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.

Key information about China population

• The China population reached 1,408.3 million people in Dec 2024, compared with the previously reported figure of 1,409.7 million people in Dec 2023
• The data reached an all-time high of 1,412.6 million people in Dec 2021 and a record low of 541.7 million people in Dec 1949

• In the latest reports, China Unemployment Rate increased to 5.1 % in Sep 2024
• Monthly earnings of the China population was 1,392.5 USD in Dec 2023
• China Labour Force Participation Rate dropped to 66.4 % in Dec 2023

In 2024, about 60.9 percent of the Chinese population was between 16 and 59 years old. Apart from the information given on broad age groups in this statistic, some more information is provided by a timeline for the age distribution and a population breakdown by smaller age groups. Demographic development in China China ranked as the second most populous country in the world with a population of nearly 1.41 billion as of mid 2024, surpassed only by India. As the world population reached more than eight billion in mid 2024, China represented almost one fifth of the global population. China's population increased exponentially between the 1950s and the early 1980s due to Mao Zedong's population policy. To tackle the problem of overpopulation, a one-child policy was implemented in 1979. Since then, China's population growth has slowed from more than two percent per annum in the 1970s to around 0.5 percent per annum in the 2000s, and finally turned negative in 2022. China's aging population One outcome of the strict population policy is the acceleration of demographic aging trends. According to the United Nations, China's population median age has more than doubled over the last five decades, from 18 years in 1970 to 37.5 years in 2020. Few countries have aged faster than China. The dramatic aging of the population is matched by slower growth. The total fertility rate, measuring the number of children a woman can expect to have in her life, stood at just around 1.2 children. This incremental decline in labor force could lead to future challenges for the Chinese government, causing instability in current health care and social insurance mechanisms. To learn more about demographic development of the rural and urban population in China, please take a look at our reports on population in China and aging population in China.

A survey conducted in January 2022 concluded that more than eight out of ten people in China received their health-related knowledge and information through articles published by official accounts of WeChat. Half of the respondents also used health apps, online forums, and websites as a reliable source of information, while only *** in **** chose to ask doctors online their health-related questions.

Key information about Hong Kong SAR (China) population

• The Hong Kong SAR (China) population reached 7.5 million people in Dec 2024, compared with the previously reported figure of 7.5 million people in Dec 2023
• The data reached an all-time high of 7.5 million people in Dec 2024 and a record low of 3.2 million people in Dec 1961

• In the latest reports, Hong Kong SAR (China) Unemployment Rate remained the same at 3.1 % in Jan 2025
• Monthly earnings of the Hong Kong SAR (China) population was 2,426.6 USD in Sep 2024
• Hong Kong SAR (China) Labour Force Participation Rate remained the same rate at 56.9 % in Jan 2025

Key information about Macau SAR (China) population

• The Macau SAR (China) population reached 0.7 million people in Dec 2024, compared with the previously reported figure of 0.7 million people in Dec 2023
• The data reached an all-time high of 0.7 million people in Dec 2024 and a record low of 0.2 million people in Dec 1960

• In the latest reports, Macau SAR (China) Unemployment Rate dropped to 1.6 % in Jan 2025
• Monthly earnings of the Macau SAR (China) population was 2,240.8 USD in Sep 2024
• Macau SAR (China) Labour Force Participation Rate dropped to 67.2 % in Jan 2025

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Notes:Variants No.1 to 83 were found in deaf patients.Variants No.84 and 86 labeled with * were carried by hearing normal controls;Mutational allele frequency: the number of mutant alleles/the number of total mutant alleles;FS:frameshift.

Notes from product: II. Notes on China 2000 and 2010 Population Census Data In order to guide you to use the data correctly, provide you some explanations as follows: (l) Census time: 0:00AM of November 1, 2000 and 2010 as the reference time for the census. (2) The 2000 and 2010 population census covered all persons who hold the nationality of, and have permanent residing place in the People's Republic of China. During the census, each person was enumerated in his/her permanent residing place. The following persons should be enumerated in their permanent residing place: a) Those who reside in the townships, towns and street communities and have their permanent household registration there. b) Those who have resided in the townships, towns and street communities for more than 6 months but the places of their permanent household registration are elsewhere. c) Those who have resided in the townships, towns and street communities for less than 6 months but have been away from the place of their permanent household registration for more than 6 months. d) Those who live in the townships, towns and street communities during the population census while the places of their household registration have not yet settled. e) Those who used to live in the townships, towns and street communities but are working or studying abroad during the census and have no Permanent household registration for the time being. (3) Two types of questionnaires (long form and short form) were used for the 2000 and 2010 population census. The short form contains items that reflect the basic situation of the population, while the long form include all short form items plus other items such as migration, education, economic activities, marriage and family, fertility , housing , etc. . According to the National Bureau of Statistics of China, the households for the Long Form survey were selected by a random sampling program. The data included in this product are from 100% Short Form survey.(4) Results in this publication are based on the processing of data directly from enumeration without any adjustment. It is therefore worthwhile to notice the following: a. Data in the publication do not include population not enumerated in the Census. b. Data in the publication do not include the servicemen of the People's Liberation Army. c. The post-enumeration sample survey indicates an undercount of 1.81% in 2000 Census and 0.12% in 2010 Census. III. Notes on the China Province GIS Maps for the 2000 and 2010 Population Census Data (1) The China Province GIS map were developed for the 2000 and 2010 population Census data, which covered all 31 municipalities, provinces and autonomous regions of China, except for Taiwan, Hong Kong and Macao. (2) The population data came from the 5th and 6th China Population Census surveyed in 2000 and 2010. The GIS data is based on the national digital map (1:1 million) developed by the National Geographic Information Center of China (NGCC), including rives, roads, residential area and administrative boundaries.(3) The China province GIS maps are developed for matching 2000 and 2010 China population Census data, which should only be used as references for research or education instead of used as official maps. The distributor is not responsible for the accuracy of the those maps if the maps are used for business or other purposes.

Knowledge of adequate diets can improve an individual's health status. Although previous studies have identified the main resources from which Chinese people acquire dietary knowledge, it is still unclear whether information sources regarding diets (ISRDs) can increase individuals' knowledge of adequate diets (KAD) and which ISRDs are most effective in conveying KAD to the Chinese population. In this study, we interviewed 4,710 residents in Eastern China regarding their ISRDs and KAD. Descriptive statistics, ANOVA, and multivariate linear regression were used to analyze the effectiveness of different ISRDs in transmitting KAD to Chinese individuals and to determine the relationship between ISRDs and KAD. Results showed that the KAD scores of the respondents were low overall in Eastern China. Providing dietary information through expert lectures, books, newspapers, magazines, and social media could significantly improve the average KAD score of Chinese individuals. Respondents with a greater number of ISRDs were more likely to have higher KAD scores. These findings suggest that the number of ISRDs should be increased. In particular, emphasis should be placed on the role of expert lectures, books, newspapers, magazines, and social media.

DVD of geospatial datasets containing 2010 census data at the township level, as well as administrative boundaries, hydrography, railways, and roads. Consult metadata for list of variables and projection parameters.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Open and free data for assessing the human presence on the planet.

The Global Human Settlement Layer (GHSL) project produces global spatial information, evidence-based analytics, and knowledge describing the human presence on the planet. The GHSL relies on the design and implementation of spatial data processing technologies that allow automatic data analytics and information extraction from large amounts of heterogeneous geospatial data including global, fine-scale satellite image data streams, census data, and crowd sourced or volunteered geographic information sources.

The JRC, together with the Directorate-General for Regional and Urban Policy (DG REGIO) and Directorate-General for Defence Industry and Space (DG DEFIS) are working towards a regular and operational monitoring of global built-up and population based on the processing of Sentinel Earth Observation data produced by European Copernicus space program. In addition, the EU Agency for the Space Programme (EUSPA) undertakes activities related to user uptake of data, information and services.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. An overview of the data can be found in Tatem et al, and a description of the modelling methods used found in Stevens et al. The 'Global per country 2000-2020' datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World for each year 2000-2020. These efforts necessarily involved some shortcuts for consistency. The 'individual countries' datasets represent older efforts to map populations for each country separately, using a set of tailored geospatial inputs and differing methods and time periods. The 'whole continent' datasets are mosaics of the individual countries datasets

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

According to the 2021 Census, 81.7% of the population of England and Wales was white, 9.3% Asian, 4.0% black, 2.9% mixed and 2.1% from other ethnic groups.

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

Abstract

China Living Standards Survey (CLSS) consists of one household survey and one community (village) survey, conducted in Hebei and Liaoning Provinces (northern and northeast China) in July 1995 and July 1997 respectively. Five villages from each three sample counties of each province were selected (six were selected in Liaoyang County of Liaoning Province because of administrative area change). About 880 farm households were selected from total thirty-one sample villages for the household survey. The same thirty-one villages formed the samples of community survey. This document provides information on the content of different questionnaires, the survey design and implementation, data processing activities, and the different available data sets.

Geographic coverage

The China Living Standards Survey (CLSS) was conducted only in Hebei and Liaoning Provinces (northern and northeast China).

Kind of data

Sample survey data [ssd]

Sampling procedure

The CLSS sample is not a rigorous random sample drawn from a well-defined population. Instead it is only a rough approximation of the rural population in Hebei and Liaoning provinces in Northeastern China. The reason for this is that part of the motivation for the survey was to compare the current conditions with conditions that existed in Hebei and Liaoning in the 1930’s. Because of this, three counties in Hebei and three counties in Liaoning were selected as "primary sampling units" because data had been collected from those six counties by the Japanese occupation government in the 1930’s. Within each of these six counties (xian) five villages (cun) were selected, for an overall total of 30 villages (in fact, an administrative change in one village led to 31 villages being selected). In each county a "main village" was selected that was in fact a village that had been surveyed in the 1930s. Because of the interest in these villages 50 households were selected from each of these six villages (one for each of the six counties). In addition, four other villages were selected in each county. These other villages were not drawn randomly but were selected so as to "represent" variation within the county. Within each of these villages 20 households were selected for interviews. Thus the intended sample size was 780 households, 130 from each county.

Unlike county and village selection, the selection of households within each village was done according to standard sample selection procedures. In each village, a list of all households in the village was obtained from village leaders. An "interval" was calculated as the number of the households in the village divided by the number of households desired for the sample (50 for main villages and 20 for other villages). For the list of households, a random number was drawn between 1 and the interval number. This was used as a starting point. The interval was then added to this number to get a second number, then the interval was added to this second number to get a third number, and so on. The set of numbers produced were the numbers used to select the households, in terms of their order on the list.

In fact, the number of households in the sample is 785, as opposed to 780. Most of this difference is due to a village in which 24 households were interviewed, as opposed to the goal of 20 households

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire

The household questionnaire contains sections that collect data on household demographic structure, education, housing conditions, land, agricultural management, household non-agricultural business, household expenditures, gifts, remittances and other income sources, and saving and loans. For some sections (general household information, schooling, housing, gift-exchange, remittance, other income, and credit and savings) the individual designated by the household members as the household head provided responses. For some other sections (farm land, agricultural management, family-run non-farm business, and household consumption expenditure) a member identified as the most knowledgeable provided responses. Identification codes for respondents of different sections indicate who provided the information. In sections where the information collected pertains to individuals (employment), whenever possible, each member of the household was asked to respond for himself or herself, except that parents were allowed to respond for younger children. Therefore, in the case of the employment section it is possible that the information was not provided by the relevant person; variables in this section indicate when this is true.

The household questionnaire was completed in a one-time interview in the summer of 1995. The survey was designed so that more sensitive issues such as credit and savings were discussed near the end. The content of each section is briefly described below.

Section 0 SURVEY INFORMATION

This section mainly summarizes the results of the survey visits. The following information was entered into the computer: whether the survey and the data entry were completed, codes of supervisor’s brief comments on interviewer, data entry operator, and related revising suggestion (e.g., 1. good, 2. revise at office, and 3. re-interview needed). Information about the date of interview, the names of interviewer, supervisor, data enterer, and detail notes of interviewer and supervisor were not entered into the computer.

Section 1 GENERAL HOUSEHOLD INFORMATION

1A HOUSEHOLD STRUCTURE 1B INFORMATION ABOUT THE HOUSEHOLD MEMBERS’ PARENTS 1C INFORMATION ABOUT THE CHILDREN WHO ARE NOT LIVING IN HOME

Section 1A lists the personal id code, sex, relationship to the household head, ethnic group, type of resident permit (agricultural [nongye], non-agricultural [fei nongye], or no resident permit), date of birth, marital status of all people who spent the previous night in that household and for household members who are temporarily away from home. The household head is listed first and receives the personal id code 1. Household members were defined to include “all the people who normally live and eat their meals together in this dwelling.” Those who were absent more than nine of the last twelve months were excluded, except for the head of household. For individuals who are married and whose spouse resides in the household, the personal id number of the spouse is noted. By doing so, information on the spouse can be collected by appropriately merging information from the section 1A and other parts of the survey.

Section 1B collects information on the parents of all household members. For individuals whose parents reside in the household, parents’ personal id numbers are noted, and information can be obtained by appropriately merging information from other parts of the survey. For individuals whose parents do not reside in the household, information is recorded on whether each parent is alive, as well as their schooling and occupation.

Section 1C collects information for children of household members who are not living in home. Children who have died are not included. The information on the name, sex, types of resident permit, age, education level, education cost, reasons not living in home, current living place, and type of job of each such child is recorded.

Section 2 SCHOOLING

In Section 2, information about literacy and numeracy, school attendance, completion, and current enrollment for all household members of preschool age and older. The interpretation of pre-school age appears to have varied, with the result that while education information is available for some children of pre-school age, not all pre-school children were included in this section. But for ages 6 and above information is available for nearly all individuals, so in essence the data on schooling can be said to apply all persons 6 age and above. For those who were enrolled in school at the time of the survey, information was also collected on school attendance, expenses, and scholarships. If applicable, information on serving as an apprentice, technical or professional training was also collected.

Section 3 EMPLOYMENT

3A GENERAL INFORMATION 3B MAJOR NON-FARM JOB IN 1994 3C THE SECOND NON-FARM JOB IN 1994 3D OTHER EMPLOYMENT ACTIVITIES IN 1994 3E SEARCHING FOR NON-FARM JOB 3F PROCESS FOR GETTING MAJOR NON-FARM JOB 3G CORVEE LABOR

All individuals age thirteen and above were asked to respond to the employment activity questions in Section 3. Section 3A collects general information on farm and non-farm employment, such as whether or not the household member worked on household own farm in 1994, when was the last year the member worked on own farm if he/she did not work in 1994, work days and hours during busy season, occupation and sector codes of the major, second, and third non-farm jobs, work days and total income of these non-farm jobs. There is a variable which indicates whether or not the individual responded for himself or herself.

Sections 3B and 3C collect detailed information on the major and the second non-farm job. Information includes number of months worked and which month in 1994 the member worked on these jobs, average works days (or hours) per month (per day), total number of years worked for these jobs by the end of 1994, different components of income, type of employment contracts. Information on employer’s ownership type and location was also collected.

Section 3D collects information on average hours spent doing chores and housework at home every day during non-busy and busy season. The chores refer to cooking, laundry, cleaning, shopping, cutting woods, as well as small-scale farm yard animals raising, for example, pigs or chickens. Large-scale animal

Key information about China Labour Force Participation Rate

• China Labour Force Participation Rate increased to 65.8 % in Dec 2023, compared with 65.8 % in the previous year.
• China Labour Force Participation Rate is updated yearly, available from Dec 1990 to Dec 2023, with an average rate of 72.1 % .
• The data reached the an all-time high of 79.2 % in Dec 1990 and a record low of 65.8 % in Dec 2022.
• China Labour Force Participation Rate is reported by reported by CEIC Data.
• In the latest reports, China Population reached 1,408.3 million people in Dec 2024.
• Unemployment Rate of China remained the same at 5.1 % in Dec 2024.
• The country's Monthly Earnings stood at 1,392.5 USD in Dec 2023.

BackgroundThe cancer screening rate in the working population is very low in China. Information-motivation-behavioral skills (IMB) model has been applied to elucidate screening behavior for various chronic diseases but has not been investigated in analyzing cancer screening behavior. This study aimed to examine factors influencing cancer screening behavior and their linkages based on the IMB model.MethodsA cross-sectional study was conducted in Shanghai, China from August to October 2021. Data were obtained through an anonymous questionnaire. Predictive relationships between variables in the IMB model and cancer screening behavior were evaluated. Structural equation modeling (SEM) was constructed to demonstrate the utility of the IMB model.ResultsAmong the 556 participants included in the analysis, 34.4% of participants had ever done a cancer screening. The construct validation analysis supported that the measure items included were acceptable. SEM found that knowledge of cancer warning signs and symptoms (β = 0.563, p

This database aims to document and share empirical research data on the dual interaction structure of "information-population" in the dissemination of emergency information in China. The study employs an information-population dual structure model to analyze the evolution of information and subject scales within the public opinion ecology during emergencies. The data contained within the database supports the model's fitting and predictive methods and offers general rules through simulation. The empirical research segment involves data from six categories of emergencies downloaded from the GsData platform, predicting the trends of population and information, with a significant enhancement in the model's fit after fine-tuning matrix processing.  Dataset Contents:  - Raw Data: Unprocessed data related to emergencies, including social media posts from various platforms, news reports, etc. - Hourly Data: Time series analysis of the original data, documenting the hourly volume of information and the number of participants. - Simulation Parameters: Parameters used to simulate the propagation patterns of emergency information dissemination.