The life satisfaction of the elderly is the key to subjective well-being and healthy aging. Many related studies are focused on the affected factors, including health status, economic level, social support, pension mode, social security, and intergenerational support, etc., but few are based on the macro perspective of healthy aging. This study constructed a healthy aging evaluation system with 6 dimensions, including 15 primary indicators and 57 secondary indicators, to evaluate the relationship between healthy aging and elderly life satisfaction. Results showed that the 13168 participants were, mainly, female (53.76%), 80–99 years old (47.99%), lived in rural areas (77.00%), married and living with their spouse (43.70%), and widowed (52.15%). 80.32% lived with household members. 70.37% elderly were satisfied with their lives. Specifically, there was no gender difference in life satisfaction of the elderly ( p = 0.273 ), but there were significant differences between groups of urban and rural ( p < 0.001 ), age groups of 65–79 and 80 older ( p < 0.001 ), marriage groups of unmarried and married ( p < 0.001 ), and types of elderly care of living alone and with others ( p < 0.001 ), respectively. Among the six dimensions of healthy aging, healthcare performed best and living environment dimension was the worst, which was an area that urgently needed to strengthen. The odds ratios (ORs) showed that the dimensions of social participation/social equity and economic finance played important roles in the well-being of the elderly. Under the macro background of healthy aging, how to take measures from the micro perspective of the healthy aging evaluation index system and ultimately improve the life satisfaction of the elderly and still needs to be explored in-depth.

Objective: Our aim was to evaluate the association between eHealth literacy and lifestyle behaviors to intervene among Chinese university students. Method: The Chinese eHealth Literacy Scale (C-eHEALS) questionnaire was used to investigate the eHealth literacy level and association with lifestyle behaviors among Chinese university students. Independent sample t-test and Pearson’s correlation coefficient were used by statistical software SPSS v20. Results: In the first round, 5,151 university students participated in the study, including 71.46% female and 28.54% male, aged 18–22 (93.13%).The average eHealth literacy score was 26.81 ± 5.83. Four lifestyle behaviors (e.g., exercise, smoking, drinking and sleeping) were all significantly correlated with eHealth literacy scores and demonstrated significant differences. In the second investigation (N = 2,939), the average eHealth literacy score was 31.64 ± 6.44, a notable improvement compared with the first investigation. Conclusion: Those in the group with high eHealth literacy scores have a healthier lifestyle than those in the low-score group. Training in eHealth-related resources is a positive measure to improve university students’ eHealth literacy.

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