Living alone and all-cause mortality in community-dwelling older adults: The moderating role of perceived neighborhood cohesion

"It's day to day problems:" Experiences of people with aphasia who live alone

PURPOSE

Living alone is increasing and associated with health and social risks. Aphasia compounds these risks but there is little research on how living alone interacts with aphasia. This study is a preliminary exploration of this issue.

METHOD

Five people with aphasia who lived alone participated in two supported semi-structured interviews, with the second interview including sharing an artefact that held significance for living alone with aphasia. Interviews were recorded, transcribed verbatim, and analysed through reflexive thematic analysis.

RESULT

Four themes encompassed meaning-making about living alone with aphasia: relationships and reliance on others; risk, vulnerability, and uncertainty; loneliness and time alone; self-reliance and the need to keep busy. Participants had to continuously manage and renegotiate daily challenges around living alone with aphasia.

CONCLUSION

Living alone increases the risk of loneliness. For people with aphasia, the buffer against loneliness provided by social connection and meaningful activity may be more difficult to achieve because of communication challenges. While experiences vary, reliance on others, managing practical and administrative tasks, and negotiating risks are all important issues when alone. The intersection of living alone, loneliness, and living with aphasia needs more research, and more explicit clinical focus when discussing and planning intervention and support.

A national cohort study of community belonging and its influence on premature mortality

BACKGROUND

Community belonging, an important constituent of subjective well-being, is an important target for improving population health. Ageing involves transitioning across different social conditions thus, community belonging on health may vary across the life course. Using a nationally representative cohort, this study estimates the life stage-specific impact of community belonging on premature mortality.

METHODS

Six cycles of the Canadian Community Health Survey (2000-2012) were combined and linked to the Canadian Vital Statistics Database (2000-2017). Respondents were followed for up to 5 years. Multivariable-adjusted modified Poisson regression models were used to estimate the relative risk of premature mortality for three life stages: early adulthood (18-35 years), middle adulthood (36-55 years) and late adulthood (56-70 years).

RESULTS

The final analytical sample included 477 100 respondents. Most reported a 'somewhat strong' sense of belonging (45.9%). Compared with their 'somewhat strong' counterparts, young adults reporting a 'somewhat weak' sense of belonging exhibited an increased relative risk (RR) of 1.76 (95% CI 1.27 to 2.43) for premature mortality, whereas middle-aged adults reporting the same exhibited a decreased RR of 0.82 (95% CI 0.69, 0.98). Among older adults, groups reporting a 'very strong' (RR 1.10, 95% CI 1.01, 1.21) or a 'very weak' sense (RR 1.14, 95% CI 1.01, 1.28) of belonging exhibited higher RRs for premature mortality.

CONCLUSION

The results demonstrate how community belonging relates to premature mortality differs across age groups underscoring the importance of considering life stage-specific perspectives when researching and developing approaches to strengthen belonging.

Social Disconnectedness, Perceived Loneliness, and Cognitive Functioning: The Role of Neighborhood Environment

Background and Objectives

Social disconnectedness and loneliness pose significant challenges for older Chinese immigrants. Yet, it remains unclear whether they are associated with an increased risk of cognitive decline in this population. This study aimed to investigate the association of social disconnectedness and loneliness with cognitive functioning and examine the moderation role of neighborhood contexts.

Research Design and Methods

This longitudinal analysis examined a sample of individuals aged 60 years and older from the Population Study of Chinese Elderly in Chicago (N = 2,044). Global cognition was assessed using the averaged z-scores of cognitive performance tests. Social disconnectedness was constructed using 5 indicators about structural aspects of social relationships. Loneliness was assessed with the R-UCLA loneliness scale. Neighborhood socioeconomic status (NSES) and neighborhood segregation index were constructed using 2010-2014 American Community Survey data at the census tract level. Individual perceptions about neighborhood environments were used to construct neighborhood cohesion index and neighborhood disorder index (NDI). Latent growth curve models with adjusted cluster robust standard errors were estimated.

Results

More loneliness was associated with a higher level of initial cognitive functioning (B = 0.030, p < .01), but also with a faster decline rate over time (B = -0.007, p < .01) after adjusting for covariates. High NSES and less neighborhood segregation buffered the negative effects of loneliness on cognitive decline, respectively. High NDI amplified the positive relationship between loneliness and initial functioning, but accelerated the rate of cognitive decline associated with loneliness.

Discussion and Implications

The study revealed that perceived loneliness, but not social disconnectedness, is a risk factor for cognitive decline among older Chinese immigrants. Living in a neighborhood with low socioeconomic status, more segregation, and high disorder elevated the detrimental effect of loneliness on long-term cognitive decline. Further research needs to investigate the complex interplay between social relationships, neighborhood environment, and cognition.

Racial and ethnic differences in predictors of participation in an intergenerational social connectedness intervention for older adults

BACKGROUND

Social connectedness is a key determinant of health and interventions have been developed to prevent social isolation in older adults. However, these interventions have historically had a low participation rate amongst minority populations. Given the sustained isolation caused by the COVID-19 pandemic, it is even more important to understand what factors are associated with an individual's decision to participate in a social intervention. To achieve this, we used machine learning techniques to model the racial and ethnic differences in participation in social connectedness interventions.

METHODS

Data were obtained from a social connectedness intervention that paired college students with Houston-area community-dwelling older adults (> 65 yo) enrolled in Medicare Advantage plans. Eligible participants were contacted telephonically and asked to complete the 3-item UCLA Loneliness Scale. We used the following machine-learning methods to identify significant predictors of participation in the program: k-nearest neighbors, logistic regression, decision tree, gradient-boosted decision tree, and random forest.

RESULTS

The gradient-boosted decision tree models yielded the best parameters for all race/ethnicity groups (96.1% test accuracy, 0.739 AUROC). Among non-Hispanic White older adults, key features of the predictive model included Functional Comorbidity Index (FCI) score, Medicare prescription risk score, Medicare risk score, and depression and anxiety indicators within the FCI. Among non-Hispanic Black older adults, key features included disability, Medicare prescription risk score, FCI and Medicare risk scores. Among Hispanic older adults, key features included depression, FCI and Medicare risk scores.

CONCLUSIONS

These findings offer a substantial opportunity for the design of interventions that maximize engagement among minority groups at greater risk for adverse health outcomes.

Neighborhood effects on the health of elderly persons: evidence from China

BACKGROUND

Presently, global aging has become increasingly serious, whereas the health concerns brought by aging have become a public issue that warrants an urgent solution from all countries across the world. Therefore, this research paper discusses the influence of neighborhood health on elderly individuals' health, and extending a realistic basis for the other economies to improve the neighborhood environment and promote the health of the elderly.

METHODS

Based on the data of CHARLS2018, this research paper adopts the samples that fulfill the study requirements (N = 7326). we constructed a comprehensive research framework integrating oprobit regression model, heterogeneity analysis, conditional mixed process(CMP)robustness testing, Furthermore, the KHB decomposition method is implemented to ascertain the influential mechanism of NMH and NPH on the mental- and physical health of elderly persons.

RESULTS

The oprobit regression model analysis indicates that NMH 0.434 and NPH 0.550 exert positive influences on the elderly's mental- and physical health. Meanwhile, the effects of conditional mixed process on NMH and NPH stand at 0.381 and4.372, which are different from the oprobit regression results; thereby, indicating the existence of endogeneity. Afterward, KHB mediating effect confirms that Internet use, gift reciprocity, and charity activity contribute 30.21% and 16.83% to mental- and physical health, respectively.

CONCLUSIONS

Firstly, the NMH and NPH demonstrate a positive influence on the mental- and physical health of the elder population. However, there exist heterogeneous differences. Secondly, the conditional mixed process deals with the endogeneity of NMH and NPH. Thirdly, social integration, social interaction, and social engagement serve as significant transmission mechanisms for the influences of NMH and NPH on the health of elderly persons.