Tse-Chuan Yang

Spatial Polygamy and Contextual Exposures (SPACEs): Promoting Activity Space Approaches in Research on Place And Health

Exposure science has developed rapidly and there is an increasing call for greater precision in the measurement of individual exposures across space and time. Social science interest in an individual’s environmental exposure, broadly conceived, has arguably been quite limited conceptually and methodologically. Indeed, in social science, we appear to lag behind our exposure science colleagues in our theories, data, and methods. In this article, we discuss a framework based on the concept of spatial polygamy to demonstrate the need to collect new forms of data on human spatial behavior and contextual exposures across time and space. Adopting new data and methods will be essential if one wants to better understand social inequality in terms of exposure to health risks and access to health resources. We discuss the opportunities and challenges focusing on the potential seemingly offered by focusing on human mobility and, specifically, the utilization of activity space concepts and data. A goal of the article is to spatialize social and health science concepts and research practice vis-à-vis the complexity of exposure. The article concludes with some recommendations for future research, focusing on theoretical and conceptual development promoting research on new types of places and human movement, the dynamic nature of contexts, and training.

Exploring the Role of the Built and Social Neighborhood Environment in Moderating Stress and Health

BackgroundHealth researchers have explored how different aspects of neighborhood characteristics contribute to health and well-being, but current understanding of built environment factors is limited.PurposeThis study explores whether the association between stress and health varies by residential neighborhood, and if yes, whether built and social neighborhood environment characteristics act as moderators.MethodsThis study uses multilevel modeling and variables derived from geospatial data to explore the role of neighborhood environment in moderating the association of stress with health. Individual-level data (N = 4,093) were drawn from residents of 45 neighborhoods within Philadelphia County, PA, collected as part of the 2006 Philadelphia Health Management Corporations Household Health Survey.ResultsWe find that the negative influence of high stress varied by neighborhood, that residential stability and affluence (social characteristics) attenuated the association of high stress with health, and that the presence of hazardous waste facilities (built environment characteristics) moderated health by enhancing the association with stress.ConclusionsOur findings suggest that neighborhood environment has both direct and moderating associations with health, after adjusting for individual characteristics. The use of geospatial data could broaden the scope of stress–health research and advance knowledge by untangling the intertwined relationship between built and social environments, stress, and health. In particular, future studies should integrate built environment characteristics in health-related research; these characteristics are modifiable and can facilitate health promotion policies.

Effect of Health Care System Distrust on Breast and Cervical Cancer Screening in Philadelphia, Pennsylvania

OBJECTIVES We investigated whether health care system distrust is a barrier to breast and cervical cancer screening and whether different dimensions of distrust-values and competence-have different impacts on cancer screening. METHODS We utilized data on 5268 women aged 18 years and older living in Philadelphia, Pennsylvania, and analyzed their use of screening services via logistic and multinomial logistic regression. RESULTS High levels of health care system distrust were associated with lower utilization of breast and cervical cancer screening services. The associations differed by dimensions of distrust. Specifically, a high level of competence distrust was associated with a reduced likelihood of having Papanicolaou tests, and women with high levels of values distrust were less likely to have breast examinations within the recommended time period. Independent of other covariates, individual health care resources and health status were associated with utilization of cancer screening. CONCLUSIONS Health care system distrust is a barrier to breast and cervical cancer screening even after control for demographic and socioeconomic determinants. Rebuilding confidence in the health care system may improve personal and public health by increasing the utilization of preventive health services.

The role of social and built environments in predicting self-rated stress: A multilevel analysis in Philadelphia

Most studies of the predictors of stress focus on individual characteristics. Linking multiple contextual data sources to an individual-level health survey, we explore the associations of both built and social environment determinants with self-rated stress. At the individual level few social factors were significant predictors, although neighborhood trust and food insecurity have independent effects on stress. At the neighborhood level, the presence of hazardous waste sites and traffic volume were determinants of self-rated stress even after controlling for other individual characteristics. The latter two factors are of relevance to public health policy as they are potentially modifiable.

Built environment and Property Crime in Seattle, 1998–2000: A Bayesian Analysis

The past decade has seen a rapid growth in the use of a spatial perspective in studies of crime. In part this growth has been driven by the availability of georeferenced data, and the tools to analyze and visualize them: geographic information systems, spatial analysis, and spatial statistics. In this paper we use exploratory spatial data analysis (ESDA) tools and Bayesian models to help better understand the spatial patterning and predictors of property crime in Seattle, Washington for 1998–2000, including a focus on built environment variables. We present results for aggregate property crime data as well as models for specific property crime types: residential burglary, nonresidential burglary, theft, auto theft, and arson. ESDA confirms the presence of spatial clustering of property crime and we seek to explain these patterns using spatial Poisson models implemented in WinBUGS. Our results indicate that built environment variables were significant predictors of property crime, especially the presence of a highway on auto theft and burglary.

Examining non-stationary effects of social determinants on cardiovascular mortality after cold surges in Taiwan.

Details about the impact of extreme cold on cardiovascular mortality are little known in the countries with warm winters like Taiwan. This study aimed to examine the ecological associations between various social determinants and cardiovascular mortality after cold surges in Taiwan with a spatial perspective focusing on spatial non-stationarity. The mortality rates at township level in Taiwan were observed from 1997 to 2003. Five social determinants (social disadvantage, lack of economic opportunity, stability, sensitive group, and rurality) were created with the 2000 Taiwan Census data. We analyzed the data using Geographically Weighted Poisson Regression. On average, an immediate increase in cardiovascular mortality was found right after cold surges. All of the five determinants were found to have spatial non-stationary effects on the cardiovascular mortality rates after cold surges. This finding provided an empirical basis for developing public health programs with local emphases on the impacts of extreme cold.

Untangling the associations among distrust, race, and neighborhood social environment: a social disorganization perspective.

Over the past decade, interest in exploring how health care system distrust is associated with individual health outcomes and behaviors has grown substantially, and the racial difference in distrust has been well documented, with African Americans demonstrating higher distrust than whites. However, relatively little is known about whether the individual-level determinants of distrust differ by various dimensions of distrust, and even less is understood regarding whether the race-distrust association could be moderated by the neighborhood social environment. This study used a dual-dimensional distrust scale (values and competence distrust), and applied social disorganization theory to address these gaps. We combined the 2008 Philadelphia Health Management Corporations household survey (N = 3746 adult respondents, 51% of which are of African American race) with neighborhood-level data (N = 45 neighborhoods) maintained by the 2000 U.S. Census and the Philadelphia Police Department. Using multilevel modeling, we found that first, after controlling for individual- and neighborhood-level covariates, African American residents have greater values distrust than whites, but no racial difference was found in competence distrust; second, competence distrust is more likely to be determined by personal health status and access to health care services than is values distrust; and third, ceteris paribus, the association between race and values distrust was weakened by the increasing level of neighborhood stability. These results not only indicate that different aspects of distrust may be determined via different mechanisms, but also suggest that establishing a stable neighborhood may ameliorate the level of distrust in the health care system among African Americans. As distrust has been identified as a barrier to medical research, the insight provided by this study can be applied to develop a health care system that is trusted, which will, in turn, improve population health.

Understanding the non-stationary associations between distrust of the health care system, health conditions, and self-rated health in the elderly: A geographically weighted regression approach

The goals of this study are to explore whether health condition is an antecedent extraneous factor for the relationship between health care system distrust and self-rated health among the elderly, and to investigate if the associations among these variables are place-specific. We used logistic geographically weighted regression to analyze data on an elderly sample residents in the Philadelphia metropolitan area. We found that the health conditions of the elderly account for the association between high distrust and poor/fair self-rated health and that the distrust/self-rated health relationship varied spatially. This finding suggests that a place-centered perspective can inform distrust/self-rated health research.

Cold surge: A sudden and spatially varying threat to health?

While cold surge is one of the most conspicuous features of the winter monsoon in East Asia, its impact on human health remains underexplored. Based on the definition by the Central Weather Bureau in Taiwan, we identified four cold surges between 2000 and 2003 and collected the cardiovascular disease mortality data 2 weeks before and 2 weeks after these events. We attempted to answer the following research questions: 1) whether the cold surges impose an adverse and immediate effect on cardiovascular mortality; 2) whether the people living in temperate zones have a higher tolerance of extreme temperature drop than those in the subtropics. With geographic weighting techniques, we not only found that the cardiovascular disease mortality rates increased significantly after the cold surges, but also discovered a spatially varying pattern of tolerance to cold surges. Even within a small study area such as Taiwan, human reaction to severe weather drop differs across space. Needless to say, in the U.S., these findings should be considered in redirecting policy to address populations living in warm places when extreme temperature drops occur.

Stochastic variability in stress, sleep duration and sleep quality across the distribution of body mass index: Insights from quantile regression

BackgroundObesity has become a problem in the USA and identifying modifiable factors at the individual level may help to address this public health concern. A burgeoning literature has suggested that sleep and stress may be associated with obesity; however, little is know about whether these two factors moderate each other and even less is known about whether their impacts on obesity differ by gender.PurposeThis study investigates whether sleep and stress are associated with body mass index (BMI) respectively, explores whether the combination of stress and sleep is also related to BMI, and demonstrates how these associations vary across the distribution of BMI values.MethodsWe analyze the data from 3,318 men and 6,689 women in the Philadelphia area using quantile regression (QR) to evaluate the relationships between sleep, stress, and obesity by gender.ResultsOur substantive findings include: (1) high and/or extreme stress were related to roughly an increase of 1.2 in BMI after accounting for other covariates; (2) the pathways linking sleep and BMI differed by gender, with BMI for men increasing by 0.77–1 units with reduced sleep duration and BMI for women declining by 0.12 unit with 1 unit increase in sleep quality; (3) stress- and sleep-related variables were confounded, but there was little evidence for moderation between these two; (4) the QR results demonstrate that the association between high and/or extreme stress to BMI varied stochastically across the distribution of BMI values, with an upward trend, suggesting that stress played a more important role among adults with higher BMI (i.e., BMI > 26 for both genders); and (5) the QR plots of sleep-related variables show similar patterns, with stronger effects on BMI at the upper end of BMI distribution.ConclusionsOur findings suggested that sleep and stress were two seemingly independent predictors for BMI and their relationships with BMI were not constant across the BMI distribution.