2026-10-14T09:51:30Z https://www.scidb.cn/oai

10.57760/sciencedb.44279 2026-08-14T10:15:15Z

2026-08-14 Associated Dataset for "Spatiotemporal Evolution and Influencing Factors of Life Expectancy of Older Adults in China" doi:10.57760/sciencedb.44279 en This dataset contains the model result data supporting Figures 5–8 in the paper titled "Spatiotemporal Evolution and Influencing Factors of Life Expectancy of Older Adults in China" (Manuscript No. dlxb2026-0145). Figures 5 and 7 are SHAP summary plots, showing the relative importance and direction of influence of various factors on the prefecture-level life expectancy of older adults in China for the periods 2000–2020 and 2010–2020. Figures 6 and 8 are SHAP dependence plots, illustrating the nonlinear effects and threshold effects of key factors such as per capita GDP, education level, urbanization rate, net population mobility rate, and income status of older adults on the life expectancy of the older population.The dataset covers 278 prefecture-level and above administrative units in China (the sample for influencing factor analysis), spanning three time periods: 2000, 2010, and 2020. The variables include economic level (per capita GDP), economic structure (share of tertiary industry), urbanization level (urbanization rate), education level (proportion of population with college education or above), medical care level (number of health technical personnel per 10,000 persons), ethnic culture (proportion of ethnic minority population), environmental baseline (mean annual temperature range), population mobility (net mobility rate), economic security of older adults (income status), and living support for older adults (non-living-alone rate). The above data are the SHAP values and corresponding original variable values output from the XGBoost-SHAP model, and can be used to verify the conclusions of the paper regarding the four types of influencing mechanisms: saturation-promoting, continuous-promoting, threshold-inhibiting, and differentiating. Life expectancy of older adults; Influencing factors; XGBoost-SHAP model; Machine Learning; Prefecture-level scale Wu Lianxia Li Wei Pan Zehan Wang Xianyu Guan Weihua EMBARGO https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank