8 research outputs found
Urban–Rural Differences in Older Adult Depression: A Systematic Review and Meta-analysis of Comparative Studies
Context: Depression among older adults (aged 60 years or older) is a problem that could be exacerbated by global trends in urbanization and population aging. The study purpose was to assess whether urban, relative to rural, residence is associated with depression among older adults and whether associations differ in countries with developed versus developing economies. Evidence acquisition: In 2017, the authors identified and extracted information from comparative studies of urban–rural depression prevalence among older adults. Studies were identified in PubMed, PsychINFO, and Web of Science and limited to English language articles published after 1985. Eighteen studies met inclusion criteria. Random effects meta-analysis was conducted to produce weighted pooled ORs estimating the association between urban–rural residence and depression for all study participants (N=31,598) and sub-analyses were conducted for developed (n=12,728) and developing (n=18,870) countries. Evidence synthesis: Depression prevalence was significantly higher among urban residents in ten studies and significantly higher among rural residents in three studies (all three conducted in China). Associations between urban–rural residence and depression generally remained significant after adjusting for covariates. In developed countries, the odds of depression were significantly higher among urban than rural residents (pooled OR=1.44, 95% CI=1.10, 1.88). However, in developing countries, this association was not observed (pooled OR=0.91, 95% CI=0.46, 1.77). Conclusions: Converging trends of urbanization and population aging could increase the global burden of depression among older adults. The pathways through which urban–rural residence influences depression risk among older adults might differ by country context. Future research should focus on measuring variation in these contexts
Examining the possible impact of daily transport on depression among older adults using an agent-based model
_Objectives:_ Daily transport may impact depression risk among older adults through several pathways including facilitating the ability to meet basic needs, enabling and promoting contact with other people and nature, and promoting physical activity (e.g. through active transportation such as walking or walking to public transit). Both daily transport and depression are influenced by the neighborhood environment. To provide insights into how transport interventions may affect depression in older adults, we developed a pilot agent-based model to explore the contribution of daily transport and neighborhood environment to older adults’ depression in urban areas.
_Method:_ The model includes about 18,500 older adults (i.e. agents) between the ages of 65 and 85Â years old, living in a hypothetical city. The city has a grid space with a number of neighborhoods and locations. Key dynamic processes in the model include aging, daily transport use and feedbacks, and the development of depression. Key parameters were derived from US data sources. The model was validated using empirical studies.
_Results:_ An intervention that combines a decrease in bus fares, shorter bus waiting times, and more bus lines and stations is most effective at reducing depression. Lower income groups are likely to be more sensitive to the public transit-oriented intervention.
_Conclusion:_ Preliminary results suggest that promoting public transit use may be a promising strategy to increase daily transport and decrease depression. Our results may have implications for transportation policies and interventions to prevent depression in older adults
Depression and alcohol misuse among older adults: exploring mechanisms and policy impacts using agent-based modelling
Purpose: To: (1) explore how multi-level factors impact the longitudinal prevalence of depression and alcohol misuse among urban older adults (≥ 65 years), and (2) simulate the impact of alcohol taxation policies and targeted interventions that increase social connectedness among excessive drinkers, socially isolated and depressed older adults; both alone and in combination. Methods: An agent-based model was developed to explore the temporal co-evolution of depression and alcohol misuse prevalence among older adults nested in a spatial network. The model was based on Los Angeles and calibrated longitudinally using data from the Multi-Ethnic Study of Atherosclerosis. Results: Interventions with a social component targeting depressed and socially isolated older adults appeared more effective in curbing depression prevalence than those focused on excessive drinkers. Targeting had similar impacts on alcohol misuse, though the effects were marginal compared to those on depression. Alcohol taxation alone had little impact on either depression or alcohol misuse trajectories. Conclusions: Interventions that improve social connectedness may reduce the prevalence of depression among older adults. Targeting considerations could play an important role in determining the success of such efforts
Complex Systems Approaches to Understand Drivers of Mental Health and Inform Mental Health Policy: A Systematic Review
We conducted a systematic review of studies employing complex systems approaches (i.e., agent based and system dynamics models) to understand drivers of mental health and inform mental health policy. We extracted key data (e.g., purpose, design, data) for each study and provide a narrative synthesis of insights generated across studies. The studies investigated drivers and policy intervention strategies across a diversity of mental health outcomes. Based on these studies and the extant literature, we propose a typology of mental health research and policy areas that may benefit from complex systems approaches
Complex Systems Approaches to Understand Drivers of Mental Health and Inform Mental Health Policy: A Systematic Review
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field