Smoking patterns based on birth-cohort-specific histories from 1965 to 2013, with projections to 2041.

BACKGROUND: Characterizing smoking patterns over time is essential for evaluating the impact of tobacco control interventions and predicting smoking-related mortality. Beginning with a 1920s birth cohort, smoking histories (i.e., estimates of smoking initiation and cessation, and prevalence of current and former smokers) were generated. DATA: The Ontario sample (n = 238,411) of the 2003 to 2013 cycles of the Canadian Community Health Survey, which is conducted biennially, was used to obtain cross-sectional information on current smoking behaviour. METHODS: Age at smoking initiation and age at smoking cessation were used to construct smoking histories for each respondent, up to the survey date. An age-period-cohort model was generated and used to examine survival differences by smoking status. Using the model, and adjusting for survival differences in smoking status, the prevalence of current, former and never smokers was estimated in cohorts from 1920 to 1985. Smoking initiation, cessation and intensity were then estimated for age-specific distributions of each birth cohort. These rates were projected forward through to 2041. Smoking patterns by highest level of education were generated using education-stratified models. RESULTS: Smoking histories show clear trends over time by sex, cohort and age. If current patterns persist, smoking prevalence is projected to decline to single digits (below 10%) by 2023 for women and 2040 for men. DISCUSSION: Birth-cohort-specific smoking histories can be generated using cross-sectional health surveys. These cohort histories can describe smoking patterns over time and into the future. In turn, these histories can be used in micro-simulation models to evaluate historic or planned tobacco control interventions, and to project smoking prevalence.

Burden of health behaviours and socioeconomic position on health care expenditure in Ontario.

Background: Smoking, unhealthy alcohol consumption, poor diet and physical inactivity are leading risk factors for morbidity and mortality, and contribute substantially to overall healthcare costs. The availability of health surveys linked to health care provides population-based estimates of direct healthcare costs. We estimated health behaviour and socioeconomic-attribute healthcare costs, and how these have changed during a period when government policies have aimed to reduce their burden.  Methods: The Ontario samples of the Canadian Community Health Surveys (conducted in 2003, 2005, and 2007-2008) were linked at the individual level to all records of health care use of publicly funded healthcare. Generalized linear models were estimated with a negative binomial distribution to ascertain the relationship of health behaviours and socioeconomic risk factors on health care costs. The multivariable cost model was applied to unlinked, Ontario CCHS samples for each year from 2004 to 2013 to examine the evolution of health behaviour and socioeconomic-attributable direct health care expenditures over a 10-year period. Results: We included 80,749 respondents, aged 25 years and older, and 312,952 person-years of follow-up. The cost model was applied to 200,324 respondents aged 25 years and older (CCHS 2004 to 2013). During the 10-year period from 2004 to 2013, smoking, unhealthy alcohol consumption, poor diet and physical inactivity attributed to 22% of Ontario's direct health care costs. Ontarians in the most disadvantaged socioeconomic position contributed to 15% of the province's direct health care costs. Combined, these health behaviour and socioeconomic risk factors were associated with 34% ($134 billion) of direct health care costs (2004 to 2013). Over this time period, we estimated a 1.9% reduction in health care expenditure ($5.0 billion) attributable to improvements in some health behaviours, most importantly reduced rates of smoking. Conclusions: Adverse health behaviours and socioeconomic position cause a large direct health care system cost burden.

Factors Associated with Residential Long-Term Care Wait-List Placement in North West Ontario.

This article is based on a study that investigated factors associated with long-term care wait list placement in Ontario, Canada. We based the study's analysis on Resident Assessment Instrument for Home Care (RAI-HC) data for 2014 in the North West Local Health Integration Network (LHIN). Our analysis quantified the contribution of three factors on the likelihood of wait list placement: (1) care recipient, (2) informal caregiver, and (3) formal system. We find that all three factors are significantly related to wait list placement. The results of this analysis could have implications for policies aimed at reducing the number of wait-listed individuals in the community.

Measuring Work Engagement, Psychological Empowerment, and Organizational Citizenship Behavior Among Health Care Aides.

PURPOSE OF THE STUDY: Health care aides (HCAs) provide most direct care in long-term care (LTC) and home and community care (HCC) settings but are understudied. We validate three key work attitude measures to better understand HCAs' work experiences: work engagement (WEng), psychological empowerment (PE), and organizational citizenship behavior (OCB-O). DESIGN AND METHODS: Data were collected from 306 HCAs working in LTC and HCC, using survey items for WEng, PE, and OCB-O adapted for HCAs. Psychometric evaluation involved confirmatory factor analysis (CFA). Predictive validity (correlations with measures of job satisfaction and turnover intention) and internal consistency reliability were examined. RESULTS: CFA supported a one-factor model of WEng, a four-factor model of PE, and a one-factor model of OCB-O. HCC workers scored higher than LTC workers on Self-determination (PE) and lower on Impact, demonstrating concurrent validity. WEng and PE correlated with worker outcomes (job satisfaction, turnover intention, and OCB-O), demonstrating predictive validity. Reliability and validity analyses indicated sound psychometric properties overall. IMPLICATIONS: Study results support psychometric properties of measures of WEng, PE, and OCB-O for HCAs. Knowledge of HCAs' work attitudes and behaviors can inform recruitment programs, incentive systems, and retention/training strategies for this vital group of care providers.