Background And Objectives: There is increasing acknowledgment that loneliness is associated with neighborhood characteristics in addition to individual characteristics. We use four waves of geocoded data to examine longitudinal associations between neighborhood characteristics and loneliness of older adults.
Research Design And Methods: We draw on "person-environment fit" theory, utilizing individual assessments of neighborhoods, while also creating aggregate assessments by combining responses from other respondents from the same geographic area to test associations with loneliness.
Results: Random-effects models demonstrate that both individual and aggregate assessments of neighborhoods are related to loneliness, however, in models that include control variables, the associations between aggregate assessments of neighborhood and loneliness were attenuated. Fixed-effects models show only individual assessments of the neighborhood are associated with variations in loneliness.
Discussion And Implications: Consistent with the "person-environment fit" theory, loneliness appears more sensitive to individual assessments of the neighborhood, irrespective of others' assessments. Our findings point to the subjective nature of loneliness and suggest that measures to reduce loneliness should focus on understanding and addressing individual perceptions of neighborhoods, emphasizing the importance of promoting age-friendly environments.
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http://dx.doi.org/10.1093/geroni/igaf006 | DOI Listing |
Background: Under the definition of positive mental health, the present study focused on the emerging group of floating elderly to explore the impact and mediating mechanisms of bonding and bridging neighbourhood social capital on their mental health.
Methods: The data were sourced from community surveys in three major cities in Guangdong Province, China, with a total of 659 respondents aged 55 and above. Structural equation modelling was used to verify the hypotheses proposed in this study.
Innov Aging
January 2025
Australian Research Council of Excellence for Children and Families over the Life Course, Brisbane, Australia.
Background And Objectives: There is increasing acknowledgment that loneliness is associated with neighborhood characteristics in addition to individual characteristics. We use four waves of geocoded data to examine longitudinal associations between neighborhood characteristics and loneliness of older adults.
Research Design And Methods: We draw on "person-environment fit" theory, utilizing individual assessments of neighborhoods, while also creating aggregate assessments by combining responses from other respondents from the same geographic area to test associations with loneliness.
Background: Research has established a bidirectional association between sleep disturbances and depression in both adults and youth, as well as links between depression and circadian rhythms and chronotype, predominantly in adult populations. However, the link between chronotype and depression in the general adolescent population, independently of poor sleep and prior mental health problems, remains unclear.
Methods: This study investigated the association between time-to-sleep (TTS) and depressive symptoms in middle adolescence (age 14 years) using data from a large, nationally representative birth cohort from the UK.
Sci Rep
March 2025
University of Wollongong, Wollongong, 2259, Australia.
As a primary approach to address feature selection problems, evolutionary algorithms have been widely proposed to deal with the problem. Most of these methods are designed to find a single feature subset. However, the optimal feature subset within a dataset is often not unique, indicating that feature selection exhibits multimodal characteristics.
View Article and Find Full Text PDFAcad Pediatr
March 2025
Department of Pediatrics, University of Massachusetts Memorial Medical Center, University of Massachusetts Chan School of Medicine.
Objectives: Among US children with low birth weight (LBW): (1) Determine prevalence of school readiness (being "healthy and ready to learn"); (2) Examine associations between school readiness and medical factors (special healthcare needs, birth weight), sociodemographic characteristics (child race/ethnicity, household income, parental education, household language), community supports (early intervention/special education, outside childcare, medical home, neighborhood amenities), parent factors (mental health, emotional support, family resilience), and parenting practices (bedtime, mealtime, storytelling routines; daily screentime).
Methods: We studied 1421 children 3-5 years with birth weight <2500g from the 2016-19 National Survey of Children's Health. We calculated prevalence of school readiness overall and in individual domains (early learning skills, physical health/motor development, social emotional development, self-regulation).
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