Development of a dynamic framework to explain population patterns of leisure-time physical activity through agent-based modeling.

Despite the increasing body of evidences on the factors influencing leisure-time physical activity, our understanding of the mechanisms and interactions that lead to the formation and evolution of population patterns is still limited. Moreover, most frameworks in this field fail to capture dynamic processes. Our aim was to create a dynamic conceptual model depicting the interaction between key psychological attributes of individuals and main aspects of the built and social environments in which they live. This conceptual model will inform and support the development of an agent-based model aimed to explore how population patterns of LTPA in adults may emerge from the dynamic interplay between psychological traits and built and social environments. We integrated existing theories and models as well as available empirical data (both from literature reviews), and expert opinions (based on a systematic expert assessment of an intermediary version of the model). The model explicitly presents intention as the proximal determinant of leisure-time physical activity, a relationship dynamically moderated by the built environment (access, quality, and available activities) - with the strength of the moderation varying as a function of the person's intention- and influenced both by the social environment (proximal network's and community's behavior) and the person's behavior. Our conceptual model is well supported by evidence and experts' opinions and will inform the design of our agent-based model, as well as data collection and analysis of future investigations on population patterns of leisure-time physical activity among adults

Neighborhood Social Resources and Depressive Symptoms: Longitudinal Results from the Multi-Ethnic Study of Atherosclerosis

The ways in which a neighborhood environment may affect depression and depressive symptoms have not been thoroughly explored. This study used longitudinal data from 5475 adults in the Multi-Ethnic Study of Atherosclerosis to investigate associations of time-varying depressive symptoms between 2000 and 2012 (measured using the 20-item Center for Epidemiologic Studies Depression Scale (CES-D)) with survey-based measures of neighborhood safety and social cohesion (both individual-level perceptions and neighborhood-level aggregates) and densities of social engagement destinations. Linear mixed models were used to examine associations of baseline cross-sectional associations and cumulative exposures with changes over time in CES-D. Econometric fixed effects models were utilized to investigate associations of within-person changes in neighborhood exposures with within-person changes in CES-D. Adjusting for relevant covariates, higher safety and social cohesion and greater density of social engagement destinations were associated with lower CES-D at baseline. Greater cumulative exposure to these features was not associated with progression of CES-D over 10 years. Within-person increases in safety and in social cohesion were associated with decreases in CES-D, although associations with cohesion were not statistically significant. Social elements of neighborhoods should be considered by community planners and public health practitioners to achieve optimal mental health

Walkability and cardiometabolic risk factors: Cross-sectional and longitudinal associations from the Multi-Ethnic Study of Atherosclerosis

We used data from 3,227 older adults in the Multi-Ethnic Study of Atherosclerosis (2004–2012) to explore cross-sectional and longitudinal associations between walkability and cardiometabolic risk factors. In cross-sectional analyses, linear regression was used to estimate associations of Street Smart Walk Score® with glucose, triglycerides, HDL and LDL cholesterol, systolic and diastolic blood pressure, and waist circumference, while logistic regression was used to estimate associations with odds of metabolic syndrome. Econometric fixed effects models were used to estimate longitudinal associations of changes in walkability with changes in each risk factor among participants who moved residential locations between 2004 and 2012 (n=583). Most cross-sectional and longitudinal associations were small and statistically non-significant. We found limited evidence that higher walkability was cross-sectionally associated with lower blood pressure but that increases in walkability were associated with increases in triglycerides and blood pressure over time. Further research over longer time periods is needed to understand the potential for built environment interventions to improve cardiometabolic health

Built environment change and change in BMI and waist circumference: Multi‐ethnic S tudy of A therosclerosis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109571/1/oby20873.pd

How much are built environments changing, and where?: Patterns of change by neighborhood sociodemographic characteristics across seven U.S. metropolitan areas

Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010–2000) in sociodemographics. Spatial patterns were assessed using Global Moran’s I to measure overall clustering of change and Local Moran’s I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran’s indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time

Geographic Variations in Cardiovascular Health in the United States: Contributions of Stateâ and Individualâ Level Factors

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139063/1/jah3932.pd

Smoke before food: a tale of Baltimore City.

Not Availablehttp://deepblue.lib.umich.edu/bitstream/2027.42/78572/1/FrancoNandi2007_AJPH.pd

The association of personal and neighborhood socioeconomic indicators with subclinical cardiovascular disease in an elderly cohort. The cardiovascular health study.

There has been recent interest in determining whether neighborhood characteristics are related to the cardiovascular health of residents. However, there are no data regarding the relationship between neighborhood socioeconomic status (SES) and prevalence of subclinical cardiovascular disease (CVD) in the elderly. We related personal SES (education, income, and occupation type) and neighborhood socioeconomic characteristics (a block-group score summing six variables reflecting neighborhood income and wealth, education, and occupation) to the prevalence of subclinical CVD (asymptomatic peripheral vascular disease or carotid atherosclerosis, electrocardiogram or echocardiogram abnormalities, and/or positive responses to Rose Questionnaire claudication or angina pectoris) among 3545 persons aged 65 and over, without prevalent CVD, in the Cardiovascular Health Study. Sixty percent of participants had at least one indicator of subclinical disease. Compared to those without, those with subclinical disease had significantly lower education, income, and neighborhood scores and were more likely to have blue-collar jobs. After adjustment for age, gender, and race, those in the lowest SES groups had increased prevalence of subclinical disease compared with those in the highest SES groups (OR = 1.50; 95% CI 1.21, 1.86 for income; OR = 1.41; 95% CI 1.18, 1.69 for education; OR = 1.39; 95% CI 1.16, 1.67 for block-group score). Those reporting a blue-collar lifetime occupation had greater prevalence of subclinical disease relative to those reporting a white-collar occupation (OR = 1.29; 95% CI 1.02-1.59). After adjustment for behavioral and biomedical risk factors, all of these associations were reduced. Neighborhood score tended to remain inversely associated with subclinical disease after adjustment for personal socioeconomic indicators but associations were not statistically significant. Personal income and blue-collar occupation remained significantly associated with subclinical disease after simultaneous adjustment for neighborhood score and education. Personal and neighborhood socioeconomic indicators were associated with subclinical disease prevalence in this elderly cohort. These relationships were reduced after controlling for traditional CVD risk factors.http://deepblue.lib.umich.edu/bitstream/2027.42/78989/1/NordstromDiezRoux2004_SocSciMed.pd

Associations of the Local Food Environment with Diet Quality—A Comparison of

There is growing interest in understanding how food environments affect diet, but characterizing the food environment is challenging. The authors investigated the relation between global diet measures (an empirically derived "fats and processed meats" (FPM) dietary pattern and the Alternate Healthy Eating Index (AHEI)) and three complementary measures of the local food environment: 1) supermarket density, 2) participant-reported assessments, and 3) aggregated survey responses of independent informants. Data were derived from the baseline examination (2000–2002) of the Multi-Ethnic Study of Atherosclerosis, a US study of adults aged 45–84 years. A healthy diet was defined as scoring in the top or bottom quintile of AHEI or FPM, respectively. The probability of having a healthy diet was modeled by each environment measure using binomial regression. Participants with no supermarkets near their homes were 25–46% less likely to have a healthy diet than those with the most stores, after adjustment for age, sex, race/ethnicity, and socioeconomic indicators: The relative probability of a healthy diet for the lowest store density category versus the highest was 0.75 (95% confidence interval: 0.59, 0.95) for the AHEI and 0.54 (95% confidence interval: 0.42, 0.70) for FPM. Similarly, participants living in areas with the worst-ranked food environments (by participants or informants) were 22–35% less likely to have a healthy diet than those in the best-ranked food environments. Efforts to improve diet may benefit from combining individual and environmental approaches.http://deepblue.lib.umich.edu/bitstream/2027.42/58345/1/Associations of the local food environment with diet quality - A comparison of Assessments based on surveys .pd

Prevalence and social correlates of cardiovascular disease risk factors in Harlem

http://deepblue.lib.umich.edu/bitstream/2027.42/55440/1/Diez Roux AV, Prevalence and social correlates of cardiovascular disease risk factors in Harlem, 1999.pd