37 datasets found
  1. Population density in Shanghai, China 2013-2023

    • statista.com
    Updated Jul 18, 2025
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    Statista (2025). Population density in Shanghai, China 2013-2023 [Dataset]. https://www.statista.com/statistics/1081928/china-population-density-in-shanghai/
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    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2023, the average resident population density in the Shanghai municipality was ***** people per square kilometer. This figure remained largely unchanged in the recent five years.

  2. Population density in Shanghai, China 2023, by district

    • statista.com
    Updated Apr 9, 2025
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    Statista (2025). Population density in Shanghai, China 2023, by district [Dataset]. https://www.statista.com/statistics/1081875/china-population-density-in-shanghai-by-district/
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    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    In 2023, the district of the Shanghai municipality with the highest resident population density was Hongkou district with an average of 29,280 people living on one square kilometer. The average density of the population of the Shanghai municipality in total was 3,923 people per square kilometer that year.

  3. Population density in China 2023, by region

    • statista.com
    Updated Nov 15, 2024
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    Statista (2024). Population density in China 2023, by region [Dataset]. https://www.statista.com/statistics/1183370/china-population-density-by-region-province/
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    Dataset updated
    Nov 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    China is a vast and diverse country and population density in different regions varies greatly. In 2023, the estimated population density of the administrative area of Shanghai municipality reached about 3,922 inhabitants per square kilometer, whereas statistically only around three people were living on one square kilometer in Tibet. Population distribution in China China's population is unevenly distributed across the country: while most people are living in the southeastern half of the country, the northwestern half – which includes the provinces and autonomous regions of Tibet, Xinjiang, Qinghai, Gansu, and Inner Mongolia – is only sparsely populated. Even the inhabitants of a single province might be unequally distributed within its borders. This is significantly influenced by the geography of each region, and is especially the case in the Guangdong, Fujian, or Sichuan provinces due to their mountain ranges. The Chinese provinces with the largest absolute population size are Guangdong in the south, Shandong in the east and Henan in Central China. Urbanization and city population Urbanization is one of the main factors which have been reshaping China over the last four decades. However, when comparing the size of cities and urban population density, one has to bear in mind that data often refers to the administrative area of cities or urban units, which might be much larger than the contiguous built-up area of that city. The administrative area of Beijing municipality, for example, includes large rural districts, where only around 200 inhabitants are living per square kilometer on average, while roughly 20,000 residents per square kilometer are living in the two central city districts. This is the main reason for the huge difference in population density between the four Chinese municipalities Beijing, Tianjin, Shanghai, and Chongqing shown in many population statistics.

  4. Age distribution of the population in Shanghai, China 2015-2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Age distribution of the population in Shanghai, China 2015-2023 [Dataset]. https://www.statista.com/statistics/1130402/china-shanghai-population-distribution-by-broad-age-group/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    As of 2023, about **** percent of the population of Shanghai municipality in China were 65 years and older. This share is expected to grow rapidly in the coming decades. Shanghai is one of the four first tier cities in China, the other three being Beijing, Shenzhen, and Guangzhou.

  5. Population of Shanghai municipality, China 1980-2024

    • statista.com
    Updated Mar 26, 2025
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    Statista (2025). Population of Shanghai municipality, China 1980-2024 [Dataset]. https://www.statista.com/statistics/1133227/china-population-of-shanghai-municipality-administrative-area/
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    Dataset updated
    Mar 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    According to official figures, around 24.8 million permanent residents were living in the administrative area of Shanghai municipality in 2024. This was 71,900 people less than in the previous year. Population development in Shanghai During the economic reform and opening-up period, Shanghai’s population more than doubled and reached 24.5 million in 2013. However, the limits of demographic growth in Chinese megacities became increasingly apparent since the beginning of the 21st century. In 2017, the Shanghai municipal government planned to limit Shanghai's population and to keep the population within the 25 million-threshold until 2035. As a result, the total population has remained relatively stable since 2013. Furthermore, inhabitants are unevenly distributed across the city districts, with the central urban areas having population densities of around 20,000 people or more per square kilometer. Current demographic shifts Under the conditions of restricted demographic inflows, the effect of population aging becomes increasingly apparent in Shanghai. The city traditionally had a low birth rate compared to other regions in China. In recent years, the number of deaths exceeded the number of births, a development that most probably started in 2020. This development is also reflected in the share of people aged 65 and over which increased steadily in recent times. If migration barriers are not lowered, population decrease in Shanghai is likely in the future.

  6. a

    Growth of Megacities-Shanghai

    • gis-for-secondary-schools-schools-be.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Sep 8, 2014
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    ArcGIS StoryMaps (2014). Growth of Megacities-Shanghai [Dataset]. https://gis-for-secondary-schools-schools-be.hub.arcgis.com/maps/eb1899ad38e5400e8b645c2173c9de92
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    Dataset updated
    Sep 8, 2014
    Dataset authored and provided by
    ArcGIS StoryMaps
    Area covered
    Description

    The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

  7. f

    Correspondence of basic service facility category names and main contents.

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Haoyuan Wu; Liangxu Wang; Zhonghao Zhang; Jun Gao (2023). Correspondence of basic service facility category names and main contents. [Dataset]. http://doi.org/10.1371/journal.pone.0256904.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Haoyuan Wu; Liangxu Wang; Zhonghao Zhang; Jun Gao
    License

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

    Description

    Correspondence of basic service facility category names and main contents.

  8. f

    Coverage rate of various basic service facilities.

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Haoyuan Wu; Liangxu Wang; Zhonghao Zhang; Jun Gao (2023). Coverage rate of various basic service facilities. [Dataset]. http://doi.org/10.1371/journal.pone.0256904.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Haoyuan Wu; Liangxu Wang; Zhonghao Zhang; Jun Gao
    License

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

    Description

    Coverage rate of various basic service facilities.

  9. Population density in China 2012-2022

    • statista.com
    Updated Feb 5, 2025
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    Statista (2025). Population density in China 2012-2022 [Dataset]. https://www.statista.com/statistics/270130/population-density-in-china/
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    Dataset updated
    Feb 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In 2022, the estimated population density of China was around 150.42 people per square kilometer. That year, China's population size declined for the first time in decades. Although China is the most populous country in the world, its overall population density is not much higher than the average population density in Asia. Uneven population distribution China is one of the largest countries in terms of land area, and its population density figures vary dramatically from region to region. Overall, the coastal regions in the East and Southeast have the highest population densities, as they belong to the more economically developed regions of the country. These coastal regions also have a higher urbanization rate. On the contrary, the regions in the West are covered with mountain landscapes which are not suitable for the development of big cities. Populous cities in China Several Chinese cities rank among the most populous cities in the world. According to estimates, Beijing and Shanghai will rank among the top ten megacities in the world by 2030. Both cities are also the largest Chinese cities in terms of land area. The previous colonial regions, Macao and Hong Kong, are two of the most densely populated cities in the world.

  10. f

    Model validation result.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
    + more versions
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    Haoyuan Wu; Liangxu Wang; Zhonghao Zhang; Jun Gao (2023). Model validation result. [Dataset]. http://doi.org/10.1371/journal.pone.0256904.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Haoyuan Wu; Liangxu Wang; Zhonghao Zhang; Jun Gao
    License

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

    Description

    Model validation result.

  11. Population of Shanghai, China 1980-2035

    • statista.com
    Updated Apr 19, 2024
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    Statista (2024). Population of Shanghai, China 1980-2035 [Dataset]. https://www.statista.com/statistics/466938/china-population-of-shanghai/
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    Dataset updated
    Apr 19, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1980 - 2010
    Area covered
    China
    Description

    By 2035, over 34 million people are projected to call Shanghai home. To reduce this number, the Chinese Government implemented population controls for the city in 2017 which aimed to limit the population living in the administrative area of Shanghai municipality to just around 25 million people in 2035.

    Megacity – Shanghai

    As China’s cities become increasingly urbanized, the demographic of this megacity has also changed considerably over the years, with more and more Chinese locals and foreigners opting to dwell in Shanghai for work and cultural opportunities. A huge proportion of residents in the city originate from other regions in China. Over 39 percent of the city’s residents are long-term migrants and Shanghai host’s many foreigners and expats.

    A global financial hub as well as the largest city by population, Shanghai is located on China’s central coast, making it an ideal location to accommodate the world’s busiest container port. The economic contribution of the city to China is significant - Shanghai’s gross domestic product contribution amounted to almost 4.7 trillion yuan in 2023. Despite recent restrictions to land made available for construction, the value of investment in real estate development in Shanghai has continued to increase. To mitigate the effects of its high population, the city has stated it will intensify environmental protection measures.

  12. f

    Shanghai public sports facilities basic datas.

    • figshare.com
    xlsx
    Updated May 13, 2025
    + more versions
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    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun (2025). Shanghai public sports facilities basic datas. [Dataset]. http://doi.org/10.1371/journal.pone.0310585.s008
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    xlsxAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun
    License

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

    Area covered
    Shanghai
    Description

    The spatial configuration and social performance of public sports facilities serve as crucial indicators for evaluating the equity of public sports services and the coherence of urban spatial structure. As Shanghai accelerates its development into a globally renowned sports city, the construction of public sports facilities has encountered significant opportunities. However, challenges persist in the spatial distribution, accessibility, and quality of these facilities. This study investigates the spatial agglomeration characteristics, accessibility, and social performance of urban public sports facilities in Shanghai at both the street and grid scales. Using geographic information system (GIS) tools and analytical methods such as kernel density estimation, standard deviation ellipse, spatial autocorrelation, Gaussian two-step moving search, and the Gini coefficient, the analysis yields the following findings: 1) Public sports facilities in Shanghai are concentrated in the central urban areas and exhibit scattered spatial distribution patterns in peripheral regions. These facilities display a significant directional coupling with population distribution (northeast-southwest), reflecting pronounced spatial imbalances. 2) Social performance analysis reveals clear regional inequities in Shanghai’s public sports facilities. While overall accessibility is relatively high, disparities remain, with suburbs facing facility shortages. Regional equity measurements indicate that the Gini coefficient for public sports facilities in Shanghai is 0.58. Central urban areas possess a high density of facilities, while suburban areas suffer from inadequate facility coverage, leading to uneven service radii and a pattern of high agglomeration but low coverage. 3) The social equity analysis shows that the service capacity entropy of public sports facilities exhibits a distinct spatial distribution, characterized by high values in the east and west and low values in the center. The highest entropy value is 4.25, while the lowest is 0.02. This study provides valuable insights for the planning and optimization of urban public sports facilities in Shanghai, contributing to the enhancement of spatial equity and service effectiveness.

  13. 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.

  14. f

    Comparison table of spatial characterization of public sports facilities in...

    • plos.figshare.com
    xls
    Updated May 13, 2025
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    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun (2025). Comparison table of spatial characterization of public sports facilities in Shanghai. [Dataset]. http://doi.org/10.1371/journal.pone.0310585.t001
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    xlsAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun
    License

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

    Area covered
    Shanghai
    Description

    Comparison table of spatial characterization of public sports facilities in Shanghai.

  15. f

    Spatial accessibility statistics of public sports facilities in Shanghai.

    • plos.figshare.com
    xls
    Updated May 13, 2025
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    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun (2025). Spatial accessibility statistics of public sports facilities in Shanghai. [Dataset]. http://doi.org/10.1371/journal.pone.0310585.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun
    License

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

    Area covered
    Shanghai
    Description

    Spatial accessibility statistics of public sports facilities in Shanghai.

  16. f

    Multi-method comparison table for social performance analysis of Shanghai...

    • plos.figshare.com
    xls
    Updated May 13, 2025
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    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun (2025). Multi-method comparison table for social performance analysis of Shanghai public sports facilities. [Dataset]. http://doi.org/10.1371/journal.pone.0310585.t003
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    xlsAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Haonan Li; Lun Li; Yuan Li; Qing Ji; Jianbo Zhao; Zixi Ge; Qi Zhou; Quan Sun
    License

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

    Area covered
    Shanghai
    Description

    Multi-method comparison table for social performance analysis of Shanghai public sports facilities.

  17. Urban and rural population of China 2014-2024

    • statista.com
    Updated Jan 17, 2025
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    Statista (2025). Urban and rural population of China 2014-2024 [Dataset]. https://www.statista.com/statistics/278566/urban-and-rural-population-of-china/
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    Dataset updated
    Jan 17, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    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.

  18. f

    Microsatellite data from: Contemporary asymmetric genetic introgression...

    • figshare.com
    bin
    Updated Apr 1, 2024
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    Xu WEI; Zhenghuan WANG (2024). Microsatellite data from: Contemporary asymmetric genetic introgression between two Pelophylax in Shanghai species in Shanghai [Dataset]. http://doi.org/10.6084/m9.figshare.22767092.v1
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    binAvailable download formats
    Dataset updated
    Apr 1, 2024
    Dataset provided by
    figshare
    Authors
    Xu WEI; Zhenghuan WANG
    License

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

    Area covered
    Shanghai
    Description

    Human disturbances are considered to break reproduction barriers among species. Significant increases in hybridization events have been reported among a large number of taxonomic groups in anthropogenic environments, providing novel insights into species evolution mechanisms and conservation management in the Anthropocene. The Eastern Golden Frog (Pelophylax plancyi) and Black-Spotted Frog (P. nigromaculatus) are two sympatric anuran species with a long history of mitochondrial genome introgression in highly urbanized continental East Asia. However, there is only limited understanding of the pattern of their contemporary hybridization and factors influencing their interspecific relationship under anthropogenic disturbances. Here, interspecific hybridizationbetween P. plancyi and P. nigromaculatus at the population level was investigated in Shanghai. All except two haplotypes obtained from both species in Shanghai were mixed together, and located in the introgression clade, implying multiple ancient mitochondrial introgression events occurred in the populations of our study area. Asymmetric genetic introgression was detected by microsatellite markers, with 0.7% of P. plancyi and 14.6% of P. nigromaculatus identified as contemporary admixed individuals. Consistent with the trend of population density,higher genetic diversity of neutral microsatellite loci was found in the more abundant P. plancyi; however, variation in mitochondrial (Cyt-b) and nuclear (POMC) genes was higher in relatively rare P. nigromaculatus. The population density of P. plancyi and number of water patches within local habitats were significantly positively correlated with both occurrences and proportions of admixed individuals in the populations of P. plancyi and P. nigromaculatus.Considering the prevalent transformation of habitats in urbanized areas, these results imply that a high population density in isolated artificially altered habitats is likely to increase interspecific hybridization. Thus, population monitoring and improvement of landscape connectivity between habitats would be needed to control the intensity ofinterspecific hybridization between P. plancyi and P. nigromaculatus in anthropogenic-disturbed environments.

  19. f

    Data Sheet 1_Spatial–temporal evolution and associated factors of older...

    • frontiersin.figshare.com
    xlsx
    Updated Jul 3, 2025
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    Xingxing Yin; Jinghang Cui; Yifan Wu; Mingxuan Cui; Kun Li; Haoxiang Guo (2025). Data Sheet 1_Spatial–temporal evolution and associated factors of older adult care institutions in Shanghai.xlsx [Dataset]. http://doi.org/10.3389/fpubh.2025.1598394.s001
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    xlsxAvailable download formats
    Dataset updated
    Jul 3, 2025
    Dataset provided by
    Frontiers
    Authors
    Xingxing Yin; Jinghang Cui; Yifan Wu; Mingxuan Cui; Kun Li; Haoxiang Guo
    License

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

    Area covered
    Shanghai
    Description

    BackgroundShanghai is one of the first Chinese cities to tackle the challenges presented by an aging population. In response, the city has been actively seeking solutions for older adult care within a metropolitan context. This study is based on data from 1,272 older adult care institutions in Shanghai. It uses spatial analysis methods to visually display the spatial evolution of older adult care institutions in the city and analyzes the influencing factors of their spatial distribution patterns using a geographic detector approach.MethodsThe research methodology used in the study includes Kernel Density Estimation for visualizing the spatial distribution of older adult care institutions in Shanghai, the Rand Index for measuring the match between older adult care institutions and the older adult population, and Geographically Weighted Regression for addressing spatial heterogeneity by providing local estimates for regression coefficients at different geographical locations.ResultsThe number of older adult care institutions in Shanghai has seen significant growth over the past 20 years, increasing fourfold due to the rise in both public and private facilities. Older adult care institutions in Shanghai exhibit clear spatial clustering features, evolving from a central cluster to a pattern of one major center surrounded by multiple secondary centers. The distribution of older adult care institutions and the aging population shows a positive trend, with the matching degree constantly increasing. The mean deviation index (M) decreased from 0.015 in 2005 to 0.011 in 2020. However, resources for older adult care institutions in central urban areas remain relatively scarce, particularly in Xuhui, Jing’an, and Putuo districts. Factors influencing the distribution of older adult care institutions show spatial heterogeneity, with varying correlations with residential, recreational, commercial, transportation-related, and healthcare facilities.ConclusionThe findings suggest that Shanghai has made progress in expanding older adult care resources to meet the needs of its aging population. However, there are still disparities in the distribution of these facilities, particularly in central urban areas. Understanding the spatial patterns and factors influencing the location of older adult care institutions can guide future planning efforts to ensure equitable access to care for the older adults in Shanghai.

  20. Age distribution of the population in China 2023, by region

    • statista.com
    Updated Nov 12, 2024
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    Statista (2024). Age distribution of the population in China 2023, by region [Dataset]. https://www.statista.com/statistics/1374770/china-population-age-distribution-by-region/
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    Dataset updated
    Nov 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    China
    Description

    The age structure of the population in China varies greatly across different regions. In 2023, only around 9.6 percent of the population in Shanghai municipality was aged 14 years or younger, while this share amounted to 24.4 percent in Tibet.

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Statista (2025). Population density in Shanghai, China 2013-2023 [Dataset]. https://www.statista.com/statistics/1081928/china-population-density-in-shanghai/
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Population density in Shanghai, China 2013-2023

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 18, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
China
Description

In 2023, the average resident population density in the Shanghai municipality was ***** people per square kilometer. This figure remained largely unchanged in the recent five years.

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