Regional variation of premature mortality in Ontario, Canada: a spatial analysis

Opioid-related deaths in Northern Ontario in the early COVID-19 pandemic period

OBJECTIVES

In the first year of pandemic measures, opioid-related deaths across Ontario's (ON) 34 public health units (PHUs) increased by 60%. Death rates for all seven Northern ON PHUs were above the provincial average. This study describes and compares factors surrounding opioid-related deaths before and after pandemic measures were introduced, for Northern ON compared to the rest of ON.

METHODS

Aggregate data were provided for Northern ON and the rest of the province by the Office of the Chief Coroner/Ontario Forensic Pathology Services. Opioid-related deaths were cohorted by date of death for the year before and after pandemic measures were introduced on March 16, 2020. Chi-square tests were used to compare between cohorts and geographies to determine significant differences for each variable, and for dichotomized levels within variables. P-values < 0.05 were considered statistically significant a priori.

RESULTS

In Northern ON, the number of opioid-related deaths approximately doubled from the pre-pandemic cohort (n = 185) to the early pandemic cohort (n = 365). Compared to the rest of ON, higher proportions of deaths occurred in Northern ON among individuals who lived and died in private residences, among women (although the majority of decedents were male) and among individuals employed in mining, quarrying, and oil and gas industries. Compared to the pre-pandemic year, in Northern ON, higher proportions of opioid-related deaths involved fentanyl and stimulants as direct contributors, and the majority involved evidence of inhaled drugs.

CONCLUSION

Differences between the circumstances of death in Northern ON and in the rest of ON suggest opportunities to tailor interventions.

A national cohort study of community belonging and its influence on premature mortality

BACKGROUND

Community belonging, an important constituent of subjective well-being, is an important target for improving population health. Ageing involves transitioning across different social conditions thus, community belonging on health may vary across the life course. Using a nationally representative cohort, this study estimates the life stage-specific impact of community belonging on premature mortality.

METHODS

Six cycles of the Canadian Community Health Survey (2000-2012) were combined and linked to the Canadian Vital Statistics Database (2000-2017). Respondents were followed for up to 5 years. Multivariable-adjusted modified Poisson regression models were used to estimate the relative risk of premature mortality for three life stages: early adulthood (18-35 years), middle adulthood (36-55 years) and late adulthood (56-70 years).

RESULTS

The final analytical sample included 477 100 respondents. Most reported a 'somewhat strong' sense of belonging (45.9%). Compared with their 'somewhat strong' counterparts, young adults reporting a 'somewhat weak' sense of belonging exhibited an increased relative risk (RR) of 1.76 (95% CI 1.27 to 2.43) for premature mortality, whereas middle-aged adults reporting the same exhibited a decreased RR of 0.82 (95% CI 0.69, 0.98). Among older adults, groups reporting a 'very strong' (RR 1.10, 95% CI 1.01, 1.21) or a 'very weak' sense (RR 1.14, 95% CI 1.01, 1.28) of belonging exhibited higher RRs for premature mortality.

CONCLUSION

The results demonstrate how community belonging relates to premature mortality differs across age groups underscoring the importance of considering life stage-specific perspectives when researching and developing approaches to strengthen belonging.

Risk of premature mortality due to smoking, alcohol use, obesity and physical activity varies by income: A population-based cohort study

Background

Premature deaths are a strong population health indicator. There is a persistent and widening pattern of income inequities for premature mortality. We sought to understand the combined effect of health behaviours and income on premature mortality in a large population-based cohort.

Methods

We analyzed a cohort of 121,197 adults in the 2005-2014 Canadian Community Health Surveys, linked to vital statistics data to ascertain deaths for up to 5 years following baseline. Information on household income quintile and mortality-relevant risk factors (smoking status, alcohol use, body mass index (BMI), and physical activity) was captured from the survey. Hazard ratios (HR) for combined income-risk factor groups were estimated using Cox proportional hazards models. Stratified Cox models were used to identify quintile-specific HR for each risk factor.

Results

For each risk factor, HR of premature mortality was highest in the lowest-income, highest-risk group. Additionally, an income gradient was seen for premature mortality HR for every exposure level of each risk factor. In the stratified models, risk factor HRs did not vary meaningfully between income groups. All findings were consistent in the unadjusted and adjusted models.

Conclusion

These findings highlight the need for targeted strategies to reduce health inequities and more careful attention to how policies and interventions are distributed at the population level. This includes targeting and tailoring resources to those in lower income groups who disproportionately experience premature mortality risk to prevent further widening health inequities.

The impact of marginalization on diffuse large B-cell lymphoma overall survival: a retrospective cohort study

The aim of this study was to describe the impact of marginalization on DLBCL overall survival (OS) within the Canadian setting. We conducted a population-based retrospective cohort study of adult patients with newly diagnosed DLBCL in Ontario between 1 January 2005 and 31 December 2017 receiving a rituximab-containing chemotherapy regimen with curative intent followed until 1 March 2020. Our primary exposure of interest was the Ontario Marginalization Index (ON-Marg). The primary outcome was 2-year OS, accounting for patient age, sex, cancer characteristics, comorbidity burden, and rural dwelling status. While two-year overall survival was inferior for individuals in the most deprived marginalization quintile (70.4% Q5 vs. 76.0% Q1), after adjustment for relevant covariates neither the composite ON-Marg nor any of its dimensions had a significant effect. Within the Canadian context, among patients who receive chemotherapy, marginalization may not have a significant association with overall survival when accounting for key patient covariates, lending support for preserved outcomes.

Geographic clustering of travel-acquired infections in Ontario, Canada, 2008-2020

As the frequency of international travel increases, more individuals are at risk of travel-acquired infections (TAIs). In this ecological study of over 170,000 unique tests from Public Health Ontario's laboratory, we reviewed all laboratory-reported cases of malaria, dengue, chikungunya, and enteric fever in Ontario, Canada between 2008-2020 to identify high-resolution geographical clusters for potential targeted pre-travel prevention. Smoothed standardized incidence ratios (SIRs) and 95% posterior credible intervals (CIs) were estimated using a spatial Bayesian hierarchical model. High- and low-incidence areas were described using data from the 2016 Census based on the home forward sortation area of patients testing positive. A second model was used to estimate the association between drivetime to the nearest travel clinic and incidence of TAI within high-incidence areas. There were 6,114 microbiologically confirmed TAIs across Ontario over the study period. There was spatial clustering of TAIs (Moran's I = 0.59, p<0.0001). Compared to low-incidence areas, high-incidence areas had higher proportions of immigrants (p<0.0001), were lower income (p = 0.0027), had higher levels of university education (p<0.0001), and less knowledge of English/French languages (p<0.0001). In the high-incidence Greater Toronto Area (GTA), each minute increase in drive time to the closest travel clinic was associated with a 3% reduction in TAI incidence (95% CI 1-6%). While urban neighbourhoods in the GTA had the highest burden of TAIs, geographic proximity to a travel clinic in the GTA was not associated with an area-level incidence reduction in TAI. This suggests other barriers to seeking and adhering to pre-travel advice.

Clarifying rural-urban disparities in alcohol-related emergency department visits and hospitalizations in Ontario, Canada: A spatial analysis

PURPOSE

Rates of alcohol-related harm are higher in rural versus urban Canada. This study characterized the spatial distribution and regional determinants of alcohol-related emergency department (ED) visits and hospitalizations in Ontario to better understand this rural-urban disparity.

METHODS

This was a cross-sectional spatial analysis of rates of alcohol-related ED visits and hospitalizations by Ministry of Health subregion (n = 76) in Ontario, Canada between 2016 and 2019. Regional hot- and cold-spots of alcohol-related harm were identified using spatial autocorrelation methods. Rurality was measured as the population weighted geographic remoteness of a subregion. The associations between rurality and rates of alcohol-related ED visits and hospitalizations were evaluated using hierarchical Bayesian spatial regression models.

FINDINGS

Rates of alcohol-related ED visits and hospitalizations varied substantially between subregions, with high rates clustering in Northern Ontario. Overall, increasing rurality was associated with higher subregion-level rates of alcohol-related ED visits (males adjusted relative rate [aRR]: 1.67, 95% credible interval [CI]: 1.49-1.87; females aRR: 1.78, 95% CI: 1.60-1.98) and hospitalizations (males aRR: 1.34, 95% CI: 1.24-1.45; females aRR: 1.59, 95% CI: 1.45-1.74). However, after the province was separated into Northern and Southern strata, this association only held in Northern subregions. In contrast, increasing rurality was associated with lower rates of alcohol-related ED visits in Southern subregions (males aRR: 0.87, 95% CI: 0.79-0.96; females aRR: 0.88, 95% CI: 0.81-0.97).

CONCLUSIONS

There are regional differences in the association between rurality and alcohol-related health service use. This regional variation should be considered when developing health policies to minimize geographic disparities in alcohol-related harm.

Area Deprivation and COVID-19 Incidence and Mortality in Bavaria, Germany: A Bayesian Geographical Analysis

Background

Area deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries.

Methods

In this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains.

Results

Deprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low.

Conclusions

In more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.

The impact of the COVID-19 pandemic on mortality: life expectancy reduction and geographical disparities in Argentina

OBJECTIVE

To assess the impact of the COVID-19 pandemic on mortality in Argentina, considering temporal trends in life expectancy at birth and premature mortality rate during 2010-2020.

METHODS

Based on demographic projections, this ecological time-series study compares a "normal" versus a "COVID-19" mortality scenario for 2020 over a set of 11 Argentine provinces. Annual life expectancy at birth and age-standardized rates of premature mortality were estimated from 2010 to 2020. Joinpoint regression and multilevel models were used.

RESULTS

A potential reduction in life expectancy at birth (a gap between scenarios >1 year) was observed. A significant (negative) point of inflection in temporal trends was identified for the country and most of the provinces, under the COVID-19 mortality scenario. However, our findings reveal disparities between provinces in the estimated life expectancy reduction toward 2020 (values range from -0.63 to -1.85 year in females and up to -2.55 years in males). While men showed more accentuated declines in life expectancy at birth in 2020 (a national gap between scenarios of -1.47 year in men vs. -1.35 year in women), women experienced more unfavorable temporal trends of premature mortality. In the absence of COVID-19, an improvement in both indicators was estimated toward 2020 in both sexes, while a return to levels reported in the past was observed under the COVID-19 scenario.

CONCLUSION

The COVID-19 pandemic might seriously affect the trends of mortality and exacerbate health disadvantages in Argentina. A temporal and contextual perspective of health inequities merits special attention in the COVID-19 research.

Neighbourhood socioeconomic improvement, residential mobility and premature death: a population-based cohort study and inverse probability of treatment weighting analysis

BACKGROUND

Causal inference using area-level socioeconomic measures is challenging due to risks of residual confounding and imprecise specification of the neighbourhood-level social exposure. By using multi-linked longitudinal data to address these common limitations, our study aimed to identify protective effects of neighbourhood socioeconomic improvement on premature mortality risk.

METHODS

We used data from the Canadian Community Health Survey, linked to health administrative data, including longitudinal residential history. Individuals aged 25-69, living in low-socioeconomic status (SES) areas at survey date (n = 8335), were followed up for neighbourhood socioeconomic improvement within 5 years. We captured premature mortality (death before age 75) until 2016. We estimated protective effects of neighbourhood socioeconomic improvement exposures using Cox proportional hazards models. Stabilized inverse probability of treatment weights (IPTW) were used to account for confounding by baseline health, social and behavioural characteristics. Separate analyses were carried out for three exposure specifications: any improvement, improvement by residential mobility (i.e. movers) or improvement in place (non-movers).

RESULTS

Overall, 36.9% of the study cohort experienced neighbourhood socioeconomic improvement either by residential mobility or improvement in place. There were noted differences in baseline health status, demographics and individual SES between exposure groups. IPTW survival models showed a modest protective effect on premature mortality risk of socioeconomic improvement overall (HR = 0.86; 95% CI 0.63, 1.18). Effects were stronger for improvement in place (HR = 0.67; 95% CI 0.48, 0.93) than for improvement by residential mobility (HR = 1.07, 95% 0.67, 1.51).

CONCLUSIONS

Our study provides robust evidence that specific neighbourhood socioeconomic improvement exposures are important for determining mortality risks.

Geographic footprints of life expectancy inequalities in the state of Geneva, Switzerland

Though Switzerland has one of the highest life expectancies in the world, this global indicator may mask significant disparities at a local level. The present study used a spatial cluster detection approach based on individual death records to investigate the geographical footprint of life expectancy inequalities in the state of Geneva, Switzerland. Individual-level mortality data (n = 22,751) were obtained from Geneva’s official death notices (2009–2016). We measured life expectancy inequalities using the years of potential life lost or gained (YPLLG) metric, defined as the difference between an individual’s age at death and their life expectancy at birth. We assessed the spatial dependence of YPLLG across the state of Geneva using spatial autocorrelation statistics (Local Moran’s I). To ensure the robustness of the patterns discovered, we ran the analyses for ten random subsets of 10,000 individuals taken from the 22,751 deceased. We also repeated the spatial analysis for YPLLG before and after controlling for individual-level and neighborhood-level covariates. The results showed that YPLLG was not randomly distributed across the state of Geneva. The ten random subsets revealed no significant difference with the geographic footprint of YPLLG and the population characteristics within Local Moran cluster types, suggesting robustness for the observed spatial structure. The proportion of women, the proportion of Swiss, the neighborhood median income, and the neighborhood median age were all significantly lower for populations in low YPLLG clusters when compared to populations in high YPLLG clusters. After controlling for individual-level and neighborhood-level covariates, we observed a reduction of 43% and 39% in the size of low and high YPLLG clusters, respectively. To our knowledge, this is the first study in Switzerland using spatial cluster detection methods to investigate inequalities in life expectancy at a local scale and based on individual data. We identified clear geographic footprints of YPLLG, which may support further investigations and guide future public health interventions at the local level.

A spatiotemporal analysis of inequalities in life expectancy and 20 causes of mortality in sub-neighbourhoods of Metro Vancouver, British Columbia, Canada, 1990-2016

Spatially varying baseline data can help identify and prioritise actions directed to determinants of intra-urban health inequalities. Twenty-seven years (1990-2016) of cause-specific mortality data in British Columbia, Canada were linked to three demographic data sources. Bayesian small area estimation models were used to estimate life expectancy (LE) at birth and 20 cause-specific mortality rates by sex and year. The gaps in LE for males and females ranged from 6.9 years to 9.5 years with widening inequality in more recent years. Inequality ratios increased for almost all causes, especially for HIV/AIDS and sexually transmitted infections, maternal and neonatal disorders, and neoplasms.

Building on existing tools to improve chronic disease prevention and screening in public health: a cluster randomized trial

BACKGROUND

The BETTER (Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Primary Care) intervention was designed to integrate the approach to chronic disease prevention and screening in primary care and demonstrated effective in a previous randomized trial.

METHODS

We tested the effectiveness of the BETTER HEALTH intervention, a public health adaptation of BETTER, at improving participation in chronic disease prevention and screening actions for residents of low-income neighbourhoods in a cluster randomized trial, with ten low-income neighbourhoods in Durham Region Ontario randomized to immediate intervention vs. wait-list. The unit of analysis was the individual, and eligible participants were adults age 40-64 years residing in the neighbourhoods. Public health nurses trained as "prevention practitioners" held one prevention-focused visit with each participant. They provided participants with a tailored prevention prescription and supported them to set health-related goals. The primary outcome was a composite index: the number of evidence-based actions achieved at six months as a proportion of those for which participants were eligible at baseline.

RESULTS

Of 126 participants (60 in immediate arm; 66 in wait-list arm), 125 were included in analyses (1 participant withdrew consent). In both arms, participants were eligible for a mean of 8.6 actions at baseline. At follow-up, participants in the immediate intervention arm met 64.5% of actions for which they were eligible versus 42.1% in the wait-list arm (rate ratio 1.53 [95% confidence interval 1.22-1.84]).

CONCLUSION

Public health nurses using the BETTER HEALTH intervention led to a higher proportion of identified evidence-based prevention and screening actions achieved at six months for people living with socioeconomic disadvantage.

TRIAL REGISTRATION

NCT03052959 , registered February 10, 2017.

Neighbourhood Social Determinants of Health and Geographical Inequalities in Premature Mortality in Taiwan: A Spatiotemporal Approach

Geographical inequalities in premature mortality and the role of neighbourhood social determinants of health (SDOH) have been less explored. This study aims to assess the geographical inequalities in premature mortality in Taiwan and how neighbourhood SDOH contribute to them and to examine the place-specific associations between neighbourhood SDOH and premature mortality. We used township-level nationwide data for the years 2015 to 2019, including age-standardized premature mortality rates and three upstream SDOH (ethnicity, education, and income). Space-time scan statistics were used to assess the geographical inequality in premature mortality. A geographical and temporal weighted regression was applied to assess spatial heterogeneity and how neighbourhood SDOH contribute to geographic variation in premature mortality. We found geographical inequality in premature mortality to be clearly clustered around mountainous rural and indigenous areas. The association between neighbourhood SDOH and premature mortality was shown to be area-specific. Ethnicity and education could explain nearly 84% variation in premature mortality. After adjusting for neighbourhood SDOH, only a handful of hotspots for premature mortality remained, mainly consisting of rural and indigenous areas in the central-south region of Taiwan. These findings provide empirical evidence for developing locally tailored public health programs for geographical priority areas.

A study protocol for a predictive algorithm to assess population-based premature mortality risk: Premature Mortality Population Risk Tool (PreMPoRT)

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 R2), 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.

Premature Mortality for Chronic Diseases in the EU Member States

Premature mortality, and especially premature mortality for chronic diseases, is a very important topic of public health, health care, or lifestyle of population. The main aim of countries is to reduce premature mortality, and therefore an analysis of the development and status of premature standardized death rates (SDR) is key for disclosure of successes or failures in this topic. A boxplot chart was used to detect extremes of SDR for both sexes. The gender ratio revealed the differences of mortality rates between men and women. Premature mortality declined steadily in the EU between 2000 and 2016. The men’s premature SDR decreased from 390 to 275.9 between 2000 and 2016, while the women’s rate declined from 180.1 to 138.2. On average, annual premature SDR dropped by 2.14% for men and 1.64% for women. Thus, the gender ratio (male/female) declined from 2.17 in 2000 to 2.0 in 2016, which is a positive change for gender gap closing. The highest proportion of premature mortality belonged to mortality for malignant neoplasms, where the rate was as high as 47% for women and 32% for men in 2016. Premature mortality for chronic disease is especially high in the “new” EU member states.