ArticleHealth promotion and chronic disease prevention in Canada : research, policy and practice2019
Trends in chronic disease incidence rates from the Canadian Chronic Disease Surveillance System.
Article in Health promotion and chronic disease prevention in Canada : research, policy and practice, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Article
- Minimum elements for reporting a multi-jurisdiction feasibility assessment of algorithms based on routinely collected health data: Health Data Research Network Canada recommendations.International journal of population data science · 2025Article
- Trend control charts for multiple sclerosis case definitions.International journal of population data science · 2024Article
- Evaluation of administrative case definitions for hypertension in Canadian children.Scientific reports · 2023Article
- Assessing sex differential in COVID-19 mortality rate by age and polymerase chain reaction test results: an Iranian multi-center study.Expert review of anti-infective therapy · 2022Article
- Control charts for chronic disease surveillance: testing algorithm sensitivity to changes in data coding.BMC public health · 2022Article
- Neighbourhood characteristics related to mental health service use among adults with diabetes: a population-based cohort study in New Brunswick, Canada.BMC research notes · 2022Observational
- Advanced detection strategies for cardiotropic virus infection in a cohort study of heart failure patients.Laboratory investigation; a journal of technical methods and pathology · 2022Article
- Cognitive leisure activity and all-cause mortality in older adults: a 4-year community-based cohort.BMC geriatrics · 2021Article
- A primer on metabolic memory: why existing diabesity treatments fail.Clinical kidney journal · 2021Review
- Validated methods for identifying individuals with obesity in health care administrative databases: A systematic review.Obesity science & practice · 2020Review
- Regional variation in multimorbidity prevalence in British Columbia, Canada: a cross-sectional analysis of Canadian Community Health Survey data, 2015/16.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2020Article
- Healthcare Service Use for Mood and Anxiety Disorders Following Acute Myocardial Infarction: A Cohort Study of the Role of Neighbourhood Socioenvironmental Characteristics in a Largely Rural Population.International journal of environmental research and public health · 2020Article
- Is there an agreement between self-reported medical diagnosis in the CARTaGENE cohort and the Québec administrative health databases?International journal of population data science · 2020Article
- At-a-glance - Twenty years of diabetes surveillance using the Canadian Chronic Disease Surveillance System.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2019Article
- Trends in antihypertensive drug utilization in British Columbia, 2004-2019: a descriptive study.CMAJ openArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe Public Health Agency of Canada's Canadian Chronic Disease Surveillance System (CCDSS) produces population-based estimates of chronic disease prevalence and incidence using administrative health data. Our aim was to assess trends in incidence rates over time, trends are essential to understand changes in population risk and to inform policy development.
methodsIncident cases of diagnosed asthma, chronic obstructive pulmonary disease (COPD), diabetes, hypertension, ischemic heart disease (IHD), and stroke were obtained from the CCDSS online infobase for 1999 to 2012. Trends in national and regional incidence estimates were tested using a negative binomial regression model with year as a linear predictor. Subsequently, models with year as a restricted cubic spline were used to test for departures from linearity using the likelihood ratio test. Age and sex were covariates in all models.
resultsBased on the models with year as a linear predictor, national incidence rates were estimated to have decreased over time for all diseases, except diabetes; regional incidence rates for most diseases and regions were also estimated to have decreased. However, likelihood ratio tests revealed statistically significant departures from a linear year effect for many diseases and regions, particularly for hypertension.
conclusionChronic disease incidence estimates based on CCDSS data are decreasing over time, but not at a constant rate. Further investigations are needed to assess if this decrease is associated with changes in health status, data quality, or physician practices. As well, population characteristics that may influence changing incidence trends also require exploration.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.