Accuracy of city postal code coordinates as a proxy for location of residence

GIS measured environmental correlates of active school transport: a systematic review of 14 studies

Background

Emerging frameworks to examine active school transportation (AST) commonly emphasize the built environment (BE) as having an influence on travel mode decisions. Objective measures of BE attributes have been recommended for advancing knowledge about the influence of the BE on school travel mode choice. An updated systematic review on the relationships between GIS-measured BE attributes and AST is required to inform future research in this area. The objectives of this review are: i) to examine and summarize the relationships between objectively measured BE features and AST in children and adolescents and ii) to critically discuss GIS methodologies used in this context.

Methods

Six electronic databases, and websites were systematically searched, and reference lists were searched and screened to identify studies examining AST in students aged five to 18 and reporting GIS as an environmental measurement tool. Fourteen cross-sectional studies were identified. The analyses were classified in terms of density, diversity, and design and further differentiated by the measures used or environmental condition examined.

Results

Only distance was consistently found to be negatively associated with AST. Consistent findings of positive or negative associations were not found for land use mix, residential density, and intersection density. Potential modifiers of any relationship between these attributes and AST included age, school travel mode, route direction (e.g., to/from school), and trip-end (home or school). Methodological limitations included inconsistencies in geocoding, selection of study sites, buffer methods and the shape of zones (Modifiable Areal Unit Problem [MAUP]), the quality of road and pedestrian infrastructure data, and school route estimation.

Conclusions

The inconsistent use of spatial concepts limits the ability to draw conclusions about the relationship between objectively measured environmental attributes and AST. Future research should explore standardizing buffer size, assess the quality of street network datasets and, if necessary, customize existing datasets, and explore further attributes linked to safety.

Reduction in overdose mortality after the opening of North America's first medically supervised safer injecting facility: a retrospective population-based study

BACKGROUND

Overdose from illicit drugs is a leading cause of premature mortality in North America. Internationally, more than 65 supervised injecting facilities (SIFs), where drug users can inject pre-obtained illicit drugs, have been opened as part of various strategies to reduce the harms associated with drug use. We sought to determine whether the opening of an SIF in Vancouver, BC, Canada, was associated with a reduction in overdose mortality.

METHODS

We examined population-based overdose mortality rates for the period before (Jan 1, 2001, to Sept 20, 2003) and after (Sept 21, 2003, to Dec 31, 2005) the opening of the Vancouver SIF. The location of death was determined from provincial coroner records. We compared overdose fatality rates within an a priori specified 500 m radius of the SIF and for the rest of the city.

FINDINGS

Of 290 decedents, 229 (79·0%) were male, and the median age at death was 40 years (IQR 32-48 years). A third (89, 30·7%) of deaths occurred in city blocks within 500 m of the SIF. The fatal overdose rate in this area decreased by 35·0% after the opening of the SIF, from 253·8 to 165·1 deaths per 100,000 person-years (p=0·048). By contrast, during the same period, the fatal overdose rate in the rest of the city decreased by only 9·3%, from 7·6 to 6·9 deaths per 100,000 person-years (p=0·490). There was a significant interaction of rate differences across strata (p=0·049).

INTERPRETATION

SIFs should be considered where injection drug use is prevalent, particularly in areas with high densities of overdose.

FUNDING

Vancouver Coastal Health, Canadian Institutes of Health Research, and the Michael Smith Foundation for Health Research.

A method for managing re-identification risk from small geographic areas in Canada

Background

A common disclosure control practice for health datasets is to identify small geographic areas and either suppress records from these small areas or aggregate them into larger ones. A recent study provided a method for deciding when an area is too small based on the uniqueness criterion. The uniqueness criterion stipulates that an the area is no longer too small when the proportion of unique individuals on the relevant variables (the quasi-identifiers) approaches zero. However, using a uniqueness value of zero is quite a stringent threshold, and is only suitable when the risks from data disclosure are quite high. Other uniqueness thresholds that have been proposed for health data are 5% and 20%.

Methods

We estimated uniqueness for urban Forward Sortation Areas (FSAs) by using the 2001 long form Canadian census data representing 20% of the population. We then constructed two logistic regression models to predict when the uniqueness is greater than the 5% and 20% thresholds, and validated their predictive accuracy using 10-fold cross-validation. Predictor variables included the population size of the FSA and the maximum number of possible values on the quasi-identifiers (the number of equivalence classes).

Results

All model parameters were significant and the models had very high prediction accuracy, with specificity above 0.9, and sensitivity at 0.87 and 0.74 for the 5% and 20% threshold models respectively. The application of the models was illustrated with an analysis of the Ontario newborn registry and an emergency department dataset. At the higher thresholds considerably fewer records compared to the 0% threshold would be considered to be in small areas and therefore undergo disclosure control actions. We have also included concrete guidance for data custodians in deciding which one of the three uniqueness thresholds to use (0%, 5%, 20%), depending on the mitigating controls that the data recipients have in place, the potential invasion of privacy if the data is disclosed, and the motives and capacity of the data recipient to re-identify the data.

Conclusion

The models we developed can be used to manage the re-identification risk from small geographic areas. Being able to choose among three possible thresholds, a data custodian can adjust the definition of "small geographic area" to the nature of the data and recipient.

Residential address errors in public health surveillance data: a description and analysis of the impact on geocoding

The residential addresses of persons with reportable communicable diseases are used increasingly for spatial monitoring and cluster detection, and public health may direct interventions based upon the results of routine spatial surveillance. There has been little assessment, however, of the quality of address data in reportable disease notifications and of the corresponding impact of these errors on geocoding and routine public health practices. The objectives of this study were to examine address errors for a selected reportable disease in a large urban center in Canada and to assess the impact of identified errors on geocoding and the estimated spatial distribution of the disease. We extracted data for all notifications of campylobacteriosis from the Montreal public health department from 1995 to 2008 and used an address verification algorithm to determine the validity of the residential address for each case and to suggest corrections for invalid addresses. We assessed the types of address errors as well as the resulting positional errors, calculating the distance between the original address and the correct address as well as changes in disease density. Address errors and missing addresses were prevalent in the public health records (10% and 5%, respectively) and they influenced the observed distribution of campylobacteriosis in Montreal, with address correction changing case location by a median of 1.1 km. Further examination of the extent of address errors in public health data is essential, as is the investigation of how these errors impact routine public health functions.

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.

Understanding Screen-Related Sedentary Behavior and its Contributing Factors among School-Aged Children: A Social-Ecologic Exploration

Purpose.

To explore the factors that contribute to children's screen-related sedentary (S-RS) behaviors.

Settings.

Elementary schools.

Subjects.

A random sample of children in grades five and six and their parents.

Measures.

The outcome measure was children's S-RS activity level measured by a self-administered questionnaire. A full spectrum of potential contributing factors for children's S-RS behaviors was obtained through surveys. Multilevel linear regression methods were used to determine the associations between these factors and children's screen time (hours per day) and results were expressed as regression coefficients (g).

Results.

Of 955 child-parent pairs in 14 participating schools, 508 pairs (53%) completed the surveys. At an intrapersonal level, protective factors included being a girl (g = − .71); belonging to a sports team inside (g = −.56) or outside (g = −.49) of school; having a negative attitude toward S-RS activities (g = −.13); and having a positive attitude toward physical activity (g = −.48). At the interpersonal and social levels, parental leisure S-RS behaviors (g = .32) were positively associated, whereas strict parental rules on computer use (g = −.27) and family income (g = −.32) were inversely correlated with S-RS behavior. At the environmental level, the presence of TVs in children's bedrooms (g = .44) and owning videogame devices (g = .58) increased the risk of S-RS behaviors, whereas after school programs (g = −.86) and schools' participation in the Turn Off the Screen Week campaign (g = −.91) decreased the risk.

Conclusions.

Public health interventions should target multilevel factors, including increasing children's awareness, promoting parental involvement in healthy lifestyle pursuits, and creating less screenogenic environments.

Tuberculosis and the city

Unrecognized tuberculosis transmission outside the household has led to "micro-epidemics". We sought to evaluate how frequently locations outside the household were addressed in tuberculosis contact investigations, and to identify associated patient factors. We reviewed all tuberculosis patients reported in Montreal, Canada, during 1996-2004. Among this largely foreign-born patient population, investigation of locations outside the household was limited: there was documented attendance at 1 non-household location for 40% of the most contagious patients. Given complex, dispersed patterns of work, educational attendance, social activity, and transportation, contact investigation strategies may warrant reevaluation in large cities such as Montreal.

The influence of the physical environment and sociodemographic characteristics on children's mode of travel to and from school

OBJECTIVES

We examined whether certain characteristics of the social and physical environment influence a child's mode of travel between home and school.

METHODS

Students aged 11 to 13 years from 21 schools throughout London, Ontario, answered questions from a travel behavior survey. A geographic information system linked survey responses for 614 students who lived within 1 mile of school to data on social and physical characteristics of environments around the home and school. Logistic regression analysis was used to test the influence of environmental factors on mode of travel (motorized vs "active") to and from school.

RESULTS

Over 62% of students walked or biked to school, and 72% from school to home. The likelihood of walking or biking to school was positively associated with shorter trips, male gender, higher land use mix, and presence of street trees. Active travel from school to home was also associated with lower residential densities and lower neighborhood incomes.

CONCLUSIONS

Our findings demonstrate that active travel is associated with environmental characteristics and suggest that school planners should consider these factors when siting schools in order to promote increased physical activity among students.

Estimating the accuracy of geographical imputation

BACKGROUND

To reduce the number of non-geocoded cases researchers and organizations sometimes include cases geocoded to postal code centroids along with cases geocoded with the greater precision of a full street address. Some analysts then use the postal code to assign information to the cases from finer-level geographies such as a census tract. Assignment is commonly completed using either a postal centroid or by a geographical imputation method which assigns a location by using both the demographic characteristics of the case and the population characteristics of the postal delivery area. To date no systematic evaluation of geographical imputation methods ("geo-imputation") has been completed. The objective of this study was to determine the accuracy of census tract assignment using geo-imputation.

METHODS

Using a large dataset of breast, prostate and colorectal cancer cases reported to the New Jersey Cancer Registry, we determined how often cases were assigned to the correct census tract using alternate strategies of demographic based geo-imputation, and using assignments obtained from postal code centroids. Assignment accuracy was measured by comparing the tract assigned with the tract originally identified from the full street address.

RESULTS

Assigning cases to census tracts using the race/ethnicity population distribution within a postal code resulted in more correctly assigned cases than when using postal code centroids. The addition of age characteristics increased the match rates even further. Match rates were highly dependent on both the geographic distribution of race/ethnicity groups and population density.

CONCLUSION

Geo-imputation appears to offer some advantages and no serious drawbacks as compared with the alternative of assigning cases to census tracts based on postal code centroids. For a specific analysis, researchers will still need to consider the potential impact of geocoding quality on their results and evaluate the possibility that it might introduce geographical bias.

Comparing circular and network buffers to examine the influence of land use on walking for leisure and errands

Background

There is increasing interest in examining the influence of the built environment on physical activity. High-resolution data in a geographic information system is increasingly being used to measure salient aspects of the built environment and studies often use circular or road network buffers to measure land use around an individual's home address. However, little research has examined the extent to which the selection of circular or road network buffers influences the results of analysis.

The objective of this study is to examine the influence of land use type (residential, commercial, recreational and park land and institutional land) on 'walking for leisure' and 'walking for errands' using 1 km circular and line-based road network buffers. Data on individual walking patterns is obtained from a survey of 1311 respondents in greater Vancouver and respondent's postal code centroids were used to construct the individual buffers. Logistic regression was used for statistical analysis.

Results

Using line-based road network buffers, increasing proportion of institutional land significantly reduced the odds of 'walking for leisure 15 minutes or less per day' no significant results were found for circular buffers. A greater proportion of residential land significantly increased the odds of 'walking for errands less than 1 hour per week' for line-based road network buffer while no significant results for circular buffers. An increased proportion of commercial land significantly decreased the odds of 'walking for errands less than 1 hour per week' for both circular and line-based road network buffers.

Conclusion

The selection of network or circular buffers has a considerable influence on the results of analysis. Land use characteristics generally show greater associations with walking using line-based road network buffers than circular buffers. These results show that researchers need to carefully consider the most appropriate buffer with which to calculate land use characteristics.

Evaluating common de-identification heuristics for personal health information

BACKGROUND

With the growing adoption of electronic medical records, there are increasing demands for the use of this electronic clinical data in observational research. A frequent ethics board requirement for such secondary use of personal health information in observational research is that the data be de-identified. De-identification heuristics are provided in the Health Insurance Portability and Accountability Act Privacy Rule, funding agency and professional association privacy guidelines, and common practice.

OBJECTIVE

The aim of the study was to evaluate whether the re-identification risks due to record linkage are sufficiently low when following common de-identification heuristics and whether the risk is stable across sample sizes and data sets.

METHODS

Two methods were followed to construct identification data sets. Re-identification attacks were simulated on these. For each data set we varied the sample size down to 30 individuals, and for each sample size evaluated the risk of re-identification for all combinations of quasi-identifiers. The combinations of quasi-identifiers that were low risk more than 50% of the time were considered stable.

RESULTS

The identification data sets we were able to construct were the list of all physicians and the list of all lawyers registered in Ontario, using 1% sampling fractions. The quasi-identifiers of region, gender, and year of birth were found to be low risk more than 50% of the time across both data sets. The combination of gender and region was also found to be low risk more than 50% of the time. We were not able to create an identification data set for the whole population.

CONCLUSIONS

Existing Canadian federal and provincial privacy laws help explain why it is difficult to create an identification data set for the whole population. That such examples of high re-identification risk exist for mainstream professions makes a strong case for not disclosing the high-risk variables and their combinations identified here. For professional subpopulations with published membership lists, many variables often needed by researchers would have to be excluded or generalized to ensure consistently low re-identification risk. Data custodians and researchers need to consider other statistical disclosure techniques for protecting privacy.

Location of residence associated with the likelihood of patient visit to the preoperative assessment clinic

BACKGROUND

Outpatient preoperative assessment clinics were developed to provide an efficient assessment of surgical patients prior to surgery, and have demonstrated benefits to patients and the health care system. However, the centralization of preoperative assessment clinics may introduce geographical barriers to utilization that are dependent on where a patient lives with respect to the location of the preoperative assessment clinic.

METHODS

The association between geographical distance from a patient's place of residence to the preoperative assessment clinic, and the likelihood of a patient visit to the clinic prior to surgery, was assessed for all patients undergoing surgery at a tertiary health care centre in a major Canadian city. The odds of attending the preoperative clinic were adjusted for patient characteristics and clinical factors.

RESULTS

Patients were less likely to visit the preoperative assessment clinic prior to surgery as distance from the patient's place of residence to the clinic increased (adjusted OR = 0.52, 95% CI 0.44-0.63 for distances between 50-100 km, and OR = 0.26, 95% CI 0.21-0.31 for distances greater than 250 km). This 'distance decay' effect was remarkable for all surgical specialties.

CONCLUSION

The present study demonstrates that the likelihood of a patient visiting the preoperative assessment clinic appears to depend on the geographical location of patients' residences. Patients who live closest to the clinic tend to be seen more often than patients who live in rural and remote areas. This observation may have implications for achieving the goals of equitable access, and optimal patient care and resource utilization in a single universal insurer health care system.