Abstract

The 1995 Kazakstan Demographic and Health Survey (KDHS) is part of the worldwide Demographic and Health Surveys (DHS) program, which is designed to collect data on fertility, family planning and maternal and child health. The 1995 KDHS was the first national level population and health survey in Kazakstan. The purpose of the survey was to provide the Ministry of Health of Kazakstan with information on fertility, reproductive practices of women, maternal care, child health and mortality, child nutrition practices, breastfeeding, nutritional status and anemia. This information is important for understanding the factors that influence the reproductive health of women and the health and survival of infants and young children. It can be used in planning effective policies and programs regarding the health and nutrition of women and their children. This is especially important now during this the time of economic transition which involves virtually all aspects of life for the people of Kazakstan. The survey provides data important to the assessment of the overall demographic situation in the country. It is expected that the findings of the KDHS will become a useful source of information necessary for the ongoing health care reform in Kazakstan.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

The 1995 KDHS employed a nationally representative probability sample of women age 15-49. The country was divided into five survey regions. Four survey regions consisted of groups of contiguous oblasts (except the East Kazakstanskaya oblast which is not contiguous). Almaty City constituted a survey region by itself although it is part of the Almatinskaya oblast. The five survey regions were defined as follows:

I) Almaty City 2) South Region: Taldy-Korganskaya, Almatinskaya (except Almaty city), Dzhambylskaya, South Kazakstanskaya, and Kzyl-Ordinskaya 3) West Region: Aktiubinskaya, Mangistauskaya, Atyrauskaya, and West Kazakstanskaya 4) Central Region: Semipalatinskaya, Zhezkazganskaya, and Tourgaiskaya 5) North and East Region: East Kazakstanskaya, Pavlodarskaya, Karagandinskaya, Akmolinskaya, Kokchetauskaya, North Kazakstanskaya, and Koustanaiskaya

It is important to note that the oblast composition of regions outside of Almaty City was determined on the basis of geographic proximity, and in order to achieve similarity with respect to reproductive practices within regions. The South and West Regions are comprised of oblasts which traditionally have a high proportion of Kazak population and high fertility levels. The Central Region contains three oblasts in which the fertility level is similar to the national average. The North and East Region contains seven oblasts situated in northern Kazakstan in which a relatively high proportion of the population is of Russian origin, and the fertility level is lower than the national average.

In Almaty City, the sample for the 1995 KDHS was selected in two stages. In the first stage, 40 census counting blocks were selected with equal probability from the 1989 list of census counting blocks. A complete listing of the households in the selected counting blocks was carried out. The lists of households served as the frame for second-stage sampling; i.e., the selection of the households to be visited by the KDHS interviewing teams. In each selected household, women age 15-49 were eligible to be interviewed.

In the rural areas, the primary sampling units (PSUs) were the raions which were selected with probability proportional to size, the size being the 1993 population published by Goskomstat (1993). At the second stage, one village was selected in each selected raion, from the 1989 Registry of Villages. This resulted in 50 rural clusters being selected. At the third stage, households were selected in each cluster following the household listing operation as in Almaty City.

In the urban areas other than Almaty City, the PSUs were the cities and towns themselves. In the second stage, one health block was selected from each town except in self-representing cities (large cities that were selected with certainty) where more than one health block was selected. The selected health blocks were segmented prior to the household listing operation which provided the household lists for the third stage selection of households. In total, 86 health blocks were selected.

On average, 22 households were selected in each urban cluster, and 33 households were selected in each rural cluster. It was expected that the sample would yield interviews with approximately 4,000 women between the ages of 15 and 49.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face

Research instrument

Two questionnaires were used for the 1995 KDHS: the Household Questionnaire and the Individual Questionnaire. The questionnaires were based on the model survey instruments developed in the DHS program. They were adapted to the data needs of Kazakhstan during consultations with specialists in the areas of reproductive health, child health and nutrition in Kazakhstan.

The Household Questionnaire was used to enumerate all usual members and visitors in tile sample households and to collect information relating to the socioeconomic position of a household. In the: first part of the Household Questionnaire, information was collected on age, sex, educational attainment, marital status, and relationship to the head of household of each person listed as a household member or visitor. A primary objective of the first part of the Household Questionnaire was to identify women who were eligible for the individual interview. In the second part of the Household Questionnaire, questions were included on the dwelling unit, such as the number of rooms, the flooring material, the source of water, the type of toilet facilities, and on the availability of a variety of consumer goods.

The Individual Questionnaire was used to collect information from women age 15-49. These women were asked questions on the following major topics: - Background characteristics - Pregnancy history - Outcome of pregnancies and antenatal care - Child health and nutrition practices - Child immunization and episodes of diarrhea and respiratory illness - Knowledge and use of contraception - Marriage and fertility preferences - Husband's background and woman's work - Anthropometry of children and mothers - Hemoglobin measurement of women and children

One of the major efforts of the 1995 KDHS was testing women and children for iron-deficiency anemia. Testing was done by measuring hemoglobin levels in the blood using the Hemocue technique. Before collecting the blood sample, each woman was asked to sign a consent form giving permission for the collection of a finger-stick blood droplet from herself and her children. Results of anemia testing were kept confidential (as are all KDHS data); however, strictly with the consent of respondents, local health care facilities were informed of women and children who had severely low levels of hemoglobin (less than 7 g/dl).

Cleaning operations

Questionnaires were returned to the Institute of Nutrition in Almaty for data processing. The office editing staff checked that the questionnaires for all selected households and eligible respondents were returned from the field. The few questions which had not been pre-coded (e.g., occupation, type of chronic disease) were coded at this time. Data were then entered and edited on microcomputers using the ISSA (Integrated System for Survey Analysis) package, with the data entry software translated into Russian. Office editing and data entry activities began in May 1995 (i.e., the same time that fieldwork started) and were completed in September 1995.

Response rate

A total of 4,480 households were selected in the sample, of which 4,241 were occupied at the time of fieldwork. The main reason for the difference was that some dwelling units which were occupied at the time of the household listing operation were either vacant or the household members were away for an extended period at the time of interviewing. Of the 4,241 occupied households, 4,178 were interviewed, yielding a household response rate of 99 percent.

In the interviewed households, 3,899 women were eligible for the individual interview (i.e., all women 15-49 years of age who were either usual residents or visitors who had spent the previous night in the household). Interviews were successfully completed with 3,771 of these women, yielding a response rate of 97 percent. The principal reason for non-response was the failure to find an eligible woman at home after repeated visits to the household. The overall response rate for the survey--the product of the household and the individual response rates--was 95 percent.

Note: See summarized response rates by place of residence in Table 1.1 of the survey report .

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the KDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate

Austria Population: Children: Below 15 Years of Age data was reported at 1,308.300 Person th in 2023. This records an increase from the previous number of 1,299.000 Person th for 2022. Austria Population: Children: Below 15 Years of Age data is updated yearly, averaging 1,291.500 Person th from Dec 1994 (Median) to 2023, with 30 observations. The data reached an all-time high of 1,413.487 Person th in 1995 and a record low of 1,212.500 Person th in 2013. Austria Population: Children: Below 15 Years of Age data remains active status in CEIC and is reported by Statistics Austria. The data is categorized under Global Database’s Austria – Table AT.G001: Population.

BackgroundAssessing exposure to infections in early childhood is of interest in many epidemiological investigations. Because exposure to infections is difficult to measure directly, epidemiological studies have used surrogate measures available from routine data such as birth order and population density. However, the association between population density and exposure to infections is unclear. We assessed whether neighbourhood child population density is associated with respiratory infections in infants.MethodsWith the Basel-Bern lung infant development study (BILD), a prospective Swiss cohort study of healthy neonates, respiratory symptoms and infections were assessed by weekly telephone interviews with the mother throughout the first year of life. Using population census data, we calculated neighbourhood child density as the number of children < 16 years of age living within a 250 m radius around the residence of each child. We used negative binomial regression models to assess associations between neighbourhood child density and the number of weeks with respiratory infections and adjusted for potential confounders including the number of older siblings, day-care attendance and duration of breastfeeding. We investigated possible interactions between neighbourhood child population density and older siblings assuming that older siblings mix with other children in the neighbourhood.ResultsThe analyses included 487 infants. We found no evidence of an association between quintiles of neighbourhood child density and number of respiratory symptoms (p = 0.59, incidence rate ratios comparing highest to lowest quintile: 1.15, 95%-confidence interval: 0.90–1.47). There was no evidence of interaction with older siblings (p = 0.44). Results were similar in crude and in fully adjusted models.ConclusionsOur study suggests that in Switzerland neighbourhood child density is a poor proxy for exposure to infections in infancy.

The typical American picture of a family with 2.5 kids might not be as relevant as it once was: In 2023, there was an average of 1.94 children under 18 per family in the United States. This is a decrease from 2.33 children under 18 per family in 1960.

Familial structure in the United States

If there’s one thing the United States is known for, it’s diversity. Whether this is diversity in ethnicity, culture, or family structure, there is something for everyone in the U.S. Two-parent households in the U.S. are declining, and the number of families with no children are increasing. The number of families with children has stayed more or less constant since 2000.

Adoptions in the U.S.

Families in the U.S. don’t necessarily consist of parents and their own biological children. In 2021, around 35,940 children were adopted by married couples, and 13,307 children were adopted by single women.

Intussusception is a serious disorder whereby part of the intestine slides into an adjacent part of the intestine in a manner similar to a collapsable telescope. This edition of Health Trends Alberta looks at intussusception rates by sex in Alberta between 1995 and 2013.

The world's population first reached one billion people in 1805, and reached eight billion in 2022, and will peak at almost 10.2 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two-thirds of the world's population lives in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a few years later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

This table contains data on mortality, the balance of foreign migration and the balance of administrative corrections, of children under 2 years of age belonging to the population of the Netherlands. The data are broken down by gender, age (on the last birthday) in days and months and year of birth. The above data are used in the calculation of mortality ratios by age on last birthday (in days and months).

Data available: 1995 to 2000.

Status of the figures: The data in this table are final.

Changes as of 30 April 2018: None, this table has been discontinued.

When are new figures coming? No longer applicable.

The consultants of the social statistic recommended the September 1995 survey to be on the topic of “housekeeping and child care. This field had already been the topic of several special programs under the titles living conditions of the female population in 1969 and 1977 and “household - children - employment in 1983. The comparison of this survey with those from the previous years shows changes in the behaviour of the partners concerning housekeeping and childcare and how much this change is the result of the increasing employment of women outside the household. Adequate institutional childcare which allows women to accommodate childcare and employment has been of public interest for the last years. An important aspect is the question of to what extent care and education is transferred from the family to public institutions.

Abstract

The 1995 Uganda Demographic and Health Survey (UDHS-II) is a nationally-representative survey of 7,070 women age 15-49 and 1,996 men age 15-54. The UDHS was designed to provide information on levels and trends of fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. Fieldwork for the UDHS took place from late-March to mid-August 1995. The survey was similar in scope and design to the 1988-89 UDHS. Survey data show that fertility levels may be declining, contraceptive use is increasing, and childhood mortality is declining; however, data also point to several remaining areas of challenge.

The 1995 UDHS was a follow-up to a similar survey conducted in 1988-89. In addition to including most of the same questions included in the 1988-89 UDHS, the 1995 UDHS added more detailed questions on AIDS and maternal mortality, as well as incorporating a survey of men. The general objectives of the 1995 UDHS are to: - provide national level data which will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; - analyse the direct and indirect factors which determine the level and trends of fertility; - measure the level of contraceptive knowledge and practice (of both women and men) by method, by urban-rural residence, and by region; - collect reliable data on maternal and child health indicators; immunisation, prevalence, and treatment of diarrhoea and other diseases among children under age four; antenatal visits; assistance at delivery; and breastfeeding; - assess the nutritional status of children under age four and their mothers by means of anthropometric measurements (weight and height), and also child feeding practices; and - assess among women and men the prevailing level of specific knowledge and attitudes regarding AIDS and to evaluate patterns of recent behaviour regarding condom use.

MAIN RESULTS

• Fertility:

Fertility Trends. UDHS data indicate that fertility in Uganda may be starting to decline. The total fertility rate has declined from the level of 7.1 births per woman that prevailed over the last 2 decades to 6.9 births for the period 1992-94. The crude birth rate for the period 1992-94 was 48 live births per I000 population, slightly lower than the level of 52 observed from the 1991 Population and Housing Census. For the roughly 80 percent of the country that was covered in the 1988-89 UDHS, fertility has declined from 7.3 to 6.8 births per woman, a drop of 7 percent over a six and a half year period.

Birth Intervals. The majority of Ugandan children (72 percent) are born after a "safe" birth interval (24 or more months apart), with 30 percent born at least 36 months after a prior birth. Nevertheless, 28 percent of non-first births occur less than 24 months after the preceding birth, with 10 percent occurring less than 18 months since the previous birth. The overall median birth interval is 29 months. Fertility Preferences. Survey data indicate that there is a strong desire for children and a preference for large families in Ugandan society. Among those with six or more children, 18 percent of married women want to have more children compared to 48 percent of married men. Both men and women desire large families.

• Family planning:

Knowledge of Contraceptive Methods. Knowledge of contraceptive methods is nearly universal with 92 percent of all women age 15-49 and 96 percent of all men age 15-54 knowing at least one method of family planning. Increasing Use of Contraception. The contraceptive prevalence rate in Uganda has tripled over a six-year period, rising from about 5 percent in approximately 80 percent of the country surveyed in 1988-89 to 15 percent in 1995.

Source of Contraception. Half of current users (47 percent) obtain their methods from public sources, while 42 percent use non-governmental medical sources, and other private sources account for the remaining 11 percent.

• Maternal and child health:

High Childhood Mortality. Although childhood mortality in Uganda is still quite high in absolute terms, there is evidence of a significant decline in recent years. Currently, the direct estimate of the infant mortality rate is 81 deaths per 1,000 births and under five mortality is 147 per 1,000 births, a considerable decline from the rates of 101 and 180, respectively, that were derived for the roughly 80 percent of the country that was covered by the 1988-89 UDHS.

Childhood Vaccination Coverage. One possible reason for the declining mortality is improvement in childhood vaccination coverage. The UDHS results show that 47 percent of children age 12-23 months are fully vaccinated, and only 14 percent have not received any vaccinations.

Childhood Nutritional Status. Overall, 38 percent of Ugandan children under age four are classified as stunted (low height-for-age) and 15 percent as severely stunted. About 5 percent of children under four in Uganda are wasted (low weight-for-height); 1 percent are severely wasted. Comparison with other data sources shows little change in these measures over time.

• AIDS:

Virtually all women and men in Uganda are aware of AIDS. About 60 percent of respondents say that limiting the number of sexual partners or having only one partner can prevent the spread of disease. However, knowledge of ways to avoid AIDS is related to respondents' education. Safe patterns of sexual behaviour are less commonly reported by respondents who have little or no education than those with more education. Results show that 65 percent of women and 84 percent of men believe that they have little or no chance of being infected.

Availability of Health Services. Roughly half of women in Uganda live within 5 km of a facility providing antenatal care, delivery care, and immunisation services. However, the data show that children whose mothers receive both antenatal and delivery care are more likely to live within 5 km of a facility providing maternal and child health (MCH) services (70 percent) than either those whose mothers received only one of these services (46 percent) or those whose mothers received neither antenatal nor delivery care (39 percent).

Geographic coverage

The 1995 Uganda Demographic and Health Survey (UDHS-II) is a nationally-representative survey. For the purpose of the 1995 UDHS, the following domains were utilised: Uganda as a whole; urban and rural areas separately; each of the four regions: Central, Eastern, Northern, and Western; areas in the USAID-funded DISH project to permit calculation of contraceptive prevalence rates.

Analysis unit

• Household
• Women age 15-49
• Men age 15-54
• Children under four

Universe

The population covered by the 1995 UDHS is defined as the universe of all women age 15-49 in Uganda. But because of insecurity, eight EAs could not be surveyed (six in Kitgum District, one in Apac District, and one in Moyo District). An additional two EAs (one in Arua and one in Moroto) could not be surveyed, but substitute EAs were selected in their place.

Kind of data

Sample survey data

Sampling procedure

A sample of 303 primary sampling units (PSU) consisting of enumeration areas (EAs) was selected from a sampling frame of the 1991 Population and Housing Census. For the purpose of the 1995 UDHS, the following domains were utilised: Uganda as a whole; urban and rural areas separately; each of the four regions: Central, Eastern, Northern, and Western; areas in the USAID-funded DISH project to permit calculation of contraceptive prevalence rates.

Districts in the DISH project area were grouped by proximity into the following five reporting domains: - Kasese and Mbarara Districts - Masaka and Rakai Districts - Luwero and Masindi Districts - Jinja and Kamuli Districts - Kampala District

The sample for the 1995 UDHS was selected in two stages. In the first stage, 303 EAs were selected with probability proportional to size. Then, within each selected EA, a complete household listing and mapping exercise was conducted in December 1994 forming the basis for the second-stage sampling. For the listing exercise, 11 listers from the Statistics Department were trained. Institutional populations (army barracks, hospitals, police camps, etc.) were not listed.

From these household lists, households to be included in the UDHS were selected with probability inversely proportional to size based on the household listing results. All women age 15-49 years in these households were eligible to be interviewed in the UDHS. In one-third of these selected households, all men age 15-54 years were eligible for individual interview as well. The overall target sample was 6,000 women and 2,000 men. Because of insecurity, eight EAs could not be surveyed (six in Kitgum District, one in Apac District, and one in Moyo District). An additional two EAs (one in Arua and one in Moroto) could not be surveyed, but substitute EAs were selected in their place.

Since one objective of the survey was to produce estimates of specific demographic and health indicators for the areas included in the DISH project, the sample design allowed for oversampling of households in these districts relative to their actual proportion in the population. Thus, the 1995 UDHS sample is not self-weighting at the national level; weights are required to estimate national-level indicators. Due to the weighting factor and rounding of estimates, figures may not add to totals. In addition, the percent total may not add to 100.0 due to rounding.

Mode of data collection

Face-to-face

Research instrument

Four questionnaires were used in the 1995 UDHS.

a) A Household Schedule was used to list the names and certain

About this dataset

Context

The dataset tabulates the Haverhill 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 Haverhill. 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 to 64 years with a poulation of 95 (56.21% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Haverhill population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Haverhill is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Haverhill 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 Haverhill Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the East Greenville 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 East Greenville. 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 1,995 (63.56% 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 East Greenville population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in East Greenville is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the East Greenville 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 East Greenville Population by Age. You can refer the same here

High social status is often associated with greater mating opportunities and fertility for men, but do women also obtain fitness benefits of high status? Greater resource access and child survivorship may be principal pathways through which social status increases women’s fitness. Here we examine whether peer-rankings of women’s social status (indicated by political influence, project leadership and respect) positively covaries with child nutritional status and health in a community of Amazonian horticulturalists. We find that maternal political influence, but not fathers’, is associated with improved child health outcomes in models adjusting for maternal age, parental height and weight, level of schooling, household income, family size, and number of co-resident kin in the community. Children of politically influential women have higher weight-for-age (B=0.33; 95% CI= 0.12 – 0.54), height-for-age (B=0.32; 95%CI=0.10 – 0.54), and weight-for-height (B= 0.24; 95% CI=0.04 – 0.44), and they are less likely to be diagnosed with common illnesses (OR= 0.48; 95% CI= 0.31 – 0.76). These results are consistent with women leveraging their social status to enhance reproductive success through improvements in child health. We discuss these results in light of parental investment theory and the implications for the evolution of female social status in humans.

Methods Social status. All resident adults in the village of study were rated by peers on three dimensions of social status: political influence, project leadership and respect. Six women and six men from the village were randomly selected as raters and were asked to evaluate photographs of community members, for each of the following questions: 1) “Whose voice carries the most weight during community debates?” (“political influence”); 2) “Who knows how to manage community projects?” (“project leadership”); and 3) “Who receives more respect in the village?” (“respect”). Men and women’s photographs were included in the same array and evaluated together by each rater.

Child health. From 2012 to 2016, as part of the Tsimane Health and Life History Project’s (THLHP) focus on health, growth and development, team physicians collected anthropometric measurements and diagnosed children’s illnesses during annual or biannual medical exams. Of the men and women whose social status measures were collected in 2014, 47 women and men had children aged 0 to 16 years who had been evaluated by the THLHP between 2012 and 2016, and who were included in our dataset resulting in 342 observations. Children’s standing and sitting height were measured without shoes to the nearest millimeter with a portable Seca 213 stadiometer. Weight was measured with a Tanita BF-572 scale in light clothing without shoes. Anthropometric measurements were used to assess population-specific z-scores (sensu [35]; localgrowth R package: https://github.com/adblackwell/localgrowth) for 1) weight-for-age (indicator of low weight), 2) height-for-age (indicator of stunting), and 3) weight-for-height (indicator of wasting). Using bilingual (Spanish-Tsimane) research assistants, physicians also diagnosed children’s illnesses using the International Classification of Diseases (ICD-10). Clinical diagnoses were binary (disease present or absent) and grouped into three categories reflecting common illnesses: gastrointestinal diseases , respiratory infections and anemia.

Socio-demographics. Demographic data used to determine kinship, age and live births per woman at the time of the child’s medical visit come from reproductive histories collected from 2003-2005 and updated annually thereafter. In interviews conducted by lead authors in 2014, parents also reported their years of schooling and income over the past year.

Child's age, maternal age, and all parental attributes were standardized in our analysis. Household income was logged then standardized.

About this dataset

Context

The dataset tabulates the Coquille 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 Coquille. 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 to 64 years with a poulation of 1,995 (49.64% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age 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 Coquille population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Coquille is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Coquille 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 Coquille Population by Age. You can refer the same here

The fertility rate of a country is the average number of children that women from that country will have throughout their reproductive years. In the United States in 1800, the average woman of childbearing age would have seven children over the course of their lifetime. As factors such as technology, hygiene, medicine and education improved, women were having fewer children than before, reaching just two children per woman in 1940. This changed quite dramatically in the aftermath of the Second World War, rising sharply to over 3.5 children per woman in 1960 (children born between 1946 and 1964 are nowadays known as the 'Baby Boomer' generation, and they make up roughly twenty percent of todays US population). Due to the end of the baby boom and increased access to contraception, fertility reached it's lowest point in the US in 1980, where it was just 1.77. It did however rise to over two children per woman between 1995 and 2010, although it is expected to drop again by 2020, to just 1.78.

About this dataset

Context

The dataset tabulates the Kaktovik 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 Kaktovik. 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 to 64 years with a poulation of 95 (62.09% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age 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 Kaktovik population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Kaktovik is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Kaktovik 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 Kaktovik Population by Age. You can refer the same here

Introduction: The first 2 years of life are a window of opportunity to obtain adequate growth and development of children, for this reason it was proposed to analyze the evolution of the nutritional status by anthropometric indicators in a child population benefiting from a comprehensive care program for children early childhood from birth to two years of age, to contribute to the early detection of nutritional disorders and strengthen the prevention and timely treatment of malnutrition. Methods: Descriptive longitudinal study with a sample of 142 boys and girls from 0 to 24 months of age. An analysis of each anthropometric indicator (height for age, weight for age, weight for height and body mass index) and denomination with a 95% confidence interval was performed. Results: 47.9% were boys and 52.1% girls from 0 to 2 years old. Prevalence of delay in taller height (18.3%) at 2 months, age-appropriate height greater than 57% in all measurements. Global and acute malnutrition greater than 1.4% and 0.7% respectively. Risk of overweight with the highest value (19.7%) at 12 and 18 months. Conclusion: Malnutrition is a problem that affects this child population from birth, however, it is also important to highlight that both the risk of malnutrition and that of overweight are relevant in monitoring the nutritional status of this population.

Abstract

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.

Geographic coverage

The Turkish Demographic and Health Survey (TDHS) is a national sample survey.

Analysis unit

• Household
• Women age 12-49
• Children under five

Universe

The population covered by the 1993 DHS is defined as the universe of all ever-married women age 12-49 who were present in the household on the night before the interview were eligible for the survey.

Kind of data

Sample survey data

Sampling procedure

The sample for the TDHS was designed to provide estimates of population and health indicators, including fertility and mortality rates for the nation as a whole, fOr urban and rural areas, and for the five major regions of the country. A weighted, multistage, stratified cluster sampling approach was used in the selection of the TDHS sample.

Sample selection was undertaken in three stages. The sampling units at the first stage were settlements that differed in population size. The frame for the selection of the primary sampling units (PSUs) was prepared using the results of the 1990 Population Census. The urban frame included provinces and district centres and settlements with populations of more than 10,000; the rural frame included subdistricts and villages with populations of less than 10,000. Adjustments were made to consider the growth in some areas right up to survey time. In addition to the rural-urban and regional stratifications, settlements were classified in seven groups according to population size.

The second stage of selection involved the list of quarters (administrative divisions of varying size) for each urban settlement, provided by the State Institute of Statistics (SIS). Every selected quarter was subdivided according tothe number of divisions(approximately 100 households)assigned to it. In rural areas, a selected village was taken as a single quarter, and wherever necessary, it was divided into subdivisions of approximately 100 households. In cases where the number of households in a selected village was less than 100 households, the nearest village was selected to complete the 100 households during the listing activity, which is described below.

After the selection of the secondary sampling units (SSUs), a household listing was obtained for each by the TDHS listing teams. The listing activity was carried out in May and June. From the household lists, a systematic random sample of households was chosen for the TDHS. All ever-married women age 12-49 who were present in the household on the night before the interview were eligible for the survey.

Mode of data collection

Face-to-face

Research instrument

Two questionnaires were used in the main fieldwork for the TDHS: the Household Questionnaire and the Individual Questionnaire for ever-married women of reproductive age. The questionnaires were based on the model survey instruments developed in the DHS program and on the questionnaires that had been employed in previous Turkish population and health surveys. The questionnaires were adapted to obtain data needed for program planning in Turkey during consultations with population and health agencies. Both questionnaires were developed in English and translated into Turkish.

a) The Household Questionnaire was used to enumerate all usual members of and visitors to the selected households and to collect information relating to the socioeconomic position of the households. In the first part of the Household Questionnaire, basic information was collected on the age, sex, educational attainment, marital status and relationship to the head of household for each person listed as a household member

Analysis unit

Woman, Birth, Child, Man, Member

Universe

Women age 15-49, Births, Children age 0-3, Men age 15-54, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: Statistics Department, Ministry of Finance and Economic Planning and Macro International Inc.

SAMPLE UNIT: Woman SAMPLE SIZE: 7070

SAMPLE UNIT: Birth SAMPLE SIZE: 22752

SAMPLE UNIT: Child SAMPLE SIZE: 5756

SAMPLE UNIT: Man SAMPLE SIZE: 1996

SAMPLE UNIT: Member SAMPLE SIZE: 36026

Mode of data collection

Face-to-face [f2f]

Abstract

The 1995 Egypt Demographic and Health Survey (EDHS-95) is part of the worldwide Demographic and Health Surveys project. It is the third survey in a series of Demographic and Health surveys that have been carried out in Egypt. The EDHS-95 collected information on fertility and child mortality, family planning awareness, approval and use, as well as basic information on maternal and child health.

The 1995 Egypt Demographic and Health Survey (EDHS-95) is aimed at providing policymakers and planners with important information for use in evaluating existing programs and formulating new programs and policies related to reproductive behavior and health. The survey was specifically designed to meet the following objectives: (1) Collect data on fertility and desired family size; (2) Monitor changes in family planning practice over time and investigate the availability and accessibility of family planning services in Egypt; (3) Determine reasons for nonuse and intention to use family planning; and (4) Measure the achievement of health policy objectives, particularly those concerning the GOE maternal and child health program.

In addition, because information on the status of women is of increasing interest to policymakers, the EDHS-95 included a special questionnaire to collect extensive data on the lives of Egyptian women. The questionnaire was administered to eligible women in one-third of the households in the EDHS-95 sample.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49

Kind of data

Sample survey data

Sampling procedure

Sample Design

The primary objective of the sample design for the EDHS-95 is to provide estimates of key population and health indicators including fertility and child mortality rates for the country as a whole and for six major administrative regions (Urban Governorates, urban Lower Egypt, rural Lower Egypt, urban Upper Egypt, rural Upper Egypt, and the Frontier Governorates). In addition, in the Urban Governorates, Lower Egypt and Upper Egypt, the design allows for governorate-level estimates of most key variables, with the exception of fertility and mortality rates and women's status indicators. In the Frontier Governorates, the sample size for individual governorates is not sufficiently large to allow for separate governorate-level estimates. However, separate estimates are possible for the western Frontier Governorates (Matrouh and New Valley) and the eastern Frontier Governorates (North Sinai, South Sinai and Red Sea). Finally, Assuit and Souhag governorates were oversampled in the EDHS-95 in order to provide sufficient cases for a special follow-up study of the reasons for nonuse of family planning in those areas.

In order to meet the survey objectives, the number of households selected in the EDHS-95 sample from each governorate was disproportional to the size of the population in the governorate. As a result, the EDHS-95 sample is not self-weighting at the national level, and weights had to be applied to the data to obtain the national-level estimates presented in this report.

Sample Implementation

Selection of PSUs: The EDHS-95 sample was selected in three stages. At the first or primary stage, the units of selection were shiakhas/towns in urban areas, and villages in rural areas. Information from the 1986 Census was used in constructing the frame from which the primary sampling units (PSU) were selected. Prior to the selection of the PSUs, the frame was updated to take into account all of the administrative changes which had occurred since 1986. The updating process included both office work and field visits during a three-month period. After it was completed, urban and rural units were stratified by geographical location in a serpentine order from the northwest comer to the southeast within each governorate. Shiakhas or villages with less than 2,500 populations were grouped with contiguous shiakhas or villages (usually within the same kism or marquez) to obtain the minimum size required (5,000 population). During the primary stage selection, a total of 467 units (204 shiakhas/towns and 263 villages) were sampled.

Quick Count: The second stage of selection involved several steps. First, detailed maps of the PSUs chosen during the first stage were obtained and divided into parts of roughly equal size. In shiakhas/towns or villages with 20,000 or more population, two parts were selected. In the remaining smaller shiakhas/towns or villages, only one part was selected. Overall, a total of 656 parts were selected from the shiakhas/towns and villages in the EDHS-95 sample.

A quick count was then carded out to divide each part into standard segments of about 200 households. This operation was conducted in order to provide an estimate of the number of households in each part so that the part could be divided into segments of roughly equal size. A group of 36 experienced field workers participated in the quick count operation. They were divided into 12 teams, each consisting of one supervisor, one cartographer and one or two counters. A one-week training course conducted prior to the quick count included both classroom sessions and field practice in a shiakha/town and a village not covered in the survey. The quick-count operation took place between late April and late July 1995.

As a quality control measure, the quick count was repeated in 10 percent of the parts. If the difference between the results of the first and second quick count were within 2 percent, then the first count was accepted. There were no major discrepancies between the two counts in most of the areas for which the count was repeated; however, in a few cases in Kafr El-Sheikh govemorate, a third visit was made to the field in order to resolve discrepancies between the counts.

Household Listing: Following the quick count, a total of 934 segments was chosen from the parts in each shiakha/town and village in the EDHS-95 sample (i.e., two segments were selected from each of the 467 PSUs). A household listing operation was then implemented in each of the selected segments. To conduct this operation, 16 supervisors and 32 listers were organized into 16 teams. Generally, each listing team consisted of a supervisor and two listers. A training course for the listing staff was held at the end of August for one week. The training involved classroom lectures and two days of field practice in two urban and rural locations. The listing operation began at the end of August and continued for about 40 days.

Around 10 percent of the segments were relisted. Two different criteria were used to select segments for relisting. First, segments were relisted when the number of households in the listing differed markedly from that expected according to the quick count information. Second, a number of segments were randomly selected to be relisted as an additional quality control test. Overall, few major discrepancies were found in comparisons of the two listings. However, a third visit to the field was necessary in a few segments in Gharbia governorate because of significant discrepancies between the results of the original listing and the relisting operation.

Selection of the Household Sample: Using the household lists for each segment, a systematic random sample of households was chosen to be interviewed in the EDHS-95. A subsample of one-third of these households was also selected for the woman's status survey, except in Assuit and Souhag governorates, where all households were included in the women's status survey. All ever-married women 15-49, who were usual residents or present in the household on the night before the interview, were eligible for the survey.

Note: See detailed description of sample design in APPENDIX B of the report which is presented in this documentation.

Mode of data collection

Face-to-face

Research instrument

The EDHS-95 involved three types of questionnaires: a household questionnaire, an individual questionnaire, and a women's status questionnaire. The household and individual questionnaires were based on the model survey instruments developed by the Demographic and Health Surveys program for high contraceptive prevalence countries. Additional questions on a number of topics not covered in the DHS mode/questionnaires were included in EDHS-95 questionnaires. In some cases, those items were drawn from the questionnaires used for the 1988 EDHS and the 1992 EDHS. In other cases, the questions were intended to collect information on topics not covered in the earlier surveys (e.g., schooling of children and female circumcision). The women's status questionnaire was based on a special set of modules developed in the DHS program to explore a number of dimensions of the status of women. The modules were modified to obtain data of interest in understanding the position of women in Egyptian society.

The household questionnaire consisted of two parts: a household schedule and a series of questions relating to the health and socioeconomic status of the household. The household schedule was used to list all usual household members and visitors and to identify those present in the household during the night before the interviewer's visit. For each of the individuals included in the schedule, information was collected on the relationship to the household head, age, sex, marital status (for those fifteen years and older), educational level and work status (for those six years and older). The second part of the household questionnaire included questions on characteristics of the physical and social environment of the household (e.g., type of dwelling, availability of electricity, source of drinking water, household possessions,

While the standard image of the nuclear family with two parents and 2.5 children has persisted in the American imagination, the number of births in the U.S. has steadily been decreasing since 1990, with about 3.6 million babies born in 2023. In 1990, this figure was 4.16 million. Birth and replacement rates A country’s birth rate is defined as the number of live births per 1,000 inhabitants, and it is this particularly important number that has been decreasing over the past few decades. The declining birth rate is not solely an American problem, with EU member states showing comparable rates to the U.S. Additionally, each country has what is called a “replacement rate.” The replacement rate is the rate of fertility needed to keep a population stable when compared with the death rate. In the U.S., the fertility rate needed to keep the population stable is around 2.1 children per woman, but this figure was at 1.67 in 2022. Falling birth rates Currently, there is much discussion as to what exactly is causing the birth rate to decrease in the United States. There seem to be several factors in play, including longer life expectancies, financial concerns (such as the economic crisis of 2008), and an increased focus on careers, all of which are causing people to wait longer to start a family. How international governments will handle falling populations remains to be seen, but what is clear is that the declining birth rate is a multifaceted problem without an easy solution.