use is 42 percent in tile East, 72 percent in tile West and more than 60 percent in tile other three regions. "File common complaints about tile methods are side effects and health concerns; these are especially prevalent for the pill and IUD. One of the major child health indicators is immunisation coverage. Among children age 12-23 months, the coverage rates for BCG and the first two doses of DPT and polio were about 90 percent, with most of the children receiving those vaccines before age one. The results indicate that 65 percent of the children had received all vaccinations at some time before the survey. On a regional basis, coverage is significantly lower in the Eastern region (41 percent), followed by the Northern and Central regions (61 percent and 65 percent, respectively). Acute respiratory infections (ARI) and diarrhea are the two most prevalent diseases of children under age five in Turkey. In the two weeks preceding the survey, the prevalence of ARI was 12 percent and the prevalence of diarrhea was 25 percent for children under age five. Among children with diarrhea 56 percent were given more fluids than usual. Breastfeeding in Turkey is widespread. Almost all Turkish children (95 percent) are breastfed for some period of time. The median duration of breastfeeding is 12 months, but supplementary foods and liquids are introduced at an early age. One-third of children are being given supplementary food as early as one month of age and by the age of 2-3 months, half of the children are already being given supplementary foods or liquids. By age five, almost one-filth of children arc stunted (short for their age), compared to an international reference population. Stunting is more prevalent in rural areas, in the East, among children of mothers with little or no education, among children who are of higher birth order, and among those born less than 24 months after a prior birth. Overall, wasting is not a problem. Two percent of children are wasted (thin for their height), and I I percent of children under five are underweight for their age. The survey results show that obesity is d problem among mothers. According to Body Mass Index (BMI) calculations, 51 percent of mothers are overweight, of which 19 percent are obese.

One in every 100 children dies before completing one year of life. Around 68 percent of infant mortality is attributed to deaths of children before completing 1 month. 15,000 children die every day – Child mortality is an everyday tragedy of enormous scale that rarely makes the headlines Child mortality rates have declined in all world regions, but the world is not on track to reach the Sustainable Development Goal for child mortality Before the Modern Revolution child mortality was very high in all societies that we have knowledge of – a quarter of all children died in the first year of life, almost half died before reaching the end of puberty Over the last two centuries all countries in the world have made very rapid progress against child mortality. From 1800 to 1950 global mortality has halved from around 43% to 22.5%. Since 1950 the mortality rate has declined five-fold to 4.5% in 2015. All countries in the world have benefitted from this progress In the past it was very common for parents to see children die, because both, child mortality rates and fertility rates were very high. In Europe in the mid 18th century parents lost on average between 3 and 4 of their children Based on this overview we are asking where the world is today – where are children dying and what are they dying from?

5.4 million children died in 2017 – Where did these children die? Pneumonia is the most common cause of death, preterm births and neonatal disorders is second, and diarrheal diseases are third – What are children today dying from? This is the basis for answering the question what can we do to make further progress against child mortality? We will extend this entry over the course of 2020.

@article{owidchildmortality, author = {Max Roser, Hannah Ritchie and Bernadeta Dadonaite}, title = {Child and Infant Mortality}, journal = {Our World in Data}, year = {2013}, note = {https://ourworldindata.org/child-mortality} }

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

Percentage of children aged 5-16 that meet the UK Chief Medical Officers' (CMOs') recommendations for physical activity (an average of at least 60 minutes moderate-vigorous intensity activity per day across the week). Weighted number of respondents reporting participation in sport and physical activity for at least 420 minutes in the last 7 days. Data is collected between September and July (term time only). Where a numerator is less than 30 for a Local Authority area, results are not presented. The values are calculated from a self-report survey, which is subjective and is influenced by the respondent's ability to recall and assess their physical activity levels. Self-reported data may also be affected by respondent desire to confirm to expectations and social norms (e.g. smoking under-estimated and PA over-estimated). However, although this might affect the absolute values, this should not affect comparisons if the bias is consistent across populations. Although a sampling framework has been developed, the selection of schools is carried out by County Sports Partnerships, who contact the schools and encourage them to take part. As not all schools are surveyed, there is the possibility that only those schools with a strong commitment to physical activity take part in the survey.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.