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

This point shapefile represents the district locations, with 2000 population census data, for the Chongqing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.

This line shapefile represents the main rivers for the Chongqing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.

This shapefile represents the railways for the Chongqing province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.

Population: Chongqing: Beibei data was reported at 837.900 Person th in 2021. This records an increase from the previous number of 836.300 Person th for 2020. Population: Chongqing: Beibei data is updated yearly, averaging 700.700 Person th from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 837.900 Person th in 2021 and a record low of 631.700 Person th in 2000. Population: Chongqing: Beibei data remains active status in CEIC and is reported by Chongqing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GW: Population: Municipality District.

CCNP takes its pilot stage (2013 – 2022) of the first ten-year. It aims at establishing protocols on the Chinese normative brain development trajectories across the human lifespan. It implements a structured multi-cohort longitudinal design (or accelerated longitudinal design), which is particularly viable for lifespan trajectory studies, and optimal for recoverable missing data. The CCNP pilot comprises three connected components: developing CCNP (devCCNP, baseline age = 6-18 years, 12 age cohorts, 3 waves, interval = 15 months), maturing CCNP (matCCNP, baseline age = 18-60 years, 14 age cohorts, 3 waves, interval = 39 months) and ageing CCNP (ageCCNP, baseline age = 60-84 years, 12 age cohorts, 3 waves, interval = 27 months). The developmental component of CCNP (devCCNP, 2013-2022), also known as "Growing Up in China", a ten-year's pilot stage of CCNP, has established follow-up cohorts in Chongqing (CKG, Southwest China) and Beijing (PEK, Northeast China). It is an ongoing project focused on longitudinal developmental research as creating and sharing a large-scale multimodal dataset for typically developing Chinese children and adolescents (ages 6.0-17.9 at enrollment) carried out in both school- and community-based samples. The devCCNP houses longitudinal data about demographics, biophysical measures, psychological and behavioral assessments, cognitive phenotyping, ocular-tracking, as well as multimodal magnetic resonance imaging (MRI) of brain's resting and naturalistic viewing function, diffusion structure and morphometry. With the collection of longitudinal structured images and psychobehavioral samples from school-age children and adolescents in multiple cohorts, devCCNP has constructed a full school-age brain template and its growth curve reference for Han Chinese which demonstrated the difference in brain development between Chinese and American school-aged children.*This dataset contains only T1-weighted MRI, Resting-state fMRI and Diffusion Tensor MRI data of devCCNP.To access the devCCNP Lite data, investigators must complete the application file Data Use Agreement on CCNP (DUA-CCNP) at http://deepneuro.bnu.edu.cn/?p=163 and have it reviewed and approved by the Chinese Color Nest Consortium (CCNC). All terms specified by the DUA-CCNP must be complied with. Meanwhile, the baseline CKG Sample on brain imaging are available to researchers via the International Data-sharing Neuroimaging Initiative (INDI) through the Consortium for Reliability and Reproducibility (CoRR). More information about CCNP can be found at: http://deepneuro.bnu.edu.cn/?p=163 or https://github.com/zuoxinian/CCNP. Requests for further information and collaboration are encouraged and considered by the CCNC, and please read the Data Use Agreement and contact us via deepneuro@bnu.edu.cn.

Data on Cognition and Attitudes towards Alzheimer’s Disease among Adult Residents in Jiulongpo District, Chongqing City. (XLSX)