Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No

UNIT DESCRIPTIONS: - Dwellings: Living quarters have been defined for census purposes as places of abode, which are structurally separate and independent. The terms separate and independent mean the following: Separate: A structure is considered separate if it is surrounded by walls, fence, etc., and is covered by roof. Independent: A structure is said to be independent if it has direct access via a public staircase, communal passageway or landing (that is, occupants can come in or go out of their living quarters without passing through someone else?s premises). In general, living quarters can be classified into two categories, that is: (i) Built or converted for living (e.g. house, flat, apartment, shophouse, makeshift hut, hotel, hostels, etc.) (ii) Not meant for living but used for this purpose on Census Day (e.g. in a building such as office, shop, barn, community hall, etc.) Living quarters built or converted for living can be further classified into housing units and collective living quarters. Housing units are classified into six main types, namely: House; Flat/apartment/condominium; Shop house, office; Room (with direct access to the outside); improvised/temporary hut; and others. House can be further classified into Detached house; and Semi-detached house. - Households: Household is a group of persons who: - Usually live together - Make common provisions for food and other essentials of living - Group quarters: --

Universe

All persons including foreigners who had stayed or intended to stay in Malaysia for six months or more in the Census year were covered. Apart from Malaysians, the following categories were also included provided they had stayed or intended to stay for 6 months or more in Malaysia: (a) Persons commuting across the Malaysian border (e.g. Singapore and Thailand) for work or studies but maintaining usual residence within Malaysia; (b) Malaysians who were away overseas as tourists, on short-term study or attending conferences/seminars or on business; (c) Expatriates and other foreign workers (including housemaids) as well as their family members; (d) Foreign long-term visitors and students; (e) Foreign military, naval and diplomatic personnel and their families staying in the country except for those who had diplomatic immunity and wished to be excluded; and (f) Persons without permanent homes and were found along footways, etc; The following categories were excluded from the Census count on the basis that they were staying in the country for less than six months in the Census year:- (a) Malaysian citizens and permanent residents who were away or intended to be away from the country for six months or more in the Census year because of work, studies etc.; (b) Malaysian military, naval and diplomatic personnel and their families who were staying outside Malaysia; and (c) Foreigners such as tourists, businessman and the like who stayed or intended to be in Malayisa for less than six months.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Department of Statistics Malaysia

SAMPLE DESIGN: With 2 per cent as the sampling fraction, or a sample interval of 50, the sample was selected using the living quarters serial number starting from 1, 51, 101, 151, 201 ??. N.

SAMPLE UNIT: household

SAMPLE FRACTION: 2%

SAMPLE SIZE (person records): 435,300

Mode of data collection

Face-to-face [f2f]

Research instrument

In the 2000 Population and Housing Census, three main schedules were used namely, Documents 1, 2 and 3/3a. Document 1, which is the Listing Book, was used to list all living quarters and obtain some related information. Document 2, which represented the main questionnaire, was divided into three sections. It collected information on living quarters, households and persons. Document 3/3a, which was an abbreviated version of Document 2, was used for institutions.

Response rate

UNDERCOUNT: 100%

This layer shows race and ethnicity data from the 2020 Census Demographic and Housing Characteristics. This is shown by Nation, Consolidated City, Census Designated Place, Incorporated Place boundaries. Each geography layer contains a common set of Census counts based on available attributes from the U.S. Census Bureau. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.   To see the full list of attributes available in this service, go to the "Data" tab above, and then choose "Fields" at the top right. Each attribute contains definitions, additional details, and the formula for calculated fields in the field description.Vintage of boundaries and attributes: 2020 Demographic and Housing Characteristics Table(s): P1, H1, H3, P5, P9 Data downloaded from: U.S. Census Bureau’s data.census.gov siteDate the Data was Downloaded: May 25, 2023Geography Levels included: Nation, Consolidated City, Census Designated Place, Incorporated PlaceNational Figures: included in Nation layer The United States Census Bureau Demographic and Housing Characteristics: 2020 Census Results 2020 Census Data Quality Geography & 2020 Census Technical Documentation Data Table Guide: includes the final list of tables, lowest level of geography by table and table shells for the Demographic Profile and Demographic and Housing Characteristics.News & Updates This layer is ready to be used in ArcGIS Pro, ArcGIS Online and its configurable apps, Story Maps, dashboards, Notebooks, Python, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the U.S. Census Bureau when using this data. Data Processing Notes: These 2020 Census boundaries come from the US Census TIGER geodatabases. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For Census tracts and block groups, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract and block group boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2020 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are unchanged and available as attributes within the data table (units are square meters).  The layer contains all US states, Washington D.C., and Puerto Rico. Census tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99). Block groups that fall within the same criteria (Block Group denoted as 0 with no area land) have also been removed.Percentages and derived counts, are calculated values (that can be identified by the "_calc_" stub in the field name). Field alias names were created based on the Table Shells file available from the Data Table Guide for the Demographic Profile and Demographic and Housing Characteristics. Not all lines of all tables listed above are included in this layer. Duplicative counts were dropped. For example, P0030001 was dropped, as it is duplicative of P0010001.To protect the privacy and confidentiality of respondents, their data has been protected using differential privacy techniques by the U.S. Census Bureau.

This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

The average American household consisted of 2.51 people in 2023.

Households in the U.S.

As shown in the statistic, the number of people per household has decreased over the past decades.

The U.S. Census Bureau defines a household as follows: “a household includes all the persons who occupy a housing unit as their usual place of residence. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from outside the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated persons who share living arrangements. (People not living in households are classified as living in group quarters.).”

The population of the United States has been growing steadily for decades. Since 1960, the number of households more than doubled from 53 million to over 131 million households in 2023.

Most of these households, about 34 percent, are two-person households. The distribution of U.S. households has changed over the years though. The percentage of single-person households has been on the rise since 1970 and made up the second largest proportion of households in the U.S. in 2022, at 28.88 percent.

In concordance with the rise of single-person households, the percentage of family households with own children living in the household has declined since 1970 from 56 percent to 40.26 percent in 2022.

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely-designed Household Survey includes modules that measure the cognitive skills (reading, writing and numeracy), socio-emotional skills (personality, behavior and preferences) and job-specific skills (subset of transversal skills with direct job relevance) of a representative sample of adults aged 15 to 64 living in urban areas, whether they work or not. The cognitive skills module also incorporates a direct assessment of reading literacy based on the Survey of Adults Skills instruments. Modules also gather information about family, health and language.

Geographic coverage

13 major metropolitan areas: Bogota, Medellin, Cali, Baranquilla, Bucaramanga, Cucuta, Cartagena, Pasto, Ibague, Pereira, Manizales, Monteira, and Villavicencio.

Analysis unit

The units of analysis are the individual respondents and households. A household roster is undertaken at the start of the survey and the individual respondent is randomly selected among all household members aged 15 to 64 included. The random selection process was designed by the STEP team and compliance with the procedure is carefully monitored during fieldwork.

Universe

The target population for the Colombia STEP survey is all non-institutionalized persons 15 to 64 years old (inclusive) living in private dwellings in urban areas of the country at the time of data collection. This includes all residents except foreign diplomats and non-nationals working for international organizations.

The following groups are excluded from the sample: - residents of institutions (prisons, hospitals, etc.) - residents of senior homes and hospices - residents of other group dwellings such as college dormitories, halfway homes, workers' quarters, etc. - persons living outside the country at the time of data collection.

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified 7-stage sample design was used in Colombia. The stratification variable is city-size category.

First Stage Sample The primary sample unit (PSU) is a metropolitan area. A sample of 9 metropolitan areas was selected from the 13 metropolitan areas on the sample frame. The metropolitan areas were grouped according to city-size; the five largest metropolitan areas are included in Stratum 1 and the remaining 8 metropolitan areas are included in Stratum 2. The five metropolitan areas in Stratum 1 were selected with certainty; in Stratum 2, four metropolitan areas were selected with probability proportional to size (PPS), where the measure of size was the number of persons aged 15 to 64 in a metropolitan area.

Second Stage Sample The second stage sample unit is a Section. At the second stage of sample selection, a PPS sample of 267 Sections was selected from the sampled metropolitan areas; the measure of size was the number of persons aged 15 to 64 in a Section. The sample of 267 Sections consisted of 243 initial Sections and 24 reserve Sections to be used in the event of complete non-response at the Section level.

Third Stage Sample The third stage sample unit is a Block. Within each selected Section, a PPS sample of 4 blocks was selected; the measure of size was the number of persons aged 15 to 64 in a Block. Two sample Blocks were initially activated while the remaining two sample Blocks were reserved for use in cases where there was a refusal to cooperate at the Block level or cases where the block did not belong to the target population (e.g., parks, and commercial and industrial areas).

Fourth Stage Sample The fourth stage sample unit is a Block Segment. Regarding the Block segmentation strategy, the Colombia document 'FINAL SAMPLING PLAN (ARD-397)' states "According to the 2005 population and housing census conducted by DANE, the average number of dwellings per block in the 13 large cities or metropolitan areas was approximately 42 dwellings. Based on this finding, the defined protocol was to report those cases in which 80 or more dwellings were present in a given block in order to partition block using a random selection algorithm." At the fourth stage of sample selection, 1 Block Segment was selected in each selected Block using a simple random sample (SRS) method.

Fifth Stage Sample The fifth stage sample unit is a dwelling. At the fifth stage of sample selection, 5582 dwellings were selected from the sampled Blocks/Block Segments using a simple random sample (SRS) method. According to the Colombia document 'FINAL SAMPLING PLAN (ARD-397)', the selection of dwellings within a participant Block "was performed differentially amongst the different socioeconomic strata that the Colombian government uses for the generation of cross-subsidies for public utilities (in this case, the socioeconomic stratum used for the electricity bill was used). Given that it is known from previous survey implementations that refusal rates are highest amongst households of higher socioeconomic status, the number of dwellings to be selected increased with the socioeconomic stratum (1 being the poorest and 6 being the richest) that was most prevalent in a given block".

Sixth Stage Sample The sixth stage sample unit is a household. At the sixth stage of sample selection, one household was selected in each selected dwelling using an SRS method.

Seventh Stage Sample The seventh stage sample unit was an individual aged 15-64 (inclusive). The sampling objective was to select one individual with equal probability from each selected household.

Sampling methodologies are described for each country in two documents and are provided as external resources: (i) the National Survey Design Planning Report (NSDPR) (ii) the weighting documentation (available for all countries)

Mode of data collection

Face-to-face [f2f]

Research instrument

The STEP survey instruments include:

• The background questionnaire developed by the World Bank (WB) STEP team
• Reading Literacy Assessment developed by Educational Testing Services (ETS).

All countries adapted and translated both instruments following the STEP technical standards: two independent translators adapted and translated the STEP background questionnaire and Reading Literacy Assessment, while reconciliation was carried out by a third translator.

The survey instruments were piloted as part of the survey pre-test.

The background questionnaire covers such topics as respondents' demographic characteristics, dwelling characteristics, education and training, health, employment, job skill requirements, personality, behavior and preferences, language and family background.

The background questionnaire, the structure of the Reading Literacy Assessment and Reading Literacy Data Codebook are provided in the document "Colombia STEP Skills Measurement Survey Instruments", available in external resources.

Cleaning operations

STEP data management process:

1) Raw data is sent by the survey firm 2) The World Bank (WB) STEP team runs data checks on the background questionnaire data. Educational Testing Services (ETS) runs data checks on the Reading Literacy Assessment data. Comments and questions are sent back to the survey firm. 3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data. 4) The WB STEP team and ETS check if the data files are clean. This might require additional iterations with the survey firm. 5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies. 6) ETS scales the Reading Literacy Assessment data. 7) The WB STEP team merges the background questionnaire data with the Reading Literacy Assessment data and computes derived variables.

Detailed information on data processing in STEP surveys is provided in "STEP Guidelines for Data Processing", available in external resources. The template do-file used by the STEP team to check raw background questionnaire data is provided as an external resource, too.`

Response rate

An overall response rate of 48% was achieved in the Colombia STEP Survey.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No (dwellings in original sample are interpreted as households in IPUMS) - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Structurally independent living quarters, consisting of one or more rooms with a private entrance, serving up to three families. - Group quarters: Group living together under relations of administrative subordination; group of six or more persons not related by kinship; or a dwelling with more than 3 families.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Instituto Brasileiro de Geografia e Estatística

SAMPLE UNIT: Household (called "dwelling" in original sample)

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 4,953,759

Mode of data collection

Face-to-face [f2f]

Research instrument

Long and short enumeration forms. The short form contains general information about the characteristics of the dwelling and each of persons in the dwelling. The long form contains general and more specific information about the characteristics of the dwelling, families, and each of the people in the dwellings and was applied to a 25% sample of the population.

Response rate

COVERAGE: No official estimates, UNDERCOUNT: No official estimates

In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Living quarters

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Group quarters: Yes - Special populations: No

UNIT DESCRIPTIONS: - Group quarters: Living quarters which is built or converted for living (e.g. house, flat, apartment, shophouse, makeshift hut, hotel, hostels, etc.).

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Department of Statistics, Malaysia

SAMPLE FRACTION: 2%

SAMPLE SIZE (person records): 175,997

Mode of data collection

Face-to-face [f2f]

Research instrument

Five separate forms constitute the total questionnaire. There was a House Listing Book, a Living Quarters Form, an Agricultural Census Form, a Household Census Form and a Persons Form. For ease of reference those were designated as Forms 1, 2, 3, 4, and 5 respectively.

Abstract

PCBS allocates particular attention to the Youth Survey because of the different definition of youth age group in studies. Some define youth as the age group (10-24 years) whereas others define them as the age group (15-29 years). In both definitions, youth constitute the largest segment of the Palestinian society. In addition to being the bulk of the society, youth are a vital strength with non-ignorable potential. They are the tenets of the future and the wealth of the nation that overweighs any other sources. Youth are the agent of change in the society. At this state, planning begins to fulfill societal needs in future skills and competences.

Geographic coverage

Palestine

Analysis unit

individual/ Household

Universe

It consists all the individuals in the age group 15-29 years old and living with their households normally in the State of Palestine in 2015.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame consists of all enumeration areas which were enumerated in 2007, each numeration area consists of buildings and housing units with average of about 124 households in it. These enumeration areas are used as primary sampling units( PSUs) in the first stage of the sampling selection. The sample is three stage stratified cluster (pps) sample:

First stage: selection a stratified sample of 321 EA with (pps) method.

Second stage: selection a random area sample of 25 households from each enumeration area selected in the first stage, the selection starts from a random point in the enumeration area (building number), Where include cases of non-responding households, and the responsive households where the age group 15-29 years is not available, and the responsive households where the age group 15-29 years is available.

Third stage: we selected one person in the household of the( 15-29) age group in a random method by using Kish tables, so that the sex of the person chosen by the serial questionnaire number in the EA sample, if an odd number we select male person and if even number we select female person.

Sample strata: The population was divided by: 1- Governorate (17 governorates) 2- Type of Locality (urban, rural, refugee camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

he Survey comprised two questionnaires: Family questionnaire: The questionnaire included detailed questions on the demographic, social, educational, professional and matrimonial characteristics of family members in addition to data on housing and identification of youth eligible for the interviews.

Youth Survey (15-29 years), which including the following sections: · Education (educational experience in different stages, assessment of educational stages, characteristics of youth enrolled in education, level of satisfaction with the learning experience) · Work and pay (employment status, characteristics of employed people, characteristics of unemployed people, entrepreneurship, financial status and savings) · Emigration (trends of emigration to other countries, emigration of friends and relatives, emigration experience) · Matrimonial and health status (spouses relation, matters related to housing, gender roles, public health, nutrition, mental health, social communication, sports and exercising, HIV awareness, life satisfaction, sexual and reproductive health) · Social participation (volunteer activities, community outreach, friends, family support, social values, political participation and future aspirations, Internet and social media)

Cleaning operations

· During this phase, a data-entry program was prepared using Oracle. Amendments were introduced to the entry screens to set entry bases in a manner that guarantees proper entry of all questionnaires and queries for data cleansing after entry. The queries test variables at questionnaire level. · At this stage, questionnaires were received from fieldwork coordinator using the template prepared for this purpose. The officer in charge controls the questionnaires to ensure they are all received using the template prepared for this purpose. · Entry and cleansing of data took place in the period from 31 August 2015 to 29 November 2015.

Response rate

The response rate in the West Bank reached 94.9 % while in Gaza Strip it reached 97.2%. The response rate in Palestine reached 95.7 %

Sampling error estimates

Data of this survey affected by sampling errors due to use of the sample and not a complete enumeration. Therefore, certain differences are expected in comparison with the real values obtained through censuses. Variance were calculated for the most important indicators, the variance table is attached with the final report. There is no problem to disseminate results at the national level and governorate level.

Data appraisal

Non-sampling errors are probable in all stages of the project, during data collection or processing. This is referred to as non-response errors, response errors, interviewing errors, and data entry errors. To avoid errors and reduce their effects, great efforts were made to train the fieldworkers intensively. They were trained in how to carry out the interview, what to discuss and what to avoid, carrying out a pilot survey and practical and theoretical training during the training course. Also data entry staff was trained on the entry program that was examined before starting the data entry process. Continuous contacts with the fieldwork team were maintained through regular visits to the field and regular meetings during the different field visits. Problems faced by fieldworkers were discussed to clarify issues and provide relevant instructions.

The implementation of the survey encountered non-response where the case (Refused to cooperate) during the fieldwork visit become the high percentage of the non response cases which reached 1.6% which is low percentage compared to the household surveys conducted by PCBS, and the reason is the clear questionnaire and the experience of the fieldwork. The lowest value of response rate reached 92.7% in the middle of west bank, and The highest value of response rate reached 98.5% in the south of west bank.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No (dwellings in original sample are interpreted as households in IPUMS) - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Structurally independent living quarters, consisting of one or more rooms with a private entrance, serving up to three families. - Group quarters: Group living together under relations of administrative subordination; group of six or more persons not related by kinship; or a dwelling with more than 3 families.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Instituto Brasileiro de Geografia e Estatística

SAMPLE UNIT: Household (called "dwelling" in original sample)

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 5,870,467

Mode of data collection

Face-to-face [f2f]

Research instrument

Long and short enumeration forms. The short form contains general information about the characteristics of the dwelling and each of persons in the dwelling. The long form contains general and more specific information about the characteristics of the dwelling, families, and each of the people in the dwellings and was applied to a 25% sample of the population.

Response rate

COVERAGE: No official estimates, UNDERCOUNT: No official estimates

Abstract

The National Household Survey - PNAD investigates annually and permanently, general characteristics of the population, education, labor, income and housing, and others with varying regularity, according to the information needs for the country. Such characteristics include migration, fertility , marriage, health, food security, among other topics. The survey of these statistics is an important instrument for the formulation, validation and evaluation of policies to socio-economic development and the improvement of living conditions in Brazil.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey is conducted by a random sample of households. The information is provided by person resident or non-resident, considered capable of providing information for the whole neighborhood and the home. The interviewer is instructed not to accept a person under 14 years of age as an informant. The sampling plan uses cluster sampling, self-weighted in three stages (respectively municipalities, census tracts and households) with geographical stratification of the units of the first stage set for each state. The large municipalities in terms of population and those belonging to the metropolitan areas were each treated as a stratum and therefore included in the sample with certainty, being called autorrepresentativos. The other municipalities within the same geographic microregion were grouped into strata of approximately equal size, and designated non autorrepresentativos. Strata in these municipalities were selected systematically with probability proportional to size (ppt). Sectors are the unit of selection in the second stage and also are selected systematically and ppt, in which case the size is measured by the number of households. The sectors were stratified according to the situation of urban and rural states of the northern region, except for Tocantins, to allow comparison of indicators from PNADs after 2004 with those performed before insertion of the rural area of the northern states. In other regions this stratification is only implicit, ie, there is an ordering for the situation of the sector before the systematic selection. Municipalities and selected sectors are kept in the sample until they are available new Census data, when they are selected new units for the sample. Each year, in each sector selected for the sample is prepared (or updated) in the field a listing of households, producing an updated register for selection. An important characteristic of this listing operation refers to the Register of New Buildings, which is prepared to contain the buildings account for large changes in the sizes of sectors. The inventory of new construction is done in the municipalities of the sample, both in the sectors selected for the sample as those not selected. An area of new construction is excluded from the area of the original sector and is dealt with separately at the time of selection of households in this case is performed according to the sample fraction of the area. Households, which are units of the third selection stage, are formed by private households and the housing units in collective households occupied during the listing operation. The initial number of households per sector in the sample was set at 16. The sampling fraction indicates the proportion of the population constituting the sample. Currently fractions ranging from 1/50 (rural area of Roraima) to 1/800 (Sao Paulo). How the selection of households in each selected sector for the sample is done systematically to ensure self-weighting sample, the selection range of households remains fixed from year to year. This procedure entails an annual increase in the number of households in the sample, it depends on the number of households upgraded the sector by listing operation. In PNAD 2008, approximately 151,000 households were selected. The final size of the sample of PNAD 2009 was approximately 851 municipalities, 7818 153837 sectors and households. In 2007 PNAD introduced the use of electronic collector ( Personal Digital Assistant - PDA) for carrying out data collection, making it possible to improve the research operating system . Also during PNAD 2007 the DIA system was used, which is an imputation system that automatically detects qualitative data errors. Developed by the National Institute of Statistics - INE of Spain, the software aims to facilitate debugging censuses and large statistical research. In this first year of use of the application, all steps of criticism usually applied to data from the National Household Survey core questionnaire were performed, followed by a process of simultaneous validation of the data collected. In 2008 PNAD used only the Canadian Census Edit and Imputation System - CANCEIS already including the procedures usually applied to critical data from the questionnaires. Starting from PNAD 2011 sample selection of Rondônia, Acre, Amazonas, Roraima, Pará and Amapá followed the same methodology in other units of the Federation.

Mode of data collection

Face-to-face [f2f]

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely-designed Household Survey includes modules that measure the cognitive skills (reading, writing and numeracy), socio-emotional skills (personality, behavior and preferences) and job-specific skills (subset of transversal skills with direct job relevance) of a representative sample of adults aged 15 to 64 living in urban areas, whether they work or not. The cognitive skills module also incorporates a direct assessment of reading literacy based on the Survey of Adults Skills instruments. Modules also gather information about family, health and language.

Geographic coverage

The cities that are covered are La Paz, El Alto, Cochabamba and Santa Cruz de la Sierra.

Analysis unit

The units of analysis are the individual respondents and households. A household roster is undertaken at the start of the survey and the individual respondent is randomly selected among all household members 15 to 64 years old. The random selection process was designed by the STEP team and compliance with the procedure is carefully monitored during fieldwork.

Universe

The STEP target population is the population 15-64 years old, living in urban areas, as defined by each country's statistical office. The following are excluded from the sample: - Residents of institutions (prisons, hospitals, etc.) - Residents of senior homes and hospices - Residents of other group dwellings such as college dormitories, halfway homes, workers' quarters, etc. - Persons living outside the country at the time of data collection

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified 3-stage sample design was implemented in Bolivia. The stratification variable is city-wealth category. There are 20 strata created by grouping the primary sample units (PSUs) into the 4 cities, i.e.,1- La Paz, 2-El Alto, 3-Cochabamba, 4-Santa Cruz de la Sierra, and 5 wealth categories, i.e., 1-Poorest, 2-Moderately Poor, 3-Middle Wealth, 4-Moderately Rich, 5-Rich.

The source of the sample frame of the first stage units is the 2001 National Census of Population and Housing carried out by the National Institute of Statistics. The primary sample unit (PSU) is a Census Sector. A sample of 218 PSUs was selected from the 10,304 PSUs on the sample frame. This sample of PSUs was comprised of 160 'initial' PSUs and 58 'reserve' PSUs. Of the 218 sampled PSUs, there were 169 activated PSUs consisting of 155 Initial Sampled PSUs and 14 Reserve sampled PSUs. Among the 160 'initial' PSUs, 5 PSUs were replaced due to security concerns; also, 14 reserve PSUs were activated to supplement the sample for initial PSUs where the target sample of 15 interviews was not achieved due to high levels of non-response; thus, only 169 PSUs were actually activated during data collection. The PSUs were grouped according to city-wealth strata, and within each city-wealth stratum PSUs were selected with probability proportional to size (PPS), where the measure of size was the number of households in a PSU.

The second stage sample unit (SSU) is a household. The sampling objective was to obtain interviews at 15 households within each of the initial PSU sample, resulting in a final initial sample of 2,400 interviews. At the second stage of sample selection, 45 households were selected in each PSU using a systematic random method. The 45 households were randomly divided into 15 'Initial' households, and 30 'Reserve' households that were ranked according to the random sample selection order. Note: Due to higher than expected levels of non-response in some PSUs, additional households were sampled; thus, the final actual sample in some PSUs exceeded 45 households.

The third stage sample unit was an individual 15-64 years old (inclusive). The sampling objective was to select one individual with equal probability from each selected household.

Mode of data collection

Face-to-face [f2f]

Research instrument

The STEP survey instruments include:

• The background questionnaire developed by the World Bank (WB) STEP team
• Reading Literacy Assessment developed by Educational Testing Services (ETS).

All countries adapted and translated both instruments following the STEP technical standards: two independent translators adapted and translated the STEP background questionnaire and Reading Literacy Assessment, while reconciliation was carried out by a third translator.

The survey instruments were piloted as part of the survey pre-test.

The background questionnaire covers such topics as respondents' demographic characteristics, dwelling characteristics, education and training, health, employment, job skill requirements, personality, behavior and preferences, language and family background.

The background questionnaire, the structure of the Reading Literacy Assessment and Reading Literacy Data Codebook are provided in the document "Bolivia STEP Skills Measurement Survey Instruments", available in external resources.

Cleaning operations

STEP data management process:

1) Raw data is sent by the survey firm 2) The World Bank (WB) STEP team runs data checks on the background questionnaire data. Educational Testing Services (ETS) runs data checks on the Reading Literacy Assessment data. Comments and questions are sent back to the survey firm. 3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data. 4) The WB STEP team and ETS check if the data files are clean. This might require additional iterations with the survey firm. 5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies. 6) ETS scales the Reading Literacy Assessment data. 7) The WB STEP team merges the background questionnaire data with the Reading Literacy Assessment data and computes derived variables.

Detailed information on data processing in STEP surveys is provided in "STEP Guidelines for Data Processing" document, available in external resources. The template do-file used by the STEP team to check raw background questionnaire data is provided as an external resource, too.

Response rate

An overall response rate of 43% was achieved in the Bolivia STEP Survey. All non-response cases were documented (refusal/not found/no eligible household member, etc.) and accounted for during the weighting process. In such cases, a reserve household was activated to replace the initial household. Procedures are described in "Operation Manual" that is provided as an external resource.

This statistic shows the 20 countries with the highest population growth rate in 2024. In SouthSudan, the population grew by about 4.65 percent compared to the previous year, making it the country with the highest population growth rate in 2024. The global population Today, the global population amounts to around 7 billion people, i.e. the total number of living humans on Earth. More than half of the global population is living in Asia, while one quarter of the global population resides in Africa. High fertility rates in Africa and Asia, a decline in the mortality rates and an increase in the median age of the world population all contribute to the global population growth. Statistics show that the global population is subject to increase by almost 4 billion people by 2100. The global population growth is a direct result of people living longer because of better living conditions and a healthier nutrition. Three out of five of the most populous countries in the world are located in Asia. Ultimately the highest population growth rate is also found there, the country with the highest population growth rate is Syria. This could be due to a low infant mortality rate in Syria or the ever -expanding tourism sector.

Abstract

The Suriname Multiple Indicator Cluster Survey (MICS) was carried out in 2010 by the Ministry of Social Affairs and Housing in collaboration with General Bureau of Statistics and the Institute for Social Research (IMWO) of the University of Suriname. Financial and technical support was provided by the United Nations Children’s Fund (UNICEF). The Suriname MICS was carried out as part of the fourth round of the global MICS household survey programme with the technical and financial support from UNICEF. MICS is a nationally representative sample survey of women aged 15‐49 and children under age five of 7,407 responding households out of a total of 9,356 sampled households. The main purpose of MICS 2010 is to support the government of Suriname to generate statistically sound and comparable data for monitoring the situation of children and women in the country. MICS 4 covers topics related to nutrition, child health, water and sanitation, reproductive health, child development, literary and education, child protection, HIV and AIDS, mass media and the use of information and communication technology and attitude towards domestic violence.

Geographic coverage

National

Analysis unit

• individuals
• households

Universe

The survey covered all de jure household members (usual residents), all women aged between 15-49 years, and all children under 5 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the Suriname Multiple Indicator Cluster Survey was to produce statistically reliable estimates of most indicators, at the national level, for areas classified as urban, rural coastal and rural interior, and for the 10 districts of the country - Paramaribo, Wanica, Nickerie, Coronie, Marowijne, Commewijne, Sarramacca, Para, Brokopondo, and Sipaliwini.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

The target sample size for the Suriname MICS was calculated as 9,000 households. For the calculation of the sample size, the key indicator used was the number of children younger than 5 years of age who had had diarrhoea in the past two weeks before the survey using the estimate of the last MICS3 survey.

Suriname is divided into 10 districts and 62 'ressorten' by law. The 'ressorten' are subdivisions at the district level. For purposes of conducting the fieldwork during the Seventh Population and Housing Census the General Bureau of Statistics subdivided each ressort in the coastal area (lowland and savannah) into 'telblokken'. A 'telblok' also called an enumeration block, was considered to be the manageable workload for a Census enumerator for the fieldwork period of two weeks and would ideally have between 100 and 150 objects. An object can be any kind of building or a construction work, like, churches, schools, stores, houses, dwellings etc. In order to clarify: not every object stands for a dwelling or living quarters of a household. In the interior (rainforest) a somewhat different fieldwork approach was used, whereby teams consisting of 5-7 fieldworkers canvassed clusters of villages. These clusters were called 'telgebieden' and were expected to have approximately 500 households, or the workload of 5 interviewers. "Telgebied" can also be called an enumeration area.

The 2004 census frame was used for the selection of clusters as the results of the 2004 Census provide a basis for provisional estimates on the number of households. Thus, the 'telblokken' and 'telgebieden' were considered the best currently available subdivisions by the General Bureau of Statistics and formed the basis for the MICS 2010 sample design.

Each of the 10 districts in the country is allocated to one of these strata, but with three towns (Nw. Nickerie in Nickerie district, and Meerzorg and Tamanredjo in Commewijne district) being counted as urban, even though they are located in what are otherwise rural districts.

In the case of MICS3, the total sample had been about 6,000 households. Survey results had been reported not only for the three strata, but also for a five-way breakdown of districts. This was achieved by grouping districts as follows: Paramaribo; Wanica and Para; Nickerie, Coronie and Saramacca; Commewijne and Marowijne; and Brokopondo and Sipaliwini. In the case of MICS4, the sample size was increased to 9,000 households. One of the main benefits of this increase was that it would permit the reporting of indicators at the district level.

The allocation within each stratum was done with probability proportional to size, where the population of each area (from the 2004 census) was used as the measure of size. It was only after the fieldwork was completed that it was realized that the samples allocated to several of the individual districts were insufficient to provide satisfactory estimates for many of the variables. A more equal allocation to each district would have provided more precise estimates for the smaller districts.

It should be noted that, according to sampling theory, it is the size of the sample, rather than the proportion of the population covered, that is the key factor in determining the precision of the estimate. Several districts have sample sizes that are around the 500 level, which is slightly on the low side. An allocation of about 700 households would have been more appropriate, which could have been achieved by reducing the allocation for Paramaribo. In the rural interior, the allocation for Brokopondo might usefully have been increased, with a corresponding reduction in Sipaliwini. Only 140 households were allocated to Cornie, reflecting its small population of less than 1,000 households, but it would have been necessary to cover a larger number of households there (say 300 or 400) in order to obtain reliable estimates.

The actual sample selection in the selected clusters was done as follows. In urban and rural coastal areas, where enumeration districts (EDs) usually contain about 150 households, one pointer address (PA) was selected at random within the ED. If it was not the address of a private household, the next address was taken as the starting point. Twenty adjacent addresses (1 to 20) were then selected around this PA, and a printed map provided to each team, showing the location of each address. In rural areas the enumeration areas might consist of either one village or several smaller villages combined. Where a village was very isolated, it was treated as one enumeration area, even though sometimes it did not contain many households.

The sampling procedures are more fully described in "Suriname Multiple Indicator Cluster Survey 2010 - Final Report" pp.178-181.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Generic MICS were structured questionnaires based on the MICS4 model questionnaire with some modifications and additions. Household questionnaires were administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes household listing form, education, water and sanitation, household characteristics, insecticide treated nets (in Brokopondo and Sipaliwini only), indoor residual spraying (in Brokopondo and Sipaliwini only), child labour, child discipline and hand washing.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or primary caretaker of the child.

The women's questionnaire includes woman's background, access to mass media and use of information/communication technology, desire for last birth, illness symptoms, maternal and newborn health, contraception, unmet need, attitudes towards domestic violence, marriage/union, sexual behavior, HIV/AIDS.

The children's questionnaire includes child's age, birth registration, early childhood development, breastfeeding, care of illness, malaria (in Brokopondo and Sipaliwini only), Immunization (Yellow Fever in Brokopondo and Sipaliwini only) and anthropometry.

In addition to the administration of questionnaires, fieldwork teams observed the place for handwashing and measured the weights and heights of children age under 5 years. Details and findings of these measurements are provided in the respective sections of the report.

The questionnaires included very few non‐standard MICS questions, such as on women’s ownership and use of cell phones, as well as a further question to mothers of children under 5 whose child’s birth had not been registered.

It should be noted that the Malaria related modules and questions were only administered in Brokopondo and Sipaliwini. The same approach was used on vaccination against Yellow Fever.

Cleaning operations

Data were entered using the CSPro software. The data were entered on 6 microcomputers and carried out by 15 data entry operators on a shift system basis and one data entry supervisor. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS4 programme and adapted to the Suriname questionnaire were used throughout. Data processing began simultaneously with data collection in July 2010 and was completed early January 2011. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program and the model tabulation syntax developed by UNICEF facilitated the generation of the estimates.

Response

Abstract

In order to support the development of an economic development strategy for the Greater Kampala metro region, an informal sector survey was undertaken between June 2016 and June 2017 to provide policy makers with analytical information on the prominent sectors within the city. The survey was designed to produce representative estimates for key indicators of the greater Kampala as a whole. The informal sector module of the National Manpower Survey (NMPS) implemented by UBOS was extended to include questions on household based enterprises. The module focuses on skill levels, remuneration, training and working conditions of those in the informal sector.

Geographic coverage

Greater Kampala

Analysis unit

Household Individual Household based enterprises

Universe

The survey targeted households with enterprise and non-household enterprise identified within the enumeration areas. These were identified during a listing operation undertaken prior to the start of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey interviewed 2,243 informal businesses, randomly drawn based on a two-stage stratified sample.

The sampling frame used for informal sector 2016 is the frame for the Uganda Population and Housing Census which was conducted on August 2014 (PHC 2014), provided by the Uganda Bureau of Statistics (UBOS). The sampling frame is a complete list of census Enumeration Areas (EA) created for the census covering the whole country, consisting of 80182 EAs. An EA is a natural village in rural areas and a city block in urban areas. Uganda is divided into 112 administrative districts, each districts is sub-divided into subdistricts, and each sub-district into parish, and each parish into villages. The frame file contains the administrative belongings for each EA and number of households at the time of the census. Each EA has also a designated residence type, urban or rural. Following are the definition of the geo-regions and the study domains.

The sample for the Uganda informal sector survey is designed to provide indicator such as employment, gross output estimates for the greater Kampala. In order to increase the efficiency of the sample design, the sampling frame will be divided into three strata which are as homogeneous as possible. The first level of stratification generally corresponds to the geographic domains of analysis that is Kampala, Wakiso and Mukono.

For more details on Sampling Procedure and Sample Allocation, Sample size determination, please refer to the Methodology document provided under the Related Materials tab.

Mode of data collection

Computer Assisted Personal Interview [capi]

As of 2023, around 37.99 million people of Mexican descent were living in the United States - the largest of any Hispanic group. Puerto Ricans, Salvadorans, Cubans, and Dominicans rounded out the top five Hispanic groups living in the U.S. in that year.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

In 2025, the Ile-de-France region, sometimes called the Paris region, was the most populous in France. It is located in the northern part of France, divided into eight departments and crossed by the Seine River. The region contains Paris, its large suburbs, and several rural areas. The total population in metropolitan France was estimated at around 65 million inhabitants. In the DOM (Overseas Department), France had more than two million citizens spread over the islands of Guadeloupe, Martinique, Reunion, Mayotte, and the South American territory of French Guyana. Ile-de-France: most populous region in France According to the source, more than 12 million French citizens lived in the Ile-de-France region. Ile-de-France was followed by Auvergne-Rhône-Alpes and Occitanie region which is in the Southern part of the country. Ile-de-France is not only the most populated region in France, it is also the French region with the highest population density. In 2020, there were 1,021.6 residents per square kilometer in Ile-de-France compared to 115.9 for Auvergne-Rhône-Alpes, the second most populated region in France. More than two million people were living in the city of Paris in 2025. Thus, the metropolitan area outside the city of Paris, called suburbs or banlieue in French, had more than ten million inhabitants. Ile-de-France concentrates the majority of the country’s economic and political activities. An urban population In 2024, the total population of France amounted to over 68 million. The population in the country increased since the mid-2000s. As well as the other European countries, France is experiencing urbanization. In 2023, more than 81 percent of the French population lived in cities. This phenomenon shapes France’s geography.

As of 2023, the bulk of the Chinese population was aged between 25 and 59 years, amounting to around half of the population. A breakdown of the population by broad age groups reveals that around 61.3 percent of the total population was in working age between 16 and 59 years in 2023. Age cohorts below 25 years were considerably smaller, although there was a slight growth trend in recent years. Population development in China Population development in China over the past decades has been strongly influenced by political and economic factors. After a time of high fertility rates during the Maoist regime, China introduced birth-control measures in the 1970s, including the so-called one-child policy. The fertility rate dropped accordingly from around six children per woman in the 1960s to below two at the end of the 20th century. At the same time, life expectancy increased consistently. In the face of a rapidly aging society, the government gradually lifted the one-child policy after 2012, finally arriving at a three-child policy in 2021. However, like in most other developed countries nowadays, people in China are reluctant to have more than one or two children due to high costs of living and education, as well as changed social norms and private values. China’s top-heavy age pyramid The above-mentioned developments are clearly reflected in the Chinese age pyramid. The age cohorts between 30 and 39 years are the last two larger age cohorts. The cohorts between 15 and 24, which now enter childbearing age, are decisively smaller, which will have a negative effect on the number of births in the coming decade. When looking at a gender distribution of the population pyramid, a considerable gender gap among the younger age cohorts becomes visible, leaving even less room for growth in birth figures.