The statistic shows the population of Chengdu in China from 1980 to 2010, with forecasts up until 2035. In 2010, the population of Chengdu had amounted to about **** million inhabitants and was forecasted to grow up to ten million by 2025.

Population: Census: Sichuan: Chengdu data was reported at 20,937.757 Person th in 12-01-2020. This records an increase from the previous number of 14,047.625 Person th for 12-01-2010. Population: Census: Sichuan: Chengdu data is updated decadal, averaging 14,047.625 Person th from Dec 2000 (Median) to 12-01-2020, with 3 observations. The data reached an all-time high of 20,937.757 Person th in 12-01-2020 and a record low of 11,108.534 Person th in 12-01-2000. Population: Census: Sichuan: Chengdu data remains active status in CEIC and is reported by Chengdu Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: By Census.

Historical dataset of population level and growth rate for the Chengdu, China metro area from 1950 to 2025.

Population: Inflow: Sichuan: Chengdu data was reported at 348.938 Person th in 2023. This records a decrease from the previous number of 351.426 Person th for 2022. Population: Inflow: Sichuan: Chengdu data is updated yearly, averaging 272.080 Person th from Dec 2001 (Median) to 2023, with 23 observations. The data reached an all-time high of 485.044 Person th in 2018 and a record low of 158.700 Person th in 2001. Population: Inflow: Sichuan: Chengdu data remains active status in CEIC and is reported by Chengdu Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Non-natural Change.

Population: Household Registration: Death Rate: Sichuan: Chengdu data was reported at 3.850 ‰ in 2023. This records a decrease from the previous number of 12.780 ‰ for 2022. Population: Household Registration: Death Rate: Sichuan: Chengdu data is updated yearly, averaging 6.200 ‰ from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 13.200 ‰ in 2017 and a record low of 3.850 ‰ in 2023. Population: Household Registration: Death Rate: Sichuan: Chengdu data remains active status in CEIC and is reported by Chengdu Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Growth Rate.

This statistic depicts the number of workers in Chengdu urban area in China as of December 2019, by employment status. By the end of 2019, around **** million people were employed in private enterprises or self-employed in the urban area of Chengdu.

Population: Sichuan: Chengdu: Household Registration data was reported at 15,982.354 Person th in 2023. This records an increase from the previous number of 15,715.700 Person th for 2022. Population: Sichuan: Chengdu: Household Registration data is updated yearly, averaging 8,747.300 Person th from Dec 1949 (Median) to 2023, with 75 observations. The data reached an all-time high of 15,982.354 Person th in 2023 and a record low of 5,013.200 Person th in 1949. Population: Sichuan: Chengdu: Household Registration data remains active status in CEIC and is reported by Chengdu Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

Population: Sichuan: Chengdu: Xindu data was reported at 718.600 Person th in 2014. This records an increase from the previous number of 702.300 Person th for 2013. Population: Sichuan: Chengdu: Xindu data is updated yearly, averaging 680.000 Person th from Dec 2004 (Median) to 2014, with 11 observations. The data reached an all-time high of 718.600 Person th in 2014 and a record low of 613.000 Person th in 2004. Population: Sichuan: Chengdu: Xindu data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

Population: Sichuan: Chengdu: Dujiangyan data was reported at 619.300 Person th in 2014. This records an increase from the previous number of 615.700 Person th for 2013. Population: Sichuan: Chengdu: Dujiangyan data is updated yearly, averaging 610.000 Person th from Dec 2004 (Median) to 2014, with 11 observations. The data reached an all-time high of 619.300 Person th in 2014 and a record low of 598.000 Person th in 2004. Population: Sichuan: Chengdu: Dujiangyan data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

ObjectiveThis study aimed to evaluate the fairness and efficiency of health resource allocation (HRAE) in Chengdu-Chongqing Economic Circle after the new healthcare reform. This study also aimed to identify existing problems, providing empirical evidence for the government to formulate regional health plans scientifically and reasonably.MethodsThe fairness of health resource allocation was analyzed using the Gini coefficient, Theil index, and agglomeration degree from population and geographical area perspectives. The three-stage data envelopment analysis and the Malmquist productivity index were used to analyze HRAE from static and dynamic perspectives.ResultsThe Gini coefficient for population allocation in Chengdu-Chongqing Economic Circle was 0.066–0.283, and the Gini coefficient for geographical area allocation was 0.297–0.469. The contribution rate within a region was greater than that between regions, and health resources were mainly concentrated in economically developed core areas. The overall fairness of Chengdu Economic Circle was relatively better than that of Chongqing Economic Circle. Moreover, the adjusted mean technical efficiency was 0.806, indicating room for HRAE improvement in Chengdu-Chongqing Economic Circle. Stochastic Frontier Analysis found that different environmental variables have varying degrees of impact on HRAE. The adjusted mean total factor productivity change (Tfpch) was 1.027, indicating an overall upward trend in HRAE since the new healthcare reform. However, scale efficiency change (Sech) (0.997) limited the improvement of Tfpch.ConclusionThe fairness of health resources allocated by population was better than that allocated by geographical area. The unfairness of health resources mainly stemmed from intra-regional differences, with considerable health resources concentrated in core areas. Over the past 13 years, HRAE has improved but exhibited spatial heterogeneity and Sech-hindered productivity improvement. The study recommends strengthening regional cooperation and sharing to promote the integrated and high-quality development of the health and well-being in Chengdu–Chongqing Economic Circle.

In 2021, around **** million people were estimated to be living in the urban area of Shanghai. Shanghai was the largest city in China in 2021, followed by Beijing, with around **** million inhabitants. The rise of the new first-tier cities The past decades have seen widespread and rapid urbanization and demographic transition in China. While the four first-tier megacities, namely Beijing, Shanghai, Guangzhou, and Shenzhen, are still highly attractive to people and companies due to their strong ability to synergize the competitive economic and social resources, some lower-tier cities are already facing declining populations, especially those in the northeastern region. Below the original four first-tier cities, 15 quickly developing cities are sharing the cake of the moving population with improving business vitality and GDP growth potential. These new first-tier cities are either municipalities directly under the central government, such as Chongqing and Tianjin, or regional central cities and provincial capitals, like Chengdu and Wuhan, or open coastal cities in the economically developed eastern regions. From urbanization to metropolitanization As more and more Chinese people migrate to large cities for better opportunities and quality of life, the ongoing urbanization has further evolved into metropolitanization. Among those metropolitans, Shenzhen's population exceeded **** million in 2020, a nearly ** percent increase from a decade ago, compared to eight percent in the already densely populated Shanghai. However, with people rushing into the big-four cities, the cost of housing, and other living standards, are soaring. As of 2020, the average sales price for residential real estate in Shenzhen exceeded ****** yuan per square meter. As a result, the fast-growing and more cost-effective new first-tier cities would be more appealing in the coming years. Furthermore, Shanghai and Beijing have set plans to control the size of their population to ** and ** million, respectively, before 2035.

Population: Sichuan: Chengdu: Shuangliu data was reported at 1,009.700 Person th in 2014. This records an increase from the previous number of 978.100 Person th for 2013. Population: Sichuan: Chengdu: Shuangliu data is updated yearly, averaging 942.000 Person th from Dec 2004 (Median) to 2014, with 11 observations. The data reached an all-time high of 1,009.700 Person th in 2014 and a record low of 906.000 Person th in 2004. Population: Sichuan: Chengdu: Shuangliu data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

Population: Sichuan: Chengdu: Xinjin data was reported at 311.700 Person th in 2014. This records an increase from the previous number of 310.000 Person th for 2013. Population: Sichuan: Chengdu: Xinjin data is updated yearly, averaging 306.000 Person th from Dec 2004 (Median) to 2014, with 11 observations. The data reached an all-time high of 311.700 Person th in 2014 and a record low of 294.000 Person th in 2004. Population: Sichuan: Chengdu: Xinjin data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

IntroductionAssociation has been reported between ambient fine particulate matter (PM) and adverse outcomes of cerebrovascular events. However, it remains unclear that whether short-term exposure to PM relates to stroke and the lag of health effects. This triggers us to examine the relationship between PM and population stroke morbidity in Chengdu.MethodsThe daily average concentration of atmospheric pollutants and meteorological factors and daily morbidity of stroke in Chengdu (2013–2015) were collected. Based on time series analysis-generalized additive models (GAM), single-pollutant, two-pollutant and multi-pollutant model were established. The effects of atmospheric PM2.5 (defined as PM less than 2.5μm in aerodynamic diameter), PMc(defined as PM less than 10μm and more than 2.5μm in aerodynamic diameter) and PM10 (defined as PM less than 10μm in aerodynamic diameter) concentration on the daily mortality of stroke were analyzed, respectively.ResultsThe three-year mean concentrations of PM2.5, PMc and PM10 for air pollutants were 75.9, 43.9 and 119.7 μg/m3, respectively. PM2.5 on the current day (lag0) and with a moving average of 0–1 days were significantly associated with the increasing risk of stroke morbidity, and PM2.5 with a lag of 0–1 days had greater association, whereas for PMc and PM10 there were no significant association observed. In our study, every 10μg/m3 increase of PM2.5 was associated with 0.69% percent change in stroke morbidity (95%CI: 0.01~1.38). For females, every 10μg/m3 increase of PM2.5 contributes to 0.80% percent change of onset. And for the group of age less than 65, we observed 0.78% higher risk every 10μg/m3 increase of PM2.5.ConclusionsThese findings suggest that short-term exposure to PM2.5 within 1 day is associated with the onset of stroke, and the younger people (age

Population: Sichuan: Chengdu: Usual Residence data was reported at 21,403.000 Person th in 2023. This records an increase from the previous number of 21,268.000 Person th for 2022. Population: Sichuan: Chengdu: Usual Residence data is updated yearly, averaging 14,842.000 Person th from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 21,403.000 Person th in 2023 and a record low of 11,108.500 Person th in 2000. Population: Sichuan: Chengdu: Usual Residence data remains active status in CEIC and is reported by Chengdu Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

Population: Sichuan: Chengdu: Pi data was reported at 542.500 Person th in 2014. This records an increase from the previous number of 526.200 Person th for 2013. Population: Sichuan: Chengdu: Pi data is updated yearly, averaging 519.000 Person th from Dec 2004 (Median) to 2014, with 11 observations. The data reached an all-time high of 546.000 Person th in 2010 and a record low of 488.000 Person th in 2004. Population: Sichuan: Chengdu: Pi data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

Distribution of numbers of daily stroke onset, air pollutants concentration and meteorological conditions in Chengdu, China (2013–2015).

Population: Sichuan: Chengdu: Pengzhou data was reported at 808.500 Person th in 2014. This records an increase from the previous number of 806.200 Person th for 2013. Population: Sichuan: Chengdu: Pengzhou data is updated yearly, averaging 800.000 Person th from Dec 2004 (Median) to 2014, with 11 observations. The data reached an all-time high of 808.500 Person th in 2014 and a record low of 777.000 Person th in 2004. Population: Sichuan: Chengdu: Pengzhou data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

IntroductionThe rapid urbanization and industrialization, accompanied by high-intensive population, energy consumption and transportation activities, have made air pollution an intractable environmental issue in China, especially in most megacities. This study identified the primary air pollutant (PAP) of a Chinese megacity—Chengdu, and analyzed the spatiotemporal changes of PAP concentrations.MethodsThe LMDI and GWR models were employed to probe the spatiotemporal drivers of air pollution in Chengdu.Results and discussionThe pollutants of PM10, PM2.5, O3, and NO2 were identified as the PAPs of Chengdu. During the period of 2015∼2021, the concentrations of the four PAPs showed decreasing trends from 90.5 μg/m3, 56.7 μg/m3, 90.0 μg/m3, and 34.0 μg/m3 to 54.2 μg/m3, 33.7 μg/m3, 87.0 μg/m3, and 29.1 μg/m3, respectively. In 2021, the spatial distributions of the PAP concentrations were characterized by being higher in the central areas. The temporal changes in the PAP concentrations were conjointly influenced by population, per capita GDP, urban built-up area per unit GDP, greenery coverage rate, and pollution load intensity of greenery, with positive effects of population, per capita GDP, and greenery coverage rate and negative effects of urban built-up area per unit GDP and pollution load intensity of greenery. In spatial, the geographical factors (including temperature, precipitation, wind speed, cultivated area and vegetation coverage rate) and socio-economic factors both affected the PAP concentrations. However, there were spatial heterogeneities in the driving forces between different districts of Chengdu, due to the disparities in both the socio-economic and geographical context in different areas. This study also highlights possible policy implications for alleviating urban air pollution, and provides scientific insights for building the clean and livable urban environments for cities.

In 2023, the gender ratio in different regions in China varied greatly, from around 113.2 men per 100 women in Hainan province to only 97.1 men per 100 women in Liaoning. In most provinces in China, there are living more men than women, leading to a national gender ratio of around 104.2 men to 100 women in 2023.