According to the data, the rate of opioid-related deaths, hospitalizations and emergency room visits is higher among Canadians of lower socioeconomic status (SES) than those of higher SES.
In a retrospective observational study of national data from 2000 to 2017, the opioid-related mortality rate was 3.8 times higher in the lowest income quintile, and the rates of hospitalizations and emergency room visits were 4, 3 and 4.9 times higher, respectively. This pattern persisted for two decades.
Dr Wasem Alsabbagh
The opioid crisis is escalating across the country,” said lead author Wasem Alsabbagh, PhD, assistant professor of pharmacy at the University of Waterloo in Kitchener, Ontario, Canada. Medscape Medical News. “The mortality rate in low-income areas in 2005 was reached in the highest-income areas in 2015. From this perspective, higher SES protected individuals from the effects of opioid crises for some time. , but the effects eventually reached high-income areas. ”
The data was published in the June issue of Health Promotion and Chronic Disease Prevention in Canada.
Closing the Mortality Gap
“Despite the uneven distribution we observed, the harms of the opioid epidemic are clearly not limited to low-income people,” the researchers wrote. “These data allow us to see the progression of the epidemic over time, with its effects moving from less advantaged areas to more advantaged areas. … Therefore, the reduction in the mortality gap could indicate that the The opioid epidemic will eventually be felt throughout Canadian society, and that high SES only delays its effects and cannot prevent it.
Investigators reviewed national administrative databases to capture opioid-related mortality (from 2000 to 2017), opioid-related hospitalizations (from 2000 to 2012) and opioid-related emergency room visits (from 2002 to 2012) and compared them to SES and income estimates. that were generated from census data.
“We calculated crude annual rates of opioid-related mortality, hospitalization, and emergency room visits in each income quintile by summing all cases per year and dividing by the estimated population,” the authors wrote. All rates have been adjusted for age and sex differences between income quintiles. The rate ratios were then calculated by dividing the rate of each income quintile by that of the highest quintile.
The results showed that the adjusted death rates ranged from 18.6 to 72.1 cases per million between the highest and lowest income quintiles, respectively. The resulting rate ratio between the bottom and top income quintiles was 3.8. For hospitalizations, the adjusted rates ranged from 96.5 to 413.2 cases per million between the highest and lowest income quintiles, for a rate ratio of 4.3. And for emergency room visits, the adjusted rates ranged from 175.4 to 861.6 cases per million between the highest and lowest income quintiles, for a rate ratio of 4.9.
There were consistently higher rates of all opioid-related outcomes in the lowest income quintile, relative to the highest, throughout the study period. The gap between the two extremes has narrowed over time for death rates, but not for hospitalizations or emergency room visits.
The authors wrote that “there is no definitive explanation for the existence of income gradients in so many health outcomes”, adding that “the clear and consistent gradient suggests that it is not material conditions (access to goods, services, neighborhood quality) that matter most….Instead, this suggests that psychosocial factors play a key role in this gradient.
Even in communities with higher SES, these psychosocial factors include “lack of social support from the immediate network (i.e. family and close friends) and the wider network (i.e. i.e. the community at large), as well as the kind of help individuals can get. coping with stressful life events, providing a sense of belonging and social solidarity,” said Alsabbagh.
“Dramatic socio-economic gradient”
Doctor Christopher Lowenstein
Commenting on the findings of medical landscape, Christopher Lowenstein, PhD, postdoctoral researcher in epidemiology at the University of California, Berkeley, said: “The implications of the study should not be underestimated. The authors’ descriptive analysis highlights a dramatic socio-economic gradient in adverse opioid-related outcomes in Canada. Many studies look only at mortality, and by drawing on other measures of morbidity (e.g., hospitalizations for opioid use disorders), the authors are able to expand the scope. in a very important way that speaks to the magnitude of this crisis. Lowenstein was not involved in the study.
Although he agrees with the authors that the results are not explained solely by income or material resources, he suggests that their alternative explanation of psychosocial factors “does not rely on any of the characteristics linked instead that co-determine the actual amount of drugs in a community”. . … I think it may be an oversight from the article.
“There is evidence that low SES areas have had higher supplies of opioids, which would explain the SES gradient rather than income, poverty or psychosocial factors, [and] reducing the supply of opioids through various policies has been shown to reduce mortality from opioids,” Lowenstein said.
Another expert, Gene Heyman, PhD, associate professor of psychology at Boston College, Newton, Massachusetts, wrote that “explanations for the overdose epidemic that do not go beyond increased access to opioids are, at best, incomplete”.
Heyman, who was not involved in the study but published his own paper on the subject, criticized the new paper’s methodology as “very basic.”
“The usual practice is to use multiple regression techniques that allow the investigator to organize statistical controls for covariates,” he said. medical landscape. “The authors, as I understand their paper, did not. For example, what they call SES is likely to be correlated with level of education (they measure income but call it SES) , race, ethnicity, political orientation, etc. So, to varying degrees, these factors, rather than income, may be related to overemphasizing the differences…. I suspect that income could still be an important predictor overdoses, but with proper controls, that would be a weaker predictor than their graphs indicate.
The study was partially funded by Health Canada’s Substance Use and Addictions Program. Alsabbagh, Lowenstein and Heyman declared no conflicts of interest.
Health Promot Chronic Dis Prev Can. 2022;42:229-237. Full Text.
kate johnson is a Montreal-based freelance medical journalist who has written for over 30 years on all areas of medicine.
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