Neighbourhood-level socio-demographic characteristics and risk of COVID-19 incidence and mortality in Ontario, Canada: A population-based study.

OBJECTIVES: We aimed to estimate associations between COVID-19 incidence and mortality with neighbourhood-level immigration, race, housing, and socio-economic characteristics. METHODS: We conducted a population-based study of 28,808 COVID-19 cases in the provincial reportable infectious disease surveillance systems (Public Health Case and Contact Management System) which includes all known COVID-19 infections and deaths from Ontario, Canada reported between January 23, 2020 and July 28, 2020. Residents of congregate settings, Indigenous communities living on reserves or small neighbourhoods with populations <1,000 were excluded. Comparing neighbourhoods in the 90th to the 10th percentiles of socio-demographic characteristics, we estimated the associations between 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics and COVID-19 incidence and mortality using Poisson generalized linear mixed models. RESULTS: Neighbourhoods with the highest proportion of immigrants (relative risk (RR): 4.0, 95%CI:3.5-4.5) and visible minority residents (RR: 3.3, 95%CI:2.9-3.7) showed the strongest association with COVID-19 incidence in adjusted models. Among individual race groups, COVID-19 incidence was highest among neighbourhoods with the high proportions of Black (RR: 2.4, 95%CI:2.2-2.6), South Asian (RR: 1.9, 95%CI:1.8-2.1), Latin American (RR: 1.8, 95%CI:1.6-2.0) and Middle Eastern (RR: 1.2, 95%CI:1.1-1.3) residents. Neighbourhoods with the highest average household size (RR: 1.9, 95%CI:1.7-2.1), proportion of multigenerational families (RR: 1.8, 95%CI:1.7-2.0) and unsuitably crowded housing (RR: 2.1, 95%CI:2.0-2.3) were associated with COVID-19 incidence. Neighbourhoods with the highest proportion of residents with less than high school education (RR: 1.6, 95%CI:1.4-1.8), low income (RR: 1.4, 95%CI:1.2-1.5) and unaffordable housing (RR: 1.6, 95%CI:1.4-1.8) were associated with COVID-19 incidence. Similar inequities were observed across neighbourhood-level sociodemographic characteristics and COVID-19 mortality. CONCLUSIONS: Neighbourhood-level inequities in COVID-19 incidence and mortality were observed in Ontario, with excess burden experienced in neighbourhoods with a higher proportion of immigrants, racialized populations, large households and low socio-economic status.

Incidence of outbreak-associated COVID-19 cases by industry in Ontario, Canada, 1 April 2020-31 March 2021.

OBJECTIVES: The objective of our study was to estimate the rate of workplace outbreak-associated cases of COVID-19 by industry in labour market participants aged 15-69 years who reported working the majority of hours outside the home in Ontario, Canada. METHODS: We conducted a population-based cross-sectional study of COVID-19 workplace outbreaks and associated cases reported in Ontario between 1 April 2020 and 31 March 2021. All outbreaks were manually classified into two-digit North American Industry Classification System codes. We obtained monthly denominator estimates from the Statistics Canada Labour Force Survey to estimate the incidence of outbreak-associated cases per 100 000 000 hours among individuals who reported the majority of hours were worked outside the home. We performed this analysis across industries and in three distinct time periods. RESULTS: Overall, 12% of cases were attributed to workplace outbreaks among working-age adults across our study period. While incidence varied across the time periods, the five industries with the highest incidence rates across our study period were agriculture, healthcare and social assistance, food manufacturing, educational services, and transportation and warehousing. CONCLUSIONS: Certain industries have consistently increased the incidence of COVID-19 over the course of the pandemic. These results may assist in ongoing efforts to reduce transmission of COVID-19 by prioritising resources, as well as industry-specific guidance, vaccination and public health messaging.

The 2011 and 2016 iterations of the Ontario Marginalization Index: updates, consistency and a cross-sectional study of health outcome associations.

OBJECTIVES: The Ontario Marginalization Index (ON-Marg) is an area-based measure used widely to measure health inequalities in Ontario. Recently, the index was updated for 2011 and 2016. The loss of the 2011 long-form census required the use of alternative data sources for the 2011 version. This paper describes the update of ON-Marg, assesses consistency in the indices across census years using Dissemination Areas, and examines associations between ON-Marg 2016 and four health and social outcomes to demonstrate its potential to measure health inequalities. METHODS: ON-Marg was created using factor analysis. Differences in quintile assignment was compared over time to assess whether the use of taxfiler, immigration, property assessment, and health card address data in 2011 affected consistency in measurement of marginalization. Inequalities in rates of overall mortality, gonorrhea incidence, mental health emergency department visits, and alcohol retail locations across quintiles of ON-Marg 2016 were quantified using the Relative Index of Inequality. RESULTS: Depending on the dimension, between 81% and 96% of DAs showed limited or no changes in quintiles of marginalization between 2006, 2011 and 2016. Of the 45-64% of DAs that did not change quintile between 2006 and 2016, 1.8% to 8.8% of DAs in 2011 differed by two or more quintiles. Findings showed significant differences in rates of health and social outcomes across quintiles of ON-Marg 2016, with strength and directionality varying by dimension of ON-Marg. CONCLUSION: Alternative data sources did not substantially affect the consistency of the 2011 version of ON-Marg. The updated ON-Marg is a comprehensive tool that can be used to study health inequalities in Ontario.

RéSUMé: OBJECTIFS: L'indice de marginalisation ontarien (indice ON-Marg) est un indicateur par secteurs largement utilisé pour mesurer les inégalités en santé dans la province. Il a récemment été mis à jour pour 2011 et 2016. Avec l'élimination du recensement long en 2011, il a fallu se tourner vers d'autres sources de données. Le présent article décrit la mise à jour de l'indice ON-Marg, évalue l'uniformité des indices d'un recensement à l'autre d'après les aires de diffusion, et examine les liens entre l'indice ON-Marg 2016 et quatre résultats en matière de santé et sur le plan social pour illustrer son potentiel à mesurer les inégalités en santé. MéTHODOLOGIE: L'indice ON-Marg a été créé selon les principes de l'analyse factorielle. Ont été comparés au fil du temps les écarts entre les quintiles pour évaluer si l'utilisation en 2011 des données des déclarants, d'immigration et d'évaluation foncière et celles des adresses des cartes Santé avait eu une incidence sur l'uniformité de la mesure de la marginalisation. Les inégalités quant au taux global de mortalité, à l'incidence de la gonorrhée, au nombre de visites dans les services d'urgence pour des raisons de santé mentale et à l'emplacement des magasins de vente au détail d'alcool par quintiles de l'indice ON-Marg 2016 ont été quantifiées au moyen de l'indice d'inégalité relative. RéSULTATS: Selon l'aspect, il y avait peu ou pas de changements dans 81 % à 96 % des aires de diffusion pour les quintiles de marginalisation de 2006, 2011 et 2016. Parmi les aires de diffusions qui n'ont pas changé de quintile de 2006 à 2016 (45 % à 64 % d'entre elles), on a observé un écart de deux quintiles ou plus en 2011 dans 1,8 % à 8,8 % des cas. L'étude témoigne d'un écart significatif dans les taux des résultats en matière de santé et sur le plan social pour l'ensemble des quintiles de l'indice ON-Marg 2016, la force et la direction variant en fonction de l'aspect. CONCLUSION: L'utilisation d'autres sources de données n'a pas eu de grande incidence sur l'uniformité de la version 2011 de l'indice ON-Marg. La dernière version mise à jour est un outil complet pouvant servir à étudier les inégalités en santé en Ontario.

Characteristics Associated With Household Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Ontario, Canada: A Cohort Study.

BACKGROUND: Within-household transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been identified as one of the main sources of spread of coronavirus disease 2019 (COVID-19) after lockdown restrictions and self-isolation guidelines are implemented. Secondary attack rates among household contacts are estimated to be 5-10 times higher than among non-household contacts, but it is unclear which individuals are more prone to transmit infection within their households. METHODS: Using address matching, a cohort was assembled of all individuals with laboratory-confirmed COVID-19 residing in private households in Ontario, Canada. Descriptive analyses were performed to compare characteristics of cases in households that experienced secondary transmission versus those that did not. Logistic regression models were fit to determine index case characteristics and neighborhood characteristics associated with transmission. RESULTS: Between January and July 2020, there were 26 714 individuals with COVID-19 residing in 21 226 households. Longer testing delays (≥5 vs 0 days; odds ratio [OR], 3.02; 95% confidence interval [CI], 2.53-3.60) and male gender (OR, 1.28; 95% CI, 1.18-1.38) were associated with greater odds of household secondary transmission, while being a healthcare worker (OR, .56; 95% CI, .50-.62) was associated with lower odds of transmission. Neighborhoods with larger average family size and a higher proportion of households with multiple persons per room were also associated with greater odds of transmission. CONCLUSIONS: It is important for individuals to get tested for SARS-CoV-2 infection as soon as symptoms appear, and to isolate away from household contacts; this is particularly important in neighborhoods with large family sizes and/or crowded households.

Material deprivation and rates of all-terrain vehicle- and snowmobile-related injuries in Ontario from 2003 to 2018: a population-based study.

OBJECTIVES: Socio-economic status (SES) is a well-established predictor of health outcomes; however, there is a dearth of evidence on the relationship between SES and off-road vehicle (ORV) injuries. In Ontario, all-terrain vehicles (ATVs) and snowmobiles present a serious risk for preventable injury. This study assessed the association between area-level material deprivation and the risk of ATV- and snowmobile-related injuries in Ontario, as well as the impact of sex and age. METHODS: A population-based, repeat cross-sectional study was conducted using administrative data of ATV- and snowmobile-related emergency room visits from 2003 to 2018. Material deprivation was measured using the Ontario Marginalization Index, which assigned a score and quintile of deprivation to each dissemination area in Ontario. Age-standardized incidence rates and relative index of inequality values were calculated, stratified by quintile of deprivation, sex, age group, vehicle type, and health region. RESULTS: We found a significant, positive relationship between ORV-related injuries and quintile of material deprivation (RII = 1.28, 95% CI: 1.01-1.63). Rates of ATV- and snowmobile-related injuries remained stable over time. Across all age groups, sex, and rural categories, we found an inverse u-shaped relationship between rates of injuries and quintile material deprivation. Males, individuals living in rural areas, and adolescents and young adults experienced the highest rates of injuries. CONCLUSION: Despite the positive relationship between ORV-related injuries and quintiles of deprivation, the inverse u-shaped relationship suggests that this increased risk of injury is likely related to exposure to ORVs. These results contribute to an understanding of the prevalence of the injury problem at a local level in Ontario. Stable rates of injury over time suggest that current public health programs are not sufficient in reducing these injuries, and further research should determine which factors amenable to intervention are contributing to increased risk of injury.

RéSUMé: OBJECTIFS: Le statut socioéconomique (SSE) est un prédicteur bien établi des résultats pour la santé, mais il existe une pénurie de preuves sur la relation entre le SSE et les blessures des véhicules hors route. En Ontario, les véhicules tout-terrain (VTT) et les motoneiges présentent un risque sérieux de blessures évitables. Cette étude a évalué l'association entre la privation matérielle au niveau de la zone et le risque de blessures liées aux VTT et aux motoneiges en Ontario, ainsi que l'impact du sexe et de l'âge. MéTHODES: Une étude transversale répétée basée sur la population a été menée à l'aide des données administratives des visites aux urgences liées aux VTT et aux motoneiges de 2003 à 2018. La privation matérielle a été mesurée à l'aide de l'Ontario Marginalization Index, qui a attribué un score et un quintile de privation à chaque aire de diffusion en Ontario. Les taux d'incidence normalisés selon l'âge et l'indice relatif des valeurs d'inégalité ont été calculés, stratifiés par quintile de privation, sexe, groupe d'âge, type de véhicule et région sanitaire. RéSULTATS: Nous avons trouvé une relation positive significative entre les blessures liées aux VTT et le quintile de privation matérielle (RII = 1,28, IC à 95% : 1,01 ­ 1,63). Les taux de blessures liées aux VTT et aux motoneiges sont demeurés élevés au fil du temps. Dans tous les groupes d'âge, sexe et catégories rurales, nous avons trouvé une relation en forme de U inverse entre les taux de blessures et les quintiles de privation matérielle. Les hommes, les personnes vivant dans les zones rurales, les adolescents et les jeunes adultes ont connu les taux de blessures les plus élevés. CONCLUSION: Malgré la relation positive entre les blessures liées aux VTT et les quintiles de privation, la relation en forme de U suggère que ce risque accru de blessures est probablement lié à l'exposition aux VTT. Ces résultats contribuent à une compréhension de la prévalence du problème de blessures au niveau local en Ontario. Des taux stables de blessures au fil du temps suggèrent que les programmes de santé publique actuels ne sont pas suffisants pour réduire ces blessures, et des recherches plus poussées devraient déterminer quels facteurs susceptibles d'intervenir contribuent à augmenter le risque de blessures.

Relation between opioid-related harms and socioeconomic inequalities in Ontario: a population-based descriptive study.

BACKGROUND: Negative health outcomes associated with the use of both prescribed and nonprescribed opioids are increasingly prevalent. We examined long-term trends in opioid-related harms in Ontario across a set of 6 indicators and the relation between harms and neighbourhood income in 2016. METHODS: We examined rates of neonatal abstinence syndrome, opioid poisoning (fatal and nonfatal) and nonpoisoning opioid-related events from 2003 to 2016 in Ontario using population-based health administrative databases. We conducted descriptive analyses for harm indicators across neighbourhood income quintiles in 2016 (2015 for death). We examined social inequalities in opioid-related harms on both relative (prevalence ratio) and absolute (potential rate reduction) scales. RESULTS: Rates of opioid-related harms increased dramatically between 2003 and 2016. In 2016, neonatal abstinence syndrome and opioid poisoning and nonpoisoning events showed a strong social gradient, with harm rates being lowest in higher-income neighbourhoods and highest in lower-income neighbourhoods. Prevalence ratios for the lowest-income neighbourhoods compared to the highest-income neighbourhoods ranged from 2.36 (95% confidence interval [CI] 2.15-2.58) for emergency department visits for opioid poisoning to 3.70 (95% CI 2.62-5.23) for neonatal abstinence syndrome. Potential rate reductions for opioid-related harms ranged from 34.8% (95% CI 29.1-40.1) to 49.9% (95% CI 36.7-60.5), which suggests that at least one-third of all harmful events could be prevented if all neighbourhoods had the same socioeconomic profile as the highest-income neighbourhoods. INTERPRETATION: Rates of opioid-related harms increased in Ontario between 2003 and 2016, and people in lower-income neighbourhoods experienced substantially higher rates of opioid-related harms than those in higher-income neighbourhoods. This finding can inform planning for opioid-related public health interventions with consideration of health equity.