In 2022, the total permanent resident population of Tibet autonomous region in China amounted to around **** million inhabitants. Tibet autonomous region is located in Western China.

This point shapefile represents the district locations, with 2000 population census data, in the Autonomous region of Tibet (Xizang) for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.

The data set contains three tables: demographic data for Tibet, demographic data for each county in Tibet, and data on rural workers. These time series data include the year-end total population, the number of men, the number of women, urban population, rural population, and statistics on workers in various rural industries in Tibet from 1967 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks.

Table 1: The table of demographic data for Tibet contains 10 fields. Field 1: Year Field 2: Year-end total population, unit: 10,000 Field 3: Total number of men, unit: 10,000 Field 4: Male proportion, unit: % Field 5: Total number of women, unit: 10,000 Field 6: Female proportion, unit: % Field 7: Urban population, unit: 10,000 Field 8: Urban population proportion, unit: % Field 9: Rural population, unit 10,000 Field 10: Rural population proportion, unit: %.

Table 2: The table of demographic data for each county contains 7 fields. Field 1: Districts and counties Field 2: Year Field 3: Year-end total number of households Field 4: Number of rural households Field 5: Year-end total population, unit: 10,000 Field 6: Rural population, unit: 10,000 Field 7: Year-end number of workers, unit: 10,000

Table 3: The table of rural workers contains 7 fields Field 1: Year Field 2: Districts and counties Field 3: Number of rural workers Field 4: Number of workers in the agricultural, forestry, animal husbandry and fishery sectors Field 5: Number of workers in the industrial sector Field 6: Number of workers in the construction sector Field 7: Number of other non-agricultural workers

The data set contains data on the birth rate, mortality rate and natural growth rate in Tibet. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks.

The table contains 4 fields. Field 1: Year of the data Field 2: Birth rate, unit: ‰ Field 3: Mortality rate, unit:‰ Field 4: Natural growth rate, unit: ‰

In 2023, the real growth rate of the gross domestic product (GDP) of Tibet Autonomous Region in China increased by *** percent compared to the previous year. Tibet Autonomous Region is located in Western China.

The main body of the Tibetan Plateau is Qinghai Province and the Tibetan Autonomous Region. The economic and social data of Qinghai Province and the Tibetan Autonomous Region are the basis for the analysis and assessment of the basic data of sustainable development of populations, resources, environment and economic society on the Tibetan Plateau by integrating the basic data of natural sciences. Under normal circumstances, the statistical yearbooks of all provinces and regions are all in paper and CD-ROM versions, and users need to perform secondary editing before they can use them. This data set mainly relies on the raw data of the Statistical Yearbook of Qinghai Province and the Tibetan Autonomous Region to carry out data conversion and integrate the current economic and social data sets. The temporal coverage of the data is from 2007 to 2016, and the temporal resolution is one year. The spatial coverage is Qinghai Province and the Tibetan Autonomous Region of the Tibetan Plateau. The spatial resolution is the administrative unit of the prefecture or city. The data include information on population, economy, finance, agriculture, forestry, animal husbandry and fishery, investment in fixed assets, education and health.

This dataset is the population index, which includes the dataset of Qinghai Province and Tibet Autonomous Region. It can be used for the coupling coordination relationship between urbanization and eco-environment in Qinghai-Tibet Plateau. The time span in Tibet Autonomous Region is 1995-2016. Permanent residents is based on the population census and the annual population change sampling survey. In addition to the total permanent population, the data were also calculated by gender and urban and rural areas. The time span is from 1952 to 2015 in Qinghai Province, and the indices are resident population, birth, death and natural increase. All data is from the statistical yearbook.

Forensic parameters of the 12 X-STR loci in Tibetans population residing in Nagqu city in the north of the Tibet Autonomous Region (TAR) in China (n = 549).

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.

The data set contains series data of populations of major cities and counties on the Tibetan Plateau from 1970 to 2006. It is used to study social and economic changes on the Tibetan Plateau. The table has six fields. Field 1: Year Interpretation: Year of the data Field 2: Province Interpretation: The province from which the data were obtained Field 3: City/Prefecture Interpretation: The city or prefecture from which the data were obtained Field 4: County Interpretation: The name of the county Field 5: Population (10,000) Interpretation: Population Field 6: Data Sources Interpretation: Source of Data Extraction The data comes from the statistical yearbook and county annals of Tibet Autonomous Region, Qinghai, Sichuan, Gansu, Yunnan and Xinjiang. Some are listed as follows: [1] Gansu Yearbook Editorial Committee. Gansu Yearbook [J]. Beijing: China Statistics Press, 1984, 1988-2009 [2] Statistical Bureau of Yunnan Province. Yunnan Statistical Yearbook [J]. Beijing: China Statistics Press, 1988-2009 [3] Statistical Bureau of Sichuan Province, Sichuan Survey Team. Sichuan Statistical Yearbook [J]. Beijing: China Statistics Press, 1987-1991, 1996-2009 [4] Statistical Bureau of Xinjiang Uighur Autonomous Region . Xinjiang Statistical Yearbook [J]. Beijing: China Statistics Press, 1989-1996, 1998-2009 [5] Statistical Bureau of Tibetan Autonomous Region. Tibet Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-2009 [6] Statistical Bureau of Qinghai Province. Qinghai Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-1994, 1996-2008. [7] County Annals Editorial Committee of Huzhu Tu Autonomous County. County Annals of Huzhu Tu Autonomous County [J]. Qinghai: Qinghai People's Publishing House, 1993 [8] Haiyan County Annals Editorial Committee. Haiyan County Annals[J]. Gansu: Gansu Cultural Publishing House, 1994 [9] Menyuan County Annals Editorial Committee. Menyuan County Annals[J]. Gansu: Gansu People's Publishing House, 1993 [10] Guinan County Annals Editorial Committee. Guinan County Annals [J]. Shanxi: Shanxi People's Publishing House, 1996 [11] Guide County Annals Editorial Committee. Guide County Annals[J]. Shanxi: Shanxi People's Publishing House, 1995 [12] Jianzha County Annals Editorial Committee. Jianzha County Annals [J]. Gansu: Gansu People's Publishing House, 2003 [13] Dari County Annals Editorial Committee. Dari County Annals [J]. Shanxi: Shanxi People's Publishing House, 1993 [14] Golmud City Annals Editorial Committee. Golmud City Annals [J]. Beijing: Fangzhi Publishing House, 2005 [15] Delingha City Annals Editorial Committee. Delingha City Annals [J]. Beijing: Fangzhi Publishing House, 2004 [16] Tianjun County Annals Editorial Committee. Tianjun County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [17] Naidong County Annals Editorial Committee. Naidong County Annals [J]. Beijing: China Tibetology Press, 2006 [18] Gulang County Annals Editorial Committee. Gulang County Annals [J]. Gansu: Gansu People's Publishing House, 1996 [19] County Annals Editorial Committee of Akesai Kazak Autonomous County. County Annals of Akesai Kazakh Autonomous County [J]. Gansu: Gansu People's Publishing House, 1993 [20] Minxian County Annals Editorial Committee. Minxian County Annals [J]. Gansu: Gansu People's Publishing House, 1995 [21] Dangchang County Annals Editorial Committee. Dangchang County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [22] Dangchang County Annals Editorial Committee. Dangchang County Annals(Sequel) (1985-2005) [J]. Gansu: Gansu Cultural Publishing House, 2006 [23] Wenxian County Annals Editorial Committee. Wenxian County Annals[J]. Gansu: Gansu Cultural Publishing House, 1997 [24] Kangle County Annals Editorial Committee. Kangle County Annals [J]. Shanghai: Sanlian Bookstore. 1995 [25] County Annals Editorial Committee of Jishishan (Baoan, Dongxiang, Sala) Autonomous County. County Annals of Jishishan (Baoan, Dongxiang, Sala) Autonomous County[J], Gansu: Gansu Cultural Publishing House, 1998 [26] Luqu County Annals Editorial Committee. Luqu County Annals [J]. Gansu: Gansu People's Publishing House, 2006 [27] Zhouqu County Annals Editorial Committee. Zhouqu County Annals [J]. Shanghai: Sanlian Bookstore. 1996 [28] Xiahe County Annals Editorial Committee. Xiahe County Annals [J]. Gansu: Gansu Cultural Publishing House, 1999 [29] Zhuoni County Annals Editorial Committee. Zhuoni County Annals [J]. Gansu: Gansu Nationality Publishing House, 1994 [30] Diebu County Annals Editorial Committee. Diebu County Annals [J]. Gansu: Lanzhou University Press, 1998 [31] Pengxian County Annals Editorial Committee. Pengxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1989 [32] Guanxian County Annals Editorial Committee. Guanxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1991 [33] Wenjiang County Annals Editorial Committee. Wenjiang County Annals [J]. Sichuan: Sichuan People's Publishing House, 1990 [34] Shifang County

The data set describes the number of students enrolled in various types of schools over time. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks.

Table 1: The table of student number in various types of schools contains 7 fields. Field 1: Year of the data Field 2: Number of students in colleges and universities Field 3: Number of students in secondary schools Field 4: Number of students in specialized secondary schools Field 5: Number of middle school students Field 6: Number of primary school students Field 7: Number of kindergarten students

Table 2: The table of teacher resource statistics in every county contains 7 fields. Field 1: Counties Field 2: Year Field 4: Number of students supervised by each teacher Field 5: Total number of school students Field 6: Number of school students in general middle schools Field 7: Number of school students in primary schools

In 2023, the gross domestic product (GDP) of Tibet Autonomous Region in China amounted to approximately ***** billion yuan, compared to about *** billion yuan in the previous year. Tibet is situated in the west of China at the border to India. The capital of Tibet is Lhasa.

A sequential Bonferroni correction was applied with a threshold p-value of 0.05. (XLSX)

In 2023, the per-capita gross domestic product (GDP) of Tibet Autonomous Region in China reached around ****** yuan. In 2011, the per-capita GDP of Tibet had amounted to approximately ****** yuan.

This line shapefile represents rivers in the Autonomous region of Tibet (Xizang) for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.

ObjectiveIn order to assess selenium (Se) flux through the soil-plant-human chain in Tibet plateau and explore the reason why local Tibetan adult residents from large scale agricultural production areas in Tibet lacked daily Se intake.MethodsA total of 210 intact highland barley plants and their corresponding cultivated topsoil samples were collected in fields of 14 agricultural counties along Yalung Zangpo River and quantitative dietary data were collected from a cross-sectional survey using a cultural-specific food frequency questionnaire that contained all local Tibetan foods in 2020.ResultsThe mean value of The estimated daily Se dietary intake by each participant was 17.1 ± 1.9 μg/day/adult, the Se concentration in topsoil and highland barley grain were 0.128 ± 0.015 mg/kg and 0.017 ± 0.003 mg/kg, respectively. Although highland barley was the first contributor of dietary Se in local adult residents (34.2%), the dietary Se intake provided by highland barley only about 10% of the EAR value (50 μg/day/adult) currently. A significantly positive relationship was determined between soil total Se content (STSe), available Se content (SASe) and highland barley grain Se content (GSe). The amount of Se in food system depends on a number of soil properties (TOC, pH, clay content, Fe/Mn/Al oxides), climate variables (MAP, MAT) and terrain factor (altitude).ConclusionTo sum up, it can be inferred that the insufficient dietary Se intake of Tibetan adult population living along Yalung Zangbo River is mainly caused by the low Se content in highland barley grain, which was result from the low Se content in cultivated soil. In order to enable adult participants in the present study to achieve recommended dietary Se-intake levels, agronomic fortification with selenised fertilizers applied to highland barley could be a great solution. It is necessary to combine the influencing factors, and comprehensively consider the spatial variation of local soil properties, climatic and topographic conditions, and planting systems.

BackgroundThe association between habitual food intake in Tibet and metabolic syndrome (MetS) is largely unclear.ObjectiveTo examine the association between Tibetan habitual food intake and MetS among Tibetan adults.MethodsA population-based cross-sectional study, named the China Multi-Ethnic Cohort (CMEC) study, was conducted between 2018 and 2019. We used data from all Tibetans in the CMEC in the current study. The participants, 1,954 men and 3,060 women aged 18–79 years, were from Lhasa, Tibet Autonomous Region, Tibet. The habitual dietary intake was assessed using a food frequency questionnaire (FFQ). MetS was defined according to ATP III guidelines. Multivariate logistic regression was used to estimate the association between five Tibetan habitual foods and MetS.ResultsTsampa, butter tea, and Qing cha intake were associated with reduced prevalence of MetS. Compared with the lowest quartile of each food, odds ratios (ORs) and their 95% confidence intervals (95% CIs) of medium and high Tsampa intake were 0.59 (0.41–0.85) and 0.53 (0.36–0.77), ORs (95% CIs) of butter tea were 0.67 (0.52–0.88) and 0.61 (0.46–0.81), and Qing cha were 0.85 (0.71–1.03) and 0.75 (0.60–0.93), respectively. When exploring the joint effects of these three foods on MetS, the adjusted ORs and their 95% CIs were 0.65 (0.49–0.87) for the middle intake group and 0.59 (0.42–0.83) for the high intake group as compared with the never/rarely group (p = 0.022 for trend). Associations of MetS with Tibetan noodles and raw beef were not observed.ConclusionTsampa, butter tea, and Qing cha were negatively associated with MetS. The recommendation of increasing the intake of these foods may be beneficial for MetS prevention.

This data contains part of the economic indicators of Qinghai province and Tibet Autonomous Region. The data statistics based on provinces can be used to construct the evaluation index system for the coupling coordination relationship between urbanization and eco-environment on the Tibetan Plateau. The data of the Tibet Autonomous Region contains seven indicators, including the gross domestic product (GDP), the primary, secondary and tertiary industries, industry, construction industry, and the per capita GDP, the time span is 1951-2016. The time span of the data set of Qinghai province is from 1952 to 2015, besides the above seven indicators, there is one more indicator of Qinghai province called agriculture forwdtry animal husbandry and fishery. All data are derived from the statistical yearbook, which is calculated at current prices. The gross domestic product (GDP) for 2005-2008 has been revised based on data from the second economic census.

Population density population distribution is the main form and the main indicators to measure regional differences in population distribution. Town (Street) at the grass-roots administrative system in China, is China's smallest administrative unit of the public release of census data, population density in the township-level data can be objective and precise characterization of the spatial pattern of population distribution and trends in China, and for research on resources, environment and population issues is of great significance. Paper standardized processing has China Liaoning, and Jilin, and in Inner Mongolia (part area), and Beijing, and Tianjin, and Shanghai, and Hebei, and Henan, and Shaanxi, and Ningxia, and Shanxi, and Shandong, and Anhui, and Jiangsu, and Hunan, and Hubei, and Jiangxi, and Zhejiang, and Fujian, and Guangdong, and Hainan, and Yunnan, and Guizhou, and Qinghai, and Tibet, 25 a province (municipalities, and autonomous regions) Township (Street) level administrative line data and the fifth times census Township (Street) level population statistics data, guarantee Township border county (district) Territories consistent, and Spatial and census information for each township unit corresponds to one by one. On this basis, accurately matching the spatial extent of each township and census information, calculated the average population density of communes, form the data set.

This data set contains information on natural disasters in Tibet of nearly 50 years, including the time, place and the consequences of natural disasters such as drought, snows disasters, frost hazards, hail, floods, gales, and lightning disasters. Tibet is located on the southwest border of China and is the main body of the Tibetan Plateau. Due to the influence of the westerly winds, weather and strong warm and wet air currents from the Indian Ocean, the dry and wet seasons are obvious. In addition, the mountains and forests are numerous, and the terrain is complex in Tibet, which makes Tibet among those regions in China having the highest frequencies of natural disasters. The main meteorological disasters that cause significant damage to the production of agriculture and animal husbandry in Tibet are snows disasters, frost hazards, hail, floods and gales. According to incomplete statistics, the average annual disaster area from 1982 to 2000 was 28,440 hectares, of which the disaster area in 1983 was the largest, 203,700 hectares, followed by 1995 with a disaster area of 133,300 hectares. From the proportions of various disaster areas in the total area affected by the disasters, the proportion under drought is the largest, reaching 38%, followed by that under diseases and insect pests, which was 25%. Tibet is sparsely populated, and the ecological environment is very fragile. Traditional farming and animal husbandry production basically relies on people. Various meteorological disasters have caused heavy losses to the lives and property of the Tibetan people. Snow disasters topped the list of various meteorological disasters in Tibet. Tibet is one of the five largest pastoral areas in the country, and livestock is the most important source of production and livelihood for herdsmen. Snow disasters often cause large numbers of livestock death, significant property losses to herdsmen and threat to their lives. The data are extracted from the Tibet Volume of Chinese Meteorological Disaster Dictionary, with manual entry, summarizing and proofreading.