Early-Life Factors and Multimorbidity Risk Later in Older Age: Evidence Based on CHARLS.

INTRODUCTION: Early-life factors were reported to exert influence on the health condition of individuals in the long-term. However, limited research explored the connection between early-life factors and multimorbidity in later years. METHODS: We utilized the data from the China Health and Retirement Longitudinal Study to assess this possible association in the present cross-sectional study. Multimorbidity was determined based on 14 common chronic diseases included in the study. Logistic regression was employed to examine the link between early-life factors and subsequent multimorbidity. RESULTS: Out of 7,578 participants who met the inclusion criteria for analysis, 3,765 (49.68%) were females. The mean age was 68.25 ± 6.70 years. Participants who rated their health during childhood as average (odds ratio [OR] 0.78, 95% confidence interval [CI] 0.63-0.96) or better [OR 0.72, 95% CI 0.57-0.91] were significantly less likely to experience multimorbidity in older life. By contrast, experiencing violence from two of the family members was significantly associated with future multimorbidity (OR [95% CI], 1.29 [1.04-1.60]). A superior family financial situation was also negatively associated with multimorbidity, with average (OR [95% CI], 0.72 [0.63-0.83]) and better off than average (OR [95% CI], 0.76 [0.62-0.93]). DISCUSSION: Individuals with poor health status, inferior family socioeconomic status, or experienced violence from family members in childhood were more likely to suffer from multimorbidity in later life. Enhanced social monitoring of potentially adverse conditions in youngsters and targeted interventions could help mitigate the progression of multimorbidity in later life.

A voxel-based morphometry investigation of brain structure variations in late-life depression with insomnia.

Background: Late-life depression (LLD) is linked to various medical conditions and influenced by aging-related processes. Sleep disturbances and insomnia symptoms may be early indicators or risk factors for depression. Neuroimaging studies have attempted to understand the neural mechanisms underlying LLD, focusing on different brain networks. This study aims to further delineate discriminative brain structural profiles for LLD with insomnia using MRI. Methods: We analyzed 24 cases in the LLD with insomnia group, 26 cases in the LLD group, and 26 in the healthy control (HC) group. Patients were evaluated using the Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Rating Scale (HAMA), Mini-Mental State Examination (MMSE), and Pittsburgh Sleep Quality Index (PSQI). Structural MRI data were gathered and analyzed using voxel-based morphometry (VBM) to identify differences in gray matter volume (GMV) among the groups. Correlation analyses were conducted to explore the relationships between GMV and clinical characteristics. Results: Significant difference in sex distribution was observed across the groups (p = 0.029). However, no significant differences were detected in age and MMSE scores among the groups. LLD with insomnia group exhibited significantly higher HAMA (p = 0.041) and PSQI scores (p < 0.05) compared to the LLD group. ANOVA identified significant difference in GMV of anterior lobe of cerebellum (peak MNI coordinate: x = 52, y = -40, z = -30) among HC, LLD, and LLD with insomnia. Post-hoc two-sample t-tests revealed that the significant difference in GMV was only found between the LLD group and the HC group (p < 0.05). The mean GMV in the cerebellum was positively correlated with HAMA scale in LLD patients (r = 0.47, p < 0.05). Conclusion: There is significant difference in GMV in the LLD group, the association between late-life depression and insomnia may be linked to anxiety. This study provides insights into the discriminative brain structural profiles of LLD and LLD with insomnia, advancing the understanding of the underlying neural mechanisms and potential targets for intervention.

Inflammation and Late-Life Depression: Unraveling the Complex Relationship and Potential Therapeutic Strategies.

The origins of late-life depression are multifaceted and remain challenging to fully understand. While the traditional monoamine neurotransmitter hypothesis provides some insights, it falls short in explaining the disease's onset and progression, leaving treatments often less than optimal. There is an emergent need to uncover new underlying mechanisms. Among these, the "inflammation hypothesis" has been gaining traction in scientific discussions regarding late-life depression. There is compelling evidence linking inflammation processes to the emergence of this form of depression. This review delves into the nuanced relationship between inflammation and late-life depression, emphasizing the pivotal role and implications of inflammation in its pathogenesis. Changes in Ca2+ homeostasis, cytokine levels, brain-derived neurotrophic factor (BDNF), white cell ratios, and the involvement of the NOD-, LRR-, and Pyrin domain-containing protein 3 (NLRP3) inflammasome have all been suggested as potential biomarkers that tie inflammation to late-life depression. Furthermore, factors such as aging-induced DNA damage, oxidative stress, mitochondrial impairments, disruptions in the hypothalamic-pituitary-adrenal axis, activated microglia and associated neuroinflammation, as well as the gut-brain axis dynamics, could serve as bridges between inflammation and depression. Deepening our understanding of these connections could usher in innovative anti-inflammatory treatments and strategies for late- life depression.

[Effect of Social Support on Multimorbidity and Related Outcomes of Middle-Aged and Older Adults in China].

Objective: To analyze the current status of social support for middle-aged and older adults with multimorbidity and to explore the correlation between different dimensions of social support and multimorbidity and the related outcomes on the basis of China Health and Retirement Longitudinal Study (CHARLS) 2015 survey data so as to reveal the complex social background of multimorbidity and the impact of social support on multimorbidity. Methods: A total of 9168 valid samples, with an average age of 59.60 years, were included in the study. Using the social support-related variables of the respondents, we conducted factor analysis and constructed regression models of common factors of social support and multimorbidity-related outcomes, intending to analyze the impact of common factors of social support on multimorbidity in the middle-aged and older adults. Results: The multimorbidity of middle-aged and older adults in China was related to multiple factors of social support, and the differences were statistically significant. Logistic regression showed that social support in the form of activity/recreational facilities and medical resources was a protective factor of multimorbidity, that family emotional support and economic support had a positive effect on life satisfaction of comorbid patients, and that social support in the form of education, social life and housing conditions was negatively correlated with catastrophic medical expenditure of the comorbid population ( P<0.05). Conclusion: Social support for middle-aged and older adults in China is unevenly distributed. Social support in the form of activity/recreational facilities and medical resources may reduce the risks of multimorbidity among middle-aged and older adults. Good family economic and emotional support can improve the life satisfaction of middle-aged and older adults with multimorbidity. Social support in the form of education, social life and housing conditions may reduce the risk of catastrophic medical expenditure in middle-aged and older adults with multimorbidity.

Influence of Internet Celebrity Medical Experts on COVID-19 Vaccination Intention of Young Adults: An Empirical Study From China.

With the continuous expansion of COVID-19, many medical experts with the characteristics of "Internet Celebrities" are increasingly influencing people's vaccination behavior, which is crucial for overall social welfare. To explore the influence of Internet celebrity medical experts on people's vaccination against COVID-19, this study constructed a conceptual model of COVID-19 vaccination intention based on the professionalism, morality, interaction dimension, and information content of Internet celebrity medical experts, to generate perceived value by establishing a trusting relationship between them and the influenced people. The empirical analysis shows that interactivity and information content are important factors determining the influence of Internet celebrity medical experts. In the context of high demands for COVID-19 vaccines, it is more effective to influence vaccination intention through strong demand than through generating trust. The empirical analysis shows that Internet celebrity medical experts have a significant role in COVID-19 vaccination, and interactivity and information content are two important factors determining the influence. Through the connection of information-demand, Internet celebrity medical experts can greatly influence the perceived value, by coaction with trust to influence the final intention. Therefore, the COVID-19 vaccination persuasion information released by Internet celebrity medical experts should be elaborately organized and demonstrated, especially from the demand aspect, and government could put more resources to support the information to spread.