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

Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

The statistic shows the development of the world population from 1950 to 2050. The world population was around 7.38 billion people in 2015.

The global population

As shown above, the total number of people living on Earth has more than doubled since the 1950s, and continues to increase. A look at the development of the world population since the beginning of the Common Era shows that such a surge in numbers is unprecedented. The first significant rise in population occurred during the 14th century, after the Black Death had killed approximately 25 million people worldwide. Subsequently, the global population increased slowly but steadily until it reached record numbers between 1950 and 2000.

The majority of the global population lives on the Asian continent, as a statistic of the world population by continent shows. In around 100 years, it is estimated that population levels on the African continent will have reached similar levels to those we see in Asia today. As for a forecast of the development of the world population, the figures are estimated to have reached more than 10 billion by the 22nd century.

Growing population numbers pose an increasing risk to the planet, since rocketing numbers equal increased consumption of food and resources. Scientists worry that natural resources, such as oil, and food resources will become scarce, endangering the human race and, even more so, the world’s ecosystem. Nowadays, the number of undernourished / starving people worldwide has decreased slightly, but forecasts paint a darker picture.

In the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.

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.

The average for 2023 based on 196 countries was 10.17 percent. The highest value was in Monaco: 36.36 percent and the lowest value was in Qatar: 1.57 percent. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

In 1800, the population of Japan was just over 30 million, a figure which would grow by just two million in the first half of the 19th century. However, with the fall of the Tokugawa shogunate and the restoration of the emperor in the Meiji Restoration of 1868, Japan would begin transforming from an isolated feudal island, to a modernized empire built on Western models. The Meiji period would see a rapid rise in the population of Japan, as industrialization and advancements in healthcare lead to a significant reduction in child mortality rates, while the creation overseas colonies would lead to a strong economic boom. However, this growth would slow beginning in 1937, as Japan entered a prolonged war with the Republic of China, which later grew into a major theater of the Second World War. The war was eventually brought to Japan's home front, with the escalation of Allied air raids on Japanese urban centers from 1944 onwards (Tokyo was the most-bombed city of the Second World War). By the war's end in 1945 and the subsequent occupation of the island by the Allied military, Japan had suffered over two and a half million military fatalities, and over one million civilian deaths.

The population figures of Japan were quick to recover, as the post-war “economic miracle” would see an unprecedented expansion of the Japanese economy, and would lead to the country becoming one of the first fully industrialized nations in East Asia. As living standards rose, the population of Japan would increase from 77 million in 1945, to over 127 million by the end of the century. However, growth would begin to slow in the late 1980s, as birth rates and migration rates fell, and Japan eventually grew to have one of the oldest populations in the world. The population would peak in 2008 at just over 128 million, but has consistently fallen each year since then, as the fertility rate of the country remains below replacement level (despite government initiatives to counter this) and the country's immigrant population remains relatively stable. The population of Japan is expected to continue its decline in the coming years, and in 2020, it is estimated that approximately 126 million people inhabit the island country.

Abstract

The Integrated Living Conditions Survey (ILCS), conducted annually by the NSS National Statistical Service of the Republic of Armenia, formed the basis for monitoring living conditions in Armenia. The ILCS is a universally recognized best-practice survey for collecting data to inform about the living standards of households. The ILCS comprises comprehensive and valuable data on the welfare of households and separate individuals which gives the NSS an opportunity to provide the public with up to date information on the population’s income, expenditures, the level of poverty and the other changes in living standards on an annual basis.

Geographic coverage

Urban and rural communities

Analysis unit

• Households;
• Individuals.

Kind of data

Sample survey data [ssd]

Sampling procedure

During the 2001-2003 surveys two-stage random sample was used; the first stage covered the selection of settlements - cities and villages, while the second stage was focused on the selection of households in these settlements. The surveys were conducted on the principle of monthly rotation of households by clusters (sample units). In 2002 and 2003 the number of households was 387 with the sample covering 14 cities and 30 villages in 2002 and 17 cities and 20 villages in 2003.

During the 2004-2006 surveys the sampling frame for the ILCS was built using the database of addresses for the 2001 Population Census; the database was developed with the World Bank technical assistance. The database of addresses of all households in Armenia was divided into 48 strata including 12 communities of Yerevan city. The households from other regions (marzes) were grouped according to the following three categories: big towns with 15,000 and more population; villages, and other towns. Big towns formed 16 strata (the only exception was the Vayots Dzor marz where there are no big towns). The villages and other towns formed 10 strata each. According to this division, a random, two-step sample stratified at marz level was developed. All marzes, as well as all urban and rural settlements were included in the sample population according to the share of population residing in those settlements as percent to the total population in the country. In the first step, the settlements, i.e. primary sample units, were selected: 43 towns out of 48 or 90 percent of all towns in Armenia were surveyed during the year; also 216 villages out of 951 or 23 percent of all villages in the country were covered by the survey. In the second step, the respondent households were selected: 6,816 households (5,088 from urban and 1,728 from rural settlements). As a result, for the first time since 1996 survey data were representative at the marz level.

During the 2007-2012 surveys the sampling frame for ILCS was designed according to the database of addresses for the 2001 Population Census, which was developed with the World Bank technical assistance. The sample consisted of two parts: core sample and oversample.

1) For the creation of core sample, the sample frame (database of addresses of all households in Armenia) was divided into 48 strata including 12 communities of Yerevan city. The households from other regions (marzes) were grouped according to three categories: large towns (with population of 15000 and higher), villages and other towns. Large towns formed by 16 groups (strata), while the villages and towns formed by 10 strata each. According to that division, a random, two-step sample stratified at the marz level was developed. All marzes, as well as all urban and rural settlements were included in the sample population according to the share of households residing in those settlements as percent to the total households in the country. In the first step, using the PPS method the enumeration units (i.e., primary sample units to be surveyed during the year) were selected. 2007 sample includes 48 urban and 18 rural enumeration areas per month. 2) The oversample was drawn from the list of villages included in MCA-Armenia Rural Roads Rehabilitation Project. The enumeration areas of villages that were already in the core sample were excluded from that list. From the remaining enumeration areas 18 enumeration areas were selected per month. Thus, the rural sample size was doubled. 3) After merging the core sample and oversample, the survey households were selected in the second step. 656 households were surveyed per month, from which 368 from urban and 288 from rural settlements. Each month 82 interviewers had conducted field work, and their workload included 8 households per month. In 2007 number of surveyed households was 7,872 (4,416 from urban and 3,456 from rural areas).

For the survey 2013 the sample frame for ILCS was designed in accordance with the database of addresses of all private households in the country developed on basis of the 2001 Population Census results, with the technical assistance of the World Bank. The method of systematic representative probability sampling was used to frame the sample. For the purpose of drawing the sample, the sample frame was divided into 32 strata including 12 communities of Yerevan City (currently, the administrative districts). According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all urban and rural communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration areas - that is primary sample units to be surveyed during the year - were selected. The ILCS 2013 sample included 32 enumeration areas in urban and 16 enumeration areas in rural communities per month. The households to be surveyed were selected in the second round. A total of 432 households were surveyed per month, of which 279 and 153 households from urban and rural communities, respectively. Every month 48 interviewers went on field work with a workload of 9 households per month.

The sample frame for 2014-2016 was designed in accordance with the database of addresses of all private households in the country developed on basis of the 2011 Population Census results, with the technical assistance of the World Bank. The method of systematic representative probability sampling was used to frame the sample.
For drawing the sample, the sample frame was divided into 32 strata including 12 communities of Yerevan City (currently, the administrative districts). According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all urban and rural communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration areas - that is primary sample units to be surveyed during the year - were selected. The ILCS 2014 sample included 30 enumeration areas in urban and 18 enumeration areas in rural communities per month. The method of representative probability sampling was used to frame the sample. At regional level, all communities were grouped into two categories - towns and villages. According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all rural and urban communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration districts - that is primary sample units to be surveyed during the year - were selected. The ILCS 2015 sample included 30 enumeration districts in urban and 18 enumeration districts in rural communities per month.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire is filled in by the interviewer during the least five visits to households per month. During face-to-face interviews with the household head or another knowledgeable adult member, the interviewer collects information on the composition and housing conditions of the household, the employment status, educational level and health condition of the members, availability and use of land, livestock, and agricultural machinery, monetary and commodity flows between households, and other information.

The 2010 survey questionnaire had the following sections: (1) "List of Household Members", (2) "Migration", (3) "Housing and Dwelling Conditions", (4) "Employment", (5) "Education", (6) "Agriculture", (7) "Food Production", (8) "Monetary and Commodity Flows between Households", (9) "Health (General) and Healthcare", (10) "Debts", (11) "Subjective Assessment of Living Conditions", (12) "Provision of Services", (13) "Social Assistance", (14) "Households as Employers for Service Personnel", and (15) "Household Monthly Consumption of Energy Resources".

The Diary is completed directly by the household for one month. Every day the household would record all its expenditures on food, non-food products and services, also giving a detailed description of such purchases; e.g. for food products the name, quantity, cost, and place of purchase of the product is recorded. Besides, the household records its consumption of food products received and used from its own land and livestock, as well as from other sources (e.g. gifts, humanitarian aid). Non-food products and services purchased or received for free are also recorded in the diary. Then, the household records its income received during the month. At the end of the month, information on rarely used food products, durable goods and ceremonies is recorded, as well. The records in the diary are verified by the interviewer in the course of 5

A collaborative project between SPC, the World Fish Centre and the University of Wollongong has produced the first detailed population estimates of people living close to the coast in the 22 Pacific Island Countries and Territories (PICTs). These estimates are stratified into 1, 5, and 10km zones. More information about this dataset: https://sdd.spc.int/mapping-coastal

Women Who were First Married by Age 15: % of Women Aged 20-24 data was reported at 0.100 % in 2020. Women Who were First Married by Age 15: % of Women Aged 20-24 data is updated yearly, averaging 0.100 % from Dec 2020 (Median) to 2020, with 1 observations. The data reached an all-time high of 0.100 % in 2020 and a record low of 0.100 % in 2020. Women Who were First Married by Age 15: % of Women Aged 20-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Population and Urbanization Statistics. Women who were first married by age 15 refers to the percentage of women ages 20-24 who were first married by age 15.;UNICEF Data; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), AIDS Indicator Surveys(AIS), Reproductive Health Survey(RHS), and other household surveys.;;This is the Sustainable Development Goal indicator 5.3.1[https://unstats.un.org/sdgs/metadata/].

Japan JP: Population: Total: Aged 65 and Above data was reported at 34,293,754.000 Person in 2017. This records an increase from the previous number of 33,735,537.000 Person for 2016. Japan JP: Population: Total: Aged 65 and Above data is updated yearly, averaging 13,829,440.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 34,293,754.000 Person in 2017 and a record low of 5,199,270.000 Person in 1960. Japan JP: Population: Total: Aged 65 and Above data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank: Population and Urbanization Statistics. Total population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2017 Revision.; Sum;

Albania Women Who were First Married by Age 18: % of Women Aged 20-24 data was reported at 11.800 % in 2018. This records an increase from the previous number of 9.600 % for 2009. Albania Women Who were First Married by Age 18: % of Women Aged 20-24 data is updated yearly, averaging 10.700 % from Dec 2009 (Median) to 2018, with 2 observations. The data reached an all-time high of 11.800 % in 2018 and a record low of 9.600 % in 2009. Albania Women Who were First Married by Age 18: % of Women Aged 20-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Population and Urbanization Statistics. Women who were first married by age 18 refers to the percentage of women ages 20-24 who were first married by age 18.;UNICEF Data; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), AIDS Indicator Surveys(AIS), Reproductive Health Survey(RHS), and other household surveys.;;This is the Sustainable Development Goal indicator 5.3.1[https://unstats.un.org/sdgs/metadata/].

Abstract

The NLSS 1995/96 is basically limited to the living standards of households.

The basic objectives of this survey was to provide information required for monitoring the progress in improving national living standards and to evaluate the impact of various government policies and program on living condition of the population. This survey captured comprehensive set of data on different aspects of households welfare like consumption, income, housing, labour markets, education, health etc.

Geographic coverage

National coverage The 4 strata of the survey: - Mountains - Hills (Urban) - Hills (Rural) - Terai

Analysis unit

• Household
• Individual
• Community

Universe

The survey covered all modified de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design

Sample Frame: A complete list of all wards in the country, with a measure of size, was developed in order to select from it with Probability Proportional to Size (PPS) the sample of wards to be visited. The 1991 Population Census of Nepal was the best starting point for building such a sample frame. The Central Bureau of Statistics (CBS) constructed a data set with basic information from the census at the ward level. This data set was used as a sample frame to develop the NLSS sample.

Sample Design: The sample size for the NLSS was set at 3,388 households. This sample was divided into four strata based on the geographic and ecological regions of the country: (i) mountains, (ii) urban Hills, (iii) rural Hills, and (iv) Terai.

The sample size was designed to provide enough observations within each ecological stratum to ensure adequate statistical accuracy, as well as enough variation in key variables for policy analysis within each stratum, while respecting resource constraints and the need to balance sampling and non-sampling errors.

A two-stage stratified sampling procedure was used to select the sample for the NLSS. The primary sampling unit (PSU) is the ward, the smallest administrative unit in the 1991 Population Census. In order to increase the variability of the sample, it was decided that a small number of households - twelve - would be interviewed in each ward. Thus, a total of275 wards was obtained.

In the first stage of the sampling, wards were selected with probability proportional to size (PPS) from each of the four ecological strata, using the number of household in the ward as the measure of size. In order to give the sample an implicit stratification respecting the division of the country into Development Regions, the sample frame was sorted by ascending order of district codes, and these were numbered from East to West. The sample frame considered all the 75 districts in the country, and indeed 73 of them were represented in the sample. In the second stage of the sampling, a fixed number of households were chosen with equal probabilities from each selected PSU.

The two-stage procedure just described has several advantages. It simplified the analysis by providing a self-weighted sample. It also reduced the travel time and cost, as 12 or 16 households are interviewed in each ward. In addition, as the number of households to be interviewed in each ward was known in advance, the procedure made it possible to plan an even workload across different survey teams.

Mode of data collection

Face-to-face [f2f]

Research instrument

A preliminary draft of the questionnaire was first prepared with several discussions held between the core staff and the consultant to the project. Several documents both received from the world bank as well as from countries that had already conducted such surveys in the past were referred during this process. Subsequently the questionnaire was translated into NepalI.

After a suitable draft design of the questionnaire, a pre-test was conducted in five different places of the country. The places selected for the pre-test were Biratnagar, Rasuwa, Palpa, Nepalganj and Kathmandu Valley. The entire teams created for the pre-test were also represented by either a consultant or an expert from the bank. Feedback received from the field was utilized for necessary improvements in finalizing the seventy page questionnaire.

The content of each questionnaire is as follows:

HOUSEHOLD QUESTIONNAIRE

Section 1. HOUSEHOLD INFORMATION This section served two main purposes: (i) identify every person who is a member of the household, and (ii) provide basic demographic data such as age, sex, and marital status of everyone presently living in the household. In addition, information collected also included data on all economic activities undertaken by household members and on unemployment.

Section 2. HOUSING This section collected information on the type of dwelling occupied by the household, as well as on the household's expenditures on housing and amenities (rent, expenditure on water, garbage collection, electricity, etc.).

Section 3. ACCESS TO FACILITIES This section collected information on the distance from the household's residence to various public facilities and services.

Section 4. MIGRATION This section collected information from the household head on permanent migration for reasons of work or land availability.

Section 5. FOOD EXPENSES AND HOME PRODUCTION This section collected information on all food expenditures of the household, as well as on consumption of food items that the household produced.

Section 6. NON-FOOD EXPENDITURES AND INVENTORY OF DURABLE GOODS This section collected information on expenditure on non-food items (clothing, fuels, items for the house, etc.), as well as on the durable goods owned by the household.

Section 7. EDUCATION This section collected information on literacy for all household members aged 5 years and above, on the level of education for those members who have attended school in the past, and on levelof education and expenditures on schooling for those currently attending an educational institution.

Section 8. HEALTH This section collected information on illnesses, use of medical facilities, expenditure on health care, children's immunization, and diarrhea.

Section 9. ANTHROPOMETRICS This section collected weight and height measurements for all children 3 years or under.

Section 10. MARRIAGE AND MATERNITY HISTORY This section collected information on maternity history, pre/post-natal care, and knowledge/use of family planning methods.

Section 11. WAGE EMPLOYMENT This section collected information on wage employment in agriculture and in non-agricultural activities, as well as on income earned through wage labor.

Section 12. FARMING AND LIVESTOCK This section collected information on all agricultural activities -- land owned or operated, crops grown, use of crops, income from the sale of crops, ownership of livestock, and income from the sale of livestock.

Section 13. NON-FARM ENTERPRISES/ACTIVITIES This section collected information on all non-agricultural enterprises and activities -- type of activity, revenue earned, expenditures, etc.

Section 14. CREDIT AND SAVINGS This section collected information on loans made by the household to others, or loans taken from others by household members, as well as on land, property, or other fixed assets owned by the household.

Section 15. REMITTANCES AND TRANSFERS This section collected information on remittances sent by members of the household to others and on transfers received by members of the household from others.

Section 16. OTHER ASSETS AND INCOME This section collected information on income from all other sources not covered elsewhere in the questionnaire.

Section 17. ADEQUACY OF CONSUMPTION This section collected information on whether the household perceives its level of consumption to be adequate or not.

RURAL COMMUNITY QUESTIONNAIRE

Section 1. POPULATION CHARACTERISTICS AND INFRASTRUCTURES This section collected information on the characteristics of the community, availability of electricity and its services and water supply and sewerage.

Section 2. ACCESS TO FACILITIES Data on services and amenities, education status and health facilities was collected.

Section 3. AGRICULTURE AND FORESTRY Information on the land situation, irrigation systems, crop cycles, wages paid to hired labor, rental rates for cattle and machinery and forestry use were asked in this section.

Section 4. MIGRATION This section collected information on the main migratory movements in and out.

Section 5. DEVELOPMENT PROGRAMS, USER GROUPS, etc. In this section, information on development programs, existence user groups, and the quality of life in the community was collected.

Section 6. RURAL PRIMARY SCHOOL This section collected information on enrollment, infrastructure, and supplies.

Section 7. RURAL HEALTH FACILITY This section collected information on health facilities, equipment and services available, and health personnel in the community.

Section 8. MARKETS AND PRICES This section collected information on local shops, Haat Bazaar, agricultural inputs, sale of crops and the conversion of local units into standard units.

URBAN COMMUNITY QUESTIONNAIRE

Section 1. POPULATION CHARACTERISTICS AND INFRASTRUCTURE Information was collected on the characteristics of the community, availability of electricity, water supply and sewerage system in the ward.

Section 2. ACCESS TO FACILITIES This section collected information on the distance from the community to the various places and public facilities and services.

Section 3. MARKETS AND PRICES This section collected information on the availability and prices of different goods.

Section 4. QUALITY OF LIFE Here the notion of the quality of life in the community was

Niger NE: Women Who were First Married by Age 15: % of Women Aged 20-24 data was reported at 28.000 % in 2012. This records a decrease from the previous number of 36.100 % for 2006. Niger NE: Women Who were First Married by Age 15: % of Women Aged 20-24 data is updated yearly, averaging 35.600 % from Dec 1992 (Median) to 2012, with 4 observations. The data reached an all-time high of 50.300 % in 1992 and a record low of 28.000 % in 2012. Niger NE: Women Who were First Married by Age 15: % of Women Aged 20-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Niger – Table NE.World Bank: Population and Urbanization Statistics. Women who were first married by age 15 refers to the percentage of women ages 20-24 who were first married by age 15.; ; Demographic and Health Surveys (DHS); ;

Abstract

The principal objective of this survey is to collect basic data reflecting the actual living conditions of the population in Tajikistan. These data will then be used for evaluating socio-economic development and formulating policies to improve living conditions.

The first assessment of living standards in Tajikistan was conducted in 1999. This assessment is bringing about data in order to update the 1999 assessment.

The survey collects information on education, health, employment and other productive activities, demographic characteristics, migration, housing conditions, expenditures and assets.

The information gathered is intended to improve economic and social policy in Tajikistan. It should enable decision-makers to 1) identify target groups for government assistance, 2) inform programs of socio-economic development, and 3) analyse the impact of decisions already made and the current economic conditions on households.

Geographic coverage

National coverage. The 2003 data are representative at the regional level (4 regions) and urban/rural.

Analysis unit

• Households
• Individuals
• Communites

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tajikistan Living Standards Survey (TLSS) for 2003 was based on a stratified random probability sample, with the sample stratified according to oblast and urban/rural settlements and with the share of each strata in the overall sample being in proportion to its share in the total number of households as recorded in the 2000 Census. The same approach was used in the TLSS 1999 although there were some differences in the sampling. First the share of each strata in the overall sample in 1999 was determined according to ‘best estimates’, as it was conducted prior to the 2000 Census. Second the TLSS 2003 over-sampled by 40 percent in Dushanbe, 300 percent in rural Gorno-Badakhshan Administrative Oblast (GBAO) and 600 percent in urban GBAO. Third the sample size was increased in 2003 in comparison with 1999 in order to reduce sampling error. In 2003, the overall sample size was 4,156 households compared with 2,000 households in 1999. [Note: Taken from “Republic of Tajikistan: Poverty Assessment Update”, Report No. 30853, Human Development Sector Unit, Central Asia Country Unit, Europe and Central Asia Region, World Bank, January 2005.]

In addition to the capital city of Dushanbe, the country has several oblasts (regions): (i) Khatlon (comprising Kurban-Tube and Khulyab), which is an agricultural area with most of the country’s cotton growing districts; (ii) the Rayons of Republican Subordination (RRS) with the massive aluminum smelter in the west and agricultural valleys in the east growing crops other than cotton; (iii) Sugd which is the most industrialized oblast; and (iv) Gorno-Badakhshan Administrative Oblast which is mountainous and remote with a small population.

The 2003 data are representative at the regional level (4 regions) and urban/rural.

Mode of data collection

Face-to-face [f2f]

Abstract

Over the past decade, Albania has been seeking to develop the framework for a market economy and more open society. It has faced severe internal and external challenges in the interim – extremely low income levels and a lack of basic infrastructure, the rapid collapse of output and inflation rise after the shift in regime in 1991, the turmoil during the 1997 pyramid crisis, and the social and economic shocks accompanying the 1999 Kosovo crisis. In the face of these challenges, Albania has made notable progress in creating conditions conducive to growth and poverty reduction.

In the process leading to its first Poverty Reduction Strategy (that is the National Strategy for Socioeconomic Development, now renamed the National Strategy for Development and Integration), the Government of Albania reinforced its commitment to strengthening its own capacity to collect and analyze on a regular basis the information it needs to inform policy-making.

Multi-purpose household surveys are one of the main sources of information to determine living conditions and measure the poverty situation of a country. They provide an indispensable tool to assist policy-makers in monitoring and targeting social programs. In its first phase (2001-2006), this monitoring system included the following data collection instruments: (i) Population and Housing Census; (ii) Living Standards Measurement Surveys every 3 years, and (iii) annual panel surveys.

The Population and Housing Census (PHC) conducted in April 2001, provided the country with a much needed updated sampling frame which is one of the building blocks for the household survey structure. The focus during this first phase of the monitoring system is on a periodic LSMS (in 2002 and 2005), followed by panel surveys on a subsample of LSMS households (in 2003, and 2004), drawing heavily on the 2001 census information.

A poverty profile based on 2002 data showed that some 25 percent of the population are poor, with many others vulnerable to poverty due to their incomes being close to the poverty threshold. Income related poverty is compounded by poor access to basic infrastructure (regular supply of electricity, clean water), education and health services, housing, etc.

The 2005 LSMS was in the field between May and early July, with an additional visit to agricultural households in October, 2005. The survey work was undertaken by the Living Standards unit of INSTAT, with the technical assistance of the World Bank.

Geographic coverage

National coverage. Domains: Tirana, other urban, rural; Agro-ecological areas (coastal, central, mountain)

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The Republic of Albania is divided geographically into 12 Prefectures (Prefekturat). The latter are divided into Districts (Rrethet) which are, in turn, divided into Cities (Qyteti) and Communes (Komunat). The Communes contain all the rural villages and the very small cities. For census purposes, the cities and the villages have been divided into enumeration areas (EAs).

1. Sampling frame

The Enumeration Areas (EA) that make up the sampling frame come from the April 2001 General Census of Population and Housing. The EAs in the frame are classified by Prefecture, District, City or Commune. The frame also contains, for every EA, the number of Housing Units (HU), the number of occupied HUs, the number of unoccupied HUs, the number of households, and the population. We are using occupied dwellings and not total number of dwellings since many EAs contain a large number of empty dwellings.

A detailed study of the list of census EAs shows that many have zero population. In order to obtain EAs with the minimum of 50 and the maximum of 120 occupied housing units, the EAs with zero population have been taken off the sampling frame. Since the sizes of the EAs varied from 0 to 395 HUs, the smaller EAs (with less than 50 HU) have been collapsed with geographically adjacent ones and the largest EAs (with more than 120 HU) have been split into two or more EAs. Subsequently, maps identifying the boundaries of every split and collapsed EA were prepared. Given that the 2002 LSMS has been conducted less than a year after the April 2001 census, a listing operation to update the sample EAs was not conducted in the field. However, since the level of construction is very high in the city of Tirana and its suburbs, a quick count of the 75 sample EAs selected in Tirana was carried out followed by a listing operation. The check of the listing based on the Census data revealed two types of discrepancies: - HUs had become invalid, i.e. vacant, nonresidential, demolished, seasonally occupied, etc. - Instead of one small building (with one or two HU), a new one with 15 HUs was identified.

During of the listing update process, HUs identified as invalid were taken off the frame. In the case of a new building, these new HUs were entered with a new sequential code. The listing sheets prepared during the listing operation in Tirana, become the sampling frame for the final stage of selection of 12 HU which has to be interviewed. The unit of analysis and the unit of observation is the household. The universe under study consists of all the households in the Republic of Albania. We have used the Housing Unit (defined as the space occupied by one household) as the sampling unit, instead of the household, because the HU is more permanent and easier to identify in the field.

1. Sample Size

In the LSMS the sample size is 450 EA and in each EA 8 households were selected. So the total sample size of the LSMS is 3600 households. In addition, since a certain level of nonresponse is expected, 4 reserve units were selected in each sample EA.

1. Stratification

The sampling frame has been divided in three regions (strata) 1. Coastal Area 2. Central Area 3. Mountain Area and Tirana (urban and other urban) is consider as a separate strata.

The first three strata were divided into major cities (the most important cities in the region), other urban (the rest of cities in the region), and rural. In each more importance was given to the major cities and rural areas. We have selected 10 EA for each major city and 65 EAs (75 EAs for Mountain Area) for each region. In the city of Tirana and its suburbs, implicit stratification was used to improve the efficiency of the sample design.

1. Procedure for the Selection of Housing Units

A fixed number of valid dwelling units (12) was selected systematically and with equal probability from the Listing Form pertaining to Tirana and from the Census forms for the other areas. Once the 12 HUs were selected, 4 of them were chosen at random and kept as reserve units. The selected HUs were numbered within the EA and identified with a circle around the number in the listing form, as well as a circle on the maps. The reserve sample (units 9 to 12) were identified from R1 to R4 during data collection to emphasize the fact that they were reserve units.

Two copies of the sample listing sheets and two copies of maps for each EA were printed. The first copy of the listing sheet and the map were given to the supervisor and included the 12 HU, the second copy was given to the enumerator. The enumerator only received the 8 dwelling units, not the reserve ones. Each time the enumerator needed a reserve HU, he/she had to ask the supervisor and explain the reason why a reserve unit was needed. This process helped determine the reason why reserve units were used and provided more control on their use.

In the field the enumerator registered the occupancy status of every unit: - occupied as principal residence - vacant - under construction (not occupied) - demolished or abandoned (not occupied) - seasonally occupied

In the case that one HU was found to be invalid, the enumerator used the first reserve unit (identified with the code R1). In the case that in one EA more than 4 DU selected were invalid, other units from that EA chosen at random by headquarter (in Tirana) were selected as replacement units to keep the enumerator load constant and maintain a uniform sample size in each EA. Before identifying the invalid HUs, the interviewer had to note the interview status of each visit for all the units for which an interview was attempted, whether these are original units or reserve units. This was done to determine the interview status: interview completed, nonresponse, refusal, etc. In other words, this will allow identifying: the completed interviews (responses obtained), the incomplete but usable ones (responses obtained), the incomplete ones but not usable (nonresponse), the refusals (nonresponse) and the "not at home" (nonresponse). Subsequently, the invalid units identified were substituted with the available reserves, always maintaining the sample of 8 HUs.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four survey instruments were used to collect information for the 2005 Albania LSMS: a household questionnaire, a diary for recording household food consumption, a community questionnaire, and a price questionnaire.

The household questionnaire included all the core LSMS modules as defined in Grosh and Glewwe (2000)1, plus additional modules on migration, fertility, subjective poverty, agriculture, non-farm enterprises, and social capital. Geographical referencing data on the longitude and latitude of each household were also recorded using portable GPS devices. Geo-referencing will enable a more efficient spatial link among the different surveys of the system, as well as between the survey households and other geo-referenced information.

The choice of the modules was aimed at matching as much as

Abstract

The ECVM/A is an integrated multi-topic household survey done for the purpose of evaluating poverty and living conditions in Niger.

The main objectives of the ECVMA are to: - Gauge the progress made with achievement of the Millennium Development Goals (MDGs); - Facilitate the updating of the social indicators used in formulating the policies aimed at improving the living conditions of the population; - Provide data related to several areas that are important to Niger without conducting specific surveys on individual topics ; - Provide data on several important areas for Niger that are not necessarily collected in other more specific surveys.

The ECVM/A involves two visits, which means that each household is visited twice. The first visit takes place during the planting season. The second visit takes place during the harvest season. The household and agriculture/livestock, as well as the community/price questionnaire are administered during the first visit. During the second visit, only the household and agriculture/livestock questionnaires are administered.

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The ECVM/A 2011 has been designed to have national coverage, including both urban and rural areas in all the regions of the country. The domains are defined as the entire country, the city of Niamey; and other urban areas, rural areas, and in the rural areas, agricultural zones, agro-pastoral zones and pastoral zones. Taking this into account, 26 explicit sampling strata were selected: Niamey, and urban, agriculture, agro-pastoral and pastoral zones of the seven regions other than Niamey.

The target population is drawn from households in all 8 regions of the country with the exception of certain strata found in Arlit (Agadez Region) because of difficulties in going there, the very low population density, and collective housing. The portion of the population excluded from the sample represents less than 0.4% of the total population of Niger. Of a total of 36,000 people not included in the sample design, about 29,000 live in Arlit and 7,000 in collective housing.

The sample was chosen through a random two stage process:

• In the first stage a certain number of Enumeration Areas (known as Zones de Dénombrement or ZDs) will be selected with Probability Proportional to Size (PPS) using the 2001 General Census of Population and Housing as the base for the sample, and the number of households as a measure of size.
• In the second stage, 12 or 18 households will be selected with equal probability in each urban or rural ZD respectively. The base for the sample will be an exhaustive listing of households that will be done before the start of the survey.

The total estimated size of the sample is 4,074 households. The fact that this is the first survey with panel households to be revisited in the future was taken into account in the design and therefore it is possible to lose households between the two surveys with minimal adverse effects on the analyses.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household questionnaire comprises 13 sections, not including the cover page which covers information of a general nature (identity, name of household head) and Section 0 which covers detailed information on household identification and the results of the survey. The second visit household questionnaire is a reduced version of the version used in the first round. It includes information to determine if members who were in the household in the first visit are still in the household and if there are any new members. When there are new members, the questionnaire is used to collect basic information on their socio-demographic.

Like the household questionnaire, the agriculture/livestock questionnaire is divided into sections and sub-sections. The different sections, numbering 8 in all, address the issues of access to land, rainy season agriculture, "contre-saison" agriculture (dry season), livestock, forestry, agricultural equipment, access to agricultural extension services, and climate change. The agriculture and livestock questionnaire, second visit, collects information on harvests from the recently completed season and information on livestock rearing and production. In addition, information was collected on tree crops, agricultural extension, and climate change.

The community questionnaire has 7 sections. In addition, the cover pages collects general information (identification information, etc.) and section 0 provides the names of the respondents. In the second visit, the community questionnaire was used only to collect local prices.

Cleaning operations

The data entry was done in the field simultaneously with the data collection. Each data collection team included a data entry operator who key entered the data soon after it was collected. The data entry program was designed in CSPro, a data entry package developed by the US Census Bureau. This program allows three types of data checks: (1) range checks; (2) intra-record checks to verify inconsistencies pertinent to the particular module of the questionnaire; and (3) inter-record checks to determine inconsistencies between the different modules of the questionnaire.

The data entry from the first passage was completed in September 2011 and data cleaning was completed in December. The data cleaning process took longer than expected because it was done simultaneously with preparing for the second visit. Data entry from the second visit was completed in January 2012 and the data cleaning for both rounds was completed in August 2012.

Guatemala GT: Women Who were First Married by Age 18: % of Women Aged 20-24 data was reported at 29.500 % in 2015. This records a decrease from the previous number of 30.300 % for 2009. Guatemala GT: Women Who were First Married by Age 18: % of Women Aged 20-24 data is updated yearly, averaging 34.650 % from Dec 1987 (Median) to 2015, with 6 observations. The data reached an all-time high of 41.200 % in 1987 and a record low of 29.500 % in 2015. Guatemala GT: Women Who were First Married by Age 18: % of Women Aged 20-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guatemala – Table GT.World Bank: Population and Urbanization Statistics. Women who were first married by age 18 refers to the percentage of women ages 20-24 who were first married by age 18.; ; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), AIDS Indicator Surveys(AIS), Reproductive Health Survey(RHS), and other household surveys.; ;

As of late 2022, Jeanne Calment was the oldest person who ever lived. Born in Arles, France, in 1875, she died at the age of 122 years and 164 days. The American, Sarah Knauss, followed, having lived 119 years and 97 days. On January 17, 2023, nun Sister André died at the age of 118.

Ageing populations a result of lower fertility rates and higher life expectancies

Population aging indicates a rise in the median age of the population. In 2022, Monaco was the country with the highest percentage of the population aged 65 years and older, amounting to 36 percent. In the same year, Japan recorded the second oldest population globally with 29 percent of the Japanese population over 65. Moreover, Monaco has recorded the highest median age in the world at over 55 years, followed, again, by Japan. In terms of fertility rates, some of the lowest figures can be found across parts of Asia, with Taiwan recording the lowest fertility rate at 1.07 children per woman.

Ageing populations put a strain on the health and social system

Geriatric healthcare refers to the health and care of the elderly. Particularly, this branch of the healthcare system addresses older adults’ healthcare needs and prevents and treats diseases among the older population, such as heart and/or respiratory diseases, cancer, and dementia. For instance, heart diseases and tumors were among the leading death causes in the United States. In most countries, to treat such diseases among others, people need either public or private insurance. In 2022, United Healthcare was the most valuable healthcare service brand worldwide.

Summary

This metadata record provides details of the data supporting the claims of the related article: “Genomic context of NTRK1/2/3 fusion-positive tumours from a large real-world population”.

The related study aimed to interrogate a large real-world database of comprehensive genomic profiling data to describe the genomic landscape and prevalence of neurotrophic tropomyosin receptor kinase (NTRK) gene fusions.

Subject of data: Homo sapiens

Sample size: Data from 295,676 de-identified, consented-for-research cases between January 2013 and December 2019 from 75 different solid tumour types were profiled. Sample size for the clinical trials population was the efficacy-evaluable population, i.e., all patients who had received at least one dose of entrectinib and had at least 6 months of follow up.

Recruitment: This is a secondary analysis of data from the clinical trials listed below. Full methods have been published previously in: https://doi.org/10.1016/s1470-2045(19)30691-6

Trial registration number: ALKA-372-001 [EudraCT 2012-000148-88], STARTRK-1 [NCT02097810], STARTRK-2 [NCT02568267]

Data access

The data were generated and analysed under the auspices of Roche, which is a member of the Vivli Center for global clinical research data. Data access conditions are described at https://vivli.org/ourmember/roche/. To request access to individual patient-level data from the clinical trials, first locate the clinical trial in Vivli (https://search.vivli.org/ requires sign up and log in) using the trial registration number (given above), then click the ‘Request Study’ button and follow the instructions. In the event that you cannot see a specific study in the Roche list, an Enquiry Form can be submitted to confirm the availability of the specific study. To request access to related clinical study documents (eg: protocols, CSR, safety reports), please use Roche’s Clinical study documents request form: https://www.roche.com/research_and_development/who_we_are_how_we_work/research_and_clinical_trials/our_commitment_to_data_sharing/clinical_study_documents_request_form.htm.Patient-level data which were derived from the Foundation Research dataset and used in the related study cannot be shared as they contain patient genomic information that, depending on the prevalence of the identified alterations, could be used to identify individuals.

To maximise transparency and provide the most thorough information without compromising patients’ personal information, the authors have created a large number of supplementary files and made them openly available as part of this figshare data record. Data underlying Supplementary Figure 2 are in the file ‘data_underlying_supplementary_figure_2.xlsx’. Data underlying Supplementary Tables 1–4, 6–12, and 14 are in the file ‘FMI NTRK manuscript_Supplementary Tables_17May2021.xlsx’.

Corresponding author(s) for this study

Dr C. Benedikt Westphalen, Comprehensive Cancer Center Munich & Department of Medicine III, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. Tel: +49 (089) 4400-75250; E-mail: cwestpha@med.lmu.de

Study approval

Approval was obtained from the Western Institutional Review Board (Protocol No. 20152817). Written consent was obtained to use the de-identified patient samples for research.