About this dataset

Context

The dataset tabulates the United States population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for United States. The dataset can be utilized to understand the population distribution of United States by age. For example, using this dataset, we can identify the largest age group in United States.

Key observations

The largest age group in United States was for the group of age 25-29 years with a population of 22,854,328 (6.93%), according to the 2021 American Community Survey. At the same time, the smallest age group in United States was the 80-84 years with a population of 5,932,196 (1.80%). 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 groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the United States is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of United States total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 United States Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Blue Earth, MN population pyramid, which represents the Blue Earth population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Blue Earth, MN, is 28.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Blue Earth, MN, is 41.5.
• Total dependency ratio for Blue Earth, MN is 69.6.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Blue Earth, MN is 2.4.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Blue Earth population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Blue Earth for the selected age group is shown in the following column.
• Population (Female): The female population in the Blue Earth for the selected age group is shown in the following column.
• Total Population: The total population of the Blue Earth for the selected age group 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 Blue Earth Population by Age. You can refer the same here

The project ´Quality of Life and Well-being of Very Old People in NRW (NRW80+)´, which is funded by the Ministry of Innovation, Science and Research of North Rhine-Westphalia and carried out by the CERES research association at the University of Cologne, is intended to provide representative statements on the living conditions of very old people in North Rhine-Westphalia. The aim is to obtain comprehensive information about the environment in which very old people live or would like to live, what their social role is and how satisfied they are with their living situation. Housing situation: type of housing; full inpatient care in the case of residential accommodation; number of rooms; duration of living in this apartment/house/home; tenure (owner, main tenant, subtenant, rent-free); always in this apartment/house or lived in this flat/house; barrier-reduced living: thresholds over 2 cm; doors at least 80 cm wide; stairs with handrail or stair lift; doors of bath and WC open to the outside; suitability of the living environment on foot or in a wheelchair (walkability); residential attachment; trust in people in the neighbourhood (social cohesion). 2. Family situation: marital status; currently stable partnership; children present; number of children; number of living children; number of grandchildren and great grandchildren; household size; household composition: sex of up to three persons and their relationship to the respondent; pets. 3. Financial situation: sources of income; net household income; costs: amount of the monthly rent for warmth; amount of the monthly rent for cold or rent without additional costs; amount of the monthly additional costs; housing loans or mortgages to be paid off and their amount; monthly costs for the stay in the home; debts from loans; amount of debts; assets: amount of the total assets. 4. Dealing with old age: autonomy; experience of ageing (e.g. greater appreciation of relationships and other people, more attention to one´s own health, decrease in mental capacity, etc.); appreciation by others (being needed, being appreciated for services, being treated as a burden, being appreciated more than before). 5. Health: cognitive tests on mental health (repeat ten selected words in two passes, convert numbers, mention as many things as possible that you can buy in the supermarket in one minute, repeat numbers in reverse order, remember the ten words at the beginning of the cognitive test); self-assessment of health; assessment of pain level in the last four weeks; height in cm; weight in kg; weight loss in the last twelve months; multimorbidity: medical treatment due to selected diseases; existence of care level or degree of care; designation of care level or degree of care; additional care level 0 (limited everyday competence); care use: use of an outpatient care service; use of day care; private care; hours of private care per week; respondent cares privately for another person and hours per week; functional health with regard to various activities of daily life (eating, dressing and undressing, personal hygiene, walking, looking up from bed and lying down, being bedridden, bathing or showering, reaching the toilet in time, frequency of problems with bladder and bowel control, using the telephone, organising routes outside the walking range (trips by taxi or bus), buying food and clothing yourself, preparing your own meals, doing housework, taking medication, regulating financial matters); use of assistive devices (hearing aid, wheelchair, home emergency call system, private car); health literacy (knowledge and compliance). 6. Everyday life and lifestyle: importance and frequency of: time spent together with other people, physical activity, rest and time for oneself, in-depth study of a topic and creative activity; preferred music style; preferences regarding clothing and food; leisure activities in the last 12 months (e.g. sports, participation in a coffee circle or regulars´ table, visiting a café, restaurant or pub, travelling, voluntary work, etc.); frequency and place of the respective activities; religious community, club membership; political participation: party affiliation; participation in the last federal election. 7. Technology setting and technology use: technology use in the last 12 months (computer or laptop, internet, smartphone, regular mobile phone, tablet computer, fitness wristband) and frequency of use; technology setting: interest, difficulties in using modern digital devices, ease of everyday life with modern digital devices); purpose of internet use in the last three months (emails, looking for information on health topics, participating in social networks, buying or selling goods or services). 8. Social inclusion: called social network; for the four most important persons the following was asked: sex, their relationship to the respondent, frequency of contact and attachment to these persons; number of other persons in the social network (size of the social network); frequency of loneliness in the last week; social support: larger gifts given or larger gifts received; frequency of social support given or received by the respondent (e.g. helped other people with their tasks, received help with tasks and tasks, received consolation, received consolation); Generativity (importance of passing on one´s own experiences to younger people, passing on social values to younger people, being a role model for younger people); Integration into society: Anomie (coping with today´s social way of life, one´s own values fit less and less with the values of today´s society, lack of orientation due to rapidly changing society). 9. Hand grip force: agreement with hand grip test; right- or left-handed; writing hand; test value 1st measurement right and left; test value 2nd measurement right and left; deviations exist. 10. Value system: Individual value system (doing things in one´s own way (self-determination), being wealthy (power), avoiding dangers and safe environment (security), spending good time (hedonism), doing good for society (benevolence), getting achievements recognized (achievement), taking risks (stimulation), avoiding teasing others (conformity), caring for nature and the environment (universalism), respecting traditions (tradition); spirituality: Importance of a connection with God or a higher power, with people and with nature; frequency of connection with God or a higher power, with people and with nature; importance of institutionalizing one´s own beliefs, e.g. in church; ; frequency of the feeling of community in institutionalized forms; orientation to the guidelines of religious institutions; importance of being part of a large entity; frequency of the feeling of being part of a larger entity; importance of practicing religious practices such as Praying or meditating, frequency of religious practices; reconciled relationship with God; God as support; desire to leave everything behind to go to God; God is threatening and punishing; importance of faith or spirituality in one´s own life; attitude towards dying and death: acceptance of one´s own mortality; death as an incriminating thought; fear of dying; frequency of thoughts about death; will written; dispositions (living will, precautionary power of attorney, care-giving will, general power of attorney). 11. Interpersonal personality: tendency to quarrel, losing control, feeling irritated and harassed); external and internal controlling life (life in one´s own hands, success through effort, life is determined by others, plans thwarted by fate). 12. Well-being and life satisfaction: frequency of selected feelings in the last year (PANAS: enthusiastic, attentive, joyfully excited/expectant, stimulated, determined); depressiveness during the last 14 days (depressed, difficult to pick up, enjoy life, even if some things are difficult, brooding a lot); Valuation of Life-Scale (and a. optimistic, consider current life as useful, life determined by religious or moral principles, etc.); Meaning in Life-Scale (satisfaction with what has been achieved in the past, with the past at peace); general life satisfaction. 13. Critical life events: perceived burden of life events in general; generally most stressful event; current burden of events related to World War II; most stressful event related to World War II; current burden of events outside World War II; most stressful event outside World War II; most stressful event outside World War II; most stressful event outside World War II Interpersonal conflicts and emotional consequences (INDICATE): Frequency of conflicts with known persons (other person has become louder/ abusive towards the respondent (intimidation), has spoken about weaknesses or impairments of the respondent (shame), blamed for an event, paternalism: Ignoring the respondent´s opinion, has caused the respondent to renounce his or her wish or right, neglect: no support given, no time given, financial exploitation: property or possessions of the respondent used for own purposes, has been kept by the respondent, physical violence: firm or rough handling, physically rough or inconsiderate handling, custodial measures restriction of freedom of movement, medication given without consent, sexualised violence: offensive behaviour, sexual harassment). 14. Biography: caregiver in childhood up to the age of 16; social status of parents: employment and occupational status of father and mother when the interviewee was 15 years old; number of siblings; occupational biography of the interviewee: end of full-time employment; occupational status; special designation of occupational status; occupational biography of spouse: end of full-time employment; occupational status; special designation of occupational status; request to politicians to improve one´s own quality of life (open). Demography: sex; age; origin: country, place of residence 1949-1990; education: country of last school attendance; highest

The global forest age dataset (GFAD) describes the age distributions of plant functional types (PFT) on a 0.5-degree grid. Each grid cell contains information on the fraction of each PFT within an age class. The four PFTs, needleaf evergreen (NEEV), needleleaf deciduous (NEDE), broadleaf evergreen (BREV) and broadleaf deciduous (BRDC) are mapped from the MODIS Collection 5.1 land cover dataset, crosswalking land cover types to PFT fractions. The source of data for the age distributions is from country-level forest inventory for temperate and high-latitude countries, and from biomass for tropical countries. The inventory and biomass data are related to fifteen age classes defined in ten-year intervals, from 1-10 up to a class greater than 150 years old. The GFAD dataset represents the 2000-2010 era.

Abstract

The Indonesia Demographic and Health Survey (IDHS) is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health. The 2002-2003 IDHS follows a sequence of several previous surveys: the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS), the 1991 IDHS, the 1994 IDHS, and the 1997 IDHS. The 2002-2003 IDHS is expanded from the 1997 IDHS by including a collection of information on the participation of currently married men and their wives and children in the health care.

The main objective of the 2002-2003 IDHS is to provide policymakers and program managers in population and health with detailed information on population, family planning, and health. In particular, the 2002-2003 IDHS collected information on the female respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding AIDS and other sexually transmitted infections in Indonesia.

The 2002-2003 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs - Measure trends in fertility and contraceptive prevalence rates, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health - Assess men’s participation and utilization of health services, as well as of their families - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN AND IMPLEMENTATION

Administratively, Indonesia is divided into 30 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts and each subdistrict is divided into villages. The entire village is classified as urban or rural.

The primary objective of the 2002-2003 IDHS is to provide estimates with acceptable precision for the following domains: · Indonesia as a whole; · Each of 26 provinces covered in the survey. The four provinces excluded due to political instability are Nanggroe Aceh Darussalam, Maluku, North Maluku and Papua. These provinces cover 4 percent of the total population. · Urban and rural areas of Indonesia; · Each of the five districts in Central Java and the five districts in East Java covered in the Safe Motherhood Project (SMP), to provide information for the monitoring and evaluation of the project. These districts are: - in Central Java: Cilacap, Rembang, Jepara, Pemalang, and Brebes. - in East Java: Trenggalek, Jombang, Ngawi, Sampang and Pamekasan.

The census blocks (CBs) are the primary sampling unit for the 2002-2003 IDHS. CBs were formed during the preparation of the 2000 Population Census. Each CB includes approximately 80 households. In the master sample frame, the CBs are grouped by province, by regency/municipality within a province, and by subdistricts within a regency/municipality. In rural areas, the CBs in each district are listed by their geographical location. In urban areas, the CBs are distinguished by the urban classification (large, medium and small cities) in each subdistrict.

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

Mode of data collection

Face-to-face

Research instrument

The 2002-2003 IDHS used three questionnaires: the Household Questionnaire, the Women’s Questionnaire for ever-married women 15-49 years old, and the Men’s Questionnaire for currently married men 15-54 years old. The Household Questionnaire and the Women’s Questionnaire were based on the DHS Model “A” Questionnaire, which is designed for use in countries with high contraceptive prevalence. In consultation with the NFPCB and MOH, BPS modified these questionnaires to reflect relevant issues in family planning and health in Indonesia. Inputs were also solicited from potential data users to optimize the IDHS in meeting the country’s needs for population and health data. The questionnaires were translated from English into the national language, Bahasa Indonesia.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic information collected for each person listed includes the following: age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, the Household Questionnaire also identifies unmarried women and men age 15-24 who are eligible for the individual interview in the Indonesia Young Adult Reproductive Health Survey (IYARHS). Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor and outer walls of the house, and ownership of various durable goods were also recorded in the Household Questionnaire. These items reflect the household’s socioeconomic status.

The Women’s Questionnaire was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics: • Background characteristics, such as age, marital status, education, and media exposure • Knowledge and use of family planning methods • Fertility preferences • Antenatal, delivery, and postnatal care • Breastfeeding and infant feeding practices • Vaccinations and childhood illnesses • Marriage and sexual activity • Woman’s work and husband’s background characteristics • Childhood mortality • Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) • Sibling mortality, including maternal mortality.

The Men’s Questionnaire was administered to all currently married men age 15-54 in every third household in the IDHS sample. The Men’s Questionnaire collected much of the same information included in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, and maternal mortality. Instead, men were asked about their knowledge and participation in the health-seeking practices for their children.

Cleaning operations

All completed questionnaires for IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This process consisted of office editing, coding of open-ended questions, data entry, verification, and editing computer-identified errors. A team of about 40 data entry clerks, data editors, and two data entry supervisors processed the data. Data entry and editing started on November 4, 2002 using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. To prepare the data entry programs, two BPS staff spent three weeks in ORC Macro offices in Calverton, Maryland in April 2002.

Response rate

A total of 34,738 households were selected for the survey, of which 33,419 were found. Of the encountered households, 33,088 (99 percent) were successfully interviewed. In these households, 29,996 ever-married women 15-49 were identified, and complete interviews were obtained from 29,483 of them (98 percent). From the households selected for interviews with men, 8,740 currently married men 15-54 were identified, and complete interviews were obtained from 8,310 men, or 95 percent of all eligible men. The generally high response rates for both household and individual interviews (for eligible women and men) were due mainly to the strict enforcement of the rule to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household, eligible women, and eligible men.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling 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 2002-2003 Indonesia Demographic and Health Survey (IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents

About this dataset

Context

The dataset tabulates the data for the White Earth, ND population pyramid, which represents the White Earth population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for White Earth, ND, is 63.6.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for White Earth, ND, is 29.5.
• Total dependency ratio for White Earth, ND is 93.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for White Earth, ND is 3.4.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the White Earth population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the White Earth for the selected age group is shown in the following column.
• Population (Female): The female population in the White Earth for the selected age group is shown in the following column.
• Total Population: The total population of the White Earth for the selected age group 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 White Earth Population by Age. You can refer the same here

The zip files contain the following files:

MOZ_population_v1_1_gridded.tifThis GeoTIFF raster (.tif), at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimated population counts per grid cell across Mozambique. The projection is the geographic coordinate system WGS84 (World Geodetic System 1984). ‘NoData’ values represent areas that were mapped as unsettled based on building footprints from “Digitize Africa data © 2020 Maxar Technologies, Ecopia.AI”. These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated populations for larger areas.MOZ_population_v1_1_agesex.zipThis zip file contains 40 rasters in GeoTIFF format. Each raster provides gridded population estimates for an age-sex group. We provide 36 rasters for the commonly reported age-sex groupings of sequential age classes for males and females separately. The files are labelled with either an “m” (male) or an “f” (female) followed by the number of the first year of the age class represented by the data. “f0” and “m0” are population counts of under 1 year olds for females and males, respectively. “f1” and “m1” are population counts of 1 to 4 year olds for females and males, respectively. Over 4 years old, the age groups are in five year bins labelled with a “5”, “10”, etc. Eighty year olds and over are represented in the groups “f80” and “m80”.We provide an additional four rasters that represent aggregated demographic groups of special interest for development programmes and interventions. These are “under1” (all females and males under the age of 1), “under5” (all females and males under the age of 5), “under15” (all females and males under the age of 15) and “f15_49” (all females between the ages of 15 and 49, inclusive). These data were produced using the peanutButter R package (Leasure et al. 2020b) which multiplied the gridded population estimates (MOZ_population_v1_1_gridded.tif) by gridded age-sex proportions that differ by region (WorldPop et al. 2018, Pezzulo et al. 2017).While each data file represents population counts, individual values contain decimals, i.e. fractions of people. This is because we do not estimate which grid cell each individual in a given age group occupies. For example, if four grid cells next to each other have values of 0.25 this indicates that there is one person of that age group somewhere in those four grid cellsThis work provides an estimate of the geographic distribution of the population of Mozambique in 2017. The outputs are intended as an interim population product to support ongoing development and operations work until such time as the official 2017 Population and Housing Census results are available in a spatial gridded format. At that time, this interim gridded population layer will be superseded and users will be advised to use the official gridded population release from INE.Data Citation: Bondarenko M, Jones P, Leasure D, Lazar AN, Tatem AJ. 2020. Census disaggregated gridded population estimates for Mozambique (2017), version 1.1. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00672 CREDITS: Patricia Jones and Donna Clarke (WorldPop) supported the generation of inputs for the application of the random forest-based dasymetric mapping approach developed by Stevens et al. (2015). The population disaggregation was done by Maksym Bondarenko (WorldPop), using the random forest population modelling R scripts (Bondarenko et al., 2020). The age-sex rasters, SQL database, and map tileswere created by Doug Leasure (WorldPop). The administrative boundaries and population totals were provided by Arlindo Charles, at INE (National Institute of Statistics) in Mozambique. Claire Dooley and Chris Jochem reviewed the population raster and its documentation, and provided comments and suggestions. Attila N. Lazar (WorldPop) coordinated the work with substantial engagement and translation support from Sandra Baptista (CIESIN). The whole WorldPop group and GRID3 partners are acknowledged for overall project support.These data were produced by the WorldPop Research Group at the University of Southampton. This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) programme funded by the Bill & Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign, Commonwealth & Development Office. It is implemented by Columbia University’s Center for International Earth Science Information Network (CIESIN), the United Nations Population Fund (UNFPA), WorldPop at the University of Southampton, and the Flowminder Foundation. The downloadable Metadata provides more information about Source Data, Methods Overview, Assumptions & Limitations and Works and Data CitedContact release@worldpop.org for more information or go here.

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

As of April 2024, it was found that men between the ages of 25 and 34 years made up Facebook largest audience, accounting for 18.4 percent of global users. Additionally, Facebook's second largest audience base could be found with men aged 18 to 24 years.

              Facebook connects the world

              Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger,
              as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

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.

As of April 2024, Facebook had an addressable ad audience reach 131.1 percent in Libya, followed by the United Arab Emirates with 120.5 percent and Mongolia with 116 percent. Additionally, the Philippines and Qatar had addressable ad audiences of 114.5 percent and 111.7 percent.

How much time do people spend on social media?

              As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in
              the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively.
              People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general.
              During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

              Instagram’s Global Audience

              As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
              As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.

              Who is winning over the generations?

              Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.

We determined first- and second-line regimens, including hematopoietic stem cell transplantations, in all diffuse large B cell lymphoma (DLBCL) patients aged ≥20 yr (n = 1,888), registered at the Belgian Cancer Registry (2013–2015). Treatments were inferred from reimbursed drugs, and procedures registered in national health insurance databases. This real-world population-based study allows to assess patients usually excluded from clinical trials such as those with comorbidities, other malignancies (12%), and advanced age (28% are ≥80 yr old). Our data show that the majority of older patients are still started on first-line regimens with curative intent and a substantial proportion of them benefit from this approach. First-line treatments included full R-CHOP (44%), “incomplete” (R-)CHOP (18%), other anthracycline (14%), non-anthracycline (9%), only radiotherapy (3%), and no chemo-/radiotherapy (13%), with significant variation between age groups. The 5-year overall survival (OS) of all patients was 56% with a clear influence of age (78% [20–59 yr] versus 16% [≥85 yr]) and of the type of first-line treatments: full R-CHOP (72%), other anthracycline (58%), “incomplete” (R-)CHOP (47%), non-anthracycline (30%), only radiotherapy (30%), and no chemo-/radiotherapy (9%). Second-line therapy, presumed for refractory (7%) or relapsed disease (9%), was initiated in 252 patients (16%) and was predominantly (71%) platinum-based. The 5-year OS after second-line treatment without autologous stem cell transplantation (ASCT) was generally poor (11% in ≥70 yr versus 17% in 1 within 3 months from incidence), subsequent malignancies (HR 2.50), prior malignancies (HR 1.34), respiratory and diabetic comorbidity (HR 1.41 and 1.24), gender (HR 1.25 for males), and first-line treatment with full R-CHOP (HR 0.41) or other anthracycline-containing regimens (HR 0.72). Despite inherent limitations, patterns of care in DLBCL could be determined using an innovative approach based on Belgian health insurance data.

As of April 2024, Bahrain was the country with the highest Instagram audience reach with 95.6 percent. Kazakhstan also had a high Instagram audience penetration rate, with 90.8 percent of the population using the social network. In the United Arab Emirates, Turkey, and Brunei, the photo-sharing platform was used by more than 85 percent of each country's population.

As of January 2024, #love was the most used hashtag on Instagram, being included in over two billion posts on the social media platform. #Instagood and #instagram were used over one billion times as of early 2024.

About this dataset

Context

The dataset tabulates the data for the Black Earth, WI population pyramid, which represents the Black Earth population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Black Earth, WI, is 44.6.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Black Earth, WI, is 70.3.
• Total dependency ratio for Black Earth, WI is 115.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Black Earth, WI is 1.4.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Black Earth population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Black Earth for the selected age group is shown in the following column.
• Population (Female): The female population in the Black Earth for the selected age group is shown in the following column.
• Total Population: The total population of the Black Earth for the selected age group 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 Black Earth Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Black Earth Town, Wisconsin population pyramid, which represents the Black Earth town population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Black Earth Town, Wisconsin, is 13.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Black Earth Town, Wisconsin, is 32.0.
• Total dependency ratio for Black Earth Town, Wisconsin is 45.8.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Black Earth Town, Wisconsin is 3.1.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Black Earth town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Black Earth town for the selected age group is shown in the following column.
• Population (Female): The female population in the Black Earth town for the selected age group is shown in the following column.
• Total Population: The total population of the Black Earth town for the selected age group 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 Black Earth town Population by Age. You can refer the same here