The population proportion in the provinces of western China residing in potential high-risk areas.

Population: Hunan: West Hunan data was reported at 2,432.000 Person th in 2023. This records a decrease from the previous number of 2,461.200 Person th for 2022. Population: Hunan: West Hunan data is updated yearly, averaging 2,548.800 Person th from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 2,850.000 Person th in 2010 and a record low of 2,432.000 Person th in 2023. Population: Hunan: West Hunan data remains active status in CEIC and is reported by West Hunan Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GN: Population: Prefecture Level Region.

Population: Hunan: West Hunan: Fenghuang data was reported at 351.700 Person th in 2022. This records a decrease from the previous number of 353.600 Person th for 2021. Population: Hunan: West Hunan: Fenghuang data is updated yearly, averaging 353.300 Person th from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 386.300 Person th in 2009 and a record low of 327.500 Person th in 2016. Population: Hunan: West Hunan: Fenghuang 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: Rural: Hunan: West Hunan: Jishou data was reported at 107.300 Person th in 2022. This records a decrease from the previous number of 109.300 Person th for 2021. Population: Rural: Hunan: West Hunan: Jishou data is updated yearly, averaging 93.400 Person th from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 183.000 Person th in 2007 and a record low of 83.300 Person th in 2014. Population: Rural: Hunan: West Hunan: Jishou 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: Rural: County Level Region.

The aging population is a common problem faced by most countries in the world. This study uses 18 years (from 2002 to 2019) of panel data from 31 regions in China (excluding Hong Kong, Macao, and Taiwan Province), and establishes a panel threshold regression model to study the non-linear impact of the aging population on economic development. It is different from traditional research in that this paper divides 31 regions in China into three regions: Eastern, Central, and Western according to the classification standard of the National Bureau of Statistics of China and compares the different impacts of the aging population on economic development in the three regions. Although this study finds that the aging population promotes the economy of China’s eastern, central, and western regions, different threshold variables have dramatically different influences. When the sum of export and import is the threshold variable, the impact of the aging population on the eastern and the central region of China is significantly larger than that of the western region of China. However, when the unemployment rate is the threshold variable, the impact of the aging population on the western region of China is dramatically higher than the other regions’ impact. Thus, one of the contributions of this study is that if the local government wants to increase the positive impact of the aging population on the per capita GDP of China, the local governments of different regions should advocate more policies that align with their economic situation rather than always emulating policies from other regions.

China’s rapid urbanisation has induced large numbers of rural residents to migrate from their homes in the countryside to urban areas in search of higher wages. As a consequence, it is estimated that more than 60 million children in rural China are left behind and live with relatives, typically their paternal grandparents. These children are called Left Behind Children (LBCs). There are concerns about the potential negative effects of parental migration on the academic performance of the LBCs that could be due to the absence of parental care. However, it might also be that when a child’s parents work away from home, their remittances can increase the household’s income and provide more resources and that this can lead to better academic performance. Hence, the net impact of out-migration on the academic performance of LBCs is unclear. This paper examines changes in academic performance before and after the parents of students out-migrate. We draw on a panel dataset collected by the authors of more than 13,000 students at 130 rural primary schools in ethnic minority areas of rural China. Using difference-in-differences and propensity score matching approaches, our results indicate that parental migration has significant, positive impacts on the academic performance of LBCs (which we measure using standardised English test scores). Heterogeneous analysis using our data demonstrates that the positive impact on LBCs is greater for poorer performing students.

Population: Hunan: West Hunan: Guzhang data was reported at 106.700 Person th in 2022. This records a decrease from the previous number of 107.200 Person th for 2021. Population: Hunan: West Hunan: Guzhang data is updated yearly, averaging 132.200 Person th from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 141.200 Person th in 2009 and a record low of 106.700 Person th in 2022. Population: Hunan: West Hunan: Guzhang 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.

BackgroundCollege students in Western China face unique economic, cultural, and educational environments, yet limited studies have specifically investigated the factors or interventions concerning emotional distress within this population.AimThis study aimed to explore whether school belongingness mediates the relationship between expectations regarding school and emotional distress among college students in Western China, and whether physical exercise moderates this mediation.MethodsEmploying a cross-sectional design, 1,063 college students in Xinjiang, China were recruited for this study. A self-administered electronic questionnaire assessed expectations regarding school, school belongingness, physical exercise, anxiety, and depression. Structural equation modeling was utilized to analyze mediating and moderating effects.ResultsExpectations regarding school was negatively associated with emotional distress. School exclusion and school acceptance fully mediated the effect of expectations regarding school on emotional distress. Physical exercise moderated the mediating effect of school exclusion, but not that of school acceptance.ConclusionExpectations regarding school and school belongingness, particularly the exclusion component, emerge as pivotal factors influencing emotional distress among college students in Western China. Furthermore, physical exercise presents itself as a promising targeted intervention for alleviating emotional distress within this demographic.

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Feng Yang. How do smart cities enhance urban economic resilience: Empirical evidence from China’s smart city pilot policies[DS/OL]. V1. Science Data Bank, 2025[2025-06-02]. https://cstr.cn/31253.11.sciencedb.24686. CSTR:31253.11.sciencedb.24686. Feng Yang. How do smart cities enhance urban economic resilience: Empirical evidence from China’s smart city pilot policies[DS/OL]. V1. Science Data Bank, 2025[2025-06-02]. https://doi.org/10.57760/sciencedb.24686. DOI:10.57760/sciencedb.24686. This article uses the entropy weight TOPSIS method to comprehensively evaluate the tourism competitiveness of Chinese prefecture level cities. The evaluation index system includes tourism resources, tourism There are a total of 28 indicators in four dimensions: tourism industry, social development support, and ecological environment support. Based on this, this article generates panel data for 272 prefecture level cities from 2005 to 2019, and estimates the impact of urban transformation on tourism competitiveness using a multi period DID method. In the DID model, the dependent variable is tourism competitiveness, the explanatory variable is the cross dummy variable of innovative cities and low-carbon city construction pilot projects, the control variables include economic development, foreign investment utilization, foreign trade, resident consumption, financial development, human capital, information technology, and population, and the mechanism variables are industrial structure rationalization, industrial structure upgrading, technological innovation input, technological innovation output, and environmental regulation. This dataset also distinguishes between eastern, central, and western cities, cities with different administrative levels, and whether they are resource-based cities.

This dataset is the precipitation and population change trend and correlation analysis data of China from 2001 to 2020, including the division of arid and humid areas by precipitation data from 2001 to 2023, two dry and wet division methods, and the east and west areas of the Hu Huanyong Line. China's elevation is divided into four categories of altitude at 1000 meters, 2000 meters, and 3000 meters. Most of the data is processed by QGIS, and the other part is implemented by python code. Origin 2024 is used to carry out trend analysis and correlation analysis, and the table data is stored in excel and csv formats. The schematic diagram is in eps format.

Distribution intervals of green ecological efficiency in western China.

This dataset contains the digitized treatments in Plazi based on the original journal article Fan, Cui, Wang, Man, Wang, Jia-Jia, Luo, Tao, Zhou, Jia-Jun, Xiao, Ning, Zhou, Jiang (2024): Sinocyclocheilus xiejiahuai (Cypriniformes, Cyprinidae), a new cave fish with extremely small population size from western Guizhou, China. ZooKeys 1214: 119-141, DOI: 10.3897/zookeys.1214.127629

Population: Hunan: West Hunan: Yongshun data was reported at 405.300 Person th in 2022. This records a decrease from the previous number of 407.300 Person th for 2021. Population: Hunan: West Hunan: Yongshun data is updated yearly, averaging 446.400 Person th from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 503.700 Person th in 2009 and a record low of 405.300 Person th in 2022. Population: Hunan: West Hunan: Yongshun 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.

BackgroundParental household wealth has been shown to be associated with offspring health conditions, while inconsistent associations were reported among generally healthy population especially in low- and middle- income countries (LMICs). Whether the household wealth upward mobility in LMICs would confer benefits to child health remains unknown.MethodsWe conducted a prospective birth cohort of children born to mothers who participated in a randomized trial of antenatal micronutrient supplementation in rural western China. Household wealth were repeatedly assessed at pregnancy, mid-childhood and early adolescence using principal component analysis for household assets and dwelling characteristics. We used conditional gains and group-based trajectory modeling to assess the quantitative changes between two single-time points and relative mobility of household wealth over life-course, respectively. We performed generalized linear regressions to examine the associations of household wealth mobility indicators with adolescent height- (HAZ) and body mass index-for-age and sex z score (BAZ), scores of full-scale intelligent quotient (FSIQ) and emotional and behavioral problems.ResultsA total of 1,188 adolescents were followed, among them 59.9% were male with a mean (SD) age of 11.7 (0.9) years old. Per SD conditional increase of household wealth z score from pregnancy to mid-childhood was associated with 0.11 (95% CI 0.04, 0.17) SD higher HAZ and 1.41 (95% CI 0.68, 2.13) points higher FSIQ at early adolescence. Adolescents from the household wealth Upward trajectory had a 0.25 (95% CI 0.03, 0.47) SD higher HAZ and 4.98 (95% CI 2.59, 7.38) points higher FSIQ than those in the Consistently low subgroup.ConclusionHousehold wealth upward mobility particularly during early life has benefits on adolescent HAZ and cognitive development, which argues for government policies to implement social welfare programs to mitigate or reduce the consequences of early-life deprivations. Given the importance of household wealth in child health, it is recommended that socioeconomic circumstances should be routinely documented in the healthcare record in LMICs.

This is the first meta-analysis of the pooled prevalence of insomnia in the general population of China. A systematic literature search was conducted via the following databases: PubMed, PsycINFO, EMBASE and Chinese databases (China National Knowledge Interne (CNKI), WanFang Data and SinoMed). Statistical analyses were performed using the Comprehensive Meta-Analysis program. A total of 17 studies with 115,988 participants met the inclusion criteria for the analysis. The pooled prevalence of insomnia in China was 15.0% (95% Confidence interval [CI]: 12.1%-18.5%). No significant difference was found in the prevalence between genders or across time period. The pooled prevalence of insomnia in population with a mean age of 43.7 years and older (11.6%; 95% CI: 7.5%-17.6%) was significantly lower than in those with a mean age younger than 43.7 years (20.4%; 95% CI: 14.2%-28.2%). The prevalence of insomnia was significantly affected by the type of assessment tools (Q = 14.1, P = 0.001). The general population prevalence of insomnia in China is lower than those reported in Western countries but similar to those in Asian countries. Younger Chinese adults appear to suffer from more insomnia than older adults.Trial Registration: CRD 42016043620

Dataset

This dataset provides a comprehensive provincial-level assessment of solar energy resources, photovoltaic (PV) development, and associated spatial equity indicators for mainland China for the year 2020. It was compiled to support the analysis and conclusions of the manuscript "Mismatch Between Solar Resource Endowment and Photovoltaic Development in China: A Provincial Assessment of Accessibility and Inequality."

### Files in this Dataset

* **`china_pv_equity_data_2020.csv`**: The main dataset containing the final calculated indicators for each of the 31 mainland provinces.
* **`Grid50km_Pop_2020.zip`**: A compressed archive containing the processed 50km gridded population data for China in shapefile (.shp) format.
* **`china_province_boundaries.zip`**: A compressed archive containing the administrative boundaries for the 31 mainland provinces of China in shapefile (.shp) format.

### Variable Descriptions

**1. For `china_pv_equity_data_2020.csv`:**

| Column Name | Description |
| :--- | :--- |
| `province_ID` | Unique numerical identifier for each province. |
| `province_name` | Name of the province in Pinyin. |
| `Region` | Regional classification: 'E' for Eastern, 'W' for Western. |
| `PV_Acc` | Population Weighted PV Accessibility (PVaccess). |
| `Rad_Acc` | Population Weighted Solar Radiation Accessibility (Radaccess). |
| `Index_coord` | Coordination Index (`PV_Acc` - `Rad_Acc`). |
| `PV_Gini` | Intra-provincial Gini coefficient for PV development. |
| `Rad_Gini` | Intra-provincial Gini coefficient for solar resources. |
| `Index_exac` | Inequality Exacerbation Index (`PV_Gini` - `Rad_Gini`). |
| `GDP in 2020` | Gross Domestic Product in 2020 (Unit: 100 million CNY). |

**2. For `Grid50km_Pop_2020.shp` (within the .zip file):**

| Field Name | Description |
| :--- | :--- |
| `FID_Provin` | Numerical identifier for the province. Same as 'province_id' in other datasets. |
| `Name` | The name of the province in which the 50km grid cell is located. |
| `Only` | Unique identifier for each 50km grid cell. |
| `COUNT` | The number of 1km WorldPop grid cells that fall within the 50km grid cell. |
| `SUM` | The total population within the 50km grid cell, aggregated from 1km WorldPop data. |
| `Shape_Leng` | The perimeter of the grid cell polygon. |
| `Shape_Area` | The area of the grid cell polygon. |

**3. For `china_province_boundaries.shp` (within the .zip file):**

| Field Name | Description |
| :--- | :--- |
| `Name` | Name of the province. |
| `province_id` | Unique numerical identifier for the province. |
| `Region` | Regional classification ('E' or 'W'). |

Code/software

All data processing, spatial analysis, and indicator calculations were performed using a combination of ArcGIS Pro, Microsoft Excel, and Python 3 (utilizing libraries such as Pandas, GeoPandas, and NumPy).

The key processing steps included:

Aggregating the 1-km resolution WorldPop population data to a 50-km grid to create the Grid50km_Pop_2020 dataset.

Spatially joining and summarizing the raw photovoltaic distribution and solar radiation data within each provincial boundary.

Calculating the Population Weighted Exposure (PWE) based indices (PV_Acc, Rad_Acc) for each province using the 50km gridded population data as weights.

Calculating the intra-provincial Gini coefficients (PV_Gini, Rad_Gini) based on the spatial distribution of resources/infrastructure and population within each province.

Compiling all final indicators and socioeconomic data into the china_pv_equity_data_2020.csv file.

Access information

Other publicly accessible locations of the data:

• Population spatial distribution data: The "WorldPop Global Project Population Data" is openly available from the WorldPop project website at: https://www.worldpop.org
• Solar resource data: The "National Solar Radiation Database (NSRDB)" is openly available from the U.S. National Renewable Energy Laboratory (NREL) at: https://nsrdb.nrel.gov
• Geographical data: The administrative boundary data for provinces are available from the National Geographic Center of China at: https://www.ngcc.cn/
• Socioeconomic data: The provincial GDP data are available in the "China Statistical Year-book-2021," published by the National Bureau of Statistics of China at: http://www.stats.gov.cn/sj/ndsj/2021/indexeh.htm
• Photovoltaic spatial distribution data: Lyu, X. et al. (2024) in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (DOI: 10.1109/JSTARS.2024.3468627)

This dataset comprises a 2-m-resolution digital elevation model (DEM) (WorldView3-DEM.tif) and 0.5-m-resolution orthophotograph (WorldView3-DOM.png) of the West Helanshan Fault (Northern China) which is a Holocene active right-lateral strike-slip fault located at the junction of the Tibetan Plateau, Alashan, and Ordos blocks. The dataset covers a 6 km wide swath along an approximately 50 km long section of the fault (the dataset extent can be found in West_Helanshan_Fault.kmz). The DEM was built from the WorldView-3 panchromatic stereo images acquired on 5 July 2018 based on the photogrammetry method, and the orthophotograph was created based on the generated DEM. Two local areas along the fault are heavily obscured by clouds in the WorldView-3 images. Thus, we used a small four-rotor Unmanned Aerial Vehicle (UAV), the Motoarsky MS670, to acquire images of the two areas on 27 September 2018. Based on the Structure-from-Motion (SfM) method, we finally obtained DEM with a spatial resolution of 0.1 m (UAV-DEM1.tif and UAV-DEM2.tif) and orthophotograph with a spatial resolution of 0.03 m (UAV-DOM1.png and UAV-DOM2.png) for the two local areas. More details of this dataset can be found in Bi, H., Zheng, W., Lei, Q., Zhang, P., Zeng, J., & Chen, G. (2020). Surface slip distribution along the West Helanshan Fault, Northern China and its implications for fault behavior. Journal of Geophysical Research: Solid Earth, doi: 10.1029/2020JB019983. (https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020JB019983).

Population: Hunan: West Hunan: Longshan data was reported at 463.600 Person th in 2022. This records a decrease from the previous number of 468.200 Person th for 2021. Population: Hunan: West Hunan: Longshan data is updated yearly, averaging 503.300 Person th from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 559.900 Person th in 2009 and a record low of 463.600 Person th in 2022. Population: Hunan: West Hunan: Longshan 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.

The Keriyan people live in an isolated village in the Taklimakan Desert in Xinjiang, Western China. The origin and migration of the Keriyans remains unclear. We studied paternal and maternal genetic variance through typing Y-STR loci and sequencing the complete control region of the mtDNA and compared them with other adjacent populations. Data show that the Keriyan have relatively low genetic diversity on both the paternal and maternal lineages and possess both European and Asian specific haplogroups, indicating Keriyan is an admixture population of West and East. There is a gender-bias in the extent of contribution from Europe vs. Asia to the Keriyan gene pool. Keriyans have more genetic affinity to Uyghurs than to Tibetans. The Keriyan are not the descendants of the Guge Tibetans.

BackgroundTaenia solium cysticercosis affects millions of impoverished people worldwide and can cause neurocysticercosis, an infection of the central nervous system which is potentially fatal. Children may represent an especially vulnerable population to neurocysticercosis, due to the risk of cognitive impairment during formative school years. While previous epidemiologic studies have suggested high prevalence in rural China, the prevalence in children as well as risk factors and impact of disease in low-resource areas remain poorly characterized.Methodology/Principal findingsUtilizing school based sampling, we conducted a cross-sectional study, administering a questionnaire and collecting blood for T. solium cysticercosis antibodies in 2867 fifth and sixth grade students across 27 schools in west Sichuan. We used mixed-effects logistic regression models controlling for school-level clustering to study associations between risk factors and to characterize factors influencing the administration of deworming medication. Overall prevalence of cysticercosis antibodies was 6%, but prevalence was significantly higher in three schools which all had prevalences of 15% or higher. Students from households owning pigs (adjusted odds ratio [OR] 1.81, 95% CI 1.08–3.03), from households reporting feeding their pigs human feces (adjusted OR 1.49, 95% CI 1.03–2.16), and self-reporting worms in their feces (adjusted OR 1.85, 95% CI 1.18–2.91) were more likely to have cysticercosis IgG antibodies. Students attending high prevalence schools were more likely to come from households allowing pigs to freely forage for food (OR 2.26, 95% CI 1.72–2.98) and lacking a toilet (OR 1.84, 95% CI 1.38–2.46). Children who were boarding at school were less likely to have received treatment for gastrointestinal worms (adjusted OR 0.58, 95% CI 0.42–0.80).Conclusions/SignificanceOur study indicates high prevalences of cysticercosis antibodies in young school aged children in rural China. While further studies to assess potential for school-based transmission are needed, school-based disease control may be an important intervention to ensure the health of vulnerable pediatric populations in T. solium endemic areas.