Longitudinal trends in incidence and health care use for pediatric concussion in Alberta, Canada.

BACKGROUND: We described longitudinal trends in the incidence of episodes of care (EOC) and follow-up care for pediatric concussion in relation to age, sex, rurality of patient residence, point of care, and area-based socioeconomic status (SES) in Alberta, Canada. METHODS: A retrospective population-based cohort study was conducted using linked, province-wide administrative health data for all patients <18 years of age who received a diagnosis of concussion, other specified injuries of head, unspecified injury of head, or post-concussion syndrome between April 1, 2004 and March 31, 2018. Data were geospatially mapped. RESULTS: Concussion EOCs increased 2.2-fold over the study period, follow-up visits 5.1-fold. Care was increasingly received in physician office (PO) settings. Concussion diagnoses in rural and remote areas occurred in emergency department (ED) settings more often than in metro centres or urban areas (76%/75% vs. 52%/60%). Proportion of concussion diagnoses was positively related to SES and age. Diagnosis and point of care varied geographically. CONCLUSIONS: The shift in care to PO settings, increased incidence of all diagnoses, and the higher use of the ED by some segments of the population all have important implications for appropriate clinical management and the efficient provision of health care for pediatric concussion. IMPACT: This is the first study to use EOC to describe longitudinal trends in incidence and follow-up care for pediatric concussion in relation to age, sex, rurality, point of care, and area-based SES. We report increased incidence of concussion in both emergency and outpatient settings and the proportion of diagnoses was positively related to SES and age. Patients increasingly received care for concussion in PO over time. Geospatial mapping indicated that the incidence of concussion and unspecified injury of head varied geographically and temporally. Results have important implications for appropriate clinical management and efficient provision of health care following pediatric concussion.

Geospatial patterns of comorbidity prevalence among people with osteoarthritis in Alberta Canada.

BACKGROUND: Knowledge of geospatial pattern in comorbidities prevalence is critical to an understanding of the local health needs among people with osteoarthritis (OA). It provides valuable information for targeting optimal OA treatment and management at the local level. However, there is, at present, limited evidence about the geospatial pattern of comorbidity prevalence in Alberta, Canada. METHODS: Five administrative health datasets were linked to identify OA cases and comorbidities using validated case definitions. We explored the geospatial pattern in comorbidity prevalence at two standard geographic areas levels defined by the Alberta Health Services: descriptive analysis at rural-urban continuum level; spatial analysis (global Moran's I, hot spot analysis, cluster and outlier analysis) at the local geographic area (LGA) level. We compared area-level indicators in comorbidities hotspots to those in the rest of Alberta (non-hotspots). RESULTS: Among 359,638 OA cases in 2013, approximately 60% of people resided in Metro and Urban areas, compared to 2% in Rural Remote areas. All comorbidity groups exhibited statistically significant spatial autocorrelation (hypertension: Moran's I index 0.24, z score 4.61). Comorbidity hotspots, except depression, were located primarily in Rural and Rural Remote areas. Depression was more prevalent in Metro (Edmonton-Abbottsfield: 194 cases per 1000 population, 95%CI 192-195) and Urban LGAs (Lethbridge-North: 169, 95%CI 168-171) compared to Rural areas (Fox Creek: 65, 95%CI 63-68). Comorbidities hotspots included a higher percentage of First Nations or Inuit people. People with OA living in hotspots had lower socioeconomic status and less access to care compared to non-hotspots. CONCLUSIONS: The findings highlight notable rural-urban disparities in comorbidities prevalence among people with OA in Alberta, Canada. Our study provides valuable evidence for policy and decision makers to design programs that ensure patients with OA receive optimal health management tailored to their local needs and a reduction in current OA health disparities.

Fine particulate air pollution, nitrogen dioxide, and systemic autoimmune rheumatic disease in Calgary, Alberta.

OBJECTIVE: To estimate the association between fine particulate (PM2.5) and nitrogen dioxide (NO2) pollution and systemic autoimmune rheumatic diseases (SARDs). METHODS: Associations between ambient air pollution (PM2.5 and NO2) and SARDs were assessed using land-use regression models for Calgary, Alberta and administrative health data (1993-2007). SARD case definitions were based on ≥2 physician claims, or ≥1 rheumatology billing code; or ≥1 hospitalization code (for systemic lupus, Sjogren's Syndrome, scleroderma, polymyositis, dermatomyositis, or undifferentiated connective tissue disease). Bayesian hierarchical latent class regression models estimated the probability that each resident was a SARD case, based on these case definitions. The sum of individual level probabilities provided the estimated number of cases in each area. The latent class model included terms for age, sex, and an interaction term between age and sex. Bayesian logistic regression models were used to generate adjusted odds ratios (OR) for NO2 and PM2.5. pollutant models, adjusting for neighbourhood income, age, sex, and an interaction between age and sex. We also examined models stratified for First-Nations (FN) and non-FN subgroups. RESULTS: Residents that were female and/or aged >45 had a greater probability of being a SARD case, with the highest OR estimates for older females. Independently, the odds of being a SARDs case increased with PM2.5 levels, but the results were inconclusive for NO2. The results stratified by FN and non-FN groups were not distinctly different. CONCLUSION: In this urban Canadian sample, adjusting for demographics, exposure to PM2.5 was associated with an increased risk of SARDs. The results for NO2 were inconclusive.

Despite Increased Disease Activity, Women who Attended a Dedicated Inflammatory Bowel Disease and Pregnancy Clinic Had Infants With Higher Apgar Scores: A Population-Based Study.

BACKGROUND: Attendance at a subspecialty pregnancy clinic for women with inflammatory bowel disease (IBD) improves disease-specific pregnancy knowledge. We examined the impact of attendance at a dedicated IBD-pregnancy clinic on IBD and perinatal outcomes. METHODS: Using linked administrative databases in Alberta, Canada (2012-2019), we identified 1061 pregnant women with IBD who delivered singleton liveborn infants in-hospital who did (n = 314) and did not attend (n = 747) the clinic. Propensity score weighted multivariable log-binomial and multinomial logistic regression models were used to determine the risk of IBD and perinatal outcomes. RESULTS: The median number of clinic visits was 3 (Q1-Q3, 3-5), with 34.7% completing a preconception consultation. A greater proportion of women who attended lived near the clinic, were nulliparous, had a disease flare prior to pregnancy, and were on maintenance IBD medication (P < .05). Women who attended had increased risks of a disease flare during pregnancy (adjusted risk ratio [aRR], 2.02; 95% CI, 1.45-2.82), an IBD-related emergency department visit during pregnancy (aRR, 2.66; 95% CI, 1.92-3.68), and cesarean delivery (aRR, 1.78; 95% CI, 1.23-2.57). Despite this, clinic attendees had a decreased risk of delivering an infant with a low Apgar score at 1 minute (risk ratio [RR], 0.49; 95% CI, 0.32-0.76) and 5 minutes (RR, 0.32; 95% CI, 0.12-0.87). CONCLUSIONS: Women who attended a dedicated IBD-pregnancy clinic were more likely to have a disease flare prior to pregnancy, reflecting a more severe disease phenotype, but had similar perinatal outcomes and infants with better Apgar scores at birth. Our study suggests the value of these subspecialty clinics in providing enhanced IBD-specific prenatal care.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

Spatial regression modelling of particulate pollution in Calgary, Canada.

The study presents a spatial analysis of particulate pollution, which includes not only particulate matter, but also black carbon, a pollutant of growing concern for human health. We developed land use regression (LUR) models for two particulate matter size fractions, PM2.5 and PM10, and for δC, an index calculated from black carbon (BC)-a component of PM2.5-which indicates the portion of organic versus elemental BC. LUR models were estimated over Calgary (Canada) for summer 2015 and winter 2016. As all samples exhibited significant spatial autocorrelation, spatial autoregressive lag (SARlag) and error (SARerr) models were computed. SARlag models were preferred for all pollutants in both seasons, and yielded goodness of fit aligned with or higher than values reported in the literature. LUR models yielded consistent sets of predictors, representing industrial activities, traffic, and elevation. The obtained model coefficients were then combined with local land use variables to compute fine-scale concentration predictions over the entire city. The predicted concentrations were slightly lower and less dispersed than the observed ones. Consistent with observed pollution records, prediction maps exhibited higher concentration over the road network, industrial areas, and the eastern quadrants of the city. Lastly, results of a corresponding study of PM in summer 2010 and winter 2011 were considered. While the small size of the 2010-2011 sample hampered a multi-temporal analysis, we cautiously note comparable seasonal patterns and consistent association with land use variables for both PM fine fractions over the 5-year interval.

Rural-Urban Differences in Non-Local Primary Care Utilization among People with Osteoarthritis: The Role of Area-Level Factors.

The utilization of non-local primary care physicians (PCP) is a key primary care indicator identified by Alberta Health to support evidence-based healthcare planning. This study aims to identify area-level factors that are significantly associated with non-local PCP utilization and to examine if these associations vary between rural and urban areas. We examined rural-urban differences in the associations between non-local PCP utilization and area-level factors using multivariate linear regression and geographically weighted regression (GWR) models. Global Moran's I and Gi* hot spot analyses were applied to identify spatial autocorrelation and hot spots/cold spots of non-local PCP utilization. We observed significant rural-urban differences in the non-local PCP utilization. Both GWR and multivariate linear regression model identified two significant factors (median travel time and percentage of low-income families) with non-local PCP utilization in both rural and urban areas. Discontinuity of care was significantly associated with non-local PCP in the southwest, while the percentage of people having university degree was significant in the north of Alberta. This research will help identify gaps in the utilization of local primary care and provide evidence for health care planning by targeting policies at associated factors to reduce gaps in OA primary care provision.

Rural-Urban Disparities in Realized Spatial Access to General Practitioners, Orthopedic Surgeons, and Physiotherapists among People with Osteoarthritis in Alberta, Canada.

Rural Canadians have high health care needs due to high prevalence of osteoarthritis (OA) but lack access to care. Examining realized access to three types of providers (general practitioners (GPs), orthopedic surgeons (Ortho), and physiotherapists (PTs)) simultaneously helps identify gaps in access to needed OA care, inform accessibility assessment, and support health care resource allocation. Travel time from a patient's postal code to the physician's postal code was calculated using origin-destination network analysis. We applied descriptive statistics to summarize differences in travel time, hotspot analysis to explore geospatial patterns, and distance decay function to examine the travel pattern of health care utilization by urbanicity. The median travel time in Alberta was 11.6 min (IQR = 4.3-25.7) to GPs, 28.9 (IQR = 14.8-65.0) to Ortho, and 33.7 (IQR = 23.1-47.3) to PTs. We observed significant rural-urban disparities in realized access to GPs (2.9 and IQR = 0.0-92.1 in rural remote areas vs. 12.6 and IQR = 6.4-21.0 in metropolitan areas), Ortho (233.3 and IQR = 171.3-363.7 in rural remote areas vs. 21.3 and IQR = 14.0-29.3 in metropolitan areas), and PTs (62.4 and IQR = 0.0-232.1 in rural remote areas vs. 32.1 and IQR = 25.2-39.9 in metropolitan areas). We identified hotspots of realized access to all three types of providers in rural remote areas, where patients with OA tend to travel longer for health care. This study may provide insight on the choice of catchment size and the distance decay pattern of health care utilization for further studies on spatial accessibility.

Association Between Residential Proximity to Hydraulic Fracturing Sites and Adverse Birth Outcomes.

Importance: The association between hydraulic fracturing and human development is not well understood. Several studies have identified significant associations between unconventional natural gas development and adverse birth outcomes; however, geology and legislation vary between regions. Objective: To examine the overall association between residential proximity to hydraulic fracturing sites and adverse birth outcomes, and investigate whether well density influenced this association. Design, Setting, and Participants: This population-based retrospective cohort study of pregnant individuals in rural Alberta, Canada, took place from 2013 to 2018. Participants included reproductive-aged individuals (18-50 years) who had a pregnancy from January 1, 2013, to December 31, 2018, and lived in rural areas. Individuals were excluded if they lived in an urban setting, were outside of the age range, or were missing data on infant sex, postal code, or area-level socioeconomic status. Exposures: Oil and gas wells that underwent hydraulic fracturing between 2013 to 2018 were identified through the Alberta Energy Regulator (n = 4871). Individuals were considered exposed if their postal delivery point was located within 10 km of 1 or more wells that was hydraulically fractured during 1 year preconception or during pregnancy. Main Outcomes and Measures: Outcomes investigated were spontaneous and indicated preterm birth, small for gestational age, major congenital anomalies, and severe neonatal morbidity or mortality. Results: After exclusions, the sample included 26 193 individuals with 34 873 unique pregnancies, and a mean (SD) parental age of 28.2 (5.2) years. Small for gestational age and major congenital anomalies were significantly higher for individuals who lived within 10 km of at least 1 hydraulically fractured well after adjusting for parental age at delivery, multiple births, fetal sex, obstetric comorbidities, and area-level socioeconomic status. Risk of spontaneous preterm birth and small for gestational age were significantly increased in those with 100 or more wells within 10 km. Conclusions and Relevance: Results suggest that individuals who were exposed to hydraulic fracturing within pregnancy may be at higher risk of several adverse birth outcomes. These results may be relevant to health policy regarding legislation of unconventional oil and gas development in Canada and internationally.

Travel Distance to Subspecialty Clinic and Outcomes in Patients with Fibrotic Interstitial Lung Disease.

Rationale: Early access to subspecialty care is associated with improved outcomes for patients with fibrotic interstitial lung disease (ILD). Access to ILD care may be limited for patients living far from subspecialty clinics. Objectives: To test the hypothesis that greater travel distance to access ILD clinical care would be associated with more severe disease at time of referral and worse clinical outcomes. Methods: Patients with fibrotic ILD were recruited from a multicenter national pulmonary fibrosis registry. Residential postal codes were geocoded to estimate travel distance from the home to the clinic. Travel distance was dichotomized at ⩽70 km (near) and >70 km (far). Demographics and disease severity at the initial referral, changes in lung function, and the risk of death or lung transplant were analyzed in unadjusted and adjusted models for their association with travel distance. Results: The cohort included 1,162 patients, of whom 856 lived near to their ILD clinic and 306 lived far from their ILD clinic. Patients residing farther from their clinic were younger, more likely to have smoked, had a greater 6-minute-walk distance, and had lower composite risk scores than patients residing closer to their clinic. In models adjusted for age, sex, and baseline forced vital capacity, patients from farther away had a greater risk of death or lung transplant than patients residing closer (hazard ratio, 1.52; 95% confidence interval [CI], 1.10-2.11), a finding predominantly driven by patients with connective tissue disease-related ILD (hazard ratio, 2.14; 95% CI, 1.16-3.94). Conclusions: Patients with fibrotic ILD with a longer travel distance to their ILD clinic had better prognostic indices at baseline but had a higher risk of death or lung transplant in the total cohort and in patients with connective tissue disease-related ILD. Assuming that disease epidemiology and severity are distributed evenly across geographic regions, these findings raise important questions about equitable access to patient care in large healthcare regions with centralized subspecialty programs.

Geographic Variation in the Prevalence of Rheumatoid Arthritis in Alberta, Canada.

OBJECTIVES: Timely access to rheumatologists remains a challenge in Alberta, a Canadian province with vast rural areas, whereas rheumatologists are primarily clustered in metro areas. To address the goal of timely and equitable access to rheumatoid arthritis (RA) care, health planners require information at the regional and local level to determine the RA prevalence and the associated health care needs. METHODS: Using Alberta Health administrative databases, we identified RA-prevalent cases (April 1, 2015-March 31, 2016) on the basis of a validated case definition. Age- and sex-standardized prevalence rates per 1000 population members and the standardized rates ratio (SRR) were calculated. We applied Global Moran's I and Gi* hotspot analysis using three different weight matrices to explore the geospatial pattern of RA prevalence in Alberta. RESULTS: Among 38 350 RA cases (68% female; n = 26 236), the prevalence rate was 11.81 cases per 1000 population members (95% confidence interval [CI] 11.80-11.81) after age and sex standardization. Approximately 60% of RA cases resided in metro (Calgary and Edmonton) and moderate metro areas. The highest rate was observed in rural areas (14.46; 95% CI 14.45-14.47; SRR 1.28), compared with the lowest in metro areas (10.69; 95% CI 10.68-10.69; SRR 0.82). The RA prevalence across local geographic areas ranged from 4.7 to 30.6 cases. The Global Moran's I index was 0.15 using three different matrices (z-score 3.96-4.24). We identified 10 hotspots in the south and north rural areas and 18 cold spots in metro and moderate metro Calgary. CONCLUSION: The findings highlight notable rural-urban variation in RA prevalence in Alberta. Our findings can inform strategies aimed at reducing geographic disparities by targeting areas with high health care needs.

Temporal and spatial effect of air pollution on hospital admissions for myocardial infarction: a case-crossover study.

BACKGROUND: In studies showing associations between ambient air pollution and myocardial infarction (MI), data have been lacking on the inherent spatial variability of air pollution. The aim of this study was to determine whether the long-term spatial distribution of air pollution influences short-term temporal associations between air pollution and admission to hospital for MI. METHODS: We identified adults living in Calgary who were admitted to hospital for an MI between 2004 and 2012. We evaluated associations between short-term exposure to air pollution (ozone [O3], nitrogen dioxide [NO2], sulfur dioxide [SO2], carbon monoxide [CO], particulate matter < 10 µm in diameter [PM10] and particulate matter < 2.5 µm in diameter [PM2.5]), and hospital admissions for MI using a time-stratified, case-crossover study design. Air Quality Health Index (AQHI) scores were calculated from a composition of O3, NO2 and PM2.5. Conditional logistic regression models were stratified by low, medium and high levels of neighbourhood NO2 concentrations derived from land use regression models; results of these analyses are presented as odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS: From 2004 to 2012, 6142 MIs were recorded in Calgary. Individuals living in neighbourhoods with higher long-term air pollution concentrations were more likely to be admitted to hospital for MI after short-term elevations in air pollution (e.g., 5-day average NO2: OR 1.20, 95% CI 1.03-1.40, per interquartile range [IQR]) as compared with regions with lower air pollution (e.g., 5-day average NO2: OR 0.90, 95% CI 0.78-1.04, per IQR). In high NO2 tertiles, the AQHI score was associated with MI (e.g., 5-day average OR 1.13, 95% CI 1.02-1.24, per IQR; 3-day average OR 1.13, 95% CI 1.04-1.23, per IQR). INTERPRETATION: Our results show that the effect of air pollution on hospital admissions for MI was stronger in areas with higher NO2 concentrations than that in areas with lower NO2 concentrations. Individuals living in neighbourhoods with higher traffic-related pollution should be advised of the health risks and be attentive to special air quality warnings.

Comparison of distance measures in spatial analytical modeling for health service planning.

BACKGROUND: Several methodological approaches have been used to estimate distance in health service research. In this study, focusing on cardiac catheterization services, Euclidean, Manhattan, and the less widely known Minkowski distance metrics are used to estimate distances from patient residence to hospital. Distance metrics typically produce less accurate estimates than actual measurements, but each metric provides a single model of travel over a given network. Therefore, distance metrics, unlike actual measurements, can be directly used in spatial analytical modeling. Euclidean distance is most often used, but unlikely the most appropriate metric. Minkowski distance is a more promising method. Distances estimated with each metric are contrasted with road distance and travel time measurements, and an optimized Minkowski distance is implemented in spatial analytical modeling. METHODS: Road distance and travel time are calculated from the postal code of residence of each patient undergoing cardiac catheterization to the pertinent hospital. The Minkowski metric is optimized, to approximate travel time and road distance, respectively. Distance estimates and distance measurements are then compared using descriptive statistics and visual mapping methods. The optimized Minkowski metric is implemented, via the spatial weight matrix, in a spatial regression model identifying socio-economic factors significantly associated with cardiac catheterization. RESULTS: The Minkowski coefficient that best approximates road distance is 1.54; 1.31 best approximates travel time. The latter is also a good predictor of road distance, thus providing the best single model of travel from patient's residence to hospital. The Euclidean metric and the optimal Minkowski metric are alternatively implemented in the regression model, and the results compared. The Minkowski method produces more reliable results than the traditional Euclidean metric. CONCLUSION: Road distance and travel time measurements are the most accurate estimates, but cannot be directly implemented in spatial analytical modeling. Euclidean distance tends to underestimate road distance and travel time; Manhattan distance tends to overestimate both. The optimized Minkowski distance partially overcomes their shortcomings; it provides a single model of travel over the network. The method is flexible, suitable for analytical modeling, and more accurate than the traditional metrics; its use ultimately increases the reliability of spatial analytical models.

Schools, Air Pollution, and Active Transportation: An Exploratory Spatial Analysis of Calgary, Canada.

An exploratory spatial analysis investigates the location of schools in Calgary (Canada) in relation to air pollution and active transportation options. Air pollution exhibits marked spatial variation throughout the city, along with distinct spatial patterns in summer and winter; however, all school locations lie within low to moderate pollution levels. Conversely, the study shows that almost half of the schools lie in low walkability locations; likewise, transitability is low for 60% of schools, and only bikability is widespread, with 93% of schools in very bikable locations. School locations are subsequently categorized by pollution exposure and active transportation options. This analysis identifies and maps schools according to two levels of concern: schools in car-dependent locations and relatively high pollution; and schools in locations conducive of active transportation, yet exposed to relatively high pollution. The findings can be mapped and effectively communicated to the public, health practitioners, and school boards. The study contributes with an explicitly spatial approach to the intra-urban public health literature. Developed for a moderately polluted city, the methods can be extended to more severely polluted environments, to assist in developing spatial public health policies to improve respiratory outcomes, neurodevelopment, and metabolic and attention disorders in school-aged children.

Exploratory Temporal and Spatial Analysis of Myocardial Infarction Hospitalizations in Calgary, Canada.

Spatial and temporal analyses are critical to understand the pattern of myocardial infarction (MI) hospitalizations over space and time, and to identify their underlying determinants. In this paper, we analyze MI hospitalizations in Calgary from 2004 to 2013, stratified by age and gender. First, a seasonal trend decomposition analyzes the seasonality; then a linear regression models the trend component. Moran's I and hot spot analyses explore the spatial pattern. Though exploratory, results show that most age and gender groups feature a statistically significant decline over the 10 years, consistent with previous studies in Canada. Decline rates vary across ages and genders, with the slowest decline observed for younger males. Each gender exhibits a seasonal pattern with peaks in both winter and summer. Spatially, MI hot spots are identified in older communities, and in socioeconomically and environmentally disadvantaged communities. In the older communities, higher MI rates appear to be more highly associated with demographics. Conversely, worse air quality appears to be locally associated with higher MI incidence in younger age groups. The study helps identify areas of concern, where MI hot spots are identified for younger age groups, suggesting the need for localized public health policies to target local risk factors.

Residence location and likelihood of kidney transplantation.

BACKGROUND: In a universal, public health care system, access to kidney transplantation should not be influenced by residence location. We determined the likelihood of kidney transplantation from deceased donors among Canadian dialysis patients living in 7 geographic regions. Within each region we also determined whether distance from the closest transplant centre was associated with the likelihood of transplantation. METHODS: A random sample of 7034 subjects initiating dialysis in Canada between 1996 and 2000 was studied. We used Cox proportional hazards models to examine the relation between residence location and the likelihood of kidney transplantation from deceased donors over a median period of 2.4 years. RESULTS: There were significant differences in the likelihood of kidney transplantation from deceased donors and predicted waiting times between the different geographic regions. For example, the adjusted relative likelihood of transplantation in Alberta was 3.74 (95% confidence interval [CI] 2.95-4.76) compared with the likelihood in Ontario (p < 0.001). These differences persisted after further adjustment for differences in the rate of deceased organ donation. Within regions, patients who resided 50.1-150 km, 150.1-300 km and more than 300 km from the closest transplant centre had a similar adjusted likelihood of receiving a kidney transplant as those who lived less than 50 km away. INTERPRETATION: The adjusted likelihood of undergoing a kidney transplant from a deceased donor varied substantially between geographic regions in Canada. In contrast, the likelihood of transplantation within regions was not affected by distance from the closest transplant centre.

Local Spatial Analysis and Dynamic Simulation of Childhood Obesity and Neighbourhood Walkability in a Major Canadian City.

Body weight is an important indicator of current and future health and it is even more critical in children, who are tomorrow's adults. This paper analyzes the relationship between childhood obesity and neighbourhood walkability in Calgary, Canada. A multivariate analytical framework recognizes that childhood obesity is also associated with many factors, including socioeconomic status, foodscapes, and environmental factors, as well as less measurable factors, such as individual preferences, that could not be included in this analysis. In contrast with more conventional global analysis, this research employs localized analysis and assesses need-based interventions. The one-size-fit-all strategy may not effectively control obesity rates, since each neighbourhood has unique characteristics that need to be addressed individually. This paper presents an innovative framework combining local analysis with simulation modeling to analyze childhood obesity. Spatial models generally do not deal with simulation over time, making it cumbersome for health planners and policy makers to effectively design and implement interventions and to quantify their impact over time. This research fills this gap by integrating geographically weighted regression (GWR), which identifies vulnerable neighbourhoods and critical factors for childhood obesity, with simulation modeling, which evaluates the impact of the suggested interventions on the targeted neighbourhoods. Neighbourhood walkability was chosen as a potential target for localized interventions, owing to the crucial role of walking in developing a healthy lifestyle, as well as because increasing walkability is relatively more feasible and less expensive then modifying other factors, such as income. Simulation results suggest that local walkability interventions can achieve measurable declines in childhood obesity rates. The results are encouraging, as improvements are likely to compound over time. The results demonstrate that the integration of GWR and simulation modeling is effective, and the proposed framework can assist in designing local interventions to control and prevent childhood obesity.

Applications of geographic information systems in public health: A geospatial approach to analyzing MMR immunization uptake in Alberta.

OBJECTIVE: This study evaluates the temporal, spatial, and spatio-temporal variation of immunization rates for measles, mumps and rubella (MMR) immunization in the province of Alberta. The study uses yearly immunization rate data for Health Zones and Local Geographic Areas (2004-2012), which were obtained from Alberta Health's Interactive Health Data Application (IHDA). METHODS: Spatial analyses include a global spatial analysis, Moran's I, and local indicators of spatial association (LISA) analysis - Getis and Ord's G* - to identify clusters of high or low immunization rates. Spatial methods are then applied to a time series analysis to examine how the immunization rates change over time in conjunction with space. RESULTS: Mapped results indicate decreasing immunization rates over time for the majority of the province where most local geographic areas (LGAs) fall short of the 95% herd immunity threshold. Clusters of high immunization rates in the metropolitan centres, and clusters of low immunization rates in the southern and northern region of the province exist spatially and spatio-temporally. Over time, the high rate clusters are decreasing in size and the low rate clusters are increasing. CONCLUSION: This research provides a localized geographic approach to assessing MMR immunization rates in Alberta. Findings from this research can be used to target public health interventions to specific areas that exhibit the lowest immunization rates. These results can also be used for hypothesis generation in future research on barriers to immunization uptake.

Accounting for spatial effects in land use regression for urban air pollution modeling.

In order to accurately assess air pollution risks, health studies require spatially resolved pollution concentrations. Land-use regression (LUR) models estimate ambient concentrations at a fine spatial scale. However, spatial effects such as spatial non-stationarity and spatial autocorrelation can reduce the accuracy of LUR estimates by increasing regression errors and uncertainty; and statistical methods for resolving these effects--e.g., spatially autoregressive (SAR) and geographically weighted regression (GWR) models--may be difficult to apply simultaneously. We used an alternate approach to address spatial non-stationarity and spatial autocorrelation in LUR models for nitrogen dioxide. Traditional models were re-specified to include a variable capturing wind speed and direction, and re-fit as GWR models. Mean R(2) values for the resulting GWR-wind models (summer: 0.86, winter: 0.73) showed a 10-20% improvement over traditional LUR models. GWR-wind models effectively addressed both spatial effects and produced meaningful predictive models. These results suggest a useful method for improving spatially explicit models.

Ambient ozone concentrations and the risk of perforated and nonperforated appendicitis: a multicity case-crossover study.

BACKGROUND: Environmental determinants of appendicitis are poorly understood. Past work suggests that air pollution may increase the risk of appendicitis. OBJECTIVES: We investigated whether ambient ground-level ozone (O3) concentrations were associated with appendicitis and whether these associations varied between perforated and nonperforated appendicitis. METHODS: We based this time-stratified case-crossover study on 35,811 patients hospitalized with appendicitis from 2004 to 2008 in 12 Canadian cities. Data from a national network of fixed-site monitors were used to calculate daily maximum O3 concentrations for each city. Conditional logistic regression was used to estimate city-specific odds ratios (ORs) relative to an interquartile range (IQR) increase in O3 adjusted for temperature and relative humidity. A random-effects meta-analysis was used to derive a pooled risk estimate. Stratified analyses were used to estimate associations separately for perforated and nonperforated appendicitis. RESULTS: Overall, a 16-ppb increase in the 7-day cumulative average daily maximum O3 concentration was associated with all appendicitis cases across the 12 cities (pooled OR = 1.07; 95% CI: 1.02, 1.13). The association was stronger among patients presenting with perforated appendicitis for the 7-day average (pooled OR = 1.22; 95% CI: 1.09, 1.36) when compared with the corresponding estimate for nonperforated appendicitis [7-day average (pooled OR = 1.02, 95% CI: 0.95, 1.09)]. Heterogeneity was not statistically significant across cities for either perforated or nonperforated appendicitis (p > 0.20). CONCLUSIONS: Higher levels of ambient O3 exposure may increase the risk of perforated appendicitis.