Mind the Gap: Disparities in Cigarette Smoking in Canada

Abstract

Objectives: The Government of Canada has proposed an ‘endgame’ target for cigarette smoking that aims to reduce prevalence below 5% by 2035. To meet this difficult goal, it will be necessary to identify populations where interventions will (1) have the greatest impact in reducing the number of smokers and (2) have the greatest impact in addressing smoking disparities. Method(s): Using data from the Canadian Community Health Survey, smoking prevalence was estimated for populations that differed with respect to demographic, substance use, and mental health factors. Risk difference, relative risk, and attributable disparity number, which describes the magnitude of the potential impact if the disparity were addressed, were calculated for each group. Results: The strongest disparities (relative risk ⩾ 2) were associated with immigration status (for women), substance use, marital status, and lifetime experience of mental health or substance use disorders. The smallest disparities (relative risk ⩽ 1.5) were associated with sexual orientation, household income, immigration status (men), and province of residence. The groups with the largest attributable disparity number were among those who used cannabis, and those who were not immigrants, not married, and white. Conclusions: Disparities which were both strong and had a large potential impact on prevalence overall were found for populations facing mental health and substance use concerns. Differences in rankings were found depending on the scale of the measure. Addressing disparities in smoking rates is an important component of developing tobacco endgame strategies.

Variation in characteristics of people with mental disorders across smoking status in the Canadian general population

“…The unmet smoking cessation needs of people with mental disorders are even worse in those who are socially deprived, such as people who are less educated, have low incomes, and are immigrants, as they face a less supportive environment that makes their smoking cessation more challenging. The challenges include less access to cessation support (due to, for example, financial constraints, language barriers, less access to resources for cessation, and less knowledge about smoking cessation support measures) and low family or social support 3,4,27 . Additionally, the high levels of nicotine exposure and dependence, and the severity of mental disorders in this group may make their smoking cessation process less successful 29 .…”

“…It is responsible for massive direct and indirect costs, including healthcare costs 1,2 . Smoking is common among vulnerable and socioeconomically disadvantaged groups and is a significant contributor of health inequalities across populations [3][4][5] . The prevalence of smoking, including the severity of smoking (i.e.…”

Particulate matter concentrations in social housing

“…PM2.5 and other pollutants can spread between apartments in multi-unit residential buildings [7,8,[47][48][49]. The impact of indoor and outdoor sources can be compounded by building factors such as underventilation or increased infiltration from outdoors respectively [26], and social factors such as an increased prevalence of smoking among populations with lowsocioeconomic status (SES) [26,50,51] given that smoking has been shown to significantly increase indoor PM2.5 concentrations [3,7,8,[52][53][54][55]. Although energy retrofits are sometimes cited as a means to reduce carbon emissions and improve thermal comfort in social housing, the impact of retrofits on PM2.5 concentration is mixed [27].…”

Variability in patient sociodemographics, clinical characteristics, and healthcare service utilization among 107,302 treatment seeking smokers in Ontario: A cross-sectional comparison

“…Patients were not a homogeneous group; there was variation across STOP models with regard to individual characteristics. Enrollees in the Web model had the youngest (39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49) and Family Health Teams the oldest (51 IQR 40-60) median age (Fig 1). Nine of eleven models had a little more than 50% female patients; Addiction Agencies had the lowest proportion of female patients (39.0%).…”

“…Comparing the sociodemographic and health profile of smokers who sought treatment via each of the STOP models can help identify which models are able to reach more vulnerable groups. A disproportionate share of tobacco-related health burden is borne by already disadvantaged groups [48], such as those with lower socioeconomic status or comorbid mental illness, due to increased prevalence of tobacco use, lower cessation rates, barriers to accessing treatment and/or greater vulnerability to associated health risks [49]. Current findings indicate that not all models equally reached socially disadvantaged, and rural dwelling, individuals that traditionally experience greater barriers to accessing treatment.…”