70 datasets found
  1. Total population of China 1980-2030

    • statista.com
    Updated Apr 23, 2025
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    Statista (2025). Total population of China 1980-2030 [Dataset]. https://www.statista.com/statistics/263765/total-population-of-china/
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    Dataset updated
    Apr 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    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.

  2. Population distribution by five-year age group in China 2023

    • statista.com
    Updated Nov 30, 2024
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    Statista (2024). Population distribution by five-year age group in China 2023 [Dataset]. https://www.statista.com/statistics/1101677/population-distribution-by-detailed-age-group-in-china/
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    Dataset updated
    Nov 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

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

  3. m

    Data for:Improved Population Mapping for China Using the 3D Build-ing,...

    • data.mendeley.com
    Updated Sep 4, 2024
    + more versions
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    Zhen Lei (2024). Data for:Improved Population Mapping for China Using the 3D Build-ing, Nighttime Light, Points-of-interest, and Land Use/Cover Data Within a Multiscale Geographically Weighted Regression Model [Dataset]. http://doi.org/10.17632/22xwh6ptk2.2
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    Dataset updated
    Sep 4, 2024
    Authors
    Zhen Lei
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    Auxiliary Data.gdb: Land_use: original land use data POI_name: interests-point-data from the Amap platform (name indicates category)

    New_gridded_population_dataset(.gdb): experimental result data, i.e., a gridded population map of mainland China with a resolution of 100 meters

    New_minus_WorldPop_PopulationResidual(.gdb): pixel-level residuals of the new gridded population dataset with the Worldpop dataset

    PopulationData_AdministrativeUnitLevel.gdb: Population_data_mainlandChina_level3: population data at the district and county level in mainland China Population_data_Name_level4_Table: township and street-level population data for provinces and municipalities

    POI_Correlation_Coefficient: Python script: programming implementation for selecting the optimal bandwidth for POI Zonal statistical output of POI kernel density values: summary of various POI kernel densities in residential areas of administrative units Summary of POI Pearson correlation coefficients: sum of Pearson's correlation coefficients for 13 types of POIs at a certain bandwidth

    Note: Due to the storage space limitation, 3D building, nighttime light, and WorldPop datasets have not been uploaded. To access these publicly available data, please visit the official website via the "Related links" at the bottom. In addition, we are not authorized to share data for the fourth level of administrative boundaries, so we only share the corresponding population data in tabular form.

  4. P

    The Chinese Longitudinal Healthy Longevity Survey (CLHLS)-Longitudinal...

    • opendata.pku.edu.cn
    bin, doc, pdf
    Updated Dec 28, 2016
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    Peking University Open Research Data Platform (2016). The Chinese Longitudinal Healthy Longevity Survey (CLHLS)-Longitudinal Data(1998-2014) [Dataset]. http://doi.org/10.18170/DVN/XRV2WN
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    doc(74240), bin(2595949), bin(323051), pdf(105444), bin(12054503)Available download formats
    Dataset updated
    Dec 28, 2016
    Dataset provided by
    Peking University Open Research Data Platform
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Chinese Longitudinal Healthy Longevity Survey (CLHLS) WELCOME! The Chinese Longitudinal Healthy Longevity Survey (CLHLS) has been supported by NIA/NIH grants R01 AG023627-01 (PI: Zeng Yi) (Grant name: Demographic Analysis of Healthy Longevity in China) and P01 AG 008761 (PI: Zeng Yi; Program Project Director: James W. Vaupel), awarded to Duke University, with Chinese matching support for personnel costs and some local expenses. UNFPA and the China Social Sciences Foundation provided additional support for expanding the 2002 CLHLS survey. The Max Planck Institute for Demographic Research has provided support for international training since the CLHLS 1998 baseline survey. Finally, in December 2004 the China Natural Sciences Foundation and the Hong Kong Research Grants Council (RGC) partnered with NIA/NIH, providing grants to partially support the CLHLS project. Until present, the CLHLS conducted face-to-face interviews with 8,959, 11,161, 20,421, 18,524 and 19,863 individuals in 1998, 2000, 20002, 2005, and 2008-09, respectively, using internationally compatible questionnaires. Among the approximately 80,000 interviews conducted in the five waves, 14,290 were with centenarians, 18,910 with nonagenarians, 20,743 with octogenarians, 14,416 with younger elders aged 65-79, and 10,569 with middle-age adults aged 35-64. At each wave, survivors were re-interviewed, and deceased interviewees were replaced with new participants. Data on mortality and health status before dying for the 17,721 elders aged 65-110 who died between waves were collected in interviews with a close family member of the deceased. The CLHLS has the largest sample of centenarians in the world according to a report in Science (see the report). Our general goal is to shed new light on a better understanding of the determinants of healthy longevity of human beings. We are compiling extensive data on a much larger population of the oldest-old aged 80-112 than has previously been studied, with a comparison group of younger elders aged 65-79. We propose to use innovative demographic and statistical methods to analyze longitudinal survey data. Our goal is to determine which factors, out of a large set of social, behavioral, biological, and environmental risk factors, play an important role in healthy longevity. The large population size, the focus on healthy longevity (rather than on a specific disease or disorder), the simultaneous consideration of various risk factors, and the use of analytical strategies based on demographic concepts make this an innovative demographic data collection and research project. Our specific objectives are as follows: Collect intensive individual interview data including health, disability, demographic, family, socioeconomic, and behavioral risk factors for mortality and healthy longevity. Follow up the oldest-old and the comparison group of the younger elders, as well as some of the elders’ adult children to ascertain changes in their health status, care needs and costs, and associated factors. We will also ascertain mortality and causes of death, as well as care needs, costs, and health/disability status before death. Analyze the collected data to estimate the impacts of social, behavioral, environmental, and biological risk factors that are determinants of healthy longevity and mortality in the oldest-old. Compare the findings with results from other studies of large populations at advanced age.

  5. World Health Survey 2003 - China

    • catalog.ihsn.org
    • apps.who.int
    • +2more
    Updated Mar 29, 2019
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    World Health Organization (WHO) (2019). World Health Survey 2003 - China [Dataset]. https://catalog.ihsn.org/catalog/2221
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    Dataset updated
    Mar 29, 2019
    Dataset provided by
    World Health Organizationhttps://who.int/
    Authors
    World Health Organization (WHO)
    Time period covered
    2003
    Area covered
    China
    Description

    Abstract

    Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

    The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

    The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

    The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

    Geographic coverage

    The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

    There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

    Analysis unit

    Households and individuals

    Universe

    The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

    If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

    The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    SAMPLING GUIDELINES FOR WHS

    Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

    The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

    The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

    All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

    STRATIFICATION

    Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

    Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

    Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

    MULTI-STAGE CLUSTER SELECTION

    A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

    In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

    In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

    It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

  6. f

    Growth and development in prefecture-level cities in China

    • plos.figshare.com
    pdf
    Updated May 30, 2023
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    Daniel Zünd; Luís M. A. Bettencourt (2023). Growth and development in prefecture-level cities in China [Dataset]. http://doi.org/10.1371/journal.pone.0221017
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    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Daniel Zünd; Luís M. A. Bettencourt
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    Nowhere has the scale and scope of urbanization been larger than in China over the last few decades. We analyze Chinese city development between the years 1996 and 2014 using data for the urbanized components of prefecture-level cities. We show that, despite much variability and fast economic and demographic change, China is undergoing transformations similar to the historical trajectory of other urban systems. We also show that the distinguishing signs of urban economies—superlinear scaling of agglomeration effects in economic productivity and economies of scale in land use—also characterize Chinese cities. We then analyze the structure of economic change in Chinese cities using a variety of metrics, characterizing employment, firms and households. Population size estimates remain a major challenge for Chinese cities, as official numbers are often reported based on the Hukou registration system. We use the information in the residuals to scaling relations for economic quantities to predict actual resident population and show that these estimates agree well with data for a subset of cities for which counts of total resident population exist. We conclude with a list of issues that must be better understood and measured to make sense of present urban development trajectories in China.

  7. A

    China, Hong Kong Special Administrative Region - Population Counts

    • data.amerigeoss.org
    geotiff
    Updated Jun 18, 2025
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    UN Humanitarian Data Exchange (2025). China, Hong Kong Special Administrative Region - Population Counts [Dataset]. https://data.amerigeoss.org/dataset/f839b006-c927-48c3-812b-d72201ef2558
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    geotiffAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    UN Humanitarian Data Exchange
    Area covered
    Hong Kong, China
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.


    Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App.
    The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively):

    - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
    - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
    - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019)
    -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019).
    -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets.
    -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020.
    -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019).

    Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent.

    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

  8. f

    DataSheet1_Increased populations will be exposed to the dangerous...

    • frontiersin.figshare.com
    docx
    Updated May 31, 2023
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    Huiwen Xu; Huopo Chen; Huijun Wang (2023). DataSheet1_Increased populations will be exposed to the dangerous precipitation extremes across China in the future.docx [Dataset]. http://doi.org/10.3389/feart.2022.963042.s001
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    docxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Frontiers
    Authors
    Huiwen Xu; Huopo Chen; Huijun Wang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    This study investigates the future changes in dangerous precipitation extremes with multiyear return periods and the population exposure across China at the 1.5–4°C warming levels via the latest simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results show that the simulations project more frequent dangerous precipitation extremes across China under the warmer climate regardless of the shared socioeconomic pathway (SSP), with more substantial occurrence increases at the high warming levels. Consequently, the population exposure to dangerous precipitation extremes is anticipated to increase persistently in most regions of China except for some parts of northwestern China and the Tibetan Plateau. For the events estimated to occur once every 10 years, the 1.5, 2.0, 3.0, and 4.0°C warming relative to the current state will result in approximately 29.9, 47.8, 72.9, and 84.3% increases in the aggregated population exposure over China under the SSP5-8.5 scenario, respectively. However, the exposure change is somewhat subject to the emission scenarios, with larger proportional increases under the regional-rivalry scenario of SSP3-7.0 compared to the fossil-fueled development scenario of SSP5-8.5. The increased exposure under all the scenarios is primarily attributed to the climate change factor, and the population change and their interaction component make a minor contribution. Furthermore, compared to the 2.0°C warmer climate, the 0.5°C less warming under the 1.5°C climate can trigger remarkable decreases of 16.5–20.8% for exposure to once-in-decade events over China. Additionally, the changes in the occurrence and exposure are much larger for the rarer events. Hence, our analyses indicate that limiting warming to 1.5°C is beneficial to reducing the impacts associated with precipitation extremes across China, particularly for the more extreme events.

  9. H

    China - Age and gender structures

    • data.humdata.org
    geotiff
    Updated Jul 30, 2025
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    WorldPop (2025). China - Age and gender structures [Dataset]. https://data.humdata.org/dataset/a92c2069-e79f-4094-9045-df862c7e9c67?force_layout=desktop
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    geotiffAvailable download formats
    Dataset updated
    Jul 30, 2025
    Dataset provided by
    WorldPop
    Area covered
    China
    Description

    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

    A description of the modelling methods used for age and gender structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/gender structure proportion datasets here.
    Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
    The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
    Data for earlier dates is available directly from WorldPop.

    WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

  10. e

    Life Story Interviews With Russian-Speaking Marriage Migrants in China,...

    • b2find.eudat.eu
    Updated Oct 30, 2023
    + more versions
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    (2023). Life Story Interviews With Russian-Speaking Marriage Migrants in China, 2015-2018 - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/3ebf64c7-526d-5c28-aba5-08dcba22f45e
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    Dataset updated
    Oct 30, 2023
    Area covered
    China
    Description

    This data collection includes 'life story' interviews with Russian-speaking women from Russia, Ukraine, and Belarus who have married Chinese citizens and moved for their married lives to the People's Republic of China. Most of the recorded interviews were transcribed verbatim in Russian. Some of the non-recorded conversations are summarised in English. The topics covered in the interviews include the women's journeys to China, their experiences of family, social, and working lives, the challenges of legal, socio-cultural and emotional adaptation, and the questions of citizenship and immigration status for women and their children.The growth of mega-cities and more generally rapid urbanization in China not only include hundreds of millions internal migrants, but an increasing number of foreign (including Taiwanese and returning ethnic Chinese) migrants as well. At present, foreign migrants fill relatively small and specific skills and knowledge gaps, but also include marriage migrants, traders, investors, retirees and unskilled workers. However as China's population growth levels off, population ageing sets in. China's working age population is set to decline, slowly at first but increasingly rapidly, especially roughly after 2025. Moreover, the population's sex imbalance will become ever more pronounced and China will face an increasing shortage of marriageable and working age people. Although international migration is set to make an important contribution to these increasing demographic and labour market shortages in China, little research has as yet been done. Our project will provide estimates and projections of the role of international and internal migration on population dynamics in China. The central focus of our project is on the impact of the second demographic transition in China, including family changes, ageing, migration and regional population changes. We will collect vital data on the interaction between labour markets and population dynamics, the consequences of migration, integration policies in China, EU-China mobility, and shifting patterns of inequality and the cultural division of labour. The project therefore speaks directly to the issues under the theme Understanding Population Change of the Europe - China call for collaborative research. This research data collection includes the transcripts of life story interviews with Russian-speaking women from the Soviet Union who have married a Chinese national and moved for a family life to the People's Republic of China. The research participants for this project were recruited through a snowballing method. A written call for participation and project information were distributed through established contacts and social media, inviting interested parties to contact the researcher. A consent form with the project information was shared with prospective participants prior to the interview. The interviews took place face-to-face or through a video or audio function in Skype or in Wechat, China's most popular social media platform.

  11. Labor force in China 2000-2023

    • statista.com
    Updated Nov 6, 2024
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    Statista (2024). Labor force in China 2000-2023 [Dataset]. https://www.statista.com/statistics/282134/china-labor-force/
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    Dataset updated
    Nov 6, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2023, China's labor force amounted to approximately 772.2 million people. The labor force in China indicated a general decreasing trend in recent years. As both the size of the population in working age and the share of the population participating in the labor market are declining, this downward trend will most likely persist in the foreseeable future. A country’s labor force is defined as the total number of employable people and incorporates both the employed and the unemployed population. Population challenges for China One of the reasons for the shrinking labor force is the Chinese one-child policy, which had been in effect for nearly 40 years, until it was revoked in 2016. The controversial policy was intended to improve people’s living standards and optimize resource distribution through controlling the size of China’s expanding population. Nonetheless, the policy also led to negative impacts on the labor market, pension system and other societal aspects. Today, China is becoming an aging society. The increase of elderly people and the lack of young people will become a big challenge for China in this century. Employment in China Despite the slowing down of economic growth, China’s unemployment rate has sustained a relatively low rate. Complete production chains and a well-educated labor force make China’s labor market one of the most attractive in the world. Working conditions and salaries in China have also improved significantly over the past years. Due to China’s leading position in terms of talent in the technology industry, the country is now attracting investment from some of the world’s leading companies in the high-tech sector.

  12. Multi Country Study Survey 2000-2001 - China

    • dev.ihsn.org
    • apps.who.int
    • +1more
    Updated Apr 25, 2019
    + more versions
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    World Health Organization (WHO) (2019). Multi Country Study Survey 2000-2001 - China [Dataset]. https://dev.ihsn.org/nada/catalog/study/CHN_2000_MCSSL_v01_M
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    Dataset updated
    Apr 25, 2019
    Dataset provided by
    World Health Organizationhttps://who.int/
    Authors
    World Health Organization (WHO)
    Time period covered
    2000 - 2001
    Area covered
    China
    Description

    Abstract

    In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

    The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

    Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

    The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

    The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

    This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A nationally representative sample of male and female adults age 18+ was used. Three provinces from 3 economic levels were sampled as follows: Shandong (high), Henan (middle), Gansu (low).

    5,000 people in Shandong, 3,000 in Henan and 2,000 in Gansu were sampled. From the sample, 53.2% males vs. 46.8% females were interviewed.

    In each province 33.7% of the respondents were interviewed in urban area, and 66.3% in rural area. According to the economic level of each province, 3-6 counties were chosen randomly. Respondents were selected randomly according to their household number.

    Missing rates were quite low, as respondents generally tended to cooperate. Illiterate respondents found some questions were too difficult (health state valuations, HSR ranking, calibration tests). Interviews were also too long and the average time for one interview was at least 2 hours if the respondent had little education.

    Mode of data collection

    Face-to-face [f2f]

    Cleaning operations

    Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

    Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

    The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

    In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

    Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

    Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

    Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

  13. Covid-19 Highest City Population Density

    • kaggle.com
    Updated Mar 25, 2020
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    lookfwd (2020). Covid-19 Highest City Population Density [Dataset]. https://www.kaggle.com/lookfwd/covid19highestcitypopulationdensity/tasks
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 25, 2020
    Dataset provided by
    Kaggle
    Authors
    lookfwd
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    This is a dataset of the most highly populated city (if applicable) in a form easy to join with the COVID19 Global Forecasting (Week 1) dataset. You can see how to use it in this kernel

    Content

    There are four columns. The first two correspond to the columns from the original COVID19 Global Forecasting (Week 1) dataset. The other two is the highest population density, at city level, for the given country/state. Note that some countries are very small and in those cases the population density reflects the entire country. Since the original dataset has a few cruise ships as well, I've added them there.

    Acknowledgements

    Thanks a lot to Kaggle for this competition that gave me the opportunity to look closely at some data and understand this problem better.

    Inspiration

    Summary: I believe that the square root of the population density should relate to the logistic growth factor of the SIR model. I think the SEIR model isn't applicable due to any intervention being too late for a fast-spreading virus like this, especially in places with dense populations.

    After playing with the data provided in COVID19 Global Forecasting (Week 1) (and everything else online or media) a bit, one thing becomes clear. They have nothing to do with epidemiology. They reflect sociopolitical characteristics of a country/state and, more specifically, the reactivity and attitude towards testing.

    The testing method used (PCR tests) means that what we measure could potentially be a proxy for the number of people infected during the last 3 weeks, i.e the growth (with lag). It's not how many people have been infected and recovered. Antibody or serology tests would measure that, and by using them, we could go back to normality faster... but those will arrive too late. Way earlier, China will have experimentally shown that it's safe to go back to normal as soon as your number of newly infected per day is close to zero.

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F197482%2F429e0fdd7f1ce86eba882857ac7a735e%2Fcovid-summary.png?generation=1585072438685236&alt=media" alt="">

    My view, as a person living in NYC, about this virus, is that by the time governments react to media pressure, to lockdown or even test, it's too late. In dense areas, everyone susceptible has already amble opportunities to be infected. Especially for a virus with 5-14 days lag between infections and symptoms, a period during which hosts spread it all over on subway, the conditions are hopeless. Active populations have already been exposed, mostly asymptomatic and recovered. Sensitive/older populations are more self-isolated/careful in affluent societies (maybe this isn't the case in North Italy). As the virus finishes exploring the active population, it starts penetrating the more isolated ones. At this point in time, the first fatalities happen. Then testing starts. Then the media and the lockdown. Lockdown seems overly effective because it coincides with the tail of the disease spread. It helps slow down the virus exploring the long-tail of sensitive population, and we should all contribute by doing it, but it doesn't cause the end of the disease. If it did, then as soon as people were back in the streets (see China), there would be repeated outbreaks.

    Smart politicians will test a lot because it will make their condition look worse. It helps them demand more resources. At the same time, they will have a low rate of fatalities due to large denominator. They can take credit for managing well a disproportionally major crisis - in contrast to people who didn't test.

    We were lucky this time. We, Westerners, have woken up to the potential of a pandemic. I'm sure we will give further resources for prevention. Additionally, we will be more open-minded, helping politicians to have more direct responses. We will also require them to be more responsible in their messages and reactions.

  14. w

    Global Financial Inclusion (Global Findex) Database 2021 - China

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Dec 16, 2022
    + more versions
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    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - China [Dataset]. https://microdata.worldbank.org/index.php/catalog/4627
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    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021 - 2022
    Area covered
    China
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    Tibet was excluded from the sample. The excluded areas represent less than 1 percent of the total population of China.

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for China is 3500.

    Mode of data collection

    Mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  15. G

    Percent of world population by country, around the world |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Mar 21, 2016
    + more versions
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    Globalen LLC (2016). Percent of world population by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/population_share/
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    csv, xml, excelAvailable download formats
    Dataset updated
    Mar 21, 2016
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    World, World
    Description

    The average for 2023 based on 196 countries was 0.51 percent. The highest value was in India: 17.94 percent and the lowest value was in Andorra: 0 percent. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

  16. f

    Data_Sheet_2_People's knowledge, attitudes, practice, and healthcare...

    • figshare.com
    docx
    Updated Jul 13, 2023
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    Zhongjing Pan; Tianpei Ma; Qinghan Zeng; Ting Xu; Qiong Ran; Tianming Li; Dan Lu (2023). Data_Sheet_2_People's knowledge, attitudes, practice, and healthcare education demand regarding OSA: a cross-sectional study among Chinese general populations.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2023.1128334.s002
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    docxAvailable download formats
    Dataset updated
    Jul 13, 2023
    Dataset provided by
    Frontiers
    Authors
    Zhongjing Pan; Tianpei Ma; Qinghan Zeng; Ting Xu; Qiong Ran; Tianming Li; Dan Lu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundPopulation knowledge and attitudes toward obstructive sleep apnea (OSA) syndrome are critical to public health initiatives to overcome the disease. Healthcare education is an appropriate approach to expediting the process to build active medical practice models in the public.ObjectiveThis study aimed to assess the level of knowledge, attitude, and practice (KAP) regarding OSA and healthcare education demand among the Chinese general population.MethodsA cross-sectional survey was performed online via Wenjuanxing in China between 8 February and 8 March 2022, using a 34-item questionnaire designed and reviewed by multidisciplinary experts.ResultsThis study enrolled 1507 respondents, aged 18 to 68, with a city-to-countryside ratio of approximately 2:1. Four-fifths of respondents reported that they had children (n = 1237), and mothers accounted for 57.7%. If they or their children had symptoms of OSA, nearly nine in 10 respondents would undertake positive medical practices, especially parents. A total of 89.4% of the respondents reported a desire to receive healthcare education through the new multimedia approach, and most were concerned about the etiology of OSA.ConclusionThe current study indicated that even the higher educated and urban populations in China had insufficient knowledge about positive attitudes toward and practices regarding OSA, indicating an urgent demand for healthcare education. A special emphasis should be placed on appropriating population demand for healthcare education and promoting the benefits of active medical practice models in sleep medicine.

  17. H

    Hong Kong SAR, China Domestic Household: Over HKD 30000: Wan Chai

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Hong Kong SAR, China Domestic Household: Over HKD 30000: Wan Chai [Dataset]. https://www.ceicdata.com/en/hong-kong/population-domestic-household-monthly-household-income-district-council-district/domestic-household-over-hkd-30000-wan-chai
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2006 - Dec 1, 2017
    Area covered
    Hong Kong
    Description

    Hong Kong Domestic Household: Over HKD 30000: Wan Chai data was reported at 41,800.000 Person in 2017. This records an increase from the previous number of 40,600.000 Person for 2016. Hong Kong Domestic Household: Over HKD 30000: Wan Chai data is updated yearly, averaging 28,500.000 Person from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 41,800.000 Person in 2017 and a record low of 22,500.000 Person in 2004. Hong Kong Domestic Household: Over HKD 30000: Wan Chai data remains active status in CEIC and is reported by Census and Statistics Department. The data is categorized under Global Database’s Hong Kong SAR – Table HK.G008: Population: Domestic Household: Monthly Household Income: District Council District.

  18. i

    World Values Survey 2005, Wave 5 - Hong Kong SAR, China

    • datacatalog.ihsn.org
    Updated Jan 16, 2021
    + more versions
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    Dr. Ng Chun Hung (2021). World Values Survey 2005, Wave 5 - Hong Kong SAR, China [Dataset]. https://datacatalog.ihsn.org/catalog/8959
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    Dataset updated
    Jan 16, 2021
    Dataset authored and provided by
    Dr. Ng Chun Hung
    Time period covered
    2005
    Area covered
    Hong Kong
    Description

    Abstract

    The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

    Geographic coverage

    The survey covers Hong Kong

    Analysis unit

    • Household
    • Individual

    Universe

    The WVS for Hong Kong covers national population, aged 18 years and over, for both sexes.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    1. The sample for the survey was selected from the Frame of Quarters maintained by the Census & Statistics Department. This frame is the most complete and up-to-date register of residential addresses in Hong Kong. It is updated by administrative returns on buildings constructed or demolished, and regularly surveys conducted by the Census & Statistics Department. For practical purposes, addresses in very remote areas will not be sampled.

    2. A two-stage stratified sample design was adopted in the survey, with the records in the frame of quarters first stratified by geographical area and type of quarters. Sampling units were selected using systematic replicated sampling technique with fixed sampling intervals and non-repetitive random numbers. The use of replicated sampling is to facilitate the calculation of sampling errors and any subsequent adjustments to the sample size, if required.

    3. In the first stage, a random sample of 2,000 living quarters was selected from the Frame of Quarters. For the second stage, a person aged 18 and above was randomly selected from each household in the addresses sampled. To ensure unbiased and random selection, the usual sampling method called birthday method was used. Research conducted in the US shows that the birthday method is better than the Kish grid method in soliciting the cooperation of the respondents, as the method is less intrusive than the Kish grid method.

    Remarks about sampling: Birthday method was used to identify a respondent. STRATIFICATION FACTORS USED: By geographical area and type of quarters in Hong Kong.

    The sample size for Hong Kong is N=1252 and includes the national population aged 18 years and over for both sexes.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    To test the questionnaire and the fieldwork arrangement, a pilot survey was conducted in around end December 2004 on an effective sample of 16 respondents aged 18 and over. We pre-tested with a more complete version of the 2000 questionnaire. Respondents found the questionnaire rather lengthy and showed depleting motivation to complete the survey. We deleted some questions that were deemed too taxing (e.g. V145A to 145F) and some seen as not quite relevant to the local context (e.g. V177 to V181, V197 to V203). The resultant questionnaire is much based on the earlier versions used in the Mainland China and Taiwan survey, with some additions and variations to suit the Hong Kong context. A multi-wave, multi-contact approach2, which aimed at increasing the proportion of respondents who were willing to co-operate in the survey and the chance of contacting the households, was adopted in data collection. This approach is briefly summarized below: Before data collection:

    a) Before the interview took place, a notification letter was sent to the living quarters sampled, about a week before the start of data collection, explaining the purposes of the survey and re-assuring the respondents that data collected in the survey will be kept strictly confidential;

    b) An enquiry hotline telephone number and a contact person was also included to enable the respondents to clarify any questions they may have on the survey, or to make appointment on the preferred survey time;

    During data collection:

    c) To facilitate verification of identity of the interviewers, the interviewers brought along with them their interviewer identity card issued by Policy 21 Ltd. of the University of Hong Kong. If in doubt, the respondents could call Policy 21 hotline to re-confirm the identity of interviewers. If the respondents were not free for an interview, the interviewers would make an appointment to come back at a time convenient to the householders;

    d) If the respondents sampled were not present in the household, which was not uncommon, the interviewers would call back at another time. The interviewers were required to make at least 5 call backs, if the first visit was not successful, at different times of the day and different days of the week, to minimize non-contact. Very often, an interviewer had to call 3 4 times in order to complete on successful interview;

    e) In case a refusal was encountered, the fieldwork managers would take over the case. The manager usually would re-assign the case to another interviewer. Occasionally, he/she would accompany the interviewer to make a second attempt. Depending on individual circumstances, sometimes the field managers would take over the case. This arrangement had helped for quality control purposes and in minimizing non-response.

    Response rate

    Response rate: 2000 A Total issued 233 B Not eligible (ill, dead, non-English speaking, not at this address) 1767 C Total eligible 1252 D Total questionnaires received 233 E - non-responses (including non-contact; see note above under sample type) 282 F Refusals (including questionnaires less than half filled in) 0 G Non-contact (included in E) 0 H Other non-response (included in E)

    Remarks about non-response: Data collection was carried out during the period from March to May 2005. A total of 1,252 respondents aged 18 and above were successfully interviewed faceto-face, and the response rate in the survey was 71%. The non-contact rate is 13%. The refusal rate is 16%.

  19. f

    Establishing a reference interval for serum anti-dsDNA antibody: A large...

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Feb 2, 2017
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    Wu, Ziyan; Deng, Chuiwen; Zhang, Shulan; Li, Jing; Li, Ping; Chen, Si; Li, Yongzhe; Zhang, Fengchun; Hu, Chaojun; Li, Liubing (2017). Establishing a reference interval for serum anti-dsDNA antibody: A large Chinese Han population-based multi-center study [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001794165
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    Dataset updated
    Feb 2, 2017
    Authors
    Wu, Ziyan; Deng, Chuiwen; Zhang, Shulan; Li, Jing; Li, Ping; Chen, Si; Li, Yongzhe; Zhang, Fengchun; Hu, Chaojun; Li, Liubing
    Description

    BackgroundA reference interval (RI) for the circulating concentration of anti-dsDNA antibody is essential for clinicians to interpret laboratory results and make clinical decisions. Therefore, we aimed to establish the RI for anti-dsDNA antibody in the Chinese Han population.MethodsThis study was designed and carried out in accordance with guideline C28-A3, which is proposed by the International Federation of Clinical Chemistry and the Clinical and Laboratory Standards Institute. A total of 2,880 apparently healthy individuals were enrolled using a posteriori sampling. These individuals were recruited from four hospitals, representing the Han populations of north, south, east, and west China. Serum anti-dsDNA antibody levels were measured using the three analytical systems AESKU, EUROIMMUNE, and INOVA, which are the most commonly used systems in China. Individuals were stratified by gender, age, and region, and the RIs were obtained by nonparametric methods.ResultsGender-specific RIs for serum anti-dsDNA antibody in the Chinese Han population were established.ConclusionThis is the first exploration of the RI for anti-dsDNA antibody in the Chinese Han population. We have established gender-specific RIs for each assay method commonly used in China.

  20. Data from: Conservation genetics of native and European-introduced Chinese...

    • zenodo.org
    • datadryad.org
    bin, txt
    Updated Jun 2, 2022
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    Vincent Savolainen; Vincent Savolainen (2022). Conservation genetics of native and European-introduced Chinese Water Deer (Hydropotes inermis) [Dataset]. http://doi.org/10.5061/dryad.kd51c5b2f
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    bin, txtAvailable download formats
    Dataset updated
    Jun 2, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Vincent Savolainen; Vincent Savolainen
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The Chinese water deer (Hydropotes inermis) belongs to a relatively early-divergence lineage of Cervidae and is thought to have retained some ancestral features of the group. This species is classified as Vulnerable on the IUCN Red List (accessed 2020), and populations in its native range have declined drastically in recent years. However, a number of individuals were introduced to the UK about a century ago; these have flourished and now make up over 40% of global numbers. To infer the population genetic structure and genetic diversity of Chinese water deer both in their native China and in populations introduced to the UK and France, mitochondrial DNA sequence variation was investigated (control region and cytochrome B) for near 100 individuals. The distribution of haplotypes among the regions shows distinct geographic structure, and only one cytochrome B haplotype was common to both China and European populations. Our results reveal lower levels of genetic diversity in the British populations, differentiation between native and introduced populations, and that the source population of British deer is likely to be extinct. Some recommendations are made for the conservation of different populations.

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Statista (2025). Total population of China 1980-2030 [Dataset]. https://www.statista.com/statistics/263765/total-population-of-china/
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Total population of China 1980-2030

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32 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
China
Description

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.

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