Using an agent-based model to simulate children’s active travel to school

Abstract Background Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children’s active travel to school. Methods An agent-based model was developed to simulate children’s school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios. Results To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity. Conclusions Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school.http://deepblue.lib.umich.edu/bitstream/2027.42/112566/1/12966_2012_Article_757.pd

Loneliness, Depression, and Inflammation: Evidence from the Multi-Ethnic Study of Atherosclerosis

Objective Both objective and subjective aspects of social isolation have been associated with alterations in immune markers relevant to multiple chronic diseases among older adults. However, these associations may be confounded by health status, and it is unclear whether these social factors are associated with immune functioning among relatively healthy adults. The goal of this study was to examine the associations between perceived loneliness and circulating levels of inflammatory markers among a diverse sample of adults. Methods Data come from a subset of the Multi-Ethnic Study of Atherosclerosis (n = 441). Loneliness was measured by three items derived from the UCLA Loneliness Scale. The association between loneliness and C-reactive protein (CRP) and fibrinogen was assessed using multivariable linear regression analyses. Models were adjusted for demographic and health characteristics. Results Approximately 50% of participants reported that they hardly ever felt lonely and 17.2% felt highly lonely. Individuals who were unmarried/unpartnered or with higher depressive symptoms were more likely to report being highly lonely. There was no relationship between perceived loneliness and ln(CRP) (β = -0.051, p = 0.239) adjusting for demographic and health characteristics. Loneliness was inversely associated with ln(fibrinogen) (β = -0.091, p = 0.040), although the absolute magnitude of this relationship was small. Conclusion These results indicate that loneliness is not positively associated with fibrinogen or CRP among relatively healthy middle-aged adults

Variability and seasonality of active transportation in USA: evidence from the 2001 NHTS

<p>Abstract</p> <p>Background</p> <p>Active transportation including walking and bicycling is an important source of physical activity. Promoting active transportation is a challenge for the fields of public health and transportation. Descriptive data on the predictors of active transportation, including seasonal patterns in active transportation in the US as a whole, is needed to inform interventions and policies.</p> <p>Methods</p> <p>This study analyzed monthly variation in active transportation for the US using National Household Travel Survey 2001 data. For each age group of children, adolescents, adults and elderly, logistic regression models were used to identify predictors of the odds of active transportation including gender, race/ethnicity, household income level, geographical region, urbanization level, and month.</p> <p>Results</p> <p>The probability of engaging in active transportation was generally higher for children and adolescents than for adults and the elderly. Active transportation was greater in the lower income groups (except in the elderly), was lower in the South than in other regions of the US, and was greater in areas with higher urbanization. The percentage of people using active transportation exhibited clear seasonal patterns: high during summer months and low during winter months. Children and adolescents were more sensitive to seasonality than other age groups. Women, non-Caucasians, persons with lower household income, who resided in the Midwest or Northeast, and who lived in more urbanized areas had greater seasonal variation.</p> <p>Conclusions</p> <p>These descriptive results suggest that interventions and policies that target the promotion of active transportation need to consider socio-demographic factors and seasonality.</p

Examining the Impact of the Walking School Bus With an Agent-Based Model

We used an agent-based model to examine the impact of the walking school bus (WSB) on children’s active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at “bus stops” to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness

Integrating social and biological factors in health research: a systems view

An important focus of recent calls for interdisciplinary approaches in health research has been the integration of social and biomedical sciences in understanding the causes of ill-health. Typical models for the incorporation of social factors into biomedical research include social factors as distal antecedents of more proximate biologic factors and gene-environment interaction. Under both models the distinction between social and biologic factors remains clear-cut, and consideration of social factors is not indispensable for understanding the biologic processes leading to disease. However, recent evidence suggests that social and biologic processes are inextricably linked in systems. This paper reviews models for the incorporation of social factors into the study of health, discusses the potentialities of systems approaches, and highlights implications for population health and epidemiologyhttp://deepblue.lib.umich.edu/bitstream/2027.42/57779/1/Integrating Social and Biological Factors in Health Research A systems view.pd

The persistent puzzle of the geographic patterning of cardiovascular disease

Not Availablehttp://deepblue.lib.umich.edu/bitstream/2027.42/78521/1/DiezRoux2009_PrevMed.pd

Commentary:Estimating and understanding area health effects

http://deepblue.lib.umich.edu/bitstream/2027.42/57894/1/Commentary Estimating and understanding area health effects.pd

A glossary for multilevel analysis

http://deepblue.lib.umich.edu/bitstream/2027.42/56188/1/Diez Roux AV, A Glossary of Multilevel Analysis, 2002.pd

The contextual effect of the local food environment on residents' diets: the atherosclerosis risk in communities study

OBJECTIVES: We studied the association between the local food environment and residents' report of recommended dietary intake. METHODS: Recommended intakes of foods and nutrients for 10 623 Atherosclerosis Risk in Communities participants were estimated from food frequency questionnaires. Supermarkets, grocery stores, and full-service and fast-food restaurants were geocoded to census tracts. RESULTS: Black Americans' fruit and vegetable intake increased by 32% for each additional supermarket in the census tract (relative risk [RR] = 1.32; 95% confidence interval [CI] = 1.08, 1.60). White Americans' fruit and vegetable intake increased by 11% with the presence of 1 or more supermarket (RR = 1.11; 95% CI = 0.93, 1.32). CONCLUSIONS: These findings suggest the local food environment is associated with residents' recommended diets.http://deepblue.lib.umich.edu/bitstream/2027.42/57740/1/The Contextual Effect of the local food environment on residents diets.pd