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Globally, poverty and illness are linked, attracting widespread attention. In China, illness contributes to about 40% of rural poverty. This study sought to investigate how healthcare-seeking behavior differs between impoverished and non-impoverished populations within the same Chinese healthcare delivery system. It also sought to understand how differences should be considered when assessing spatial accessibility to provide more accurate recommendations for healthcare resource optimization and promote village revitalization and health equity in China. Methodologically, a survey conducted in May 2019 in Enshi Prefecture (a national impoverished region in Hubei Province, China) collected data on healthcare resource utilization regarding the inpatient and outpatient needs of both impoverished and non-impoverished populations. A Chi-square test compared their respective healthcare-seeking behaviors in three respects (e.g., preference for healthcare institution type, transportation mode, and travel time). Baidu Map data with healthcare institution locations and real-life travel times were then incorporated to assess spatial access to different types of healthcare institutions. Results showed that in Enshi, the most widespread village clinics (low-level) were generally the most utilized healthcare institutions for outpatient visits, with patients usually walking for about 30 min. The middle-level Township Health Centers (THCs) and high-level public hospitals were the most used for inpatient visits, with patients willing to drive up to 30 min to THCs and 60 min to hospitals. Comparatively, the impoverished have more frequent service demands but tend to choose lower-level healthcare institutions, with longer travel times and limited transportation modes. Although 75% of Enshi's area was covered within 30 min by village clinics and 51% of the villages were within 60 min' drive to hospitals, considerable areas remain under-served compared with the shortest travel time targets in China. In conclusion, spatial access to healthcare resources in Enshi must be further improved, especially by strengthening the service capacity of primary healthcare institutions to address the healthcare needs of Enshi's impoverished population. The disparity in healthcare-seeking behavior between different population groups should be fully considered to effectively allocate limited healthcare resources to promote health equity for vulnerable populations as proposed in international and domestic policies. [ABSTRACT FROM AUTHOR]

Background: The rising prevalence of depressive symptoms presents a pressing global public health concern, exacerbated by prevailing social inequality. Aim: This study seeks to identify latent profiles of social inequality perception and explore their associations with depressive symptoms. Methods: Data were obtained from the China Family Panel Studies (CFPS) involving 10,529 residents aged 18 years and above. Latent profile analysis (LPA) was used to identify different patterns of social inequality perception. Multiple linear regression analysis examined the links between these patterns and depressive symptoms. Results: Three distinct patterns of social inequality perception were identified: the disappointed pattern (TDP), the neutral pattern (TNP), and the positive pattern (TPP). Perceived social inequality was significantly associated with short-term and long-term depressive symptoms (β =.51, 95% CI [0.29, 0.72] vs. β =.51, 95% CI [0.27, 0.74]). Increases in social inequality perception patterns were also related to more severe depressive symptoms (β =.55, 95% CI [0.36, 0.74]). Conclusions: Increasing perceived social inequality is closely linked to elevated depressive symptoms in Chinese adults. This underscores the need for tailored strategies aimed at addressing heightened perceptions of social inequality to reduce the risk of depressive symptoms. [ABSTRACT FROM AUTHOR]

Background: The increasing prevalence of depressive symptoms has emerged as a critical public health issue globally, highlighting the need for analyses of the factors contributing to depressive symptoms within the Chinese population and the development of targeted recommendations for improving mental well-being. We aimed to explore the correlation between internet use and depressive symptoms and the role of socioeconomic inequalities in this association., Methods: We included data on 8019 residents aged 18 years and above, which we retrieved from the 2018 and 2020 waves of the China Family Panel Studies. We used latent profile analysis to categorise individuals' internet usage patterns and multiple linear regression to determine their association with depressive symptoms., Results: Higher socioeconomic status (SES) was associated with fewer depressive symptoms (τ = -0.08; 95% confidence interval (CI) = -0.36, -0.18). Individuals in the high-dependence group presented a greater likelihood of developing depressive symptoms (τ = 0.04; 95% CI = 0.007, 0.66). We observed no significant difference in the interaction effect between individual-level SES and the four patterns of internet usage. However, compared with urban-dwelling respondents, those in rural areas had a stronger association between internet usage patterns and depressive symptoms, especially those in the high-dependence group (τ = -0.07; 95% CI = -1.47, -0.20)., Conclusions: Our findings indicate a significant association between depressive symptoms and internet usage patterns, indicating a need for interventions related to internet use, especially those targeted at reducing the risk of depressive symptoms in individuals of lower SES., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no relevant interests., (Copyright © 2024 by the Journal of Global Health. All rights reserved.)