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Objective: To examine diabetes screening, predictors of screening, and the burden of undiagnosed diabetes in the immigrant population and whether these estimates differ by ethnicity.Research Design and Methods: A population-based retrospective cohort linking administrative health data to immigration files was used to follow the entire diabetes-free population aged 40 years and up in Ontario, Canada (N = 3,484,222) for 3 years (2004-2007) to determine whether individuals were screened for diabetes. Multivariate regression was used to determine predictors of having a diabetes test.Results: Screening rates were slightly higher in the immigrant versus the general population (76.0 and 74.4%, respectively; P < 0.001), with the highest rates in people born in South Asia, Mexico, Latin America, and the Caribbean. Immigrant seniors (age ≥65 years) were screened less than nonimmigrant seniors. Percent yield of new diabetes subjects among those screened was high for certain countries of birth (South Asia, 13.0%; Mexico and Latin America, 12.1%; Caribbean, 9.5%) and low among others (Europe, Central Asia, U.S., 5.1-5.2%). The number of physician visits was the single most important predictor of screening, and many high-risk ethnic groups required numerous visits before a test was administered. The proportion of diabetes that remained undiagnosed was estimated to be 9.7% in the general population and 9.0% in immigrants.Conclusions: Overall diabetes-screening rates are high in Canada's universal health care setting, including among high-risk ethnic groups. Despite this finding, disparities in screening rates between immigrant subgroups persist and multiple physician visits are often required to achieve recommended screening levels. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Congestive heart failure (CHF) is increasingly recognized as an important cause of morbidity and mortality. Previous studies in urban settings have shown that patients frequently are not receiving recommended therapy. There is a paucity of studies that have evaluated CHF management in a rural setting. We therefore reviewed hospital and outpatient care in this setting as an initial step toward improving CHF care. METHOD: A retrospective chart review was used to examine the care of all 34 patients hospitalized for CHF from 2000-2001 in a small rural hospital, to assess the need for improved CHF management. RESULTS: The median age of the patients was 78 yr, and a number of them had many co-morbid cardiovascular risks. Similar to other studies, only 23% of patients were prescribed recommended doses of angiotensin-converting enzyme (ACE) inhibitors. Use of beta-blockers was far below expected rates. Although there was follow-up care for nearly all patients (97%), few patients had echocardiography performed (38%) or had their medications altered in the outpatient setting. CONCLUSION: There is a need for improved management of CHF in the rural setting. Approaches to improving CHF care should use the continuity of care advantage provided by primary care physicians to optimize outpatient medical treatment regimens and improve access to diagnostic services such as echocardiography. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the use of low-molecular-weight heparin (LMWH) for acute coronary syndromes (ACS) in a rural setting.Methods: A review of LMWH effectiveness and a simplified costing exercise that focused on potential differences between rural and urban settings for delivering LMWH versus unfractionated heparin (UFH).Results: LMWH is as clinically effective as UFH for the treatment of ACS in a rural setting. The estimated drug delivery cost of the dalteparin ($65 per admission) was less than that for UFH ($110). The high cost of after-hours activated partial thromboplastin time monitoring in a rural setting ($86 per admission) more than offset the increased cost of LMWH compared to UFH.Conclusions: LMWH is the heparin of choice for the treatment of ACS in a rural setting. The method of using an abbreviated effectiveness and costing exercise may be a practical approach for evaluating other health interventions in a rural setting. [ABSTRACT FROM AUTHOR]

Background: Mortality has declined substantially among people with diabetes mellitus over the last decade. Whether all income groups have benefited equally, however, is unclear. We examined the impact of income on mortality trends among people with diabetes.Methods: In this population-based, retrospective cohort study, we compared changes in mortality from Apr. 1, 1994, to Mar. 31, 2005, by neighbourhood income strata among people with diabetes aged 30 years or more in the province of Ontario, Canada.Results: Overall, the annual age- and sex-adjusted mortality declined, from 4.05% in 1994/95 (95% confidence interval [CI] 3.98%-4.11%) to 2.69% in 2005/06 (95% CI 2.66%-2.73%). The decrease was significantly greater in the highest income group (by 36%) than in the lowest income group (by 31%; p < 0.001). This trend was most pronounced in the younger group (age 30-64 years): the mortality rate ratio widened by more than 40% between the lowest and highest income groups, from 1.12 to 1.59 among women and from 1.14 to 1.60 among men. Income had a much smaller effect on mortality trends in the older group, whose drug costs are subsidized: the income-related difference rose by only 0.9% over the study period.Interpretation: Mortality declined overall among people with diabetes from 1994 to 2005; however, the decrease was substantially greater in the highest income group than in the lowest, particularly among those aged 30-64 years. These findings illustrate the increasing impact of income on the health of people with diabetes even in a publicly funded health care setting. Further studies are needed to explore factors responsible for these income-related differences in mortality. [ABSTRACT FROM AUTHOR]

Background: There are concerns that testing for type 2 diabetes is low and many people with diabetes are not diagnosed. We sought to describe the rates of diabetes-related lab testing in Ontario from 1995-2005, among adults without diabetes, and to explore the extent to which the Canadian clinical practice guidelines for screening are being followed.Methods: Descriptive counts of outpatient diabetes laboratory tests performed within Ontario's publicly funded, provincial health insurance program were recorded. The study population was Ontario residents, 20 years and older from 1995 to 2005 (9.3 million people in 2005). The Ontario Diabetes Database, a cumulative registry derived from administrative health records, was used to exclude people who had physician-diagnosed diabetes (n = 839,127 in 2005) from the primary analyses. Diabetes tests included serum blood glucose (SBG), hemoglobin A1c (HbA1c), and oral glucose tolerance tests (OGTT).Results: In 2005, 37% of Ontario adults without pre-existing diabetes were tested with an SBG test, a 28% increase from 1995. The age-adjusted proportion of adults without diabetes undergoing a HbA1c test increased from 1.7% in 1995 to 6.0% in 2005. In 2005, a similar number of HbA1c tests were performed for individuals with diabetes (483,746) and without diabetes (496,616) despite large differences in the two groups' denominators. Less than 1% of Ontarians underwent OGTT testing in any year between 1995-2005. Nearly two-thirds of adults age 40 years and over had an SBG test over a 3-year period (April 1, 2002-March 31, 2005), in accordance with the Canadian Diabetes Association recommendations.Conclusion: Diabetes testing is common and has increased over the last ten years. Despite its absence in Canada's diabetes screening recommendations, HbA1c testing among individuals without diabetes is increasing rapidly, and OGTT, which is recommended, is rarely performed. [ABSTRACT FROM AUTHOR]

Background: The purposes of this cohort study were to establish how frequently people with physician-diagnosed diabetes self-reported the disease, to determine factors associated with self-reporting of diabetes, and to evaluate subsequent differences in self-management behaviour, health care utilisation and clinical outcomes between people who do and do not report their disease.Methods: We used a registry of physician-diagnosed diabetes as a reference standard. We studied respondents to a 2000/01 population-based health survey who were in the registry (n = 1,812), and we determined the proportion who reported having diabetes during the survey. Baseline factors associated with self-report and subsequent behavioural, utilisation and clinical differences between those who did and did not self-report were defined from the survey responses and from linkage with administrative data sources.Results: Only 75% of people with physician-diagnosed diabetes reported having the disease. People who did self-report were more likely to be male, to live in rural areas, to have longer disease duration and to have received specialist physician care. People who did not report having diabetes in the survey were markedly less likely to perform capillary blood glucose monitoring in the subsequent two years (OR 0.05, 95% CI 0.02 to 0.08). They were also less likely to receive specialist physician care (OR 0.55, 95% CI 0.37 to 0.86), and were less likely to require hospital care for hypo- or hyperglycaemia (OR 0.09, 95% CI 0.01 to 0.28).Conclusion: Many people with physician-diagnosed diabetes do not report having the disease, but most demographic and clinical features do not distinguish these individuals. These individuals are much less likely to perform capillary glucose monitoring, suggesting that their diabetes self-management is inadequate. Clinicians may be able to use the absence of glucose monitoring as a screening tool to identify people needing a detailed evaluation of their disease knowledge. [ABSTRACT FROM AUTHOR]

Background: Day-to-day variation in the measurement of SARS-CoV-2 in wastewater can challenge public health interpretation. We assessed a Bayesian smoothing and forecasting method previously used for surveillance and short-term projection of COVID-19 cases, hospitalizations, and deaths., Methods: SARS-CoV-2 viral measurement from the sewershed in Ottawa, Canada, sampled at the municipal wastewater treatment plant from July 1, 2020, to February 15, 2022, was used to assess and internally validate measurement averaging and prediction. External validation was performed using viral measurement data from influent wastewater samples from 15 wastewater treatment plants and municipalities across Ontario., Results: Plots of SARS-CoV-2 viral measurement over time using Bayesian smoothing visually represented distinct COVID-19 "waves" described by case and hospitalization data in both initial (Ottawa) and external validation in 15 Ontario communities. The time-varying growth rate of viral measurement in wastewater samples approximated the growth rate observed for cases and hospitalization. One-week predicted viral measurement approximated the observed viral measurement throughout the assessment period from December 23, 2020, to August 8, 2022. An uncalibrated model showed underprediction during rapid increases in viral measurement (positive growth) and overprediction during rapid decreases. After recalibration, the model showed a close approximation between observed and predicted estimates., Conclusion: Bayesian smoothing of wastewater surveillance data of SARS-CoV-2 allows for accurate estimates of COVID-19 growth rates and one- and two-week forecasting of SARS-CoV-2 in wastewater for 16 municipalities in Ontario, Canada. Further assessment is warranted in other communities representing different sewersheds and environmental conditions., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2024. Published by Elsevier B.V.)

Objectives: To develop and validate a model to predict time-to-LTC admissions among individuals with dementia., Design: Population-based retrospective cohort study using health administrative data., Setting and Participants: Community-dwelling older adults (65+) in Ontario living with dementia and assessed with the Resident Assessment Instrument for Home Care (RAI-HC) between April 1, 2010 and March 31, 2017., Methods: Individuals in the derivation cohort (n = 95,813; assessed before March 31, 2015) were followed for up to 360 days after the index RAI-HC assessment for admission into LTC. We used a multivariable Fine Gray sub-distribution hazard model to predict the cumulative incidence of LTC entry while accounting for all-cause mortality as a competing risk. The model was validated in 34,038 older adults with dementia with an index RAI-HC assessment between April 1, 2015 and March 31, 2017., Results: Within one year of a RAI-HC assessment, 35,513 (37.1%) individuals in the derivation cohort and 10,735 (31.5%) in the validation cohort entered LTC. Our algorithm was well-calibrated (Emax = 0.119, ICIavg = 0.057) and achieved a c-statistic of 0.707 (95% confidence interval: 0.703-0.712) in the validation cohort., Conclusions and Implications: We developed an algorithm to predict time to LTC entry among individuals living with dementia. This tool can inform care planning for individuals with dementia and their family caregivers., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background and Aims: Alcohol retail access is associated with alcohol use and related harms. This study measured whether this association differs for people with and without heavy and disordered patterns of alcohol use., Design: The study used a repeated cross-sectional analysis of health administrative databases., Setting, Participants/cases: All residents of Ontario, Canada aged 10-105 years with universal health coverage (n = 10 677 604 in 2013) were included in the analysis., Measurements: Quarterly rates of emergency department (ED) and outpatient visits attributable to alcohol in 464 geographic regions between 2013 and 2019 were measured. Quarterly off-premises alcohol retail access scores were calculated (average drive to the closest seven stores) for each geographic region. Mixed-effect linear regression models adjusted for area-level socio-demographic covariates were used to examine associations between deciles of alcohol retail access and health-care visits attributable to alcohol. Stratified analyses were run for individuals with and without prior alcohol-attributable health-care use in the past 2 years., Findings: We included 437 707 ED visits and 505 271 outpatient visits attributable to alcohol. After adjustment, rates of ED visits were 39% higher [rate ratio (RR) = 1.39, 95% confidence interval (CI) = 1.20-1.61] and rates of outpatient visits were 49% higher (RR = 1.49, 95% CI = 1.26-1.75) in the highest versus lowest decile of alcohol access. There was a positive association between alcohol access and outpatient visits attributable to alcohol for individuals without prior health-care attributable to alcohol (RR = 1.65, 95% CI = 1.39-1.95 for the highest to lowest decile of alcohol access) but not for individuals with prior health-care attributable to alcohol (RR = 1.08, 95% CI = 0.90-1.30). There was a positive association between alcohol access and ED visits attributable to alcohol for individuals with and without prior health-care for alcohol for ED visits., Conclusion: In Ontario, Canada, greater alcohol retail access appears to be associated with higher rates of emergency department (ED) and outpatient health-care visits attributable to alcohol. Individuals without prior health-care for alcohol may be more susceptible to greater alcohol retail access for outpatient but not ED visits attributable to alcohol., (© 2024 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Objectives: This study aimed to assess the acceptability, value, and perceived barriers of using electronic risk calculators for predicting and communicating the risk of death in community-dwelling older adults., Methods: One focus group and eight interviews were conducted with 16 participants with experience caring for patients or family members at end of life. A prototype mortality risk tool was used to anchor discussions. Data were analysed using a qualitative content analysis approach., Results: Five themes emerged: acceptability, communication, barriers to use, broadening the circle of care, and tool limitations. Participants found the tool helpful for preparation, planning, and providing care, but disagreed on its community availability. Personalized risk estimates were valued for facilitating early goals of care conversations and normalizing discussions about death. However, concerns were raised about the tool's interpretation for individuals with different language, cultural, or educational backgrounds., Conclusions: While electronic risk calculators were found to be acceptable, balancing autonomy with varying preferences for receiving the information and potential need for support is crucial., Innovation: Providing patient-oriented life-expectancy estimates can enhance decisional capacity and facilitate shared decision-making between patients, their families, and healthcare professionals. Further research is needed to explore effective communication of personalized risk tools and additional benefits, harms, and barriers to implementation., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V.)

Objectives: To develop and test the direct and indirect associations between caregiver distress and its many contributing factors and covariates., Design: Analysis using data from a national, cross-sectional survey of Canadian caregivers., Setting and Participants: A total of 6502 respondents of the 2012 General Social Survey-Caregiving and Care-receiving who self-identified as a caregiver., Methods: We used exploratory structural equation modeling to achieve our aims. Based on literature review, we hypothesized a structural model of 5 caregiving factors that contribute to distress: caregiving burden, caregiving network and support, disruptions of family and social life, positive emotional experiences, and caregiving history. Survey items hypothesized to measure each latent factor were modeled using exploratory factor analysis (EFA). After establishing a well-fit EFA model, structural equation modeling was performed to examine the relationships between caregiving factors and caregiver distress while controlling for covariates such as caregiver's and care-recipient's sociodemographic characteristics and kinship., Results: EFA established a well-fit model that represented caregiver distress and its 5 contributing factors as hypothesized. Although all 5 had significant effects on caregiver distress, disruptions of family and social life contributed the most (β = 0.462), almost 3 times that of caregiving burden (β = 0.162). Positive emotional experiences also substantially reduced distress (β = -0.310)., Conclusions and Implications: Understanding the multifaceted nature of caregiver distress is crucial for developing effective strategies to support caregivers. In addition to reducing caregiving burden, having flexible resources and policies to minimize disruptions to caregivers' families (eg, flexible work policies; family-oriented education, training, and counseling) and enhance the positive aspects of caregiving may more effectively reduce distress., Competing Interests: Disclosure The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Language barriers can impact health care and outcomes. Valid and reliable language data is central to studying health inequalities in linguistic minorities. In Canada, language variables are available in administrative health databases; however, the validity of these variables has not been studied. This study assessed concordance between language variables from administrative health databases and language variables from the Canadian Community Health Survey (CCHS) to identify Francophones in Ontario., Methods: An Ontario combined sample of CCHS cycles from 2000 to 2012 (from participants who consented to link their data) was individually linked to three administrative databases (home care, long-term care [LTC], and mental health admissions). In total, 27,111 respondents had at least one encounter in one of the three databases. Language spoken at home (LOSH) and first official language spoken (FOLS) from CCHS were used as reference standards to assess their concordance with the language variables in administrative health databases, using the Cohen kappa, sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV)., Results: Language variables from home care and LTC databases had the highest agreement with LOSH (kappa = 0.76 [95%CI, 0.735-0.793] and 0.75 [95%CI, 0.70-0.80], respectively) and FOLS (kappa = 0.66 for both). Sensitivity was higher with LOSH as the reference standard (75.5% [95%CI, 71.6-79.0] and 74.2% [95%CI, 67.3-80.1] for home care and LTC, respectively). With FOLS as the reference standard, the language variables in both data sources had modest sensitivity (53.1% [95%CI, 49.8-56.4] and 54.1% [95%CI, 48.3-59.7] in home care and LTC, respectively) but very high specificity (99.8% [95%CI, 99.7-99.9] and 99.6% [95%CI, 99.4-99.8]) and predictive values. The language variable from mental health admissions had poor agreement with all language variables in the CCHS., Conclusions: Language variables in home care and LTC health databases were most consistent with the language often spoken at home. Studies using language variables from administrative data can use the sensitivity and specificity reported from this study to gauge the level of mis-ascertainment error and the resulting bias., (© 2024. The Author(s).)

Background: Cardiovascular disease is a leading cause of death in Canada, but how the major cardiovascular risk factors vary across ethnicity and immigration status has yet to be examined., Methods: Using data from the Canadian Community Health Surveys, national trends in health conditions (hypertension, diabetes, high blood cholesterol level, and obesity) and health behaviours (smoking, activity levels, and alcohol consumption) were estimated for the period 2001-2018. In this cross-sectional study, the trends were then compared across sex, age, ethnicity, and immigration status., Results: A total of 1,065,391 respondents were examined, for the period 2001-2018. During the study period, the prevalence of the following risk factors increased in Canada over time, as follows: diabetes by 54.5%; hypertension by 23.4%; and obesity by 32.3%. For health behaviours, smoking prevalence decreased overall, especially in racialized populations. Heavy drinking was most prevalent for nonracialized and non-Indigenous Canadian-born populations, and was of lowest prevalence among racialized immigrants. Physical inactivity was most prevalent for racialized immigrant populations. The prevalence of self-reported heart disease decreased by 21.0%, except for racialized established immigrants (≥ 10 years since immigration to Canada), who had a 4.2% increase., Conclusions: During this study period, decreases occurred in the prevalences of smoking and physical inactivity, along with increases in obesity, diabetes, and hypertension prevalences. By migration-group status, established immigrants in Canada had a higher prevalence of cardiovascular disease risk factors compared to that among their Canadian-born counterparts. Migration gaps should be considered in future interventions targeted at reducing these cardiovascular risk factors in Canada., (© 2024 The Authors.)

Objective: Estimate the impact of 20 % flat-rate and tiered sugary drink tax structures on the consumption of sugary drinks, sugar-sweetened beverages and 100 % juice by age, sex and socio-economic position., Design: We modelled the impact of price changes - for each tax structure - on the demand for sugary drinks by applying own- and cross-price elasticities to self-report sugary drink consumption measured using single-day 24-h dietary recalls from the cross-sectional, nationally representative 2015 Canadian Community Health Survey-Nutrition. For both 20 % flat-rate and tiered sugary drink tax scenarios, we used linear regression to estimate differences in mean energy intake and proportion of energy intake from sugary drinks by age, sex, education, food security and income., Setting: Canada., Participants: 19 742 respondents aged 2 and over., Results: In the 20 % flat-rate scenario, we estimated mean energy intake and proportion of daily energy intake from sugary drinks on a given day would be reduced by 29 kcal/d (95 % UI: 18, 41) and 1·3 % (95 % UI: 0·8, 1·8), respectively. Similarly, in the tiered tax scenario, additional small, but meaningful reductions were estimated in mean energy intake (40 kcal/d, 95 % UI: 24, 55) and proportion of daily energy intake (1·8 %, 95 % UI: 1·1, 2·5). Both tax structures reduced, but did not eliminate, inequities in mean energy intake from sugary drinks despite larger consumption reductions in children/adolescents, males and individuals with lower education, food security and income., Conclusions: Sugary drink taxation, including the additional benefit of taxing 100 % juice, could reduce overall and inequities in mean energy intake from sugary drinks in Canada.

Background: In Canada, only 15% of patients requiring palliative care receive such services in the year before death. We describe health care utilization patterns among home care users in their last 6 months of life to inform care planning for older people with varying mortality risks and evolving care needs as they decline., Methods: Using population health administrative data from Ontario, we performed a retrospective cohort study involving home care clients aged 50 years and older who received at least 1 interRAI (Resident Assessment Instrument) Home Care assessment between April 2018 and September 2019. We report the proportion of clients who used acute care, long-term care, and palliative home care services within 6 months of their assessment, stratified by their predicted 6-month mortality risk using a prognostic tool called the Risk Evaluation for Support: Predictions for Elder-life in their Communities Tool (RESPECT) and vital status., Results: The cohort included 247 377 adults, 11.9% of whom died within 6 months of an assessment. Among decedents, 50.6% of those with a RESPECT-estimated median survival of fewer than 3 months received at least 1 nonphysician palliative home care visit before death. This proportion declined to 38.7% and 29.5% among decedents with an estimated median survival between 3 and 6 months and between 6 and 12 months, respectively., Interpretation: Many older adults in Ontario do not receive any palliative home care before death. Prognostic tools such as RESPECT may improve recognition of reduced life expectancies and palliative care needs of individuals in their final years of life., Competing Interests: Competing interests: Amy Hsu is an executive lead on the steering committee of the Ontario Centres for Learning, Research, and Innovation in Long-Term Care. Funding for the centres comes from the Ontario Ministry of Health and Ministry of Long-Term Care and is partially administered by the Bruyère Research Institute. No other competing interests were declared., (© 2024 CMA Impact Inc. or its licensors.)

Introduction: Avoidable hospitalizations are considered preventable given effective and timely primary care management and are an important indicator of health system performance. The ability to predict avoidable hospitalizations at the population level represents a significant advantage for health system decision-makers that could facilitate proactive intervention for ambulatory care-sensitive conditions (ACSCs). The aim of this study is to develop and validate the Avoidable Hospitalization Population Risk Tool (AvHPoRT) that will predict the 5-year risk of first avoidable hospitalization for seven ACSCs using self-reported, routinely collected population health survey data., Methods and Analysis: The derivation cohort will consist of respondents to the first 3 cycles (2000/01, 2003/04, 2005/06) of the Canadian Community Health Survey (CCHS) who are 18-74 years of age at survey administration and a hold-out data set will be used for external validation. Outcome information on avoidable hospitalizations for 5 years following the CCHS interview will be assessed through data linkage to the Discharge Abstract Database (1999/2000-2017/2018) for an estimated sample size of 394,600. Candidate predictor variables will include demographic characteristics, socioeconomic status, self-perceived health measures, health behaviors, chronic conditions, and area-based measures. Sex-specific algorithms will be developed using Weibull accelerated failure time survival models. The model will be validated both using split set cross-validation and external temporal validation split using cycles 2000-2006 compared to 2007-2012. We will assess measures of overall predictive performance (Nagelkerke R 2 ), calibration (calibration plots), and discrimination (Harrell's concordance statistic). Development of the model will be informed by the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement., Ethics and Dissemination: This study was approved by the University of Toronto Research Ethics Board. The predictive algorithm and findings from this work will be disseminated at scientific meetings and in peer-reviewed publications., (© 2024. The Author(s).)

The recent SARS-COV-2 pandemic has sparked the adoption of wastewater-based epidemiology (WBE) as a low-cost way to monitor the health of populations. In parallel, the pandemic has encouraged researchers to openly share their data to serve the public better and accelerate science. However, environmental surveillance data are highly dependent on context and are difficult to interpret meaningfully across sites. This paper presents the second iteration of the Public Health Environmental Surveillance Open Data Model (PHES-ODM), an open-source dictionary and set of data tools to enhance the interoperability of environmental surveillance data and enable the storage of contextual (meta)data. The data model describes how to store environmental surveillance program data, metadata about measurements taken on various specimens (water, air, surfaces, sites, populations) and data about measurement protocols. The model provides software tools that support the collection and use of PHES-ODM formatted data, including performing PCR calculations and data validation, recording data into input templates, generating wide tables for analysis, and producing SQL database definitions. Fully open-source and already adopted by institutions in Canada, the European Union, and other countries, the PHES-ODM provides a path forward for creating robust, interoperable, open datasets for environmental public health surveillance for SARS-CoV-2 and beyond.

Background: Prior studies have demonstrated the negative impact of language barriers on access, quality, and safety of healthcare, which can lead to health disparities in linguistic minorities. As the population ages, those with multiple chronic diseases will require increasing levels of home care and long-term services. This study described the levels of multimorbidity among recipients of home care in Ontario, Canada by linguistic group., Methods: Population-based retrospective cohort of 510,685 adults receiving home care between April 1, 2010, to March 31, 2018, in Ontario, Canada. We estimated and compared prevalence and characteristics of multimorbidity (2 or more chronic diseases) across linguistic groups (Francophones, Anglophones, Allophones). The most common combinations and clustering of chronic diseases were examined. Logistic regression models were used to explore the main predictors of 'severe' multimorbidity (defined as the presence of five or more chronic diseases)., Results: The proportion of home care recipients with multimorbidity and severe multimorbidity was 92% and 44%, respectively. The prevalence of multimorbidity was slightly higher among Allophones (93.6%) than among Anglophones (91.8%) and Francophones (92.4%). However, Francophones had higher rates of cardiovascular and respiratory disease (64.9%) when compared to Anglophones (60.2%) and Allophones (61.5%), while Anglophones had higher rates of cancer (34.2%) when compared to Francophones (25.2%) and Allophones (24.3%). Relative to Anglophones, Allophones were more likely to have severe multimorbidity (adjusted OR = 1.04, [95% CI: 1.02-1.06])., Conclusions: The prevalence of multimorbidity among Ontarians receiving home care services is high; especially for whose primary language is a language other than English or French (i.e., Allophones). Understanding differences in the prevalence and characteristics of multimorbidity across linguistic groups will help tailor healthcare services to the unique needs of patients living in minority linguistic situations., (© 2023. The Author(s).)

Background: The route into the body for many pathogens is through the eyes, nose and mouth (i.e., the 'T-zone') via inhalation or fomite-based transfer during face touching. It is important to understand factors that are associated with touching the T-zone to inform preventive strategies., Purpose: To identify theory-informed predictors of intention to reduce facial 'T-zone' touching and self-reported 'T-zone' touching., Methods: We conducted a nationally representative prospective questionnaire study of Canadians. Respondents were randomized to answer questions about touching their eyes, nose, or mouth with a questionnaire assessing 11 factors from an augmented Health Action Process Approach at baseline: intention, outcome expectancies, risk perception, individual severity, self-efficacy, action planning, coping planning, social support, automaticity, goal facilitation and stability of context. At 2-week follow-up, we assessed HAPA-based indicators of self-regulatory activities (awareness of standards, effort, self-monitoring) and self-reported behaviour (primary dependent variable)., Results: Of 656 Canadian adults recruited, 569 responded to follow-up (87% response rate). Across all areas of the 'T-zone', outcome expectancy was the strongest predictor of intention to reduce facial 'T-zone' touching, while self-efficacy was a significant predictor for only the eyes and mouth. Automaticity was the strongest predictor of behaviour at the 2-week follow-up. No sociodemographic or psychological factors predicted behaviour, with the exception of self-efficacy, which negatively predicted eye touching., Conclusion: Findings suggest that focusing on reflective processes may increase intention to reduce 'T-zone' touching, while reducing actual 'T-zone' touching may require strategies that address the automatic nature of this behaviour., (© 2023 The Authors. British Journal of Health Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Importance: The impact of nonmedical cannabis legalization on traffic injuries and cannabis involvement in traffic injuries is unclear., Objective: To examine changes in the number and characteristics of cannabis-involved traffic injury emergency department (ED) visits from before to after legalization and subsequent commercialization (ie, increased retail store and product availability) of cannabis in Ontario, Canada., Design, Setting, and Participants: This repeated cross-sectional study examined changes in cannabis- and alcohol-involved traffic injury ED visits in Ontario, Canada, during 3 time periods: prelegalization (January 2010-September 2018), legalization with product and retail store restrictions (October 2018-February 2020), and commercialization with new products and expanded number of stores, which coincided with the COVID-19 pandemic (March 2020-December 2021). All individuals aged 16 years and older eligible for Ontario's Universal Health Coverage were included. Season- and time-adjusted quasi-Poisson models were used to generate rate ratios with 95% CIs. Data were analyzed from March to April 2023., Main Outcomes and Measures: Quarterly counts of cannabis-involved ED visits for traffic injury., Results: There were 947 604 traffic injury ED visits, of which 426 (0.04%) had documented cannabis involvement and 7564 (0.8%) had documented alcohol involvement. Of the 418 individuals with documented cannabis involvement, 330 (78.9%) were male, 109 (25.6%) were aged 16 to 21 years (mean [SD] age at visit, 30.6 [12.0] years), and 113 (27.0%) had an ED visit or hospitalization for substance use in the 2 years before their traffic injury ED visit. Annual rates of cannabis-involved traffic injury ED visits increased 475.3% over the study period (0.18 visits per 1000 total motor vehicle collisions in 2010 to 1.01 in 2021). Over the same period, alcohol-involved traffic injury ED visits increased by 9.4% (8.03 in 2010 to 8.79 per 1000 traffic injury ED visits in 2021). Legalization with restrictions was associated with a 94% increase in the quarterly rate of cannabis involvement in traffic injury ED visits relative to prelegalization (adjusted rate ratio [aRR], 1.94; 95% CI, 1.37-2.75). Commercialization/COVID-19 was associated with a greater increase of 223% in rates (aRR, 3.23; 95% CI, 2.42-4.33). After adjusting for time trends before legalization, only commercialization/COVID-19 was associated with increased rates. Male sex (adjusted odds ratio [aOR], 3.38; 95% CI, 2.66-4.29), living in the lowest-income neighborhood (aOR, 1.92; 95% CI, 1.39-2.67), being aged 19 to 21 years (aOR, 4.67; 95% CI, 3.27-6.67), and having a prior cannabis-related ED visit (aOR, 8.03; 95% CI, 5.85-11.02) were all positively associated with cannabis involvement during a traffic injury ED visit., Conclusions and Relevance: This cross-sectional study found large increases in cannabis involvement in ED visits for traffic injury over time, which may have accelerated following nonmedical cannabis commercialization. Although the frequency of visits was rare, they may reflect broader changes in cannabis-impaired driving. Greater prevention efforts, including targeted education and policy measures, in regions with legal cannabis are indicated.

Monitoring of viral signal in wastewater is considered a useful tool for monitoring the burden of COVID-19, especially during times of limited availability in testing. Studies have shown that COVID-19 hospitalizations are highly correlated with wastewater viral signals and the increases in wastewater viral signals can provide an early warning for increasing hospital admissions. The association is likely nonlinear and time-varying. This project employs a distributed lag nonlinear model (DLNM) (Gasparrini et al., 2010) to study the nonlinear exposure-response delayed association of the COVID-19 hospitalizations and SARS-CoV-2 wastewater viral signals using relevant data from Ottawa, Canada. We consider up to a 15-day time lag from the average of SARS-CoV N1 and N2 gene concentrations to COVID-19 hospitalizations. The expected reduction in hospitalization is adjusted for vaccination efforts. A correlation analysis of the data verifies that COVID-19 hospitalizations are highly correlated with wastewater viral signals with a time-varying relationship. Our DLNM based analysis yields a reasonable estimate of COVID-19 hospitalizations and enhances our understanding of the association of COVID-19 hospitalizations with wastewater viral signals., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Background: Physician home visits are associated with better health outcomes, yet most patients near the end of life never receive such a visit. Our objectives were to describe the receipt of physician home visits during the last year of life after a referral to home care - an indication that the patient can no longer live independently - and to measure associations between patient characteristics and receipt of a home visit., Methods: We conducted a retrospective cohort study using linked population-based health administrative databases housed at ICES. We identified adult (aged ≥ 18 yr) decedents in Ontario who died between Mar. 31, 2013, and Mar. 31, 2018, who were receiving primary care and were referred to publicly funded home care services. We described the provision of physician home visits, office visits and telephone management. We used multinomial logistic regression to calculate the odds of receiving home visits from a rostered primary care physician, controlling for referral during the last year of life, age, sex, income quintile, rurality, recent immigrant status, referral by rostered physician, referral during hospital stay, number of chronic conditions and disease trajectory based on the cause of death., Results: Of the 58 753 decedents referred in their last year of life, 3125 (5.3%) received a home visit from their family physician. Patient characteristics associated with higher odds of receiving home visits compared to office-based or telephone-based care were being female (adjusted odds ratio [OR] 1.28, 95% confidence interval [CI] 1.21-1.35), being 85 years of age or older (adjusted OR 2.42, 95% CI 1.80-3.26) and living in a rural area (adjusted OR 1.09, 95% CI 1.00-1.18). Increased odds were associated with home care referrals by the patient's primary care physician (adjusted OR 1.49, 95% CI 1.39-1.58) and referrals occurring during a hospital stay (adjusted OR 1.20, 95% CI 1.13-1.28)., Interpretation: A small proportion of patients near the end of life received home-based physician care, and patient characteristics did not explain the low visit rates. Future work on system- and provider-level factors may be critical to improve access to home-based end-of-life primary care., Competing Interests: Competing interests: None declared., (© 2023 CMA Impact Inc. or its licensors.)

Optimal performance is desired for decision-making in any field with binary classifiers and diagnostic tests, however common performance measures lack depth in information. The area under the receiver operating characteristic curve (AUC) and the area under the precision recall curve are too general because they evaluate all decision thresholds including unrealistic ones. Conversely, accuracy, sensitivity, specificity, positive predictive value and the F1 score are too specific-they are measured at a single threshold that is optimal for some instances, but not others, which is not equitable. In between both approaches, we propose deep ROC analysis to measure performance in multiple groups of predicted risk (like calibration), or groups of true positive rate or false positive rate. In each group, we measure the group AUC (properly), normalized group AUC, and averages of: sensitivity, specificity, positive and negative predictive value, and likelihood ratio positive and negative. The measurements can be compared between groups, to whole measures, to point measures and between models. We also provide a new interpretation of AUC in whole or part, as balanced average accuracy, relevant to individuals instead of pairs. We evaluate models in three case studies using our method and Python toolkit and confirm its utility.

Background: Prediction tools that incorporate self-reported health information could increase CKD awareness, identify modifiable lifestyle risk factors, and prevent disease. We developed and validated a survey-based prediction equation to identify individuals at risk for incident CKD (eGFR <60 ml/min per 1.73 m2), with and without a baseline eGFR., Methods: A cohort of adults with an eGFR ≥70 ml/min per 1.73 m2 from Ontario, Canada, who completed a comprehensive general population health survey between 2000 and 2015 were included (n=22,200). Prediction equations included demographics (age, sex), comorbidities, lifestyle factors, diet, and mood. Models with and without baseline eGFR were derived and externally validated in the UK Biobank (n=15,522). New-onset CKD (eGFR <60 ml/min per 1.73 m2) with ≤8 years of follow-up was the primary outcome., Results: Among Ontario individuals (mean age, 55 years; 58% women; baseline eGFR, 95 (SD 15) ml/min per 1.73 m2), new-onset CKD occurred in 1981 (9%) during a median follow-up time of 4.2 years. The final models included lifestyle factors (smoking, alcohol, physical activity) and comorbid illnesses (diabetes, hypertension, cancer). The model was discriminating in individuals with and without a baseline eGFR measure (5-year c-statistic with baseline eGFR: 83.5, 95% confidence interval [CI], 82.2 to 84.9; without: 81.0, 95% CI, 79.8 to 82.4) and well calibrated. In external validation, the 5-year c-statistic was 78.1 (95% CI, 74.2 to 82.0) and 66.0 (95% CI, 61.6 to 70.4), with and without baseline eGFR, respectively, and maintained calibration., Conclusions: Self-reported lifestyle and health behavior information from health surveys may aid in predicting incident CKD., Podcast: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast.aspx?p=CJASN&e=2023&#95;01&#95;10&#95;CJN05650522.mp3., (Copyright © 2023 by the American Society of Nephrology.)

Importance: Lockdown measures and the stress of the COVID-19 pandemic are factors associated with increased risk of violence, yet there is limited information on trends in emergency department (ED) encounters for sexual assault., Objective: To compare changes in ED encounters for sexual assault during the COVID-19 pandemic vs prepandemic estimates., Design, Setting, and Participants: This retrospective, population-based cohort study used linked health administrative data from 197 EDs across Ontario, Canada, representing more than 15 million residents. Participants included all patients who presented to an ED in Ontario from January 11, 2019, to September 10, 2021. Male and female individuals of all ages were included. Data analysis was performed from March to October 2022., Exposures: Sexual assault, defined through 27 International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, procedure and diagnoses codes., Main Outcomes and Measures: Ten bimonthly time periods were used to compare differences in the frequency and rates of ED encounters for sexual assault between 2020 to 2021 (during the pandemic) compared with baseline prepandemic rates in 2019. Rate differences (RDs) and age adjusted rate ratios (aRRs) and Wald 95% CIs were calculated using Poisson regression., Results: From January 11, 2019, to September 10, 2021, there were 14 476 656 ED encounters, including 10 523 for sexual assault (9304 [88.4%] among female individuals). The median (IQR) age was 23 (17-33) years for female individuals and 15 (4-29) years for male individuals. Two months before the pandemic, ED encounters increased for sexual assault among female individuals (8.4 vs 6.9 cases per 100 000; RD, 1.51 [95% CI, 1.06 to 1.96]; aRR, 1.22 [95% CI, 1.09 to 1.38]) and male individuals (1.2 vs 1.0 cases per 100 000; RD, 0.19 [95% CI, 0.05 to 0.36]; aRR, 1.19 [95% CI, 0.87 to 1.64]). During the first 2 months of the pandemic, the rates decreased for female individuals (4.2 vs 8.3 cases per 100 000; RD, -4.07 [95% CI, -4.48 to -3.67]; aRR, 0.51 [95% CI, 0.44 to 0.58]) and male individuals (0.5 vs 1.2 cases per 100 000; RD, -0.72 [95% CI, -0.86 to -0.57]; aRR, 0.39 [95% CI, 0.26 to 0.58]). For the remainder of the study period, the rates of sexual assault oscillated, returning to prepandemic levels during the summer months and between COVID-19 waves., Conclusions and Relevance: These findings suggest that lockdown protocols should evaluate the impact of limited care for sexual assault. Survivors should still present to EDs, especially when clinical care or legal interventions are needed.

Background: To our knowledge, no population-based studies have examined whether family or friend caregivers of men and women differ in their experience of distress over time. Thus, we aimed to describe, on a population-level and longitudinally, how older men and women care-receivers differed in their health and care needs, compare their caregivers' distress trajectories, and identify factors that contribute to the observed differences., Methods: This is a population-based, retrospective cohort study using routinely collected data. We examined longitudinally 485,407 community-dwelling Ontario residents, aged over 50 years, who have received at least one Residential Assessment Instrument-Home Care (RAI-HC) assessment between April 2008 and June 2015. Descriptive analyses were performed on the demographic characteristics, health profiles, and care needs of men and women. We also compared their caregivers' baseline and one-year change in distress status. Logistic regressions were performed to examine if the effect of gender on caregiver distress is reduced after controlling for care-receiver's health and functional status as well as their caregiver's kinship and co-residence status., Results: Men (39.5% of our cohort) were frailer, required more care, were mostly cared for by their spouses (52%), and mostly lived with their caregiver (66%). In contrast, women (60.5%) were more likely cared for by their child/child-in-law (60%), less likely to live with caregivers (47%), and received less care. Caregivers of men were more likely to be distressed at baseline (27.7% versus 20.4% of women caregivers) and remain distressed (74.6% versus 69.5%) or become distressed (19.3% versus 14.3%) throughout the year. In logistic regression modelling, the effect of care-receiver's gender on caregiver distress is reduced from an unadjusted odds ratio of 1.49 (95% CI: 1.47-1.51) to 1.17 (95% CI: 1.15-1.19) when care-receiver's health and caregiving factors are controlled for., Conclusion: Older men and women differed in health and care needs. Caregivers, especially those caring for men, were often distressed and remained so through time. These results highlight the need for policies that account for the differential care needs and caregiver profiles of men and women in order to offer targetted and appropriate support., (© 2022. The Author(s).)

Objective: The aim of this study was to describe sugary drink (beverages with free sugars), sugar-sweetened beverage (beverages with added sugars, SSB) and 100% juice (beverages with natural sugars) consumption across socioeconomic position (SEP) among Canadians., Methods: We conducted a cross-sectional analysis of 19,742 respondents of single-day 24-h dietary recalls in the nationally representative 2015 Canadian Community Health Survey-Nutrition. Poisson regressions were used to estimate the prevalence of consuming each beverage type on a given day. Among consumers on a given day, linear regressions were used to estimate mean energy intake. Models included household education, food security and income quintiles as separate unadjusted exposures. Sex-specific models were estimated separately for children/adolescents (2-18 years) and adults (19 +)., Results: Among female children/adolescents, the prevalence of consuming sugary drinks and, separately, SSB ranged from 11 to 21 and 8 to 27 percentage-points higher among lower education compared to 'Bachelor degree or above' households. In female adults, the prevalence of consuming sugary drinks and, separately, SSB was 10 (95% CI: 1, 19) and 14 (95% CI: 2, 27) percentage-points higher in food insecure compared to secure households. In males, the prevalence of consuming 100% juice was 9 (95% CI: - 18, 0) percentage-points lower among food insecure compared to secure households. Social inequities in energy intake were observed in female adult consumers, among whom mean energy from sugary drinks was 27 kcal (95% CI: 3, 51) higher among food insecure compared to secure and 35 kcal (95% CI: 2, 67) higher from 100% juice among 'less than high school' education compared to 'Bachelor degree or above' households., Conclusion: Social inequities in sugary drink consumption exist in Canada. The associations differed by SEP indicator. Equitable interventions to reduce consumption are warranted., (© 2022. Crown.)

Background: Nonpharmaceutical interventions such as physical distancing and mandatory masking were adopted in many jurisdictions during the coronavirus disease 2019 pandemic to decrease spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We determined the effects of these interventions on incidence of healthcare utilization for other infectious diseases., Methods: Using a healthcare administrative dataset, we employed an interrupted time series analysis to measure changes in healthcare visits for various infectious diseases across the province of Ontario, Canada, from January 2017 to December 2020. We used a hierarchical clustering algorithm to group diagnoses that demonstrated similar patterns of change through the pandemic months., Results: We found that visits for infectious diseases commonly caused by communicable respiratory pathogens (eg, acute bronchitis, acute sinusitis) formed distinct clusters from diagnoses that often originate from pathogens derived from the patient's own flora (eg, urinary tract infection, cellulitis). Moreover, infectious diagnoses commonly arising from communicable respiratory pathogens (hierarchical cluster 1: highly impacted diagnoses) were significantly decreased, with a rate ratio (RR) of 0.35 (95% confidence interval [CI], .30-.40; P  < .001) after the introduction of public health interventions in April-December 2020, whereas infections typically arising from the patient's own flora (hierarchical cluster 3: minimally impacted diagnoses) did not demonstrate a sustained change in incidence (RR, 0.95 [95% CI, .90-1.01]; P  = .085)., Conclusions: Public health measures to curtail the incidence of SARS-CoV-2 were widely effective against other communicable respiratory infectious diseases with similar modes of transmission but had little effect on infectious diseases not strongly dependent on person-to-person transmission., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background: Modern health surveillance and planning requires an understanding of how preventable risk factors impact population health, and how these effects vary between populations. In this study, we compare how smoking, alcohol consumption, diet and physical activity are associated with all-cause mortality in Canada and the United States using comparable individual-level, linked population health survey data and identical model specifications., Methods: The Canadian Community Health Survey (CCHS) (2003-2007) and the United States National Health Interview Survey (NHIS) (2000, 2005) linked to individual-level mortality outcomes with follow up to December 31, 2011 were used. Consistent variable definitions were used to estimate country-specific mortality hazard ratios with sex-specific Cox proportional hazard models, including smoking, alcohol, diet and physical activity, sociodemographic indicators and proximal factors including disease history., Results: A total of 296,407 respondents and 1,813,884 million person-years of follow-up from the CCHS and 58,232 respondents and 497,909 person-years from the NHIS were included. Absolute mortality risk among those with a 'healthy profile' was higher in the United States compared to Canada, especially among women. Adjusted mortality hazard ratios associated with health behaviours were generally of similar magnitude and direction but often stronger in Canada., Conclusion: Even when methodological and population differences are minimal, the association of health behaviours and mortality can vary across populations. It is therefore important to be cautious of between-study variation when aggregating relative effect estimates from differing populations, and when using external effect estimates for population health research and policy development., (© 2022. The Author(s).)

Background: Life expectancy in people with inflammatory bowel disease (IBD) has increased but remains shorter than in people without IBD. We describe the life expectancy associated with IBD therapies among the growing number of older adults living with IBD., Methods: Older adults (≥ 65 years) with IBD were identified from population-based health administrative data using a validated algorithm. Life expectancy on patients' 65th birthday, stratified by sex, was calculated using a period life table approach from age- and sex-specific mortality rates among patients receiving immunomodulator monotherapy, biologic monotherapy, combination therapy, mesalamine, systemic steroids, and no therapy., Results: Among 28,260 older adults with IBD (239,125 person-years of follow-up), life expectancy at 65 years was longest for patients taking mesalamine (females: 22.1 years, 95% CI 21.8-22.5; males: 19.6 years, 95% CI 19.3-20.0) and shortest for patients taking steroids (females: 11.7 years, 95% CI 11.0-12.4; males 10.3 years, 95% CI 9.7-10.8). Life expectancy was similar for patients receiving immunomodulator monotherapy and biologic monotherapy. Immunomodulator monotherapy was associated with a reduction in life expectancy compared to combination therapy by 5.1 (95% CI 2.3-7.8) in females and 2.8 years (95% CI 0.1-5.5) in males., Conclusions: Life expectancy varies across therapies used for IBD, with differences likely arising from a combination of medication effectiveness, safety profiles, disease severity, and comorbid conditions. These considerations should be balanced when deciding on a therapeutic approach for the management of IBD in older adults., (© 2021. The Author(s).)

Objectives: To understand users' perceptions about receiving their personalized depression risk score and to gain an understanding about how to improve the efficiency of risk communication from the user perspective., Methods: A qualitative study embedded in a randomized controlled trial (RCT) on evaluating the impact of providing personalized depression risk information on psychological harms and benefits. The participants (20 males and 20 females) were randomly selected from the intervention arm of the RCT after the 12-month assessment. The qualitative interviews were conducted through telephone, audio recorded and transcribed verbatim. We conducted a content analysis to describe the content and contextual meaning of data collected from participants., Results: The first theme explained the motivation for receiving a risk score. Most participants chose to receive their personalised depression risk score with the goal of improving their self-awareness. The results revealed three sub-themes surrounding perceptions and implication of receiving their risk score: positive, negative, and neutral. Most participants found that receiving their score was positive because it improved their awareness of their mental health, but some participants could see that some people would have negative feelings when getting the score causing them to be more likely to get depression. The final theme focussed on improvements including: the best delivery methods, having resources and strategies, and targeting younger people., Conclusion: The most significant motivation for, and benefit of receiving one's personalized depression risk score was improved awareness of one's mental health. A comprehensive risk communication program may improve the uptake and maximize the impact on behavior changes and risk reduction., (© 2021. The Author(s).)

Background: Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year dementia risk in the community setting was developed., Methods: The Dementia Population Risk Tool (DemPoRT) was derived using Ontario respondents to the Canadian Community Health Survey (survey years 2001 to 2012). Five-year incidence of physician-diagnosed dementia was ascertained by individual linkage to administrative healthcare databases and using a validated case ascertainment definition with follow-up to March 2017. Sex-specific proportional hazards regression models considering competing risk of death were developed using self-reported risk factors including information on socio-demographic characteristics, general and chronic health conditions, health behaviours and physical function., Results: Among 75 460 respondents included in the combined derivation and validation cohorts, there were 8448 cases of incident dementia in 348 677 person-years of follow-up (5-year cumulative incidence, men: 0.044, 95% CI: 0.042 to 0.047; women: 0.057, 95% CI: 0.055 to 0.060). The final full models each include 90 df (65 main effects and 25 interactions) and 28 predictors (8 continuous). The DemPoRT algorithm is discriminating (C-statistic in validation data: men 0.83 (95% CI: 0.81 to 0.85); women 0.83 (95% CI: 0.81 to 0.85)) and well-calibrated in a wide range of subgroups including behavioural risk exposure categories, socio-demographic groups and by diabetes and hypertension status., Conclusions: This algorithm will support the development and evaluation of population-level dementia prevention strategies, support decision-making for population health and can be used by individuals or their clinicians for individual risk assessment., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Setting: The Canadian Community Health Survey (CCHS) is one of the world's largest ongoing cross-sectional population health surveys, with over 130,000 respondents every two years or over 1.1 million respondents since its inception in 2001. While the survey remains relatively consistent over the years, there are differences between cycles that pose a challenge to analyze the survey over time., Intervention: A program package called cchsflow was developed to transform and harmonize CCHS variables to consistent formats across multiple survey cycles. An open science approach was used to maintain transparency, reproducibility and collaboration., Outcomes: The cchsflow R package uses CCHS survey data between 2001 and 2014. Worksheets were created that identify variables, their names in previous cycles, their category structure, and their final variable names. These worksheets were then used to recode variables in each CCHS cycle into consistently named and labelled variables. Following, survey cycles can be combined. The package was then added as a GitHub repository to encourage collaboration with other researchers., Implication: The cchsflow package has been added to the Comprehensive R Archive Network (CRAN) and contains support for over 160 CCHS variables, generating a combined data set of over 1 million respondents. By implementing open science practices, cchsflow aims to minimize the amount of time needed to clean and prepare data for the many CCHS users across Canada.

Background: Prognostication tools that report personalized mortality risk and survival could improve discussions about end-of-life and advance care planning. We sought to develop and validate a mortality risk model for older adults with diverse care needs in home care using self-reportable information - the Risk Evaluation for Support: Predictions for Elder-Life in the Community Tool (RESPECT)., Methods: Using a derivation cohort that comprised adults living in Ontario, Canada, aged 50 years and older with at least 1 Resident Assessment Instrument for Home Care (RAI-HC) record between Jan. 1, 2007, and Dec. 31, 2012, we developed a mortality risk model. The primary outcome was mortality 6 months after a RAI-HC assessment. We used proportional hazards regression with robust standard errors to account for clustering by the individual. We validated this algorithm for a second cohort of users of home care who were assessed between Jan. 1 and Dec. 31, 2013. We used Kaplan-Meier survival curves to estimate the observed risk of death at 6 months for assessment of calibration and median survival. We constructed 61 risk groups based on incremental increases in the estimated median survival of about 3 weeks among adults at high risk and 3 months among adults at lower risk., Results: The derivation and validation cohorts included 435 009 and 139 388 adults, respectively. We identified a total of 122 823 deaths within 6 months of a RAI-HC assessment in the derivation cohort. The mean predicted 6-month mortality risk was 10.8% (95% confidence interval [CI] 10.7%-10.8%) and ranged from 1.54% (95% CI 1.53%-1.54%) in the lowest to 98.1% (95% CI 98.1%-98.2%) in the highest risk group. Estimated median survival spanned from 28 days (11 to 84 d at the 25th and 75th percentiles) in the highest risk group to over 8 years (1925 to 3420 d) in the lowest risk group. The algorithm had a c-statistic of 0.753 (95% CI 0.750-0.756) in our validation cohort., Interpretation: The RESPECT mortality risk prediction tool that makes use of readily available information can improve the identification of palliative and end-of-life care needs in a diverse older adult population receiving home care., Competing Interests: Competing interests: Spruin has received support as a research assistant from Bruyère Research Institute. No other competing interests were declared., (© 2021 CMA Joule Inc. or its licensors.)

Hospital data for covid-19 surveillance, planning and modelling are challenging to find worldwide in public aggregation portals. Detailed covid-19 hospital data provides insights into covid-19's health burden including identifying which sociodemographic groups are at greatest risk of covid-19 morbidity and mortality. Timely hospital data is the best source of information for actionable forecasts and projection models of hospital capacity, including critical resources such as intensive care unit beds and ventilators that take time to plan or procure. A challenge to generate timely and detailed hospital data is the reliance on separation or discharge abstracts and census counts. What are needed are well-maintained lists of patients hospitalized with covid-19. From the standpoint of public health and health services researchers and practitioners, we describe the role of hospital data for studying covid-19, why admission data are hard to find, and how improved data infrastructure can meet surveillance and planning needs in the near future. Modern hospital electronic health records can create covid-19 patient lists and these decision support tools are increasingly used for research. These tools can generate patient lists that are transmitted and combined with public health data systems., Competing Interests: Conflicts of interest: The authors declares that they have no conflicts of interest.

Background : High sodium intake is a leading modifiable risk factor for cardiovascular diseases. This study estimated full compliance to Canada's voluntary sodium reduction guidance (SRG) targets on social inequities and population sodium intake. Methods : We conducted a modeling study using n = 19,645, 24 h dietary recalls (Canadians ≥ 2 years) from the 2015 Canadian Community Health Survey-Nutrition (2015 CCHS-N). Multivariable linear regressions were used to estimate mean sodium intake in measured (in the 2015 CCHS-N) and modelled (achieving SRG targets) scenarios across education, income and food security. The percentage of Canadians with sodium intakes above chronic disease risk reduction (CDRR) thresholds was estimated using the US National Cancer Institute (NCI) method. Results : In children aged 2-8, achieving SRG targets reduced mean sodium intake differences between food secure and insecure households from 271 mg/day (95%CI: 75,468) to 83 mg/day (95%CI: -45,212); a finding consistent across education and income. Mean sodium intake inequities between low and high education households were eliminated for females aged 9-18 (96 mg/day, 95%CI: -149,341) and adults aged 19 and older (males: 148 mg/day, 95%CI: -30,327; female: -45 mg/day, 95%CI: -141,51). Despite these declines (after achieving the SRG targets) the majority of Canadians' are above the CDRR thresholds. Conclusion : Achieving SRG targets would eliminate social inequities in sodium intake and reduce population sodium intake overall; however, additional interventions are required to reach recommended sodium levels.

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 disease. There are concerns regarding limited testing capacity and the exclusion of cases from unproven screening criteria. Knowing COVID-19 risks can inform testing. This study derived and assessed a model to predict risk of SARS-CoV-2 in community-based people., Methods: All people presenting to a community-based COVID-19 screening center answered questions regarding symptoms, possible exposure, travel, and occupation. These data were anonymously linked to SARS-CoV-2 testing results. Logistic regression was used to derive a model to predict SARS-CoV-2 infection. Bootstrap sampling evaluated the model., Results: A total of 9172 consecutive people were studied. Overall infection rate was 6.2% but this varied during the study period. SARS-CoV-2 infection likelihood was primarily influenced by contact with a COVID-19 case, fever symptoms, and recent case detection rates. Internal validation found that the SARS-CoV-2 Risk Prediction Score (SCRiPS) performed well with good discrimination (c-statistic 0.736, 95%CI 0.715-0.757) and very good calibration (integrated calibration index 0.0083, 95%CI 0.0048-0.0131). Focusing testing on people whose expected SARS-CoV-2 risk equaled or exceeded the recent case detection rate would increase the number of identified SARS-CoV-2 cases by 63.1% (95%CI 54.5-72.3)., Conclusion: The SCRiPS model accurately estimates the risk of SARS-CoV-2 infection in community-based people undergoing testing. Using SCRiPS can importantly increase SARS-CoV-2 infection identification when testing capacity is limited.

Background: Characterizing smoking patterns over time is essential for evaluating the impact of tobacco control interventions and predicting smoking-related mortality. Beginning with a 1920s birth cohort, smoking histories (i.e., estimates of smoking initiation and cessation, and prevalence of current and former smokers) were generated., Data: The Ontario sample (n = 238,411) of the 2003 to 2013 cycles of the Canadian Community Health Survey, which is conducted biennially, was used to obtain cross-sectional information on current smoking behaviour., Methods: Age at smoking initiation and age at smoking cessation were used to construct smoking histories for each respondent, up to the survey date. An age-period-cohort model was generated and used to examine survival differences by smoking status. Using the model, and adjusting for survival differences in smoking status, the prevalence of current, former and never smokers was estimated in cohorts from 1920 to 1985. Smoking initiation, cessation and intensity were then estimated for age-specific distributions of each birth cohort. These rates were projected forward through to 2041. Smoking patterns by highest level of education were generated using education-stratified models., Results: Smoking histories show clear trends over time by sex, cohort and age. If current patterns persist, smoking prevalence is projected to decline to single digits (below 10%) by 2023 for women and 2040 for men., Discussion: Birth-cohort-specific smoking histories can be generated using cross-sectional health surveys. These cohort histories can describe smoking patterns over time and into the future. In turn, these histories can be used in micro-simulation models to evaluate historic or planned tobacco control interventions, and to project smoking prevalence.

Background: Inflammatory bowel disease (IBD) may be life-threatening and often reduces quality of life. We determined trends in life expectancy and health-adjusted life expectancy in people with and without IBD., Methods: We conducted a retrospective cohort study of population-level health administrative, demographic and health survey data available from databases in Ontario. We matched people with a diagnosis of IBD to those without a diagnosis of IBD. We used period life tables that were generated using age- and sex-specific 5-year mortality rates to calculate life expectancy (for 1996, 2000, 2008 and 2011). We incorporated the Health Utility Index (National Population Health Study; Canadian Community Health Survey) to estimate health-adjusted life expectancy (for 1996, 2000 and 2008)., Results: Life expectancy in patients with IBD increased between 1996 and 2011 (females: from 75.5 to 78.4 yr, difference: 2.9 yr [95% confidence interval (CI) 1.3 to 4.5]; males: from 72.2 to 75.5 yr, difference: 3.2 yr [95% CI 2.1 to 4.4]). Between 1996 and 2008, health-adjusted life expectancy decreased among males by 3.9 years (95% CI 1.2 to 6.6). There was no statistically significant change in health-adjusted life expectancy among females with IBD (difference: 2.0 yr, 95% CI -1.6 to 5.7). Life expectancy and health-adjusted life expectancy were lower in people with IBD compared with those without IBD. Differences in life expectancy in people with and without IBD ranged from 6.6 to 8.1 years in females and 5.0 to 6.1 years in males, depending on the year. Differences in health-adjusted life expectancy for people with and without IBD ranged from 9.5 to 13.5 years in females and 2.6 to 6.7 years in males., Interpretation: Whilst life expectancy has increased among people with IBD, a gap in life expectancy between those with and without IBD remains, and the effect of pain on daily functioning contributes substantially to reduced health-adjusted life expectancy, suggesting that improved pain mitigation strategies should be implemented., Competing Interests: Competing interests: None declared., (© 2020 Joule Inc. or its licensors.)

Background: Premature mortality is an important population health indicator used to assess health system functioning and to identify areas in need of health system intervention. Predicting the future incidence of premature mortality in the population can facilitate initiatives that promote equitable health policies and effective delivery of public health services. This study protocol proposes the development and validation of the Premature Mortality Risk Prediction Tool (PreMPoRT) that will predict the incidence of premature mortality using large population-based community health surveys and multivariable modeling approaches., Methods: PreMPoRT will be developed and validated using various training, validation, and test data sets generated from the six cycles of the Canadian Community Health Survey (CCHS) linked to the Canadian Vital Statistics Database from 2000 to 2017. Population-level risk factor information on demographic characteristics, health behaviors, area level measures, and other health-related factors will be used to develop PreMPoRT and to predict the incidence of premature mortality, defined as death prior to age 75, over a 5-year period. Sex-specific Weibull accelerated failure time models will be developed using a Canadian provincial derivation cohort consisting of approximately 500,000 individuals, with approximately equal proportion of males and females, and about 12,000 events of premature mortality. External validation will be performed using separate linked files (CCHS cycles 2007-2008, 2009-2010, and 2011-2012) from the development cohort (CCHS cycles 2000-2001, 2003-2004, and 2005-2006) to check the robustness of the prediction model. Measures of overall predictive performance (e.g., Nagelkerke's R 2 ), calibration (e.g., calibration plots), and discrimination (e.g., Harrell's concordance statistic) will be assessed, including calibration within defined subgroups of importance to knowledge users and policymakers., Discussion: Using routinely collected risk factor information, we anticipate that PreMPoRT will produce population-based estimates of premature mortality and will be used to inform population strategies for prevention.

Setting: This paper documents a participatory process of Health Portfolio staff in the design of a clock, and announces the 2020 Canadian Health Clock, with links to numerous online health calculators. The clock is part of the Health Portfolio's celebration activities in 2019 of "100 Years of Health", as the Department of Health was established in Canada in 1919., Intervention: The intervention was the development of a clock on the Government of Canada website with linkage to calculators as a health promotion tool. The clock was built on the concept of the 2004 Chronic Disease Clock, which shows the number of deaths so far today, and so far this year. The clock was developed using a consultative approach, following a review of the original clock., Outcomes: The 2020 clock incorporates new data visualization concepts. New features, facilitated by improved technology, include: expansion to all causes of death; blinking red dots to enhance visual impact; and three clock versions (analogue, featuring a moving circle; digital, table format; and graphical, bar chart format). The clock also provides links to a number of health calculators, to allow people to seek personalized information to improve their health., Implications: The online health clock and health calculators are good examples of innovation in health risk communication tools for effective knowledge translation and dissemination. They inform people about health statistics (clock) and their health (calculators). The clock engages people in the context of the Canadian population, whereas the calculators provide personalized information about improving an individual's future health.

Background: National health surveys linked to vital statistics and health care information provide a growing source of individual-level population health data. Pooling linked surveys across jurisdictions would create comprehensive datasets that are larger than most existing cohort studies, and that have a unique international and population perspective. This paper's objectives are to examine the feasibility of pooling linked population health surveys from three countries, facilitate the examination of health behaviours, and present useful information to assist in the planning of international population health surveillance and research studies., Data and Methods: The design, methodologies and content of the Canadian Community Health Survey (2003 to 2008), the United States National Health Interview Survey (2000, 2005) and the Scottish Health Survey (SHeS) (2003, 2008 to 2010) were examined for comparability and consistency. The feasibility of creating common variables for measuring smoking, alcohol consumption, physical activity and diet was assessed. Sample size and estimated mortality events were collected., Results: The surveys have comparable purposes, designs, sampling and administration methodologies, target populations, exclusions, and content. Similar health behaviour questions allow for comparable variables to be created across the surveys. However, the SHeS uses a more detailed risk factor evaluation for alcohol consumption and diet data. Therefore, comparisons of alcohol consumption and diet data between the SHeS and the other two surveys should be performed with caution. Pooling these linked surveys would create a dataset with over 350,000 participants, 28,424 deaths and over 2.4 million person-years of follow-up., Discussion: Pooling linked national population health surveys could improve population health research and surveillance. Innovative methodologies must be used to account for survey dissimilarities, and further discussion is needed on how to best access and analyze data across jurisdictions.