Vol 1. Policy Statement to Promoting a Viable Population and Environment within the Paradigm of Responsible Sustainable Development.

With the focus on ensuring a comprehensive National Population Policy, taking into account the multidisciplinary relationship of population issues and development, demographic change, and the inclusion of demographic dynamics is in the process of the Royal Government preparing the National Population Policy 2016-2020 in the following two concepts: 1/ To carry on with the principles of National Population Policy 2003, recognizing and supporting the rights of spouses and individuals to have the fundamental decision on the free and responsible number of children and contraception with access through information, education, services, and means; 2/ To demonstrate an overview of economic and social development, demographic implications for current and future development, setting out a number of orientations based upon policies and programs to be implemented by ministries and professional institutions. The strategic goal of the National Population Policy 2016-2030 is to contribute towards the continuous improvement of the quality of life and poverty alleviation to the Cambodian people; focusing on environmentally friendly development and joint efforts to be sustainable and equitable economic growth, social development, and environmental protection within the framework of national and global development.

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Day, New York, is 11.6.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Day, New York, is 64.3.
• Total dependency ratio for Day, New York is 75.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Day, New York is 1.6.

Content

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

Age groups:

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

Variables / Data Columns

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

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Day town Population by Age. You can refer the same here

Abstract

The 2021 NPHC is tthe first census conducted under the federal structure of Nepal. The main census enumeration was originally scheduled to take place over 15 days- from June 8 to 22, 2021, but due to the COVID-19 pandemic, the enumeration was postponed for five months. Once the impact of the pandemic subsided, the enumeration was carried out according to a new work plan for a 15 dya period from November 11 to 25, 2021.

This report contains statistical tables at the national, provincial, district and municipal levels, derived from the topics covered in the census questionaires. The work of the analyzing the data in detail is still in progress. The report provides insights into the different aspects of the census operation, including its procedure, concepts, methodology, quality control, logistics, communication, data processing, challenges faced, and other management aspects.

This census slightly differs from the previous censuses mainly due to the following activities: i. three modes of data collection (CAPI, PAPI and e-census); ii. a full count of all questions instead of sampling for certain questions, as was done in the previous two censuses, iii. collaboration with Ministry of Health and Population to ascertain the likely maternal mortality cases reported in the census by skilled health personnel; iv. data processing within its premises; v. recuitment of fresh youths as supervisor and enumerators; and vi. using school teachers as master trainers, especially for the local level training of enumerators.

The objectives of the 2021 Population Census were:

a) to develop a set of benchmark data for different purposes. b) to provide distribution of population by demographic, social and economic characteristics. c) to provide data for small administrative areas of the country on population and housing characteristics. d) to provide reliable frames for different types of sample surveys. e) to provide many demographic indicators like birth rates, death rates and migration rates. f) to project population for the coming years.

The total population of Nepal, as of the census day (25 November 2021) is 29,164,578, of which the number of males is 14,253,551 (48.87 %) and the number of females is 14,911,027 (51.13 %). Accordingly, the sex ratio is 95.59 males per 100 females. Annual average population growth rate is 0.92 percent in 2021.

Geographic coverage

National Level, Ecological belt, Urban and Rural, Province, District, Municipality, Ward Level

Analysis unit

The census results provide information up to the ward level (the lowest administrative level of Nepal), household and indivisual.

Universe

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

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f] and online

Research instrument

In this census three main questionnaires were developed for data collection. The first was the Listing Form deveoped mainly for capturing the basic household informatioin in each Enumeration area of the whole country. The second questionnaire was the main questionnaire with eight major Sections as mentioned hereunder.

Listing Questionaire Section 1. Introduction Section 2. House information Section 3. Household information Section 4. Agriculture and livestock information Section 5. Other information

Main Questionaire Section 1. Introduction Section 2. Household Information Section 3. Individual Information Section 4. Educational Information Section 5. Migration Section 6. Fertility Section 7.Disability Section 8. Economic Activity

For the first time, the NPHC, 2021 brougt a Community Questionnaire aiming at capturing the socio-economic and demographic characteristics of the Wards (the lowest administrative division under Rural/Urban Municipalities). The Community Questionnaire contains 6 Chapters. The information derived from community questionnaire is expected to validate (cross checks) certain information collected from main questionnaire.

Community questionaire Section 1. Introduction Section 2. Basic information of wards Section 3. Caste and mother tongue information Section 4. Current status of service within wards Section 5. Access of urban services and facilities within wards Section 6. Status of Disaster Risk

It is noteworty that the digital version of questionnare was applied in collecting data within the selected municipalities of Kathmandu Valley. Enumerators mobilized in Kathmandu Valley were well trained to use tablets. Besides, online mode of data collection was adpoted for all the Nepalese Diplomatic Agencies located abroad.

Cleaning operations

For the concistency of data required logics were set in the data entry programme. For the processing and analysis of data SPSS and STATA programme were employed.

According to latest figures, the Chinese population decreased by 1.39 million to around 1.408 billion people in 2024. After decades of rapid growth, China arrived at the turning point of its demographic development in 2022, which was earlier than expected. The annual population decrease is estimated to remain at moderate levels until around 2030 but to accelerate thereafter. Population development in China China had for a long time been the country with the largest population worldwide, but according to UN estimates, it has been overtaken by India in 2023. As the population in India is still growing, the country is very likely to remain being home of the largest population on earth in the near future. Due to several mechanisms put into place by the Chinese government as well as changing circumstances in the working and social environment of the Chinese people, population growth has subsided over the past decades, displaying an annual population growth rate of -0.1 percent in 2024. Nevertheless, compared to the world population in total, China held a share of about 17 percent of the overall global population in 2024. China's aging population In terms of demographic developments, the birth control efforts of the Chinese government had considerable effects on the demographic pyramid in China. Upon closer examination of the age distribution, a clear trend of an aging population becomes visible. In order to curb the negative effects of an aging population, the Chinese government abolished the one-child policy in 2015, which had been in effect since 1979, and introduced a three-child policy in May 2021. However, many Chinese parents nowadays are reluctant to have a second or third child, as is the case in most of the developed countries in the world. The number of births in China varied in the years following the abolishment of the one-child policy, but did not increase considerably. Among the reasons most prominent for parents not having more children are the rising living costs and costs for child care, growing work pressure, a growing trend towards self-realization and individualism, and changing social behaviors.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS (INS) - TUNISIA

The survey aims at estimating the demographic and educational characteristics of the population. It also calculates the economic indicators of the population such as the number of active individuals, the additional demand for jobs, the number of employed and their characteristics, the number of jobs created, the characteristics of the unemployed and the unemployment rate. Furthermore, this survey estimates these indicators on the household level and their living conditions.

The results of this survey were compared with the results of the second quarter of the national survey on population and employment 2011. It should also be noted that the National Institute of Statistics -Tunisia uses the unemployment definition and concepts adopted by the International Labour Organization. This definition implies that, the individual did not work during the week preceding the day of the interview, was looking for a job in the month preceding the date of the interview, is available to work within two weeks after the day of the interview.

In 2010, the National Institute of Statistics has adopted a strict ILO definition for unemployment, by conditioning that the person must perform effective approaches to search for a job in the month preceding the day of the interview.

Geographic coverage

Covering a representative sample at the national and regional level (governorates).

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

The sample is drawn from the frame of the 2004 General Census of Population and Housing.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three modules were designed for data collection:

• Household Questionnaire (Module 1): Includes questions regarding household characteristics, living conditions, individuals and their demographic, educational and economic characteristics. This module also provides information on internal and external migration.

• Active Employed Questionnaire (Module 2): Includes questions regarding the characteristics of the employed individuals as occupation, industry and wages for employees.

• Active Unemployed Questionnaire (Module 3): Includes questions regarding the characteristics of the unemployed as unemployment duration, the last occupation, activity, and the number of days worked during the last year...etc.

Cleaning operations

Harmonized Data

• SPSS software is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Agency.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
• A post-harmonization cleaning process is then conducted on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Brazil and the United States are the two most populous countries in the Americas today. In 1500, the year that Pedro Álvares Cabral made landfall in present-day Brazil and claimed it for the Portuguese crown, it is estimated that there were roughly one million people living in the region. Some estimates for the present-day United States give a population of two million in the year 1500, although estimates vary greatly. By 1820, the population of the U.S. was still roughly double that of Brazil, but rapid growth in the 19th century would see it grow 4.5 times larger by 1890, before the difference shrunk during the 20th century. In 2024, the U.S. has a population over 340 million people, making it the third most populous country in the world, while Brazil has a population of almost 218 million and is the sixth most populous. Looking to the future, population growth is expected to be lower in Brazil than in the U.S. in the coming decades, as Brazil's fertility rates are already lower, and migration rates into the United States will be much higher. Historical development The indigenous peoples of present-day Brazil and the U.S. were highly susceptible to diseases brought from the Old World; combined with mass displacement and violence, their population growth rates were generally low, therefore migration from Europe and the import of enslaved Africans drove population growth in both regions. In absolute numbers, more Europeans migrated to North America than Brazil, whereas more slaves were transported to Brazil than the U.S., but European migration to Brazil increased significantly in the early 1900s. The U.S. also underwent its demographic transition much earlier than in Brazil, therefore its peak period of population growth was almost a century earlier than Brazil. Impact of ethnicity The demographics of these countries are often compared, not only because of their size, location, and historical development, but also due to the role played by ethnicity. In the mid-1800s, these countries had the largest slave societies in the world, but a major difference between the two was the attitude towards interracial procreation. In Brazil, relationships between people of different ethnic groups were more common and less stigmatized than in the U.S., where anti-miscegenation laws prohibited interracial relationships in many states until the 1960s. Racial classification was also more rigid in the U.S., and those of mixed ethnicity were usually classified by their non-white background. In contrast, as Brazil has a higher degree of mixing between those of ethnic African, American, and European heritage, classification is less obvious, and factors such as physical appearance or societal background were often used to determine racial standing. For most of the 20th century, Brazil's government promoted the idea that race was a non-issue and that Brazil was racially harmonious, but most now acknowledge that this actually ignored inequality and hindered progress. Racial inequality has been a prevalent problem in both countries since their founding, and today, whites generally fare better in terms of education, income, political representation, and even life expectancy. Despite this adversity, significant progress has been made in recent decades, as public awareness of inequality has increased, and authorities in both countries have made steps to tackle disparities in areas such as education, housing, and employment.

Comprehensive demographic dataset for John Day, OR, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Abstract

The Republic of Sierra Leone is a small coastal West African country bordered by Guinea and Liberia. Sierra Leone has an area of 71,620 square kilometers (about 28,000 square miles). The country is divided into four major Administrative Areas namely, The Western Area, Northern Province, Southern Province and Eastern Province.

The Provinces are divided into twelve districts and the districts are divided into one hundred and forty nine chiefdoms. Western Area is divided into (Western Urban) Freetown and Western Rural Areas. Freetown is divided into wards.

There are five Physical Regions in Sierra Leone: (i) The Central Plains, (ii) The Northern Woodlands Savannah, (iii) The South Western Upland, (iv) The Western Coastal Swamps and (v) the Western Peninsula Upland Region.

The country is mountainous; about 50% of the terrain is covered by mountains including the Capital, Freetown. Agriculture is the main occupation for the people of Sierra Leone; especially rice farming in which about 60% of the people are engaged through the practice of shifting cultivation.

Sierra Leone has a tropical climate with two very different seasons - the Dry Season, traditionally from November to April and the Rainy Season from May to October with July and August being the wettest months of the year. In 2004, the census was taken in December.

BACKGROUND OF AND JUSTIFICATION FOR THE 2004 POPULATION AND HOUSING CENSUS

The first population count in Sierra Leone was undertaken in 1802 in what is now the Western Area. Subsequently, a number of population counts in various parts of the country were conducted. However, it was not until 1963 that the whole country was covered for the first time and, since then, censuses have been carried out at intervals ranging from 10 to 17 years.

The first full-scale modern Population Census, however, was that of April 1963. It was also the first post independence census and it was conducted with the expectation that a decennial census programme would be maintained. Due to various constraints, however, the next two censuses were conducted at eleven-year intervals in 1974 and 1985. Due to the war situation, a census was not conducted in 1995. The next Population Census was conducted in December 2004.

The 1985 census showed a total population of about 3.5 million. It was a de facto count with December 1, 2004 as the reference date. The topics covered in the census were: Relationship, sex, age, maternal orphan hood, birth place, nationality, place of residence, level of education, marital status, type of economic activity, occupation, industry, employment status, children ever born to women aged 10 years and above, particulars of most recent birth and housing conditions.

The census data was processed on a Wang Vs 80 mini-computer and data entry was done on 19 workstations.

The publication plan relating to the 1985 Census results proposed the following:

· The Preliminary Reports · National Statistical Tables · Summary Statistics on Settlements of 1000 or more people · Analytical Report · Report of Seminar on the use of census data

The provisional census results indicating a total population of 3,515,812 was announced in January 1986 and The Preliminary Report published in August 1986. Due to delay in the installation of the data processing equipments, however, there were delays in the production of the final statistical tables. Further, considerable time was spent investigating a significant difference (about 9 percent) between the provisional results and the total population figure of 3,222,901 obtained after the computer processing of the census returns. On the basis of the investigation, the Sierra Leone Government endorsed the 3, 515,812 as the total population of the 1985 Census.

Following the acceptance of the census results, a team of local consultants carried out the analysis of the census data on the following themes:

· The Land and The People · Population size, growth, age and sex structure · Education and Literacy · Employment and Labour Force · Nuptiality and Fertility · Mortality Levels and Differentials · Household and Dwelling Characteristics · The Census Operations

The following reports were published as a result of these consultant reports:

· Volume 1: Summary Results; May 1992 · Volume 2: National Dissemination Seminar Report; July1992 · Volume 3: Analytical Report, 1996

In addition to the published reports, census data including computer printout of tabulations were sent out to some Ministries, Departments and Agencies and various other data users such as the University of Sierra Leone.

Since the 1985 Population and Housing Census, a number of nation-wide surveys in the area of education, health, HIV/AIDS etc. have been conducted by the National Statistical Agency (formerly Central Statistics Office and now Statistics Sierra Leone) and other stakeholders: These include the following:

· Labour Force Survey (1988/89) · Survey on Household Expenditure and Household Economic Activities (1989/90) · Demographic and Social Monitoring Survey (1992) · National Nutrition Survey by the Ministry of Health and Sanitation with support from UNICEF (1989) · Multi Indicator Cluster Survey II with support from UNICEF (2000)

The National Population Commission (NPC) which was established in 1982 also used the 1985 Census data to adopt a “National Population Policy for Development Progress and Welfare” in August 1989. Even before the development of the National Population Policy, the first five-year Development Plan (1974 - 1979) had drawn attention to the “interactive role of population and development planning generally”.

Population data is therefore needed on a continuous basis for the formulation, implementation, monitoring and evaluation of the country's population programme and development planning. Thus, Population Censuses and Household Sample Surveys constituted the major sources of national population data in the country. The decennial Population Censuses and the Central Statistics Office/Statistics Sierra Leone inter-censual programme of household Surveys are therefore regarded as essential elements in the country's population programme and development plans.

The Population Censuses together with the related Enumeration Areas (EA) maps provide a sampling frame for the Household Sample Surveys. Therefore, the two data collection systems are considered complementary. Prior to the 2004 Census, the available EA maps were those prepared for the 1974 Census because it had been planned to update the EAs for the 1985 Census and some field work was initiated but due to time constraint and inadequate planning, the exercise could not be completed. Thus, the 1974 EA maps were used for the 1985 Census Enumeration and two or more enumerators assigned to each EA. This might have contributed to the suspected under-enumeration in the 1985 Census. Therefore, the cartographic exercise for the 2004 Census was thoroughly done.

The 2004 Population and Housing Census together with the cartographic work was, therefore, undertaken not only to maintain a regular census programme but also to provide a more accurate updated bench-mark population data as well as a geographic frame for inter-censual surveys and related statistical sample enquiries.

Please note that because of the difference in the methodology used in the censuses prior to 1963, the population totals of the country prior to 1963 can not be compared with the more recent censuses. The population totals for the period 1901 to 2004 were as follows:

· 1901 1,024,178 · 1911 1,400,132 · 1921 1,540,554 · 1931 1,768,480 · 1948 1,858,275 · 1963 2,180,355 · 1974 2,735,159 · 1985 3, 515,812 · 2004 4,976,871

THE OBJECTIVES OF THE 2004 POPULATION AND HOUSING CENSUS

The last census that was held in Sierra Leone was in 1985 and according to normal procedure, there should have been another census in 1995 but due the eleven-year war, it was not possible and the 1985 census data had become completely obsolete and needed to be updated. Therefore the main objectives of the 2004 population and Housing Census were: · To help ensure the availability of a time series of population data to support socio-economic development planning and population programmes as well as to contribute to the development of national capacity for statistical enquiries.

· Continue the regular pattern of the conduct of censuses in Sierra Leone as a continuing scheme of statistical data collection.

· Provide information on housing conditions in the country after the eleven-year war.

FUNDING AND IMPLEMENTATION STRATEGY

A census requires substantial financial, material and human resources. Because of the security situation in the country for the last eleven years, the Sierra Leone Government had to play a greater leadership role than it had in previous censuses as a confidence building measure so as to attract foreign Donors. The Sierra Leone Government demonstrated this by providing funding for the locality listing exercise, which started in January 2001. The Government of Sierra Leone also provided funds for the purchase of vehicles, office and data processing equipments needed for the start of cartographic field work.

Donors started coming on board after they were satisfied that the security situation had improved to the level that can justify their confidence. In the end, the project benefited from two major Donors, UNFPA whose support was mainly in the area of cartography, Geographic Information Systems (GIS) and capacity building at SSL and European Union who supported data collection, data processing, data analysis , evaluation and dissemination.
The objectives were expected to be realized through a number of interrelated activities, which were carried out in the

Comprehensive demographic dataset for Days Creek, OR, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

About this dataset

Context

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

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for John Day, OR, is 27.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for John Day, OR, is 28.9.
• Total dependency ratio for John Day, OR is 56.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for John Day, OR is 3.5.

Content

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

Age groups:

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

Variables / Data Columns

• Age Group: This column displays the age group for the John Day population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the John Day for the selected age group is shown in the following column.
• Population (Female): The female population in the John Day for the selected age group is shown in the following column.
• Total Population: The total population of the John Day for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for John Day Population by Age. You can refer the same here

Abstract

The primary mission of the 2006 Population and Housing Census (PHC) of Nigeria was to provide data for policy-making, evidence-based planning and good governance. The Government at all tiers, researchers, the academia, civil society organizations and the international agencies will find the sets of socio-demographic data useful in formulating developmental policies and planning. The 2006 data will certainly provide benchmarks for monitoring the Millennium Development Goals (MDGs). Enumeration in the 2006 PHC was conducted between March 21st and 27th 2006. It was designed to collect information on the quality of the population and housing, under the following broad categories: demographic and social, education, disability, household composition, economic activity, migration, housing and amenities, mortality and fertility. The results of the exercise are being released as per the Commission's Tabulation Plan which began with the release of the total enumerated persons by administrative areas in the country in the Official Gazette of the Federal Republic of Nigeria No.2, Vol 96 of February 2,2009 and followed with the release of Priority Tables that provide some detailed characteristics of the population of Nigeria by State and LGA.

Geographic coverage

National

Analysis unit

Individuals Households

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Census 2006 Processing: The Technology and Methodology:-

Unlike the data capture method used for the country’s previous censuses, where information from the census forms are typed into the computer system, data capture for census 2006 was carried out by OMR/OCR/ICR systems where questionnaires are scanned through high speed optical scanners. The choice of the scanning system was because it is faster and more accurate than the data keying method.

OMR/OCR/ICR Technology

Definition of terms

• OMR (Optical Mark Recognition) - This means the ability of the scanning machine to detect pencil marks made on the questionnaires by the Enumerators in accordance with the responses given by the respondents.
• OCR (Optical Character Recognition) - This means the ability of the scanning machine to recognize machine printed characters on the questionnaires.
• ICR (Intelligent Character Recognition) - This means the ability of the scanner to recognize characters hand written by the Enumerators in accordance with the responses given by the respondents.

Processing Procedures of Census 2006 at the DPCs:- Data processing took place in the Commission’s seven (7) Data Processing Centres located in different geographical zones in the country. There was absolute uniformity in the processing procedures in the seven DPCs.

(a) Questionnaire Retrieval/Archiving Questionnaires from the fields were taken directly from the Local Government Areas to designated DPCs. The forms on arrival at the DPCs were counted, archived and labeled. Retrieval of the questionnaires at the DPCs were carried out based on the EA frame received from the Cartography Department. Necessary Transmittal Forms are completed on receipt of the Forms at the DPCs. The Transmittal Forms are also used to keep track of questionnaires movement within the DPC.

(b) Forms Preparation The scanning machine has been designed to handle A4 size paper. And the Census form being twice that size has to be split into two through the dotted lines at the middle of the form. This forms preparation procedure is to get the questionnaires, for each Enumeration Areas (EAs), ready for scanning. There is a Batch Header to identify each batch.

(c) Scanning Each Batch on getting to the Scanning Room was placed on joggers (a vibrating machine)to properly align the forms, and get rid of dust or particles that might be on the forms.

The forms are thereafter fed into the scanner. There were security codes in form of bar codes on each questionnaire to identify its genuineness. There was electronic editing and coding for badly coded or poorly shaded questionnaires by the Data Editors. Torn, stained or mutilated forms are rejected by the scanner. These categories of forms were later manually keyed into the system.

Re-archiving of Scanned Forms:- Scanned forms were placed in their appropriate marked envelopes in batches, and thereafter returned to the Archiving Section for re-archiving.

Data Output from the Scanning Machine:- The OMR/OCR Software interprets the output from the scanner and translates it into an XML file from where it is further translated into the desired ASCII output that is compatible for use by the CSPro Package for further processing and tabulation.

Data back-up and transfer:- After being sure that the data are edited for each EA batch in an LGA, data then was exported to the SAN (Storage Area Network) of the Server. Two copies of images of the questionnaires for each EA copied to the LTO tapes as backup and then transferred to the Headquarters. The ASCII data files for each LGA are zipped and encrypted, and thereafter transfer to the Data Validation Unit (DVU) at the Headquarters in Abuja.

Data appraisal

Data collation and validation:- The Data Validation Unit at the Headquarters was responsible for collating these data into EAs, LGAs, States and National levels. The data are edited/validated for consistency errors and invalid entries. The Census and Survey Processing (CSPro) software is used for this process. The edited, and error free data are thereafter processed into desired tables.

Activities of the Data Validation unit (DVU):-

Decryption of each LGA Data File Concatenation/merging of Data Files Check each EA batch file for EA completeness within an LGA and State Check for File/Data Structure Check for Range and Invalid Data items Check for Blank and empty questionnaire Check for inter and intra record consistency Check for Skip Patterns Perform Data Validation and Imputation Generate Statistics Report of each function/activity Generate Statistical Tables on LGA, State and National levels.

Economically Active Population Survey: Employed population by type of working day, sex and age group. Absolute values and percentages. Quarterly. National.

No abstract provided

Original dataset title: Access: Proportion of the population consuming less than 2100 kcal per day (average of 2011-2013), National Statistics Committee 2013

Abstract

The population and housing census (PHC) is the unique source of reliable and comprehensive data about the size of population and also on major socio-economic & socio-demographic characteristics of the country. It provides data on geographic and administrative distribution of population and household in addition to the demographic and socio-economic characteristics of all the people in the country. Generally, it provides for comparing and projecting demographic data, social and economic characteristics, as well as household and housing conditions at all levels of the country’s administrative units and dimensions: national, regional, districts and localities. The data from the census is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various multi-sectorial development programs at the national and community levels. Data on all key variables namely area, household, population, economic activity, literacy and education, fertility and child survival, housing conditions and sanitation are collected and available in the census data. The 2021 PHC in Ghana had an overarching goal of generating updated demographic, social and economic data, housing characteristics and dwelling conditions to support national development planning activities.

Geographic coverage

National Coverage , Region , District

Analysis unit

• Individuals
• Households
• Emigrants
• Absentee population
• Mortality
• Type of residence (households and non household)

Universe

All persons who spent census night (midnight of 27th June 2021) in Ghana

Kind of data

Census/enumeration data [cen]

Sampling procedure

This 10% sample data for the 2021 PHC is representative at the district/subdistrict level and also by the urban rural classification.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

GSS developed two categories of instruments for the 2021 PHC: the listing form and the enumeration instruments. The listing form was only one, while the enumeration instruments comprised six questionnaires, designated as PHC 1A, PHC 1B, PHC 1C, PHC 1D, PHC 1E and PHC 1F. The PHC 1A was the most comprehensive with the others being its subsets.

1. Listing Form: The listing form was developed to collect data on type of structures, level of completion, whether occupied or vacant and use(s) of the structures. It was also used to collect information about the availability, number and types of toilet facilities in the structures. It was also used to capture the number of households in a structure, number of persons in households and the sex of the persons residing in the households if occupied. Finally, the listing form was used to capture data on non-household populations such as the population in institutions, floating population and sex of the non-household populations.

2. PHC 1A: The PHC 1A questionnaire was used to collect data from all households in the country. Primarily, it was used to capture household members and visitors who spent the Census Night in the dwelling of the household, and their relationship with the head of the household. It was also used to collect data on homeless households. Members of the households who were absent were enumerated at the place where they had spent the Census Night. The questionnaire was also used to collect the following household information: emigration; socio-demographic characteristics (sex, age, place of birth and enumeration, survival status of parents, literacy and education; economic activities; difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

3. PHC 1B: The PHC 1B questionnaire was used to collect data from persons in stable institutions comprising boarding houses, hostels and prisons who were present on Census Night. Other information that was captured with this instrument are socio-demographic characteristics, literacy and education, economic activities, difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

4. PHC 1C: The PHC 1C questionnaire was used to collect data from persons in “unstable” institutions such as hospitals and prayer camps who were present at these places on Census Night. The instrument was used to capture only the socio-demographic characteristics of individuals.

5. PHC 1D: The PHC 1D questionnaire was used to collect data from the floating population. This constitutes persons who were found at airports, seaports, lorry stations and similar locations waiting for or embarking on long-distance travel, as well as outdoor sleepers on Census Night. The instrument captured the socio-demographic information of individuals.

6. PHC 1E: All persons who spent the Census Night at hotels, motels and guest houses were enumerated using the PHC 1E. The content of the questionnaire was similar to that of the PHC 1D.

7. PHC 1F: The PHC 1F questionnaire was administered to diplomats in the country.

Cleaning operations

The Census data editing was implemented at three levels: 1. data editing by enumerators and supervisors during data collection 2. data editing was done at the regional level by the regional data quality monitors during data collection 3. Final data editing was done at the national level using the batch edits in CSPro and STATA Data editing and cleaning was mainly digital.

Response rate

100 percent

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error.

Usually resident population aged 1 year and over by usual residence 1 year before Census Day by Small Area. (Census 2022 Theme 2 Table 3 )Census 2022 table 2.3 is the population usually resident in Ireland by usual residence 1 year before Census Day. Details include population by usual residence 1 year before Census Day. Census 2022 theme 2 is Migration, Ethnicity, Religion and Foreign Languages. Census Small Areas are the lowest level of geography for the dissemination of Census data and typically contain between 50 and 200 dwellings. They are generally comprised of complete neighbourhoods or townlands and they nest within CSO Electoral Divisions. Census 2022 Small Areas have been redrawn to ensure they remain consistent with the principle of data protection and are relatively comparable in size. This redraw was necessary following changes in population size and distribution between 2016 and 2022 and was done by the CSO with support from Tailte Éireann. Small Areas were first published for Census 2011 following work undertaken by the National Institute of Regional and Spatial Analysis (NIRSA) on behalf of Tailte Éireann and in consultation with the CSO. Coordinate reference system: Irish Transverse Mercator (EPSG 2157). These boundaries are based on 20m generalised boundaries sourced from Tailte Éireann Open Data Portal. CSO Small Areas 2022

Table 1 provides the size of the 2008 population aged 15–49 y, adult population growth rate, and adult HIV incidence from Spectrum, which is populated with UN population data [27],[43],[44]. The years for the pre-scale-up male circumcision and adult HIV prevalence data are as follows: Botswana (2004) [30], Lesotho (2004) [9],[39], Malawi (2004) [40], Mozambique (2003) [35], Namibia (2007) [38], Nyanza Province, Kenya (2008/2009) [36], Rwanda (2005) [9],[34], South Africa (2008), Swaziland (2006/2007) [32], Tanzania (2007/2008) [42], Uganda (2004) [37], Zambia (2007) [31], and Zimbabwe (2005/2006) [33].

Financial overview and grant giving statistics of National Council On Pet Population Study And Policy

This study contains selected demographic, social, economic, public policy, and political comparative data for Switzerland, Canada, France, and Mexico for the decades of 1900-1960. Each dataset presents comparable data at the province or district level for each decade in the period. Various derived measures, such as percentages, ratios, and indices, constitute the bulk of these datasets. Data for Switzerland contain information for all cantons for each decennial year from 1900 to 1960. Variables describe population characteristics, such as the age of men and women, county and commune of origin, ratio of foreigners to Swiss, percentage of the population from other countries such as Germany, Austria and Lichtenstein, Italy, and France, the percentage of the population that were Protestants, Catholics, and Jews, births, deaths, infant mortality rates, persons per household, population density, the percentage of urban and agricultural population, marital status, marriages, divorces, professions, factory workers, and primary, secondary, and university students. Economic variables provide information on the number of corporations, factory workers, economic status, cultivated land, taxation and tax revenues, canton revenues and expenditures, federal subsidies, bankruptcies, bank account deposits, and taxable assets. Additional variables provide political information, such as national referenda returns, party votes cast in National Council elections, and seats in the cantonal legislature held by political groups such as the Peasants, Socialists, Democrats, Catholics, Radicals, and others. Data for Canada provide information for all provinces for the decades 1900-1960 on population characteristics, such as national origin, the net internal migration per 1,000 of native population, population density per square mile, the percentage of owner-occupied dwellings, the percentage of urban population, the percentage of change in population from preceding censuses, the percentage of illiterate population aged 5 years and older, and the median years of schooling. Economic variables provide information on per capita personal income, total provincial revenue and expenditure per capita, the percentage of the labor force employed in manufacturing and in agriculture, the average number of employees per manufacturing establishment, assessed value of real property per capita, the average number of acres per farm, highway and rural road mileage, transportation and communication, the number of telephones per 100 population, and the number of motor vehicles registered per 1,000 population. Additional variables on elections and votes are supplied as well. Data for France provide information for all departements for all legislative elections since 1936, the two presidential elections of 1965 and 1969, and several referenda held in the period since 1958. Social and economic data are provided for the years 1946, 1954, and 1962, while various policy data are presented for the period 1959-1962. Variables provide information on population characteristics, such as the percentages of population by age group, foreign-born, bachelors aged 20 to 59, divorced men aged 25 and older, elementary school students in private schools, elementary school students per million population from 1966 to 1967, the number of persons in household in 1962, infant mortality rates per million births, and the number of priests per 10,000 population in 1946. Economic variables focus on the Gross National Product (GNP), the revenue per capita per household, personal income per capita, income tax, the percentage of active population in industry, construction and public works, transportation, hotels, public administration, and other jobs, the percentage of skilled and unskilled industrial workers, the number of doctors per 10,000 population, the number of agricultural cooperatives in 1946, the average hectares per farm, the percentage of farms cultivated by the owner, tenants, and sharecroppers, the number of workhorses, cows, and oxen per 100 hectares of farmland in 1946, and the percentages of automobiles per 1,000 population, radios per 100 homes, and cinema seats per 1,000 population. Data are also provided on the percentage of Communists (PCF), Socialists, Radical Socialists, Conservatives, Gaullists, Moderates, Poujadists, Independents, Turnouts, and other political groups and p

United States US: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 1.500 % in 2016. This records an increase from the previous number of 1.200 % for 2013. United States US: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 1.000 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 1.500 % in 2016 and a record low of 0.700 % in 1991. United States US: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.