The purpose of this literature review is to identify how geographic information system (GIS) applications have been used in health-related research and to critically examine the issues, strengths, and challenges inherent to those approaches from the lenses of health promotion and public health. Through the review process, conducted in 2007, it is evident that health promotion and public health applications of GIS can be generally categorized into four predominant themes: disease surveillance (n = 227), risk analysis (n = 189), health access and planning (n = 138), and community health profiling (n = 115). This review explores how GIS approaches have been used to inform decision making and discusses the extent to which GIS can be applied to address health promotion and public health questions. The contribution of this literature review will be to generate a broader understanding of how GIS-related methodological techniques and tools developed in other disciplines can be meaningfully applied to applications in public health policy, promotion, and practice.

BETTER (Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Primary Care) is a patient-based intervention to improve chronic disease prevention and screening (CDPS) for cardiovascular disease, diabetes, cancer, and associated lifestyle factors in patients aged 40 to 65. The key component of BETTER is a prevention practitioner (PP), a health care professional with specialized skills in CDPS who meets with patients to develop a personalized prevention prescription, using the BETTER toolkit and Brief Action Planning. The purpose of this qualitative study was to understand facilitators and barriers of the implementation of the BETTER 2 program among clinicians, patients, and stakeholders in three (urban, rural, and remote) primary care settings in Newfoundland and Labrador, Canada. We collected and analyzed responses from 20 key informant interviews and 5 focus groups, as well as memos and field notes. Data were organized using Nvivo 10 software and coded using constant comparison methods. We then employed the Consolidated Framework for Implementation Research (CFIR) to focus our analysis on the domains most relevant for program implementation. The following key elements, within the five CFIR domains, were identified as impacting the implementation of BETTER 2: (1) intervention characteristics—complexity and cost of the intervention; (2) outer setting—perception of fit including lack of remuneration, lack of resources, and duplication of services, as well as patients’ needs as perceived by physicians and patients; (3) characteristics of prevention practitioners—interest in prevention and ability to support and motivate patients; (4) inner setting—the availability of a local champion and working in a team versus working as a team; and (5) process—planning and engaging, collaboration, and teamwork. The implementation of a novel CDPS program into new primary care settings is a complex, multi-level process. This study identified key elements that hindered or facilitated the implementation of the BETTER approach in three primary care settings in Newfoundland and Labrador. Employing the CFIR as an overarching typology allows for comparisons with other contexts and settings, and may be useful for practices, researchers, and policy-makers interested in the implementation of CDPS programs.

People's perceptions of local food environments influence their abilities to eat healthily. PhotoVoice participants from four communities in Alberta, Canada took pictures of barriers and opportunities for healthy eating and shared their stories in one-on-one semi-structured interviews. Using a socioecological framework, emergent themes were organized by type and size of environment. Findings show that, while availability and access to food outlets influence healthy eating practices, these factors may be eclipsed by other non-physical environmental considerations, such as food regulations and socio-cultural preferences. This study identifies a set of meta-themes that summarize and illustrate the interrelationships between environmental attributes, people's perceptions, and eating behaviors: a) availability and accessibility are interrelated and only part of the healthy eating equation; b) local food is synonymous with healthy eating; c) local food places for healthy eating help define community identity; d) communal dining (commensality) does not necessarily mean healthy eating; e) rewarding an achievement or celebrating special occasions with highly processed foods is socially accepted; f) food costs seemed to be driving forces in food decisions; g) macro-environmental influences are latent in food decisions. Recognizing the interrelationship among multiple environmental factors may help efforts to design effective community-based interventions and address knowledge gaps on how sociocultural, economic, and political environments intersect with physical worlds.

Walk Score® is a proprietary walkability metric that ranks locations by proximity to destinations, with emerging health promotion applications for increasing walking as physical activity. Currently, field validations of Walk Score® have only occurred in metropolitan regions of the United States; moreover, many studies employ an earlier Walk Score® version utilizing straight line distance. To address this gap, we conducted a field validation of the newest, network-based metric for three municipal types along a rural-urban continuum in Alberta, Canada. In 2015, using street-level systematic observations collected in Bonnyville, Medicine Hat, and North Central Edmonton in 2008 (part of the Community Health and the Built Environment (CHBE) project), we reverse engineered 2181 scores with the network Walk Score® algorithm. We computed means, 95% confidence intervals, and t-tests (α = 0.05) for both sets of scores. Applying the Clifford-Richardson adjustment for spatial autocorrelation, we calculated Spearman's Rank Correlation Coefficients (rho, rs) and adjusted p-values to measure the strength of association between the derived scores and original network scores provided by Walk Score®. Spearman's rho for scores were very high for Bonnyville (rs = 0.950, adjusted p < 0.001), and high for Medicine Hat (rs = 0.790, adjusted p < 0.001) and North Central Edmonton (rs = 0.763, adjusted p < 0.001). High to very high correlations between derived scores and Walk Scores® field validated this metric across small, medium, and large population centres in Alberta, Canada. However, we suggest caution in interpreting Walk Score® for planning and evaluating health promotion interventions, since the strength of association between destinations and walking may vary across different municipal types.