Where it’s at - linking data geographically.

Introduction Most public health-related concepts and outcomes can be defined as to their geographic location. The surroundings often have a strong influence or interactions with studied phenomena. For this reason a good understand and accurate geographic placement, linking, and aggregation of studied concepts is a critical yet often underestimated procedure. Objectives and Approach The main objectives of this presentation are: 1) an easy to understand review and explanation of geographic delineation markers in common healthcare databases, and 2) ways and pitfalls of geographic data linkages. Common point- and area-defined databases will be described. Nuances of ‘point-to-area’, ‘area-to-area’ linkages will be discussed, with additional explanations of scale and zone effects. Examples of common linkages between the following common spatial delineators will be explained: Postal Code Conversion File (PCCF), small area Canada Census units, common health system geographies (e.g. sub-regions, LHINs). Frequently committed errors and best practices in geographic data linkages will be discussed. Results Examples of the influence of various methods of geographic data linkages on study simulated outcomes will be shown. Conclusion/Implications Improper geographic linkage procedures can lead to incorrect study results. Enhancing the knowledge of geographic concepts in public health research and promotion of correct procedures in spatial placements, linkages and aggregation are the main take home messages of this presentation

Rurality as a Risk Factor for Attempted Suicide and Death by Suicide in Ontario, Canada : La ruralité comme facteur de risque des tentatives de suicide et des décès par suicide en Ontario, Canada

OBJECTIVE: This study aims to examine rural and urban differences in attempted suicide and death by suicide in Ontario, Canada. METHOD: This is a population-based nested case-control study. Data were obtained from administrative databases held at ICES, which capture all hospital and emergency department visits across Ontario between 2007 and 2017. All adults living in Ontario who attempted suicide or died by suicide are included in the study, and controls were matched by sex and age. Suicides were captured using vital statistics. Suicide attempts were determined using emergency department service codes. RESULTS: Rurality is a risk factor for attempted suicide and death by suicide. Rural males are more likely to die by suicide compared with urban males (adjusted odds ratio(AOR) = 1.70, 95% confidence interval (CI), 1.49 to 1.95), and the odds of death by suicide increase with increasing levels of rurality. Rural males and females have an increased risk of attempted suicide compared with their urban counterparts (males: AOR = 1.37, 95% CI, 1.24 to 1.50) (females: AOR = 1.26, 95% CI,  1.14 to 1.39), with a pattern of increasing risk of suicide attempts with increasing rurality. Rural females are not at increased risk of suicide compared with urban females (AOR = 1.08, 95% CI, 0.80 to 1.45). Sensitivity analyses corroborated the results. CONCLUSIONS: Rural males are almost two times more likely to die by suicide compared with urban males, and both rural males and females have an elevated risk of suicide attempts compared with urban residents. Future research should examine potential mediators of the relationship between rurality and suicide

Impact of the COVID-19 pandemic on antidepressant and antipsychotic use among children and adolescents: a population-based study

BackgroundThe COVID-19 pandemic was associated with increases in the prevalence of depression, anxiety and behavioural problems among children and youth. Less well understood is the influence of the pandemic on antidepressant and antipsychotic use among children. This is important, as it is possible that antidepressants and antipsychotics were used as a “stop-gap” measure to treat mental health symptoms when in-person access to outpatient care and school-based supportive services was disrupted. Furthermore, antipsychotics and antidepressants have been associated with harm in children and youth. We examined trends in dispensing of these medications two years following the pandemic among children 18 years of age and under in Ontario, Canada.MethodsWe conducted a population-based time-series study of antidepressant and antipsychotic medication dispensing to children and adolescents ≤18 years old between September 1, 2014, and March 31, 2022. We measured monthly population-adjusted rates of antidepressant and antipsychotics obtained from the IQVIA Geographic Prescription Monitor (GPM) database. We used structural break analyses to identify the pandemic month(s) when changes in the dispensing of antidepressants and antipsychotics occurred. We used interrupted time series models to quantify changes in dispensing following the structural break and compare observed and expected use of these drugs.ResultsOverall, we found higher-than-expected dispensing of antidepressants and antipsychotics in children and youth. Specifically, we observed an immediate step decrease in antidepressant dispensing associated with a structural break in April 2020 (−55.8 units per 1,000 individuals; 95% confidence intervals [CI] CI: −117.4 to 5.8), followed by an increased monthly trend in the rate of antidepressant dispensing of 13.0 units per 1,000 individuals (95% CI: 10.2–15.9). Antidepressant dispensing was consistently greater than predicted from September 2020 onward. Antipsychotic dispensing increased immediately following a June 2020 structural break (26.4 units per 1,000 individuals; 95% CI: 15.8–36.9) and did not change appreciably thereafter. Antipsychotic dispensing was higher than predicted at all time points from June 2020 onward.ConclusionWe found higher-than-expected dispensing of antidepressants and antipsychotics in children and youth. These increases were sustained through nearly two years of observation and are especially concerning in light of the potential for harm with the long-term use of antipsychotics in children. Further research is required to understand the clinical implications of these findings

Eviction filings during bans on enforcement throughout the COVID-19 pandemic: an interrupted time series analysis.

OBJECTIVE: Bans on evictions were implemented to reduce the spread of COVID-19 and to protect vulnerable populations during a public health crisis. Our objective was to examine how three bans on eviction enforcement impacted eviction filings from March 2020 through January 2022 in Ontario, Canada. METHODS: Data were derived from eviction application records kept by the Ontario Landlord and Tenant Board. We used segmented regression analysis to model changes in the average weekly filing rates for evictions due to non-payment of rent (L1 filings) and reasons other than non-payment of rent (L2 filings). RESULTS: The average number of weekly L1 and L2 applications dropped by 67.5 (95% CI: 55.2, 79.9) and 31.7 (95% CI: 26.7, 36.6) filings per 100,000 rental dwellings, respectively, following the first ban on eviction enforcement (p < 0.0001). Notably, they did not fall to zero. Level changes during the second and third bans were insubstantial and slope changes for L2 applications varied throughout the study period. The L1 filing rate appeared to increase towards the end of the study period (slope change: 1.3; 95% CI: 0.1, 2.6; p = 0.0387). CONCLUSION: Our findings suggest that while the first ban on eviction enforcement appeared to substantially reduce filing rates, subsequent bans were less effective and none of them eliminated eviction filings altogether. Enacting upstream policies that tackle the root causes of displacement would better equip jurisdictions during future public health emergencies

Neighborhood greenspace and health in a large urban center

Studies have shown that natural environments can enhance health and here we build upon that work by examining the associations between comprehensive greenspace metrics and health. We focused on a large urban population center (Toronto, Canada) and related the two domains by combining high-resolution satellite imagery and individual tree data from Toronto with questionnaire-based self-reports of general health perception, cardio-metabolic conditions and mental illnesses from the Ontario Health Study. Results from multiple regressions and multivariate canonical correlation analyses suggest that people who live in neighborhoods with a higher density of trees on their streets report significantly higher health perception and significantly less cardio-metabolic conditions (controlling for socio-economic and demographic factors). We find that having 10 more trees in a city block, on average, improves health perception in ways comparable to an increase in annual personal income of $10,000 and moving to a neighborhood with$10,000 higher median income or being 7 years younger. We also find that having 11 more trees in a city block, on average, decreases cardio-metabolic conditions in ways comparable to an increase in annual personal income of $20,000 and moving to a neighborhood with$20,000 higher median income or being 1.4 years younger

Neighborhood greenspace and health in a large urban center

Studies have shown that natural environments can enhance health and here we build upon that work by examining the associations between comprehensive greenspace metrics and health. We focused on a large urban population center (Toronto, Canada) and related the two domains by combining high-resolution satellite imagery and individual tree data from Toronto with questionnaire-based self-reports of general health perception, cardio-metabolic conditions and mental illnesses from the Ontario Health Study. Results from multiple regressions and multivariate canonical correlation analyses suggest that people who live in neighborhoods with a higher density of trees on their streets report significantly higher health perception and significantly less cardio-metabolic conditions (controlling for socio-economic and demographic factors). We find that having 10 more trees in a city block, on average, improves health perception in ways comparable to an increase in annual personal income of $10,000 and moving to a neighborhood with$10,000 higher median income or being 7 years younger. We also find that having 11 more trees in a city block, on average, decreases cardio-metabolic conditions in ways comparable to an increase in annual personal income of $20,000 and moving to a neighborhood with$20,000 higher median income or being 1.4 years younger

Making health data maps: a case study of a community/university research collaboration

This paper presents the main findings from a collaborative community/university research project in Canada. The goal of the project was to improve access to community health information, and in so doing, enhance our knowledge of the development of community health information resources and community/university collaboration. The project built on a rich history of community/university collaboration in Southeast Toronto (SETO), and employed an interdisciplinary applied research and action design. Specific project objectives were to: (1) develop via active community/university collaboration a geographic information system (GIS) for ready access to routinely collected health data, and to study logistical, conceptual and technical problems encountered during system development; and (2) to document and analyze issues that can emerge in the process of community/university research collaboration. System development involved iteration through community user assessment of need, development or refinement of the GIS, and assessment of the GIS by community users. Collaborative process assessment entailed analysis of archival material, interviews with investigators and participant observation. Over the course of the project, a system was successfully developed, and favorably assessed by users. System development problems fell into four main areas: maintaining user involvement in system development, understanding and integrating data, bringing disparate data sources together, and making use of assembled data. Major themes emerging from the community/university collaborative research process included separate community and university cultures, time as an important issue for all involved, and the impact of uncertainty and ambiguity on the collaborative process

Development of a neighborhood drivability index and its association with transportation behavior in Toronto.

Background: Car driving is a form of passive transport that is associated with an increase in physical inactivity, obesity, air pollution and noise. Built environment characteristics may influence transport mode choice, but comprehensive indices for built environment characteristics that drive car use are still lacking, while such an index could provide tangible policy entry points. Objective: We developed and validated a neighbourhood drivability index, capturing combined dimensions of the neighbourhood environment in the City of Toronto, and investigated its association with transportation choices (car, public transit or active transport), overall, by trip length, and combined for residential neighbourhood and workplace drivability. Methods: We used exploratory factor analysis to derive distinct factors (clusters of one or more environmental characteristics) that reflect the degree of car dependency in each neighbourhood, drawing from candidate variables that capture density, diversity, design, destination accessibility, distance to transit, and demand management. Area-level factor scores were then combined into a single composite score, reflecting neighbourhood drivability. Negative binomial generalized estimating equations were used to test the association between driveability quintiles (Q) and primary travel mode (>50% of trips by car, public transit, or walking/cycling) in a population-based sample of 63,766 Toronto residents enrolled in the Transportation Tomorrow Survey (TTS) wave 2016, adjusting for individual and household characteristics, and accounting for clustering of respondents within households. Results: The drivability index consisted of three factors: Urban sprawl, pedestrian facilities and parking availability. Relative to those living in the least drivable neighbourhoods (Q1), those in high drivability areas (Q5) had a significantly higher rate of car travel (adjusted Risk Ratio (RR): 1.80, 95%CI: 1.77–1.88), and lower rate of public transit use (RR: 0.90, 95%CI: 0.85–0.94) and walking/cycling (RR: 0.22, 95%CI: 0.19–0.25). Associations were strongest for short trips (<3 km) (RR: 2.72, 95%CI: 2.48–2.92), and in analyses where both residential and workplace drivability was considered (RR for car use in high/high vs. low/low residential/workplace drivability: 2.18, 95%CI: 2.08–2.29). Conclusion: This novel neighbourhood drivability index predicted whether local residents drive or use active modes of transportation and can be used to investigate the association between drivability, physical activity, and chronic disease risk

Higher Neighborhood Drivability Is Associated With a Higher Diabetes Risk in Younger Adults: A Population-Based Cohort Study in Toronto, Canada.

OBJECTIVE: Car dependency contributes to physical inactivity and, consequently, may increase the likelihood of diabetes. We investigated whether neighborhoods that are highly conducive to driving confer a greater risk of developing diabetes and, if so, whether this differs by age. RESEARCH DESIGN AND METHODS: We used administrative healthcare data to identify all working-age Canadian adults (20-64 years) who were living in Toronto on 1 April 2011 without diabetes (type 1 or 2). Neighborhood drivability scores were assigned using a novel, validated index that predicts driving patterns based on built environment features divided into quintiles. Cox regression was used to examine the association between neighborhood drivability and 7-year risk of diabetes onset, overall and by age-group, adjusting for baseline characteristics and comorbidities. RESULTS: Overall, there were 1,473,994 adults in the cohort (mean age 40.9 ± 12.2 years), among whom 77,835 developed diabetes during follow-up. Those living in the most drivable neighborhoods (quintile 5) had a 41% higher risk of developing diabetes compared with those in the least drivable neighborhoods (adjusted hazard ratio 1.41, 95% CI 1.37-1.44), with the strongest associations in younger adults aged 20-34 years (1.57, 95% CI 1.47-1.68, P < 0.001 for interaction). The same comparison in older adults (55-64 years) yielded smaller differences (1.31, 95% CI 1.26-1.36). Associations appeared to be strongest in middle-income neighborhoods for younger residents (middle income 1.96, 95% CI 1.64-2.33) and older residents (1.46, 95% CI 1.32-1.62). CONCLUSIONS: High neighborhood drivability is a risk factor for diabetes, particularly in younger adults. This finding has important implications for future urban design policies