Associations between depressive symptom clusters and care utilization and costs among community‐dwelling older adults

Author(s):  
Shiyu Lu ◽  
Yan Zhang ◽  
Tianyin Liu ◽  
Dara, K. Y. Leung ◽  
Wai‐Wai Kwok ◽  
...  
Author(s):  
Martino Belvederi Murri ◽  
Luigi Grassi ◽  
Rosangela Caruso ◽  
Maria Giulia Nanni ◽  
Luigi Zerbinati ◽  
...  

2020 ◽  
Vol 3 (12) ◽  
pp. e2030090 ◽  
Author(s):  
Elizabeth A. Jacobs ◽  
Rebecca Schwei ◽  
Scott Hetzel ◽  
Jane Mahoney ◽  
Katherine Sebastian ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jasmine C. Mah ◽  
Susan J. Stevens ◽  
Janice M. Keefe ◽  
Kenneth Rockwood ◽  
Melissa K. Andrew

Abstract Background Older adults want to live at home as long as possible, even in the face of circumstances that limit their autonomy. Home care services reflect this emergent preference, allowing older adults to ‘age in place’ in familiar settings rather than receiving care for chronic health conditions or ageing needs in an institutionalized setting. Numerous social factors, generally studied in isolation, have been associated with home care utilization. Even so, social circumstances are complex and how these factors collectively influence home care use patterns remains unclear. Objectives To provide a broad and comprehensive overview of the social factors influencing home care utilization; and to evaluate the influence of discrete social factors on patterns of home care utilization in community-dwelling older adults in high-income countries. Methods A scoping review was conducted of six electronic databases for records published between 2010 and 2020; additional records were obtained from hand searching review articles, reference lists of included studies and documents from international organisations. A narrative synthesis was presented, complemented by vote counting per social factor, harvest plots and an evaluation of aggregated findings to determine consistency across studies. Results A total of 2,365 records were identified, of which 66 met inclusion criteria. There were 35 discrete social factors grouped into four levels of influence using a socio-ecological model (individual, relationship, community and societal levels) and grouped according to outcome of interest (home care propensity and intensity). Across all studies, social factors consistently showing any association (positive, negative, or equivocal in pattern) with home care propensity were: age, ethnicity/race, self-assessed health, insurance, housing ownership, housing problems, marital status, household income, children, informal caregiving, social networks and urban/rural area. Age, education, personal finances, living arrangements and housing ownership were associated with home care intensity, also with variable patterns in utilization. Additional community and societal level factors were identified as relevant but lacking consistency across the literature; these included rurality, availability of community services, methods of financing home care systems, and cultural determinants. Conclusion This is the first literature review bringing together a wide range of reported social factors that influence home care utilization. It confirms social factors do influence home care utilization in complex interactions, distinguishes level of influences at which these factors affect patterns of use and discusses policy implications for home care reform.


2017 ◽  
Vol 31 (2) ◽  
pp. 280-292 ◽  
Author(s):  
Richard E. Kennedy ◽  
Courtney P. Williams ◽  
Patricia Sawyer ◽  
Alexander X. Lo ◽  
Kay Connelly ◽  
...  

Objective: To determine whether decline in life-space mobility predicts increased health care utilization among community-dwelling older adults. Method: Health care utilization (number of emergency department [ED] visits and hospitalizations) was self-reported during monthly interviews among 419 community-dwelling African American and non-Hispanic White adults aged 75 years and older in The University of Alabama at Birmingham (UAB) Study of Aging II. Life-space was measured using the UAB Life-Space Assessment. Generalized estimating equations were used to examine associations of life-space at the beginning of each interval with health care utilization over the 1-month interval. Results: Overall, 400 participants were followed for 36 months. A 10-point decrease in life-space was associated with 14% increased odds of an ED visit and/or hospitalization over the next month, adjusting for demographics, transportation difficulty, comorbidity, and having a doctor visit in the last month. Discussion: Life-space is a practical alternative in predicting future health care utilization to performance-based measures, which can be difficult to incorporate into clinical or public health practice.


2021 ◽  
Author(s):  
Chiyoung Lee ◽  
Xiao Hu

Abstract This cross-sectional study investigated the sex differences in depressive symptom networks among community-dwelling older adults in Korea. The analysis was based on the 2019 Korean Community Health Survey data targeting older adults aged 65 years or older. Using network analysis, depressive symptom networks were constructed according to the items listed in the Patient Health Questionnaire-9 for propensity score-matched male (n = 1,885) and female groups (n = 2,848). Strength centrality and network stability were tested. A network comparison test was performed to compare the global strength, network structure, and specific edge strength between the networks. Symptoms central to the network were similar between sexes, which were suicidal ideation, hopelessness, and psychomotor retardation/agitation. However, the global structure (S = 0.67, p = .008) and network structure (M = 0.11, p = .043) differed between sexes. The female symptom network showed more strengthened edges (Smale = 2.00; Sfemale = 2.66). Particularly, four edges—loss of interest–hopelessness (E = 0.09, p = .016), sleep disturbance–low energy/fatigue (E = 0.11, p = .005), loss of interest–concentration difficulty (E = 0.05, p = .047), and worthlessness–concentration difficulty (E = 0.08, p = .045)—were more pronounced in the female network. Our results may help guide future research and clinical interventions for female depression.


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