Differential Patterns by Area-Level Social Determinants of Health in Coronavirus Disease 2019 (COVID-19)-Related Mortality and Non-COVID-19 Mortality: A Population-Based Study of 11.8 Million People in Ontario, Canada

Increased mortality in socioeconomic disadvantaged municipalities during the first phase of the COVID-19 pandemic in Lombardy region

BACKGROUND

Lombardy was the first European region most severely affected by the coronavirus disease 2019 pandemic in the spring of 2020. During that period, a substantial increase in socioeconomic inequality in total mortality was observed. This study aims to evaluate mortality data in the region up to September 2023 to verify whether the increased disparities between the poorest and the wealthiest municipalities persisted in the subsequent phases of the pandemic.

METHODS

This study analyzed mortality data from January 2019 to September 2023 in Lombardy's municipalities by month and pandemic phases characterized by the predominance of the different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Municipalities were grouped according to the average income or pension of their residents. Age-standardized mortality rates (ASMRs) and the ASMR ratio between the poorest and the wealthiest municipalities were compared throughout the study period.

RESULTS

In the pre-pandemic period (January 2019 - February 2020), the ASMR ratio at all ages between the poorest and the wealthiest municipalities fluctuated between 1.12 [95% confidence interval (CI): 1.07-1.16] and 1.29 (95% CI: 1.25-1.34). In March 2020, the ASMR ratio increased to 1.49 (95% CI: 1.45-1.52 95%) and returned to values registered before the pandemic thereafter. A similar pattern was observed in the analysis of mortality ≥ 65, using the average pension for group municipalities.

CONCLUSIONS

During the dramatic circumstances that the region faced in March 2020, pre-existing socioeconomic inequalities substantially widened. With the reorganization of the health system and the availability of vaccines, these disparities returned to the levels recorded before the pandemic.

A cohort study of patients hospitalised with SARS-CoV-2 infection in Ontario: patient characteristics and outcomes by wave

INTRODUCTION

Each wave of the COVID-19 pandemic exhibited a unique combination of epidemiological, social and structural characteristics. We explore similarities and differences in wave-over-wave characteristics of patients hospitalised with COVID-19.

METHODS

This was a population-based study in Ontario province, Canada. Patients hospitalised with SARS-CoV-2 between 26 February 2020 and 31 March 2022 were included. An admission was considered related to SARS-CoV-2 infection if the provincial inpatient or outpatient hospital databases contained the ICD-10 diagnostic codes U071/U072 or the Ontario Laboratories Information System indicated a positive SARS-CoV-2 test result (PCR or rapid antigen testing) during the admission or up to two weeks prior. The primary outcome was 90-day mortality (modified Poisson regression). Secondary outcomes were use of critical care during the admission (logistic regression) and total length-of-stay (linear regression with heteroskedastic-consistent standard-error estimators). All models were adjusted for demographic characteristics, neighbourhood socioeconomic factors and indicators of illness severity.

RESULTS

There were 73,201 SARS-CoV-2-related admissions: 6127 (8%) during wave 1 (wild-type), 14,371 (20%) during wave 2 (wild-type), 16,653 (23%) during wave 3 (Alpha), 5678 (8%) during wave 4 (Delta) and 30,372 (42%) during wave 5 (Omicron). SARS-CoV-2 was the most responsible diagnosis for 70% of admissions during waves 1-2 and 42% in wave 5. The proportion of admitted patients who were long-term care residents was 18% (n = 1111) during wave 1, decreasing to 10% (n = 1468) in wave 2 and <5% in subsequent waves. During waves 1-3, 46% of all admitted patients resided in a neighbourhood assigned to the highest ethnic diversity quintile, which declined to 27% during waves 4-5. Compared to wave 1, 90-day mortality was similar during wave 2 (adjusted risk ratio [aRR]: 1.00 [95% CI: 0.95-1.04]), but lower during wave 3 (aRR: 0.89 [0.85-0.94]), wave 4 (aRR: 0.85 [0.79-0.91]) and wave 5 (aRR: 0.83 [0.80-0.88]). Improvements in survival over waves were observed among elderly patients (p-interaction <0.0001). Critical care admission was significantly less likely during wave 5 than previous waves (adjusted odds ratio: 0.50 [0.47-0.54]). The length of stay was a median of 8.5 (3.6-23.8) days during wave 1 and 5.3 (2.2-12.6) during wave 5. After adjustment, the mean length of stay was on average -10.4 (-11.1 to -9.8) days, i.e. shorter, in wave 5 vs wave 1.

CONCLUSION

Throughout the pandemic, sociodemographic characteristics of patients hospitalised with SARS-CoV-2 changed over time, particularly in terms of ethnic diversity, but still disproportionately affected patients from more marginalised regions. Improved survival and reduced use of critical care during the Omicron wave are reassuring.

Towards closing socio-economic status disparities in COVID-19 premature mortality: a nationwide and trend analysis in Chile

BACKGROUND

Socio-economic status (SES) disparities in coronavirus disease 2019 (COVID-19) mortality have been reported but complete information and time trends are scarce. In this study, we analysed the years of life lost (YLL) due to COVID-19 premature mortality during the pandemic in Chile and its evolution according to SES and sex compared with a counterfactual scenario [cerebrovascular accidents (stroke)].

METHOD

We used Chile's national mortality databases from 2020 to 2022. YLL and age-standardized YLL and mortality rates by sex and by epidemic waves were determined. The 346 communes were stratified into SES groups according to their poverty index quintile. Negative binomial regression models were used to test trends.

RESULTS

In >2 years of the pandemic, the COVID-19 YLL was 975 937, corresponding to 61 174 deaths. The YLL rate per 100 000 inhabitants was 1027 for males and 594 for females. There was a heterogeneous distribution of YLL rates and the regional level. Communes in the most advantaged SES quintile (Q5) had the highest YLL during the first wave compared with those in the lowest SES quintile (Q1) (P < 0.001) but the opposite was true during the second wave. COVID-19 YLL trends declined and differences between Q1 and Q2 vs Q5 converged from the second to the fourth waves (0.33 and 0.15, Ptrend < 0.001 and Ptrend = 0.024). YLL declined but differences persisted in stroke (-0.002, Ptrend = 0.979).

CONCLUSIONS

COVID-19 deaths resulted in a higher impact on premature death in Chile, especially in men, with a heterogeneous geographic distribution along the territory. SES and sex disparities in COVID-19 premature mortality had narrowed by the end of the pandemic.

Social determinants of health during and after coronavirus: a qualitative study

BACKGROUND

Health has multiple dimensions influenced not only by individual factors but also by broader social, economic, cultural, and political structures. The widespread COVID-19 pandemic has multidimensional effects on people's lives, which can have effects on individuals' lifestyles after the COVID-19. This study aimed to speculate the social determinants of health during and after the COVID-19, which can lead to more effective planning for promoting community health.

METHODS

The present study interviewed 21 experts in social and medical fields during four months. The sampling method was snowball. The interviews were semi-structured and administered in-person or electronic. All interviews were transcribed and analyzed according to the Brown and Clarke's six-stage framework to extract themes.

RESULTS

the participants were 13 males, eight experts in social field, all had PhD, 17 were academic members, and 10 were members of the Social Determinants of Health Research Center. The qualitative content analysis induced seven different social themes that affect the health which included: justice (3 Subcategories), integration (4 Subcategories), acceptance (4 Subcategories), participation (2 Subcategories), adaptation (3 Subcategories), flourishing (4 Subcategories), and cohesion (3 Subcategories).

CONCLUSIONS

According to the present study, a grand plan to cover all positive and negative social effects of COVID-19 should have at least seven different dimensions. However, the present models of effective social determinants in health do not have such comprehensiveness. Future studies may provide a proper model to be used in clinical and research fields.

Neighbourhood-level socioeconomic status and prevalence of teacher-reported health disorders among Canadian kindergarten children

Background

The evidence on the association between neighborhood-level socioeconomic status (SES) and health disorders in young children is scarce. This study examined the prevalence of health disorders in Canadian kindergarten (5-6 years old) children in relation to neighborhood SES in 12/13 Canadian jurisdictions.

Methods

Data on child development at school entry for an eligible 1,372,980 children out of the total population of 1,435,428 children from 2004 to 2020, collected using the Early Development Instrument (EDI), were linked with neighborhood sociodemographic data from the 2006 Canadian Census and the 2005 Taxfiler for 2,058 neighborhoods. We examined the relationship using linear regressions. Children's HD included special needs, functional impairments limiting a child's ability to participate in classroom activities, and diagnosed conditions.

Results

The neighborhood prevalence of health disorders across Canada ranged from 1.8 to 46.6%, with a national average of 17.3%. The combined prevalence of health disorders was 16.4%, as 225,711 children were identified as having at least one health disorder. Results of an unadjusted linear regression showed a significant association between neighborhood-level SES and prevalence of health disorders (F(1, 2051) = 433.28, p < 0.001), with an R2 of 0.17. When province was added to the model, the R2 increased to 0.40 (F(12, 2040) = 115.26, p < 0.001). The association was strongest in Newfoundland & Labrador and weakest in Ontario.

Conclusion

Our study demonstrated that the prevalence of health disorders among kindergarten children was higher in lower SES neighborhoods and varied by jurisdiction in Canada, which has implications for practice and resource allocation.

Variability in excess deaths across countries with different vulnerability during 2020-2023

Excess deaths provide total impact estimates of major crises, such as the COVID-19 pandemic. We evaluated excess death trajectories across countries with accurate death registration and population age structure data and assessed relationships with vulnerability indicators. Using the Human Mortality Database on 34 countries, excess deaths were calculated for 2020-2023 (to week 29, 2023) using 2017-2019 as reference, with adjustment for 5 age strata. Countries were divided into less and more vulnerable; the latter had per capita nominal GDP < $30,000, Gini > 0.35 for income inequality and/or at least ≥2.5% of their population living in poverty. Excess deaths (as proportion of expected deaths, p%) were inversely correlated with per capita GDP (r = -0.60), correlated with proportion living in poverty (r = 0.66), and modestly correlated with income inequality (r = 0.45). Incidence rate ratio for deaths was 1.062 (95% CI, 1.038-1.087) in more versus less vulnerable countries. Excess deaths started deviating in the two groups after the first wave. Between-country heterogeneity diminished gradually within each group. Less vulnerable countries had mean p% = -0.8% and 0.4% in 0-64 and >65-y-old strata. More vulnerable countries had mean p% = 7.0% and 7.2%, respectively. Lower death rates were seen in children of age 0-14 y during 2020-2023 versus prepandemic years. While the pandemic hit some countries earlier than others, country vulnerability dominated eventually the cumulative impact. Half the analyzed countries witnessed no substantial excess deaths versus prepandemic levels, while the others suffered major death tolls.

Smoke and Spike: Benzo[a]pyrene Enhances SARS-CoV-2 Infection by Boosting NR4A2-Induced ACE2 and TMPRSS2 Expression

Cigarette smoke aggravates severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, the underlying mechanisms remain unclear. Here, they show that benzo[a]pyrene in cigarette smoke extract facilitates SARS-CoV-2 infection via upregulating angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2). Benzo[a]pyrene trans-activates the promoters of ACE2 and TMPRSS2 by upregulating nuclear receptor subfamily 4 A number 2 (NR4A2) and promoting its binding of NR4A2 to their promoters, which is independent of functional genetic polymorphisms in ACE2 and TMPRSS2. Benzo[a]pyrene increases the susceptibility of lung epithelial cells to SARS-CoV-2 pseudoviruses and facilitates the infection of authentic Omicron BA.5 in primary human alveolar type II cells, lung organoids, and lung and testis of hamsters. Increased expression of Nr4a2, Ace2, and Tmprss2, as well as decreased methylation of CpG islands at the Nr4a2 promoter are observed in aged mice compared to their younger counterparts. NR4A2 knockdown or interferon-λ2/λ3 stimulation downregulates the expression of NR4A2, ACE2, and TMPRSS2, thereby inhibiting the infection. In conclusion, benzo[a]pyrene enhances SARS-CoV-2 infection by boosting NR4A2-induced ACE2 and TMPRSS2 expression. This study elucidates the mechanisms underlying the detrimental effects of cigarette smoking on SARS-CoV-2 infection and provides prophylactic options for coronavirus disease 2019, particularly for the elderly population.

Variability in excess deaths across countries with different vulnerability during 2020-2023

Excess deaths provide total impact estimates of major crises, such as the COVID-19 pandemic. We evaluated excess death's trajectories during 2020-2023 across countries with accurate death registration and population age structure data; and assessed relationships with economic indicators of vulnerability. Using the Human Mortality Database on 34 countries, excess deaths were calculated for 2020-2023 (to week 29, 2023) using 2017-2019 as reference, with weekly expected death calculations and adjustment for 5 age strata. Countries were divided into less and more vulnerable; the latter had per capita nominal GDP<$30,000, Gini>0.35 for income inequality and/or at least 2.5% of their population living in poverty. Excess deaths (as proportion of expected deaths, p%) were inversely correlated with per capita GDP (r=-0.60), correlated with proportion living in poverty (r=0.66) and modestly correlated with income inequality (r=0.45). Incidence rate ratio for deaths was 1.06 (95% confidence interval, 1.04-1.08) in the more versus less vulnerable countries. Excess deaths started deviating in the two groups after the first wave. Between-country heterogeneity diminished over time within each of the two groups. Less vulnerable countries had mean p%=-0.8% and 0.4% in 0-64 and >65 year-old strata while more vulnerable countries had mean p%=7.0% and 7.2%, respectively. Usually lower death rates were seen in children 0-14 years old during 2020-2023 versus pre-pandemic years. While the pandemic hit some countries earlier than others, country vulnerability dominated eventually the cumulative impact. Half of the analyzed countries witnessed no substantial excess deaths versus pre-pandemic levels, while the other half suffered major death tolls.

Temporal trends and determinants of COVID-19 vaccine coverage and series initiation during pregnancy in Ontario, Canada, December 2020 to December 2021: A population-based retrospective cohort study

BACKGROUND

Population-based COVID-19 vaccine coverage estimates among pregnant individuals are limited. We assessed temporal patterns in vaccine coverage (≥1 dose before or during pregnancy) and evaluated factors associated with vaccine series initiation (receiving dose 1 during pregnancy) in Ontario, Canada.

METHODS

We linked the provincial birth registry with COVID-19 vaccination records from December 14, 2020 to December 31, 2021 and assessed coverage rates among all pregnant individuals by month, age, and neighborhood sociodemographic characteristics. Among individuals who gave birth since April 2021-when pregnant people were prioritized for vaccination-we assessed associations between sociodemographic, behavioral, and pregnancy-related factors with vaccine series initiation using multivariable regression to estimate adjusted risk ratios (aRR) and risk differences (aRD) with 95% confidence intervals (CI).

RESULTS

Among 221,190 pregnant individuals, vaccine coverage increased to 71.2% by December 2021. Gaps in coverage across categories of age and sociodemographic characteristics decreased over time, but did not disappear. Lower vaccine series initiation was associated with lower age (<25 vs. 30-34 years: aRR 0.53, 95%CI 0.51-0.56), smoking (vs. non-smoking: 0.64, 0.61-0.67), no first trimester prenatal care visit (vs. visit: 0.80, 0.77-0.84), and residing in neighborhoods with the lowest income (vs. highest: 0.69, 0.67-0.71). Vaccine series initiation was marginally higher among individuals with pre-existing medical conditions (vs. no conditions: 1.07, 1.04-1.10).

CONCLUSIONS

COVID-19 vaccine coverage among pregnant individuals remained lower than in the general population, and there was lower vaccine initiation by multiple characteristics.

Which Curve Are We Flattening? The Disproportionate Impact of COVID-19 Among Economically Marginalized Communities in Ontario, Canada, Was Unchanged From Wild-Type to Omicron

Person-level surveillance (N = 14 million) and neighborhood-level income data were used to explore magnitude of inequalities in COVID-19 hospitalizations and deaths over 5 waves in Ontario, Canada. Despite attempts at equity-informed policies alongside fluctuating levels of public health measures, the magnitude of inequalities in hospitalizations and deaths remained unchanged across waves.