Statistics Canada

About: Statistics Canada is a government organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Population & Earnings. The organization has 1091 authors who have published 2595 publications receiving 85937 citations. The organization is also known as: StatCan.

A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review

Abstract: Accurate assessment is required to assess current and changing physical activity levels, and to evaluate the effectiveness of interventions designed to increase activity levels. This study systematically reviewed the literature to determine the extent of agreement between subjectively (self-report e.g. questionnaire, diary) and objectively (directly measured; e.g. accelerometry, doubly labeled water) assessed physical activity in adults. Eight electronic databases were searched to identify observational and experimental studies of adult populations. Searching identified 4,463 potential articles. Initial screening found that 293 examined the relationship between self-reported and directly measured physical activity and met the eligibility criteria. Data abstraction was completed for 187 articles, which described comparable data and/or comparisons, while 76 articles lacked comparable data or comparisons, and a further 30 did not meet the review's eligibility requirements. A risk of bias assessment was conducted for all articles from which data was abstracted. Correlations between self-report and direct measures were generally low-to-moderate and ranged from -0.71 to 0.96. No clear pattern emerged for the mean differences between self-report and direct measures of physical activity. Trends differed by measure of physical activity employed, level of physical activity measured, and the gender of participants. Results of the risk of bias assessment indicated that 38% of the studies had lower quality scores. The findings suggest that the measurement method may have a significant impact on the observed levels of physical activity. Self-report measures of physical activity were both higher and lower than directly measured levels of physical activity, which poses a problem for both reliance on self-report measures and for attempts to correct for self-report – direct measure differences. This review reveals the need for valid, accurate and reliable measures of physical activity in evaluating current and changing physical activity levels, physical activity interventions, and the relationships between physical activity and health outcomes.

A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review

Abstract: Obesity is a rapidly increasing public health problem, with surveillance most often based on self-reported values of height and weight. We conducted a systematic review to determine what empirical evidence exists regarding the agreement between objective (measured) and subjective (reported) measures in assessing height, weight and body mass index (BMI). Five electronic databases were searched to identify observational and experimental studies on adult populations over the age of 18. Searching identified 64 citations that met the eligibility criteria and examined the relationship between self-reported and directly measured height or weight. Overall, the data show trends of under-reporting for weight and BMI and over-reporting for height, although the degree of the trend varies for men and women and the characteristics of the population being examined. Standard deviations were large indicating that there is a great deal of individual variability in reporting of results. Combining the results quantitatively was not possible because of the poor reporting of outcomes of interest. Accurate estimation of these variables is important as data from population studies such as those included in this review are often used to generate regional and national estimates of overweight and obesity and are in turn used by decision makers to allocate resources and set priorities in health.

Introduction To Variance Estimation

Abstract: The Method of Random Groups.- Variance Estimation Based on Balanced Half-Samples.- The Jackknife Method.- The Bootstrap Method.- Taylor Series Methods.- Generalized Variance Functions.- Variance Estimation for Systematic Sampling.- Summary of Methods for Complex Surveys.- Hadamard Matrices.- Asymptotic Theory of Variance Estimators.- Transformations.- The Effect of Measurement Errors on Variance Estimation.- Computer Software for Variance Estimation.- The Effect of Imputation on Variance Estimation.

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter

Abstract: Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

The accuracy of self-reported smoking: a systematic review of the relationship between self-reported and cotinine-assessed smoking status.

Abstract: INTRODUCTION Smoking is a leading cause of premature mortality and preventable morbidity. Surveillance is most often based on self-reported data, but studies have shown that self-reports tend to underestimate smoking status. METHODS This study systematically reviewed the literature to measure the concordance between self-reported smoking status and smoking status determined through measures of cotinine in biological fluids. Four electronic databases were searched to identify observational and experimental studies on adult populations over the age of 18 years. RESULTS Searching identified 67 studies that met the eligibility criteria and examined the relationship between self-reported smoking and smoking confirmed by cotinine measurement. Overall, the data show trends of underestimation when smoking prevalence is based on self-report and varying sensitivity levels for self-reported estimates depending on the population studied and the medium in which the biological sample is measured. Sensitivity values were consistently higher when cotinine was measured in saliva instead of urine or blood. Meta-analysis was not appropriate because of the substantial heterogeneity among the cutpoints used to define smokers and the poor reporting on outcomes of interest. DISCUSSION Further research in this field would benefit from the standardization of cutpoints to define current smokers and the implementation of standard reporting guidelines to enhance comparability across studies. Accurate estimation of smoking status is important as data from population studies such as those included in this review are used to generate regional and national estimates of smoking status and in turn are used to allocate resources and set health priorities.