In network theory depression is conceptualized as a complex network of individual symptoms that influence each other, and central symptoms in the network have the greatest impact on other symptoms. Clinical features of depression are largely determined by sociocultural context. No previous study examined the network structure of depressive symptoms in Hong Kong residents. The aim of this study was to characterize the depressive symptom network structure in a community adult sample in Hong Kong during the COVID-19 pandemic. A total of 11,072 participants were recruited between 24 March and 20 April 2020. Depressive symptoms were measured using the Patient Health Questionnaire-9. The network structure of depressive symptoms was characterized, and indices of “strength”, “betweenness”, and “closeness” were used to identify symptoms central to the network. Network stability was examined using a case-dropping bootstrap procedure. Guilt, Sad Mood, and Energy symptoms had the highest centrality values. In contrast, Concentration, Suicide, and Sleep had lower centrality values. There were no significant differences in network global strength (p = 0.259), distribution of edge weights (p = 0.73) and individual edge weights (all p values > 0.05 after Holm–Bonferroni corrections) between males and females. Guilt, Sad Mood, and Energy symptoms were central in the depressive symptom network. These central symptoms may be targets for focused treatments and future psychological and neurobiological research to gain novel insight into depression.

The purposes of this review are to describe the existing research on frailty measurement of older people and to understand their characteristics, with a focus on conceptual definitions, psychometric properties, and diagnostic accuracies. We reviewed the published literature to explore if cross‐cultural studies of different types of frailty measurements have been conducted and to determine their applicability in the community setting. Narrative review with limited electronic database search and cross reference searching of included studies was performed. Studies published after year 2001 were searched for using MEDLINE and CINAHL Plus databases with keywords. A total of 5144 search results were obtained, but only 42 frailty measurements were identified in 68 studies. For the type, three different measurements were indicated, namely, self‐report instrument (n = 17), clinical observation assessment (n = 19), and mixed frailty assessment instrument (n = 6). Only 12 (29%) measurements examined reliability and validity. Nevertheless, over 35% did not perform any psychometric testing before applying. For diagnosis accuracies, 35 (83%) frailty measurements reported the cut‐off value(s) for determining level of the frailty. However, the sensitivity (56%‐89.5%) and specificity (52%‐91.3%) varied. The applicability was also diverse and some frailty instruments should be only used in some specific population and mode of administration. This review provides an overview of three major types of frailty measurements used in different settings with different purposes. For estimating the prevalence of frailty of older people in a community, the self‐report type may be appropriate. The psychometric properties of many reviewed instruments are reported insufficiently. The cut‐off value(s) are usually suggested with diverse sensitivity and specificity. Self‐report instruments, such as Groningen Frailty Indicator (GFI) and Tilburg Frailty Indicator (TFI), are the most extensively examined in terms of satisfactory psychometric properties. Thus, GFI and TFI, with the current evidence, are recommended to be used in the community setting for frailty screening tools.

Background: The early identification of pre-frailty and frailty among older people is a global priority because of the increasing incidence of frailty and associated adverse health outcomes. This study aimed to validate the Groningen Frailty Indicator-Chinese (GFI-C), a widely used screening instrument, and determine the optimal cut-off value in Chinese communities to facilitate pre-frailty and frailty screening.Methods: This methodological study employed a cross-sectional and correlational design to examine the psychometric properties of GFI-C, namely, internal consistency, stability, and concurrent and construct validities. The appropriate cut-off values for pre-frailty and frailty screening in the receiver-operating characteristic (ROC) curve were determined through sensitivity and specificity analysis.Results: A total of 350 community older people had been assessed and interviewed by a nurse. The GFI-C showed satisfactory internal consistency (Cronbach’s α = 0.87) and two-week test-retest reliability (intra-class correlation coefficient = 0.87). Concurrent validity (r = 0.76,p < 0.001) showed a moderate correlation with Fried’s frailty phenotype. The known-groups method, hypothesis testing and confirmatory factory analysis (three-factor model; χ²/df = 2.87, TLI = 0.92, CFI = 0.93, GFI = 0.92, RMR = 0.014; RMSEA = 0.073) were suitable for the establishment of construct validity. Based on the ROC and Youden’s index, the optimal cut-off GFI-C values were 2 (sensitivity, 71.5%; specificity, 84.7%) for pre-frailty and 3 for frailty (sensitivity, 88.2%; specificity, 79.6%).Conclusions: The result indicated that GFI-C is a reliable and valid instrument for pre-frailty and frailty screening among older Chinese people in communities. For optimal diagnostic accuracy, the cut-off values of 3 for frailty and 2 for pre-frailty are recommended.

Background: Nutritional status affects the health of the public and is one of the key factors influencing social-economic development. To date, little research on the nutritional status of the Macao university student population has been conducted. Objectives: To identify and evaluate the dietary pattern and the nutritional intake among Macao university students. Methods: The Macao students were selected by the stratified cluster random sampling method. A semi-quantitative food frequency questionnaire was used to investigate food consumption. Data were analyzed through a t-test and factor analysis by using SPSS Version 24.0. Results: A total of 1230 questionnaires were distributed. From the respondents, 1067 (86.7%) were valid. In general, we identified three major dietary patterns in this population: (1) fruit and vegetable dietary pattern, characterized by abundant consumption of fruits and vegetables; (2) grain and high fat dietary pattern, characterized as high intakes of grains and animal foods; (3) high sugar dietary pattern, characterized by a large quantity of daily sugary drinks. The average daily intake of vitamin A, thiamine, calcium, and iodine were significantly lower than the Chinese Recommended Nutrient Intake (RNI) in the subjects. Conclusions: The dietary pattern of Macao students is similar to that of other Asians. Surprisingly, the daily intake of vitamin A, thiamine, calcium, and iodine by Macao university students is significantly lower than the Chinese RNI.

Objective: This methodological research aimed to investigate and compare the sensitivity and specificity of conventional and new face validation in identifying incomprehensible items empirically.Methods: A purposive sample of 15 older people living in three residential care homes (RCHs) in Hong Kong was used to evaluate a newly developed 106 items covering seven quality‐of‐life dimensions. The abbreviated Mental Test (Hong Kong version; AMT) was used as a screening tool for excluding those with impaired cognition. The interview was audiotaped, and incomprehensible items were identified by the research panel accordingly (served as the gold standard). The socio‐demographics of the respondents were described. Understandability (yes/no, conventional face validation method) and interpretability (4‐point Likert scale, new method) were compared and used to compute the Kappa value (representing chance agreement), sensitivity, and specificity analysis.Results: Fifteen older people were interviewed and responded to the structured interview of 106 items regarding understandability and interpretability. 61 items (57%) obtained 100% positive understandability while only 35 items (33%) obtained 100% correct interpretability.The Kappa coefficient was 0.388 (P < 0.001) of the chance agreement between understandability and interpretability. The panel confirmed that 32% of items required revision (i.e., incomprehensible items). The false negative rate of using the conventional approach was up to 70.59% while both the false positive and negative rates of using the new approach were low (0%–5.88%).Conclusion: This empirical evidence indicated that the conventional approach of face validation for checking incomprehensible items by older people encountered a high false negative rate. On the contrary, the new approach was recommended because it demonstrated high sensitivity and specificity and low false positive and negative rates in identifying incomprehensible items.

Depression is a common psychiatric comorbidity in individuals with end-stage renal disease (ESRD). However, the underlying biological mechanisms and the precise relationship between depression and renal failure remain unclear. While interventions such as cognitive behavioral therapy and exercise have been shown to alleviate symptoms, the interplay between these conditions and their molecular pathways is poorly understood. An integrated analysis was conducted combining bioinformatics approaches and data from the UK Biobank (UKB) cohort. The UKB study revealed a significant association between renal failure and depression. Gene expression data from the Gene Expression Omnibus (GEO) database were analyzed to identify key co-expression modules using Weighted Gene Co-expression Network Analysis (WGCNA). Protein-protein interaction (PPI) networks were constructed using the STRING database, and immune cell infiltration was assessed with the CIBERSORT tool. UKB data confirmed a robust association between renal failure and depression. Bioinformatics analyses highlighted significant enrichment in pathways related to the acute inflammatory response, specific granule lumen, and immune receptor activity. PPI network analysis identified 23 hub genes, including CYP4F2, KCNA3, KISS1R, LILRA5, and ZC3H12D, as key players in the shared pathophysiology of ESRD and depression. Validation studies further emphasized the roles of LILRA5, CYP4F2, and KISS1R in these mechanisms. This study reveals novel insights into the molecular and immune interactions underlying the comorbidity of renal failure and depression. By combining cohort and bioinformatics analyses, we identify potential therapeutic targets and pathways that may inform innovative treatment strategies.