Neighborhood characteristics and transport walking: Exploring multiple pathways of influence using a structural equation modeling approach.
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ABSTRACT:
SUBMITTER: Li J
PROVIDER: S-EPMC7351081 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundNeighborhood walking connotes physical activity and opportunities for social and cognitive engagement and improved mental health, factors previously associated with outcomes including mortality, cardiovascular disease, and dementia. Few studies have examined correlates of neighborhood-specific walking in older adults.PurposeWe investigated the individual and neighborhood/regional correlates of neighborhood-based walking among US older adults.MethodsWe obtained cross-sectional data on ≥ 65 year olds from the population-based 2017 National Household Travel Survey (n = 73,523). Respondents completed diaries detailing trips during an assigned travel day. Adjusted logistic regression (using survey weights) tested associations between individual, neighborhood, and regional characteristics and ≥ 1 versus no neighborhood walk trips/day (from travel diary).ResultsTwelve percent had ≥ 1 neighborhood walk trip/day and 54% of the neighborhood walkers achieved ≥ 30 min of walking/day. African Americans/Blacks (versus non-Hispanic Whites) and working individuals (versus retired) had lower odds of neighborhood walking. Individuals without cars, bus/train users, and those with higher neighborhood housing density had greater odds of neighborhood walking. Utilitarian walking was less likely among African Americans/Blacks and Hispanics but more likely among Asians (versus non-Hispanic Whites). Social/recreational neighborhood walking was more likely for those without cars, bus/train users, and those with greater neighborhood housing density.ConclusionFew US older adults walked in their neighborhoods, suggesting a potentially fruitful target for health promotion efforts and community interventions to improve health and quality of life in older adults. Future work is needed to determine other neighborhood factors associated with greater neighborhood walking.
| S-EPMC7786124 | biostudies-literature
Project description:Vacant housing can produce many issues that affect residents' quality of life, especially in historically segregated communities of color. To address these challenges, local governments invest in strategic, place-based revitalization initiatives focused on the regeneration of vacant housing. Yet, the outcomes of these efforts remain contested. To maximize health benefits of revitalization investments, a more nuanced understanding of pathways between neighborhood changes and residents' responses, adaptations, and ability to thrive is necessary, though, remains largely absent in the literature. Using the Vacants to Value initiative in Baltimore, MD as a case study, we explore (1) how health manifests among certain groups in the context of vacant housing revitalization; (2) how vacant housing and its regeneration engender social and cultural environmental change i.e., gentrification; and (3) what structural determinants (cultural norms, policies, institutions, and practices) contribute to the distribution of material resources and benefits of revitalization. Results suggest that vacant housing revitalization requires more than just physical remedies to maximize health. Our findings demonstrate how vacant housing revitalization influences the physical environment, social environment, and structural determinants of material resources and community engagement that can ultimately impact residents' physical, mental, and social health. This study recommends that because housing disparities are rooted in structural inequalities, how policies, practices, and processes moderate pathways for residents to adapt and benefit from neighborhood changes is consequential for health and health equity. Establishing shared governance structures is a promising approach to foster equitable decision-making and outcomes. Going forward in urban regeneration, pathways to retain and strengthen the social environment while revitalizing the physical environment may be promising to achieve healthy communities.
| S-EPMC9675168 | biostudies-literature
Project description:BackgroundChildhood maltreatment affects social functioning in the general adult population. However, how child abuse affects functional disability in adulthood remains unknown. Thus, we investigated the correlation between child abuse, depressive symptoms, cognitive complaints, and functional disability in adult community volunteers.MethodsParticipants (N = 556) completed the Child Abuse and Trauma Scale, Patient Health Questionnaire-9, Cognitive Complaints in Bipolar Disorder Rating Assessment, and Sheehan Disability Scale. Multiple regression analyses and structural equation modeling were performed to evaluate scale correlations.ResultsStructural equation modeling showed that the direct effect of childhood maltreatment on depressive symptoms, the indirect effect of childhood maltreatment on cognitive function via depressive symptoms, and the indirect effects of childhood maltreatment on functional disability via depressive symptoms and via cognitive function were all significant. The direct effects of childhood maltreatment on cognitive function and functional disability were not significant. There was no significant association between variables.LimitationsCross-sectional designs cannot identify causal relationships between parameters. Participants were adult volunteers from the community; therefore, results may not be generalizable to individuals with psychiatric disorders. Sociodemographic variability was a limitation because we used self-reported childhood maltreatment.ConclusionsChildhood maltreatment indirectly affects functional disability via depressive symptoms and via cognitive function through depressive symptoms. We suggest that depressive symptoms and cognitive function play crucial roles in the influence of childhood maltreatment on functional disability in adult community volunteers.
| S-EPMC7529428 | biostudies-literature
Project description:Public health problems caused by rapid urbanization have attracted increasing amounts of attention. Existing studies show that improving the frequency and duration of physical activity among urban residents can effectively reduce their disease risk. A community greenway, as a green space for public activity directly serving community residents, is one of the best spatial place for bringing health benefits to people. Although the scale and scope of greenway construction have been increasing in recent years, the utilization rate of some greenways is not high for various reasons, restricting the extent to which people engage in healthy physical activities in greenway spaces. In this study, the greenway of Nancheng Community in Wenjiang District, Chengdu city, China was selected as the object of study, and structural equation modeling was conducted to explore the objective environmental factors and individual characteristics acting as barriers to use of the community greenway by the population for physical activity. The results show that user experience, the greenway landscape, and safety and accessibility are important factors that restrict people's willingness engage in physical activity in the community greenway environment. The results of this study provide a direction for further consideration of ways to enhance people's willingness to make use of greenways for physical activity, and further provide a theoretical basis for the healthy design and transformation of community greenway spaces.
| S-EPMC10392127 | biostudies-literature
Project description:Gene expression is controlled by multiple regulators and their interactions. Data from genome-wide gene expression assays can be used to estimate molecular activities of regulators within a model organism and extrapolate them to biological processes in humans. This approach is valuable in studies to better understand complex human biological systems which may be involved in diseases and hence, have potential clinical relevance. In order to achieve this, it is necessary to infer gene interactions that are not directly observed (i.e. latent or hidden) by way of structural equation modeling (SEM) on the expression levels or activities of the downstream targets of regulator genes. Here we developed an R Shiny application, termed "Structural Equation Modeling of In silico Perturbations (SEMIPs)" to compute a two-sided t-statistic (T-score) from analysis of gene expression data, as a surrogate to gene activity in a given human specimen. SEMIPs can be used in either correlational studies between outcome variables of interest or subsequent model fitting on multiple variables. This application implements a 3-node SEM model that consists of two upstream regulators as input variables and one downstream reporter as an outcome variable to examine the significance of interactions among these variables. SEMIPs enables scientists to investigate gene interactions among three variables through computational and mathematical modeling (i.e. in silico). In a case study using SEMIPs, we have shown that putative direct downstream genes of the GATA Binding Protein 2 (GATA2) transcription factor are sufficient to infer its activities in silico for the conserved progesterone receptor (PGR)-GATA2-SRY-box transcription factor 17 (SOX17) genetic network in the human uterine endometrium.
| S-EPMC8652139 | biostudies-literature
Project description:ObjectiveTo study the relationships between the different domains of quality of primary health care for the evaluation of health system performance and for informing policy decision making.Data sourcesA total of 137 quality indicators collected from 7,607 English practices between 2011 and 2012.Study designCross-sectional study at the practice level. Indicators were allocated to subdomains of processes of care ("quality assurance," "education and training," "medicine management," "access," "clinical management," and "patient-centered care"), health outcomes ("intermediate outcomes" and "patient-reported health status"), and patient satisfaction. The relationships between the subdomains were hypothesized in a conceptual model and subsequently tested using structural equation modeling.Principal findingsThe model supported two independent paths. In the first path, "access" was associated with "patient-centered care" (? = 0.63), which in turn was strongly associated with "patient satisfaction" (? = 0.88). In the second path, "education and training" was associated with "clinical management" (? = 0.32), which in turn was associated with "intermediate outcomes" (? = 0.69). "Patient-reported health status" was weakly associated with "patient-centered care" (? = -0.05) and "patient satisfaction" (? = 0.09), and not associated with "clinical management" or "intermediate outcomes."ConclusionsThis is the first empirical model to simultaneously provide evidence on the independence of intermediate health care outcomes, patient satisfaction, and health status. The explanatory paths via technical quality clinical management and patient centeredness offer specific opportunities for the development of quality improvement initiatives.
| S-EPMC5785308 | biostudies-literature
Project description:MotivationA major task in genetic studies is to identify genes related to human diseases and traits to understand functional characteristics of genetic mutations and enhance patient diagnosis. Compared to marginal analyses of individual genes, identification of gene pathways, i.e., a set of genes with known interactions that collectively contribute to specific biological functions, can provide more biologically meaningful results. Such gene pathway analysis can be formulated into a high-dimensional two-sample testing problem. Given the typically limited sample size of gene expression datasets, most existing two-sample tests tend to have compromised powers because they ignore or only inefficiently incorporate the auxiliary pathway information on gene interactions.ResultsWe propose T2-DAG, a Hotelling's T 2-type test for detecting differentially expressed gene pathways, which efficiently leverages the auxiliary pathway information on gene interactions from existing pathway databases through a linear structural equation model. We further establish its asymptotic distribution under pertinent assumptions. Simulation studies under various scenarios show that T2-DAG outperforms several representative existing methods with well-controlled type-I error rates and substantially improved powers, even with incomplete or inaccurate pathway information or unadjusted confounding effects. We also illustrate the performance of T2-DAG in an application to detect differentially expressed KEGG pathways between different stages of lung cancer.AvailabilityThe R package T2DAG is available on Github at https://github.com/Jin93/T2DAG.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC8796375 | biostudies-literature
Project description:At least 282 Food Policy Councils (FPCs) are currently working to improve access to healthy foods in their communities by connecting food system sectors, gathering community input, and advising food policy. Empirical research on FPCs is limited. This study empirically evaluates FPCs to better understand the relationships between Organizational Capacity, Social Capital, and Council Effectiveness by testing a FPC Framework adapted from Allen and colleagues (2012). Members of all FPCs in the U.S., Canada, and Native American Tribes and First Nations were invited to complete the Food Policy Council Self-Assessment Tool (FPC-SAT). Structural equation modeling was used to test the FPC Framework. Three hundred and fifty-four FPC members from 95 councils completed the FPC-SAT. After slight modification, a revised FPC Framework was a good fit with the data (?2 = 40.085, df = 24, p-value = .021, comparative fit index = 0.988, Tucker Lewis index = 0.982, root mean squared error of approximation = 0.044, p-close = .650). A moderation analysis revealed that community context influences the relationship between Social Capital and Council Effectiveness within the FPC Framework. The FPC Framework can guide capacity building interventions and FPC evaluations. The empirically tested framework can help FPCs efficiently work toward achieving their missions and improving their local food system.
| S-EPMC7262635 | biostudies-literature
Project description:ObjectivesWhen examining the relationship between smoking intensity and toxicant exposure biomarkers in an effort to understand the potential risk for smoking-related disease, individual biomarkers may not be strongly associated with smoking intensity because of the inherent variability in biomarkers. Structural equation modeling (SEM) offers a powerful solution by modeling the relationship between smoking intensity and multiple biomarkers through a latent variable.MethodsBaseline data from a randomized trial (N = 1250) were used to estimate the relationship between smoking intensity and a latent toxicant exposure variable summarizing five volatile organic compound biomarkers. Two variables of smoking intensity were analyzed: the self-report cigarettes smoked per day and total nicotine equivalents in urine. SEM was compared with linear regression with each biomarker analyzed individually or with the sum score of the five biomarkers.ResultsSEM models showed strong relationships between smoking intensity and the latent toxicant exposure variable, and the relationship was stronger than its counterparts in linear regression with each biomarker analyzed separately or with the sum score.ConclusionsSEM is a powerful multivariate statistical method for studying multiple biomarkers assessing the same class of harmful constituents. This method could be used to evaluate exposure from different combusted tobacco products.
| S-EPMC9075702 | biostudies-literature
Project description:TikTok, the most popular social media, brings various benefits to nowadays living. However, the problematic use of TikTok has also elicited a range of health problems, such as sleep problems. Physical activity (PA) appears to play a protective role in the problematic use of TikTok and its health consequences, but the pathways between PA and sleep health are understudied. Therefore, we aimed to propose a framework to check whether PA can benefit the sleep health of TikTok users by reducing bedtime delays for TikTok. Stress and mental health issues were also considered as they are potential mediators between PA and sleep health and may also influence the problematic use of smartphones. A cross-sectional investigation that involved 660 Chinese TikTok users was conducted in April 2021. The volume of PA, perceived stress (PSS-10), depression (PHQ-9), anxiety (GAD-7), bedtime delay for TikTok use, and sleep quality (PSQI) were investigated through an online questionnaire survey. Structural equation modeling was employed to examine pathways from PA to sleep quality through stress, mental health issues (depression and anxiety), and bedtime delay for TikTok. We found that PA exerted a significant effect on sleep quality through indirect pathways (β = -0.056, p = 0.001). Stress was a critical mediator of all indirect pathways, and the pathway mediated by stress and mental health issues made a major contribution to the total effect (β = -0.048, p = 0.002). The identified pathways mediated by bedtime delay for TikTok were relatively weak but significant. PA showed a distinct effect on bedtime delay for TikTok through stress and mental health issues (β = -0.043, p = 0.001). In conclusion, our framework highlights some pathways to understanding the benefits of PA on TikTok users' sleep quality. Future research is warranted to explore extra indirect pathways and re-examine the causal relationships between variables.
| S-EPMC9105446 | biostudies-literature