In 2024, about 943.5 million people lived in urban regions in China and 464.8 million in rural. That year, the country had a total population of approximately 1.41 billion people. As of 2024, China was the second most populous country in the world. Urbanization in China Urbanization refers to the process by which people move from rural to urban areas and how a society adapts to the population shift. It is usually seen as a driving force in economic growth, accompanied by industrialization, modernization and the spread of education. Urbanization levels tend to be higher in industrial countries, whereas the degree of urbanization in developing countries remains relatively low. According to World Bank, a mere 19.4 percent of the Chinese population had been living in urban areas in 1980. Since then, China’s urban population has skyrocketed. By 2024, about 67 percent of the Chinese population lived in urban areas. Regional urbanization rates In the last decades, urbanization has progressed greatly in every region of China. Even in most of the more remote Chinese provinces, the urbanization rate surpassed 50 percent in recent years. However, the most urbanized areas are still to be found in the coastal eastern and southern regions of China. The population of Shanghai, the largest city in China and the world’s seventh largest city ranged at around 24 million people in 2023. China’s urban areas are characterized by a developing middle class. Per capita disposable income of Chinese urban households has more than doubled between 2010 and 2020. The emerging middle class is expected to become a significant driver for the continuing growth of the Chinese economy.

In 2023, the ratio of urban to rural population varied greatly in different provinces of China. While Guangdong province had an urban population of around 95.8 million and a rural population of 31.2 million, Tibet had an urban population of only 1.4 million, but a rural population of around 2.2 million.

Context

Some friends at kaggle said them would like to see more dataset about China. I'm just uncertain what kind of data do you want. So I simply collect a population dataset as a beginning. I'm very glad that our international friends can know more about the real China, my great motherland from these datasets.

Content

注：1981年及以前人口数据为户籍统计数；1982、1990、2000、2010、2020年数据为当年人口普查数据推算数；其余年份数据为年度人口抽样调查推算数据。总人口和按性别分人口中包括现役军人，按城乡分人口中现役军人计入城镇人口。 数据来源：国家统计局

Note: Population data in 1981 and before are household registration statistics; The data of 1982, 1990, 2000, 2010 and 2020 are calculated from the census data of the same year. Data for the remaining years were derived from annual population sampling surveys. Active servicemen are included in the total population and population by sex, and active servicemen are included in the urban population by urban and rural population. Source: National Bureau of Statistics.

Tips: what you should notice is that all the numbers with the counting unit (10 thousand) or we said in Chinese ‘万’, as a very usual counting unit rather than 'thousand' in English.

Inspiration

By this dataset, you can see the progress of China's urbanization.

In 2024, the average annual per capita consumption expenditure of urban households in China amounted to around ****** yuan. The consumption expenditure of rural households reached more than half of the amount of their urban counterparts.

The main purpose of this survey is to understand the basic living conditions of the elderly population and their changes since 2006, provide decision-making basis for relevant national departments to formulate relevant aging policies, plans, and strengthen the construction of aging service systems, provide rich and detailed basic data support for the development of China's aging industry and scientific research on aging, and provide information services for knowledgeable individuals from all walks of society who care about and participate in the development of the aging industry. When designing this survey questionnaire, based on the survey questionnaires from 2000 and 2006, and after consulting a large number of relevant literature and surveys in recent years, nine aspects of the personal survey questionnaire and its analytical framework were determined. Including: (1) Basic information; (2) Retirement and reemployment: (3) Economic security and insurance: (4) Housing and environment: (5) Community services and utilization: (6) Family networks and social participation; (7) Health, self-care ability, and care needs; (8) Demand for medical security and healthcare services; (9) Psychological health, spiritual comfort, and outlook on life. The subjects of this survey are elderly people aged 60 and above living in households (with the main survey subjects being those surveyed in 2006) and their communities. The survey questionnaire is divided into individual questionnaires for elderly people in urban and rural areas, as well as questionnaires for village committees, townships and streets, and communities at the city and county levels. A total of 20009 personal questionnaires were collected during the survey, and the validated total sample was 19986 people, including 10032 in urban areas and 9954 in rural areas. There are a total of 2863 valid community questionnaires.

BackgroundIn 2016, the Chinese government introduced an integration reform of the health insurance system with the aim to enhance equity in healthcare coverage and reduce disparities between urban and rural sectors. The gradual introduction of the policy integrating urban and rural medical insurance in pilot cities provides an opportunity to evaluate the policy impact. This study attempts to assess the policy impact of urban–rural health insurance integration on the chronic poverty of rural residents and to analyze the mechanisms.MethodBased on the four waves of data from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, we employed a staggered difference-in-differences (staggered DID) model to assess the impact of integrating urban–rural health insurance on poverty vulnerability among rural inhabitants and a mediation model to analyze the mechanism channel of the policy impact.Results(1) Baseline regression analysis revealed that the urban–rural health insurance integration significantly reduced the poverty vulnerability of rural residents by 6.32% (p 

The challenge of population ageing in China is an emergent area of concern with significant implications as China enters into a period referred to as 'super ageing' (Joseph and Phillips 1999). By 2008 the number of people in China who were 60 or over had reached 159 million, comprising 12 per cent of the total population. Accelerated by economic reforms, a large scale migration of younger workers from rural to urban areas has taken place since the 1990s, which has geographically separated many adult children from their ageing parents and has posed significant challenges to traditional patterns of familial support to rural older people. By focusing upon micro-level processes, the project will employ qualitative techniques to examine the impact of these socio-economic transitions on the experiences of older people in rural areas where two thirds of China's ageing population reside. Through life history interviews and in-depth studies of two rural villages, the project examines the extent to which rural-urban migration has reshaped expectations and experiences of familial support in old age and whether and how intergenerational/gender relations have been transformed by migration.

The survey encompassed 160 cities (counties) across 20 provinces, autonomous regions, and municipalities nationwide, along with 640 streets (townships) and 2000 neighborhoods (villages). It was conducted on December 1, 2000, targeting individuals aged 60 and above in urban and rural areas within the designated sampling scope. Three distinct questionnaires were utilized: urban, rural, and urban-rural community questionnaires. The survey content primarily addressed fundamental aspects of elderly life, including living conditions, economic support, healthcare, community services, cultural activities, social participation, grassroots elderly organizations, and employment status.

As of June 2025, around **** percent of internet users in China lived in rural areas. Meanwhile, the Internet penetration in rural areas was **** percent.

China Government Expenditure: Urban and Rural Community Affairs data was reported at 2,174,200.000 RMB mn in 2024. This records an increase from the previous number of 2,053,576.000 RMB mn for 2023. China Government Expenditure: Urban and Rural Community Affairs data is updated yearly, averaging 1,714,049.000 RMB mn from Dec 2007 (Median) to 2024, with 18 observations. The data reached an all-time high of 2,489,524.000 RMB mn in 2019 and a record low of 324,469.000 RMB mn in 2007. China Government Expenditure: Urban and Rural Community Affairs data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FAS: Final Account: General Public Budget Revenue & Expenditure: National.

The reference time of this survey is August 1, 2015 at 0:00. The survey targets Chinese citizens aged 60 and above residing in the People's Republic of China (excluding Hong Kong, Macao, and Taiwan). The survey covers 31 provinces, autonomous regions, municipalities directly under the central government (excluding Hong Kong, Macao, and Taiwan) and Xinjiang Production and Construction Corps. The sample covers 1864 townships (streets) and 7456 village (neighborhood) committees in 466 counties (cities, districts). The sample size of the survey is 2236800, with a sampling ratio of approximately 1.0‰.

In 2024, the average annual per capita disposable income of rural households in China was approximately ****** yuan, roughly ** percent of the income of urban households. Although living standards in China’s rural areas have improved significantly over the past 20 years, the income gap between rural and urban households is still large. Income increase of China’s households From 2000 to 2020, disposable income per capita in China increased by around *** percent. The fast-growing economy has inevitably led to the rapid income increase. Furthermore, inflation has been maintained at a lower rate in recent years compared to other countries. While the number of millionaires in China has increased, many of its population are still living in humble conditions. Consequently, the significant wealth gap between China’s rich and poor has become a social problem across the country. However, in recent years rural areas have been catching up and disposable income has been growing faster than in the cities. This development is also reflected in the Gini coefficient for China, which has decreased since 2008. Urbanization in China The urban population in China surpassed its rural population for the first time in 2011. In fact, the share of the population residing in urban areas is continuing to increase. This is not surprising considering remote, rural areas are among the poorest areas in China. Currently, poverty alleviation has been prioritized by the Chinese government. The measures that the government has taken are related to relocation and job placement. With the transformation and expansion of cities to accommodate the influx of city dwellers, neighboring rural areas are required for the development of infrastructure. Accordingly, land acquisition by the government has resulted in monetary gain by some rural households.

Intergenerational income mobility in urban and rural China from 1988-2008

The main component of China’s income gap is the urban–rural income gap, which is largely affected by urbanization. It is worth studying how new-type urbanization affects the income gap between urban and rural areas. Research mostly focuses on the urbanization rate as the core explanatory variable to explain the impact using one or two factors. This paper analyzes the mechanism of the effect using a comprehensive number of factors, with the quality of new-type urbanization development as the core explanatory variable. In terms of theoretical research, we believe that new-type urbanization affects the urban–rural income gap by promoting the transfer of labor, changing industrial structure, and policy tendency. Using both static and dynamic empirical analyses, we test the impact of new-type urbanization on the urban–rural income gap based on China’s provincial data. We find that new-type urbanization is conducive to narrowing the income gap between urban and rural areas. The transfer of labor significantly reduces the urban–rural income gap. However, the upgrading of industrial structure will enlarge the gap. The impact of China’s policy orientation is negligible. Policy should focus on promoting urbanization and improving the marginal rate of return of agriculture, improve the level of human capital, reverse the mismatch between employment structure and industrial structure, increase support for rural areas, and make substantial progress in promoting common prosperity.

IntroductionThe Healthy China Initiative emphasizes family health. Education is an upstream determinant of health, which can both achieve upward mobility and cause class solidification.MethodsUsing nationwide large-scale data collected in 2021, the present study explored the relationship between education and family health in the urban-rural dual society via Oaxaca-Blinder decomposition and propensity score matching.ResultsOur data revealed disparities in family health, educational attainment, household income, healthcare coverage, and job type between urban and rural China. An inverted U-shaped relationship existed between increasing years of education and family health. The upper limit was 17.1 years for urban residents and 13.7 years for rural residents, with limited health benefits from higher education obtained by rural residents. Mediated by work-family conflict, highly-educated people received gradually diminishing health returns. The results of the Oaxaca-Blinder decomposition showed that 25.8% of the urban-rural gap in family health could be explained by the disparity in education. Urban residents could translate cultural capital and economic capital into health capital to a greater extent. After propensity score matching, a robust, inverted U-shaped relationship was found between education and family health. The inverted U-shaped relationship was found to replace family health with self-rated health and quality of life.DiscussionFamily-centered public health and education programs, policies, and goals should be developed to break urban-rural dual structure barriers and advance social equity in China.

China Government Expenditure: Urban & Rural Community Affairs data was reported at 195.700 RMB bn in Mar 2025. This records a decrease from the previous number of 343.600 RMB bn for Dec 2024. China Government Expenditure: Urban & Rural Community Affairs data is updated monthly, averaging 104.083 RMB bn from Jan 2007 (Median) to Mar 2025, with 202 observations. The data reached an all-time high of 512.100 RMB bn in Sep 2019 and a record low of 11.470 RMB bn in Jan 2007. China Government Expenditure: Urban & Rural Community Affairs data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FA: Government Revenue and Expenditure: Monthly.

Background: Substantial evidence indicated that absolute income is directly associated with health. Few studies have, however, examined if relative income may be equally associated with health. This study aimed to investigate the association between absolute income/relative deprivation (RD) and self-rated health (SRH). We also investigated whether the urban-rural difference was existing in these associations.Methods: Using cross-sectional data of 7,070 participants in the Shandong Family Health Service Survey of older people, this study applied binary logistic model and semi-parametric model to estimate the effect of absolute income and relative deprivation on SRH of older people. The Kakwani Index was used as a measure of relative deprivation at the individual level.Results: Absolute income has a significant positive effect on the SRH among both urban and rural older people. When considered RD as a variable, both absolute income and RD have negative significant effects on SRH among all older people. In addition, the negative effect of RD on rural elderly is more pronounced than that of urban older populations. Semi-parametric regression results show that there was a complex non-linear relationship between income and SRH. Psychological distress substantially attenuated the association between relative deprivation and SRH.Conclusions: Relative deprivation is negatively associated with self-rated health in both urban and rural older people after controlling the absolute income. RD may partly explain the association between income inequality and worse health status. Compared with the urban elderly, the effect of income-based relative deprivation on SRH was more pronounced among the rural elderly, and more care should be given to the lower income and rural older populations.

China Area of Urban Zone data was reported at 2,371,372.710 sq km in 2022. This records an increase from the previous number of 2,368,544.490 sq km for 2021. China Area of Urban Zone data is updated yearly, averaging 1,986,564.870 sq km from Dec 2006 (Median) to 2022, with 17 observations. The data reached an all-time high of 2,371,372.710 sq km in 2022 and a record low of 1,899,921.300 sq km in 2010. China Area of Urban Zone data remains active status in CEIC and is reported by Ministry of Housing and Urban-Rural Development. The data is categorized under China Premium Database’s Land and Resources – Table CN.NLL: Urban Area.

Natural habitats transformed to city or countryside with human activities of different intensities have reshaped regional and global landscapes, especially in those rapid developed low- and mid-income countries, like China. China’s rapid shift in urban and rural expansion, which are greater than and equal to, and below county-level’s artificial land expansion, and reduction in farmland and ecological land are important for determining future urban and rural development under the conservation and protection of farmland and ecosystems; however, such an understanding is still inadequate. Here, we show that both urban and rural expansions have encroached on farmland and ecological land since 1980; rural areas, with 1.33 km2 × 105 km2 in 2020, remain larger than urban areas, with 0.97 km2 × 105 km2 in 2020. However, urban areas (1857.5 km2/year) increased faster than rural areas (695.0 km2/year) during 1980–2020, rural expansion primarily occurred in the 1980s and 1990s, and urban expansion primarily occurred after 2000 especially 2000s. Farmland is the major land cover that has been occupied by urban and rural expansion for 53.7 and 39.1 thousand km2, especially in East China’s densely populated areas. And, both farmland and ecological land were primarily encroached during 2000s. Our results demonstrate imbalanced urban and rural expansion and encroachment on farmland and ecological land; thus, both forms of encroachment should be optimized at the regional scale based on the socioeconomic needs and natural conditions, and diverse policies can be designed to support local sustainable development.

From the early 1980s the proportion of male births in China has risen sharply with an average of 120 male births for every 100 female. These unprecedented sex ratio imbalances are now affecting the reproductive age groups, with 20 million excess men of reproductive age by 2020. Yet almost no empirical studies exist which explore this phenomenon, so the consequences of this huge surplus of excess men remains unknown. The overall objective of the study was to explore, through comparisons of urban and rural settings in three provinces, the demographic, social and psychological consequences of high sex ratios on (a) young men, (b) young women and (c) society more generally.

The specific objectives were:to compare key socio-demographic indicators for areas with differing sex ratios; to explore and understand the experiences of young men and women living in environments with different sex ratios and their perceptions, if any, of the impact of excess males on society;to explore the psychological and social impact of the sex ratio for partnered and unpartnered men and women;to test hypotheses derived from the literature, including that in high sex ratio areas men are more vulnerable to depression and aggression, women have better mental health with less depression and anxiety, and violent crime and prostitution are more common.Further information may be found on the ESRC The impact of high sex ratios in urban and rural China project award webpage.

The data cover sociodemographic, lifestyle, attitudes and mental health information, including: sociodemographic details; marriage: children; women's status in society; attitudes to sexual behaviour; unmarried older people; problems of excess men; depression; aggression; and sociosexuality.

Measurement scales used: Chinese versions of: 1) The Beck Depression Inventory 2) Rosenberg self-esteem scale 3) Bryant and Smith's adaptation of the Buss/Perry aggression scale 4) Sociosexual Inventory 5) Adaptation of Spence, Helmrich and Stapp's Attitudes Towards Women scale.