China's Less-Children-Aging Dataset

China's provincial, municipal, and county-level shares of the juvenile population, shares of the elderly population, types of juvenile-aging, transition paths of the types, and changes in the Sangitu in 2000, 2010, and 2020; and typical regional divisions based on the county level and their share of the types of juvenile-aging.1. The proportion of the lesser population, the proportion of the elderly population and their types: the level of aging is measured by the proportion of the elderly population in the total population, and when the proportion of the elderly population aged 65 and above in a country or region exceeds 7%, it is considered that the country or region has entered an aging society. With reference to relevant studies and the actual situation, the proportion of the elderly population aged 65 and above is set at less than 7% as unaged, at 7% to 14% as mildly aged, at 14% to 20% as moderately aged, and at more than 20% as severely aged. The level of underageing is measured by the proportion of children aged 0 to 14 years old, and when the proportion of children aged 0 to 14 years old in a country or region is less than 20%, it is considered to have entered an underage society. Referring to the study of Ding Jinhong et al, the proportion of the population of children less than 20% is set as oligonization, when 20% to 40% is set as polyonization, and 40% to 60% is set as hyperpolyonization. The quadrant diagram (X, Y) tool was introduced to determine the type of oligo-polyploidization. The horizontal axis (X) represents the proportion of elderly population and the vertical axis (Y) represents the proportion of oligo-population, and a two-dimensional matrix is constructed to obtain different combinations of types.2. Sanger diagram: Use the above three scales of types to calculate the size of the type shift flow from 2000 to 2010 and from 2010 to 2020 respectively, e.g., 30% of type 1 shifted to type 2, and 20% were retained as type 1, etc.3. Cluster analysis: using K-Means clustering method to cluster the type shift of oligo - aging at county scale from 2000 to 2010, 2010 to 2020, and 2000 to 2020.4. Pie Chart: A certain type of oligo - aging in a region / the total number of types in the region in that year * 1005. multinomial logistic regression:choose the difference between urbanization rate, population inflow rate, female illiteracy rate and birth rate in time period t (2000-2010, 2010-2020) as the independent variables. Apply multinomial