Multilevel Analysis in Rural Cancer Control: A Conceptual Framework and Methodological Implications

Rural populations experience a myriad of cancer disparities ranging from lower screening rates to higher cancer mortality rates. These disparities are due in part to individual-level characteristics like age and insurance status, but the physical and social context of rural residence also plays a role. Our objective was two-fold: 1) to develop a multilevel conceptual framework describing how rural residence and relevant micro, macro, and supra-macro factors can be considered in evaluating disparities across the cancer control continuum and 2) to outline the unique considerations of multilevel statistical modeling in rural cancer research. We drew upon several formative frameworks that address the cancer control continuum, population-level disparities, access to health care services, and social inequities. Micro-level factors comprised individual-level characteristics that either predispose or enable individuals to utilize health care services or that may affect their cancer risk. Macro-level factors included social context (e.g. domains of social inequity) and physical context (e.g. access to care). Rural-urban status was considered a macro-level construct spanning both social and physical context, as “rural” is often characterized by sociodemographic characteristics and distance to health care services. Supra-macro-level factors included policies and systems (e.g. public health policies) that may affect cancer disparities. Our conceptual framework can guide researchers in conceptualizing multilevel statistical models to evaluate the independent contributions of rural-urban status on cancer while accounting for important micro, macro, and supra-macro factors. Statistically, potential collinearity of multilevel model predictive variables, model structure, and spatial dependence should also be considered

Therapeutic landscapes and networks in restricted lives: Constructing restorative experiences among Indonesian female domestic workers in Hong Kong

This research explores the connections between therapeutic landscapes (TLs) and therapeutic networks (TNs) among women who work in domestic employment and experience severe space-time constraints in their everyday lives. Although these connections are often recognized, the links between TL and TN have not been widely investigated. Based on an online survey of 190 Indonesian female domestic workers (FDWs) in Hong Kong, therapeutic landscape locations were identified. Open-ended quotes describing characteristics and benefits of TL were analyzed via MAXQDA and incorporated in qualitative mapping in ArcGIS Pro 2.6. Results showed four types of therapeutic landscape (green spaces, blue spaces, religious sites, and built environment) that were crucial in enhancing FDWs’ wellbeing on their rest day. FDWs’ relationships with health-promoting places and efforts in creating restorative experiences were tied to their social interactions, as TNs and TLs were created synergistically. For the understudied population of FDWs, our findings highlight the importance of both the mandated rest day and public spaces including parks, beaches, and buildings, for sustaining FDWs wellbeing despite their highly restricted daily lives

On Epidemiology and Geographic Information Systems: A Review and Discussion of Future Directions

Geographic information systems are powerful automated systems for the capture, storage, retrieval, analysis, and display of spatial data. While the systems have been in development for more than 20 years, recent software has made them substantially easier to use for those outside the field. The systems offer new and expanding opportunities for epidemiology because they allow an informed user to choose between options when geographic distributions are part of the problem. Even when used minimally, these systems allow a spatial perspective on disease. Used to their optimum level, as tools for analysis and decision making, they are indeed a new information management vehicle with a rich potential for public health and epidemiology