Predictive model of psychological distress in family caregivers of patients with cancer: a cross-sectional study.

PURPOSE: To examine a predictive theoretical model of psychological distress based on the following variables reflected on family caregivers of patients with cancer: the unmet supportive care needs, subjective caregiving burden, social support, and the positive aspects of caregiving. METHODS: A cross-sectional descriptive study was conducted on a sample of 484 dyads of patients and their family caregivers. The caregivers completed structured questionnaires designed to measure psychological distress, unmet supportive care needs, subjective caregiving burden, positive aspects of caregiving, and social support. Patients' demographic variables and medical data were collected from a medical record review. We used a structural equation modeling to test the predictive theoretical model. RESULTS: Path analysis results partially supported the proposed model with satisfactory fit indices. Specifically, family caregivers with an increasing number of unmet needs or a heavier caregiving burden were more likely to have more severe psychological distress. Bootstrapping results supported that the caregiving burden and social support were significant mediators. Greater unmet supportive care needs predicted higher psychological distress through increasing caregiving burden. Stronger social support predicted lower psychological distress through decreasing caregiving burden. Positive aspects of caregiving predicted lower caregiving burden through the increasing perceived social support, which in turn eliminated psychological distress. CONCLUSIONS: Unmet supportive care needs could cause psychological distress through increasing caregiving burden. The positive aspects of caregiving reduced caregiving burden through increasing social support, which subsequently alleviated psychological distress. Interventions that aim to satisfy supportive care needs, to reduce caregiving burden, and to strengthen social support ties may boost the mental health of family caregivers.

Association of Visceral Adiposity Surrogates with Impaired Fasting Glucose in Nonobese Individuals.

Background: Nonobese individuals with disproportionate body fat distribution are also vulnerable to dysglycemia. This study aimed to evaluate the association between three visceral adiposity surrogates and impaired fasting glucose (IFG) in nonobese Chinese individuals. Methods: A total of 70,200 nonobese adults without diabetes were included in this analysis. Two diagnostic criteria (IFG-ADA and IFG-WHO) were used to define IFG. The values of the visceral adiposity index, lipid accumulation product index (LAP), and cardiometabolic index (CMI) were calculated. Multivariable logistic analysis was used to evaluate the association between these surrogates and IFG. Results: Among the three indicators, only LAP and CMI were positively correlated with fasting plasma glucose (all P < 0.001). After fully adjusting for confounders, only LAP and CMI exhibited significant associations with IFG. For women, the odds ratios (ORs) for IFG-ADA in the highest quartile of the LAP and CMI were 1.967 (95% confidence interval [CI]: 1.645-2.353) and 1.594 (95% CI: 1.383-1.836), respectively; and were 2.025 (95% CI: 1.597-2.567) and 2.017 (95% CI: 1.647-2.470), respectively, for IFG-WHO (all P < 0.001). For men, the ORs for IFG-ADA of the LAP and CMI were 1.503 (95% CI: 1.233-1.833) and 2.045 (95% CI: 1.752-2.388), respectively; and were 1.534 (95% CI: 1.174-2.005) and 2.541 (95% CI: 2.025-3.188), respectively, for IFG-WHO (all P < 0.001). Conclusions: The LAP and CMI, cost-effective and simple visceral adiposity surrogates, are strongly associated with IFG in nonobese Chinese individuals. These surrogates might be potential targets to monitor for the recognition and management of excess visceral adiposity in nonobese individuals with prediabetes.

The resilience status of empty-nest elderly in a community: A latent class analysis.

OBJECTIVE: The aim of this study was to examine the status and characteristics of resilience among empty-nest elderly in a community in China using exploratory latent class analysis (LCA). METHODS: This study enrolled 250 empty-nest elderly as the study respondents. General information regarding the resilience of empty-nest elderly was investigated using the General Information Questionnaire and Connor-Davidson Resilience Scale, Chinese version, and we then used LCA and multivariate logistic regression to discuss the characteristics of resilience among empty-nest elderly individuals. RESULTS: Through the analysis, we found that the resilience of empty-nest elderly had obvious group characteristics and that statistical indicators can support the three categories of potential model. On the basis of the conditional probability on the various items of the questionnaire in each category, they were named "high resilience group," "low pressure resilience group," and "low resilience group," and the proportion was 26.6%, 40.4%, and 32.9%, respectively. Further study showed that age, marital status, education level, relationship with children, and physical exercise had a significant effect on the high resilience group compared to the low resilience group. Gender, education level, relationship with children, and physical exercise had a significant effect on the low pressure resilience group compared to the low resilience group. CONCLUSIONS: The resilience status of empty-nest elderly in communities can be divided into three categories. Each category had different characteristics of demographic information.