Background: This study examined the incidence of a person’s first diagnosis of a selected chronic disease, and the relationships between modifiable lifestyle risk factors and age to first of six chronic diseases.Methods: Ontario respondents from 2001 to 2010 of the Canadian Community Health Survey were followed up with administrative data until 2014 for congestive heart failure, chronic obstructive respiratory disease, diabetes, lung cancer, myocardial infarction and stroke. By sex, the cumulative incidence function of age to first chronic disease was calculated for the six chronic diseases individually and compositely. The associations between modifiable lifestyle risk factors (alcohol, body mass index, smoking, diet, physical inactivity) and age to first chronic disease were estimated using cause-specific Cox proportional hazards models and Fine-Gray competing risk models.Results: Diabetes was the most common disease. By age 70.5 years (2015 world life expectancy), 50.9% of females and 58.1% of males had at least one disease and few had a death free of the selected diseases (3.4% females; 5.4% males). Of the lifestyle factors, heavy smoking had the strongest association with the risk of experiencing at least one chronic disease (cause-specific hazard ratio = 3.86; 95% confidence interval = 3.46, 4.31). The lifestyle factors were modelled for each disease separately, and the associations varied by chronic disease and sex.Conclusions: We found that most individuals will have at least one of the six chronic diseases before dying. This study provides a novel approach using competing risk methods to examine the incidence of chronic diseases relative to the life course and how their incidences are associated with lifestyle behaviours.

Knowledge brokers (KBs) work collaboratively with key stakeholders to facilitate the transfer and exchange of information in a given context. Currently, there is a perceived lack of evidence about the effectiveness of knowledge brokering and the factors that influence its success as a knowledge translation (KT) mechanism. Thus, the goal of this review was to systematically gather evidence regarding the nature of knowledge brokering in health-related settings and determine if KBs effectively contributed to KT in these settings. A systematic review was conducted using a search strategy designed by a health research librarian. Eight electronic databases (MEDLINE, Embase, PsycINFO, CINAHL, ERIC, Scopus, SocINDEX, and Health Business Elite) and relevant grey literature sources were searched using English language restrictions. Two reviewers independently screened the abstracts, reviewed full-text articles, extracted data, and performed quality assessments. Analysis included a confirmatory thematic approach. To be included, studies must have occurred in a health-related setting, reported on an actual application of knowledge brokering, and be available in English. In total, 7935 records were located. Following removal of duplicates, 6936 abstracts were screened and 240 full-text articles were reviewed. Ultimately, 29 articles, representing 22 unique studies, were included in the thematic analysis. Qualitative (n = 18), quantitative (n = 1), and mixed methods (n = 6) designs were represented in addition to grey literature sources (n = 4). Findings indicated that KBs performed a diverse range of tasks across multiple health-related settings; results supported the KB role as a ‘knowledge manager’, ‘linkage agent’, and ‘capacity builder’. Our systematic review explored outcome data from a subset of studies (n = 8) for evidence of changes in knowledge, skills, and policies or practices related to knowledge brokering. Two studies met standards for acceptable methodological rigour; thus, findings were inconclusive regarding KB effectiveness. As knowledge managers, linkage agents, and capacity builders, KBs performed many and varied tasks to transfer and exchange information across health-related stakeholders, settings, and sectors. How effectively they fulfilled their role in facilitating KT processes is unclear; further rigourous research is required to answer this question and discern the potential impact of KBs on education, practice, and policy.

Healthcare spending occurs disproportionately among a very small portion of the population. Research on these high-cost users (HCUs) of health care has been overwhelmingly cross-sectional in nature and limited to the few sociodemographic and clinical characteristics available in health administrative databases. This study is the first to bridge this knowledge gap by applying a population health lens to HCUs. We investigate associations between a broad range of SES characteristics and future HCUs. A cohort of adults from two cycles of large, nationally representative health surveys conducted in 2003 and 2005 was linked to population-based health administrative databases from a universal healthcare plan for Ontario, Canada. Comprehensive person-centered estimates of annual healthcare spending were calculated for the subsequent 5 years following interview. Baseline HCUs (top 5%) were excluded and healthcare spending for non-HCUs was analyzed. Adjusted for predisposition and need factors, the odds of future HCU status (over 5 years) were estimated according to various individual, household, and neighborhood SES factors. Analyses were conducted in 2014. Low income (personal and household); less than post-secondary education; and living in high-dependency neighborhoods greatly increased the odds of future HCUs. After adjustment, future HCU status was most strongly associated with food insecurity, personal income, and non-homeownership. Living in highly deprived or low ethnic concentration neighborhoods also increased the odds of becoming an HCU. Findings suggest that addressing social determinants of health, such as food and housing security, may be important components of interventions aiming to improve health outcomes and reduce costs.

Health care spending is overwhelmingly concentrated within a very small proportion of the population, referred to as the high-cost users (HCU). To date, research on HCU has been limited in scope, focusing mostly on those characteristics available through administrative databases, which have been largely clinical in nature, or have relied on ecological measures of socio-demographics. This study links population health surveys to administrative data, allowing for the investigation of a broad range of individual-level characteristics and provides a more thorough characterization of community-dwelling HCU across demographic, social, behavioral and clinical characteristics. We linked three cycles of the Canadian Community Health Survey (CCHS) to medical claim data for the years 2003-2008 for Ontario, Canada. Participants were ranked according to gradients of cost (Top 1%, Top 2-5%, Top 6-50% and Bottom 50%) and multinomial logistic regression was used to investigate a wide range of factors, including health behaviors and socio-demographics, likely associated with HCU status. Using a total sample of 91,223 adults (18 and older), we found that HCU status was strongly associated with being older, having multiple chronic conditions, and reporting poorer self-perceived health. Specifically, in the fully-adjusted model, poor self-rated health (vs. good) was associated with a 26-fold increase in odds of becoming a Top 1% HCU (vs. Bottom 50% user) [95% CI: (18.9, 36.9)]. Further, HCU tended to be of lower socio-economic status, former daily smokers, physically inactive, current non-drinkers, and obese. The results of this study have provided valuable insights into the broader characteristics of community-dwelling HCU, including unique demographic and behavioral characteristics. Additionally, strong associations with self-reported clinical variables, such as self-rated general and mental health, highlight the importance of the patient perspective for HCU. These findings have the potential to inform policies for health care and public health, particularly in light of increasing decision-maker attention in the sustainability of the health care system, improving patient outcomes and, more generally, in order to achieve the common goal of improving population health outcomes.

Health interventions aimed at facilitating connectedness among seniors have recently gained traction, seeing as social connectedness is increasingly being recognized as an important determinant of health. However, research examining the association between connectedness and health across all age groups is limited, and few studies have focused on community belonging as a tangible aspect of social connectedness. Using a population-based Canadian cohort, this study aims to investigate (1) the associations between community belonging with self-rated general health and self-rated mental health, and (2) how these associations differ across life stages. Data from six cycles of a national population health survey (Canadian Community Health Survey) from 2003 to 2014 were combined. Multinomial logistic regressions were run for both outcomes on the overall study sample, as well as within three age strata: (1) 18–39, (2) 40–59, and (3) ≥ 60 years old. Weaker community belonging exhibited an association with both poorer general and mental health, though a stronger association was observed with mental health. These associations were observed across all three age strata. In the fully adjusted model, among those reporting a very weak sense of community belonging, the odds of reporting the poorest versus best level of health were 3.21 (95% CI: 3.11, 3.31) times higher for general health, and 4.95 (95% CI: 4.75, 5.16) times higher for mental health, compared to those reporting a very strong sense of community belonging. The largest effects among those reporting very weak community belonging were observed among those aged between 40 and 59 years old. This study contributed to the evidence base supporting life stage differences in the relationship between community belonging and self-perceived health. This is a starting point to identifying how age-graded differences in unmet social needs relate to population health interventions.

During a pandemic, news media play a crucial role in communicating public health and policy information. Traditional newspaper coverage is important amidst increasing disinformation, yet uncertainties make covering health risks and efforts to limit transmission difficult. This study assesses print and online newspaper coverage of the coronavirus disease COVID-19 for March 2020, when the global pandemic was declared, through August 2020 in three countries: Canada (with the lowest per-capita case and death rates during the study timeframe), the United Kingdom (with a pronounced early spike), and the United States (with persistently high rates). Tools previously validated for pandemic-related news records allow measurement of multiple indicators of scientific quality (i.e., reporting that reflects the state of scientific knowledge) and of sensationalism (i.e., strategies rendering news as more extraordinary than it really is). COVID-19 reporting had moderate scientific quality and low sensationalism across 1331 sampled articles in twelve newspapers spanning the political spectrums of the three countries. Newspapers oriented towards the populist-right had the lowest scientific quality in reporting, combined with very low sensationalism in some cases. Against a backdrop of world-leading disease rates, U.S. newspapers on the political left had more exposing coverage, e.g., focused on policy failures or misinformation, and more warning coverage, e.g., focused on the risks of the disease, compared to U.S. newspapers on the political right. Despite the generally assumed benefits of low sensationalism, pandemic-related coverage with low scientific quality that also failed to alert readers to public-health risks, misinformation, or policy failures may have exacerbated the public-health effects of the disease. Such complexities will likely remain central for both pandemic news media reporting and public-health strategies reliant upon it.